Rotations and Translations of Head Posture Parameters as a Predictor of the Rehabilitation Management Outcomes in Patients with Chronic Nonspecific Neck Pain: A Multicenter Prospective Case Series

Rotations and Translations of Head Posture Parameters as a Predictor of the Rehabilitation Management Outcomes in Patients with Chronic Nonspecific Neck Pain: A Multicenter Prospective Case Series | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Rotations and Translations of Head Posture Parameters as a Predictor of the Rehabilitation Management Outcomes in Patients with Chronic Nonspecific Neck Pain: A Multicenter Prospective Case Series Ghydaa Anwar, Ibrahim M. Moustafa, Amal Ahbouch, Abdulla Alrahoomi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4720644/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 May, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract A multicenter, prospective consecutive case series study was conducted in 5 physiotherapy clinics in the UAE from January 2021 to March 2023 to assess rotations and translations of head posture parameters as potential predictors of conservative therapy outcomes in patients with chronic non-specific neck pain (CNSNP). Eighty-six patients (mean age 35 yrs., 65% male) with CNSNP underwent conservative therapy. All participants received a detailed examination including a computerized cervical spine posture analysis and demographic data was collected. Interventions included specific exercises, diathermy, longitudinal traction, education, a detailed exercise program, ergonomic advice, and medications. Interventions were applied 3 times per week for 8 weeks. Follow-up was 6-months after final treatment. A successful outcome was based on a minimum improvement of the following four outcomes using the patient centered outcome questionnaire (PCOQ): ( 1 ) reduction of pain by 17.5 points (0–100 NRS); ( 2 ) fatigue reduction by 7.5 points; ( 3 ) distress reduction by 5 points; and ( 4 ) interference reduction by 9.5 points. At 6-month follow-up it was found that success rates for pain, fatigue, distress, and interference were above 60% for the total participants. The logistic regression for predicting overall success in combined outcomes based on age, gender, smoking status, marital status, and sagittal head translation was: 1) Age : the odds ratio (0.69) suggests that as age increases, the likelihood of overall success decreases (p = 0.001); 2) Sex : females have higher odds of overall success compared to males (OR = 2.71, p < 0.001); 3) Smoking status and marital status : neither of these factors were statistically significant predictors of overall success; 4) Sagittal head translation : each unit increase (more anterior) in this abnormal posture reduced the odds of success by 13%, showing a strong and significant effect (OR = 0.13, p < 0.001). Overall, our findings indicate that younger age, female sex, and better posture alignment of the cervical spine all had a substantial impact on the likelihood of success of 6-month outcomes in patients suffering CNSNP. Health sciences/Health care Health sciences/Medical research Cervical spine posture neck pain disability case series CVA forward head posture Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Chronic non-specific neck pain (CNSNP) is a prevalent clinical problem 1,2 that significantly impacts an individual’s quality of life, 3–6 leading to delayed recovery, persistent disability, 1 and increased healthcare costs. 2,6 With a reported prevalence varying widely, CNSNP imposes a substantial financial burden on the healthcare system. 2,6 Although the occurrence of CNSNP increases with age, there is generally no significant sex difference in its prevalence. 7 Despite its high prevalence, the conservative treatment of CNSNP remains challenging. 8 Many patients continue to experience symptoms for extended periods, often a year or longer. Recent systematic reviews have highlighted the lack of clearly effective conservative treatments for CNSNP, 8 particularly for long-term management. 9 Identifying specific outcomes that predict the success of conservative treatment for CNSNP is crucial. Predictors can help tailor treatment options to individual patients, enhancing clinical care and improve long-term prognosis. 10 Various predictors, such as the perception of treatment outcome success, 10 pain intensity, 10,11 duration of complaints, 12 and response to specific physical tests, have been reported previously​. Importantly, the role of mechanical alignment of the cervical spine as a predictor of management outcomes has often been overlooked in clinical practice and research. 13 According to Harrison et al., 13 the recent focus on the bio-psycho-social model has led to an underemphasis on the 'bio' component, particularly biomechanics, in the treatment of spinal disorders. It is relevant that several studies indicate that the sagittal plane alignment and overall biomechanics of the cervical spine significantly impact patient outcomes, including pain, disability, and functional mobility. 14 For example, randomized controlled trials have demonstrated that interventions aimed at correcting cervical sagittal alignment, such as cervical extension traction (CET), results in better long-term health outcomes as compared to conventional treatments that do not address spinal alignment. 13,15–18 This evidence underscores the importance of considering biomechanical factors in developing treatment plans for spinal disorders; thus, advocating for a more balanced approach that integrates mechanical alignment with psycho-social factors to enhance patient care and outcomes. Recent technological advancements have enabled precise measurement and quantification of head posture in terms of translational and rotational displacements. 19,20 Studies have demonstrated that postural aberrations, both head translations and rotations, are linked to physical fitness and cardiopulmonary functions. 21,22 These findings highlight the importance in evaluating and addressing postural imbalances to enhance clinical outcomes. However, often, rehabilitation programs for CNSNP do not typically consider the rotations and translations of head posture parameters and thus do not include specific interventions and outcomes designed to improve these as part of a multi-modal program of care. Accordingly, our study aims to investigate the rotations and translations of head posture parameters as predictors of conservative treatment outcomes in patients with CNSNP. This multicenter prospective cohort study used a 6-month follow-up to determine if the magnitude of these displacements predicts success or failure of conservative care outcomes in this patient population. We hypothesized that the magnitude of rotations and translations of head posture parameters would be predictors of the outcomes of conservative care in patients with CNSNP​​​​. Results The demographic characteristics of the study participants are shown in Table 1 . This was a young adult population with an average age of 35.22 years (SD = 5.93). The body mass index (BMI) distribution shows that 50% of participants had a normal BMI, 33.3% were overweight, and 16.7% were obese, highlighting a substantial portion falling into higher BMI categories. Table 2 shows the differences between males and females for each of the study variables. The sex distribution was skewed towards males (65.2%) compared to females (34.8%). Additionally, 79% of participants were non-smokers, and 67.5% were married. Posture parameters, including craniovertebral angle (CVA), sagittal head translation (SHT), coronal head translation, and lateral angulation, displayed variability among participants as depicted in the boxplot across all participants within males and females in Fig. 1 . Pain, fatigue, distress, and interference were assessed at pre-treatment, post-treatment, and 6-months, showing general improvement post-treatment but variable long-term outcomes. Success rates for pain, fatigue, distress, and interference were above 60%, indicating substantial but not universal improvement. Table 1 and Table 2 . When comparing demographic characteristics across sex, there was no significant difference in age, BMI, smoking status, or marital status (Table 2 ) . Posture parameters showed no significant sex differences except for lateral head tilt, being greater in males (p = 0.03). Figure 1 shows the boxplot for the distribution of the 4 postural variables between males and females. Pain at 6-months was significantly higher in females (p = 0.04). Fatigue and distress scores did not significantly differ between sexes across any time point. Similarly, interference scores and success and failure rates for pain, fatigue, distress, and interference did not differ significantly between sexes. Table 2 presents this detailed data between males and females. Table 1 Demographic characteristics of the study participants (n = 86). BMI: body mass index; N: number; In.: inches. Demographic characteristic Variable Age 35.22 ± 5.93 BMI - Normal (BMI = 18.5 to 24.9) 43 (50%) - Overweight (BMI = 25–29) 29 (33.3%) - Obese (BMI = 30–35) 14 (16.7%) Sex - Female 30 (34.8%) - Male 56 (65.2%) Smoking - No 68 (79%) - Yes 18 (21%) Marital status - Married 58 (67.5%) - Not Married 28 (32.5%) Posture parameters - CVA (°) 51.52 ± 5.30 - Sagittal head translation (in.) 1.87 ± 1.15 - Coronal head translation (in.) 1.01 ± 0.50 - Lateral angulation (°) 13.94 ± 4.60 Pain - Pre treatment 72.82 ± 9.59 - Post treatment 8-weeks 25.74 ± 13.20 - At 6 Month follow up 41.76 ± 31.16 Fatigue - Pre treatment 61.22 ± 7.62 - Post treatment 8 weeks 13.11 ± 9.55 - At 6 month follow up 30.00 ± 26.07 Distress - Pre treatment 67.99 ± 11.53 - Post treatment 8 weeks 22.70 ± 12.37 - At 6 month follow up 46.20 ± 24.42 Interference - Pre treatment 69.39 ± 7.07 - Post treatment 8 weeks 20.41 ± 12.77 - At 6 month follow up 30.12 ± 3.89 Success and failure rates Pain - Success rate 61.11% Pain - Failure rate 38.89% Fatigue - Success rate 66.67% Fatigue - Failure rate 33.33% Distress - Success rate 62.22% Distress - Failure rate 37.78% Interference - Success rate 62.22% Interference - Failure rate 37.78% Table 2 Demographic characteristics distributed across sex. BMI: body mass index; CVA: craniovertebral angle; In.: inches. Demographic characteristic Female (N = 30) Male (N = 56) p-value Age 36 ± 5.99 34 ± 5.94 0.45 BMI 0.63 - Normal 15 (50%) 28 (50%) - Overweight 10 (33.3%) 19 (33.3%) - Obese 5 (16.7%) 9 (16.7%) Smoking 0.77 - No 23 (76.7%) 45 (78.3%) - Yes 7 (23.3%) 11 (21.7%) Marital status 0.12 - Married 20 (66.7%) 38 (66.7%) - Not Married 10 (33.3%) 18 (33.3%) Posture parameters - CVA (°) 51.84 ± 5.28 51.26 ± 5.34 0.60 - Sagittal head translation (in.) 1.82 ± 1.08 1.91 ± 1.21 0.69 - Coronal head translation (in.) 0.93 ± 0.48 1.07 ± 0.52 0.19 - Lateral angulation (°) 12.81 ± 4.48 14.89 ± 4.52 0.03 Pain - Pre treatment 72.56 ± 10.05 73.04 ± 9.28 0.81 - Post treatment 8 weeks 25.73 ± 13.36 25.76 ± 13.21 0.99 - At 6 month follow up 34.41 ± 31.68 47.90 ± 29.65 0.04 Fatigue - Pre treatment 61.44 ± 7.90 61.04 ± 7.45 0.80 - Post treatment 8 weeks 11.15 ± 9.17 14.76 ± 9.65 0.07 - At 6 month follow up 24.68 ± 26.57 34.45 ± 25.05 0.07 Distress - Pre treatment 68.29 ± 12.28 67.73 ± 10.99 0.82 - Post treatment 8 weeks 22.00 ± 12.35 23.29 ± 12.48 0.62 - At 6 month follow up 41.85 ± 25.99 49.84 ± 22.64 0.12 Interference - Pre treatment 68.54 ± 6.85 70.10 ± 7.24 0.29 - Post treatment 8 weeks 19.17 ± 12.42 21.45 ± 13.10 0.40 - At 6 month follow up 36.49 ± 27.56 46.36 ± 28.04 0.09 Success and failure rates Pain - Success rate 63% 60% 0.19 Pain - Failure rate 37% 40% Fatigue - Success rate 68% 65% 0.18 Fatigue - Failure rate 32% 35% Distress - Success rate 64% 61% 0.55 Distress - Failure rate 36% 39% Interference - Success rate 64% 61% 0.55 Interference - Failure rate 36% 39% The correlation matrix indicates high correlations among posture variables, suggesting multicollinearity as shown in Table 3 . As a result, only the sagittal (anterior) head translation is used in logistic regression models to avoid multicollinearity issues. This ensures more reliable and interpretable results in the subsequent analyses. The box plots of the sagittal head translation distance in inches measured for all patients, in successful outcome patients, and in those with lack of success or failure to respond to conservative care for the combined outcome is shown in Fig. 2 . This figure clearly identifies that increased sagittal head translation, measured in inches, is strongly related to those patients who failed to respond at 6-month follow-up. The logistic regression result for predicting overall success is shown in Table 4 . 1) Age : the odds ratio (0.69) suggests that as age increases, the likelihood of overall success decreases (p = 0.001). 2) BMI : for BMI, the odds ratio is 0.85, indicating that an increase in BMI slightly decreases the likelihood of overall success, but this effect is not statistically significant (p = 0.23). 3) Sagittal head translation : more anterior movement of the head in the sagittal plane significantly lowers the chances of success. Each unit increase in this movement reduces the odds of success to about 13%, showing a strong and significant effect (p < 0.001). 4) Sex : females have higher odds of overall success compared to males (OR = 2.7, p < 0.001). 5) Smoking status and marital status : neither of these factors are statistically significant predictors of overall success. See Table 4 . Table 3 Multicollinearity check of posture variables. CVA Sagittal head translation Coronal head translation Lateral head angulation CVA 1.0 -0.38 -0.66 -0.57 Sagittal head translation -0.38 1.0 0.31 0.49 Coronal head translation -0.66 0.31 1.0 0.63 Lateral head angulation -0.57 0.49 0.63 1.0 Table 4 Logistic regression results for overall success. Variable Odds Ratio (95% CI) p-value Age 0.69 (0.555–0.865) 0.001 BMI 0.85 (0.63–1.15) 0.23 Sagittal head translation 0.13 (0.048–0.349) < 0.001 Sex 2.7 (1.833–4.008) < 0.001 Smoking status 0.96 (0.645–1.441) = 0.86 Marital status 1.34 (0.877–2.060) = 0.17 The logistic regression result for predicting pain success is shown in Table 5 . 1) Age : the odds ratio of 0.97 suggests no significant impact of age on pain success (p = 0.53). 2) BMI : the odds ratio of 0.77 indicates no significant impact of BMI on pain success (p = 0.53). 3) Sex : shows that females have significantly higher odds of pain success compared to males, with an odds ratio of 0.27 (p = 0.03). This indicates that being female increases the likelihood of pain success. 4) Smoking and marital status : neither smoking or marital status are significant predictors of pain success (p = 0.68 and p = 0.53, respectively). 5) Sagittal head translation : greater sagittal head translation significantly reduces the odds of pain success (OR = 0.11, 95% CI: 0.04–0.31, p < 0.001). Table 5 Logistic regression results for pain success. Predictor Estimate SE Z p-value Odds Ratio (95% CI) Intercept 5.2435 2.042 2.56 0.01 - Age -0.030 0.049 -0.61 0.53 0.97 (0.88–1.068) BMI -0.2592 0.42 -0.617 0.54 0.77 (0.33–1.75) Sex 1.3092 0.594 2.20 0.03 0.27 (0.085–0.86) Smoking status 0.1248 0.311 0.401 0.69 1.13 (0.616–2.08) Marital status 0.250 0.400 0.625 0.532 1.28 (0.58–2.82) Sagittal head translation -2.1916 0.522 -4.198 < 0.001 0.11 (0.040–0.31) The logistic regression result for predicting fatigue success is shown in Table 6 . 1) Age : The odds ratio of 1.06 indicates that age does not have a significant impact on fatigue success (p = 0.89). 2) BMI : The negative coefficient suggests a potential inverse relationship, where an increase in BMI might be associated with lower odds of fatigue success. However, this relationship is not statistically significant (p = 0.57). 3) Sex : Sex does not have a statistically significant impact on fatigue success. Although females have 2.46 times the odds of fatigue success compared to males, this finding is not statistically significant (p = 0.24). 4) Smoking Status : Smoking status is a significant predictor of fatigue success. Smokers have 6.62 times the odds of achieving fatigue success compared to non-smokers, and this relationship is statistically significant (p = 0.037). 5. Marital Status : Based on the logistic regression results, there is no strong evidence to suggest that marital status is significantly related to fatigue success. Although the odds ratio indicates that being married might be associated with higher odds of pain success. 6) Sagittal Head Translation : Increased sagittal head translation significantly decreases the likelihood of achieving fatigue success. The odds ratio of 0.057 indicates a strong inverse relationship, and this finding is statistically significant (p < 0.001). Table 6 Logistic regression results for fatigue success. Predictor Estimate SE Z p-value Odds ratio (95% CI) Intercept -1.64 1.27 -1.29 0.20 - Age 0.06 0.42 0.14 0.89 1.06 (0.46–2.44) BMI -0.28 0.50 -0.56 0.57 0.76 (0.28–2.07) Marital Status 0.26 0.50 0.52 0.60 1.30 (0.47–3.00) Sex 0.90 0.76 1.18 0.24 2.46 (0.51–12.00) Smoking Status 1.89 0.91 2.08 0.037 6.62 (1.66–26.41) Sagittal head translation -2.87 0.79 -3.63 < 0.001 0.057 (0.012–0.27) The logistic regression result for predicting distress is shown in Table 7 . 1) Age : older participants are significantly more likely to succeed in managing distress (OR = 1.16, 95% CI: 1.031–1.324, p = 0.015). 2) BMI : higher BMI is not a significant predictor of distress success (OR = 2.87, 95% CI: 0.838–9.669, p = 0.093). 3) Sex : gender is not a significant predictor of distress success (OR = 0.33, 95% CI: 0.078–1.463, p = 0.147). 4) Smoking status : smoking status is not a significant predictor of distress success (OR = 1.35, 95% CI: 0.602–3.038, p = 0.464). 5) Marital status is not a significant predictor of distress success (OR = 0.77, 95% CI: 0.29–2.05, p = 0.60). 6) Sagittal head translation : greater sagittal head translation significantly reduces the odds of distress success (OR = 0.16, 95% CI: 0.038–0.718, p = 0.016). Table 7 Logistic regression results for distress success. Predictor Estimate SE Z p-value Odds ratio Intercept -6.16 2.77 -2.226 0.026 - Age 0.15 0.06 2.43 0.015 1.16 (1.031–1.32) BMI 1.05 0.62 1.67 0.09 2.87 (0.838–9.66) Sex 1.08 0.74 1.45 0.14 0.33 (0.078–1.46) Smoking status 0.30 0.41 0.73 0.46 1.35 (0.602–3.03) Marital status 0.262 0.504 0.52 0.60 0.77 (0.29–2.05) Sagittal head translation -1.80 0.75 -2.40 0.01 0.16 (0.038–0.71) The logistic regression result for predicting interference success is shown in Table 8 . 1) Age : the odds ratio of 0.96 suggests no significant impact of age on interference success (p = 0.433). 2) BMI : the odds ratio of 0.66 indicates no significant impact of BMI on interference success (p = 0.321). 3) Sex : gender is marginally significant, with males less likely to succeed in managing interference compared to females (OR = 0.33, 95% CI: 0.110–1.026, p = 0.055). 4) Smoking status : smoking status is not a significant predictor of interference success (OR = 1.04, 95% CI: 0.574–1.887, p = 0.897). 5) 5) Marital status: Marital status is not a significant predictor of interference success (p = 0.67). The odds ratio of 1.16 suggests a non-significant increase in the odds of interference success for married individuals. 6) Sagittal head translation : greater sagittal head translation significantly reduces the odds of interference success (OR = 0.13, 95% CI: 0.048–0.349, p < 0.001). Table 8 Logistic regression results for interference success. Predictor Estimate SE Z p-value Odds ratio Intercept 5.34 2.005 2.66 0.008 - Age -0.03 0.047 -0.78 0.43 0.96 (0.87–1.05) BMI -0.40 0.412 -0.99 0.32 0.66 (0.29–1.47) Sex 1.09 0.57 1.91 0.05 0.33 (0.110–1.02) Smoking status 0.03 0.304 0.12 0.89 1.04 (0.57–1.88) Marital status 0.150 0.355 0.42 0.67 1.16 (0.57–2.37) Sagittal head translation -2.03 0.502 -4.06 < 0.001 0.13 (0.048–0.34) The Generalized estimation equation (GEE) result for assessing the effect of time and other predictors on pain scores is shown in Table 9 . Only time and sagittal head translation are statistically related to time on pain scores, p < 0.001. Other Variables : age, BMI, sex, and smoking status do not significantly predict pain scores. Table 9 The generalized estimation equations (GEE) results for pain scores. Variable Beta 95% CI p-value Intercept 53.9 36.99–70.99 < 0.001 Time -15.5 -18.45–12.61 < 0.001 Age -0.12 -0.57–0.32 0.58 BMI -1.60 -4.99–1.77 0.35 Sex 3.79 -1.22–8.80 0.13 Smoking status -1.17 -4.08–1.73 0.43 Sagittal head translation 7.57 5.75–9.40 < 0.001 The GEE result for assessing the effect of time and other predictors (age, BMI, sex, smoking status, and sagittal head translation) on fatigue scores is shown in Table 10 . The main interpretation is that time and sagittal head translation are statistically significant predictors of fatigue scores, p < 0.001. Other variables such as age, BMI, sex, and smoking status are not statistically significant. Table 10 The generalized estimation equations (GEE) results for fatigue scores. Variable Beta 95% CI p-value Intercept 39.70 26.67–52.73 < 0.001 Time -15.61 -18.44 - -12.78 < 0.001 Age -0.02 -0.35–0.30 0.86 BMI -0.79 -4.08–2.49 0.63 Sex 3.66 -0.03–7.35 0.05 Smoking status 0.22 -1.93–2.38 0.83 Sagittal head translation 5.59 4.25–6.93 < 0.001 The GEE result for assessing the effect of time and other predictors (age, BMI, sex, smoking status, and sagittal head translation) on distress scores is shown in Table 11 . Time and sagittal head translation are statistically significant predictors of distress scores, p < 0.001. Other variables such as age, BMI, sex, and smoking status are not statistically significant. Table 11 The generalized estimation equations (GEE) results for distress scores. Variable Beta 95% CI p-value Intercept 51.97 37.62–66.33 < 0.001 Time -10.89 -13.44 - -8.34 < 0.001 Age -0.13 -0.50–0.23 0.46 BMI -1.28 -4.27–1.69 0.39 Sex 2.37 -1.58–6.34 0.24 Smoking status 0.67 -1.58–2.93 0.55 Sagittal head translation 4.72 3.23–6.20 < 0.001 Lastly, the GEE result for assessing the effect of time and other predictors (age, BMI, sex, smoking status, and sagittal head translation) on interference scores is shown in Table 12 . Time and sagittal head translation are statistically significant predictors of interference scores, p < 0.001. Other variables such as age, BMI, sex, and smoking status are not statistically significant. Table 12 The generalized estimation equations (GEE) results for interference scores. Variable Beta 95% CI p-value Intercept 38.94 22.9–54.92 < 0.001 Time -13.76 -16.2 - -11.27 < 0.001 Age 0.17 -0.25–0.61 0.41 BMI 0.40 -2.59–3.40 0.79 Sex 3.72 -0.75–8.20 0.10 Smoking status -1.88 -4.50–0.72 0.15 Sagittal head translation 6.56 4.62–8.50 < 0.001 Discussion The current prospective, multi-center, consecutive case series was conducted to investigate if postural parameters of the cervical spine and demographic variables might predict the successful outcome of physiotherapeutic interventions in clinical practice in patients suffering from a primary complaint of CNSNP. Our study’s primary hypothesis was that cervical spine posture displacements would be predictors of success or failure of conservative care outcomes in patients suffering from CNSNP. One of our primary findings was that the magnitude of SHT (a measure of forward head posture) significantly affected the odds of a successful outcome of conservative care. In fact, considering all four domains on the patient centered outcome questionnaire (PCOQ) 23,24 simultaneously, for each unit increase in SHT distance, the odds of a successful outcome decreased by 13%. Thus, our study’s main hypothesis is confirmed by our results. Additionally, we found that younger age and female sex had substantial impacts on the likelihood of a successful outcome when considering all four domains on the PCOQ. Negative predictors: Marital status, Smoking and Obesity Several demographic and socio-economic variables have been shown to predict chronicity and outcomes in CNSNP. 3,6,7,10,25 In the current project, we looked at several demographic variables as they relate to the odds of improving CNSNP using the four parts of the patient centered outcome questionnaire (PCOQ) 23,24 : pain intensity, fatigue, distress, and interference following a multi-modal conservative care program. Interestingly, we found no relationship with marital status, smoking status, and BMI and the odds of overall recovery; there is conflicting evidence on this in the chronic cervical spine pain literature. For example, studies have provided evidence supporting the notion that higher levels of perceived social support and justice correlate with decreased pain-related disability among individuals dealing with chronic pain-related psychosocial conditions but that age, sex, marital status, and pain duration were not related. 26 In the current project we did not account for social support (other than marital status) nor did we account for injustice and it is difficult to compare our findings of conservative care for CNSNP to those outcome investigatons that did not specifically look at CNSNP exclusively. 26 In the current project, we did have a significant sample of high BMI patients (BMI > 30): where 16.7% of our sample were classified as obese (BMI > 35) and 33%, were classifed as overweight (35 > BMI > 30). The logistic regression result for predicting fatigue success on the PCOQ indicated that BMI had a negative coefficient implying a potential inverse relationship (increased BMI might be associated with lower odds of fatigue success), but this relationship was not statistically significant. In a recent systematic review of risk factors for chronic neck pain, strong evidence for high BMI in women and conflicting evidence for high BMI in men was found; however, this was not a treatment outcomes investigation so it is difficult to compare these findings with ours. 27 Similarly, smoking status was not a significant predictor of overall success on the total PCOQ score. However, smoking status was found to be a significant predictor of fatigue success; where smokers had 6.62 times the odds of achieving fatigue success compared to non-smokers, and this relationship is statistically significant (p = 0.037). The fatigue success increase with smokers is difficult to explain and it may be unique to our population of younger individuals. In general, though our overall finding of lack of a non-significant smoking effect on outcomes is in general agreement with systematic literature reviews where smoking is not necessarily a contributor to specific chronic neck pain but is more of a risk for low back pain and wide spread pain. 28,29 Based on the logistic regression results, for marital status there was no strong evidence to suggest that marital status was significantly related to pain success; although the odds ratio indicated that being married might be non-statistically associated with higher odds of pain success implying this could be a type of social support for selected individuals. 26 Positive predictors: Age and Gender Our logistic regression result for predicting overall success on the four parts of the PCOQ identified that participant age was a statistically significant predictor for the odds of success (OR = 0.69, p = 0.001) suggesting that older age reduced the overall success. This finding that younger age is a significant predictor of treatment success is consistent with previous investigations on chronic neck pain. 25,30,31 For example, the prevalence of CNSNP peaks between the ages of 45–49 years in men and 50–54 in women. 31 Regarding sex differences, the results of our logistic regression analysis for predicting overall success on the four parts of the PCOQ identified that females have a higher odd of overall success compared to males for treatment improvement results when suffering CNSNP (OR = 2.7, p < 0.001). There are general conflicting findings regarding sex and the development and treatment outcomes for CNSNP. 25 For example, McLean et al. 30 and Cote and colleagues 32 have identified that women are at greater risk for the development of neck pain. Whereas Kazeminasab et al. 25 reviewed the recent epidemiological studies and found no meaningful sex differences between male and females across age groups in populations with chronic neck pain. Specific to treatment outcomes for CNSNP, Chen and colleagues 33 presented a systematic review and meta-analysis of RCTs analyzing the effect of scapular treatment on improving chronic neck pain incidence and found that females seemed to be better treated with scapular exercise training. The finding from Chen et al. 33 is comparable with our results with women experiencing an overall greater benefit than men although we did not specifically incorporate scapular retraining exercises into our treatment regimen. Postural predictors Our primary finding of interest, herein, is that we identified that the sagittal head translation (SHT) significantly affected the odds of success of overall and individual outcomes on the PCOQ. Specifically, greater anterior movement of the head in the sagittal plane significantly lowers the chances of success, where each unit increase in SHT movement reduced the odds of success by 13% (p < 0.001). Importantly, we found multicollinearity between the potential postural predictors, i.e. that the potential postural predictors were interrelated. A statistical consequence of this is that a multivariate regression model may give non-significant results even if several of the factors are important and significant in bivariate analyses. For instance, all the postural displacements assessed herein (CVA, SHT, coronal head translation, and coronal lateral bending) are likely important predictors, but since these variables are correlated a regression model may give non-significant results for these predictors. As a matter of fact, the SHT postural predictor is directly related to the CVA postural variable as they are both attempting to measure the same postural phenomenon of forward head posture. In several of the stepwise regression models, the SHT was selected first and this is the reason this posture was chosen in the current investigative results. The fact that other postural predictors were not selected does not mean that they are unimportant, but they can be omitted, herein, because part of the information they contain is accounted for by the SHT distance already included in the model. Recent investigations have identified that imbalance of cervical spine postural alignment in both the coronal and sagittal planes negatively affects patient outcomes and is associated with increased pain, disability, altered neurophysiology, and altered cardio-pulmonary performance. 13–18,21,22 Specific to our regression modelling results, forward head posture (FHP) as measured with the SHT method herein, is a very common posture abnormality and multiple recent systematic reviews and meta-analyses have been published on this postural abnormality. 33–37 From these reviews, it is clear that FHP is a significant postural abnormality related to pain, disability, and function and interventional strategies are recommended to improve identified abnormalities in patients to within normal values as found in asymptomatic populations. 33–37 Thus, our primary finding that SHT magnitude is a predictor of poor outcomes in patients undergoing treatment for CNSNP is strongly consistent with the current literature on the topic of FHP in varying populations. Our investigation is the first to look at each of the four scales on the PCOQ in patients with altered posture undergoing treatment for CNSNP which adds value to the evolving literature on the topic of FHP and related outcomes. In contrast, our specific finding that SHT magnitude predicts those patients who fail a conservative care program incorporating a considerable cervical spine exercise regimen is in conflict with a recent meta-analysis review on the topic of exercise types for chronic neck pain. 38 Rasmussen-Barr and colleagues 38 identified that there is low to high certainty of evidence for positive effects of a variety of cervical spine exercises on pain and disability used in chronic neck pain compared to no-exercise interventions. However, they found no evidence of a superior type of cervical spine exercise program, but rather all of them appear to have some beneficial effect. Our results suggest that exercise or other interventions that specifically target altered postural displacements and specifically document their correction should show superiority in treatment outcomes of CNSNP. Preliminarily there appears to be support for this in the recent literature 16,17,39 though continued investigation in the form of high-quality randomized trials is needed to further validate this finding. Limitations and future investigations. As with all investigations, our study has limitations. Primarily, this was not a randomized controlled trial looking at the success or failure of specific treatment interventions. Thus, it is not known whether the exact type of treatment provided was optimum as it was a compilation of interventions known to aid patients suffering from CNSNP. Furthermore, because we did not specifically look at interventions that are known to improve cervical spine posture displacements, we cannot say whether improving these cervical spine postural specific variables would result in better success for patients with this suffering from CNSNP. Future randomized trials are needed to investigate these limitations to determine more effective clinical intervention strategies for patients with altered cervical spine posture and CNSNP. Additionally, we recognize the importance of conducting exploratory, associative analyses to investigate how factors such as education, employment status, economic resources, health behaviors, and physical and mental health conditions may influence the association between patient education, patient expectations and management parameters. Another source of potential bias in this study was the lack of standardization protocols among different hospitals. While our study did not aim to standardize treatment programs across multiple centers, we meticulously selected centers from a similar demographic area with similar treatment approaches to mitigate potential biases. Additionally, we have provided detailed descriptions of our rehabilitation program, thereby enhancing the credibility and reproducibility of our findings. Conclusions In this multicenter, prospective consecutive case series conducted across 5 physiotherapy clinics in the UAE and Egypt, our findings indicate that younger age, female sex, and better cervical spine posture alignment all had a substantial impact on the likelihood of success of 6-month outcomes in patients suffering from chronic nonspecific neck pain (CNSNP). Non-significant (no association) predictors of patient outcomes included marital status, BMI, and smoking perhaps (except where smokers had an increase success on the fatigue scale) due to our unique sample and categorization of these patients. Importantly, a primary biomechanical driver of poor outcomes at 6-month follow-up after a 2-month multi-modal treatment program for CNSNP is altered cervical spine postural alignment. Thus, future rehabilitation programs incorporating specific postural corrective approaches need to be tested for short and long-term patient relevant outcomes in patients suffering from CNSNP. Future randomized trials are needed to evaluate treatment outcomes based on correcting cervical spine posture displacements. Materials and Methods Study Design and Population This is a multicenter, prospective cohort study conducted across five physiotherapy clinics in the UAE and Egypt from January 2021 to March 2023 to assess the rotations and translations of head posture parameters as potential predictors of conservative therapy outcomes in patients with CNSNP. The protocol of the study was approved by the Ethical Review Board of the University of Sharjah (REC-21-03-11-03-S). Written informed consent was obtained from all participants and all experimental protocols were carried out following the guidelines of the World Medical Association Declaration of Helsinki. Patients with CNSNP who underwent conservative therapy as the first line of treatment were included in this prospective study. Conservative therapy included rest, physical therapy (neck exercises, diathermy therapy, and distraction (longitudinal) traction), education with instructions for home-based exercise, and medications such as nonsteroidal anti-inflammatory drugs (NSAIDs), analgesics, muscle relaxants, or oral narcotics. Conservative Therapy Although our study, being multi-center in nature, did not intend to standardize the treatment program, we selected centers that predominantly align with a similar treatment approach. The therapeutic approach involved a comprehensive yet personalized treatment strategy. This multifaceted regimen comprises various components to alleviate pain and enhance functionality. This comprehensive conservative therapy aimed to manage CNSNP by addressing pain, functional limitations, and enhancing overall quality of life of the patients. The 8-week conservative therapy protocol for treatment of CNSNP involves a comprehensive treatment approach administered three times per week for the 8-weeks. The protocol begins with a 2-week education phase focusing on patient education, self-management, and activity modification to promote ergonomic practices and proper posture. Simultaneously, therapeutic exercises are introduced from week 1, starting with stabilization and isometric exercises. These exercises progress in intensity and complexity every two weeks, evolving into strengthening exercises targeting deep neck flexors and incorporating motor control principles. From week 3 onwards, manual therapy, including grade III posteroanterior mobilizations, is integrated and continues through week 8. Throughout the entire treatment period, modalities such as heat therapy and TENS are applied to alleviate pain and enhance treatment efficacy. Ergonomic advice emphasized from the beginning and continuously reinforced to support a neutral spine position and improve overall functionality. Each treatment session, conducted three times per week for 8 weeks, is tailored to ensure patient comfort and progress, with modifications made as needed based on individual responses. Conservative Treatment Modalities 1) Education and Self-Management: Patient Education : Informing patients about the nature of their condition, the importance of maintaining good posture, and ergonomic adjustments can empower them to manage their symptoms better. Activity Modification : Advising on modifying daily activities to avoid exacerbating movements and encourage the adoption of ergonomic practices at work and home. 2) Therapeutic Exercises: Stabilization Exercises : These exercises aim to improve the control and endurance of the deep cervical flexors and extensors, which can help in reducing pain and preventing recurrence. The protocol for stabilization exercises was adapted from Shin et al. 40 It consisted of a 30-minute exercise session, preceded by a 5-minute warm up, and followed by a 5-minute cool down. The warmup and cool down phases included general stretching of the upper extremity and neck. The main exercise session included: Supine isometrics of deep neck flexors Sitting cervical multidirectional isometrics (flexion, extension, lateral flexion, rotation) Upper extremity movement exercises Cervical resistive exercises with Thera-band Strengthening Exercises : Progressive resistance exercises for the neck and shoulder muscles can enhance overall muscular support for the cervical spine. Therefore, strengthening exercises were incorporated in this intervention program mainly targeting deep neck flexor muscles. The exercises were based on principles of motor control as described by Domingues et al 41 in their randomized controlled trial. The program consisted of three phases: Phase one: This phase targeted activation of deep flexors in the upper cervical region, specifically the longus capitis and colli. Patients were instructed to perform cranio-cervical flexion (chin tuck) in supine position, with a pressure cuff placed behind their neck. This position was held for 10 seconds and repeated 10 times. Successfully completing 10 repetitions at 26 mmHg permits the transfer to the second phase. Phase two: This phase continues the previous exercises in loading positions such as sitting and quadruped / 4-point kneeling, while maintaining a neutral cervical spine. Additionally, the pressure level was increased to 28 and 30 mmHg. Phase three: This phase begins with the chin tucks and is progressed with a higher load by adding 15 repetitions of shoulder flexion and head lifts in supine position. Exercise prescription The previously mentioned volumes and intensity were the foundation of exercise prescription for all patients. However, individual modifications were made when required to ensure prescription was suitable for each patient and they remained pain-free. Stretching Exercises : Regular stretching of the cervical muscles, especially the upper trapezius, levator scapulae, scalenes, and sternocleidomastoid, can help alleviate tightness and improve range of motion (ROM). Therefore, stretches were incorporated in this intervention plan where participants performed 3 sets of stretches with a 15 second hold. 42 3) Manual Therapy: Mobilization Techniques : Gentle, repetitive movements were applied to the cervical spine to enhance joint mobility and reduce pain. Protocol : The manual therapy protocol used in this study was adopted from a randomized controlled trial by Lopez-Lopez et al. 43 Initially, the patient is instructed to lie prone with hands under their forehead. The therapist stands at the patient’s head and places their thumbs over the spinous process of the targeted vertebra. The vertebra that is selected for mobilization is the one that is identified as symptomatic and hypomobile. Then, the therapist applies a grade III posteroanterior (PA) oscillatory force at the frequency of 2 Hz. This is carried on for 3 sets, each lasting 2 minutes, with a 1-minute rest interval between sets. 4) Modalities: Heat Therapy : Application of heat can relax tight muscles and improve blood flow. Electrotherapy : Techniques such as transcutaneous electrical nerve stimulation (TENS) provide pain relief by modulating the pain signals sent to the brain. This method was added to the intervention plan for pain relief as it is effective in the treatment of CNSNP. TENS was administered using four electrodes placed over painful areas on the neck and shoulder region. The stimulation was delivered at a frequency of 80 Hz and an intensity of 10 mA to 30 mA, for 25 minutes. 44 5) Ergonomic Adjustments: Recommendations for workplace adjustments, such as chair height, monitor position, and keyboard placement, can help maintain a neutral spine position. Outcome Variables The primary outcome variable used in this study was the conservative treatment outcome after a 6-month follow-up after completion of active interventions (defined as success or failure). In this study, the success criteria were defined from the spine pain patient’s perspective across multiple relevant domains using the patient centered outcome questionnaire (PCOQ). 23 This questionnaire instructs the patient to rate their current level of pain, fatigue, distress, and interference of daily activities on a numerical rating scale (NRS), ranging from 0 to 100. The patient then repeats the rating in the second section of the questionnaire, but instead of rating current levels, they rate levels of the four domains they expect to achieve following the physical therapy intervention. This allows for the assessment of the patients’ presentation, expectation, and goals, and quantifies the impact these four domains have on the patient’s health, as well as how the intervention will affect them. The following four endpoints were considered because previous research has shown them to be clinically relevant with good reliability and concurrent validity: reduction of pain, reduction of fatigue, reduction of distress, and reduction of interference. 24 The rehabilitation program was considered successful if the 4 domain outcomes were decreased at discharge time by the optimal cutoff points according to Brown et al., 24 and this improvement was maintained or further improved at the 6-month follow up, otherwise it was considered as a failure. The optimal cutoff points were: ( 1 ) reduction of pain of 17.5 points or more (0–100 numerical rating scale); ( 2 ) fatigue reduction of 7.5 points or more; ( 3 ) reduction for distress by 5 points or more; and ( 4 ) reduction of interference by 9.5 points or more. The criteria for the 6-month follow-up failure were: ( 1 ) increase of pain or reduction less than 17.5 points; ( 2 ) increase of fatigue or reduction less than 7.5 points; ( 3 ) increase of distress or reduction less than 5 points; and ( 4 ) increase in the inference with daily activities or reduction less 9.5 points. 24 Rotations and Translations of Head Posture Parameters The rotations and translations of head posture parameters were measured using a standardized protocol. This included the assessment of cervical spine angles, head tilt, head rotation, and the translation of the head in relation to the cervical spine. Posture measurement was achieved by the PostureScreen® Mobile app (PSM) which is a digital posturographic assessment tool used to perform 3D postural examinations. The PSM has been established in research as a reliable and valid method for evaluating static posture. For example, investigations have identified that PSM has an intra-rater reliability that ranges from 0.71 to 0.99, and an inter-rater reliability which is good to excellent for all translations (ICC’s between 0.85 and 0.98). 19,20 PSM captures images of the participant from four directions: anterior and posterior (coronal plane) and the left and right sides (sagittal plane). After the photograph is captured, specific anatomical reference points are digitized by the user such as the pelvic iliac spines, the greater trochanter, the femoral condyle, and the tragus. To ensure maximum accuracy of the manual digitization of landmarks, participants were instructed to undress/wear clothing that exposes the landmarks required so that they could be identified and labelled prior to digitization. Moreover, the landmarks were digitized by the same research team member and then cross-checked by the same 2 members to ensure accuracy for all participants’ data. The PSM then calculates specific body angles and distances based on the anatomical digitization and creates an output file containing values of posture variables and images of the participant that can be used to compare and analyze the postural deviations from neutral among participants. The following postural parameters were assessed using the PSM app: The cranio-vertebral angle (CVA (°)) is the acute angle that is formed between a straight line that connects the spinous process of C7 to the tragus of the ear, and the horizontal line that passes through the spinous process of C7. The angle is identified by the intersection of those two lines. 45 See Fig. 3 . Sagittal head translation, which is the movement of the head (tragus of the ear) anteriorly relative to the center of the glenohumeral joint. See Fig. 3 . Coronal head translation (CHT) or left and right head translation, is the movement of the cervical spine and head laterally to either side. Figure 4 depicts this measurement. Lateral head angulation (LHA) or coronal plane side bending of the head towards either side. The PSM app allows LHA to be assessed in either the anterior or posterior view. Figure 5 depicts this measurement. Data Analysis The descriptive statistics utilized in our investigation included count and percentages to describe categorical data. The Shapiro-Wilk test was used to test the normality of the numerical variables. Based on this, we report the median and interquartile ranges (IQR) to describe numerical data since all the numerical data, such as age, head posture parameters, and the scores of the four study outcomes, were not normally distributed. Multiple logistic regression models were used to assess the predictors of the success of each of the four outcomes as well as the four outcomes combined into one variable. Generalized estimation equations (GEE) were developed to assess the effect of time on pain, fatigue, distress, and interference scores, as well as the effect of other potential predictors. SPSS version 25.0 for Windows (IBM, Armonk, NY, USA) was used for data analysis. Declarations Acknowledgement Authors would like to thank CBP NonProfit, Inc. for the possible funding of this manuscript if accepted for publication. Author contributions Authors GA, IMM, A.Ah, A.Al and DEH all participated in the conception and design. GA, IMM, A.Ah, A.Al each participated in study implementation and data collection. GA, IMM, A.Ah, A.Al, DEH contributed to the statistical analysis and interpretation. IMM, A.Ah, A.Al participated in supervision. GA, IMM, A.Ah, A.Al and DEH all contributed to the interpretation of the results and wrote the drafts. All authors have read and agreed to the published version of the manuscript. Competing interests DEH is the CEO of Chiropractic BioPhysics and lectures on rehabilitation methods, and distributes products for patient rehabilitation to physicians in the USA; none of these products were used in this manuscript. All the other authors declare that they have no competing interests. All the other authors declare that they have no competing interests. Data Availability Data is available upon reasonable request from the corresponding author. References Price, J.; Rushton, A.; Tyros, V.; Heneghan, N.R. Expert Consensus on the Importance of Chronic Non-Specific Neck Pain Motor Control and Segmental Exercise and Dosage Variables: An International e-Delphi Study. PLoS One 2021, 16 , e0253523, doi: 10.1371/journal.pone.0253523 . Raizah, A.; Reddy, R.S.; Alshahrani, M.S.; Gautam, A.P.; Alkhamis, B.A.; Kakaraparthi, V.N.; Ahmad, I.; Kandakurti, P.K.; ALMohiza, M.A. A Cross-Sectional Study on Mediating Effect of Chronic Pain on the Relationship between Cervical Proprioception and Functional Balance in Elderly Individuals with Chronic Neck Pain: Mediation Analysis Study. J Clin Med 2023, 12 , 3140, doi: 10.3390/jcm12093140 . Chen, Z.; Falla, D.; Elgueta Cancino, E.; A Deane, J. Can Baseline Features Predict a Reduction in Pain and Disability Following Neck-Specific Exercise in People with Chronic Non-Specific Neck Pain?: A Systematic Review and Meta-Analysis Protocol. BMJ Open 2023, 13 , e074494, doi: 10.1136/bmjopen-2023-074494 . Côté, P.; Wong, J.J.; Sutton, D.; Shearer, H.M.; Mior, S.; Randhawa, K.; Ameis, A.; Carroll, L.J.; Nordin, M.; Yu, H.; et al. Management of Neck Pain and Associated Disorders: A Clinical Practice Guideline from the Ontario Protocol for Traffic Injury Management (OPTIMa) Collaboration. European Spine Journal 2016, 25 , 2000–2022, doi: 10.1007/s00586-016-4467-7 . Cerezo-Téllez, E.; Torres-Lacomba, M.; Mayoral-del-Moral, O.; Pacheco-da-Costa, S.; Prieto-Merino, D.; Sánchez-Sánchez, B. Health Related Quality of Life Improvement in Chronic Non-Specific Neck Pain: Secondary Analysis from a Single Blinded, Randomized Clinical Trial. Health Qual Life Outcomes 2018, 16 , 207, doi: 10.1186/s12955-018-1032-6 . Park, S.J.; Lee, R.; Yoon, D.M.; Yoon, K.B.; Kim, K.; Kim, S.H. Factors Associated with Increased Risk for Pain Catastrophizing in Patients with Chronic Neck Pain. Medicine 2016, 95 , e4698, doi: 10.1097/MD.0000000000004698 . Zheng, B.; Zheng, L.; Li, M.; Lin, J.; Zhu, Y.; Jin, L.; You, R.; Gao, Y.; Liu, X.; Wang, S. Sex Differences in Factors Associated with Neck Pain among Undergraduate Healthcare Students: A Cross-Sectional Survey. BMC Musculoskelet Disord 2022, 23 , 842, doi: 10.1186/s12891-022-05782-z . de Zoete, R.M.J. Exercise Therapy for Chronic Neck Pain: Tailoring Person-Centred Approaches within Contemporary Management. J Clin Med 2023, 12 , 7108, doi: 10.3390/jcm12227108 . Cheng, C.-H.; Su, H.-T.; Yen, L.-W.; Liu, W.-Y.; Cheng, H.-Y.K. Long-Term Effects of Therapeutic Exercise on Nonspecific Chronic Neck Pain: A Literature Review. J Phys Ther Sci 2015, 27 , 1271–1276, doi: 10.1589/jpts.27.1271 . Groeneweg, R.; Haanstra, T.; Bolman, C.A.W.; Oostendorp, R.A.B.; van Tulder, M.W.; Ostelo, R.W.J.G. Treatment Success in Neck Pain: The Added Predictive Value of Psychosocial Variables in Addition to Clinical Variables. Scand J Pain 2017, 14 , 44–52, doi: 10.1016/j.sjpain.2016.10.003 . Fernández-Carnero, J.; Beltrán-Alacreu, H.; Arribas-Romano, A.; Cerezo-Téllez, E.; Cuenca-Zaldivar, J.N.; Sánchez-Romero, E.A.; Lerma Lara, S.; Villafañe, J.H. Prediction of Patient Satisfaction after Treatment of Chronic Neck Pain with Mulligan’s Mobilization. Life 2022, 13 , 48, doi: 10.3390/life13010048 . Guillén, D.; Guekos, A.; Graf, N.; Humphreys, B.K.; Peterson, C.; Schweinhardt, P. Limited Prognostic Value of Pain Duration in Non-specific Neck Pain Patients Seeking Chiropractic Care. European Journal of Pain 2022, 26 , 1333–1342, doi: 10.1002/ejp.1954 . Harrison, D.E.; Oakley, P.A.; Moustafa, I.M. Don’t Throw the ‘Bio’ out of the Bio-Psycho-Social Model: Editorial for Spine Rehabilitation in 2022 and Beyond. J Clin Med 2023, 12 , 5602, doi: 10.3390/jcm12175602 . Abdalatef N, Diab AA. Cervical Sagittal Balance as a Predictor for the Outcome of Multimodal Treatment Program for Non Specific Neck Pain. Med J Cairo Univ 2019, 87 , 4651–4659, doi: 10.21608/mjcu.2019.80827 . Moustafa, I.M.; Diab, A.A.; Hegazy, F.; Harrison, D.E. Demonstration of Central Conduction Time and Neuroplastic Changes after Cervical Lordosis Rehabilitation in Asymptomatic Subjects: A Randomized, Placebo-Controlled Trial. Sci Rep 2021, 11 , 15379, doi: 10.1038/s41598-021-94548-z . Moustafa IM, Diab AA, Hegazy F, Harrison DE. Does improvement towards a normal cervical sagittal configuration aid in the management of cervical myofascial pain syndrome: a 1- year randomized controlled trial. BMC Musculoskelet Disord. 2018;19(1):396. doi: 10.1186/s12891-018-2317-y Suwaidi ASA, Moustafa IM, Kim M, Oakley PA, Harrison DE. A Comparison of Two Forward Head Posture Corrective Approaches in Elderly with Chronic Non-Specific Neck Pain: A Randomized Controlled Study. J Clin Med. 2023;12(2):542. doi: 10.3390/jcm12020542 . Moustafa IM, Ozsahin DU, Mustapha MT, Ahbouch A, Oakley PA, Harrison DE. Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction. Sci Rep. 2024;14(1):11781. doi: 10.1038/s41598-024-62812-7 . Boland, D.M.; Neufeld, E. V.; Ruddell, J.; Dolezal, B.A.; Cooper, C.B. Inter- and Intra-Rater Agreement of Static Posture Analysis Using a Mobile Application. J Phys Ther Sci 2016, 28 , 3398–3402, doi: 10.1589/jpts.28.3398 . Szucs, K.A.; Brown, E.V.D. Rater Reliability and Construct Validity of a Mobile Application for Posture Analysis. J Phys Ther Sci 2018, 30 , 31–36, doi: 10.1589/jpts.30.31 . Tamim, M.; Moustafa, I.M.; Alaparthi, G.K.; Oakley, P.A.; Harrison, D.E. Translational and Rotational Postural Aberrations Are Related to Pulmonary Functions and Skill-Related Physical Fitness Components in Collegiate Athletes. J Clin Med 2023, 12 , 4618, doi: 10.3390/jcm12144618 . Moustafa, I.; Kim, M.; Harrison, D.E. Comparison of Sensorimotor Integration and Skill-Related Physical Fitness Components Between College Athletes With and Without Forward Head Posture. J Sport Rehabil 2023, 32 , 53–62, doi: 10.1123/jsr.2022-0094 . Zeppieri, G.; George, S.Z. Patient-Defined Desired Outcome, Success Criteria, and Expectation in Outpatient Physical Therapy: A Longitudinal Assessment. Health Qual Life Outcomes 2017, 15 , 29, doi: 10.1186/s12955-017-0604-1 . Brown, J.L.; Edwards, P.S.; Atchison, J.W.; Lafayette-Lucey, A.; Wittmer, V.T.; Robinson, M.E. Defining Patient-Centered, Multidimensional Success Criteria for Treatment of Chronic Spine Pain. Pain Medicine 2008, 9 , 851–862, doi: 10.1111/j.1526-4637.2007.00357.x . Kazeminasab S, Nejadghaderi SA, Amiri P, Pourfathi H, Araj-Khodaei M, Sullman MJM, et al. Neck pain: global epidemiology, trends and risk factors. BMC Musculoskelet Disord. 2022;23(1):26. doi: 10.1186/s12891-021-04957-4 Martínez-Borba V, Ripoll-Server P, Yakobov E, Suso-Ribera C. Predicting the Physical and Mental Health Status of Individuals With Chronic Musculoskeletal Pain From a Biopsychosocial Perspective: A Multivariate Approach. Clin J Pain. 2021;37(3):211–218. doi: 10.1097/AJP.0000000000000913 . Manderlier A, de Fooz M, Patris S, Berquin A. Modifiable lifestyle-related prognostic factors for the onset of chronic spinal pain: A systematic review of longitudinal studies. Ann Phys Rehabil Med. 2022;65(6):101660. doi: 10.1016/j.rehab.2022.101660 . Mansfield M, Thacker M, Spahr N, Smith T. Factors associated with physical activity participation in adults with chronic cervical spine pain: a systematic review. Physiotherapy. 2018;104(1):54–60. doi: 10.1016/j.physio.2017.01.004 . Dai Y, Huang J, Hu Q, Huang L, Wu J, Hu J. Association of Cigarette Smoking with Risk of Chronic Musculoskeletal Pain: A Meta-Analysis. Pain Physician. 2021;24(8):495–506. PMID: 34793634. McLean SM, May S, Klaber-Moffett J, Sharp DM, Gardiner E. Risk factors for the onset of non-specific neck pain: a systematic review. J Epidemiol Community Health. 2010;64(7):565–72. doi: 10.1136/jech.2009.090720 . Safiri S, Kolahi AA, Hoy D, Buchbinder R, Mansournia MA, Bettampadi D, Ashrafi-Asgarabad A, Almasi-Hashiani A, Smith E, Sepidarkish M, Cross M, Qorbani M, Moradi-Lakeh M, Woolf AD, March L, Collins G, Ferreira ML. Global, regional, and national burden of neck pain in the general population, 1990–2017: systematic analysis of the Global Burden of Disease Study 2017. BMJ. 2020;368:m791. doi: 10.1136/bmj.m791 . Côté P, Cassidy DJ, Carroll LJ, Kristman V. The annual incidence and course of neck pain in the general population: a population-based cohort study. Pain. 2004;112(3):267–273. doi: 10.1016/j.pain.2004.09.004 . Chen Y, Yang C, Nie K, Huang J, Qu Y, Wang T. Effects of scapular treatment on chronic neck pain: a systematic review and meta-analysis of randomized controlled trials. BMC Musculoskelet Disord. 2024;25(1):252. doi: 10.1186/s12891-024-07220-8 . Yang S, Boudier-Revéret M, Yi YG, Hong KY, Chang MC. Treatment of Chronic Neck Pain in Patients with Forward Head Posture: A Systematic Narrative Review. Healthcare (Basel). 2023;11(19):2604. doi: 10.3390/healthcare11192604 . Chaudhuri S, Chawla JK, Phadke V. Physiotherapeutic Interventions for Upper Cross Syndrome: A Systematic Review and Meta-Analysis. Cureus. 2023;15(9):e45471. doi: 10.7759/cureus . Rani B, Paul A, Chauhan A, Pradhan P, Dhillon MS. Is Neck Pain Related to Sagittal Head and Neck Posture?: A Systematic Review and Meta-analysis. Indian J Orthop. 2023;57(3):371–403. doi: 10.1007/s43465-023-00820-x Mahmoud NF, Hassan KA, Abdelmajeed SF, Moustafa IM, Silva AG. The Relationship Between Forward Head Posture and Neck Pain: a Systematic Review and Meta-Analysis. Curr Rev Musculoskelet Med. 2019;12(4):562–577. doi: 10.1007/s12178-019-09594-y . Rasmussen-Barr E, Halvorsen M, Bohman T, Boström C, Dedering Å, Kuster RP, Olsson CB, Rovner G, Tseli E, Nilsson-Wikmar L, Grooten WJA. Summarizing the effects of different exercise types in chronic neck pain - a systematic review and meta-analysis of systematic reviews. BMC Musculoskelet Disord. 2023;24(1):806. doi: 10.1186/s12891-023-06930-9 . Comparison of pressure biofeedback unit and mirror imaging technique in craniovertebral angle, pain, and strength of deep cervical flexors among collegiate students with forward head posture. Yugato 2024; 76()1):1–16. ISSN: 0387–5695, eISSN: 0387–5695 Shin, H.-J.; Kim, S.-H.; Hahm, S.-C.; Cho, H.-Y. Thermotherapy Plus Neck Stabilization Exercise for Chronic Nonspecific Neck Pain in Elderly: A Single-Blinded Randomized Controlled Trial. Int J Environ Res Public Health 2020, 17 , 5572, doi: 10.3390/ijerph17155572 . Domingues, L.; Pimentel-Santos, F.M.; Cruz, E.B.; Sousa, A.C.; Santos, A.; Cordovil, A.; Correia, A.; Torres, L.S.; Silva, A.; Branco, P.S.; et al. Is a Combined Programme of Manual Therapy and Exercise More Effective than Usual Care in Patients with Non-Specific Chronic Neck Pain? A Randomized Controlled Trial. Clin Rehabil 2019, 33 , 1908–1918, doi: 10.1177/0269215519876675 . Demir, O.; Atıcı, E.; Torlak, M.S. Therapeutic and Stabilization Exercises after Manual Therapy in Patients with Non-Specific Chronic Neck Pain: A Randomised Clinical Trial. International Journal of Osteopathic Medicine 2023, 47 , 100639, doi: 10.1016/j.ijosm.2022.10.001 . Lopez-Lopez, A.; Alonso Pérez, J.L.; Gonzalez Gutierez, J.L.; La Touche, R.; Lerma Lara, S.; Izquierdo, H.; Fernández-Carnero, J. Mobilization versus Manipulations versus Sustain Apophyseal Natural Glide Techniques and Interaction with Psychological Factors for Patients with Chronic Neck Pain: Randomized Controlled Trial. Eur J Phys Rehabil Med 2015, 51 , 121–132. Yesil, H.; Hepguler, S.; Dundar, U.; Taravati, S.; Isleten, B. Does the Use of Electrotherapies Increase the Effectiveness of Neck Stabilization Exercises for Improving Pain, Disability, Mood, and Quality of Life in Chronic Neck Pain? Spine (Phila Pa 1976) 2018, 43 , E1174–E1183, doi: 10.1097/BRS.0000000000002663 . Singla D, Veqar Z, Hussain ME. Photogrammetric Assessment of Upper Body Posture Using Postural Angles: A Literature Review. J Chiropr Med. 2017;16(2):131–138. doi: 10.1016/j.jcm.2017.01.005 . Additional Declarations Competing interest reported. DEH is the CEO of Chiropractic BioPhysics and lectures on rehabilitation methods, and distributes products for patient rehabilitation to physicians in the USA; none of these products were used in this manuscript. All the other authors declare that they have no competing interests. All the other authors declare that they have no competing interests. Cite Share Download PDF Status: Published Journal Publication published 30 May, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 11 Dec, 2024 Reviews received at journal 09 Dec, 2024 Reviewers agreed at journal 03 Dec, 2024 Reviews received at journal 03 Nov, 2024 Reviewers agreed at journal 14 Oct, 2024 Reviewers agreed at journal 05 Sep, 2024 Reviewers invited by journal 31 Jul, 2024 Editor assigned by journal 31 Jul, 2024 Editor invited by journal 25 Jul, 2024 Submission checks completed at journal 20 Jul, 2024 First submitted to journal 10 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4720644","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":339171941,"identity":"deb0b806-7ed6-4ca6-8d09-2e8de8ba0f9d","order_by":0,"name":"Ghydaa Anwar","email":"","orcid":"","institution":"University of Sharjah","correspondingAuthor":false,"prefix":"","firstName":"Ghydaa","middleName":"","lastName":"Anwar","suffix":""},{"id":339171942,"identity":"4fa33d3f-61ac-445c-98f9-01dc798dca4f","order_by":1,"name":"Ibrahim M. Moustafa","email":"","orcid":"","institution":"University of Sharjah","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"M.","lastName":"Moustafa","suffix":""},{"id":339171943,"identity":"ec4fc2d6-369c-4dda-ac81-471001fe2e5c","order_by":2,"name":"Amal Ahbouch","email":"","orcid":"","institution":"University of Sharjah","correspondingAuthor":false,"prefix":"","firstName":"Amal","middleName":"","lastName":"Ahbouch","suffix":""},{"id":339171944,"identity":"d55d62b5-7fbb-41a4-ad02-c31db714fa90","order_by":3,"name":"Abdulla Alrahoomi","email":"","orcid":"","institution":"Rehabilitation Hospital, Sh. Tahnoon Bin Mohammed Medical City (STMC), UAE","correspondingAuthor":false,"prefix":"","firstName":"Abdulla","middleName":"","lastName":"Alrahoomi","suffix":""},{"id":339171945,"identity":"0adee0fa-e764-48e6-839c-58d8356b6ae1","order_by":4,"name":"Deed E. Harrison","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYDCCAwwGDAxsNjxABuMBBgYJorWkgbQwkKTlMANUCxGA7/bhjQ8+lJ2X4Tve/ODgzx0WefwMzA8f3cCjRfJcWrHhjHO3eSTPHDM4zHtGoliygc3YOAePFoMzPGbSvG23eQxuJBgcZmyTSNxwgIdNmoAW899/287xGNx//uHgT6CW/URoMWNmbDsAtIXH4AAvyBYGAlokz7AVS/acSwb6JacA5JfEGYcJ+IXvDPPGDz/K7Oz5jh/f+PDnjrrE/vbmh4/xaUEFjA1Agplo5XAto2AUjIJRMArQAADT/FP965gNoQAAAABJRU5ErkJggg==","orcid":"","institution":"CBP Nonprofit (a Spine Research Foundation)","correspondingAuthor":true,"prefix":"","firstName":"Deed","middleName":"E.","lastName":"Harrison","suffix":""}],"badges":[],"createdAt":"2024-07-10 21:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4720644/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4720644/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-04187-x","type":"published","date":"2025-05-30T15:57:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62730734,"identity":"8ca09754-9e10-4d54-9292-f337cc9de743","added_by":"auto","created_at":"2024-08-18 23:22:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":109531,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot for posture parameters across genders. CVA(°): craniovertebral angle; Sagittal head translation: anterior head posture in inches (in.); Coronal head translation: left and right head translation (in.); Lateral angulation: lateral head tilt left or right (°); M: males; F: females.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4720644/v1/c5e471ba9ff9096814ee8689.jpeg"},{"id":62730739,"identity":"388fc885-e70e-46bd-a111-ca06d24f4903","added_by":"auto","created_at":"2024-08-18 23:22:05","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65064,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot of sagittal head translation distance in inches, for: 1) all patients, 2) in successful outcome patients and, 3) in those with lack of success or failure at 6-months.\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4720644/v1/e773fe1478a827729ddb7d6a.jpeg"},{"id":62730738,"identity":"d539bc53-6950-4d74-8f57-0295d86bef93","added_by":"auto","created_at":"2024-08-18 23:22:05","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":130354,"visible":true,"origin":"","legend":"\u003cp\u003eTwo measurements of forward head posture. 1) The craniovertebral angle (CVA°) is measured using two landmarks: the tragus of the ear and the C7 spinous process (marked in yellow). A line (marked in red) is then extended horizontally from the C7 spinous process, and another connects the C7 to the tragus; this intersection creates the CVA. 2) Sagittal head translation (SHT) in inches. A vertical line is constructed at the center of the glenohumeral joint and the horizontal offset of the tragus of the ear is measured as the SHT in inches. Note this is a computer generated image and not an actual human.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4720644/v1/9ba6a488d2d321d22f1ca7e4.jpeg"},{"id":62730736,"identity":"1809b1f1-e20b-406d-991d-0072cac818ad","added_by":"auto","created_at":"2024-08-18 23:22:04","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":159915,"visible":true,"origin":"","legend":"\u003cp\u003eCoronal heat translation (CHT) left and right measured in inches. CHT can be assessed in anterior and posterior views in the PSM app. The figure above shows the lateral head translation (marked in red) of the head from the true vertical plumbline (marked in black). Note this is a computer generated image and not an actual human.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4720644/v1/ad0aeaaec5bf1e7b7a489bdc.jpeg"},{"id":62730737,"identity":"fcce2f3d-118c-4def-88d3-719eaa0054b1","added_by":"auto","created_at":"2024-08-18 23:22:05","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":175037,"visible":true,"origin":"","legend":"\u003cp\u003eLateral head angulation (LHA°) left and right (coronal plane bending) can be assessed in either the anterior and posterior views. The figure above shows the lateral tilt (marked in red) of the head from the true vertical plumbline. Note this is a computer generated image and not an actual human.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4720644/v1/4f10cc674e790e09f7d0d38b.jpeg"},{"id":83782979,"identity":"33b559c0-6fe6-4a63-b425-616bf4b9bc7b","added_by":"auto","created_at":"2025-06-02 16:09:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2061709,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4720644/v1/5251e276-1b24-402c-ad9d-5c99992fe778.pdf"}],"financialInterests":"Competing interest reported. DEH is the CEO of Chiropractic BioPhysics and lectures on rehabilitation methods, and distributes products for patient rehabilitation to physicians in the USA; none of these products were used in this manuscript. All the other authors declare that they have no competing interests. All the other authors declare that they have no competing interests.","formattedTitle":"Rotations and Translations of Head Posture Parameters as a Predictor of the Rehabilitation Management Outcomes in Patients with Chronic Nonspecific Neck Pain: A Multicenter Prospective Case Series","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic non-specific neck pain (CNSNP) is a prevalent clinical problem\u003csup\u003e1,2\u003c/sup\u003e that significantly impacts an individual\u0026rsquo;s quality of life,\u003csup\u003e3\u0026ndash;6\u003c/sup\u003e leading to delayed recovery, persistent disability,\u003csup\u003e1\u003c/sup\u003e and increased healthcare costs.\u003csup\u003e2,6\u003c/sup\u003e With a reported prevalence varying widely, CNSNP imposes a substantial financial burden on the healthcare system.\u003csup\u003e2,6\u003c/sup\u003e Although the occurrence of CNSNP increases with age, there is generally no significant sex difference in its prevalence.\u003csup\u003e7\u003c/sup\u003e Despite its high prevalence, the conservative treatment of CNSNP remains challenging.\u003csup\u003e8\u003c/sup\u003e Many patients continue to experience symptoms for extended periods, often a year or longer. Recent systematic reviews have highlighted the lack of clearly effective conservative treatments for CNSNP,\u003csup\u003e8\u003c/sup\u003e particularly for long-term management.\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIdentifying specific outcomes that predict the success of conservative treatment for CNSNP is crucial. Predictors can help tailor treatment options to individual patients, enhancing clinical care and improve long-term prognosis.\u003csup\u003e10\u003c/sup\u003e Various predictors, such as the perception of treatment outcome success,\u003csup\u003e10\u003c/sup\u003e pain intensity,\u003csup\u003e10,11\u003c/sup\u003e duration of complaints,\u003csup\u003e12\u003c/sup\u003e and response to specific physical tests, have been reported previously​. Importantly, the role of mechanical alignment of the cervical spine as a predictor of management outcomes has often been overlooked in clinical practice and research.\u003csup\u003e13\u003c/sup\u003e According to Harrison et al.,\u003csup\u003e13\u003c/sup\u003e the recent focus on the bio-psycho-social model has led to an underemphasis on the 'bio' component, particularly biomechanics, in the treatment of spinal disorders. It is relevant that several studies indicate that the sagittal plane alignment and overall biomechanics of the cervical spine significantly impact patient outcomes, including pain, disability, and functional mobility.\u003csup\u003e14\u003c/sup\u003e For example, randomized controlled trials have demonstrated that interventions aimed at correcting cervical sagittal alignment, such as cervical extension traction (CET), results in better long-term health outcomes as compared to conventional treatments that do not address spinal alignment.\u003csup\u003e13,15\u0026ndash;18\u003c/sup\u003e This evidence underscores the importance of considering biomechanical factors in developing treatment plans for spinal disorders; thus, advocating for a more balanced approach that integrates mechanical alignment with psycho-social factors to enhance patient care and outcomes.\u003c/p\u003e \u003cp\u003eRecent technological advancements have enabled precise measurement and quantification of head posture in terms of translational and rotational displacements.\u003csup\u003e19,20\u003c/sup\u003e Studies have demonstrated that postural aberrations, both head translations and rotations, are linked to physical fitness and cardiopulmonary functions.\u003csup\u003e21,22\u003c/sup\u003e These findings highlight the importance in evaluating and addressing postural imbalances to enhance clinical outcomes. However, often, rehabilitation programs for CNSNP do not typically consider the rotations and translations of head posture parameters and thus do not include specific interventions and outcomes designed to improve these as part of a multi-modal program of care.\u003c/p\u003e \u003cp\u003eAccordingly, our study aims to investigate the rotations and translations of head posture parameters as predictors of conservative treatment outcomes in patients with CNSNP. This multicenter prospective cohort study used a 6-month follow-up to determine if the magnitude of these displacements predicts success or failure of conservative care outcomes in this patient population. We hypothesized that the magnitude of rotations and translations of head posture parameters would be predictors of the outcomes of conservative care in patients with CNSNP​​​​.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe demographic characteristics of the study participants are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. This was a young adult population with an average age of 35.22 years (SD\u0026thinsp;=\u0026thinsp;5.93). The body mass index (BMI) distribution shows that 50% of participants had a normal BMI, 33.3% were overweight, and 16.7% were obese, highlighting a substantial portion falling into higher BMI categories. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the differences between males and females for each of the study variables. The sex distribution was skewed towards males (65.2%) compared to females (34.8%). Additionally, 79% of participants were non-smokers, and 67.5% were married. Posture parameters, including craniovertebral angle (CVA), sagittal head translation (SHT), coronal head translation, and lateral angulation, displayed variability among participants as depicted in the boxplot across all participants within males and females in \u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e. Pain, fatigue, distress, and interference were assessed at pre-treatment, post-treatment, and 6-months, showing general improvement post-treatment but variable long-term outcomes. Success rates for pain, fatigue, distress, and interference were above 60%, indicating substantial but not universal improvement. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eWhen comparing demographic characteristics across sex, there was no significant difference in age, BMI, smoking status, or marital status (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Posture parameters showed no significant sex differences except for lateral head tilt, being greater in males (p\u0026thinsp;=\u0026thinsp;0.03). Figure\u0026nbsp;1 shows the boxplot for the distribution of the 4 postural variables between males and females. Pain at 6-months was significantly higher in females (p\u0026thinsp;=\u0026thinsp;0.04). Fatigue and distress scores did not significantly differ between sexes across any time point. Similarly, interference scores and success and failure rates for pain, fatigue, distress, and interference did not differ significantly between sexes. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents this detailed data between males and females.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of the study participants (n\u0026thinsp;=\u0026thinsp;86). BMI: body mass index; N: number; In.: inches.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic characteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.22\u0026thinsp;\u0026plusmn;\u0026thinsp;5.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Normal (BMI\u0026thinsp;=\u0026thinsp;18.5 to 24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Overweight (BMI\u0026thinsp;=\u0026thinsp;25\u0026ndash;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Obese (BMI\u0026thinsp;=\u0026thinsp;30\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (34.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (65.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (79%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (67.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Not Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePosture parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- CVA (\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.52\u0026thinsp;\u0026plusmn;\u0026thinsp;5.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Sagittal head translation (in.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Coronal head translation (in.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Lateral angulation (\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.94\u0026thinsp;\u0026plusmn;\u0026thinsp;4.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.82\u0026thinsp;\u0026plusmn;\u0026thinsp;9.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8-weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.74\u0026thinsp;\u0026plusmn;\u0026thinsp;13.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 Month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.76\u0026thinsp;\u0026plusmn;\u0026thinsp;31.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFatigue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.22\u0026thinsp;\u0026plusmn;\u0026thinsp;7.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.11\u0026thinsp;\u0026plusmn;\u0026thinsp;9.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.00\u0026thinsp;\u0026plusmn;\u0026thinsp;26.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistress\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.99\u0026thinsp;\u0026plusmn;\u0026thinsp;11.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.70\u0026thinsp;\u0026plusmn;\u0026thinsp;12.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.20\u0026thinsp;\u0026plusmn;\u0026thinsp;24.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.39\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.41\u0026thinsp;\u0026plusmn;\u0026thinsp;12.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.12\u0026thinsp;\u0026plusmn;\u0026thinsp;3.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSuccess and failure rates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.67%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistress - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistress - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterference - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterference - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics distributed across sex. BMI: body mass index; CVA: craniovertebral angle; In.: inches.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic characteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale (N\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale (N\u0026thinsp;=\u0026thinsp;56)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 \u0026plusmn; 5.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 \u0026plusmn; 5.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Overweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Obese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (76.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (78.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Yes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (21.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Not Married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePosture parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- CVA (\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.84\u0026thinsp;\u0026plusmn;\u0026thinsp;5.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.26\u0026thinsp;\u0026plusmn;\u0026thinsp;5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Sagittal head translation (in.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Coronal head translation (in.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Lateral angulation (\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.81\u0026thinsp;\u0026plusmn;\u0026thinsp;4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.89\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePain\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.56\u0026thinsp;\u0026plusmn;\u0026thinsp;10.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.04\u0026thinsp;\u0026plusmn;\u0026thinsp;9.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.73\u0026thinsp;\u0026plusmn;\u0026thinsp;13.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.76\u0026thinsp;\u0026plusmn;\u0026thinsp;13.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.41\u0026thinsp;\u0026plusmn;\u0026thinsp;31.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.90\u0026thinsp;\u0026plusmn;\u0026thinsp;29.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFatigue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.44\u0026thinsp;\u0026plusmn;\u0026thinsp;7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.04\u0026thinsp;\u0026plusmn;\u0026thinsp;7.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.15\u0026thinsp;\u0026plusmn;\u0026thinsp;9.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.76\u0026thinsp;\u0026plusmn;\u0026thinsp;9.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.68\u0026thinsp;\u0026plusmn;\u0026thinsp;26.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.45\u0026thinsp;\u0026plusmn;\u0026thinsp;25.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistress\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.29\u0026thinsp;\u0026plusmn;\u0026thinsp;12.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.73\u0026thinsp;\u0026plusmn;\u0026thinsp;10.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.29\u0026thinsp;\u0026plusmn;\u0026thinsp;12.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.85\u0026thinsp;\u0026plusmn;\u0026thinsp;25.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.84\u0026thinsp;\u0026plusmn;\u0026thinsp;22.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Pre treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.54\u0026thinsp;\u0026plusmn;\u0026thinsp;6.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.10\u0026thinsp;\u0026plusmn;\u0026thinsp;7.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Post treatment 8 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.17\u0026thinsp;\u0026plusmn;\u0026thinsp;12.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.45\u0026thinsp;\u0026plusmn;\u0026thinsp;13.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- At 6 month follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.49\u0026thinsp;\u0026plusmn;\u0026thinsp;27.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.36\u0026thinsp;\u0026plusmn;\u0026thinsp;28.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSuccess and failure rates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistress - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistress - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterference - Success rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterference - Failure rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe correlation matrix indicates high correlations among posture variables, suggesting multicollinearity as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. As a result, only the sagittal (anterior) head translation is used in logistic regression models to avoid multicollinearity issues. This ensures more reliable and interpretable results in the subsequent analyses. The box plots of the sagittal head translation distance in inches measured for all patients, in successful outcome patients, and in those with lack of success or failure to respond to conservative care for the combined outcome is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This figure clearly identifies that increased sagittal head translation, measured in inches, is strongly related to those patients who failed to respond at 6-month follow-up.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe logistic regression result for predicting overall success is shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. 1) \u003cem\u003eAge\u003c/em\u003e: the odds ratio (0.69) suggests that as age increases, the likelihood of overall success decreases (p\u0026thinsp;=\u0026thinsp;0.001). 2) \u003cem\u003eBMI\u003c/em\u003e: for BMI, the odds ratio is 0.85, indicating that an increase in BMI slightly decreases the likelihood of overall success, but this effect is not statistically significant (p\u0026thinsp;=\u0026thinsp;0.23). 3) \u003cem\u003eSagittal head translation\u003c/em\u003e: more anterior movement of the head in the sagittal plane significantly lowers the chances of success. Each unit increase in this movement reduces the odds of success to about 13%, showing a strong and significant effect (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). 4) \u003cem\u003eSex\u003c/em\u003e: females have higher odds of overall success compared to males (OR\u0026thinsp;=\u0026thinsp;2.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). 5) \u003cem\u003eSmoking status and marital status\u003c/em\u003e: neither of these factors are statistically significant predictors of overall success. See Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMulticollinearity check of posture variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoronal head translation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLateral head angulation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLateral head angulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression results for overall success.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.69 (0.555\u0026ndash;0.865)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.85 (0.63\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.13 (0.048\u0026ndash;0.349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.7 (1.833\u0026ndash;4.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96 (0.645\u0026ndash;1.441)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e=\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.34 (0.877\u0026ndash;2.060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e=\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe logistic regression result for predicting pain success is shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. 1) \u003cem\u003eAge\u003c/em\u003e: the odds ratio of 0.97 suggests no significant impact of age on pain success (p\u0026thinsp;=\u0026thinsp;0.53). 2) \u003cem\u003eBMI\u003c/em\u003e: the odds ratio of 0.77 indicates no significant impact of BMI on pain success (p\u0026thinsp;=\u0026thinsp;0.53). 3) \u003cem\u003eSex\u003c/em\u003e: shows that females have significantly higher odds of pain success compared to males, with an odds ratio of 0.27 (p\u0026thinsp;=\u0026thinsp;0.03). This indicates that being female increases the likelihood of pain success. 4) \u003cem\u003eSmoking and marital status\u003c/em\u003e: neither smoking or marital status are significant predictors of pain success (p\u0026thinsp;=\u0026thinsp;0.68 and p\u0026thinsp;=\u0026thinsp;0.53, respectively). 5) \u003cem\u003eSagittal head translation\u003c/em\u003e: greater sagittal head translation significantly reduces the odds of pain success (OR\u0026thinsp;=\u0026thinsp;0.11, 95% CI: 0.04\u0026ndash;0.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression results for pain success.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.2435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97 (0.88\u0026ndash;1.068)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.2592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77 (0.33\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.3092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27 (0.085\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.1248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.13 (0.616\u0026ndash;2.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.28 (0.58\u0026ndash;2.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.1916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11 (0.040\u0026ndash;0.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe logistic regression result for predicting fatigue success is shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. 1) \u003cem\u003eAge\u003c/em\u003e: The odds ratio of 1.06 indicates that age does not have a significant impact on fatigue success (p\u0026thinsp;=\u0026thinsp;0.89). 2) \u003cem\u003eBMI\u003c/em\u003e: The negative coefficient suggests a potential inverse relationship, where an increase in BMI might be associated with lower odds of fatigue success. However, this relationship is not statistically significant (p\u0026thinsp;=\u0026thinsp;0.57). 3) \u003cem\u003eSex\u003c/em\u003e: Sex does not have a statistically significant impact on fatigue success. Although females have 2.46 times the odds of fatigue success compared to males, this finding is not statistically significant (p\u0026thinsp;=\u0026thinsp;0.24). 4) \u003cem\u003eSmoking Status\u003c/em\u003e: Smoking status is a significant predictor of fatigue success. Smokers have 6.62 times the odds of achieving fatigue success compared to non-smokers, and this relationship is statistically significant (p\u0026thinsp;=\u0026thinsp;0.037). 5. \u003cem\u003eMarital Status\u003c/em\u003e: Based on the logistic regression results, there is no strong evidence to suggest that marital status is significantly related to fatigue success. Although the odds ratio indicates that being married might be associated with higher odds of pain success. 6) \u003cem\u003eSagittal Head Translation\u003c/em\u003e: Increased sagittal head translation significantly decreases the likelihood of achieving fatigue success. The odds ratio of 0.057 indicates a strong inverse relationship, and this finding is statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression results for fatigue success.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06 (0.46\u0026ndash;2.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76 (0.28\u0026ndash;2.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.30 (0.47\u0026ndash;3.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.46 (0.51\u0026ndash;12.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.62 (1.66\u0026ndash;26.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.057 (0.012\u0026ndash;0.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe logistic regression result for predicting distress is shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. \u003cem\u003e1) Age\u003c/em\u003e: older participants are significantly more likely to succeed in managing distress (OR\u0026thinsp;=\u0026thinsp;1.16, 95% CI: 1.031\u0026ndash;1.324, p\u0026thinsp;=\u0026thinsp;0.015). 2) \u003cem\u003eBMI\u003c/em\u003e: higher BMI is not a significant predictor of distress success (OR\u0026thinsp;=\u0026thinsp;2.87, 95% CI: 0.838\u0026ndash;9.669, p\u0026thinsp;=\u0026thinsp;0.093). 3) \u003cem\u003eSex\u003c/em\u003e: gender is not a significant predictor of distress success (OR\u0026thinsp;=\u0026thinsp;0.33, 95% CI: 0.078\u0026ndash;1.463, p\u0026thinsp;=\u0026thinsp;0.147). 4) \u003cem\u003eSmoking status\u003c/em\u003e: smoking status is not a significant predictor of distress success (OR\u0026thinsp;=\u0026thinsp;1.35, 95% CI: 0.602\u0026ndash;3.038, p\u0026thinsp;=\u0026thinsp;0.464). 5) \u003cem\u003eMarital status\u003c/em\u003e is not a significant predictor of distress success (OR\u0026thinsp;=\u0026thinsp;0.77, 95% CI: 0.29\u0026ndash;2.05, p\u0026thinsp;=\u0026thinsp;0.60). 6) \u003cem\u003eSagittal head translation\u003c/em\u003e: greater sagittal head translation significantly reduces the odds of distress success (OR\u0026thinsp;=\u0026thinsp;0.16, 95% CI: 0.038\u0026ndash;0.718, p\u0026thinsp;=\u0026thinsp;0.016).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression results for distress success.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.16 (1.031\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.87 (0.838\u0026ndash;9.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33 (0.078\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.35 (0.602\u0026ndash;3.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77 (0.29\u0026ndash;2.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16 (0.038\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe logistic regression result for predicting interference success is shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. 1) \u003cem\u003eAge\u003c/em\u003e: the odds ratio of 0.96 suggests no significant impact of age on interference success (p\u0026thinsp;=\u0026thinsp;0.433). 2) \u003cem\u003eBMI\u003c/em\u003e: the odds ratio of 0.66 indicates no significant impact of BMI on interference success (p\u0026thinsp;=\u0026thinsp;0.321). 3) \u003cem\u003eSex\u003c/em\u003e: gender is marginally significant, with males less likely to succeed in managing interference compared to females (OR\u0026thinsp;=\u0026thinsp;0.33, 95% CI: 0.110\u0026ndash;1.026, p\u0026thinsp;=\u0026thinsp;0.055). 4) \u003cem\u003eSmoking status\u003c/em\u003e: smoking status is not a significant predictor of interference success (OR\u0026thinsp;=\u0026thinsp;1.04, 95% CI: 0.574\u0026ndash;1.887, p\u0026thinsp;=\u0026thinsp;0.897). 5) 5) Marital status: Marital status is not a significant predictor of interference success (p\u0026thinsp;=\u0026thinsp;0.67). The odds ratio of 1.16 suggests a non-significant increase in the odds of interference success for married individuals. 6) \u003cem\u003eSagittal head translation\u003c/em\u003e: greater sagittal head translation significantly reduces the odds of interference success (OR\u0026thinsp;=\u0026thinsp;0.13, 95% CI: 0.048\u0026ndash;0.349, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression results for interference success.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.87\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66 (0.29\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33 (0.110\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.04 (0.57\u0026ndash;1.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.16 (0.57\u0026ndash;2.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13 (0.048\u0026ndash;0.34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe Generalized estimation equation (GEE) result for assessing the effect of time and other predictors on pain scores is shown in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. Only time and sagittal head translation are statistically related to time on pain scores, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. \u003cem\u003eOther Variables\u003c/em\u003e: age, BMI, sex, and smoking status do not significantly predict pain scores.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe generalized estimation equations (GEE) results for pain scores.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.99\u0026ndash;70.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-18.45\u0026ndash;12.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.57\u0026ndash;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.99\u0026ndash;1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.22\u0026ndash;8.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.08\u0026ndash;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.75\u0026ndash;9.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe GEE result for assessing the effect of time and other predictors (age, BMI, sex, smoking status, and sagittal head translation) on fatigue scores is shown in Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. The main interpretation is that time and sagittal head translation are statistically significant predictors of fatigue scores, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Other variables such as age, BMI, sex, and smoking status are not statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe generalized estimation equations (GEE) results for fatigue scores.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.67\u0026ndash;52.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-15.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-18.44 - -12.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.35\u0026ndash;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.08\u0026ndash;2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.03\u0026ndash;7.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.93\u0026ndash;2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.25\u0026ndash;6.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe GEE result for assessing the effect of time and other predictors (age, BMI, sex, smoking status, and sagittal head translation) on distress scores is shown in Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e. Time and sagittal head translation are statistically significant predictors of distress scores, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Other variables such as age, BMI, sex, and smoking status are not statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe generalized estimation equations (GEE) results for distress scores.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.62\u0026ndash;66.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-10.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-13.44 - -8.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.50\u0026ndash;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.27\u0026ndash;1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.58\u0026ndash;6.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.58\u0026ndash;2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.23\u0026ndash;6.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLastly, the GEE result for assessing the effect of time and other predictors (age, BMI, sex, smoking status, and sagittal head translation) on interference scores is shown in Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e. Time and sagittal head translation are statistically significant predictors of interference scores, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Other variables such as age, BMI, sex, and smoking status are not statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe generalized estimation equations (GEE) results for interference scores.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.9\u0026ndash;54.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-13.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-16.2 - -11.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.25\u0026ndash;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.59\u0026ndash;3.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.75\u0026ndash;8.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.50\u0026ndash;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSagittal head translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.62\u0026ndash;8.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe current prospective, multi-center, consecutive case series was conducted to investigate if postural parameters of the cervical spine and demographic variables might predict the successful outcome of physiotherapeutic interventions in clinical practice in patients suffering from a primary complaint of CNSNP. Our study\u0026rsquo;s primary hypothesis was that cervical spine posture displacements would be predictors of success or failure of conservative care outcomes in patients suffering from CNSNP. One of our primary findings was that the magnitude of SHT (a measure of forward head posture) significantly affected the odds of a successful outcome of conservative care. In fact, considering all four domains on the patient centered outcome questionnaire (PCOQ)\u003csup\u003e23,24\u003c/sup\u003e simultaneously, for each unit increase in SHT distance, the odds of a successful outcome decreased by 13%. Thus, our study\u0026rsquo;s main hypothesis is confirmed by our results. Additionally, we found that younger age and female sex had substantial impacts on the likelihood of a successful outcome when considering all four domains on the PCOQ.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eNegative predictors: Marital status, Smoking and Obesity\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSeveral demographic and socio-economic variables have been shown to predict chronicity and outcomes in CNSNP.\u003csup\u003e3,6,7,10,25\u003c/sup\u003e In the current project, we looked at several demographic variables as they relate to the odds of improving CNSNP using the four parts of the patient centered outcome questionnaire (PCOQ)\u003csup\u003e23,24\u003c/sup\u003e: pain intensity, fatigue, distress, and interference following a multi-modal conservative care program. Interestingly, we found no relationship with marital status, smoking status, and BMI and the odds of overall recovery; there is conflicting evidence on this in the chronic cervical spine pain literature. For example, studies have provided evidence supporting the notion that higher levels of perceived social support and justice correlate with decreased pain-related disability among individuals dealing with chronic pain-related psychosocial conditions but that age, sex, marital status, and pain duration were not related.\u003csup\u003e26\u003c/sup\u003e In the current project we did not account for social support (other than marital status) nor did we account for injustice and it is difficult to compare our findings of conservative care for CNSNP to those outcome investigatons that did not specifically look at CNSNP exclusively.\u003csup\u003e26\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn the current project, we did have a significant sample of high BMI patients (BMI\u0026thinsp;\u0026gt;\u0026thinsp;30): where 16.7% of our sample were classified as obese (BMI\u0026thinsp;\u0026gt;\u0026thinsp;35) and 33%, were classifed as overweight (35\u0026thinsp;\u0026gt;\u0026thinsp;BMI\u0026thinsp;\u0026gt;\u0026thinsp;30). The logistic regression result for predicting fatigue success on the PCOQ indicated that BMI had a negative coefficient implying a potential inverse relationship (increased BMI might be associated with lower odds of fatigue success), but this relationship was not statistically significant. In a recent systematic review of risk factors for chronic neck pain, strong evidence for high BMI in women and conflicting evidence for high BMI in men was found; however, this was not a treatment outcomes investigation so it is difficult to compare these findings with ours.\u003csup\u003e27\u003c/sup\u003e Similarly, smoking status was not a significant predictor of overall success on the total PCOQ score. However, smoking status was found to be a significant predictor of fatigue success; where smokers had 6.62 times the odds of achieving fatigue success compared to non-smokers, and this relationship is statistically significant (p\u0026thinsp;=\u0026thinsp;0.037). The fatigue success increase with smokers is difficult to explain and it may be unique to our population of younger individuals. In general, though our overall finding of lack of a non-significant smoking effect on outcomes is in general agreement with systematic literature reviews where smoking is not necessarily a contributor to specific chronic neck pain but is more of a risk for low back pain and wide spread pain.\u003csup\u003e28,29\u003c/sup\u003e Based on the logistic regression results, for marital status there was no strong evidence to suggest that marital status was significantly related to pain success; although the odds ratio indicated that being married might be non-statistically associated with higher odds of pain success implying this could be a type of social support for selected individuals.\u003csup\u003e26\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePositive predictors: Age and Gender\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur logistic regression result for predicting overall success on the four parts of the PCOQ identified that participant age was a statistically significant predictor for the odds of success (OR\u0026thinsp;=\u0026thinsp;0.69, p\u0026thinsp;=\u0026thinsp;0.001) suggesting that older age reduced the overall success. This finding that younger age is a significant predictor of treatment success is consistent with previous investigations on chronic neck pain.\u003csup\u003e25,30,31\u003c/sup\u003e For example, the prevalence of CNSNP peaks between the ages of 45\u0026ndash;49 years in men and 50\u0026ndash;54 in women.\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRegarding sex differences, the results of our logistic regression analysis for predicting overall success on the four parts of the PCOQ identified that females have a higher odd of overall success compared to males for treatment improvement results when suffering CNSNP (OR\u0026thinsp;=\u0026thinsp;2.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There are general conflicting findings regarding sex and the development and treatment outcomes for CNSNP.\u003csup\u003e25\u003c/sup\u003e For example, McLean et al.\u003csup\u003e30\u003c/sup\u003e and Cote and colleagues\u003csup\u003e32\u003c/sup\u003e have identified that women are at greater risk for the development of neck pain. Whereas Kazeminasab et al.\u003csup\u003e25\u003c/sup\u003e reviewed the recent epidemiological studies and found no meaningful sex differences between male and females across age groups in populations with chronic neck pain. Specific to treatment outcomes for CNSNP, Chen and colleagues\u003csup\u003e33\u003c/sup\u003e presented a systematic review and meta-analysis of RCTs analyzing the effect of scapular treatment on improving chronic neck pain incidence and found that females seemed to be better treated with scapular exercise training. The finding from Chen et al.\u003csup\u003e33\u003c/sup\u003e is comparable with our results with women experiencing an overall greater benefit than men although we did not specifically incorporate scapular retraining exercises into our treatment regimen.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePostural predictors\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOur primary finding of interest, herein, is that we identified that the sagittal head translation (SHT) significantly affected the odds of success of overall and individual outcomes on the PCOQ. Specifically, greater anterior movement of the head in the sagittal plane significantly lowers the chances of success, where each unit increase in SHT movement reduced the odds of success by 13% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Importantly, we found multicollinearity between the potential postural predictors, i.e. that the potential postural predictors were interrelated. A statistical consequence of this is that a multivariate regression model may give non-significant results even if several of the factors are important and significant in bivariate analyses. For instance, all the postural displacements assessed herein (CVA, SHT, coronal head translation, and coronal lateral bending) are likely important predictors, but since these variables are correlated a regression model may give non-significant results for these predictors. As a matter of fact, the SHT postural predictor is directly related to the CVA postural variable as they are both attempting to measure the same postural phenomenon of forward head posture. In several of the stepwise regression models, the SHT was selected first and this is the reason this posture was chosen in the current investigative results. The fact that other postural predictors were not selected does not mean that they are unimportant, but they can be omitted, herein, because part of the information they contain is accounted for by the SHT distance already included in the model.\u003c/p\u003e\u003cp\u003eRecent investigations have identified that imbalance of cervical spine postural alignment in both the coronal and sagittal planes negatively affects patient outcomes and is associated with increased pain, disability, altered neurophysiology, and altered cardio-pulmonary performance.\u003csup\u003e13\u0026ndash;18,21,22\u003c/sup\u003e Specific to our regression modelling results, forward head posture (FHP) as measured with the SHT method herein, is a very common posture abnormality and multiple recent systematic reviews and meta-analyses have been published on this postural abnormality.\u003csup\u003e33\u0026ndash;37\u003c/sup\u003e From these reviews, it is clear that FHP is a significant postural abnormality related to pain, disability, and function and interventional strategies are recommended to improve identified abnormalities in patients to within normal values as found in asymptomatic populations.\u003csup\u003e33\u0026ndash;37\u003c/sup\u003e Thus, our primary finding that SHT magnitude is a predictor of poor outcomes in patients undergoing treatment for CNSNP is strongly consistent with the current literature on the topic of FHP in varying populations.\u003c/p\u003e\u003cp\u003eOur investigation is the first to look at each of the four scales on the PCOQ in patients with altered posture undergoing treatment for CNSNP which adds value to the evolving literature on the topic of FHP and related outcomes. In contrast, our specific finding that SHT magnitude predicts those patients who fail a conservative care program incorporating a considerable cervical spine exercise regimen is in conflict with a recent meta-analysis review on the topic of exercise types for chronic neck pain.\u003csup\u003e38\u003c/sup\u003e Rasmussen-Barr and colleagues\u003csup\u003e38\u003c/sup\u003e identified that there is low to high certainty of evidence for positive effects of a variety of cervical spine exercises on pain and disability used in chronic neck pain compared to no-exercise interventions. However, they found no evidence of a superior type of cervical spine exercise program, but rather all of them appear to have some beneficial effect. Our results suggest that exercise or other interventions that specifically target altered postural displacements and specifically document their correction should show superiority in treatment outcomes of CNSNP. Preliminarily there appears to be support for this in the recent literature\u003csup\u003e16,17,39\u003c/sup\u003e though continued investigation in the form of high-quality randomized trials is needed to further validate this finding.\u003c/p\u003e\u003cp\u003e\u003cem\u003eLimitations and future investigations.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAs with all investigations, our study has limitations. Primarily, this was not a randomized controlled trial looking at the success or failure of specific treatment interventions. Thus, it is not known whether the exact type of treatment provided was optimum as it was a compilation of interventions known to aid patients suffering from CNSNP. Furthermore, because we did not specifically look at interventions that are known to improve cervical spine posture displacements, we cannot say whether improving these cervical spine postural specific variables would result in better success for patients with this suffering from CNSNP. Future randomized trials are needed to investigate these limitations to determine more effective clinical intervention strategies for patients with altered cervical spine posture and CNSNP. Additionally, we recognize the importance of conducting exploratory, associative analyses to investigate how factors such as education, employment status, economic resources, health behaviors, and physical and mental health conditions may influence the association between patient education, patient expectations and management parameters.\u003c/p\u003e\u003cp\u003eAnother source of potential bias in this study was the lack of standardization protocols among different hospitals. While our study did not aim to standardize treatment programs across multiple centers, we meticulously selected centers from a similar demographic area with similar treatment approaches to mitigate potential biases. Additionally, we have provided detailed descriptions of our rehabilitation program, thereby enhancing the credibility and reproducibility of our findings.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this multicenter, prospective consecutive case series conducted across 5 physiotherapy clinics in the UAE and Egypt, our findings indicate that younger age, female sex, and better cervical spine posture alignment all had a substantial impact on the likelihood of success of 6-month outcomes in patients suffering from chronic nonspecific neck pain (CNSNP). Non-significant (no association) predictors of patient outcomes included marital status, BMI, and smoking perhaps (except where smokers had an increase success on the fatigue scale) due to our unique sample and categorization of these patients. Importantly, a primary biomechanical driver of poor outcomes at 6-month follow-up after a 2-month multi-modal treatment program for CNSNP is altered cervical spine postural alignment. Thus, future rehabilitation programs incorporating specific postural corrective approaches need to be tested for short and long-term patient relevant outcomes in patients suffering from CNSNP. Future randomized trials are needed to evaluate treatment outcomes based on correcting cervical spine posture displacements.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eStudy Design and Population\u003c/h2\u003e\n\u003cp\u003eThis is a multicenter, prospective cohort study conducted across five physiotherapy clinics in the UAE and Egypt from January 2021 to March 2023 to assess the rotations and translations of head posture parameters as potential predictors of conservative therapy outcomes in patients with CNSNP. The protocol of the study was approved by the Ethical Review Board of the University of Sharjah (REC-21-03-11-03-S). Written informed consent was obtained from all participants and all experimental protocols were carried out following the guidelines of the World Medical Association Declaration of Helsinki. Patients with CNSNP who underwent conservative therapy as the first line of treatment were included in this prospective study. Conservative therapy included rest, physical therapy (neck exercises, diathermy therapy, and distraction (longitudinal) traction), education with instructions for home-based exercise, and medications such as nonsteroidal anti-inflammatory drugs (NSAIDs), analgesics, muscle relaxants, or oral narcotics.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eConservative Therapy\u003c/h2\u003e\n\u003cp\u003eAlthough our study, being multi-center in nature, did not intend to standardize the treatment program, we selected centers that predominantly align with a similar treatment approach. The therapeutic approach involved a comprehensive yet personalized treatment strategy. This multifaceted regimen comprises various components to alleviate pain and enhance functionality. This comprehensive conservative therapy aimed to manage CNSNP by addressing pain, functional limitations, and enhancing overall quality of life of the patients. The 8-week conservative therapy protocol for treatment of CNSNP involves a comprehensive treatment approach administered three times per week for the 8-weeks. The protocol begins with a 2-week education phase focusing on patient education, self-management, and activity modification to promote ergonomic practices and proper posture. Simultaneously, therapeutic exercises are introduced from week 1, starting with stabilization and isometric exercises. These exercises progress in intensity and complexity every two weeks, evolving into strengthening exercises targeting deep neck flexors and incorporating motor control principles. From week 3 onwards, manual therapy, including grade III posteroanterior mobilizations, is integrated and continues through week 8. Throughout the entire treatment period, modalities such as heat therapy and TENS are applied to alleviate pain and enhance treatment efficacy. Ergonomic advice emphasized from the beginning and continuously reinforced to support a neutral spine position and improve overall functionality. Each treatment session, conducted three times per week for 8 weeks, is tailored to ensure patient comfort and progress, with modifications made as needed based on individual responses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConservative Treatment Modalities\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003cp\u003e1) Education and Self-Management:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003ePatient Education\u003c/em\u003e: Informing patients about the nature of their condition, the importance of maintaining good posture, and ergonomic adjustments can empower them to manage their symptoms better.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eActivity Modification\u003c/em\u003e: Advising on modifying daily activities to avoid exacerbating movements and encourage the adoption of ergonomic practices at work and home.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n2) Therapeutic Exercises:\u003cbr /\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eStabilization Exercises\u003c/em\u003e: These exercises aim to improve the control and endurance of the deep cervical flexors and extensors, which can help in reducing pain and preventing recurrence. The protocol for stabilization exercises was adapted from Shin et al.\u003csup\u003e40\u003c/sup\u003e It consisted of a 30-minute exercise session, preceded by a 5-minute warm up, and followed by a 5-minute cool down. The warmup and cool down phases included general stretching of the upper extremity and neck. The main exercise session included:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eSupine isometrics of deep neck flexors\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eSitting cervical multidirectional isometrics (flexion, extension, lateral flexion, rotation)\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eUpper extremity movement exercises\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eCervical resistive exercises with Thera-band\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eStrengthening Exercises\u003c/em\u003e: Progressive resistance exercises for the neck and shoulder muscles can enhance overall muscular support for the cervical spine. Therefore, strengthening exercises were incorporated in this intervention program mainly targeting deep neck flexor muscles. The exercises were based on principles of motor control as described by Domingues et al\u003csup\u003e41\u003c/sup\u003e in their randomized controlled trial. The program consisted of three phases:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003ePhase one: This phase targeted activation of deep flexors in the upper cervical region, specifically the longus capitis and colli. Patients were instructed to perform cranio-cervical flexion (chin tuck) in supine position, with a pressure cuff placed behind their neck. This position was held for 10 seconds and repeated 10 times. Successfully completing 10 repetitions at 26 mmHg permits the transfer to the second phase.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePhase two: This phase continues the previous exercises in loading positions such as sitting and quadruped / 4-point kneeling, while maintaining a neutral cervical spine. Additionally, the pressure level was increased to 28 and 30 mmHg.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePhase three: This phase begins with the chin tucks and is progressed with a higher load by adding 15 repetitions of shoulder flexion and head lifts in supine position.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eExercise prescription\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eThe previously mentioned volumes and intensity were the foundation of exercise prescription for all patients. However, individual modifications were made when required to ensure prescription was suitable for each patient and they remained pain-free.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eStretching Exercises\u003c/em\u003e: Regular stretching of the cervical muscles, especially the upper trapezius, levator scapulae, scalenes, and sternocleidomastoid, can help alleviate tightness and improve range of motion (ROM). Therefore, stretches were incorporated in this intervention plan where participants performed 3 sets of stretches with a 15 second hold.\u003csup\u003e42\u003c/sup\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n3) Manual Therapy:\u003cbr /\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eMobilization Techniques\u003c/em\u003e: Gentle, repetitive movements were applied to the cervical spine to enhance joint mobility and reduce pain.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eProtocol\u003c/em\u003e: The manual therapy protocol used in this study was adopted from a randomized controlled trial by Lopez-Lopez et al.\u003csup\u003e43\u003c/sup\u003e Initially, the patient is instructed to lie prone with hands under their forehead. The therapist stands at the patient\u0026rsquo;s head and places their thumbs over the spinous process of the targeted vertebra. The vertebra that is selected for mobilization is the one that is identified as symptomatic and hypomobile. Then, the therapist applies a grade III posteroanterior (PA) oscillatory force at the frequency of 2 Hz. This is carried on for 3 sets, each lasting 2 minutes, with a 1-minute rest interval between sets.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n4) Modalities:\u003cbr /\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eHeat Therapy\u003c/em\u003e: Application of heat can relax tight muscles and improve blood flow.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cem\u003eElectrotherapy\u003c/em\u003e: Techniques such as transcutaneous electrical nerve stimulation (TENS) provide pain relief by modulating the pain signals sent to the brain. This method was added to the intervention plan for pain relief as it is effective in the treatment of CNSNP. TENS was administered using four electrodes placed over painful areas on the neck and shoulder region. The stimulation was delivered at a frequency of 80 Hz and an intensity of 10 mA to 30 mA, for 25 minutes.\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n5) Ergonomic Adjustments: Recommendations for workplace adjustments, such as chair height, monitor position, and keyboard placement, can help maintain a neutral spine position.\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003eOutcome Variables\u003c/h2\u003e\n\u003cp\u003eThe primary outcome variable used in this study was the conservative treatment outcome after a 6-month follow-up after completion of active interventions (defined as success or failure). In this study, the success criteria were defined from the spine pain patient\u0026rsquo;s perspective across multiple relevant domains using the patient centered outcome questionnaire (PCOQ).\u003csup\u003e23\u003c/sup\u003e This questionnaire instructs the patient to rate their current level of pain, fatigue, distress, and interference of daily activities on a numerical rating scale (NRS), ranging from 0 to 100. The patient then repeats the rating in the second section of the questionnaire, but instead of rating\u003c/p\u003e\n\u003cp\u003ecurrent levels, they rate levels of the four domains they expect to achieve following the physical therapy intervention. This allows for the assessment of the patients\u0026rsquo; presentation, expectation, and goals, and quantifies the impact these four domains have on the patient\u0026rsquo;s health, as well as how the intervention will affect them.\u003c/p\u003e\n\u003cp\u003eThe following four endpoints were considered because previous research has shown them to be clinically relevant with good reliability and concurrent validity: reduction of pain, reduction of fatigue, reduction of distress, and reduction of interference.\u003csup\u003e24\u003c/sup\u003e The rehabilitation program was considered successful if the 4 domain outcomes were decreased at discharge time by the optimal cutoff points according to Brown et al.,\u003csup\u003e24\u003c/sup\u003e and this improvement was maintained or further improved at the 6-month follow up, otherwise it was considered as a failure. The optimal cutoff points were: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) reduction of pain of 17.5 points or more (0\u0026ndash;100 numerical rating scale); (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) fatigue reduction of 7.5 points or more; (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) reduction for distress by 5 points or more; and (\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e) reduction of interference by 9.5 points or more. The criteria for the 6-month follow-up failure were: (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) increase of pain or reduction less than 17.5 points; (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) increase of fatigue or reduction less than 7.5 points; (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) increase of distress or reduction less than 5 points; and (\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e) increase in the inference with daily activities or reduction less 9.5 points.\u003csup\u003e24\u003c/sup\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003eRotations and Translations of Head Posture Parameters\u003c/h2\u003e\n\u003cp\u003eThe rotations and translations of head posture parameters were measured using a standardized protocol. This included the assessment of cervical spine angles, head tilt, head rotation, and the translation of the head in relation to the cervical spine. Posture measurement was achieved by the PostureScreen\u0026reg; Mobile app (PSM) which is a digital posturographic assessment tool used to perform 3D postural examinations. The PSM has been established in research as a reliable and valid method for evaluating static posture. For example, investigations have identified that PSM has an intra-rater reliability that ranges from 0.71 to 0.99, and an inter-rater reliability which is good to excellent for all translations (ICC\u0026rsquo;s between 0.85 and 0.98).\u003csup\u003e19,20\u003c/sup\u003e PSM captures images of the participant from four directions: anterior and posterior (coronal plane) and the left and right sides (sagittal plane). After the photograph is captured, specific anatomical reference points are digitized by the user such as the pelvic iliac spines, the greater trochanter, the femoral condyle, and the tragus. To ensure maximum accuracy of the manual digitization of landmarks, participants were instructed to undress/wear clothing that exposes the landmarks required so that they could be identified and labelled prior to digitization. Moreover, the landmarks were digitized by the same research team member and then cross-checked by the same 2 members to ensure accuracy for all participants\u0026rsquo; data. The PSM then calculates specific body angles and distances based on the anatomical digitization and creates an output file containing values of posture variables and images of the participant that can be used to compare and analyze the postural deviations from neutral among participants.\u003c/p\u003e\n\u003cp\u003eThe following postural parameters were assessed using the PSM app:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cp\u003eThe cranio-vertebral angle (CVA (\u0026deg;)) is the acute angle that is formed between a straight line that connects the spinous process of C7 to the tragus of the ear, and the horizontal line that passes through the spinous process of C7. The angle is identified by the intersection of those two lines.\u003csup\u003e45\u003c/sup\u003e See Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eSagittal head translation, which is the movement of the head (tragus of the ear) anteriorly relative to the center of the glenohumeral joint. See Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u0026nbsp;Coronal head translation (CHT) or left and right head translation, is the movement of the cervical spine and head laterally to either side. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e depicts this measurement.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLateral head angulation (LHA) or coronal plane side bending of the head towards either side. The PSM app allows LHA to be assessed in either the anterior or posterior view. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e depicts this measurement.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003eData Analysis\u003c/h2\u003e\n\u003cp\u003eThe descriptive statistics utilized in our investigation included count and percentages to describe categorical data. The Shapiro-Wilk test was used to test the normality of the numerical variables. Based on this, we report the median and interquartile ranges (IQR) to describe numerical data since all the numerical data, such as age, head posture parameters, and the scores of the four study outcomes, were not normally distributed. Multiple logistic regression models were used to assess the predictors of the success of each of the four outcomes as well as the four outcomes combined into one variable. Generalized estimation equations (GEE) were developed to assess the effect of time on pain, fatigue, distress, and interference scores, as well as the effect of other potential predictors. SPSS version 25.0 for Windows (IBM, Armonk, NY, USA) was used for data analysis.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors would like to thank CBP NonProfit, Inc. for the possible funding of this manuscript if accepted for publication. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors GA, IMM, A.Ah, A.Al and DEH all participated in the conception and design. GA, IMM, A.Ah, A.Al each participated in study implementation and data collection. \u0026nbsp;GA, IMM, A.Ah, A.Al, DEH contributed to the statistical analysis and interpretation. IMM, A.Ah, A.Al participated in supervision. GA, IMM, A.Ah, A.Al and DEH all contributed to the interpretation of the results and wrote the drafts. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDEH is the CEO of Chiropractic BioPhysics and lectures on rehabilitation methods, and distributes products for patient rehabilitation to physicians in the USA; none of these products were used in this manuscript. All the other authors declare that they have no competing interests.\u0026nbsp;All the other authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available upon reasonable request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePrice, J.; Rushton, A.; Tyros, V.; Heneghan, N.R. Expert Consensus on the Importance of Chronic Non-Specific Neck Pain Motor Control and Segmental Exercise and Dosage Variables: An International e-Delphi Study. PLoS One 2021, \u003cem\u003e16\u003c/em\u003e, e0253523, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0253523\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0253523\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaizah, A.; Reddy, R.S.; Alshahrani, M.S.; Gautam, A.P.; Alkhamis, B.A.; Kakaraparthi, V.N.; Ahmad, I.; Kandakurti, P.K.; ALMohiza, M.A. A Cross-Sectional Study on Mediating Effect of Chronic Pain on the Relationship between Cervical Proprioception and Functional Balance in Elderly Individuals with Chronic Neck Pain: Mediation Analysis Study. J Clin Med 2023, \u003cem\u003e12\u003c/em\u003e, 3140, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12093140\u003c/span\u003e\u003cspan address=\"10.3390/jcm12093140\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, Z.; Falla, D.; Elgueta Cancino, E.; A Deane, J. Can Baseline Features Predict a Reduction in Pain and Disability Following Neck-Specific Exercise in People with Chronic Non-Specific Neck Pain?: A Systematic Review and Meta-Analysis Protocol. BMJ Open 2023, \u003cem\u003e13\u003c/em\u003e, e074494, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2023-074494\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2023-074494\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC\u0026ocirc;t\u0026eacute;, P.; Wong, J.J.; Sutton, D.; Shearer, H.M.; Mior, S.; Randhawa, K.; Ameis, A.; Carroll, L.J.; Nordin, M.; Yu, H.; et al. Management of Neck Pain and Associated Disorders: A Clinical Practice Guideline from the Ontario Protocol for Traffic Injury Management (OPTIMa) Collaboration. European Spine Journal 2016, \u003cem\u003e25\u003c/em\u003e, 2000\u0026ndash;2022, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00586-016-4467-7\u003c/span\u003e\u003cspan address=\"10.1007/s00586-016-4467-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCerezo-T\u0026eacute;llez, E.; Torres-Lacomba, M.; Mayoral-del-Moral, O.; Pacheco-da-Costa, S.; Prieto-Merino, D.; S\u0026aacute;nchez-S\u0026aacute;nchez, B. Health Related Quality of Life Improvement in Chronic Non-Specific Neck Pain: Secondary Analysis from a Single Blinded, Randomized Clinical Trial. Health Qual Life Outcomes 2018, \u003cem\u003e16\u003c/em\u003e, 207, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12955-018-1032-6\u003c/span\u003e\u003cspan address=\"10.1186/s12955-018-1032-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark, S.J.; Lee, R.; Yoon, D.M.; Yoon, K.B.; Kim, K.; Kim, S.H. Factors Associated with Increased Risk for Pain Catastrophizing in Patients with Chronic Neck Pain. Medicine 2016, \u003cem\u003e95\u003c/em\u003e, e4698, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MD.0000000000004698\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000004698\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng, B.; Zheng, L.; Li, M.; Lin, J.; Zhu, Y.; Jin, L.; You, R.; Gao, Y.; Liu, X.; Wang, S. Sex Differences in Factors Associated with Neck Pain among Undergraduate Healthcare Students: A Cross-Sectional Survey. BMC Musculoskelet Disord 2022, \u003cem\u003e23\u003c/em\u003e, 842, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12891-022-05782-z\u003c/span\u003e\u003cspan address=\"10.1186/s12891-022-05782-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Zoete, R.M.J. Exercise Therapy for Chronic Neck Pain: Tailoring Person-Centred Approaches within Contemporary Management. J Clin Med 2023, \u003cem\u003e12\u003c/em\u003e, 7108, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12227108\u003c/span\u003e\u003cspan address=\"10.3390/jcm12227108\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng, C.-H.; Su, H.-T.; Yen, L.-W.; Liu, W.-Y.; Cheng, H.-Y.K. Long-Term Effects of Therapeutic Exercise on Nonspecific Chronic Neck Pain: A Literature Review. J Phys Ther Sci 2015, \u003cem\u003e27\u003c/em\u003e, 1271\u0026ndash;1276, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1589/jpts.27.1271\u003c/span\u003e\u003cspan address=\"10.1589/jpts.27.1271\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGroeneweg, R.; Haanstra, T.; Bolman, C.A.W.; Oostendorp, R.A.B.; van Tulder, M.W.; Ostelo, R.W.J.G. Treatment Success in Neck Pain: The Added Predictive Value of Psychosocial Variables in Addition to Clinical Variables. Scand J Pain 2017, \u003cem\u003e14\u003c/em\u003e, 44\u0026ndash;52, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.sjpain.2016.10.003\u003c/span\u003e\u003cspan address=\"10.1016/j.sjpain.2016.10.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFern\u0026aacute;ndez-Carnero, J.; Beltr\u0026aacute;n-Alacreu, H.; Arribas-Romano, A.; Cerezo-T\u0026eacute;llez, E.; Cuenca-Zaldivar, J.N.; S\u0026aacute;nchez-Romero, E.A.; Lerma Lara, S.; Villafa\u0026ntilde;e, J.H. Prediction of Patient Satisfaction after Treatment of Chronic Neck Pain with Mulligan\u0026rsquo;s Mobilization. Life 2022, \u003cem\u003e13\u003c/em\u003e, 48, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/life13010048\u003c/span\u003e\u003cspan address=\"10.3390/life13010048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuill\u0026eacute;n, D.; Guekos, A.; Graf, N.; Humphreys, B.K.; Peterson, C.; Schweinhardt, P. Limited Prognostic Value of Pain Duration in Non-specific Neck Pain Patients Seeking Chiropractic Care. European Journal of Pain 2022, \u003cem\u003e26\u003c/em\u003e, 1333\u0026ndash;1342, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ejp.1954\u003c/span\u003e\u003cspan address=\"10.1002/ejp.1954\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarrison, D.E.; Oakley, P.A.; Moustafa, I.M. Don\u0026rsquo;t Throw the \u0026lsquo;Bio\u0026rsquo; out of the Bio-Psycho-Social Model: Editorial for Spine Rehabilitation in 2022 and Beyond. J Clin Med 2023, \u003cem\u003e12\u003c/em\u003e, 5602, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12175602\u003c/span\u003e\u003cspan address=\"10.3390/jcm12175602\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdalatef N, Diab AA. Cervical Sagittal Balance as a Predictor for the Outcome of Multimodal Treatment Program for Non Specific Neck Pain. Med J Cairo Univ 2019, \u003cem\u003e87\u003c/em\u003e, 4651\u0026ndash;4659, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21608/mjcu.2019.80827\u003c/span\u003e\u003cspan address=\"10.21608/mjcu.2019.80827\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoustafa, I.M.; Diab, A.A.; Hegazy, F.; Harrison, D.E. Demonstration of Central Conduction Time and Neuroplastic Changes after Cervical Lordosis Rehabilitation in Asymptomatic Subjects: A Randomized, Placebo-Controlled Trial. Sci Rep 2021, \u003cem\u003e11\u003c/em\u003e, 15379, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-021-94548-z\u003c/span\u003e\u003cspan address=\"10.1038/s41598-021-94548-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoustafa IM, Diab AA, Hegazy F, Harrison DE. Does improvement towards a normal cervical sagittal configuration aid in the management of cervical myofascial pain syndrome: a 1- year randomized controlled trial. BMC Musculoskelet Disord. 2018;19(1):396. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12891-018-2317-y\u003c/span\u003e\u003cspan address=\"10.1186/s12891-018-2317-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuwaidi ASA, Moustafa IM, Kim M, Oakley PA, Harrison DE. A Comparison of Two Forward Head Posture Corrective Approaches in Elderly with Chronic Non-Specific Neck Pain: A Randomized Controlled Study. J Clin Med. 2023;12(2):542. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12020542\u003c/span\u003e\u003cspan address=\"10.3390/jcm12020542\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoustafa IM, Ozsahin DU, Mustapha MT, Ahbouch A, Oakley PA, Harrison DE. Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction. Sci Rep. 2024;14(1):11781. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-024-62812-7\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-62812-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoland, D.M.; Neufeld, E. V.; Ruddell, J.; Dolezal, B.A.; Cooper, C.B. Inter- and Intra-Rater Agreement of Static Posture Analysis Using a Mobile Application. J Phys Ther Sci 2016, \u003cem\u003e28\u003c/em\u003e, 3398\u0026ndash;3402, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1589/jpts.28.3398\u003c/span\u003e\u003cspan address=\"10.1589/jpts.28.3398\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzucs, K.A.; Brown, E.V.D. Rater Reliability and Construct Validity of a Mobile Application for Posture Analysis. J Phys Ther Sci 2018, \u003cem\u003e30\u003c/em\u003e, 31\u0026ndash;36, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1589/jpts.30.31\u003c/span\u003e\u003cspan address=\"10.1589/jpts.30.31\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTamim, M.; Moustafa, I.M.; Alaparthi, G.K.; Oakley, P.A.; Harrison, D.E. Translational and Rotational Postural Aberrations Are Related to Pulmonary Functions and Skill-Related Physical Fitness Components in Collegiate Athletes. J Clin Med 2023, \u003cem\u003e12\u003c/em\u003e, 4618, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm12144618\u003c/span\u003e\u003cspan address=\"10.3390/jcm12144618\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoustafa, I.; Kim, M.; Harrison, D.E. Comparison of Sensorimotor Integration and Skill-Related Physical Fitness Components Between College Athletes With and Without Forward Head Posture. J Sport Rehabil 2023, \u003cem\u003e32\u003c/em\u003e, 53\u0026ndash;62, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1123/jsr.2022-0094\u003c/span\u003e\u003cspan address=\"10.1123/jsr.2022-0094\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeppieri, G.; George, S.Z. Patient-Defined Desired Outcome, Success Criteria, and Expectation in Outpatient Physical Therapy: A Longitudinal Assessment. Health Qual Life Outcomes 2017, \u003cem\u003e15\u003c/em\u003e, 29, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12955-017-0604-1\u003c/span\u003e\u003cspan address=\"10.1186/s12955-017-0604-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown, J.L.; Edwards, P.S.; Atchison, J.W.; Lafayette-Lucey, A.; Wittmer, V.T.; Robinson, M.E. Defining Patient-Centered, Multidimensional Success Criteria for Treatment of Chronic Spine Pain. Pain Medicine 2008, \u003cem\u003e9\u003c/em\u003e, 851\u0026ndash;862, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1526-4637.2007.00357.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1526-4637.2007.00357.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKazeminasab S, Nejadghaderi SA, Amiri P, Pourfathi H, Araj-Khodaei M, Sullman MJM, et al. Neck pain: global epidemiology, trends and risk factors. BMC Musculoskelet Disord. 2022;23(1):26. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12891-021-04957-4\u003c/span\u003e\u003cspan address=\"10.1186/s12891-021-04957-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMart\u0026iacute;nez-Borba V, Ripoll-Server P, Yakobov E, Suso-Ribera C. Predicting the Physical and Mental Health Status of Individuals With Chronic Musculoskeletal Pain From a Biopsychosocial Perspective: A Multivariate Approach. Clin J Pain. 2021;37(3):211\u0026ndash;218. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/AJP.0000000000000913\u003c/span\u003e\u003cspan address=\"10.1097/AJP.0000000000000913\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManderlier A, de Fooz M, Patris S, Berquin A. Modifiable lifestyle-related prognostic factors for the onset of chronic spinal pain: A systematic review of longitudinal studies. Ann Phys Rehabil Med. 2022;65(6):101660. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.rehab.2022.101660\u003c/span\u003e\u003cspan address=\"10.1016/j.rehab.2022.101660\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMansfield M, Thacker M, Spahr N, Smith T. Factors associated with physical activity participation in adults with chronic cervical spine pain: a systematic review. Physiotherapy. 2018;104(1):54\u0026ndash;60. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.physio.2017.01.004\u003c/span\u003e\u003cspan address=\"10.1016/j.physio.2017.01.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDai Y, Huang J, Hu Q, Huang L, Wu J, Hu J. Association of Cigarette Smoking with Risk of Chronic Musculoskeletal Pain: A Meta-Analysis. Pain Physician. 2021;24(8):495\u0026ndash;506. PMID: 34793634.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLean SM, May S, Klaber-Moffett J, Sharp DM, Gardiner E. Risk factors for the onset of non-specific neck pain: a systematic review. J Epidemiol Community Health. 2010;64(7):565\u0026ndash;72. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/jech.2009.090720\u003c/span\u003e\u003cspan address=\"10.1136/jech.2009.090720\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSafiri S, Kolahi AA, Hoy D, Buchbinder R, Mansournia MA, Bettampadi D, Ashrafi-Asgarabad A, Almasi-Hashiani A, Smith E, Sepidarkish M, Cross M, Qorbani M, Moradi-Lakeh M, Woolf AD, March L, Collins G, Ferreira ML. Global, regional, and national burden of neck pain in the general population, 1990\u0026ndash;2017: systematic analysis of the Global Burden of Disease Study 2017. BMJ. 2020;368:m791. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.m791\u003c/span\u003e\u003cspan address=\"10.1136/bmj.m791\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC\u0026ocirc;t\u0026eacute; P, Cassidy DJ, Carroll LJ, Kristman V. The annual incidence and course of neck pain in the general population: a population-based cohort study. Pain. 2004;112(3):267\u0026ndash;273. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pain.2004.09.004\u003c/span\u003e\u003cspan address=\"10.1016/j.pain.2004.09.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Yang C, Nie K, Huang J, Qu Y, Wang T. Effects of scapular treatment on chronic neck pain: a systematic review and meta-analysis of randomized controlled trials. BMC Musculoskelet Disord. 2024;25(1):252. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12891-024-07220-8\u003c/span\u003e\u003cspan address=\"10.1186/s12891-024-07220-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang S, Boudier-Rev\u0026eacute;ret M, Yi YG, Hong KY, Chang MC. Treatment of Chronic Neck Pain in Patients with Forward Head Posture: A Systematic Narrative Review. Healthcare (Basel). 2023;11(19):2604. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/healthcare11192604\u003c/span\u003e\u003cspan address=\"10.3390/healthcare11192604\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaudhuri S, Chawla JK, Phadke V. Physiotherapeutic Interventions for Upper Cross Syndrome: A Systematic Review and Meta-Analysis. Cureus. 2023;15(9):e45471. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7759/cureus\u003c/span\u003e\u003cspan address=\"10.7759/cureus\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRani B, Paul A, Chauhan A, Pradhan P, Dhillon MS. Is Neck Pain Related to Sagittal Head and Neck Posture?: A Systematic Review and Meta-analysis. Indian J Orthop. 2023;57(3):371\u0026ndash;403. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s43465-023-00820-x\u003c/span\u003e\u003cspan address=\"10.1007/s43465-023-00820-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahmoud NF, Hassan KA, Abdelmajeed SF, Moustafa IM, Silva AG. The Relationship Between Forward Head Posture and Neck Pain: a Systematic Review and Meta-Analysis. Curr Rev Musculoskelet Med. 2019;12(4):562\u0026ndash;577. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12178-019-09594-y\u003c/span\u003e\u003cspan address=\"10.1007/s12178-019-09594-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRasmussen-Barr E, Halvorsen M, Bohman T, Bostr\u0026ouml;m C, Dedering \u0026Aring;, Kuster RP, Olsson CB, Rovner G, Tseli E, Nilsson-Wikmar L, Grooten WJA. Summarizing the effects of different exercise types in chronic neck pain - a systematic review and meta-analysis of systematic reviews. BMC Musculoskelet Disord. 2023;24(1):806. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12891-023-06930-9\u003c/span\u003e\u003cspan address=\"10.1186/s12891-023-06930-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eComparison of pressure biofeedback unit and mirror imaging technique in craniovertebral angle, pain, and strength of deep cervical flexors among collegiate students with forward head posture. Yugato 2024; 76()1):1\u0026ndash;16. ISSN: 0387\u0026ndash;5695, eISSN: 0387\u0026ndash;5695\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShin, H.-J.; Kim, S.-H.; Hahm, S.-C.; Cho, H.-Y. Thermotherapy Plus Neck Stabilization Exercise for Chronic Nonspecific Neck Pain in Elderly: A Single-Blinded Randomized Controlled Trial. Int J Environ Res Public Health 2020, \u003cem\u003e17\u003c/em\u003e, 5572, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph17155572\u003c/span\u003e\u003cspan address=\"10.3390/ijerph17155572\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDomingues, L.; Pimentel-Santos, F.M.; Cruz, E.B.; Sousa, A.C.; Santos, A.; Cordovil, A.; Correia, A.; Torres, L.S.; Silva, A.; Branco, P.S.; et al. Is a Combined Programme of Manual Therapy and Exercise More Effective than Usual Care in Patients with Non-Specific Chronic Neck Pain? A Randomized Controlled Trial. Clin Rehabil 2019, \u003cem\u003e33\u003c/em\u003e, 1908\u0026ndash;1918, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0269215519876675\u003c/span\u003e\u003cspan address=\"10.1177/0269215519876675\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemir, O.; Atıcı, E.; Torlak, M.S. Therapeutic and Stabilization Exercises after Manual Therapy in Patients with Non-Specific Chronic Neck Pain: A Randomised Clinical Trial. International Journal of Osteopathic Medicine 2023, \u003cem\u003e47\u003c/em\u003e, 100639, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijosm.2022.10.001\u003c/span\u003e\u003cspan address=\"10.1016/j.ijosm.2022.10.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez-Lopez, A.; Alonso P\u0026eacute;rez, J.L.; Gonzalez Gutierez, J.L.; La Touche, R.; Lerma Lara, S.; Izquierdo, H.; Fern\u0026aacute;ndez-Carnero, J. Mobilization versus Manipulations versus Sustain Apophyseal Natural Glide Techniques and Interaction with Psychological Factors for Patients with Chronic Neck Pain: Randomized Controlled Trial. Eur J Phys Rehabil Med 2015, \u003cem\u003e51\u003c/em\u003e, 121\u0026ndash;132.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYesil, H.; Hepguler, S.; Dundar, U.; Taravati, S.; Isleten, B. Does the Use of Electrotherapies Increase the Effectiveness of Neck Stabilization Exercises for Improving Pain, Disability, Mood, and Quality of Life in Chronic Neck Pain? \u003cem\u003eSpine (Phila Pa\u003c/em\u003e 1976) 2018, \u003cem\u003e43\u003c/em\u003e, E1174\u0026ndash;E1183, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/BRS.0000000000002663\u003c/span\u003e\u003cspan address=\"10.1097/BRS.0000000000002663\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingla D, Veqar Z, Hussain ME. Photogrammetric Assessment of Upper Body Posture Using Postural Angles: A Literature Review. J Chiropr Med. 2017;16(2):131\u0026ndash;138. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcm.2017.01.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jcm.2017.01.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cervical spine, posture, neck pain, disability, case series, CVA, forward head posture","lastPublishedDoi":"10.21203/rs.3.rs-4720644/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4720644/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA multicenter, prospective consecutive case series study was conducted in 5 physiotherapy clinics in the UAE from January 2021 to March 2023 to assess rotations and translations of head posture parameters as potential predictors of conservative therapy outcomes in patients with chronic non-specific neck pain (CNSNP). Eighty-six patients (mean age 35 yrs., 65% male) with CNSNP underwent conservative therapy. All participants received a detailed examination including a computerized cervical spine posture analysis and demographic data was collected. Interventions included specific exercises, diathermy, longitudinal traction, education, a detailed exercise program, ergonomic advice, and medications. Interventions were applied 3 times per week for 8 weeks. Follow-up was 6-months after final treatment. A successful outcome was based on a minimum improvement of the following four outcomes using the patient centered outcome questionnaire (PCOQ): (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) reduction of pain by 17.5 points (0\u0026ndash;100 NRS); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) fatigue reduction by 7.5 points; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) distress reduction by 5 points; and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) interference reduction by 9.5 points. At 6-month follow-up it was found that success rates for pain, fatigue, distress, and interference were above 60% for the total participants. The logistic regression for predicting overall success in combined outcomes based on age, gender, smoking status, marital status, and sagittal head translation was: 1) \u003cem\u003eAge\u003c/em\u003e: the odds ratio (0.69) suggests that as age increases, the likelihood of overall success decreases (p\u0026thinsp;=\u0026thinsp;0.001); 2) \u003cem\u003eSex\u003c/em\u003e: females have higher odds of overall success compared to males (OR\u0026thinsp;=\u0026thinsp;2.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); 3) \u003cem\u003eSmoking status and marital status\u003c/em\u003e: neither of these factors were statistically significant predictors of overall success; 4) \u003cem\u003eSagittal head translation\u003c/em\u003e: each unit increase (more anterior) in this abnormal posture reduced the odds of success by 13%, showing a strong and significant effect (OR\u0026thinsp;=\u0026thinsp;0.13, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Overall, our findings indicate that younger age, female sex, and better posture alignment of the cervical spine all had a substantial impact on the likelihood of success of 6-month outcomes in patients suffering CNSNP.\u003c/p\u003e","manuscriptTitle":"Rotations and Translations of Head Posture Parameters as a Predictor of the Rehabilitation Management Outcomes in Patients with Chronic Nonspecific Neck Pain: A Multicenter Prospective Case Series","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-18 23:21:59","doi":"10.21203/rs.3.rs-4720644/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-11T06:42:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-09T22:12:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"307837996238922054821857750068502446032","date":"2024-12-03T16:25:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-03T23:20:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191165325967029611354731831958773797920","date":"2024-10-14T08:09:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42407118911910140685564289909097675200","date":"2024-09-05T05:27:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-31T06:10:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-31T06:09:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-25T15:32:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-20T04:50:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-07-10T21:13:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f1837601-ac3a-4980-954b-b21237fa0d24","owner":[],"postedDate":"August 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":35927984,"name":"Health sciences/Health care"},{"id":35927985,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2025-06-02T16:03:09+00:00","versionOfRecord":{"articleIdentity":"rs-4720644","link":"https://doi.org/10.1038/s41598-025-04187-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-05-30 15:57:52","publishedOnDateReadable":"May 30th, 2025"},"versionCreatedAt":"2024-08-18 23:21:59","video":"","vorDoi":"10.1038/s41598-025-04187-x","vorDoiUrl":"https://doi.org/10.1038/s41598-025-04187-x","workflowStages":[]},"version":"v1","identity":"rs-4720644","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4720644","identity":"rs-4720644","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}