Knowledge, Attitudes, and Practice of Women in Lebanon Surrounding Uterine Adenomyosis: A Cross-Sectional Study

Knowledge, Attitudes, and Practice of Women in Lebanon Surrounding Uterine Adenomyosis: A Cross-Sectional Study | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Knowledge, Attitudes, and Practice of Women in Lebanon Surrounding Uterine Adenomyosis: A Cross-Sectional Study Abdullah Kadhim, Aya Shaaban, Mohammad Ziad Bakkar, Mariam Mghames, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-11153706/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Background Adenomyosis is a common gynaecological disorder associated with dysmenorrhea, abnormal uterine bleeding, pelvic pain, and reproductive complications. Despite the clinical burden presented by it, awareness remains limited. This study aimed to assess knowledge, attitudes, and practice (KAP) regarding adenomyosis in reproductive-aged women in Lebanon. Methods A cross-sectional online survey was conducted among women aged 18–49 in Lebanon using snowball and convenience sampling. A modified standardized questionnaire adapted from a previous study was used to assess KAP. Differences in KAP scores were tested using the non-parametric Mann Whitney and Kruskal Wallis tests. Multivariable models were fitted for each KAP domain, as well as a multinominal logit model for “I don’t know” responses and a structural equation model. Results Among 418 participants, 79.4% had poor knowledge and only 2.4% had good knowledge. Almost 50% of the responses for each knowledge item were “I don’t know”. 50.0% had good attitudes while only 7.4% had good practice. Healthcare worker/ student status and greater self-reported gynaecological knowledge were associated with higher knowledge scores, while healthcare worker/ student status was also associated with higher practice scores. Knowledge was positively associated with attitude and practice and there was no evidence of an indirect association between knowledge and practice through attitude. Conclusion Our findings suggest that substantial gaps in adenomyosis-related knowledge and practice exist in reproductive-aged women in Lebanon, despite favourable attitudes. Disease-specific educational initiatives emphasizing symptom recognition and appropriate healthcare seeking behaviours may help bridge these gaps. Adenomyosis Health Knowledge Attitudes Practice Women Health Lebanon Survey study Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Menstruation – a physiological bodily process of adult females in reproductive years - is not uncommonly accompanied by menstrual irregularities and symptoms ranging from mild discomfort to severe pain and bleeding ( 2 ). Dysmenorrhea, defined as painful menstruation, is one of the most common gynaecological complaints among women of reproductive age with a recent 71% global prevalence estimate ( 3 ). Dysmenorrhea is classified as either primary or secondary. Primary dysmenorrhea refers to painful menstruation occurring in the absence of an identifiable pathology ( 4 ) while secondary dysmenorrhea is a consequence of an underlying pelvic pathology such as endometriosis, uterine leiomyomas, pelvic inflammatory disease, and adenomyosis ( 4 , 5 ). Although mild menstrual discomfort may be a normal part of menstruation; severe, persistent, or a progressively worsening menses pain should raise suspicion and warrant further evaluation ( 4 , 5 ). Dysmenorrhea is frequently undertreated and some women tend to normalize its symptoms or consider menstrual pain something they are expected to tolerate ( 4 ). This further contributes to delayed gynaecological-seeking and diagnosis of any underling pathologies. Among causes of secondary dysmenorrhea, uterine adenomyosis is an increasingly recognized condition. It is defined as a chronic benign gynaecological disorder characterized by the presence of endometrial glands and stroma within the myometrium ( 6 ). The exact pathogenesis is incompletely understood, with suggested mechanisms including invagination of the endometrium into the underlying myometrium and metaplastic development of endometrial tissue from embryonic remnants or stem cells ( 6 , 7 ). Historically, adenomyosis was considered predominantly a disease of middle-aged women, largely due to diagnosis being restricted to histopathological examination of hysterectomy specimens ( 6 , 8 ). However, advances in non-invasive imaging,– namely transvaginal ultrasonography and magnetic resonance imaging – have facilitated the diagnosis of adenomyosis and its recognition among younger reproductive-aged women ( 6 , 8 , 9 ). Women with adenomyosis may experience severe or progressively worsening dysmenorrhea, heavy menstrual or abnormal uterine bleeding, chronic pelvic pain, and dyspareunia ( 5 , 6 , 8 ). The condition may also have consequences beyond menstrual symptoms such as impaired fertility and adverse pregnancy outcomes ( 10 ). Furthermore, adenomyosis-related pain and abnormal bleeding can negatively affect quality of life and sexual well-being ( 5 , 11 ). Nonetheless, adenomyosis remains a challenge to recognize and diagnose. Its symptoms are heterogeneous and may overlap with those of other common gynaecological disorders, particularly endometriosis and uterine leiomyomas, that may also coexist with adenomyosis ( 6 , 8 ). Moreover, the epidemiological burden of adenomyosis remains difficult to establish, with reported prevalence varying substantially according to the population studied, diagnostic modality, and diagnostic criteria used ( 6 , 8 ). These factors, combined with the possibility that women may normalize severe menstrual pain or heavy bleeding, underscore the importance of increasing awareness to adenomyosis among women of reproductive age. In this context, assessing women's knowledge, attitudes, and practices (KAP) regarding adenomyosis provides an important insight into how the condition is understood and approached by the population. Knowledge can reflect women's understanding of adenomyosis, its symptoms, risk factors, diagnosis, and treatment, while attitudes reflect perceptions of the seriousness of the disease and the importance of seeking medical care. Practices can provide information regarding symptom recognition, healthcare-seeking behaviour, and management of symptoms. However, such studies in this context are scarce. A recent cross-sectional study among 520 Chinese reproductive-aged women found inadequate knowledge, unfavourable attitudes, and poor practices regarding uterine adenomyosis ( 12 ). To our knowledge, women's KAP regarding uterine adenomyosis have not previously been investigated in the Lebanese population. Given the substantial burden of dysmenorrhea among Lebanese women ( 13 ) and the potential for severe menstrual pain to reflect an underlying gynaecological pathology, investigating KAP surrounding adenomyosis in this population is warranted. Investigating the current level of KAP helps identify specific areas of deficiency and provides a foundation for future educational initiatives and awareness campaigns. Therefore, we sought to assess the KAP of Lebanese women regarding uterine adenomyosis and the sociodemographic, reproductive, and clinical factors associated with different levels of KAP. Methods Study Design and Procedures The cross-sectional online survey study was conducted using Google Forms. Surveys were sent via text messages and social media, and participants were encouraged to share the form with women they know. Reproductive aged women aging between 18 and 49 were included. Males, post-menopausal females, and those with limited literacy were excluded from our study, as well as participants deemed to have a logical conflict as per the knowledge questionnaire. Sample Size Using the sample size formula for estimating population proportions (alpha = 5%, 95% confidence level, n = 20000, response distribution = 50% to yield the maximum required sample size), 385 participants were required. We sought to collect at least 424 responses (n = 385 + 0.10*385) to account for non-response and possible exclusions. Questionnaire The study questionnaire was first constructed in English by referring to previous studies ( 12 , 14 ) then translated into Arabic by two bilingual translators using forward-backward translation. Participants could see both the Arabic and English text to ensure comprehension. Also, the questionnaire was reviewed by a physician specialized in obstetrics and gynaecology as well as 10 people of the target population to evaluate comprehension, and comments were addressed. The KAP instrument was adapted from Ren et al ( 12 ) and underwent some wording modifications to better suite the Lebanese population. Each KAP domain score was rescaled to range from 0-100 and represent the percentage of total possible score for comparability across KAP domains ( 15 ). The modified Bloom’s cutoffs were used to categorize KAP domains for descriptive purposes as follows: poor ( < = 59%), moderate (60–79%), and good (80–100%) ( 16 ). Each of the three KAP domains showed good to excellent internal consistency in our sample (Cronbach alpha = 0.914, 0.942, and 0.822 for knowledge, attitudes, and practice respectively). The final version of the questionnaire comprised 54 questions distributed across 5 sections: Sociodemographics : information about participants age, height, weight, nationality, governorate, educational level, average monthly income, marital status and healthcare worker/ student status. Gynaecological, reproductive, and medical characteristics : information about participants gynaecological history (menarche, average menses duration, average cycle duration), gravidity, parity, adenomyosis or other gynaecological disease diagnoses, gynaecological symptoms, and other information. Knowledge : the knowledge section comprised 12 true or false questions (K1-K12). An additional “I don’t know” (IDK) option was added to the original instrument since we anticipated lack of knowledge in our sample and wanted to mitigate random guessing ( 15 ). Participants were instructed to “Please try to answer with "I don't know" only when you truly have no knowledge of the mentioned statement and would practically be making a random guess” to ensure accuracy. Knowledge items K3 and K9 were designed to be diametrically opposite trap questions with the same meaning but opposite answers. Participants who had contradictory answers for both items were ruled to have a logical conflict and excluded. Knowledge items were scored 1 for correct answers and 0 for incorrect answers or IDK then summed into a total score 0–10. Attitudes : the attitude section consisted of 7 questions (A1-A6.1). The first five questions were scored on a five-point Likert scale ranging from “very negative” (1 point) to “very positive” (5 points) which were summed to give the raw score (5–25). Questions A6 and A6.1 were purely descriptive questions regarding the use of hysterectomy as a treatment for adenomyosis and alternative therapies and thus were not scored. Practice : the practice section involved 8 questions (P1-P8) about women’s practices surrounding adenomyosis. One question was added to the original study’s questionnaire: P4 – “You regularly attend gynaecological checkups as recommended”. P1 to P8 were scored on a five-point Likert scale ranging from “extremely non-compliant” (1 point) to “completely compliant” (5 points) for P1-P7 while P8 ranged from “never” (1 point) to “always” (5 points). Items were summed to give a total score 8–40. Ethical Considerations This study was conducted in accordance with the ethical principles laid by the declaration of Helsinki ( 1 ). Institutional Review Board (IRB) approval was obtained from Beirut Arab University and potential respondents provided informed consent before beginning the survey. Statistical Analysis Statistical analysis was conducted using Stata 19 BE. Normality of variables was evaluated using the Shapiro Wilk test, histograms, and kernel density plots. Due to non-normal distributions, non-parametric methods were used for the analysis. Descriptive statistics were reported as both mean with standard deviation and median with interquartile range for continuous variables and frequencies with percentages for factor variables. The non-parametric Mann-Whitney U and Kruskal Wallis H tests were used to determine bivariate associations of KAP domains with factor variables of 2 or more categories respectively. Spearman correlation was used to determine the associations between KAP and continuous variables. Multivariable linear regression was used to determine independent predictors of each KAP domain. The assumptions of linearity, absence of multicollinearity, normality of residuals, and homoskedasticity were evaluated thoroughly and adjustments were made to satisfy them and improve model fit. Correspondingly, heteroskedasticity robust standard errors were used in the knowledge and practice models and polynomial terms were added in the attitude model. Adjusted R 2 values were reported for each model as well as raw coefficients, standard errors, t statistics, p values, and 95% confidence intervals for each predictor. A multinominal logistic regression was also used to determine predictors of answering correctly or incorrectly with confidence compared to answering IDK with association reported as adjusted odds ratios (aOR). Furthermore, structural equational modelling (SEM) with bootstrapping (2000 repetitions) was done to evaluate the hypothesized effects of knowledge on attitude, knowledge on practice, attitude on practice, and any possible mediation. Standardized direct and indirect effect coefficients are reported. The variables height, menarche, menses, and cycle had missing values in part due to erroneous entries as well as participants being allowed to skip menstrual history questions in case they were pregnant at the time of completing the survey. Pairwise deletion was used to exclude missing values on an analysis-by-analysis basis. Statistical significance was set at a two-sided p value less than 0.05. Results Initially, 565 responses were collected. 63 participants did not belong to our target population (reproductive age adult females) and so were excluded. Also, 84 participants had conflicting answers on the diametrically opposite knowledge questions (k3 and k9) leading to their exclusion. The final sample consisted of 418 participants who were relatively young (median age = 25, IQR: 15), predominantly of Lebanese nationality (n = 391, 93.5%), single (n = 257, 61.5%), and of good socio-economic and educational status. Detailed sociodemographic and reproductive characteristics of participants are shown in Tables 1 and 2 . The distributions of knowledge, attitude, and practice scores are shown in Fig. 1 . Our study sample had overall insufficient knowledge regarding uterine adenomyosis (mean ± SD = 29.74 ± 28.74; median (IQR) = 25 (58.33)) where 79.43% (n = 332) had poor knowledge, 18.18% (n = 76) had moderate knowledge, and only 2.39% (n = 10) had good knowledge. Notably, almost all knowledge questions were answered with IDK by 50% or more of participants (Fig. 2 ), underscoring the lack of knowledge in this study sample. The top three most correct-answered knowledge questions were K11 (51%) “A healthy diet, regular exercise, and consistent follow-up can improve the condition of patients with adenomyosis”, K1 (41%) “Typical clinical manifestations of adenomyosis encompass heavy/ increased menstrual flow and painful menstrual cramps”, and K4 (39%) “Diagnostic approaches for adenomyosis include ultrasonography and magnetic resonance imaging (MRI)”. On the other hand, the most incorrectly answered were K5 (14.83%) “Therapeutic interventions for adenomyosis may involve pharmacological treatments or surgical options. Post-remission, symptoms will never recur “, K2 (12.68%) “Women of reproductive age are not the primary demographic impacted by adenomyosis “, and K12 (12.68%) “Adenomyosis does not possess cancerous transformation potential “. As for attitudes (mean ± SD = 74.55 ± 23.77, median (IQR) = 77.5 ( 20 )), 18.18% (n = 76), 31.82% (n = 133), and 50.00% (n = 209) had poor, moderate, and good attitudes respectively. Additionally, practice scores (mean ± SD = 52.08 ± 20.68, median (IQR) = 53.13 (31.25)) were also predominantly poor (n = 268, 64.11%) and moderate (n = 119, 28.47%) with only 7.42% (n = 31) scoring good practice. Item-level descriptives for KAP domains are shown in Tables 3 – 4 and Fig. 2 . Table 1 – Sociodemographic Characteristics of the Study Sample N Mean (SD) | Median (IQR) | Frequency (Percentage) 418 Age Mean (SD) 28.38 (9.03) Median (IQR) 25.00 (15.00) Body mass index (kg/m2) Mean (SD) 24.840 (4.735) Median (IQR) 23.733 (6.188) Lebanese citizen No 27 (6.5%) Yes 391 (93.5%) Governorate Akkar 6 (1.4%) Beirut 125 (29.9%) Beqaa 17 (4.1%) I do not currently live in Lebanon 12 (2.9%) Mount Lebanon 122 (29.2%) Nabatiyeh 28 (6.7%) North Lebanon 33 (7.9%) South Lebanon 75 (17.9%) Married No 257 (61.5%) Yes 161 (38.5%) Average monthly income Less than 100 $ 16 (3.8%) Between 100 $ − 299 $ 33 (7.9%) Between 300 $ − 599 $ 74 (17.7%) Between 600 $ − 899 $ 89 (21.3%) Greater than 900 $ 206 (49.3%) Educational level Primary education (elementary) 1 (0.2%) Secondary education (middle/high school) 74 (17.7%) Higher vocational school (non-university degree) 36 (8.6%) Bachelors or Master’s degree 281 (67.2%) Post-graduate education 26 (6.2%) Healthcare Worker/ Student No 292 (69.9%) Yes 126 (30.1%) Table 2 – Reproductive Characteristics of the Study Sample Age at Menarche Mean (SD) | Median (IQR) | Frequency (Percentage) Mean (SD) 12.425 (1.531) Median (IQR) 12.000 1.000 Average Menses Length (days) Mean (SD) 5.737 (2.163) Median (IQR) 6.000 2.000 Average Cycle Length (days) Mean (SD) 27.752 (4.458) Median (IQR) 28.000 4.000 Average menstrual pain severity Mean (SD) 6.323 (2.447) Median (IQR) 7.000 3.000 Gravidity Mean (SD) 1.010 (1.624) Median (IQR) 0.000 2.000 Parity Mean (SD) 0.785 (1.247) Median (IQR) 0.000 2.000 Had an abortion No 350 (83.7%) Yes 68 (16.3%) Regular cycle No 81 (19.4%) Yes 337 (80.6%) Diagnosed with adenomyosis No 405 (96.9%) Yes 13 (3.1%) Do you know anyone diagnosed with uterine adenomyosis? No one I know 375 (89.7%) Immediate family 12 (2.9%) Extended family 8 (1.9%) Friends 25 (6.0%) Diagnosed gynaecological diseases None 286 (68.4%) Polycystic ovarian syndrome 99 (23.7%) Endometriosis 12 (2.9%) Leiomyomas (uterine fibroids) 11 (2.6%) Malignant cancers (uterine, ovarian, endometrial, cervical, other…) 2 (0.5%) Ever used oral contraceptive pills No 284 (67.9%) Yes 134 (32.1%) Gynaecological symptoms Dysmenorrhea 1 153 (36.6%) Dyspareunia 25 (6.0%) Dyschezia 49 (11.7%) Pelvic heaviness 71 (17.0%) Intermenstrual bleeding 22 (5.3%) Uterine tenderness 31 (7.4%) Infertility 2 4 (1.0%) Lightest menstrual flow 3 Spotting 100 (23.9%) Light 194 (46.4%) Moderate 112 (26.8%) Heavy 12 (2.9%) Heaviest menstrual flow 3 Spotting 0 (0.0%) Light 16 (3.8%) Moderate 218 (52.2%) Heavy 184 (44.0%) Subjective knowledge of gynaecological topics Almost no knowledge 48 (11.5%) Very little knowledge 173 (41.4%) Basic knowledge 137 (32.8%) Well-versed in gynaecological topics 60 (14.4%) SD: standard deviation; IQR: interquartile range; 1 defined as “pelvic pain occurring before or after your period, unrelieved by painkillers” or “period pain that is different from typical cramps (sharp or burning)”; 2 defined as “failure to conceive after one year of frequent unprotected coitus”; 3 participants were shown an illustration to help standardize responses (Supp Fig. 1 ) The dashed lines divide the graph into the three categories poor, moderate, and good according to Bloom’s cutoffs; boxes represent the interquartile range and the white dot represents the median; wider distributions at a given value correspond to higher frequency. Dashed lines at the 50th percentile represent the median in each graph. Knowledge items K3 & K9 are diametrically opposite and were only used for screening. Attitude item A6 and A6.1 as well as practice item P8 were not plotted since their response categories differ. Table 3 – Correctness of Individual Knowledge Items Item Correctness K1: Typical clinical manifestations of adenomyosis encompass heavy/ increased menstrual flow and painful menstrual cramps. 172 (41.15%) K2: Women of reproductive age are not the primary demographic impacted by adenomyosis. 127 (30.38%) K4: Diagnostic approaches for adenomyosis include ultrasonography and magnetic resonance imaging (MRI). 165 (39.47%) K5: Therapeutic interventions for adenomyosis may involve pharmacological treatments or surgical options. Post-remission, symptoms will never recur. 109 (26.08%) K6: Pharmacological management of adenomyosis often entails the use of painkillers, oral contraceptives, and progestogens. 164 (39.23%) K7: For patients with symptomatic adenomyosis seeking definitive resolution, removal of the uterus may be considered. 134 (23.06%) K8: Adenomyosis can potentially contribute to infertility. 162 (38.76%) K10: Adenomyosis is a chronic condition necessitating long-term management strategies. 152 (36.36%) K11: A healthy diet, regular exercise, and consistent follow-up can improve the condition of patients with adenomyosis. 213 (50.96%) K12: Adenomyosis does not possess cancerous transformation potential. 94 (22.49%) Table 4 – Responses to Individual Attitude and Practice Items Attitude Items Strongly Disagree Disagree Neutral Agree Strongly Agree A1: You agree that women of childbearing age should have a basic understanding of uterine adenomyosis. 23 (5.50%) 9 (2.15%) 45 (10.77%) 156 (37.32%) 185 (44.26%) A2: You believe that uterine adenomyosis can potentially lead to serious adverse outcomes and should be taken seriously in terms of prevention and management, regardless of the diagnosis. 21 (5.02%) 11 (2.63%) 85 (20.33%) 159 (38.04%) 142 (33.97%) A3: You acknowledge that adopting a healthy lifestyle, including maintaining good sleep patterns, regular exercise, and a positive mindset, can contribute to the prevention and treatment of uterine adenomyosis. 21 (5.02%) 14 (3.35%) 69 (16.51%) 160 (38.28%) 154 (36.84%) A4: You agree that controlling body weight and reducing the number of abortions can help prevent the occurrence and development of uterine adenomyosis. 21 (5.02%) 18 (4.31%) 107 (25.60%) 169 (40.43%) 103 (24.64%) A5: It is crucial for the prevention and management of uterine adenomyosis to follow the doctor’s treatment plan, adhere to medication schedules, and attend regular check-ups as advised. 22 (5.26%) 11 (2.63%) 57 (13.64%) 137 (32.78%) 191 (45.69%) Yes No A6: You think that a total removal of the uterus is an acceptable option for curing uterine adenomyosis. 137 (32.78%) 281 (67.22%) Conservative surgery (preserving the uterus) Interventional treatment (uterine artery embolization, ablation, etc..) Not sure about the choice, prefer to follow the doctor’s recommendation A6.1: If you chose “no”, in cases where medication treatment is ineffective, you prefer what alternative treatment 78 (28.26%) 20 (7.25%) 178 (64.49%) Practice Items Extremely non-compliant Non-compliant Uncertain Compliant Completely compliant P1: In your daily life, you seek information and knowledge about the mechanisms, symptoms, and management of adenomyosis. 77 (18.42%) 139 (33.25%) 85 (20.33%) 91 (21.77%) 26 (6.22%) P2: You consciously strive to understand the treatment options for uterine adenomyosis. 75 (17.94%) 110 (26.32%) 93 (22.25%) 104 (24.88%) 36 (8.61%) P3: You engage in discussions with other women of childbearing age to share insights on adenomyosis. 74 (17.70%) 127 (30.38%) 101 (24.16%) 90 (21.53%) 26 (6.22%) P4: You regularly attend gynecological checkups as recommended. 71 (16.99%) 102 (24.40%) 69 (16.51%) 123 (29.43%) 53 (12.68%) P5: You are sensitive to detecting unusual physical symptoms in daily life, such as abnormal bleeding or pain. 35 (8.37%) 44 (10.53%) 68 (16.27%) 161 (38.52%) 110 (26.32%) P6: When experiencing unusual symptoms like menstrual pain, prolonged periods, or infertility, you take them seriously. 48 (11.48%) 61 (14.59%) 59 (14.11%) 158 (37.80%) 92 (22.01%) P7: You confide in family and friends or consult with a healthcare professional for support. 56 (13.40%) 50 (11.96%) 67 (16.03%) 158 (37.80%) 87 (20.81%) Never Occasionally Sometimes Often Always P8: You maintain a regular exercise routine in your daily life. 42 (10.05%) 83 (19.86%) 151 (36.12%) 79 (18.90%) 63 (15.07%) Knowledge Associations: Multiple linear regression of knowledge scores (Table 5 ) had good fit (aR 2 = 0.257, p < 0.001) and showed that being a healthcare worker / student (B = 10.786, p = 0.005, 95% CI: 3.285, 18.286) and self-reported "having basic gynaecological knowledge" (B = 20.335, p < 0.001, 95% CI: 11.325, 29.345) or "being well-versed in gynaecological topics" (B = 27.915, p < 0.001, 95% CI: 16.335, 39.494) were all associated with higher knowledge scores. Conversely, not personally knowing anyone diagnosed with uterine adenomyosis was associated with lower knowledge scores (B = − 12.373, p = 0.008, 95% CI: -21.456, -3.290). Furthermore, the bivariate analysis (supplementary tables 1–2) indicated higher knowledge associations for health care worker / student status, higher incomes and educational attainment, higher menstrual pain severity, dysmenorrhea, bleeding between periods, and knowing friends or immediate family with adenomyosis. Additionally, higher age, gravidity, and parity correlated negatively with knowledge. Similarly, having had an abortion and not personally knowing anyone with adenomyosis showed negative knowledge associations. The multinominal logistic model of knowledge answers (supplementary table 3) evaluated the probability that a participant would confidently choose a correct or incorrect answer rather than choosing IDK (reference category) and had a pseudo R 2 = 0.116 (p < 0.001). Being a healthcare worker/ student had greater odds of answering confidently, whether correctly (aOR = 1.926, p = 0.003, 95% CI = 1.247, 2.976) or incorrectly (aOR = 1.803, p = 0.013, 95% CI: 1.133, 2.869). The negligible difference between the reported aORs highlights the net decrease in IDK scores in healthcare workers / students with slight evidence of a knowledge advantage. Furthermore, not personally knowing people with adenomyosis was associated with significantly lower odds of answering correctly (aOR = 0.436, p = 0.004, 95% CI: 0.249, 0.763) or incorrectly (aOR = 0.384, p = 0.003, 95% CI: 0.204, 0.724) as opposed to admitting not having sufficient knowledge. Moreover, higher perceived knowledge on gynaecological topics was consistently associated with higher odds of choosing an answer rather than IDK. The odds of answering incorrectly rather than IDK is 2.75, 5.88, and 10.50 times greater for those who reported "very little knowledge", "basic knowledge", and "well versed in gynaecological topics" respectively compared to "almost no knowledge" (all p < 0.05). As for the odds of answering correctly rather than IDK, they were 1.58, 3.92, and 7.71 times greater in those who reported “very little knowledge”, "basic knowledge", and "well versed in gynaecological topics" compared to "almost no knowledge", though the first failed to reach statistical significance. This underscores a general misinformation or information-confidence mismatch where participants who self-report higher knowledge are more confident in answering in general but the relative odds that this answer is incorrect is greater than the relative odds of it being correct. Significant results from this model are represented in Fig. 3 . Table 5 – Linear Regression Model for Knowledge Age Coefficient Standard Error t statistic p-value 95% CI 0.012 0.285 0.042 0.967 -0.548, 0.572 Body mass index (kg/m2) -0.020 0.280 -0.071 0.944 -0.570, 0.530 Lebanese citizen 4.229 4.381 0.965 0.335 -4.384, 12.843 Married -6.407 4.238 -1.512 0.131 -14.738, 1.924 Average monthly income Less than 100 $ 0.000 0.000 Between 100 $ − 299 $ 0.409 8.219 0.050 0.960 -15.750, 16.567 Between 300 $ − 599 $ -0.737 7.780 -0.095 0.925 -16.032, 14.558 Between 600 $ − 899 $ 7.253 7.614 0.953 0.341 -7.717, 22.223 Greater than 900 $ 7.643 7.473 1.023 0.307 -7.049, 22.334 Educational level High school or lower 0.000 0.000 Higher vocational school (non-university degree) -8.184 5.009 -1.634 0.103 -18.033, 1.664 Bachelor's or Master's degree -3.842 3.847 -0.999 0.319 -11.404, 3.721 Post-graduate education -6.077 6.846 -0.888 0.375 -19.536, 7.382 Healthcare worker 10.786** 3.815 2.827 0.005 3.285, 18.286 Average menstrual pain severity 0.486 0.567 0.857 0.392 -0.628, 1.599 Diagnosed with adenomyosis 3.311 7.729 0.428 0.669 -11.884, 18.506 No one I personally know has been diagnosed with uterine adenomyosis -12.373** 4.620 -2.678 0.008 -21.456, -3.290 Gravidity -0.285 1.641 -0.174 0.862 -3.512, 2.941 Had an abortion -0.778 4.502 -0.173 0.863 -9.629, 8.074 Used oral contraceptive pills 3.499 3.033 1.154 0.249 -2.464, 9.462 Pelvic heaviness -0.815 3.983 -0.205 0.838 -8.646, 7.015 Bleeding between periods 1.808 5.577 0.324 0.746 -9.157, 12.773 Subjective knowledge Almost no knowledge 0.000 0.000 Very little knowledge 5.550 4.074 1.362 0.174 -2.460, 13.560 Basic knowledge 20.335*** 4.583 4.437 0.000 11.325, 29.345 Well versed 27.915*** 5.890 4.740 0.000 16.335, 39.494 Dysmenorrhea 1.136 3.015 0.377 0.707 -4.791, 7.063 Intercept 17.498 12.467 1.404 0.161 -7.013, 42.009 *** p < .001; ** p < .01, * p < 0.05 Only predictors with statistically significant results are shown Attitude: Multiple linear regression of attitude scores (Table 6 ) significantly predicted the outcome better than a null model (p = 0.012) but failed to explain much of its variance (aR 2 = 0.0226). Consequently, being a health care worker / student was the only significant predictor of higher attitude (B = 7.669, p = 0.009, 95% CI: 1.893, 13.445). Additionally, bivariate analysis only showed positive attitude associations for healthcare worker / student status, participants with immediate family members with adenomyosis, history of malignant gynaecological cancers, and longer average cycle length. Furthermore, history of abortion was associated with lower attitude scores (supplementary tables 1–2). Table 6 – Multiple Linear Regression of Predictors Associated with Attitude Age (mean centered) Coefficient Standard Error t statistic p-value 95% CI -0.570 0.377 -1.511 0.132 -1.312, 0.172 Age quadratic term -0.006 0.036 -0.157 0.875 -0.076, 0.064 Age cubic term 0.003 0.002 1.142 0.254 -0.002, 0.007 Married 6.400 4.081 1.568 0.118 -1.623, 14.422 Average monthly income Less than 100 $ 0.000 0.000 Between 100 $ − 299 $ -1.445 7.134 -0.203 0.840 -15.470, 12.580 Between 300 $ − 599 $ 2.189 6.708 0.326 0.744 -10.999, 15.376 Between 600 $ − 899 $ -1.863 6.744 -0.276 0.783 -15.122, 11.396 Greater than 900 $ 2.349 6.482 0.362 0.717 -10.395, 15.093 Educational level High school or lower 0.000 0.000 Higher vocational school (non-university degree) -0.500 5.261 -0.095 0.924 -10.843, 9.843 Bachelor's or Master's degree 5.725 3.461 1.654 0.099 -1.079, 12.529 Post-graduate education 1.399 7.003 0.200 0.842 -12.368, 15.167 Healthcare worker / student 7.669** 2.938 2.610 0.009 1.893, 13.445 Average menstrual pain severity (mean centered) -0.798 0.634 -1.260 0.209 -2.044, 0.448 Average menstrual pain quadratic term -0.461* 0.210 -2.200 0.028 -0.873, -0.049 Diagnosed with adenomyosis 9.771 6.076 1.608 0.109 -2.175, 21.717 No one I personally know has been diagnosed with uterine adenomyosis -0.573 4.567 -0.125 0.900 -9.551, 8.405 I have not been diagnosed with any other gynaecological diseases -1.408 2.541 -0.554 0.580 -6.403, 3.588 Gravidity 0.081 1.398 0.058 0.954 -2.668, 2.830 Had an abortion -4.079 4.193 -0.973 0.331 -12.322, 4.164 Pelvic heaviness 1.554 3.513 0.442 0.658 -5.352, 8.461 Uterine tenderness 4.696 4.721 0.995 0.320 -4.585, 13.977 Intercept 67.792*** 8.697 7.795 0.000 50.694, 84.890 *** p < .001; ** p < .01, * p < 0.05 Practice Associations: Multiple linear regression of practice scores (Table 7 ) – p < 0.001 aR 2 = 0.0914 – showed that being a Lebanese national (B = 11.820, p = 0.004, 95% CI: 3.780, 19.859) and having attained post-graduate education (B = 10.359, p = 0.035, 95% CI: 0.708, 20.010) were significantly associated with higher levels of practice. Furthermore, those with "heavy" lightest menstrual blood flow also had higher practice scores (B = 17.185, p = 0.009, 95% CI: 4.249, 30.121) unlike participants whose heaviest menstrual flow was "moderate" (B = -10.689, p = 0.041, 95% CI: -20.945, -0.433) or "heavy" (B = -11.835, p = 0.028, 95% CI: -22.383, -1.286). Also, intermenstrual bleeding was associated with better practice (B = 11.828, p = 0.017, 95% CI: 2.146, 21.510). These findings relating to menstrual flow prompted an exploratory rerun of the model with a composite “flow difference” variable = heaviest flow – lightest flow; assuming that the positive association of heavy lightest flow paired with the negative associations of heaviest flow indicate an underlying relationship of the difference in flow between the lightest and heaviest. As the difference between heaviest flow and lightest flow increases, practice scores decrease (B = -2.55, p = 0.041, 95% CI: -4.992, -0.104), suggesting that women who have heavier baseline (lightest) flow intensity have better practice. As for the bivariate analysis, there were no statistically significant negative predictors of practice. However, being a healthcare worker or Lebanese citizen, having higher educational attainment, having been personally diagnosed with adenomyosis or personally knowing someone who has been, and other comorbidities, symptoms, and menstrual characteristics were associated with better practice (supplementary tables 1–2). Table 7 – Multiple Linear Regression of Predictors Associated with Practice Age Coefficient Standard Error t statistic p-value 95% CI -0.026 0.174 -0.147 0.883 -0.369, 0.317 Lebanese citizen 11.820** 4.089 2.890 0.004 3.780, 19.859 Married -1.880 3.089 -0.609 0.543 -7.954, 4.193 Average monthly income Less than 100 $ 0.000 0.000 Between 100 $ − 299 $ -0.019 6.129 -0.003 0.998 -12.069, 12.032 Between 300 $ − 599 $ -4.029 5.557 -0.725 0.469 -14.955, 6.897 Between 600 $ − 899 $ -0.710 5.474 -0.130 0.897 -11.473, 10.053 Greater than 900 $ -3.624 5.252 -0.690 0.491 -13.950, 6.702 Educational level High school or lower 0.000 0.000 Higher vocational school (non-university degree) 3.205 4.194 0.764 0.445 -5.040, 11.450 Bachelor's or Master's degree 1.165 2.714 0.429 0.668 -4.170, 6.500 Post-graduate education 10.359* 4.909 2.110 0.035 0.708, 20.010 Healthcare worker / student 6.428** 2.384 2.696 0.007 1.741, 11.116 Age at menarche 0.954 0.657 1.451 0.148 -0.339, 2.246 Lightest menstrual flow Spotting 0.000 0.000 Light 1.806 2.540 0.711 0.477 -3.187, 6.800 Moderate 2.645 2.923 0.905 0.366 -3.101, 8.392 Heavy 17.185** 6.580 2.612 0.009 4.249, 30.121 Heaviest menstrual flow Light 0.000 0.000 Moderate -10.689* 5.217 -2.049 0.041 -20.945, -0.433 Heavy -11.835* 5.365 -2.206 0.028 -22.383, -1.286 Diagnosed with adenomyosis 5.863 6.728 0.871 0.384 -7.364, 19.090 No one I personally know has been diagnosed with uterine adenomyosis -4.127 3.624 -1.139 0.255 -11.253, 2.998 I have not been diagnosed with any other gynaecological diseases -0.339 2.388 -0.142 0.887 -5.033, 4.356 Used oral contraceptive pills 1.953 2.323 0.841 0.401 -2.614, 6.521 Dyspareunia 3.036 4.317 0.703 0.482 -5.451, 11.523 Dyschezia 2.445 3.283 0.745 0.457 -4.009, 8.899 Pelvic heaviness 1.223 2.830 0.432 0.666 -4.341, 6.787 Bleeding between periods 11.828* 4.924 2.402 0.017 2.146, 21.510 Dysmenorrhea -0.350 2.249 -0.156 0.876 -4.771, 4.072 Intercept 40.375** 13.018 3.101 0.002 14.780, 65.970 *** p < .001; ** p < .01, * p < 0.05 Knowledge, Attitude, and Practice: Structural equational modelling results of knowledge, attitude, and practice adjusting for age, marital status, income, educational level, and healthcare worker status are shown in Fig. 4 . standardized coefficients are shown The SEM model showed good fit: Root Mean Squared Error of Approximation (RMSEA) = 0.078 ( 0.8), Comparative Fit Index (CFI) = 0.890 (> 0.8). Knowledge had a direct effect on attitudes (Beta = 0.170, p = 0.001) and practice (Beta = 0.292, p < 0.001). Attitude had a direct negative effect on practice (Beta = -0.143, p = 0.019). Furthermore, the indirect effect of knowledge on practice through attitude failed to reach statistical significance (Beta = -0.024, p = 0.063), suggesting absence of mediation. Discussion This study assessed reproductive-aged women’s KAP towards uterine adenomyosis in Lebanon. There was a large disconnect between knowledge, attitudes and practice. Nearly four-fifths of participants lacked adenomyosis-related knowledge (79.4%), and almost two-thirds had poor practice scores (64.1%), despite comparatively more favourable attitudes, with 50% of the participants falling into the good attitude category. The knowledge deficits we found in our sample are similar to those reported in other research on adenomyosis and other gynaecological conditions. Ren et al reported insufficient knowledge of adenomyosis among Chinese reproductive-age women, with a mean score of 3.54/10, and no knowledge item exceeding 50% correctness ( 12 ). Although the scoring approaches differ between the mentioned study and ours, they both highlight that the poor knowledge regarding adenomyosis is not limited to either population. Limited gynaecological awareness has also been found locally. A KAP study on endometriosis among Lebanese women reported gaps in knowledge of the condition ( 14 ). While uterine adenomyosis and endometriosis are distinct diseases, the similarity of awareness deficit may reflect a broader gap in public knowledge of chronic gynaecological conditions in Lebanon. Part of the high percentage of participants with poor knowledge in our sample may also be due to the addition of an IDK response option to the questionnaire. While adding this option allows participants to admit the absence of knowledge/ uncertainty rather than guessing an answer they don’t truly endorse, it may decrease engagement of participants where they can choose IDK without thinking about the question at hand. However, we tried to mitigate this possibility by instructing the participants to select IDK only when picking an actual answer would be making a random guess and by implementing a logical conflict screening exclusion. Subjective knowledge – how knowledgeable participants believed themselves to be about gynaecological topics – was positively associated with their actual adenomyosis knowledge scores. As self-perceived knowledge increased, the odds of answering correctly and incorrectly increased compared to selecting IDK. However, the increase in odds relative to IDK was numerically larger for incorrect responses. This may reflect a confidence-accuracy miscalibration, where a greater confidence in knowledge was not always matched with higher accuracy. It’s important to consider the clinical aspect of this mismatch. Those who are confident in inaccurate health knowledge may be less likely to question their understanding and recognize that they need more information, which could reduce their tendencies to seek clarification and additional health information ( 17 ). Beyond self-perceived knowledge, a healthcare-related background was also associated with better knowledge about adenomyosis. Healthcare worker/ student status had a 10.8-point higher knowledge score in our sample after multivariable adjustment. However, the odds of choosing the correct answer rather than IDK were very similar to those of choosing the incorrect answer rather than IDK (1.93 vs 1.80), suggesting that a healthcare-related background may increase familiarity with the condition without consistently translating into a more superiorly accurate adenomyosis knowledge. This may indicate that knowledge gaps about uterine adenomyosis persist even among healthcare workers/ students. Similarly, previous literature findings showed persistent adenomyosis knowledge and awareness gaps among healthcare professionals ( 18 , 19 ). In addition, knowing someone with uterine adenomyosis was associated with a greater disease knowledge score, particularly among those who have an immediate family member diagnosed with this condition. Lindenmeyer et al. reported that health information is shared between family members through everyday “health talk”, which helps build an understanding of the diseases from shared experiences and medical information ( 20 ). Although the attitude scores were more favourable compared to knowledge and practice, the factors examined in this study offered little explanation for why attitude scores differed between participants (final mode adjusted R 2 = 0.0226). Hence, the variation in attitudes may be driven by factors outside of what we measured. Some of these may be societal beliefs, culture, stigma, symptom normalization, and previous healthcare experiences, as an adenomyosis scoping review highlighted their role in shaping overall women’s perceptions and experiences of the condition ( 19 ). The generally favourable attitude findings in our sample were similarly reported in the Ren et al. study, though their population exhibited higher levels of agreement on the first 5 attitude statements ( 12 ). Interestingly, the attitudes towards hysterectomy in this context were similar between the two studies, with approximately two-thirds of participants not considering total hysterectomy an acceptable option for curing uterine adenomyosis. According to Ren et al., this finding may indicate gaps in participants’ awareness of available treatment options. Adenomyosis-related practice was generally poor in our study, with 64.1% of participants showing poor practice and only 7.4% demonstrating good practice, despite approximately half of participants reporting good attitudes. This discrepancy suggests that favourable perceptions alone may not necessarily translate into appropriate health-related practices, highlighting the potential influence of broader factors that shape how women perceive, interpret, and respond to adenomyosis and its symptoms ( 19 ). In the multivariable analysis, Lebanese nationality, postgraduate education, and healthcare worker/ student status were independently associated with higher practice scores. The association with Lebanese nationality may reflect the accessibility and potentially the familiarity with the local healthcare system and the available healthcare services and information ( 21 ). Similarly, the positive relationship between postgraduate education and practice may be related with higher health literacy, as higher educational attainment may facilitate the acquisition, interpretation, and application of health information ( 22 ). The association between healthcare worker/student status and higher practice scores may reflect the practical advantage of the greater exposure to medical information and environment which could facilitate the application of knowledge and strengthen relevant clinical competencies ( 23 ). However, the presence of adenomyosis-specific knowledge gaps in this population suggests that general exposure to healthcare knowledge and clinical settings may support appropriate health practices without necessarily ensuring condition-specific knowledge. This highlights the potential value of incorporating adenomyosis-specific content into the education and training of healthcare professionals and students ( 18 ). Menstrual flow characteristics were also significantly associated with practice. The lightest menstrual flow being “heavy” was associated with higher practice scores whereas reporting “moderate” or “heavy” flow as the heaviest flow were both associated with lower practice scores. An exploratory analysis of flow difference (heaviest flow – lightest flow) showed that a greater flow difference was associated with lower practice scores (B=-2.55, P = 0.041), suggesting that greater menstrual symptom burden at severity baseline may increase attention to menstrual health and encourage care seeking ( 24 ), whereas greater variability may reflect less predictable menstrual patterns and potentially hinder consistent monitoring. The SEM findings provide further insight into the relations between knowledge, attitude and practice surrounding adenomyosis. Although knowledge showed positive direct association with both attitude and practice, there was no evidence that attitude mediated the relationship between knowledge and practice, as the indirect effect was statistically insignificant. This finding may suggest that increasing factual understanding of adenomyosis may be associated with more appropriate practices without necessarily operating through the measured attitudes, and that knowledge may influence practice through pathways independent of attitude or through other unmeasured factors. However, given the cross-sectional design, these associations could not be interpreted causally, and the model was saturated, so it merely reflected the observations in our sample. Notably, attitude exhibited a significant negative direct association with practice (B= -0.143) which is counterintuitive. A potential explanation is that more positive attitudes may not necessarily reflect greater perceived urgency to engage in practical or health protective behaviours. Alternatively, the measured attitudes may have captured the general positivity and acceptance toward adenomyosis rather than specific health protective beliefs that induce action. Thus, participants may express favourable views toward the condition while lacking the knowledge, perceived risk, or personal relevance needed to adopt corresponding practices. Despite these mechanisms being speculative, they suggest that favourable attitude alone may not be sufficient to promote appropriate health practices, emphasizing the potential importance of disease-specific knowledge and perceived relevance in shaping behaviour. The observed gap between favourable attitudes and limited practice suggests that improving adenomyosis-related outcomes may require interventions extending beyond attitude enhancement and general awareness toward improving disease and symptoms recognition and promoting appropriate health-seeking behaviours. Healthcare workers and students demonstrated comparatively better knowledge and practice in our study, however their greater likelihood to provide confident responses including incorrect answers may reflect persisting knowledge gaps, suggesting that they may represent a potential prioritized and primary target to enhance their adenomyosis-specific knowledge through strengthening disease recognition and improving awareness and knowledge on information limitations. Moreover, given that almost half or more of the participants selected IDK for most knowledge items, with almost 90% having no personal connections with anyone diagnosed with adenomyosis, underscores the need for educational opportunities regarding disease specific knowledge provided for the general population. Such education could be incorporated into gynaecological consultations, primary care and women’s health visits, menstrual health campaigns, accessible public health and social media initiatives ( 18 ). These approaches may help women recognize potentially concerning symptoms, understand abnormal or heavy bleeding and changes in menstrual patterns, and encourage appropriate and timely care seeking. A multifaceted approach combining healthcare-professional education with public awareness and interventions promoting calibrated health knowledge and confidence that focus on encouraging health action and practices may therefore be more appropriate than information provision alone. This study has several strengths. The questionnaire underwent forward-backward translation with some wording modifications to better suit the Lebanese population and demonstrated good to excellent internal consistency across all KAP domains. Furthermore, the explicit inclusion of an IDK option allowed uncertainty or lack of knowledge to be captured and minimized the bias of simply guessing correctly. Logical-conflict screening further strengthened data quality despite introducing selection bias, while the multinomial analysis distinguished confident correct and incorrect responses from IDK answers, yielding additional insight into the relationship between certainty and accuracy. Nonetheless, several limitations should be considered. The cross-sectional design precludes establishing causal relationships. Additionally, convenience and snowball sampling through messages/social media and participant sharing may have introduced selection bias and limits generalizability. Although the composite knowledge score treated IDK responses as equivalent to incorrect responses, potentially obscuring the distinction between uncertainty and misinformation, the multinomial analysis partially mitigated this limitation by examining correct, incorrect, and I don’t know responses independently. Finally, the modest explanatory power – particularly for attitude – indicates that substantial variability in KAP remains unexplained, suggesting additional determinants not captured in this study may have contributed to adenomyosis related KAP. Conclusion This study identified gaps in both adenomyosis-related knowledge and practice in light of relatively favourable attitudes. Most participants demonstrated poor knowledge and nearly two-thirds had poor adenomyosis-related practice. Healthcare worker/ student status and greater self-reported gynaecological knowledge were associated with higher knowledge, while a healthcare background was associated with more favourable practice scores. These findings support the need for accessible, disease-specific educational initiatives and interventions regarding adenomyosis, its diagnosis, symptoms, and available management options while encouraging healthcare seeking for symptomatic women. Abbreviations KAP Knowledge attitude practice Declarations Ethics approval and consent to participate This study was conducted in accordance with the ethical principles laid by the declaration of Helsinki. Ethics approval was obtained for Beirut Arab University’s Institutional Review Board. Informed consent was acquired from all respondents before filling the survey. Consent for publication Not applicable Competing interests The authors have no competing interests to declare. IDK I don't know IRB Institutional Review Board aOR adjusted Odds Ratio SEM structural equational modelling IQR interquartile range SD standard deviation aR 2 adjusted R squared CI confidence interval Funding This work did not receive any funding. Author Contribution A.Ka. was responsible for the conceptualization of the study, visualizations, and formal analysis. A.Ka. and A.S handled the study methods. A.Ka. and S.M. handled project administration and supervision. A.Ka., A.S., M.M., M.B., A.Ke., Y.A.S, A.Z., D.S., A.H., and S.C. participated in investigation, writing the original draft, and reviewing and editing the final draft. All authors read and approved the final version of the manuscript. Data Availability Data analyzed in the present study is available from the corresponding author upon reasonable request. References World Medical Association. World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Participants. JAMA. 2025;333(1):71–4. 10.1001/jama.2024.21972 . PubMed PMID: 39425955. McKenna KA, Fogleman CD, Dysmenorrhea. Am Fam Physician. 2021;104(2):164–70. PubMed PMID: 34383437. de Arruda GT, Barbosa-Silva J, Driusso P, Pathmanathan C, Armijo-Olivo S, Avila MA. Worldwide prevalence of dysmenorrhea: a systematic review and meta-analysis across 70 countries. Pain. 2026;167(1):41–55. 10.1097/j.pain.0000000000003768 . PubMed PMID: 41031966. Osayande AS, Mehulic S. 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Supplementary Files AdenomyosisSupplementary.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 25 Oct, 2026 Reviewers agreed at journal 21 Oct, 2026 Reviewers agreed at journal 20 Oct, 2026 Reviewers agreed at journal 20 Oct, 2026 Reviews received at journal 20 Oct, 2026 Reviewers agreed at journal 20 Oct, 2026 Reviewers agreed at journal 20 Oct, 2026 Reviewers agreed at journal 19 Oct, 2026 Reviewers agreed at journal 19 Oct, 2026 Reviewers invited by journal 08 Oct, 2026 Editor invited by journal 30 Sep, 2026 Editor assigned by journal 28 Sep, 2026 Submission checks completed at journal 28 Sep, 2026 First submitted to journal 24 Sep, 2026 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. 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Also discoverable on Platform About In Review Editorial Policies 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-11153706","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":740206094,"identity":"f6b87c88-b08f-4a9a-9ee1-c89d1c918743","order_by":0,"name":"Abdullah Kadhim","email":"data:image/png;base64,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","orcid":"","institution":"Beirut Arab University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Abdullah","middleName":"","lastName":"Kadhim","suffix":""},{"id":740206095,"identity":"17fb107a-015b-4463-ba3d-c30ab6873336","order_by":1,"name":"Aya Shaaban","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aya","middleName":"","lastName":"Shaaban","suffix":""},{"id":740206096,"identity":"e89b3e88-f7ac-4f89-bf29-9ac570330156","order_by":2,"name":"Mohammad Ziad Bakkar","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Ziad","lastName":"Bakkar","suffix":""},{"id":740206097,"identity":"da565bf7-d84e-4d51-8c30-69a264b7e732","order_by":3,"name":"Mariam Mghames","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mariam","middleName":"","lastName":"Mghames","suffix":""},{"id":740206099,"identity":"76bab23d-d0ef-47ee-9c2c-de53fef0fe12","order_by":4,"name":"Ali Kerdieh","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Kerdieh","suffix":""},{"id":740206101,"identity":"560b0163-35d8-40e8-b413-602cb0f600d2","order_by":5,"name":"Yolla Abou Salha","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yolla","middleName":"Abou","lastName":"Salha","suffix":""},{"id":740206103,"identity":"56d1c4ed-8f56-4e98-9328-8373f4523e68","order_by":6,"name":"Adam Zaiour","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Adam","middleName":"","lastName":"Zaiour","suffix":""},{"id":740206105,"identity":"735339a9-94f1-4d88-bdc4-320aaee51542","order_by":7,"name":"Dana Salloum","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dana","middleName":"","lastName":"Salloum","suffix":""},{"id":740206107,"identity":"2c13a4b2-fdf8-498f-bf19-f9c0473c3dc4","order_by":8,"name":"Abdelhadi Moursel","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Abdelhadi","middleName":"","lastName":"Moursel","suffix":""},{"id":740206109,"identity":"8ec62538-4bfa-4084-87b0-380f077e70d0","order_by":9,"name":"Salim Chahine","email":"","orcid":"","institution":"New Mazloum Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Salim","middleName":"","lastName":"Chahine","suffix":""},{"id":740206111,"identity":"6a4e8d20-17ef-4956-a64a-cc7a38a56c59","order_by":10,"name":"Salah Malas","email":"","orcid":"","institution":"Beirut Arab University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Salah","middleName":"","lastName":"Malas","suffix":""}],"badges":[],"createdAt":"2026-09-24 12:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-11153706/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-11153706/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":123755373,"identity":"778b8beb-97d5-4968-9d6c-ac911fc7c101","added_by":"auto","created_at":"2026-10-23 10:15:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29771,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eViolin plot of Knowledge, Attitude, and Practice Scores\u003c/strong\u003e \u003cbr\u003e\nThe dashed lines divide the graph into the three categories poor, moderate, and good according to Bloom’s cutoffs; boxes represent the interquartile range and the white dot represents the median; wider distributions at a given value correspond to higher frequency.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-11153706/v1/b4aa864cffadb9f511b4ec17.png"},{"id":123755163,"identity":"f9698e86-ddcb-4816-8da1-12c9e7eaadc0","added_by":"auto","created_at":"2026-10-23 10:14:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41639,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHorizontal Bar Chart of Percentage Responses to Each Questions for Each Domain\u003c/strong\u003e\u003cbr\u003e\nDashed lines at the 50\u003csup\u003eth\u003c/sup\u003e percentile represent the median in each graph. Knowledge items K3 \u0026amp; K9 are diametrically opposite and were only used for screening. Attitude item A6 and A6.1 as well as practice item P8 were not plotted since their response categories differ.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-11153706/v1/ac72366ed0f07585d1a2bb51.png"},{"id":123712090,"identity":"4286cbe5-3d82-4662-bc54-ada3101e8ad8","added_by":"auto","created_at":"2026-10-23 01:11:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35646,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOdds of Answering Correctly or Incorrectly vs IDK \u003c/strong\u003e\u003cbr\u003e\nOnly predictors with statistically significant results are shown\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-11153706/v1/73216a71076e2bfa512b54d8.png"},{"id":123754911,"identity":"5d149d37-7324-4b14-bc01-25dda274bb23","added_by":"auto","created_at":"2026-10-23 10:14:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":97523,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKnowledge, Attitude, and Practice Structural Equation Model\u003c/strong\u003e\u003cbr\u003e\nstandardized coefficients are shown\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-11153706/v1/2094bfaaa051a6f4ebb4d860.png"},{"id":123757776,"identity":"fe963826-3497-4ace-9911-4c90a4eae172","added_by":"auto","created_at":"2026-10-23 10:24:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":813202,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-11153706/v1/1d3f2084-58a9-4c66-b4e6-85701eacb511.pdf"},{"id":123712088,"identity":"0a43e84e-4093-4017-9126-463297267640","added_by":"auto","created_at":"2026-10-23 01:11:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":786348,"visible":true,"origin":"","legend":"","description":"","filename":"AdenomyosisSupplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-11153706/v1/8669243b374945edfb64b947.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Knowledge, Attitudes, and Practice of Women in Lebanon Surrounding Uterine Adenomyosis: A Cross-Sectional Study","fulltext":[{"header":"Background","content":"\u003cp\u003eMenstruation \u0026ndash; a physiological bodily process of adult females in reproductive years - is not uncommonly accompanied by menstrual irregularities and symptoms ranging from mild discomfort to severe pain and bleeding (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Dysmenorrhea, defined as painful menstruation, is one of the most common gynaecological complaints among women of reproductive age with a recent 71% global prevalence estimate (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Dysmenorrhea is classified as either primary or secondary. Primary dysmenorrhea refers to painful menstruation occurring in the absence of an identifiable pathology (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) while secondary dysmenorrhea is a consequence of an underlying pelvic pathology such as endometriosis, uterine leiomyomas, pelvic inflammatory disease, and adenomyosis (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Although mild menstrual discomfort may be a normal part of menstruation; severe, persistent, or a progressively worsening menses pain should raise suspicion and warrant further evaluation (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Dysmenorrhea is frequently undertreated and some women tend to normalize its symptoms or consider menstrual pain something they are expected to tolerate (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This further contributes to delayed gynaecological-seeking and diagnosis of any underling pathologies.\u003c/p\u003e \u003cp\u003eAmong causes of secondary dysmenorrhea, uterine adenomyosis is an increasingly recognized condition. It is defined as a chronic benign gynaecological disorder characterized by the presence of endometrial glands and stroma within the myometrium (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The exact pathogenesis is incompletely understood, with suggested mechanisms including invagination of the endometrium into the underlying myometrium and metaplastic development of endometrial tissue from embryonic remnants or stem cells (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Historically, adenomyosis was considered predominantly a disease of middle-aged women, largely due to diagnosis being restricted to histopathological examination of hysterectomy specimens (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, advances in non-invasive imaging,\u0026ndash; namely transvaginal ultrasonography and magnetic resonance imaging \u0026ndash; have facilitated the diagnosis of adenomyosis and its recognition among younger reproductive-aged women (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWomen with adenomyosis may experience severe or progressively worsening dysmenorrhea, heavy menstrual or abnormal uterine bleeding, chronic pelvic pain, and dyspareunia (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The condition may also have consequences beyond menstrual symptoms such as impaired fertility and adverse pregnancy outcomes (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Furthermore, adenomyosis-related pain and abnormal bleeding can negatively affect quality of life and sexual well-being (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Nonetheless, adenomyosis remains a challenge to recognize and diagnose. Its symptoms are heterogeneous and may overlap with those of other common gynaecological disorders, particularly endometriosis and uterine leiomyomas, that may also coexist with adenomyosis (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Moreover, the epidemiological burden of adenomyosis remains difficult to establish, with reported prevalence varying substantially according to the population studied, diagnostic modality, and diagnostic criteria used (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). These factors, combined with the possibility that women may normalize severe menstrual pain or heavy bleeding, underscore the importance of increasing awareness to adenomyosis among women of reproductive age.\u003c/p\u003e \u003cp\u003eIn this context, assessing women's knowledge, attitudes, and practices (KAP) regarding adenomyosis provides an important insight into how the condition is understood and approached by the population. Knowledge can reflect women's understanding of adenomyosis, its symptoms, risk factors, diagnosis, and treatment, while attitudes reflect perceptions of the seriousness of the disease and the importance of seeking medical care. Practices can provide information regarding symptom recognition, healthcare-seeking behaviour, and management of symptoms. However, such studies in this context are scarce. A recent cross-sectional study among 520 Chinese reproductive-aged women found inadequate knowledge, unfavourable attitudes, and poor practices regarding uterine adenomyosis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo our knowledge, women's KAP regarding uterine adenomyosis have not previously been investigated in the Lebanese population. Given the substantial burden of dysmenorrhea among Lebanese women (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and the potential for severe menstrual pain to reflect an underlying gynaecological pathology, investigating KAP surrounding adenomyosis in this population is warranted. Investigating the current level of KAP helps identify specific areas of deficiency and provides a foundation for future educational initiatives and awareness campaigns. Therefore, we sought to assess the KAP of Lebanese women regarding uterine adenomyosis and the sociodemographic, reproductive, and clinical factors associated with different levels of KAP.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Procedures\u003c/h2\u003e \u003cp\u003eThe cross-sectional online survey study was conducted using Google Forms. Surveys were sent via text messages and social media, and participants were encouraged to share the form with women they know. Reproductive aged women aging between 18 and 49 were included. Males, post-menopausal females, and those with limited literacy were excluded from our study, as well as participants deemed to have a logical conflict as per the knowledge questionnaire.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample Size\u003c/h3\u003e\n\u003cp\u003eUsing the sample size formula for estimating population proportions (alpha\u0026thinsp;=\u0026thinsp;5%, 95% confidence level, n\u0026thinsp;=\u0026thinsp;20000, response distribution\u0026thinsp;=\u0026thinsp;50% to yield the maximum required sample size), 385 participants were required. We sought to collect at least 424 responses (n\u0026thinsp;=\u0026thinsp;385\u0026thinsp;+\u0026thinsp;0.10*385) to account for non-response and possible exclusions.\u003c/p\u003e\n\u003ch3\u003eQuestionnaire\u003c/h3\u003e\n\u003cp\u003eThe study questionnaire was first constructed in English by referring to previous studies (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) then translated into Arabic by two bilingual translators using forward-backward translation. Participants could see both the Arabic and English text to ensure comprehension. Also, the questionnaire was reviewed by a physician specialized in obstetrics and gynaecology as well as 10 people of the target population to evaluate comprehension, and comments were addressed.\u003c/p\u003e \u003cp\u003eThe KAP instrument was adapted from Ren et al (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) and underwent some wording modifications to better suite the Lebanese population. Each KAP domain score was rescaled to range from 0-100 and represent the percentage of total possible score for comparability across KAP domains (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The modified Bloom\u0026rsquo;s cutoffs were used to categorize KAP domains for descriptive purposes as follows: poor (\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;59%), moderate (60\u0026ndash;79%), and good (80\u0026ndash;100%) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Each of the three KAP domains showed good to excellent internal consistency in our sample (Cronbach alpha\u0026thinsp;=\u0026thinsp;0.914, 0.942, and 0.822 for knowledge, attitudes, and practice respectively). The final version of the questionnaire comprised 54 questions distributed across 5 sections:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eSociodemographics\u003c/em\u003e: information about participants age, height, weight, nationality, governorate, educational level, average monthly income, marital status and healthcare worker/ student status.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eGynaecological, reproductive, and medical characteristics\u003c/em\u003e: information about participants gynaecological history (menarche, average menses duration, average cycle duration), gravidity, parity, adenomyosis or other gynaecological disease diagnoses, gynaecological symptoms, and other information.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eKnowledge\u003c/em\u003e: the knowledge section comprised 12 true or false questions (K1-K12). An additional \u0026ldquo;I don\u0026rsquo;t know\u0026rdquo; (IDK) option was added to the original instrument since we anticipated lack of knowledge in our sample and wanted to mitigate random guessing (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Participants were instructed to \u0026ldquo;Please try to answer with \"I don't know\" only when you truly have no knowledge of the mentioned statement and would practically be making a random guess\u0026rdquo; to ensure accuracy. Knowledge items K3 and K9 were designed to be diametrically opposite trap questions with the same meaning but opposite answers. Participants who had contradictory answers for both items were ruled to have a logical conflict and excluded. Knowledge items were scored 1 for correct answers and 0 for incorrect answers or IDK then summed into a total score 0\u0026ndash;10.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eAttitudes\u003c/em\u003e: the attitude section consisted of 7 questions (A1-A6.1). The first five questions were scored on a five-point Likert scale ranging from \u0026ldquo;very negative\u0026rdquo; (1 point) to \u0026ldquo;very positive\u0026rdquo; (5 points) which were summed to give the raw score (5\u0026ndash;25). Questions A6 and A6.1 were purely descriptive questions regarding the use of hysterectomy as a treatment for adenomyosis and alternative therapies and thus were not scored.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003ePractice\u003c/em\u003e: the practice section involved 8 questions (P1-P8) about women\u0026rsquo;s practices surrounding adenomyosis. One question was added to the original study\u0026rsquo;s questionnaire: P4 \u0026ndash; \u0026ldquo;You regularly attend gynaecological checkups as recommended\u0026rdquo;. P1 to P8 were scored on a five-point Likert scale ranging from \u0026ldquo;extremely non-compliant\u0026rdquo; (1 point) to \u0026ldquo;completely compliant\u0026rdquo; (5 points) for P1-P7 while P8 ranged from \u0026ldquo;never\u0026rdquo; (1 point) to \u0026ldquo;always\u0026rdquo; (5 points). Items were summed to give a total score 8\u0026ndash;40.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical principles laid by the declaration of Helsinki (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Institutional Review Board (IRB) approval was obtained from Beirut Arab University and potential respondents provided informed consent before beginning the survey.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was conducted using Stata 19 BE. Normality of variables was evaluated using the Shapiro Wilk test, histograms, and kernel density plots. Due to non-normal distributions, non-parametric methods were used for the analysis. Descriptive statistics were reported as both mean with standard deviation and median with interquartile range for continuous variables and frequencies with percentages for factor variables. The non-parametric Mann-Whitney U and Kruskal Wallis H tests were used to determine bivariate associations of KAP domains with factor variables of 2 or more categories respectively. Spearman correlation was used to determine the associations between KAP and continuous variables.\u003c/p\u003e \u003cp\u003eMultivariable linear regression was used to determine independent predictors of each KAP domain. The assumptions of linearity, absence of multicollinearity, normality of residuals, and homoskedasticity were evaluated thoroughly and adjustments were made to satisfy them and improve model fit. Correspondingly, heteroskedasticity robust standard errors were used in the knowledge and practice models and polynomial terms were added in the attitude model. Adjusted R\u003csup\u003e2\u003c/sup\u003e values were reported for each model as well as raw coefficients, standard errors, t statistics, p values, and 95% confidence intervals for each predictor. A multinominal logistic regression was also used to determine predictors of answering correctly or incorrectly with confidence compared to answering IDK with association reported as adjusted odds ratios (aOR). Furthermore, structural equational modelling (SEM) with bootstrapping (2000 repetitions) was done to evaluate the hypothesized effects of knowledge on attitude, knowledge on practice, attitude on practice, and any possible mediation. Standardized direct and indirect effect coefficients are reported.\u003c/p\u003e \u003cp\u003eThe variables height, menarche, menses, and cycle had missing values in part due to erroneous entries as well as participants being allowed to skip menstrual history questions in case they were pregnant at the time of completing the survey. Pairwise deletion was used to exclude missing values on an analysis-by-analysis basis. Statistical significance was set at a two-sided p value less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eInitially, 565 responses were collected. 63 participants did not belong to our target population (reproductive age adult females) and so were excluded. Also, 84 participants had conflicting answers on the diametrically opposite knowledge questions (k3 and k9) leading to their exclusion. The final sample consisted of 418 participants who were relatively young (median age\u0026thinsp;=\u0026thinsp;25, IQR: 15), predominantly of Lebanese nationality (n\u0026thinsp;=\u0026thinsp;391, 93.5%), single (n\u0026thinsp;=\u0026thinsp;257, 61.5%), and of good socio-economic and educational status. Detailed sociodemographic and reproductive characteristics of participants are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe distributions of knowledge, attitude, and practice scores are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Our study sample had overall insufficient knowledge regarding uterine adenomyosis (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;29.74\u0026thinsp;\u0026plusmn;\u0026thinsp;28.74; median (IQR)\u0026thinsp;=\u0026thinsp;25 (58.33)) where 79.43% (n\u0026thinsp;=\u0026thinsp;332) had poor knowledge, 18.18% (n\u0026thinsp;=\u0026thinsp;76) had moderate knowledge, and only 2.39% (n\u0026thinsp;=\u0026thinsp;10) had good knowledge. Notably, almost all knowledge questions were answered with IDK by 50% or more of participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), underscoring the lack of knowledge in this study sample. The top three most correct-answered knowledge questions were K11 (51%) \u0026ldquo;A healthy diet, regular exercise, and consistent follow-up can improve the condition of patients with adenomyosis\u0026rdquo;, K1 (41%) \u0026ldquo;Typical clinical manifestations of adenomyosis encompass heavy/ increased menstrual flow and painful menstrual cramps\u0026rdquo;, and K4 (39%) \u0026ldquo;Diagnostic approaches for adenomyosis include ultrasonography and magnetic resonance imaging (MRI)\u0026rdquo;. On the other hand, the most incorrectly answered were K5 (14.83%) \u0026ldquo;Therapeutic interventions for adenomyosis may involve pharmacological treatments or surgical options. Post-remission, symptoms will never recur \u0026ldquo;, K2 (12.68%) \u0026ldquo;Women of reproductive age are not the primary demographic impacted by adenomyosis \u0026ldquo;, and K12 (12.68%) \u0026ldquo;Adenomyosis does not possess cancerous transformation potential \u0026ldquo;. As for attitudes (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;74.55\u0026thinsp;\u0026plusmn;\u0026thinsp;23.77, median (IQR)\u0026thinsp;=\u0026thinsp;77.5 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)), 18.18% (n\u0026thinsp;=\u0026thinsp;76), 31.82% (n\u0026thinsp;=\u0026thinsp;133), and 50.00% (n\u0026thinsp;=\u0026thinsp;209) had poor, moderate, and good attitudes respectively. Additionally, practice scores (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;52.08\u0026thinsp;\u0026plusmn;\u0026thinsp;20.68, median (IQR)\u0026thinsp;=\u0026thinsp;53.13 (31.25)) were also predominantly poor (n\u0026thinsp;=\u0026thinsp;268, 64.11%) and moderate (n\u0026thinsp;=\u0026thinsp;119, 28.47%) with only 7.42% (n\u0026thinsp;=\u0026thinsp;31) scoring good practice. Item-level descriptives for KAP domains are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\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\u003e\u0026ndash; Sociodemographic Characteristics of the Study Sample\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD) | Median (IQR) | \u003c/p\u003e \u003cp\u003eFrequency (Percentage)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e418\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=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.38 (9.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.00 (15.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\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\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.840 (4.735)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.733 (6.188)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLebanese citizen\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e391 (93.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernorate\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\u003eAkkar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeirut\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125 (29.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeqaa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI do not currently live in Lebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMount Lebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNabatiyeh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Lebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Lebanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e257 (61.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage monthly income\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\u003eLess than 100\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 100\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;299\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 300\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;599\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 600\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;899\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater than 900\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e206 (49.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\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\u003ePrimary education (elementary)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary education (middle/high school)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher vocational school (non-university degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelors or Master\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e281 (67.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-graduate education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare Worker/ Student\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e292 (69.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126 (30.1%)\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=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Reproductive Characteristics of the Study Sample\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge at Menarche\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD) | Median (IQR) | \u003c/p\u003e \u003cp\u003eFrequency (Percentage)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.425 (1.531)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.000 1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Menses Length (days)\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\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.737 (2.163)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.000 2.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Cycle Length (days)\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\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.752 (4.458)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.000 4.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage menstrual pain severity\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\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.323 (2.447)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.000 3.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGravidity\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\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.010 (1.624)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000 2.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity\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\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.785 (1.247)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000 2.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad an abortion\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e350 (83.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular cycle\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e337 (80.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed with adenomyosis\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e405 (96.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you know anyone diagnosed with uterine adenomyosis?\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\u003eNo one I know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e375 (89.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmediate family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtended family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriends\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed gynaecological diseases\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\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e286 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolycystic ovarian syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometriosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeiomyomas (uterine fibroids)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignant cancers (uterine, ovarian, endometrial, cervical, other\u0026hellip;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver used oral contraceptive pills\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e284 (67.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e134 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynaecological symptoms\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\u003eDysmenorrhea \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e153 (36.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspareunia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyschezia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePelvic heaviness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermenstrual bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterine tenderness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfertility \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLightest menstrual flow \u003csup\u003e3\u003c/sup\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\u003eSpotting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (23.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e194 (46.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeaviest menstrual flow \u003csup\u003e3\u003c/sup\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\u003eSpotting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e218 (52.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184 (44.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective knowledge of gynaecological topics\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\u003eAlmost no knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery little knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e173 (41.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137 (32.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell-versed in gynaecological topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSD: standard deviation; IQR: interquartile range; \u003csup\u003e1\u003c/sup\u003e defined as \u0026ldquo;pelvic pain occurring before or after your period, unrelieved by painkillers\u0026rdquo; or \u0026ldquo;period pain that is different from typical cramps (sharp or burning)\u0026rdquo;; \u003csup\u003e2\u003c/sup\u003e defined as \u0026ldquo;failure to conceive after one year of frequent unprotected coitus\u0026rdquo;; \u003csup\u003e3\u003c/sup\u003e participants were shown an illustration to help standardize responses (Supp Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe dashed lines divide the graph into the three categories poor, moderate, and good according to Bloom\u0026rsquo;s cutoffs; boxes represent the interquartile range and the white dot represents the median; wider distributions at a given value correspond to higher frequency.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDashed lines at the 50th percentile represent the median in each graph. Knowledge items K3 \u0026amp; K9 are diametrically opposite and were only used for screening. Attitude item A6 and A6.1 as well as practice item P8 were not plotted since their response categories differ.\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\u003e\u0026ndash; Correctness of Individual Knowledge Items\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrectness\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK1: Typical clinical manifestations of adenomyosis encompass heavy/ increased menstrual flow and painful menstrual cramps.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172 (41.15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2: Women of reproductive age are not the primary demographic impacted by adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127 (30.38%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK4: Diagnostic approaches for adenomyosis include ultrasonography and magnetic resonance imaging (MRI).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e165 (39.47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK5: Therapeutic interventions for adenomyosis may involve pharmacological treatments or surgical options. Post-remission, symptoms will never recur.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e109 (26.08%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK6: Pharmacological management of adenomyosis often entails the use of painkillers, oral contraceptives, and progestogens.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e164 (39.23%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK7: For patients with symptomatic adenomyosis seeking definitive resolution, removal of the uterus may be considered.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e134 (23.06%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK8: Adenomyosis can potentially contribute to infertility.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162 (38.76%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK10: Adenomyosis is a chronic condition necessitating long-term management strategies.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e152 (36.36%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK11: A healthy diet, regular exercise, and consistent follow-up can improve the condition of patients with adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e213 (50.96%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK12: Adenomyosis does not possess cancerous transformation potential.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94 (22.49%)\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\u003e\u0026ndash; Responses to Individual Attitude and Practice Items\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAttitude Items\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Disagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStrongly Agree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1: You agree that women of childbearing age should have a basic understanding of uterine adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (5.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (2.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e45 (10.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e156 (37.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e185 (44.26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA2: You believe that uterine adenomyosis can potentially lead to serious adverse outcomes and should be taken seriously in terms of prevention and management, regardless of the diagnosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (5.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (2.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e85 (20.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e159 (38.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e142 (33.97%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA3: You acknowledge that adopting a healthy lifestyle, including maintaining good sleep patterns, regular exercise, and a positive mindset, can contribute to the prevention and treatment of uterine adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (5.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (3.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e69 (16.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e160 (38.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e154 (36.84%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA4: You agree that controlling body weight and reducing the number of abortions can help prevent the occurrence and development of uterine adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (5.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (4.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e107 (25.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e169 (40.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103 (24.64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA5: It is crucial for the prevention and management of uterine adenomyosis to follow the doctor\u0026rsquo;s treatment plan, adhere to medication schedules, and attend regular check-ups as advised.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (5.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (2.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e57 (13.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e137 (32.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e191 (45.69%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA6: You think that a total removal of the uterus is an acceptable option for curing uterine adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e137 (32.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e281 (67.22%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eConservative surgery (preserving the uterus)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eInterventional treatment (uterine artery embolization, ablation, etc..)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eNot sure about the choice, prefer to follow the doctor\u0026rsquo;s recommendation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA6.1: If you chose \u0026ldquo;no\u0026rdquo;, in cases where medication treatment is ineffective, you prefer what alternative treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e78 (28.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e20 (7.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e178 (64.49%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePractice Items\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExtremely non-compliant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-compliant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eUncertain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCompliant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCompletely compliant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1: In your daily life, you seek information and knowledge about the mechanisms, symptoms, and management of adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (18.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139 (33.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e85 (20.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91 (21.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26 (6.22%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2: You consciously strive to understand the treatment options for uterine adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (17.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (26.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e93 (22.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e104 (24.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36 (8.61%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3: You engage in discussions with other women of childbearing age to share insights on adenomyosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (17.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127 (30.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e101 (24.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90 (21.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26 (6.22%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP4: You regularly attend gynecological checkups as recommended.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (16.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (24.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e69 (16.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e123 (29.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53 (12.68%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP5: You are sensitive to detecting unusual physical symptoms in daily life, such as abnormal bleeding or pain.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (8.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (10.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e68 (16.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e161 (38.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e110 (26.32%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP6: When experiencing unusual symptoms like menstrual pain, prolonged periods, or infertility, you take them seriously.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (11.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (14.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e59 (14.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e158 (37.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92 (22.01%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP7: You confide in family and friends or consult with a healthcare professional for support.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (13.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (11.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e67 (16.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e158 (37.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87 (20.81%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOften\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAlways\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP8: You maintain a regular exercise routine in your daily life.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (10.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (19.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e151 (36.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79 (18.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63 (15.07%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eKnowledge Associations:\u003c/h3\u003e\n\u003cp\u003eMultiple linear regression of knowledge scores (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) had good fit (aR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.257, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and showed that being a healthcare worker / student (B\u0026thinsp;=\u0026thinsp;10.786, p\u0026thinsp;=\u0026thinsp;0.005, 95% CI: 3.285, 18.286) and self-reported \"having basic gynaecological knowledge\" (B\u0026thinsp;=\u0026thinsp;20.335, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI: 11.325, 29.345) or \"being well-versed in gynaecological topics\" (B\u0026thinsp;=\u0026thinsp;27.915, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI: 16.335, 39.494) were all associated with higher knowledge scores. Conversely, not personally knowing anyone diagnosed with uterine adenomyosis was associated with lower knowledge scores (B\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;12.373, p\u0026thinsp;=\u0026thinsp;0.008, 95% CI: -21.456, -3.290). Furthermore, the bivariate analysis (supplementary tables 1\u0026ndash;2) indicated higher knowledge associations for health care worker / student status, higher incomes and educational attainment, higher menstrual pain severity, dysmenorrhea, bleeding between periods, and knowing friends or immediate family with adenomyosis. Additionally, higher age, gravidity, and parity correlated negatively with knowledge. Similarly, having had an abortion and not personally knowing anyone with adenomyosis showed negative knowledge associations.\u003c/p\u003e \u003cp\u003eThe multinominal logistic model of knowledge answers (supplementary table 3) evaluated the probability that a participant would confidently choose a correct or incorrect answer rather than choosing IDK (reference category) and had a pseudo R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.116 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Being a healthcare worker/ student had greater odds of answering confidently, whether correctly (aOR\u0026thinsp;=\u0026thinsp;1.926, p\u0026thinsp;=\u0026thinsp;0.003, 95% CI\u0026thinsp;=\u0026thinsp;1.247, 2.976) or incorrectly (aOR\u0026thinsp;=\u0026thinsp;1.803, p\u0026thinsp;=\u0026thinsp;0.013, 95% CI: 1.133, 2.869). The negligible difference between the reported aORs highlights the net decrease in IDK scores in healthcare workers / students with slight evidence of a knowledge advantage. Furthermore, not personally knowing people with adenomyosis was associated with significantly lower odds of answering correctly (aOR\u0026thinsp;=\u0026thinsp;0.436, p\u0026thinsp;=\u0026thinsp;0.004, 95% CI: 0.249, 0.763) or incorrectly (aOR\u0026thinsp;=\u0026thinsp;0.384, p\u0026thinsp;=\u0026thinsp;0.003, 95% CI: 0.204, 0.724) as opposed to admitting not having sufficient knowledge. Moreover, higher perceived knowledge on gynaecological topics was consistently associated with higher odds of choosing an answer rather than IDK. The odds of answering incorrectly rather than IDK is 2.75, 5.88, and 10.50 times greater for those who reported \"very little knowledge\", \"basic knowledge\", and \"well versed in gynaecological topics\" respectively compared to \"almost no knowledge\" (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). As for the odds of answering correctly rather than IDK, they were 1.58, 3.92, and 7.71 times greater in those who reported \u0026ldquo;very little knowledge\u0026rdquo;, \"basic knowledge\", and \"well versed in gynaecological topics\" compared to \"almost no knowledge\", though the first failed to reach statistical significance. This underscores a general misinformation or information-confidence mismatch where participants who self-report higher knowledge are more confident in answering in general but the relative odds that this answer is incorrect is greater than the relative odds of it being correct. Significant results from this model are represented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\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\u003e\u0026ndash; Linear Regression Model for Knowledge\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=\"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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et statistic\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\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.548, 0.572\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.570, 0.530\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLebanese citizen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.384, 12.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-14.738, 1.924\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage monthly income\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 100\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 100\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;299\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-15.750, 16.567\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 300\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;599\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-16.032, 14.558\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 600\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;899\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.717, 22.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater than 900\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.049, 22.334\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher vocational school (non-university degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-8.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-18.033, 1.664\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's or Master's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-11.404, 3.721\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-graduate education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-19.536, 7.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare worker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.786**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.285, 18.286\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage menstrual pain severity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.628, 1.599\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed with adenomyosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-11.884, 18.506\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo one I personally know has been diagnosed with uterine adenomyosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-12.373**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-21.456, -3.290\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGravidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.512, 2.941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad an abortion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-9.629, 8.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUsed oral contraceptive pills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.464, 9.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePelvic heaviness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-8.646, 7.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding between periods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-9.157, 12.773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective knowledge\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlmost no knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery little knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.460, 13.560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.335***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.325, 29.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell versed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.915***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.335, 39.494\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDysmenorrhea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.791, 7.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.013, 42.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*** p \u0026lt; .001; ** p \u0026lt; .01, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOnly predictors with statistically significant results are shown\u003c/p\u003e\n\u003ch3\u003eAttitude:\u003c/h3\u003e\n\u003cp\u003eMultiple linear regression of attitude scores (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) significantly predicted the outcome better than a null model (p\u0026thinsp;=\u0026thinsp;0.012) but failed to explain much of its variance (aR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0226). Consequently, being a health care worker / student was the only significant predictor of higher attitude (B\u0026thinsp;=\u0026thinsp;7.669, p\u0026thinsp;=\u0026thinsp;0.009, 95% CI: 1.893, 13.445). Additionally, bivariate analysis only showed positive attitude associations for healthcare worker / student status, participants with immediate family members with adenomyosis, history of malignant gynaecological cancers, and longer average cycle length. Furthermore, history of abortion was associated with lower attitude scores (supplementary tables 1\u0026ndash;2).\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\u003e\u0026ndash; Multiple Linear Regression of Predictors Associated with Attitude\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=\"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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (mean centered)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et statistic\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\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.570\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.511\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.312, 0.172\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge quadratic term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.076, 0.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge cubic term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.002, 0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.623, 14.422\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage monthly income\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 100\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 100\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;299\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-15.470, 12.580\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 300\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;599\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10.999, 15.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 600\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;899\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-15.122, 11.396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater than 900\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10.395, 15.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher vocational school (non-university degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10.843, 9.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's or Master's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.079, 12.529\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-graduate education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-12.368, 15.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare worker / student\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.669**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.893, 13.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage menstrual pain severity (mean centered)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.044, 0.448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage menstrual pain quadratic term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.461*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.873, -0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed with adenomyosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.175, 21.717\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo one I personally know has been diagnosed with uterine adenomyosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-9.551, 8.405\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI have not been diagnosed with any other gynaecological diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6.403, 3.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGravidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.668, 2.830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad an abortion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-12.322, 4.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePelvic heaviness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.352, 8.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterine tenderness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.585, 13.977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.792***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.694, 84.890\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*** p \u0026lt; .001; ** p \u0026lt; .01, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePractice Associations:\u003c/h2\u003e \u003cp\u003eMultiple linear regression of practice scores (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) \u0026ndash; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 aR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0914 \u0026ndash; showed that being a Lebanese national (B\u0026thinsp;=\u0026thinsp;11.820, p\u0026thinsp;=\u0026thinsp;0.004, 95% CI: 3.780, 19.859) and having attained post-graduate education (B\u0026thinsp;=\u0026thinsp;10.359, p\u0026thinsp;=\u0026thinsp;0.035, 95% CI: 0.708, 20.010) were significantly associated with higher levels of practice. Furthermore, those with \"heavy\" lightest menstrual blood flow also had higher practice scores (B\u0026thinsp;=\u0026thinsp;17.185, p\u0026thinsp;=\u0026thinsp;0.009, 95% CI: 4.249, 30.121) unlike participants whose heaviest menstrual flow was \"moderate\" (B = -10.689, p\u0026thinsp;=\u0026thinsp;0.041, 95% CI: -20.945, -0.433) or \"heavy\" (B = -11.835, p\u0026thinsp;=\u0026thinsp;0.028, 95% CI: -22.383, -1.286). Also, intermenstrual bleeding was associated with better practice (B\u0026thinsp;=\u0026thinsp;11.828, p\u0026thinsp;=\u0026thinsp;0.017, 95% CI: 2.146, 21.510). These findings relating to menstrual flow prompted an exploratory rerun of the model with a composite \u0026ldquo;flow difference\u0026rdquo; variable\u0026thinsp;=\u0026thinsp;heaviest flow \u0026ndash; lightest flow; assuming that the positive association of heavy lightest flow paired with the negative associations of heaviest flow indicate an underlying relationship of the difference in flow between the lightest and heaviest. As the difference between heaviest flow and lightest flow increases, practice scores decrease (B = -2.55, p\u0026thinsp;=\u0026thinsp;0.041, 95% CI: -4.992, -0.104), suggesting that women who have heavier baseline (lightest) flow intensity have better practice. As for the bivariate analysis, there were no statistically significant negative predictors of practice. However, being a healthcare worker or Lebanese citizen, having higher educational attainment, having been personally diagnosed with adenomyosis or personally knowing someone who has been, and other comorbidities, symptoms, and menstrual characteristics were associated with better practice (supplementary tables 1\u0026ndash;2).\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\u003e\u0026ndash; Multiple Linear Regression of Predictors Associated with Practice\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=\"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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et statistic\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\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.026\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.147\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.369, 0.317\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLebanese citizen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.820**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.780, 19.859\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.954, 4.193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage monthly income\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 100\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 100\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;299\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-12.069, 12.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 300\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;599\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-14.955, 6.897\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetween 600\u003cspan\u003e$\u003c/span\u003e \u0026minus;\u0026thinsp;899\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-11.473, 10.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater than 900\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-13.950, 6.702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher vocational school (non-university degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.040, 11.450\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's or Master's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.170, 6.500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-graduate education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.359*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.708, 20.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare worker / student\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.428**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.741, 11.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at menarche\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.339, 2.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLightest menstrual flow\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpotting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.187, 6.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.101, 8.392\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.185**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.249, 30.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeaviest menstrual flow\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-10.689*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-20.945, -0.433\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-11.835*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-22.383, -1.286\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosed with adenomyosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7.364, 19.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo one I personally know has been diagnosed with uterine adenomyosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-11.253, 2.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI have not been diagnosed with any other gynaecological diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.033, 4.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUsed oral contraceptive pills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.614, 6.521\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspareunia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.451, 11.523\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyschezia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.009, 8.899\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePelvic heaviness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.341, 6.787\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding between periods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.828*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.146, 21.510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDysmenorrhea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.771, 4.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.375**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.780, 65.970\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*** p \u0026lt; .001; ** p \u0026lt; .01, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eKnowledge, Attitude, and Practice:\u003c/h2\u003e \u003cp\u003eStructural equational modelling results of knowledge, attitude, and practice adjusting for age, marital status, income, educational level, and healthcare worker status are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003estandardized coefficients are shown\u003c/p\u003e \u003cp\u003eThe SEM model showed good fit: Root Mean Squared Error of Approximation (RMSEA)\u0026thinsp;=\u0026thinsp;0.078 (\u0026lt;\u0026thinsp;0.08), Tucker-Lewis Index (TLI)\u0026thinsp;=\u0026thinsp;0.877 (\u0026gt;\u0026thinsp;0.8), Comparative Fit Index (CFI)\u0026thinsp;=\u0026thinsp;0.890 (\u0026gt;\u0026thinsp;0.8). Knowledge had a direct effect on attitudes (Beta\u0026thinsp;=\u0026thinsp;0.170, p\u0026thinsp;=\u0026thinsp;0.001) and practice (Beta\u0026thinsp;=\u0026thinsp;0.292, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Attitude had a direct negative effect on practice (Beta = -0.143, p\u0026thinsp;=\u0026thinsp;0.019). Furthermore, the indirect effect of knowledge on practice through attitude failed to reach statistical significance (Beta = -0.024, p\u0026thinsp;=\u0026thinsp;0.063), suggesting absence of mediation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed reproductive-aged women\u0026rsquo;s KAP towards uterine adenomyosis in Lebanon. There was a large disconnect between knowledge, attitudes and practice. Nearly four-fifths of participants lacked adenomyosis-related knowledge (79.4%), and almost two-thirds had poor practice scores (64.1%), despite comparatively more favourable attitudes, with 50% of the participants falling into the good attitude category.\u003c/p\u003e \u003cp\u003eThe knowledge deficits we found in our sample are similar to those reported in other research on adenomyosis and other gynaecological conditions. Ren et al reported insufficient knowledge of adenomyosis among Chinese reproductive-age women, with a mean score of 3.54/10, and no knowledge item exceeding 50% correctness (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Although the scoring approaches differ between the mentioned study and ours, they both highlight that the poor knowledge regarding adenomyosis is not limited to either population. Limited gynaecological awareness has also been found locally. A KAP study on endometriosis among Lebanese women reported gaps in knowledge of the condition (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). While uterine adenomyosis and endometriosis are distinct diseases, the similarity of awareness deficit may reflect a broader gap in public knowledge of chronic gynaecological conditions in Lebanon. Part of the high percentage of participants with poor knowledge in our sample may also be due to the addition of an IDK response option to the questionnaire. While adding this option allows participants to admit the absence of knowledge/ uncertainty rather than guessing an answer they don\u0026rsquo;t truly endorse, it may decrease engagement of participants where they can choose IDK without thinking about the question at hand. However, we tried to mitigate this possibility by instructing the participants to select IDK only when picking an actual answer would be making a random guess and by implementing a logical conflict screening exclusion.\u003c/p\u003e \u003cp\u003eSubjective knowledge \u0026ndash; how knowledgeable participants believed themselves to be about gynaecological topics \u0026ndash; was positively associated with their actual adenomyosis knowledge scores. As self-perceived knowledge increased, the odds of answering correctly and incorrectly increased compared to selecting IDK. However, the increase in odds relative to IDK was numerically larger for incorrect responses. This may reflect a confidence-accuracy miscalibration, where a greater confidence in knowledge was not always matched with higher accuracy. It\u0026rsquo;s important to consider the clinical aspect of this mismatch. Those who are confident in inaccurate health knowledge may be less likely to question their understanding and recognize that they need more information, which could reduce their tendencies to seek clarification and additional health information (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBeyond self-perceived knowledge, a healthcare-related background was also associated with better knowledge about adenomyosis. Healthcare worker/ student status had a 10.8-point higher knowledge score in our sample after multivariable adjustment. However, the odds of choosing the correct answer rather than IDK were very similar to those of choosing the incorrect answer rather than IDK (1.93 vs 1.80), suggesting that a healthcare-related background may increase familiarity with the condition without consistently translating into a more superiorly accurate adenomyosis knowledge. This may indicate that knowledge gaps about uterine adenomyosis persist even among healthcare workers/ students. Similarly, previous literature findings showed persistent adenomyosis knowledge and awareness gaps among healthcare professionals (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). In addition, knowing someone with uterine adenomyosis was associated with a greater disease knowledge score, particularly among those who have an immediate family member diagnosed with this condition. Lindenmeyer et al. reported that health information is shared between family members through everyday \u0026ldquo;health talk\u0026rdquo;, which helps build an understanding of the diseases from shared experiences and medical information (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough the attitude scores were more favourable compared to knowledge and practice, the factors examined in this study offered little explanation for why attitude scores differed between participants (final mode adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0226). Hence, the variation in attitudes may be driven by factors outside of what we measured. Some of these may be societal beliefs, culture, stigma, symptom normalization, and previous healthcare experiences, as an adenomyosis scoping review highlighted their role in shaping overall women\u0026rsquo;s perceptions and experiences of the condition (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The generally favourable attitude findings in our sample were similarly reported in the Ren et al. study, though their population exhibited higher levels of agreement on the first 5 attitude statements (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Interestingly, the attitudes towards hysterectomy in this context were similar between the two studies, with approximately two-thirds of participants not considering total hysterectomy an acceptable option for curing uterine adenomyosis. According to Ren et al., this finding may indicate gaps in participants\u0026rsquo; awareness of available treatment options.\u003c/p\u003e \u003cp\u003e Adenomyosis-related practice was generally poor in our study, with 64.1% of participants showing poor practice and only 7.4% demonstrating good practice, despite approximately half of participants reporting good attitudes. This discrepancy suggests that favourable perceptions alone may not necessarily translate into appropriate health-related practices, highlighting the potential influence of broader factors that shape how women perceive, interpret, and respond to adenomyosis and its symptoms (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the multivariable analysis, Lebanese nationality, postgraduate education, and healthcare worker/ student status were independently associated with higher practice scores. The association with Lebanese nationality may reflect the accessibility and potentially the familiarity with the local healthcare system and the available healthcare services and information (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Similarly, the positive relationship between postgraduate education and practice may be related with higher health literacy, as higher educational attainment may facilitate the acquisition, interpretation, and application of health information (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The association between healthcare worker/student status and higher practice scores may reflect the practical advantage of the greater exposure to medical information and environment which could facilitate the application of knowledge and strengthen relevant clinical competencies (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). However, the presence of adenomyosis-specific knowledge gaps in this population suggests that general exposure to healthcare knowledge and clinical settings may support appropriate health practices without necessarily ensuring condition-specific knowledge. This highlights the potential value of incorporating adenomyosis-specific content into the education and training of healthcare professionals and students (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMenstrual flow characteristics were also significantly associated with practice. The lightest menstrual flow being \u0026ldquo;heavy\u0026rdquo; was associated with higher practice scores whereas reporting \u0026ldquo;moderate\u0026rdquo; or \u0026ldquo;heavy\u0026rdquo; flow as the heaviest flow were both associated with lower practice scores. An exploratory analysis of flow difference (heaviest flow \u0026ndash; lightest flow) showed that a greater flow difference was associated with lower practice scores (B=-2.55, P\u0026thinsp;=\u0026thinsp;0.041), suggesting that greater menstrual symptom burden at severity baseline may increase attention to menstrual health and encourage care seeking (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), whereas greater variability may reflect less predictable menstrual patterns and potentially hinder consistent monitoring.\u003c/p\u003e \u003cp\u003eThe SEM findings provide further insight into the relations between knowledge, attitude and practice surrounding adenomyosis. Although knowledge showed positive direct association with both attitude and practice, there was no evidence that attitude mediated the relationship between knowledge and practice, as the indirect effect was statistically insignificant. This finding may suggest that increasing factual understanding of adenomyosis may be associated with more appropriate practices without necessarily operating through the measured attitudes, and that knowledge may influence practice through pathways independent of attitude or through other unmeasured factors. However, given the cross-sectional design, these associations could not be interpreted causally, and the model was saturated, so it merely reflected the observations in our sample.\u003c/p\u003e \u003cp\u003eNotably, attitude exhibited a significant negative direct association with practice (B= -0.143) which is counterintuitive. A potential explanation is that more positive attitudes may not necessarily reflect greater perceived urgency to engage in practical or health protective behaviours. Alternatively, the measured attitudes may have captured the general positivity and acceptance toward adenomyosis rather than specific health protective beliefs that induce action. Thus, participants may express favourable views toward the condition while lacking the knowledge, perceived risk, or personal relevance needed to adopt corresponding practices. Despite these mechanisms being speculative, they suggest that favourable attitude alone may not be sufficient to promote appropriate health practices, emphasizing the potential importance of disease-specific knowledge and perceived relevance in shaping behaviour.\u003c/p\u003e \u003cp\u003eThe observed gap between favourable attitudes and limited practice suggests that improving adenomyosis-related outcomes may require interventions extending beyond attitude enhancement and general awareness toward improving disease and symptoms recognition and promoting appropriate health-seeking behaviours. Healthcare workers and students demonstrated comparatively better knowledge and practice in our study, however their greater likelihood to provide confident responses including incorrect answers may reflect persisting knowledge gaps, suggesting that they may represent a potential prioritized and primary target to enhance their adenomyosis-specific knowledge through strengthening disease recognition and improving awareness and knowledge on information limitations. Moreover, given that almost half or more of the participants selected IDK for most knowledge items, with almost 90% having no personal connections with anyone diagnosed with adenomyosis, underscores the need for educational opportunities regarding disease specific knowledge provided for the general population. Such education could be incorporated into gynaecological consultations, primary care and women\u0026rsquo;s health visits, menstrual health campaigns, accessible public health and social media initiatives (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). These approaches may help women recognize potentially concerning symptoms, understand abnormal or heavy bleeding and changes in menstrual patterns, and encourage appropriate and timely care seeking. A multifaceted approach combining healthcare-professional education with public awareness and interventions promoting calibrated health knowledge and confidence that focus on encouraging health action and practices may therefore be more appropriate than information provision alone.\u003c/p\u003e \u003cp\u003eThis study has several strengths. The questionnaire underwent forward-backward translation with some wording modifications to better suit the Lebanese population and demonstrated good to excellent internal consistency across all KAP domains. Furthermore, the explicit inclusion of an IDK option allowed uncertainty or lack of knowledge to be captured and minimized the bias of simply guessing correctly. Logical-conflict screening further strengthened data quality despite introducing selection bias, while the multinomial analysis distinguished confident correct and incorrect responses from IDK answers, yielding additional insight into the relationship between certainty and accuracy.\u003c/p\u003e \u003cp\u003eNonetheless, several limitations should be considered. The cross-sectional design precludes establishing causal relationships. Additionally, convenience and snowball sampling through messages/social media and participant sharing may have introduced selection bias and limits generalizability. Although the composite knowledge score treated IDK responses as equivalent to incorrect responses, potentially obscuring the distinction between uncertainty and misinformation, the multinomial analysis partially mitigated this limitation by examining correct, incorrect, and I don\u0026rsquo;t know responses independently. Finally, the modest explanatory power \u0026ndash; particularly for attitude \u0026ndash; indicates that substantial variability in KAP remains unexplained, suggesting additional determinants not captured in this study may have contributed to adenomyosis related KAP.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study identified gaps in both adenomyosis-related knowledge and practice in light of relatively favourable attitudes. Most participants demonstrated poor knowledge and nearly two-thirds had poor adenomyosis-related practice. Healthcare worker/ student status and greater self-reported gynaecological knowledge were associated with higher knowledge, while a healthcare background was associated with more favourable practice scores. These findings support the need for accessible, disease-specific educational initiatives and interventions regarding adenomyosis, its diagnosis, symptoms, and available management options while encouraging healthcare seeking for symptomatic women.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eKAP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKnowledge\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eattitude\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003epractice\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was conducted in accordance with the ethical principles laid by the declaration of Helsinki. Ethics approval was obtained for Beirut Arab University\u0026rsquo;s Institutional Review Board. Informed consent was acquired from all respondents before filling the survey.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eIDK\u003c/h2\u003e \u003cp\u003eI don't know\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIRB\u003c/strong\u003e \u003cp\u003eInstitutional Review Board\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eaOR\u003c/strong\u003e \u003cp\u003eadjusted Odds Ratio\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSEM\u003c/strong\u003e \u003cp\u003estructural equational modelling\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIQR\u003c/strong\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSD\u003c/strong\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eaR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e \u003cp\u003eadjusted R squared\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCI\u003c/strong\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work did not receive any funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.Ka. was responsible for the conceptualization of the study, visualizations, and formal analysis. A.Ka. and A.S handled the study methods. A.Ka. and S.M. handled project administration and supervision. A.Ka., A.S., M.M., M.B., A.Ke., Y.A.S, A.Z., D.S., A.H., and S.C. participated in investigation, writing the original draft, and reviewing and editing the final draft. All authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData analyzed in the present study is available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Medical Association. World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Participants. JAMA. 2025;333(1):71\u0026ndash;4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2024.21972\u003c/span\u003e\u003cspan address=\"10.1001/jama.2024.21972\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e . PubMed PMID: 39425955.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcKenna KA, Fogleman CD, Dysmenorrhea. Am Fam Physician. 2021;104(2):164\u0026ndash;70. PubMed PMID: 34383437.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Arruda GT, Barbosa-Silva J, Driusso P, Pathmanathan C, Armijo-Olivo S, Avila MA. Worldwide prevalence of dysmenorrhea: a systematic review and meta-analysis across 70 countries. 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Eur J Contracept Reproductive Health Care. 2021;26(5):390\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13625187.2021.1925881\u003c/span\u003e\u003cspan address=\"10.1080/13625187.2021.1925881\" 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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Adenomyosis, Health Knowledge, Attitudes, Practice, Women Health, Lebanon, Survey study","lastPublishedDoi":"10.21203/rs.3.rs-11153706/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-11153706/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAdenomyosis is a common gynaecological disorder associated with dysmenorrhea, abnormal uterine bleeding, pelvic pain, and reproductive complications. Despite the clinical burden presented by it, awareness remains limited. This study aimed to assess knowledge, attitudes, and practice (KAP) regarding adenomyosis in reproductive-aged women in Lebanon.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional online survey was conducted among women aged 18\u0026ndash;49 in Lebanon using snowball and convenience sampling. A modified standardized questionnaire adapted from a previous study was used to assess KAP. Differences in KAP scores were tested using the non-parametric Mann Whitney and Kruskal Wallis tests. Multivariable models were fitted for each KAP domain, as well as a multinominal logit model for \u0026ldquo;I don\u0026rsquo;t know\u0026rdquo; responses and a structural equation model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 418 participants, 79.4% had poor knowledge and only 2.4% had good knowledge. Almost 50% of the responses for each knowledge item were \u0026ldquo;I don\u0026rsquo;t know\u0026rdquo;. 50.0% had good attitudes while only 7.4% had good practice. Healthcare worker/ student status and greater self-reported gynaecological knowledge were associated with higher knowledge scores, while healthcare worker/ student status was also associated with higher practice scores. Knowledge was positively associated with attitude and practice and there was no evidence of an indirect association between knowledge and practice through attitude.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur findings suggest that substantial gaps in adenomyosis-related knowledge and practice exist in reproductive-aged women in Lebanon, despite favourable attitudes. Disease-specific educational initiatives emphasizing symptom recognition and appropriate healthcare seeking behaviours may help bridge these gaps.\u003c/p\u003e","manuscriptTitle":"Knowledge, Attitudes, and Practice of Women in Lebanon Surrounding Uterine Adenomyosis: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-10-23 01:10:56","doi":"10.21203/rs.3.rs-11153706/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-10-25T15:32:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"182982791525895438529411910912092068176","date":"2026-10-21T06:17:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42250810098895976377559092055362441060","date":"2026-10-20T11:57:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176984613698105404696994793681059899091","date":"2026-10-20T11:51:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-10-20T11:28:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248367940466693597394572549442528243668","date":"2026-10-20T10:42:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1924819880741512880022474588554816983","date":"2026-10-20T10:42:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186626375815368181866078207505950018771","date":"2026-10-19T12:53:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237049061997744856818281490097973116610","date":"2026-10-19T05:57:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-10-08T19:20:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-09-30T09:56:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-09-28T06:46:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-09-28T06:45:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2026-09-24T12:20:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"561d9511-bf60-4de3-8260-b20baee57900","owner":[],"postedDate":"October 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-10-25T15:32:01+00:00","index":161,"fulltext":""},{"type":"reviewerAgreed","content":"182982791525895438529411910912092068176","date":"2026-10-21T06:17:45+00:00","index":160,"fulltext":""},{"type":"reviewerAgreed","content":"42250810098895976377559092055362441060","date":"2026-10-20T11:57:27+00:00","index":159,"fulltext":""},{"type":"reviewerAgreed","content":"176984613698105404696994793681059899091","date":"2026-10-20T11:51:35+00:00","index":158,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-10-20T11:28:48+00:00","index":157,"fulltext":""},{"type":"reviewerAgreed","content":"248367940466693597394572549442528243668","date":"2026-10-20T10:42:20+00:00","index":156,"fulltext":""},{"type":"reviewerAgreed","content":"1924819880741512880022474588554816983","date":"2026-10-20T10:42:06+00:00","index":155,"fulltext":""},{"type":"reviewerAgreed","content":"186626375815368181866078207505950018771","date":"2026-10-19T12:53:18+00:00","index":152,"fulltext":""},{"type":"reviewerAgreed","content":"237049061997744856818281490097973116610","date":"2026-10-19T05:57:51+00:00","index":81,"fulltext":""},{"type":"reviewersInvited","content":"117","date":"2026-10-08T19:20:01+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-10-23T01:10:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-10-23 01:10:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-11153706","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-11153706","identity":"rs-11153706","version":["v1"]},"buildId":"uzvnyPIH0yfUW73ClG4p1","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}