Determinants of Disability Adaptation Following Rehabilitation in Individuals with Spinal Cord Injury in Bangladesh: A 6-Month to 10-Year Post-Injury Analysis

Determinants of Disability Adaptation Following Rehabilitation in Individuals with Spinal Cord Injury in Bangladesh: A 6-Month to 10-Year Post-Injury Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Determinants of Disability Adaptation Following Rehabilitation in Individuals with Spinal Cord Injury in Bangladesh: A 6-Month to 10-Year Post-Injury Analysis Md Muid Reshad, Asma Islam, Mehrin Sultana, Punam Costa, Kamrunnaher Koly This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7474313/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Study Design A cross-sectional study design Objectives This study explored how individuals with SCI in Bangladesh adapt to disability following rehabilitation and identified the key determinants that influence this adaptation. Setting Adaptation to disability is a complex, ongoing process shaped by personal, social, and cultural factors. While previous studies in Bangladesh have explored community reintegration and quality of life after spinal cord injury, none have specifically examined how individuals adapt to disability in the community following hospital discharge. Methods Participants were recruited from the SCI follow-up database, consisting of individuals who completed their rehabilitation at the Centre for the Rehabilitation of the Paralysed (CRP) between June 2015 and June 2025, using cluster sampling across all eight divisions of Bangladesh. Data were collected through interviews using a combined questionnaire that included both semi-structured items and the validated Bangla versions of the structured WHODAS 2.0 and the Adaptation to Disability Scale-Revised (ADS-R) Results Among 210 adults, most participants (71.4%) showed moderate adaptation, while 28.1% had low adaptation and only 0.5% had high adaptation. Poor adaptation was associated with complete injuries, tetraplegia, unemployment, pressure ulcers, and delays in starting rehabilitation. Surprisingly, higher education did not always support emotional adjustment. Early rehabilitation, steady income, and family support emerged as key enablers. Conclusion Many individuals with SCI in Bangladesh continue to struggle with adaptation. Timely rehabilitation, emotional support, and better access to income-generating opportunities are vital for improving long-term adaptation to disability Health sciences/Neurology Biological sciences/Neuroscience/Cognitive neuroscience/Perception Spinal Cord Injury (SCI) Disability Adaptation Rehabilitation WHODAS 2.0 ADS-R Bangladesh Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Spinal cord injuries (SCI), whether traumatic or non-traumatic, caused by infections, vascular problems, degenerative diseases, or cancers, are sudden and serious neurological events that significantly disrupt people's lives [ 1 ]. The burden of SCI is much higher in low- and middle-income countries (LMICs), where its prevalence is four times greater than in wealthier nations [ 2 ]. Although exact national data are unavailable, Bangladesh is estimated to experience 20 to 40 new SCI cases per million people each year, totaling approximately 3,280 to 6,560 new cases, with an average age of onset at 34.53 years (range: 16–83 years) [ 7 ]. SCI mainly affects younger adults and requires long-term, costly rehabilitation, making it a major public health problem in resource-limited settings [ 1 ]. In Bangladesh, 70.5% of SCI cases result in paraplegia, while 29.5% lead to tetraplegia [ 8 ]. Beyond physical impairments, individuals experience extensive psychological and social challenges. Their quality of life (QoL) is shaped by numerous factors, including age, gender, education, socioeconomic status, interpersonal relationships, health status, and pain [ 3 ]. Despite medical advances that have improved life expectancy, concerns remain regarding long-term QoL and health outcomes among SCI populations, particularly in LMICs [ 9 ]. In such environments, limited access to quality rehabilitation contributes to poor outcomes, with increased risks of pressure sores, urinary tract infections, depression, pain, and higher mortality rates [ 4 ]. Compounding these issues are social stigma, lack of mobility aids, poor health literacy, economic hardship, and inadequate rehabilitative services [ 5 ]. Reintegration into the community after rehabilitation remains challenging in Bangladesh. High rates of morbidity and mortality continue to affect individuals with SCI long after discharge, undermining QoL and community participation [ 6 ]. The absence of a national SCI registry, demographic data, or a structured care framework further complicates coordinated care, forcing patients to seek fragmented services across multiple hospitals [ 10 ]. Even years after injury, many still face significant barriers such as unemployment, poverty, environmental obstacles, and persistent complications, including depression, pressure ulcers, and psychological distress [ 11 , 12 ]. Alarmingly, 67% of affected households were already living below the poverty line before the injury occurred, exacerbating the long-term caregiving burden [ 7 ]. With limited formal caregiving systems, families often provide essential support, leading to emotional and financial strain. In LMICs, long-term care for SCI often costs more than for dementia or multiple sclerosis, with far fewer resources available. [ 13 ]. Despite these ongoing challenges, many individuals with spinal cord injury (SCI) report improved well-being over time through emotional and psychological adjustment, even in the absence of physical recovery. A key factor in this process is disability acceptance, which reduces psychological distress, supports self-redefinition, and promotes overall adaptation [ 14 , 15 ]. Moreover, cultural frameworks significantly influence how disability is perceived and managed, leading to varied adaptation experiences across societies [ 47 , 48 ]. This study addresses critical gaps in understanding the adaptation level among individuals with SCI in Bangladesh. By identifying key determinants, it aims to inform rehabilitation policymakers of an effective rehabilitation model for culturally responsive national SCI care in Bangladesh. Methods Study design and setting A cross-sectional study design examined individuals with spinal cord injury (SCI) who completed initial rehabilitation between June 2015 and June 2025 at the Centre for the Rehabilitation of the Paralysed (CRP) and were living in community settings across Bangladesh. Participants This study received approval from the Institutional Review Board (IRB) and Ethical Review Board (ERB) of the Centre for the Rehabilitation of the Paralysed (CRP), following the Declaration of Helsinki and Bangladesh Medical Research Council (BMRC) guidelines (IRB clearance number: CRP/BHPI/IRB/07/2024/921). Participants included individuals with spinal cord injury (SCI), aged 18 years and older. The duration since injury ranged from 6 months to 10 years. Participants who had traumatic or non-traumatic brain injuries in addition to SCI, as well as those with severe comorbid conditions that impaired effective communication, were excluded from the study. Data Collection Data were collected from July 2024 to May 2025 across all eight divisions of Bangladesh, each serving as a cluster. Eligible participants were identified from the CRP Rehabilitation Wing’s CBR-SCI follow-up database and screened using predefined criteria. Structured and semi-structured questionnaires were used, with interviews conducted primarily face-to-face. A total 210 community living individuals with SCI participated in this study. Where 181 data were collected by face to face while 29 participants were not reachable in physical visit, for this reason data were collected by phone call. Two trained data collectors conducted the interviews under the supervision of the principal investigator. Informed consent was obtained, and participants were assured of confidentiality, voluntary participation, and the right to withdraw. Although no direct benefit was provided, the study aims to enhance SCI rehabilitation in Bangladesh. All data were anonymized and securely stored. Measures Data were gathered on demographics, psychosocial and comorbid factors, lifestyle habits, injury-related details, and rehabilitation and management history ( Table-1 ). Disability was evaluated with the culturally adapted Bangla version of the 36-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), which assesses six functional domains (cognition, mobility, self-care, getting along, life activities and participation) over the past 30 days and has been validated in numerous studies [ 11 , 23 ]. Adaptation to disability was measured using the Adaptation to Disability Scale–Revised (ADS-R), a validated tool widely used in disability research [ 22 , 21 , 20 ] Psychometric Validation of the Bangla ADS-R The Bangla version of the Adaptation to Disability Scale-Revised (ADS-R) was translated and linguistically validated following standard procedures recommended by Beaton, as also applied in our previous study [ 16 ] ( Appendix 1 ). Content validity was assessed through the Item-Objective Congruence (IOC) index, with expert panel evaluations confirming item relevance and clarity. An item-level content validity index (I-CVI) of ≥ 0.80 was considered acceptable [ 18 ], while values ≥ 0.50 were deemed suitable for a large-scale testing context [ 19 ]. Construct validity was evaluated using Exploratory Factor Analysis (EFA), which confirmed the underlying factor structure of the scale. Internal consistency was assessed using Cronbach’s alpha, demonstrating satisfactory reliability in this population. According to established guidelines, Cronbach’s alpha values ≥ 0.70 are acceptable, ≥ 0.80 are good, and ≥ 0.90 are considered excellent [ 17 ]. Statistical Analysis Descriptive statistics were used to summarize participants’ demographic, psychosocial/comorbid, lifestyle, injury-related, and rehabilitation-related characteristics. To assess normality, the Kolmogorov–Smirnov and Shapiro–Wilk tests were performed. Based on the data distribution, inferential analyses were carried out using Chi-square tests, one-way ANOVA, and Kruskal–Wallis tests to examine the relationships among participant characteristics, disability levels, and adaptation to disability. Spearman's correlation was employed to evaluate the strength and direction of relationships between key variables. Finally, a multiple regression model was used to identify significant determinants of disability adaptation in individuals with spinal cord injury (SCI). All tests were conducted with the Statistical Package for Social Science (SPSS) version 22. Significance was set at P < 0.05 for all analyses. Results Participants (Demographic, psychosocial/comorbidity, Lifestyle, Injury-related, and rehabilitation care and management) The study included 210 individuals with spinal cord injury (SCI), with a median age of 31 years (IQR = 17.75). Gender data from 210 participants showed 88% male and 12% female. Most participants were married (58.1%), followed by unmarried (32.9%), divorced/separated (8.1%), and widowed (0.5%). The majority (84.3%) lived in nuclear families, while 11.9% lived in multigenerational households, and 3.8% lived alone. Participants represented all eight administrative divisions of Bangladesh, with Rajshahi (19.0%), Khulna (16.7%), and Barishal (14.3%) having the highest numbers. Most (71.4%) resided in rural areas. Education levels varied, with 34.8% having completed Class 1–9 education, 29.5% finishing secondary school, 17.6% having no formal education, 16.2% being college graduates, and only 1.9% being university graduates. Employment status revealed that 43.1% were unemployed due to physical illness, 26.8% were self-employed or farmers, 10% were students, and 9.1% were household workers or housewives. Before their injury, 56.7% were the primary earners for their families, 5.2% contributed financially, and 38.1% were financially dependent. Among those who contributed, 60.5% indicated that the primary earner could not manage financially without their income. Most participants (86.7%) had someone available to take over the primary earner role if needed. Post-injury, 85.7% were unable to return to their previous employment. The average monthly income before injury was approximately 120.83 ± 81.66 USD, which dropped to a median of 0 USD (IQR = 40.88 USD) after injury, with 64.3% reporting a total loss of income. Only 5.7% had pressure injuries or ulcers. Most participants (87.1%) did not engage in smoking, betel leaf chewing, or tobacco use. Regular exercise (≥ 3 days/week) was rare before injury (3.8%) but increased substantially after injury (93.3%). The median duration of injury was 36 months. Traumatic injuries accounted for 92.4%, with 7.6% being non-traumatic. Paraplegia was more common (71.9%) than tetraplegia (28.1%). Complete SCI was reported by 55.7% and incomplete by 44.3%. Manual wheelchairs were the predominant mobility aid (79%), with a minority using sticks, walkers, motorized wheelchairs, or no devices. Most participants (88.1%) received invasive medical management, while 10.5% received conservative treatment, and 1.4% underwent acute rehabilitation. The median time to first rehabilitation was 40 days post-injury. At the time of data collection, only 19% were receiving rehabilitation services; 42.9% were in their first rehab experience. The average initial rehabilitation duration was approximately 137 days. A majority (83.8%) received comprehensive multidisciplinary rehabilitation, which included physiotherapy, occupational therapy, speech-language therapy, and counseling. Nearly all (98.1%) had a history of hospitalization related to SCI. Rehabilitation referrals mainly came from doctors (76.7%), followed by former patients (15.7%) and self-referrals (2.4%). Family support for caregiving was nearly universal (98.1%), with most participants assuming caregiving roles before their injury. Table 1 Participants' Demographic, Psychosocial, and Comorbidity Characteristics, Lifestyle, Injury-related Rehabilitation and Medical Care Information Demographic characteristics Variables Category Percentage (Number) Age (Yrs) Median = 31, IQR = 17.75 ª Gender Male 88% (n = 184) Female 12% (n = 26) Marital Status Married 58.1% (n = 122) Unmarried 32.9% (n = 69) Divorced/Separated 8.1% (n = 17) Widowed .5% (n = 1) Prefer not to disclose .5% (n = 1) Family type Lives in a single-family 84.3% (n = 177) Lives in a multigenerational family 11.9% (n = 25) Lives alone 3.8% (n = 8) Divisional areas Rajshahi 19% (n = 40) Khulna 16.7% (n = 35) Barishal 14.3% (n = 30) Sylhet 12.9% (n = 27) Mymensingh 12.9% (n = 27) Chottogram 10% (n = 21) Rangpur 8.6% (n = 18) Dhaka 5.7% (n = 12) Living areas Rural 71.4% (n = 150) City 28.6% (n = 60) Education Class (1–9) 34.8% (n = 73) Secondary School (SSC) 29.5% (n = 62) No formal education 17.6% (n = 37) College level education 16.2% (n = 34) University graduate 1.9% (n = 4) Employment Unemployed (Due to Physical illness) 43.1% (n = 90) Self-employed/Farming 26.8% (n = 56) Student 10% (n = 21) Household worker 9.1% (n = 19) Psychosocial and Comorbidity Characteristics Pre-injury earning status Primary earner 56.7% (n = 119) Financial contributor 5.2% (n = 11) Financially dependent 38.1% (n = 80) Family backup earner available Yes 86.7% (n = 182) Post-injury employment Unable to return 85.7% (n = 180) Monthly income (Pre-injury) Mean 120.83 ± 81.66 USD Monthly income (Post-injury) Median 0 USD, IQR = 40.88 USD Reported full income loss Yes 64.3% (n = 135) Pressure Injuries/ulcers Present 5.7% Lifestyle factors Personal habits (Smoking/betel leaf/Tobacco+…others No 87.1% (n = 183) Regular exercise (pre-injury) Yes 3.8% (n = 8) Regular exercise (Post-injury) Yes 93.3% (n = 196) Injury profile Duration since injury (Months) Median = 36, (IQR = 41.25)ª Cause of injury Traumatic 92.4% (n = 194) Non-traumatic 7.6% (n = 16) Level of lesion Paraplegia 71.9% (n = 151) Tetraplegia 28.1% (n = 59) Type of SCI Complete 55.7% (n = 117) Incomplete 44.3% (n = 93) Assistive device Manual Wheelchair 79% (n = 166) Others 21% (n = 44) Rehabilitation and management Acute Medical Management Invasive 88.1% (n = 185) Conservative 10.5% (n = 22) Acute rehab 1.4% (n = 3) Time to first rehabilitation (days) Median = 40, ª IQR = 63 Currently receiving rehab Yes 19% (n = 40) First-time rehab users Yes 42.9% (n = 18) Average duration of initial rehab (days) 137 ± 55.44** Type of rehab service received Multidisciplinary 83.8% (n = 176) Immediate hospitalization after SCI Yes 98.1% Referral source for rehab Doctors 76.7% (n = 161) Former patients 15.7% (n = 33) Self-referral 2.4% (n = 5) Others (relatives/Known/Unknown persons) 5.2% (n = 11) Caregiver support Family member 98% (n = 206) Caregiving role pre-injury Involved in caregiving for family members 87.1% (183) ªIQR = Interquartile Range; ** ± (SD) = Standard Deviation Disability level and association with demographic, psychosocial, lifestyle, injury-related, and rehabilitation care and management factors Adaptation in SCI Among the 210 participants, the majority (71.4%, n = 150) reported a medium level of adaptation to disability, while 28.1% (n = 59) exhibited a low level of adaptation. Only one participant (0.5%) demonstrated a high level of adaptation. The mean total adaptation score was 69.24 ± 8.71, indicating that most participants experienced a low to medium level of acceptance of their disability. Regarding subdomain scores, the average for “Transformation from comparative status to asset values” was 20.23 ± 2.93, for “Containment of disability” 17.04 ± 3.84, for “Enlargement of scope of values” 24.07 ± 3.30, and for “Subordination of physique” 7.88 ± 1.90. These subscale scores suggest that the adaptation experience was multifaceted and varied across different psychological domains. Relationship between adaptation and demographic, psychosocial/comorbid, lifestyle, injury-related, rehabilitation and management factors A Pearson chi-square test and one-way ANOVA were used to assess associations between categorical and continuous variables, respectively, and levels of adaptation. Significant associations were found between adaptation levels and participants' age, F(2, 205) = 4.16, p = .017, with those in the low adaptation group being older (38.93 ± 16.40) than those in the medium (33.27 ± 10.95) and high (34) adaptation groups. Family composition (χ²(4) = 12.00, p = .017), division (χ²(14) = 25.03, p = .034), and post-injury employment status (χ²(14) = 24.40, p = .041) also showed significant associations. Low adaptation was more common among participants belongs to multigenerational families (44%) and those living alone (37.5%), whereas medium adaptation predominated in nuclear families (74.6%). Regionally, Rangpur had the highest rate of medium adaptation (94.4%), while Rajshahi (45%) and Mymensingh (44.4%) had the highest rates of low adaptation. Unemployment due to illness was linked to low adaptation (35.6%), while self-employed individuals (76.8%) and those involved in household responsibilities (78.9%) mostly reported medium adaptation. Gender, marital status, living area, and education were not significantly related to adaptation levels (p > 0.05). Among psychosocial factors, the ability to return to the pre-injury job role was significantly associated with adaptation level (χ²(2) = 10.92, p = .004). Most individuals who returned to their previous jobs (96.7%) reported medium adaptation, while 32.2% of those unable to return showed low adaptation. The presence of pressure injuries approached significance (χ²(2) = 5.78, p = .056), with 58.3% of those affected falling into the low adaptation group, compared to 26.3% among those without ulcers. In contrast, 73.2% of individuals without pressure ulcers exhibited medium adaptation. Post-injury monthly income also showed a significant association with adaptation level, F(2, 207) = 3.13, p = .045. Participants with high adaptation reported the highest average income (57.26 USD), compared to those in the medium (24.05 ± 38.29 USD) and low adaptation groups (11.93 ± 23.11 USD). Although other financial variables such as pre-injury financial role, ability to manage family expenses, availability to take primary earner role, and income changes, were not significantly related to adaptation (p > 0.05), individuals who previously contributed financially had the highest proportion of low adaptation (45.5%). Similarly, those with total income loss due to injury more frequently reported low adaptation (31.9%). Injury-related factors such as duration of injury, cause, and use of assistive devices were not significantly associated with adaptation in SCI. However, strong associations were found with the level of injury (χ²(2) = 21.21, p < .001) and type of injury (χ²(2) = 8.96, p = .011). Individuals with tetraplegia more frequently reported low adaptation (50.8%) compared to those with paraplegia (19.2%). Similarly, participants with complete injuries had a higher prevalence of low adaptation (35.9%) than those with incomplete injuries (18.3%). Lifestyle factors showed no significant relationship with adaptation (p > 0.05). Among rehabilitation and medical management variables, only time to access rehabilitation services was significantly associated with adaptation, F(2, 207) = 4.29, p = .015; those with low adaptation experienced longer delays (239.54 ± 615.12 days) compared to the high adaptation group (mean = 2 days). Association between disability status and adaptation A one-way ANOVA was conducted to examine whether levels of disability adaptation were associated with variations in functioning among individuals with spinal cord injuries. Significant differences were found across all WHODAS 2.0 domains, including cognition, mobility, self-care, getting along, life activities, participation, and overall disability severity based on adaptation levels (p < .001 for all), indicating strong associations between disability acceptance and perceived functional ability. Participants with low acceptance had the highest disability scores (e.g., total WHODAS 2.0 score: 111.42 ± 18.51). At the same time, those with high acceptance showed markedly better functioning (mean score: 56.00). The Percentage of disability severity also declined from 69.82% in the low-acceptance group to 35% in the high-acceptance group. Factors Correlated with Adaptation Spearman’s correlation analysis indicated significant associations between disability adaptation and various factors. A strong negative correlation was found between adaptation and WHODAS 2.0 score (r = − 0.614, p < .001), indicating that higher adaptation corresponds to lower disability. Post-injury income had a positive association with adaptation (r = 0.223, p < .01), while age was negatively associated (r = − 0.184, p < .01). WHODAS 2.0 scores were negatively correlated with post-injury income (r = − 0.318, p < .001) and positively with age (r = 0.217, p < .01). Additionally, post-injury income correlated significantly with pre-injury income (r = 0.406) and age (r = 0.629), whereas delayed rehabilitation access was negatively linked to post-injury income (r = − 0.166, p < .05). No significant association was found between injury duration and adaptation. Table 2 Spearman’s Correlation Between Adaptation, Disability, and Related Variables Variables Spearman’s r P-value Adaptation vs. WHODAS 2.0 -0.614** 0.000* Adaptation vs Post Post-Injury Income 0.223 0.001* Adaptation vs Age -0.184** 0.008* WHODAS 2.0 vs Post injury income -0.318** 0.000* WHODAS 2.0 vs Age 0.217 0.002* Post injury income vs pre injury income 0.406 0.000* Post injury income vs Age 0.629 0.000* Post-injury income vs Time to access Rehab -0.166** 0.016* Duration of injury vs Adaptation 0.110 0.114 Time to First Access Rehab vs. Adaptation -0.064** 0.357 *Significant value p < 0.05; **(-) = Negative correlation Determinants of disability adaptation in SCI A multiple linear regression analysis was performed to identify the determinants of adaptation to disability among individuals with spinal cord injury (N = 210). The demographic model accounted for 35.3% of the variance in adaptation (F(29,177) = 3.333, p < .001). Notably, living in a single-family was positively associated with adaptation compared to living alone (B = 7.214, p = .017), while residing in the Rajshahi division predicted lower adaptation compared to living in other divisions in Bangladesh. Surprisingly, participants with graduate-level education had lower adaptation scores relative to those with no formal education (B = − 12.632, p = .009). Employment status revealed mixed effects, such as day laborers (B = 9.080, p = 0.004) and self-employed/farmers (B = 5.190, p = 0.001) exhibited higher adaptation, whereas non-profit/social workers (B=-24.726, p = 0.003) and retirees (B=-12.606, p = 0.007) showed lower adaptation. Psychosocial and comorbidity variables did not significantly predict adaptation overall (F(11,26) = 1.381, p = .240), though higher pre-injury income was linked to poorer adaptation (B = − 0.001, p = .026). Lifestyle factors, including pre- and post-injury personal habits and exercise, were not significant predictors (F(3,206) = 0.393, p = .758). Clinical and injury-related factors explained 11.4% of the variance (F(9,200) = 2.855, p = .003), with paraplegia positively associated (B = 4.035, p = .003) and complete injury negatively associated with adaptation (B = − 2.824, p = .038). Although none of the predictors reached statistical significance, the variable “Caregiver availability = Family member(s) not available to support” approached significance (B = -22.03, p = .053), indicating a potentially meaningful negative association with adaptation. Both severe and extreme disability levels significantly predicted lower adaptation scores compared to moderate disability. Severe disability was associated with a 5-point decrease (B = -5.047, p < .001), while extreme disability showed a much larger negative impact (B = -15.695, p < .001). Table 3 Summary of Significant Predictors of Disability Adaptation in SCI Predictors B (Unstandardized) Std. Error Standardized Beta t Sig. Demographic predictors (Constant) 62.764 4.683 — 13.402 0.001* Family Composition = Single family 7.214 2.991 0.303 2.412 0.017* Division = Rajshahi -7.348 2.887 -0.333 -2.545 0.012* Education = Graduate -12.632 4.767 -0.173 -2.650 0.009* Employment = Day Labour 9.080 3.126 0.188 2.905 0.004* Employment = Self-employed/Farmer 5.190 1.418 0.265 3.660 0.001* Employment = Non-profit/Social Worker -24.726 8.155 -0.197 -3.032 0.003* Employment = Retired -12.606 4.613 -0.199 -2.733 0.007* Psychosocial and comorbidity predictors (Constant) 70.027 14.081 — 4.973 0.001* Monthly Income (Pre-Injury) -0.001 0.000 -0.543 -2.357 0.026* Monthly Income Change = Unchanged -29.453 12.189 -0.425 -2.416 0.023* Injury-related predictors (Constant) 69.103 3.01 — 22.942 0.001* Level of SCI = Paraplegia 4.035 1.324 0.209 3.047 0.003* Type of Injury = Complete Injury -2.824 1.349 -0.161 -2.094 0.038* Rehabilitation care and management (Constant) 89.012 14.23 — 6.255 0.001* Caregiver Availability = Family Members Not Available -22.032 10.89 -0.354 -2.022 0.053† Disability level (Constant) 74.12 .85 — 86.34 0.001* Disability Level = Severe Disability -5.047 1.098 -0.290 -4.590 0.001* Disability Level = Extreme Disability -15.695 1.567 -0.632 -10.010 0.001* * Predictors with p < .05 were considered statistically significant; † Predictors with p < .10 were considered marginally significant and retained for exploratory purposes, consistent with conventions in rehabilitation and social science research. Discussion This study explored how individuals with spinal cord injury (SCI) in Bangladesh adapt to disability, using data from 210 participants. The first aim was the linguistic validation of the Bangla version of the Adaptation to Disability Scale-Revised (ADS-R), which showed strong content validity (IOC = 0.67–1.00) and internal consistency (Cronbach’s α = 0.85), aligning with standard thresholds [ 17 , 16 ]. The exploratory factor analysis showed some differences from the original four-factor structure, but the Subordination domain stayed the same. Keeping four components with eigenvalues > 1 supports the tool's validity in both its design and cultural context [ 31 ]. The predominantly male (88%) sample with a median age of 31 reflects global trends of higher SCI risk among young men due to occupational hazards and risk behaviors, especially in low- and middle-income countries [ 24 ]. A high proportion of rural participants (71.4%) reflects limited access to specialized rehabilitation, underscoring the burden on under-resourced health systems [ 25 ]. Participants were mostly from Rajshahi, Khulna, and Barishal, which may reflect regional referral trends and differences in accessing long-term rehabilitation, as supported in previous literature [ 26 ]. Trauma or violence accounted for 92.4% of SCIs, with 88.1% undergoing surgical or invasive procedures in the acute-phase treatment, consistent with global trends [ 27 , 24 ]. Despite intervention, 71.9% developed paraplegia and 55.7% experienced complete bowel and bladder dysfunction, reflecting severe functional impairment. A notable 8.1% were divorced, indicating the potential strain of SCI on marital relationships, echoing a previous study [ 28 ] that emphasized the need for psychosocial and marital support. Educational attainment was low, with only 1.9% being graduates. Consistent with previous research [ 7 ], low educational attainment could limit opportunities for vocational reintegration and exacerbate socioeconomic vulnerability. Besides, approximately 64.3% lost their entire income due to injury, and only 1% had access to motorized or advanced mobility aids, highlighting economic barriers to independence [ 29 , 30 ]. The majority of the participants with SCI (84.3%) lived in a nuclear or single-family. Before their injury, 87.1% of participants had been caregivers, and this role reversal created additional stress, particularly for those now living alone. This finding is novel in the context of SCI, as previous studies [ 32 , 33 ] highlighted the importance of family support but did not address the unique challenge of individuals transitioning from being caregivers to becoming care recipients within their families. The mean disability score (57.42 ± 13.6%) reflected that most participants experience severe to extreme disability, also highlighting significant limitations in physical functioning and daily activities, especially mobility, followed by challenges in participation in social activities, consistent with the previous literature, how SCI restricts social engagement due to physical and attitudinal barriers [ 34 , 35 ]. Multifactorial Influences on Adaptation Adaptation to disability in SCI is shaped by intersecting demographic, psychosocial, injury-related, and environmental factors. Younger age significantly predicted better adaptation (r = − 0.184, p = 0.008), suggesting age-related flexibility may aid adaptation. Gender showed no significant association (p = 0.887), though females had slightly higher adaptation scores. These findings contrast with Study [ 22 ], which reported no age effect but found that women were better adapted. The differences may reflect contextual or cultural variations in adaptation patterns. Family structure influenced outcomes; those living in single-family adapted better than individuals living alone or in multigenerational families. This highlights clear differences, while a previous study [ 37 ] reported that family environment affects psychosocial well-being but did not clearly distinguish how family size and type influence adaptation. Geographically, adaptation was highest in Dhaka and lowest in Rajshahi, indicating unequal access to rehabilitation and community support. While rural or city residence wasn't independently significant (p = 0.593), rural participants reported slightly better adaptation, possibly due to stronger communal bonds [ 38 ]. Individuals without formal education showed better adaptation than graduates, possibly due to fewer disrupted aspirations and lower psychosocial stress. This contrasts with the study [ 46 ], which found that higher education facilitates better adaptation. Similarly, study [ 22 ] reported no significant effect of education, suggesting that cultural context may influence this relationship. Besides, Individuals who were the primary earners before injury exhibited lower levels of adaptation, likely due to the loss of social identity and financial stability, supporting previous evidence [ 5 ]. Notably, a higher pre-injury income was associated with poorer adaptation (B = − 0.543, p = 0.026), indicating that the psychological impact of economic loss may be more severe for those with greater financial means. Surprisingly, individuals who retained their income after injury adapted worse than those who experienced complete income loss (p = 0.023), possibly reflecting internal conflicts or unmet personal and social expectations. The presence of pressure injuries was marginally linked to poorer adaptation (p = 0.056), aligning with findings of a previous study [ 39 ], which reported that pressure ulcers negatively affect self-esteem and quality of life. Although personal habits such as smoking and betel leaf use did not reach statistical significance, smokers tended to show slightly lower adaptation levels, consistent with the literature [ 40 ], which reported that smoking hinders recovery. Despite high rates of participation in physical activity after injury did not significantly influence adaptation. While previous literature [ 41 ] highlighted the role of physical activity in enhancing resilience, it did not emerge as a major predictor in our analysis. In contrast, individuals with paraplegia or incomplete injuries adapted better than those with tetraplegia or complete injuries, likely due to greater functional independence. This finding contrasts with previous literature [ 22 ], which reported no such association. Time since injury showed no significant effect on adaptation (p = 0.574), supporting the conclusions of the studies [ 42 , 22 ] that psychosocial and environmental factors play a more crucial role than duration alone. However, users of advanced assistive technology often demonstrated lower adaptation levels, potentially due to poor infrastructure and environmental barriers in rural Bangladesh, which limit the practical utility of such devices [ 43 , 44 ]. While not statistically significant, individuals without caregiver support showed poorer adaptation (P > 0.05), reinforcing how essential caregivers are in providing stability and improving life after discharge [ 45 ] Adaptation and Psychosocial Adjustment The average adaptation score (69.24 ± 8.71) indicates a moderate acceptance of disability, although 28.1% exhibited low adaptation, suggesting a significant psychological burden. Across various areas, the lowest scores were found in Subordination of Physique and Containment of Disability, highlighting ongoing issues with body image and emotional regulation. The Containment domain showed the greatest variation (F = 94.488, p < 0.001), emphasizing its importance in evaluating psychosocial adjustment in this context ( Appendix-2 ). Adaptation scores were negatively correlated with disability scores (r = − 0.614, p < 0.01), meaning that greater functional limitations predicted poorer adaptation, especially concerning mobility and social participation in SCI, supporting the previous statement [ 36 ], while fewer functional issues are associated with better psychosocial adaptation in SCI [ 46 ]. Study limitations The cross-sectional design offers only a single-time snapshot, restricting understanding of how adaptation evolves over time. Although validated tools were used, reliance on self-reported data may introduce response bias or misinterpretation due to varying levels of understanding among participants. The study was also limited by the inability to ensure an equal distribution of male and female participants. These factors may influence the generalizability of the findings and highlight the need for broader, more inclusive future research Conclusion This study reveals that adapting to life with a spinal cord injury (SCI) is a complex, multifaceted process shaped by physical, emotional, social, and economic challenges. Many participants, particularly those with severe disabilities and limited access to rehabilitation, struggled to adjust. Higher levels of education and income before the injury were sometimes linked to lower levels of adaptation, possibly due to greater disruptions to personal and professional identity. In contrast, individuals involved in farming or self-employment, as well as those with strong family support, demonstrated better adjustment, highlighting the importance of flexible livelihoods and close community ties. These findings underscore the urgent need to reframe rehabilitation, not just as physical recovery but as a holistic process that addresses mental health, social inclusion, economic reintegration and quality of life. Community-based and inclusive care models are essential, particularly in resource-limited settings. By tailoring rehabilitation to local needs, empowering families and communities, and creating employment opportunities, we can help people with SCI rebuild lives filled with dignity, purpose, and independence. Declarations Disclosure of Interest and Acknowledgement Ethics declaration: I, the undersigned, declare that this manuscript is original, has not been published previously, and is not under consideration for publication elsewhere . Ethical Approval: Ethical approval for this study was obtained from the Ethical Review Committee of the Centre for the Rehabilitation of the Paralysed (CRP), Institutional Review Board (IRB), and subsequently accepted by the Bangladesh Health Professions Institute (BHPI). Permission to use the ADS-R questionnaire was obtained via email from the original author. Additional permission was secured from the Rehabilitation Wing Department at CRP to facilitate smooth data collection and conduct of the research. Consent to participate: Participation in this study was entirely voluntary, and informed consent was obtained from all participants before data collection. Participants were informed that they would not receive any direct personal benefit from the study; however, their contributions may help improve future rehabilitation processes for individuals with spinal cord injury. They were also assured of their right to withdraw from the study at any point without any consequences, should they lose interest or feel uncomfortable. Funding disclosures: The study was self-funded by the authors without any external financial support Authorship Contribution Statement: Md Muid Hossain Reshad- Concept development, Methodology, Analysis, Results, writing manuscripts, Software analysis, Asma Islam- Reviewing, Editing, Discussion, Conclusion, Supervision, Mehrin Sultana- Data curating, Methodology, Reviewing discussion and manuscript , Organizing tables and graphs, Punam D Costa- Review analysis, Methodology, Discussion, Conclusion Kamrunnnaher Koly - Review, Editing. Declaration of competing interest: The authors declare no conflicts of interest Data availability: Data can be shared based on a reasonable request Acknowledgement: The authors would like to express their heartfelt gratitude to the faculty members of the M.Sc. in Rehabilitation Science (MRS) program at BHPI, affiliated with the University of Dhaka, for their academic guidance and encouragement throughout this study. Special thanks are due to Associate Professor Asma Islam, the principal supervisor, for her consistent support, insightful feedback, and mentorship. The authors are also deeply grateful to Professor Darlene Groomes of Oakland University, USA, for generously sharing the ADS-R questionnaire and accompanying guidelines, which played a crucial role in this research. Additionally, sincere appreciation is extended to, Centre for the Rehabilitation of the Paralysed (CRP) and the participants who made this study possible. 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2","display":"","copyAsset":false,"role":"figure","size":17879,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSignificant factors associated with the level of adaptation in spinal cord injury in Bangladesh (n=210)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7474313/v1/4992b2b75750dbf033f3e255.png"},{"id":90320565,"identity":"a0bf0de8-91bc-4fae-9c4f-2c2c85dc826d","added_by":"auto","created_at":"2025-09-01 10:47:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":15822,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship Between Disability Status and Adaptation Among Individuals with Spinal Cord Injury (n=210)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7474313/v1/fda745b44904d2ea2a5f0e4f.png"},{"id":90320566,"identity":"936d2891-8386-4466-a05f-4f1d5a804c6f","added_by":"auto","created_at":"2025-09-01 10:47:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":28640,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScatter Plot Showing the Predictive Relationship Between Key Determinants and Disability Adaptation with 95% Cl (Confidence Intervals)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7474313/v1/f58177d0ee0b7b55541d9543.png"},{"id":90321901,"identity":"5d093f16-6a8d-4955-bcc8-d191b648446b","added_by":"auto","created_at":"2025-09-01 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Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpinal cord injuries (SCI), whether traumatic or non-traumatic, caused by infections, vascular problems, degenerative diseases, or cancers, are sudden and serious neurological events that significantly disrupt people's lives [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The burden of SCI is much higher in low- and middle-income countries (LMICs), where its prevalence is four times greater than in wealthier nations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although exact national data are unavailable, Bangladesh is estimated to experience 20 to 40 new SCI cases per million people each year, totaling approximately 3,280 to 6,560 new cases, with an average age of onset at 34.53 years (range: 16\u0026ndash;83 years) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. SCI mainly affects younger adults and requires long-term, costly rehabilitation, making it a major public health problem in resource-limited settings [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In Bangladesh, 70.5% of SCI cases result in paraplegia, while 29.5% lead to tetraplegia [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Beyond physical impairments, individuals experience extensive psychological and social challenges. Their quality of life (QoL) is shaped by numerous factors, including age, gender, education, socioeconomic status, interpersonal relationships, health status, and pain [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite medical advances that have improved life expectancy, concerns remain regarding long-term QoL and health outcomes among SCI populations, particularly in LMICs [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In such environments, limited access to quality rehabilitation contributes to poor outcomes, with increased risks of pressure sores, urinary tract infections, depression, pain, and higher mortality rates [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Compounding these issues are social stigma, lack of mobility aids, poor health literacy, economic hardship, and inadequate rehabilitative services [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Reintegration into the community after rehabilitation remains challenging in Bangladesh. High rates of morbidity and mortality continue to affect individuals with SCI long after discharge, undermining QoL and community participation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The absence of a national SCI registry, demographic data, or a structured care framework further complicates coordinated care, forcing patients to seek fragmented services across multiple hospitals [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Even years after injury, many still face significant barriers such as unemployment, poverty, environmental obstacles, and persistent complications, including depression, pressure ulcers, and psychological distress [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Alarmingly, 67% of affected households were already living below the poverty line before the injury occurred, exacerbating the long-term caregiving burden [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. With limited formal caregiving systems, families often provide essential support, leading to emotional and financial strain. In LMICs, long-term care for SCI often costs more than for dementia or multiple sclerosis, with far fewer resources available. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite these ongoing challenges, many individuals with spinal cord injury (SCI) report improved well-being over time through emotional and psychological adjustment, even in the absence of physical recovery. A key factor in this process is disability acceptance, which reduces psychological distress, supports self-redefinition, and promotes overall adaptation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Moreover, cultural frameworks significantly influence how disability is perceived and managed, leading to varied adaptation experiences across societies [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. This study addresses critical gaps in understanding the adaptation level among individuals with SCI in Bangladesh. By identifying key determinants, it aims to inform rehabilitation policymakers of an effective rehabilitation model for culturally responsive national SCI care in Bangladesh.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and setting\u003c/h2\u003e\u003cp\u003eA cross-sectional study design examined individuals with spinal cord injury (SCI) who completed initial rehabilitation between June 2015 and June 2025 at the Centre for the Rehabilitation of the Paralysed (CRP) and were living in community settings across Bangladesh.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003e This study received approval from the Institutional Review Board (IRB) and Ethical Review Board (ERB) of the Centre for the Rehabilitation of the Paralysed (CRP), following the Declaration of Helsinki and Bangladesh Medical Research Council (BMRC) guidelines (IRB clearance number: CRP/BHPI/IRB/07/2024/921). Participants included individuals with spinal cord injury (SCI), aged 18 years and older. The duration since injury ranged from 6 months to 10 years. Participants who had traumatic or non-traumatic brain injuries in addition to SCI, as well as those with severe comorbid conditions that impaired effective communication, were excluded from the study.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eData were collected from July 2024 to May 2025 across all eight divisions of Bangladesh, each serving as a cluster. Eligible participants were identified from the CRP Rehabilitation Wing\u0026rsquo;s CBR-SCI follow-up database and screened using predefined criteria. Structured and semi-structured questionnaires were used, with interviews conducted primarily face-to-face. A total 210 community living individuals with SCI participated in this study. Where 181 data were collected by face to face while 29 participants were not reachable in physical visit, for this reason data were collected by phone call. Two trained data collectors conducted the interviews under the supervision of the principal investigator. Informed consent was obtained, and participants were assured of confidentiality, voluntary participation, and the right to withdraw. Although no direct benefit was provided, the study aims to enhance SCI rehabilitation in Bangladesh. All data were anonymized and securely stored.\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eData were gathered on demographics, psychosocial and comorbid factors, lifestyle habits, injury-related details, and rehabilitation and management history (\u003cb\u003eTable-1\u003c/b\u003e). Disability was evaluated with the culturally adapted Bangla version of the 36-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), which assesses six functional domains (cognition, mobility, self-care, getting along, life activities and participation) over the past 30 days and has been validated in numerous studies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Adaptation to disability was measured using the Adaptation to Disability Scale\u0026ndash;Revised (ADS-R), a validated tool widely used in disability research [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e\n\u003ch3\u003ePsychometric Validation of the Bangla ADS-R\u003c/h3\u003e\n\u003cp\u003eThe Bangla version of the Adaptation to Disability Scale-Revised (ADS-R) was translated and linguistically validated following standard procedures recommended by Beaton, as also applied in our previous study [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] (\u003cb\u003eAppendix 1\u003c/b\u003e). Content validity was assessed through the Item-Objective Congruence (IOC) index, with expert panel evaluations confirming item relevance and clarity. An item-level content validity index (I-CVI) of \u0026ge;\u0026thinsp;0.80 was considered acceptable [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], while values\u0026thinsp;\u0026ge;\u0026thinsp;0.50 were deemed suitable for a large-scale testing context [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Construct validity was evaluated using Exploratory Factor Analysis (EFA), which confirmed the underlying factor structure of the scale. Internal consistency was assessed using Cronbach\u0026rsquo;s alpha, demonstrating satisfactory reliability in this population. According to established guidelines, Cronbach\u0026rsquo;s alpha values\u0026thinsp;\u0026ge;\u0026thinsp;0.70 are acceptable, \u0026ge; 0.80 are good, and \u0026ge;\u0026thinsp;0.90 are considered excellent [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to summarize participants\u0026rsquo; demographic, psychosocial/comorbid, lifestyle, injury-related, and rehabilitation-related characteristics. To assess normality, the Kolmogorov\u0026ndash;Smirnov and Shapiro\u0026ndash;Wilk tests were performed. Based on the data distribution, inferential analyses were carried out using Chi-square tests, one-way ANOVA, and Kruskal\u0026ndash;Wallis tests to examine the relationships among participant characteristics, disability levels, and adaptation to disability. Spearman's correlation was employed to evaluate the strength and direction of relationships between key variables. Finally, a multiple regression model was used to identify significant determinants of disability adaptation in individuals with spinal cord injury (SCI). All tests were conducted with the Statistical Package for Social Science (SPSS) version 22. Significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eParticipants (Demographic, psychosocial/comorbidity, Lifestyle, Injury-related, and rehabilitation care and management)\u003c/h2\u003e\u003cp\u003eThe study included 210 individuals with spinal cord injury (SCI), with a median age of 31 years (IQR\u0026thinsp;=\u0026thinsp;17.75). Gender data from 210 participants showed 88% male and 12% female. Most participants were married (58.1%), followed by unmarried (32.9%), divorced/separated (8.1%), and widowed (0.5%). The majority (84.3%) lived in nuclear families, while 11.9% lived in multigenerational households, and 3.8% lived alone. Participants represented all eight administrative divisions of Bangladesh, with Rajshahi (19.0%), Khulna (16.7%), and Barishal (14.3%) having the highest numbers. Most (71.4%) resided in rural areas. Education levels varied, with 34.8% having completed Class 1\u0026ndash;9 education, 29.5% finishing secondary school, 17.6% having no formal education, 16.2% being college graduates, and only 1.9% being university graduates. Employment status revealed that 43.1% were unemployed due to physical illness, 26.8% were self-employed or farmers, 10% were students, and 9.1% were household workers or housewives. Before their injury, 56.7% were the primary earners for their families, 5.2% contributed financially, and 38.1% were financially dependent. Among those who contributed, 60.5% indicated that the primary earner could not manage financially without their income. Most participants (86.7%) had someone available to take over the primary earner role if needed. Post-injury, 85.7% were unable to return to their previous employment. The average monthly income before injury was approximately 120.83\u0026thinsp;\u0026plusmn;\u0026thinsp;81.66 USD, which dropped to a median of 0 USD (IQR\u0026thinsp;=\u0026thinsp;40.88 USD) after injury, with 64.3% reporting a total loss of income. Only 5.7% had pressure injuries or ulcers. Most participants (87.1%) did not engage in smoking, betel leaf chewing, or tobacco use. Regular exercise (\u0026ge;\u0026thinsp;3 days/week) was rare before injury (3.8%) but increased substantially after injury (93.3%). The median duration of injury was 36 months. Traumatic injuries accounted for 92.4%, with 7.6% being non-traumatic. Paraplegia was more common (71.9%) than tetraplegia (28.1%). Complete SCI was reported by 55.7% and incomplete by 44.3%. Manual wheelchairs were the predominant mobility aid (79%), with a minority using sticks, walkers, motorized wheelchairs, or no devices. Most participants (88.1%) received invasive medical management, while 10.5% received conservative treatment, and 1.4% underwent acute rehabilitation. The median time to first rehabilitation was 40 days post-injury. At the time of data collection, only 19% were receiving rehabilitation services; 42.9% were in their first rehab experience. The average initial rehabilitation duration was approximately 137 days. A majority (83.8%) received comprehensive multidisciplinary rehabilitation, which included physiotherapy, occupational therapy, speech-language therapy, and counseling. Nearly all (98.1%) had a history of hospitalization related to SCI. Rehabilitation referrals mainly came from doctors (76.7%), followed by former patients (15.7%) and self-referrals (2.4%). Family support for caregiving was nearly universal (98.1%), with most participants assuming caregiving roles before their injury.\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\u003eParticipants' Demographic, Psychosocial, and Comorbidity Characteristics, Lifestyle, Injury-related Rehabilitation and Medical Care Information\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eDemographic characteristics\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage (Number)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (Yrs)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian\u0026thinsp;=\u0026thinsp;31, IQR\u0026thinsp;=\u0026thinsp;17.75 \u0026ordf;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88% (n\u0026thinsp;=\u0026thinsp;184)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12% (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eMarital Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.1% (n\u0026thinsp;=\u0026thinsp;122)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnmarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.9% (n\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced/Separated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.1% (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.5% (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrefer not to disclose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.5% (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eFamily type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLives in a single-family\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e84.3% (n\u0026thinsp;=\u0026thinsp;177)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLives in a multigenerational family\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.9% (n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLives alone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.8% (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003eDivisional areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRajshahi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19% (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKhulna\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.7% (n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBarishal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.3% (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSylhet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.9% (n\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMymensingh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.9% (n\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChottogram\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10% (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRangpur\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.6% (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDhaka\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.7% (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLiving areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71.4% (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.6% (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eClass (1\u0026ndash;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.8% (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary School (SSC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.5% (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.6% (n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege level education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.2% (n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity graduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.9% (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eEmployment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed (Due to Physical illness)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.1% (n\u0026thinsp;=\u0026thinsp;90)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSelf-employed/Farming\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.8% (n\u0026thinsp;=\u0026thinsp;56)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10% (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousehold worker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.1% (n\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychosocial and Comorbidity Characteristics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePre-injury earning status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary earner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.7% (n\u0026thinsp;=\u0026thinsp;119)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFinancial contributor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.2% (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFinancially dependent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.1% (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily backup earner available\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.7% (n\u0026thinsp;=\u0026thinsp;182)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-injury employment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnable to return\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.7% (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonthly income (Pre-injury)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120.83\u0026thinsp;\u0026plusmn;\u0026thinsp;81.66 USD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonthly income (Post-injury)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 USD, IQR\u0026thinsp;=\u0026thinsp;40.88 USD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReported full income loss\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.3% (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePressure Injuries/ulcers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLifestyle factors\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePersonal habits (Smoking/betel leaf/Tobacco+\u0026hellip;others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87.1% (n\u0026thinsp;=\u0026thinsp;183)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegular exercise (pre-injury)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.8% (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegular exercise (Post-injury)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.3% (n\u0026thinsp;=\u0026thinsp;196)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInjury profile\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration since injury (Months)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian\u0026thinsp;=\u0026thinsp;36, (IQR\u0026thinsp;=\u0026thinsp;41.25)\u0026ordf;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCause of injury\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraumatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92.4% (n\u0026thinsp;=\u0026thinsp;194)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-traumatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.6% (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eLevel of lesion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParaplegia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71.9% (n\u0026thinsp;=\u0026thinsp;151)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTetraplegia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.1% (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eType of SCI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eComplete\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55.7% (n\u0026thinsp;=\u0026thinsp;117)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncomplete\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.3% (n\u0026thinsp;=\u0026thinsp;93)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAssistive device\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eManual Wheelchair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79% (n\u0026thinsp;=\u0026thinsp;166)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21% (n\u0026thinsp;=\u0026thinsp;44)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRehabilitation and management\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAcute Medical Management\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInvasive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88.1% (n\u0026thinsp;=\u0026thinsp;185)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConservative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.5% (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcute rehab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.4% (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime to first rehabilitation (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian\u0026thinsp;=\u0026thinsp;40, \u0026ordf; IQR\u0026thinsp;=\u0026thinsp;63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrently receiving rehab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19% (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst-time rehab users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.9% (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAverage duration of initial rehab (days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e137\u0026thinsp;\u0026plusmn;\u0026thinsp;55.44**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of rehab service received\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMultidisciplinary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83.8% (n\u0026thinsp;=\u0026thinsp;176)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImmediate hospitalization after SCI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eReferral source for rehab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDoctors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.7% (n\u0026thinsp;=\u0026thinsp;161)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFormer patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.7% (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSelf-referral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.4% (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers (relatives/Known/Unknown persons)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.2% (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaregiver support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamily member\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98% (n\u0026thinsp;=\u0026thinsp;206)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaregiving role pre-injury\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInvolved in caregiving for family members\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87.1% (183)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e\u0026ordf;IQR\u0026thinsp;=\u0026thinsp;Interquartile Range; ** \u0026plusmn; (SD)\u0026thinsp;=\u0026thinsp;Standard Deviation\u003c/h2\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eDisability level and association with demographic, psychosocial, lifestyle, injury-related, and rehabilitation care and management factors\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eAdaptation in SCI\u003c/h2\u003e\u003cp\u003eAmong the 210 participants, the majority (71.4%, n\u0026thinsp;=\u0026thinsp;150) reported a medium level of adaptation to disability, while 28.1% (n\u0026thinsp;=\u0026thinsp;59) exhibited a low level of adaptation. Only one participant (0.5%) demonstrated a high level of adaptation. The mean total adaptation score was 69.24\u0026thinsp;\u0026plusmn;\u0026thinsp;8.71, indicating that most participants experienced a low to medium level of acceptance of their disability. Regarding subdomain scores, the average for \u0026ldquo;Transformation from comparative status to asset values\u0026rdquo; was 20.23\u0026thinsp;\u0026plusmn;\u0026thinsp;2.93, for \u0026ldquo;Containment of disability\u0026rdquo; 17.04\u0026thinsp;\u0026plusmn;\u0026thinsp;3.84, for \u0026ldquo;Enlargement of scope of values\u0026rdquo; 24.07\u0026thinsp;\u0026plusmn;\u0026thinsp;3.30, and for \u0026ldquo;Subordination of physique\u0026rdquo; 7.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90. These subscale scores suggest that the adaptation experience was multifaceted and varied across different psychological domains.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eRelationship between adaptation and demographic, psychosocial/comorbid, lifestyle, injury-related, rehabilitation and management factors\u003c/h2\u003e\u003cp\u003eA Pearson chi-square test and one-way ANOVA were used to assess associations between categorical and continuous variables, respectively, and levels of adaptation. Significant associations were found between adaptation levels and participants' age, F(2, 205)\u0026thinsp;=\u0026thinsp;4.16, p\u0026thinsp;=\u0026thinsp;.017, with those in the low adaptation group being older (38.93\u0026thinsp;\u0026plusmn;\u0026thinsp;16.40) than those in the medium (33.27\u0026thinsp;\u0026plusmn;\u0026thinsp;10.95) and high (34) adaptation groups. Family composition (χ\u0026sup2;(4)\u0026thinsp;=\u0026thinsp;12.00, p\u0026thinsp;=\u0026thinsp;.017), division (χ\u0026sup2;(14)\u0026thinsp;=\u0026thinsp;25.03, p\u0026thinsp;=\u0026thinsp;.034), and post-injury employment status (χ\u0026sup2;(14)\u0026thinsp;=\u0026thinsp;24.40, p\u0026thinsp;=\u0026thinsp;.041) also showed significant associations. Low adaptation was more common among participants belongs to multigenerational families (44%) and those living alone (37.5%), whereas medium adaptation predominated in nuclear families (74.6%). Regionally, Rangpur had the highest rate of medium adaptation (94.4%), while Rajshahi (45%) and Mymensingh (44.4%) had the highest rates of low adaptation. Unemployment due to illness was linked to low adaptation (35.6%), while self-employed individuals (76.8%) and those involved in household responsibilities (78.9%) mostly reported medium adaptation. Gender, marital status, living area, and education were not significantly related to adaptation levels (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Among psychosocial factors, the ability to return to the pre-injury job role was significantly associated with adaptation level (χ\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;10.92, p\u0026thinsp;=\u0026thinsp;.004). Most individuals who returned to their previous jobs (96.7%) reported medium adaptation, while 32.2% of those unable to return showed low adaptation. The presence of pressure injuries approached significance (χ\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;5.78, p\u0026thinsp;=\u0026thinsp;.056), with 58.3% of those affected falling into the low adaptation group, compared to 26.3% among those without ulcers. In contrast, 73.2% of individuals without pressure ulcers exhibited medium adaptation. Post-injury monthly income also showed a significant association with adaptation level, F(2, 207)\u0026thinsp;=\u0026thinsp;3.13, p\u0026thinsp;=\u0026thinsp;.045. Participants with high adaptation reported the highest average income (57.26 USD), compared to those in the medium (24.05\u0026thinsp;\u0026plusmn;\u0026thinsp;38.29 USD) and low adaptation groups (11.93\u0026thinsp;\u0026plusmn;\u0026thinsp;23.11 USD). Although other financial variables such as pre-injury financial role, ability to manage family expenses, availability to take primary earner role, and income changes, were not significantly related to adaptation (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), individuals who previously contributed financially had the highest proportion of low adaptation (45.5%). Similarly, those with total income loss due to injury more frequently reported low adaptation (31.9%). Injury-related factors such as duration of injury, cause, and use of assistive devices were not significantly associated with adaptation in SCI. However, strong associations were found with the level of injury (χ\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;21.21, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and type of injury (χ\u0026sup2;(2)\u0026thinsp;=\u0026thinsp;8.96, p\u0026thinsp;=\u0026thinsp;.011). Individuals with tetraplegia more frequently reported low adaptation (50.8%) compared to those with paraplegia (19.2%). Similarly, participants with complete injuries had a higher prevalence of low adaptation (35.9%) than those with incomplete injuries (18.3%). Lifestyle factors showed no significant relationship with adaptation (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Among rehabilitation and medical management variables, only time to access rehabilitation services was significantly associated with adaptation, F(2, 207)\u0026thinsp;=\u0026thinsp;4.29, p\u0026thinsp;=\u0026thinsp;.015; those with low adaptation experienced longer delays (239.54\u0026thinsp;\u0026plusmn;\u0026thinsp;615.12 days) compared to the high adaptation group (mean\u0026thinsp;=\u0026thinsp;2 days).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAssociation between disability status and adaptation\u003c/h2\u003e\u003cp\u003eA one-way ANOVA was conducted to examine whether levels of disability adaptation were associated with variations in functioning among individuals with spinal cord injuries. Significant differences were found across all WHODAS 2.0 domains, including cognition, mobility, self-care, getting along, life activities, participation, and overall disability severity based on adaptation levels (p\u0026thinsp;\u0026lt;\u0026thinsp;.001 for all), indicating strong associations between disability acceptance and perceived functional ability. Participants with low acceptance had the highest disability scores (e.g., total WHODAS 2.0 score: 111.42\u0026thinsp;\u0026plusmn;\u0026thinsp;18.51). At the same time, those with high acceptance showed markedly better functioning (mean score: 56.00). The Percentage of disability severity also declined from 69.82% in the low-acceptance group to 35% in the high-acceptance group.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eFactors Correlated with Adaptation\u003c/h2\u003e\u003cp\u003eSpearman\u0026rsquo;s correlation analysis indicated significant associations between disability adaptation and various factors. A strong negative correlation was found between adaptation and WHODAS 2.0 score (r = \u0026minus;\u0026thinsp;0.614, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), indicating that higher adaptation corresponds to lower disability. Post-injury income had a positive association with adaptation (r\u0026thinsp;=\u0026thinsp;0.223, p\u0026thinsp;\u0026lt;\u0026thinsp;.01), while age was negatively associated (r = \u0026minus;\u0026thinsp;0.184, p\u0026thinsp;\u0026lt;\u0026thinsp;.01). WHODAS 2.0 scores were negatively correlated with post-injury income (r = \u0026minus;\u0026thinsp;0.318, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and positively with age (r\u0026thinsp;=\u0026thinsp;0.217, p\u0026thinsp;\u0026lt;\u0026thinsp;.01). Additionally, post-injury income correlated significantly with pre-injury income (r\u0026thinsp;=\u0026thinsp;0.406) and age (r\u0026thinsp;=\u0026thinsp;0.629), whereas delayed rehabilitation access was negatively linked to post-injury income (r = \u0026minus;\u0026thinsp;0.166, p\u0026thinsp;\u0026lt;\u0026thinsp;.05). No significant association was found between injury duration and adaptation.\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\u003eSpearman\u0026rsquo;s Correlation Between Adaptation, Disability, and Related Variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eSpearman\u0026rsquo;s r\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdaptation vs. WHODAS 2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.614**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.000*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdaptation vs Post Post-Injury Income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdaptation vs Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.184**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.008*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWHODAS 2.0 vs Post injury income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.318**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.000*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWHODAS 2.0 vs Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost injury income vs pre injury income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.000*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost injury income vs Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.000*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-injury income vs Time to access Rehab\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.166**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.016*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of injury vs Adaptation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime to First Access Rehab vs. Adaptation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.064**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.357\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e*Significant value p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **(-)\u0026thinsp;=\u0026thinsp;Negative correlation\u003c/h2\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003eDeterminants of disability adaptation in SCI\u003c/h2\u003e\u003cp\u003eA multiple linear regression analysis was performed to identify the determinants of adaptation to disability among individuals with spinal cord injury (N\u0026thinsp;=\u0026thinsp;210). The demographic model accounted for 35.3% of the variance in adaptation (F(29,177)\u0026thinsp;=\u0026thinsp;3.333, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Notably, living in a single-family was positively associated with adaptation compared to living alone (B\u0026thinsp;=\u0026thinsp;7.214, p\u0026thinsp;=\u0026thinsp;.017), while residing in the Rajshahi division predicted lower adaptation compared to living in other divisions in Bangladesh. Surprisingly, participants with graduate-level education had lower adaptation scores relative to those with no formal education (B = \u0026minus;\u0026thinsp;12.632, p\u0026thinsp;=\u0026thinsp;.009). Employment status revealed mixed effects, such as day laborers (B\u0026thinsp;=\u0026thinsp;9.080, p\u0026thinsp;=\u0026thinsp;0.004) and self-employed/farmers (B\u0026thinsp;=\u0026thinsp;5.190, p\u0026thinsp;=\u0026thinsp;0.001) exhibited higher adaptation, whereas non-profit/social workers (B=-24.726, p\u0026thinsp;=\u0026thinsp;0.003) and retirees (B=-12.606, p\u0026thinsp;=\u0026thinsp;0.007) showed lower adaptation. Psychosocial and comorbidity variables did not significantly predict adaptation overall (F(11,26)\u0026thinsp;=\u0026thinsp;1.381, p\u0026thinsp;=\u0026thinsp;.240), though higher pre-injury income was linked to poorer adaptation (B = \u0026minus;\u0026thinsp;0.001, p\u0026thinsp;=\u0026thinsp;.026). Lifestyle factors, including pre- and post-injury personal habits and exercise, were not significant predictors (F(3,206)\u0026thinsp;=\u0026thinsp;0.393, p\u0026thinsp;=\u0026thinsp;.758). Clinical and injury-related factors explained 11.4% of the variance (F(9,200)\u0026thinsp;=\u0026thinsp;2.855, p\u0026thinsp;=\u0026thinsp;.003), with paraplegia positively associated (B\u0026thinsp;=\u0026thinsp;4.035, p\u0026thinsp;=\u0026thinsp;.003) and complete injury negatively associated with adaptation (B = \u0026minus;\u0026thinsp;2.824, p\u0026thinsp;=\u0026thinsp;.038). Although none of the predictors reached statistical significance, the variable \u0026ldquo;Caregiver availability\u0026thinsp;=\u0026thinsp;Family member(s) not available to support\u0026rdquo; approached significance (B = -22.03, p\u0026thinsp;=\u0026thinsp;.053), indicating a potentially meaningful negative association with adaptation. Both severe and extreme disability levels significantly predicted lower adaptation scores compared to moderate disability. Severe disability was associated with a 5-point decrease (B = -5.047, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), while extreme disability showed a much larger negative impact (B = -15.695, p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\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\u003eSummary of Significant Predictors of Disability Adaptation in SCI\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\"\u003e\u003cp\u003ePredictors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB (Unstandardized)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStandardized Beta\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSig.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eDemographic predictors\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.764\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.683\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.402\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily Composition\u0026thinsp;=\u0026thinsp;Single family\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.303\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.412\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.017*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDivision\u0026thinsp;=\u0026thinsp;Rajshahi\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-7.348\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.012*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation\u0026thinsp;=\u0026thinsp;Graduate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-12.632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.767\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\u003e-2.650\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.009*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment\u0026thinsp;=\u0026thinsp;Day Labour\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.004*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment\u0026thinsp;=\u0026thinsp;Self-employed/Farmer\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.418\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment\u0026thinsp;=\u0026thinsp;Non-profit/Social Worker\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-24.726\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.003*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEmployment\u0026thinsp;=\u0026thinsp;Retired\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-12.606\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.733\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.007*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePsychosocial and comorbidity predictors\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.081\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMonthly Income (Pre-Injury)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.001\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\u003cp\u003e-0.543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.357\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.026*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMonthly Income Change\u0026thinsp;=\u0026thinsp;Unchanged\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-29.453\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.425\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.416\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.023*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInjury-related predictors\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69.103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22.942\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLevel of SCI\u0026thinsp;=\u0026thinsp;Paraplegia\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.324\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.209\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.003*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eType of Injury\u0026thinsp;=\u0026thinsp;Complete Injury\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.349\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.038*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRehabilitation care and management\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e89.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCaregiver Availability\u0026thinsp;=\u0026thinsp;Family Members Not Available\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-22.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.053\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDisability level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e86.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDisability Level\u0026thinsp;=\u0026thinsp;Severe Disability\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-5.047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.290\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-4.590\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDisability Level\u0026thinsp;=\u0026thinsp;Extreme Disability\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-15.695\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.567\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-10.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e* \u003cem\u003ePredictors with p\u0026thinsp;\u0026lt;\u0026thinsp;.05 were considered statistically significant; \u0026dagger; Predictors with p\u0026thinsp;\u0026lt;\u0026thinsp;.10 were considered marginally significant and retained for exploratory purposes, consistent with conventions in rehabilitation and social science research.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study explored how individuals with spinal cord injury (SCI) in Bangladesh adapt to disability, using data from 210 participants. The first aim was the linguistic validation of the Bangla version of the Adaptation to Disability Scale-Revised (ADS-R), which showed strong content validity (IOC\u0026thinsp;=\u0026thinsp;0.67\u0026ndash;1.00) and internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.85), aligning with standard thresholds [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The exploratory factor analysis showed some differences from the original four-factor structure, but the Subordination domain stayed the same. Keeping four components with eigenvalues\u0026thinsp;\u0026gt;\u0026thinsp;1 supports the tool's validity in both its design and cultural context [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The predominantly male (88%) sample with a median age of 31 reflects global trends of higher SCI risk among young men due to occupational hazards and risk behaviors, especially in low- and middle-income countries [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. A high proportion of rural participants (71.4%) reflects limited access to specialized rehabilitation, underscoring the burden on under-resourced health systems [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Participants were mostly from Rajshahi, Khulna, and Barishal, which may reflect regional referral trends and differences in accessing long-term rehabilitation, as supported in previous literature [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Trauma or violence accounted for 92.4% of SCIs, with 88.1% undergoing surgical or invasive procedures in the acute-phase treatment, consistent with global trends [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Despite intervention, 71.9% developed paraplegia and 55.7% experienced complete bowel and bladder dysfunction, reflecting severe functional impairment. A notable 8.1% were divorced, indicating the potential strain of SCI on marital relationships, echoing a previous study [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] that emphasized the need for psychosocial and marital support. Educational attainment was low, with only 1.9% being graduates. Consistent with previous research [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], low educational attainment could limit opportunities for vocational reintegration and exacerbate socioeconomic vulnerability. Besides, approximately 64.3% lost their entire income due to injury, and only 1% had access to motorized or advanced mobility aids, highlighting economic barriers to independence [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The majority of the participants with SCI (84.3%) lived in a nuclear or single-family. Before their injury, 87.1% of participants had been caregivers, and this role reversal created additional stress, particularly for those now living alone. This finding is novel in the context of SCI, as previous studies [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] highlighted the importance of family support but did not address the unique challenge of individuals transitioning from being caregivers to becoming care recipients within their families. The mean disability score (57.42\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6%) reflected that most participants experience severe to extreme disability, also highlighting significant limitations in physical functioning and daily activities, especially mobility, followed by challenges in participation in social activities, consistent with the previous literature, how SCI restricts social engagement due to physical and attitudinal barriers [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eMultifactorial Influences on Adaptation\u003c/h2\u003e\u003cp\u003eAdaptation to disability in SCI is shaped by intersecting demographic, psychosocial, injury-related, and environmental factors. Younger age significantly predicted better adaptation (r = \u0026minus;\u0026thinsp;0.184, p\u0026thinsp;=\u0026thinsp;0.008), suggesting age-related flexibility may aid adaptation. Gender showed no significant association (p\u0026thinsp;=\u0026thinsp;0.887), though females had slightly higher adaptation scores. These findings contrast with Study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which reported no age effect but found that women were better adapted. The differences may reflect contextual or cultural variations in adaptation patterns. Family structure influenced outcomes; those living in single-family adapted better than individuals living alone or in multigenerational families. This highlights clear differences, while a previous study [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] reported that family environment affects psychosocial well-being but did not clearly distinguish how family size and type influence adaptation. Geographically, adaptation was highest in Dhaka and lowest in Rajshahi, indicating unequal access to rehabilitation and community support. While rural or city residence wasn't independently significant (p\u0026thinsp;=\u0026thinsp;0.593), rural participants reported slightly better adaptation, possibly due to stronger communal bonds [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Individuals without formal education showed better adaptation than graduates, possibly due to fewer disrupted aspirations and lower psychosocial stress. This contrasts with the study [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], which found that higher education facilitates better adaptation. Similarly, study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] reported no significant effect of education, suggesting that cultural context may influence this relationship. Besides, Individuals who were the primary earners before injury exhibited lower levels of adaptation, likely due to the loss of social identity and financial stability, supporting previous evidence [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Notably, a higher pre-injury income was associated with poorer adaptation (B = \u0026minus;\u0026thinsp;0.543, p\u0026thinsp;=\u0026thinsp;0.026), indicating that the psychological impact of economic loss may be more severe for those with greater financial means. Surprisingly, individuals who retained their income after injury adapted worse than those who experienced complete income loss (p\u0026thinsp;=\u0026thinsp;0.023), possibly reflecting internal conflicts or unmet personal and social expectations. The presence of pressure injuries was marginally linked to poorer adaptation (p\u0026thinsp;=\u0026thinsp;0.056), aligning with findings of a previous study [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which reported that pressure ulcers negatively affect self-esteem and quality of life. Although personal habits such as smoking and betel leaf use did not reach statistical significance, smokers tended to show slightly lower adaptation levels, consistent with the literature [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], which reported that smoking hinders recovery. Despite high rates of participation in physical activity after injury did not significantly influence adaptation. While previous literature [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] highlighted the role of physical activity in enhancing resilience, it did not emerge as a major predictor in our analysis. In contrast, individuals with paraplegia or incomplete injuries adapted better than those with tetraplegia or complete injuries, likely due to greater functional independence. This finding contrasts with previous literature [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which reported no such association. Time since injury showed no significant effect on adaptation (p\u0026thinsp;=\u0026thinsp;0.574), supporting the conclusions of the studies [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] that psychosocial and environmental factors play a more crucial role than duration alone. However, users of advanced assistive technology often demonstrated lower adaptation levels, potentially due to poor infrastructure and environmental barriers in rural Bangladesh, which limit the practical utility of such devices [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. While not statistically significant, individuals without caregiver support showed poorer adaptation (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), reinforcing how essential caregivers are in providing stability and improving life after discharge [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eAdaptation and Psychosocial Adjustment\u003c/h2\u003e\u003cp\u003eThe average adaptation score (69.24\u0026thinsp;\u0026plusmn;\u0026thinsp;8.71) indicates a moderate acceptance of disability, although 28.1% exhibited low adaptation, suggesting a significant psychological burden. Across various areas, the lowest scores were found in Subordination of Physique and Containment of Disability, highlighting ongoing issues with body image and emotional regulation. The Containment domain showed the greatest variation (F\u0026thinsp;=\u0026thinsp;94.488, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), emphasizing its importance in evaluating psychosocial adjustment in this context (\u003cb\u003eAppendix-2\u003c/b\u003e). Adaptation scores were negatively correlated with disability scores (r = \u0026minus;\u0026thinsp;0.614, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), meaning that greater functional limitations predicted poorer adaptation, especially concerning mobility and social participation in SCI, supporting the previous statement [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], while fewer functional issues are associated with better psychosocial adaptation in SCI [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eStudy limitations\u003c/h2\u003e\u003cp\u003eThe cross-sectional design offers only a single-time snapshot, restricting understanding of how adaptation evolves over time. Although validated tools were used, reliance on self-reported data may introduce response bias or misinterpretation due to varying levels of understanding among participants. The study was also limited by the inability to ensure an equal distribution of male and female participants. These factors may influence the generalizability of the findings and highlight the need for broader, more inclusive future research\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study reveals that adapting to life with a spinal cord injury (SCI) is a complex, multifaceted process shaped by physical, emotional, social, and economic challenges. Many participants, particularly those with severe disabilities and limited access to rehabilitation, struggled to adjust. Higher levels of education and income before the injury were sometimes linked to lower levels of adaptation, possibly due to greater disruptions to personal and professional identity. In contrast, individuals involved in farming or self-employment, as well as those with strong family support, demonstrated better adjustment, highlighting the importance of flexible livelihoods and close community ties. These findings underscore the urgent need to reframe rehabilitation, not just as physical recovery but as a holistic process that addresses mental health, social inclusion, economic reintegration and quality of life. Community-based and inclusive care models are essential, particularly in resource-limited settings. By tailoring rehabilitation to local needs, empowering families and communities, and creating employment opportunities, we can help people with SCI rebuild lives filled with dignity, purpose, and independence.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure of Interest and Acknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration:\u0026nbsp;\u003c/strong\u003eI, the undersigned, declare that this manuscript is original, has not been published previously, and is not under consideration for publication elsewhere\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval:\u0026nbsp;\u003c/strong\u003eEthical approval for this study was obtained from the Ethical Review Committee of the Centre for the Rehabilitation of the Paralysed (CRP), Institutional Review Board (IRB), and subsequently accepted by the Bangladesh Health Professions Institute (BHPI). Permission to use the ADS-R questionnaire was obtained via email from the original author. Additional permission was secured from the Rehabilitation Wing Department at CRP to facilitate smooth data collection and conduct of the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eParticipation in this study was entirely voluntary, and informed consent was obtained from all participants before data collection. Participants were informed that they would not receive any direct personal benefit from the study; however, their contributions may help improve future rehabilitation processes for individuals with spinal cord injury. They were also assured of their right to withdraw from the study at any point without any consequences, should they lose interest or feel uncomfortable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding disclosures:\u0026nbsp;\u003c/strong\u003eThe study was self-funded by the authors without any external financial support \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship Contribution Statement:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMd Muid Hossain Reshad-\u0026nbsp;\u003c/strong\u003eConcept development, Methodology, Analysis, Results, writing manuscripts, Software analysis,\u003cstrong\u003e\u0026nbsp;Asma Islam-\u0026nbsp;\u003c/strong\u003eReviewing, Editing, Discussion, Conclusion, Supervision, \u003cstrong\u003eMehrin Sultana-\u0026nbsp;\u003c/strong\u003eData curating, Methodology, Reviewing discussion\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand manuscript\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eOrganizing tables and graphs, \u003cstrong\u003ePunam D Costa-\u003c/strong\u003e Review analysis, Methodology, Discussion, Conclusion \u003cstrong\u003eKamrunnnaher Koly\u003c/strong\u003e- Review, Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eData can be shared based on a reasonable request\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eThe authors would like to express their heartfelt gratitude to the faculty members of the M.Sc. in Rehabilitation Science (MRS) program at BHPI, affiliated with the University of Dhaka, for their academic guidance and encouragement throughout this study. Special thanks are due to Associate Professor Asma Islam, the principal supervisor, for her consistent support, insightful feedback, and mentorship. The authors are also deeply grateful to Professor Darlene Groomes of Oakland University, USA, for generously sharing the ADS-R questionnaire and accompanying guidelines, which played a crucial role in this research. Additionally, sincere appreciation is extended to, Centre for the Rehabilitation of the Paralysed (CRP) and the participants who made this study possible. Lastly, special thanks to the data collectors who faced numerous challenges to complete the data collection.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCoura AS, Enders BC, Franca IS, Vieira CE, Dantas DN, Menezes DJ. Ability for self-care and its association with sociodemographic factors of people with spinal cord injury. 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Autism. 2024;28(11):2685\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/13623613241285678\u003c/span\u003e\u003cspan address=\"10.1177/13623613241285678\" 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":true,"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":"spinal-cord","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"sc","sideBox":"Learn more about [Spinal Cord](http://www.nature.com/sc/)","snPcode":"41393","submissionUrl":"https://mts-sc.nature.com/cgi-bin/main.plex","title":"Spinal Cord","twitterHandle":"@journalsci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Spinal Cord Injury (SCI), Disability, Adaptation, Rehabilitation, WHODAS 2.0, ADS-R, Bangladesh","lastPublishedDoi":"10.21203/rs.3.rs-7474313/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7474313/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study design\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study explored how individuals with SCI in Bangladesh adapt to disability following rehabilitation and identified the key determinants that influence this adaptation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSetting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdaptation to disability is a complex, ongoing process shaped by personal, social, and cultural factors. While previous studies in Bangladesh have explored community reintegration and quality of life after spinal cord injury, none have specifically examined how individuals adapt to disability in the community following hospital discharge.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were recruited from the SCI follow-up database, consisting of individuals who completed their rehabilitation at the Centre for the Rehabilitation of the Paralysed (CRP) between June 2015 and June 2025, using cluster sampling across all eight divisions of Bangladesh. Data were collected through interviews using a combined questionnaire that included both semi-structured items and the validated Bangla versions of the structured WHODAS 2.0 and the Adaptation to Disability Scale-Revised (ADS-R)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 210 adults, most participants (71.4%) showed moderate adaptation, while 28.1% had low adaptation and only 0.5% had high adaptation. Poor adaptation was associated with complete injuries, tetraplegia, unemployment, pressure ulcers, and delays in starting rehabilitation. Surprisingly, higher education did not always support emotional adjustment. Early rehabilitation, steady income, and family support emerged as key enablers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMany individuals with SCI in Bangladesh continue to struggle with adaptation. Timely rehabilitation, emotional support, and better access to income-generating opportunities are vital for improving long-term adaptation to disability\u003c/p\u003e","manuscriptTitle":"Determinants of Disability Adaptation Following Rehabilitation in Individuals with Spinal Cord Injury in Bangladesh: A 6-Month to 10-Year Post-Injury Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-01 10:39:46","doi":"10.21203/rs.3.rs-7474313/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-01-16T21:53:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-20T09:47:55+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-12T16:07:03+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-11-12T04:24:54+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-11-12T02:58:49+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-25T07:05:45+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-09-30T05:10:46+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-09-23T11:35:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-16T17:06:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T15:54:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Spinal Cord","date":"2025-09-02T07:02:25+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-09-01T18:24:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"spinal-cord","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"sc","sideBox":"Learn more about [Spinal Cord](http://www.nature.com/sc/)","snPcode":"41393","submissionUrl":"https://mts-sc.nature.com/cgi-bin/main.plex","title":"Spinal Cord","twitterHandle":"@journalsci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"bd136fe4-47e3-4304-bac9-bf89506ccd9e","owner":[],"postedDate":"September 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":53805184,"name":"Health sciences/Neurology"},{"id":53805185,"name":"Biological sciences/Neuroscience/Cognitive neuroscience/Perception"}],"tags":[],"updatedAt":"2026-03-15T21:55:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-01 10:39:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7474313","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7474313","identity":"rs-7474313","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}