METHODS: The initial proposals were based on 5 main areas of PRM research: biosciences in rehabilitation, biomedical rehabilitation sciences and engineering, clinical PRM sciences, integrative rehabilitation sciences, and human functioning sciences. This list became a model for structuring the abstracts for the 9th and 10th World Congresses of PRM, held in Berlin, Germany (2015) and Kuala Lumpur, Malaysia (2016), respectively. The next step was to evaluate the implementation of this model in both congresses.
RESULTS: It was found that the 5 main research areas were still used as the main principles (chapters) in which to organize the abstracts. However, some modifications have been made to cover topics that were not included in the initial proposal.
CONCLUSION: A more comprehensive list of topics has been developed, not only for topic list announcements, but also for the structuring and classification of abstracts for future international, regional or national PRM congresses.
METHODS: Secondary data for 9,850 participants were obtained from the Social Security Organisation Return To Work database. The dependent variable was the Return To Work programme outcome, successful return to employment (same employer or different employer) or unsuccessful return. Logistic regression analysis with weighted sum contrasts was performed to assess the odds ratios with 95% confidence interval (95% CI) for successful return to employment across the various subgroups of participants.
RESULTS: Overall, 65.5% of participants successfully returned to employment, either with their former employers or with new employers. Successful return to employment was found to be significantly higher than the overall proportion among those participants who had had commuting accidents, followed by those who had had workplace accidents. Successful return to employment was also associated with injuries of the upper and lower limbs, employers who were interested in hiring disabled workers, motivation to participate in the programme, an intervention period of 3 months or less, age 29 years or younger, and male participants.
CONCLUSION: A structured multidisciplinary intervention programme provides a positive outcome in terms of returning to work. Related factors have various impacts on successful return to work.
METHODS: A cross-sectional pilot survey (Pakistan, Morocco, Nigeria, Malaysia) of health professionals' working in rehabilitation in hospital and community settings. A situational-analysis survey captured assessment of clinical skills required in various rehabilitation settings. Responses were coded in a line-by-line process, and linked to categories in domains of the International Classification of Functioning, Disability and Health (ICF).
RESULTS: Respondents (n = 532) from Pakistan 248, Nigeria 159, Morocco 93 and Malaysia 32 included the following: physiotherapists (52.8%), nurses (8.8%), speech (5.3%) and occupational therapists (8.5%), rehabilitation physicians (3.8%), other doctors (5.5%) and prosthetist/orthotists (1.5%). The 10 commonly used clinical skills reported were prescription of: physical activity, medications, transfer-techniques, daily-living activities, patient/carer education, diagnosis/screening, behaviour/cognitive interventions, comprehensive patient-care, referrals, assessments and collaboration. There was significant overlap in skills listed irrespective of profession. Most responses linked with ICF categories in activities/participation and personal factors.
CONCLUSION: The core skills identified reflect general rehabilitation practice and a task-shifting approach, to address shortages of health workers in low-and middle-income countries.
SUBJECTS: Patients who were admitted to the University of Malaya Medical Centre due to cardiac events.
METHODS: Eight different machine learning models were evaluated. The models included 3 different sets of features: full features; significant features from multiple logistic regression; and features selected from recursive feature extraction technique. The performance of the prediction models with each set of features was compared.
RESULTS: The AdaBoost model with the top 20 features obtained the highest performance score of 92.4% (area under the curve; AUC) compared with other prediction models.
CONCLUSION: The findings showed the potential of using machine learning models to predict return to work after cardiac rehabilitation.
DESIGN: This cross-sectional study recruited adults aged 50 and above by convenient sampling and grouped them into: knee osteoarthritis-diabetes-, knee osteoarthritis+diabetes-, knee osteoarthritis-diabetes+, and knee osteoarthritis+diabetes+.
SUBJECTS/PATIENTS: Of 436 recruited participants, 261 (59.8%) participants reported knee osteoarthritis.
METHODS: Handgrip strength, Timed Up and Go test, 6 Meter Walk Test, and 5 Times Sit to Stand Test were measured using standardized procedures. Six questionnaires were administered for the remaining parameters.
RESULTS: Across groups, there were significant differences: 6 Meter Walk Test (p = 0.024), Timed Up and Go test (p = 0.020), and 5 Times Sit to Stand Test (p
METHODS: The collaboration integrates HUMS's academic and clinical strengths with JKNS's existing rehabilitation services. Key components include developing postgraduate training for rehabilitation medicine, expanding community-based rehabilitation outreach services, and establishing a referral network between hospitals and community healthcare providers.
RESULTS: The partnership has resulted in the implementation of a comprehensive framework that enhances academic capacity, fosters research collaboration, and improves rehabilitation service delivery across Sabah. This approach is aligned with the WHO's Rehabilitation 2030 initiative, advocating for stronger integration of rehabilitation into healthcare systems.
CONCLUSION: The collaborative efforts between HUMS and JKNS demonstrate the critical role of partnerships between academic institutions and public health departments in strengthening rehabilitation services. This model offers a replicable strategy for influencing policy development and ensuring resource allocation to meet the growing rehabilitation needs in underserved regions.
METHODS: This cross-sectional study utilized the International Spinal Cord Injury (InSCI) Community Survey and involved 8 hospitals and 1 spinal cord injury organization. A total of 285 participants met the inclusion criteria. Subsequently, 6/11 sections of the InSCI questionnaire were analysed through a path analysis.
RESULTS: The 3 most utilized healthcare providers reported were physical and rehabilitation medicine specialists (76.5%), physiotherapists (36.8%), and primary care physicians (27.4%). The top 3 most severe health problems reported were sexual dysfunction, muscle spasm and spasticity, and contractures. Healthcare services satisfaction was high. Health problems predicted healthcare utilization (β = 0.443), while activity limitation and participation restriction predicted healthcare services satisfaction (β = -0.202). The activity limitation and participation restriction in male participants was moderated by the spinal cord injury severity (B = 2.330, p