Urban-Rural Disparities in Community Participation after Spinal Cord Injury in Ontario

被引:0
作者
Amiri, Mohammadreza [1 ,2 ]
Alavinia, Mohammad [2 ]
Farahani, Farnoosh [2 ]
Khasiyeva, Natavan [3 ]
Burley, Meredith [3 ]
Kangatharan, Suban [2 ]
Craven, Beverley Catharine [2 ,4 ,5 ]
机构
[1] Univ Queensland, Ctr Business & Econ Hlth, St Lucia, Qld 4072, Australia
[2] Univ Hlth Network, KITE Res Inst, Toronto, ON M5G 2A2, Canada
[3] Spinal Cord Injury Ontario, Toronto, ON M4G 3V9, Canada
[4] Univ Toronto, Temerty Fac Med, Dept Med, Div Phys Med & Rehabil, Toronto, ON M5S 3H2, Canada
[5] Univ Toronto, Inst Hlth Policy Management & Evaluat, Toronto, ON M5S 1B2, Canada
关键词
spinal cord injury or disease (SCI/D); community participation; Moorong Self-Efficacy Scale (MSES); Reintegration to Normal Living Index (RNLI); artificial intelligence; optical mark recognition (OMR); NORMAL LIVING INDEX; SELF-EFFICACY; PSYCHOMETRIC VALIDATION; NEUROLOGICAL CLASSIFICATION; INTERNATIONAL STANDARDS; ENVIRONMENTAL BARRIERS; PEOPLE; HEALTH; IMPACT; REINTEGRATION;
D O I
10.3390/healthcare12202089
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Personal, social, and environmental factors may influence self-efficacy and social reintegration among people living with spinal cord injury or disease (SCI/D) in urban and rural areas. Novel data collection methods have the potential to characterize community participation (CP) in diverse settings. Objectives: The objectives were (1) to describe and compare self-reported community participation (Reintegration to Normal Living Index (RNLI) and Moorong Self-Efficacy Scale (MSES)) levels of individuals with SCI/D living in urban or rural Ontario, Canada; and (2) to determine the accuracy of an artificial intelligence (AI) optical mark recognition tool for extracting data from CP surveys conducted among participants after transitioning from inpatient rehabilitation to home and residing in the community. Methods: We partnered with SCI Ontario staff to collect MSES and RNLI survey data from adults with motor complete (e.g., AIS A-B) and incomplete (AIS C-D) SCI/D living in urban or rural Ontario, Canada, between January and October 2022. The Rurality Index of Ontario (RIO) from the postal code determined urban or rural residency. Optical mark recognition (OMR) software was used for survey data extraction. A Research Associate validated the extracted survey responses. Descriptive statistics, correlation analysis, and non-parametric statistics were used to describe the participants, their impairments, and their reported CP levels across urban and rural settings. Results: Eighty-five individuals with SCI/D (mean age 53.7 years, 36.5% female) completed the survey. Most of the participants resided in major urban areas (69.4%) and had traumatic injuries (64.7%). The mean total MSES score for Ontarians with SCI/D was 87.96 (95% confidence interval [CI]: 84.45, 91.47), while the mean total RNLI score for the same individuals was 75.61 (95% CI: 71.85, 79.37). Among the MSES domains, the lowest score was observed in response to sexual satisfaction (mean: 4.012, 95% CI: 3.527, 4.497), while the lowest RNLI domain item score was associated with the ability to travel out of town (mean: 5.965, 95% CI: 5.252, 6.678). Individuals with incomplete injuries in rural areas reported lower MSES and RNLI scores than those with complete motor injuries, whereas no significant differences were found in MSES and RNLI scores among urban residents based on impairment. These findings suggest that, depending on the environmental context (e.g., rural vs. urban areas), AIS categories may influence the perception of CP among people living with SCI/D. The OMR tool had 97.4% accuracy in extracting data from the surveys. Conclusions: The CP (MSES and RNLI) scores reported by individuals with SCI/D differ based on their living setting. In rural Ontario, individuals with greater functional ability reported lower CP than their counterparts living in urban settings. Although CP remains a challenge, the needs of individuals with motor incomplete SCI/D and heterogeneous levels of mobility residing in rural areas require exploration and targeted interventions. The OMR tool facilitates accurate data extraction from surveys across settings.
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共 56 条
  • [41] Residential location of people with chronic spinal cord injury: the importance of local health care infrastructure
    Ronca, Elias
    Brunkert, Thekla
    Koch, Hans Georg
    Jordan, Xavier
    Gemperli, Armin
    [J]. BMC HEALTH SERVICES RESEARCH, 2018, 18
  • [42] Computer Implementation of the International Standards for Neurological Classification of Spinal Cord Injury for Consistent and Efficient Derivation of Its Subscores Including Handling of Data from Not Testable Segments
    Schuld, Christian
    Wiese, Julia
    Hug, Andreas
    Putz, Cornelia
    van Hedel, Hubertus J. A.
    Spiess, Martina R.
    Weidner, Norbert
    Rupp, Ruediger
    [J]. JOURNAL OF NEUROTRAUMA, 2012, 29 (03) : 453 - 461
  • [43] Impact of Surgical Timing and Approaches to Health Care Utilization in Patients Undergoing Surgery for Acute Traumatic Cervical Spinal Cord Injury
    Sharma, Mayur
    Dietz, Nicholas
    Ugiliweneza, Beatrice
    Wang, Dengzhi
    Khattar, Nicolas
    Adams, Shawn W.
    Ball, Tyler
    Boakye, Maxwell
    [J]. CUREUS JOURNAL OF MEDICAL SCIENCE, 2019, 11 (11)
  • [44] From basics to clinical: A comprehensive review on spinal cord injury
    Silva, Nuno A.
    Sousa, Nuno
    Reis, Rui L.
    Salgado, Antonio J.
    [J]. PROGRESS IN NEUROBIOLOGY, 2014, 114 : 25 - 57
  • [45] Spinal Cord Injury Implementation Evaluation and Quality Care Consortium (SCI-IEQCC), 2023, About us
  • [46] Spinal Cord Injury Ontario (SCIO), About SCIO: Serving the community for over 75 years
  • [47] Guidelines for the conduct of clinical trials for spinal cord injury (SCI) as developed by the ICCP panel: clinical trial outcome measures
    Steeves, J. D.
    Lammertse, D.
    Curt, A.
    Fawcett, J. W.
    Tuszynski, M. H.
    Ditunno, J. F.
    Ellaway, P. H.
    Fehlings, M. G.
    Guest, J. D.
    Kleitman, N.
    Bartlett, P. F.
    Blight, A. R.
    Blight, A. R.
    Dietz, V.
    Dobkin, B. H.
    Grossman, R.
    Short, D.
    Nakamura, M.
    Coleman, W. P.
    Gaviria, M.
    Privat, A.
    [J]. SPINAL CORD, 2007, 45 (03) : 206 - 221
  • [48] PREDICTING COMMUNITY PARTICIPATION AFTER SPINAL CORD INJURY IN THAILAND
    Suttiwong, Jatuporn
    Vongsirinavarat, Mantana
    Chaiyawat, Pakaratee
    Vachalathiti, Roongtiwa
    [J]. JOURNAL OF REHABILITATION MEDICINE, 2015, 47 (04) : 325 - 329
  • [49] Svestkova O, 2008, Prague Med Rep, V109, P268
  • [50] Social Integration Among Adults Aging With Spinal Cord Injury: The Role of Features in the Built and Natural Environment
    Tan, Nasya
    Forchheimer, Martin
    Tate, Denise G.
    Meade, Michelle A.
    Reber, Lisa
    Clarke, Philippa J.
    [J]. JOURNAL OF AGING AND ENVIRONMENT, 2024, 38 (03): : 275 - 289