Improving Self-Management Skills Among People With Spinal Cord Injury: Protocol for a Mixed-Methods Study

Abstract

BackgroundMost people with spinal cord injury will develop secondary complications with potentially devastating consequences. Self-management is a key prevention strategy for averting the development of secondary complications and their recurrence. Several studies have shown that self-management programs improve self-management behaviors and health outcomes in individuals living with chronic conditions such as asthma, diabetes, hypertension, and arthritis. Given the burgeoning health care costs related to secondary complications, we developed an alternative electronic health–based implementation to facilitate the development of self-management skills among people with spinal cord injury.ObjectiveThis study aims to evaluate the efficacy of a self-management app in spinal cord injury populations. The primary outcome is attainment of self-selected, self-management goals. Secondary outcomes include increases in general and self-management self-efficacy and reductions in self-reported health events, health care utilization, and secondary complications related to spinal cord injury. This study also aims to explore how the intervention was implemented and how the app was experienced by end users.MethodsThis study will employ a mix of qualitative and quantitative methods. The quantitative portion of our study will involve a rater-blinded, randomized controlled trial with a stepped wedge design (ie, delayed intervention control group). The primary outcome is successful goal attainment, and secondary outcomes include increases in self-efficacy and reductions in self-reported health events, health care utilization, and secondary conditions related to spinal cord injury. The qualitative portion will consist of semistructured interviews with a subsample of the participants.ResultsWe expect that the mobile self-management app will help people with spinal cord injury to attain their self-management goals, improve their self-efficacy, reduce secondary complications, and decrease health care utilization.ConclusionsIf the results are positive, this study will produce credible new knowledge describing multiple outcomes that people with spinal cord injury realize from an app-based self-management intervention and support its implementation in clinical practice.Trial RegistrationClinicalTrials.gov NCT03140501; http://clinicaltrials.gov/ct2/show/NCT03140501 (Archived by WebCite at http://www.webcitation.org/73Gw0ZlWZ)International Registered Report Identifier (IRRID)PRR1-10.2196/11069

Mobile Health Self-management Support for Spinal Cord Injury: Systematic Literature Review

“…The 24 included publications comprised 20 (83%) studies [ 36 , 37 , 40 , 42 - 57 , 59 ], 3 (12%) reports [ 38 , 39 , 58 ], and 1 (4%) protocol paper [ 41 ] (Table S1 Multimedia Appendix 3 ). The included publications primarily aimed to describe and develop mHealth tools (10/24, 42%) [ 38 , 39 , 43 , 45 , 46 , 48 , 54 , 56 - 58 ], evaluate implementation factors (9/24, 38%) [ 37 , 40 , 45 , 46 , 49 , 50 , 54 , 55 , 57 ], evaluate usability and user experience (7/24, 29%) [ 45 - 48 , 52 - 54 ] and effectiveness (6/24, 25%) [ 36 , 41 , 42 , 44 , 51 , 54 ], and describe stakeholder perspectives (1/24, 4%). The included publications were published between 2015 and 2022, and most (18/24, 75%) were published from 2018 onward [ 41 - 57 , 59 ].…”

“…The included publications primarily aimed to describe and develop mHealth tools (10/24, 42%) [ 38 , 39 , 43 , 45 , 46 , 48 , 54 , 56 - 58 ], evaluate implementation factors (9/24, 38%) [ 37 , 40 , 45 , 46 , 49 , 50 , 54 , 55 , 57 ], evaluate usability and user experience (7/24, 29%) [ 45 - 48 , 52 - 54 ] and effectiveness (6/24, 25%) [ 36 , 41 , 42 , 44 , 51 , 54 ], and describe stakeholder perspectives (1/24, 4%). The included publications were published between 2015 and 2022, and most (18/24, 75%) were published from 2018 onward [ 41 - 57 , 59 ]. The research teams were mainly based in North America (15/24, 62%) [ 38 , 40 - 42 , 44 - 47 , 50 , 52 , 53 , 55 , 56 , 58 , 59 ], followed by Europe (6/24, 25%) [ 36 , 37 , 48 , 49 , 54 , 57 ], Asia (2/24, 8%) [ 43 , 51 ], and Europe and Asia (1/24, 4%) [ 39 ].…”

“…A total of 19 mHealth tools were identified ( Table 1 and Table S2 Multimedia Appendix 3 ). In total, 4% (1/24) of the publications focused on 2 tools [ 37 ], 12% (3/24) focused on 1 tool [ 41 , 47 , 50 ], and 2 sets of 2 focused on 1 tool equally (2/24, 8%) [ 40 , 48 , 49 , 58 ]. In total, 4 tools were unnamed (4/24, 17%) [ 38 , 40 , 43 , 48 , 49 ].…”

“…In total, 4 tools were unnamed (4/24, 17%) [ 38 , 40 , 43 , 48 , 49 ]. The included publications documented mHealth tools mainly at their testing stage (10/19, 53%) [ 36 , 40 , 43 - 45 , 47 , 50 - 52 , 54 , 55 , 58 ], followed by the developmental (6/19, 32%) [ 38 , 39 , 41 , 46 , 48 , 56 , 59 ], proof-of-concept (3/19, 16%) [ 37 , 42 , 49 ], proposal (1/19, 5%) [ 57 ], and launch (1/19, 5%) [ 53 ] stages.…”

“…The primary technologies used were apps (16/19, 84%) [ 37 - 39 , 41 - 55 , 57 , 59 ], mobile-optimized websites (2/19, 11%) [ 40 , 56 , 58 ], and a glove (ie, wearable; 1/19, 5%) [ 36 ]. These technologies were mainly connected to mobile phones (10/19, 53%) [ 39 , 42 - 44 , 46 , 48 , 49 , 51 , 53 , 54 , 57 ], followed by tablets (7/19, 37%) [ 37 , 39 , 41 , 45 , 47 , 50 , 52 , 54 , 55 ], unspecified mobile devices (4/19, 21%) [ 36 , 38 , 40 , 56 , 58 ], pressure mats (2/19, 11%) [ 46 , 53 ], smartwatches (ie, wearable; 2/19, 11%) [ 42 , 55 ], smart garments (ie, wearable; 1/19, 5%) [ 39 ], and Raspberry Pi (1/19, 5%) [ 46 ].…”