Abstract
OBJECTIVE: eHealth-mediated interventions have been proposed as one option to support self-management in those with musculoskeletal disorders (MSDs). This scoping review aimed to chart the evidence regarding eHealth modalities, musculoskeletal diagnosis, and outcomes of eHealth-mediated self-management support interventions in persons with MSDs and identify any gaps within the literature. METHODS: Six electronic databases (MEDLINE, CINAHL, PsycINFO, Embase, Scopus, and the Cochrane Database of Systematic Reviews), 7 grey literature sources (eg, OpenGrey), and reference and citation lists of included studies were searched from database inception to July 2020. Published studies of adult participants with a MSD utilizing an eHealth intervention to support self-management were included. Studies were limited to those published in English. Two reviewers independently screened all studies. Data were extracted by 1 reviewer and reviewed by another reviewer. RESULTS: After screening 3377 titles and abstracts followed by 176 full texts, 87 studies fulfilled the eligibility criteria. The majority were published in the last 5 years (n = 48; 55%), with almost one-third originating in the United States (n = 28; 32%). The most common eHealth modality type was internet based (n = 22; 35%), with almost one-half (n = 41; 47%) of the included studies involving participants with widespread musculoskeletal symptoms. The most commonly reported outcomes were related to body functions (ie, pain intensity) (n = 67; 45%), closely followed by activities and participation (ie, function) (n = 65; 44%), with environmental factors (ie, health care utilization) the least commonly reported (n = 17; 20%). CONCLUSIONS: There is considerable variation within the eHealth-mediated self-management support intervention literature. Research is needed on the role of eHealth-mediated self-management support interventions across a broad range of MSDs to guide clinical practice. IMPACT: This scoping review has identified gaps in the literature relating to specific eHealth modalities, musculoskeletal diagnoses, and health care utilization data, which should guide future research.