The ability to self-manage and problem solve effectively is an important component of managing chronic conditions. For individuals with limb loss, problem solving the fit of their prosthetic socket is crucial to being able to functionally ambulate with a prosthetic leg. This study evaluates and compares two innovative problem-solving tools designed to empower prosthesis wearers in self-managing their socket fit.
Fourteen paper-based problem-solving decision trees were integrated into a mobile health app displayed on an iPad. Thirty prosthesis wearers performed a total of six trials split between the two conditions (paper-based and mobile app).Technical effectiveness, efficiency, and acceptability were assessed during and after participants used each tool to problem solve real-life scenarios. Technical effectiveness was a measure of the number of errors, whereas efficiency was a measure of the amount of time needed to complete each trial. Acceptability was measured using Likert-like questionnaires and semistructured interviews.
Results demonstrated significantly better efficiency (paper-based = 124.22 seconds on average, app = 108.76 seconds; P = 0.0076) and technical effectiveness (paper-based = 0.66 errors on average, app = 0.2 errors; P < 0.001) for the app. Age and education were correlated with the outcomes.
The mobile app demonstrated significantly better outcomes as compared with the paper-based decision trees. Both the mobile app and paper-based tool had high acceptability; however, the mobile app was found to be significantly easier to use and less confusing than the paper-based version of the decision trees. Further study is required to assess the efficacy of the decision trees to manage a prosthetic fit issue in an individual who is currently having difficult managing a prosthetic socket fit issue.
DANIEL JOSEPH LEE, PT, DPT, GCS, and ADAM D. GOODWORTH, PhD, are affiliated with the University of Hartford, Hartford, Connecticut.
DIANA A. VENERI, PT, EdD, NCS, is affiliated with Sacred Heart University, Fairfield, Connecticut.
Funding: This research study was funded by an internal grant from the University of Hartford.
Disclosures: Daniel Lee owns the intellectual property associated with the unidentified mobile app. The other authors have no conflicts to disclose.
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF version of this article on the journal's Web site (https://journals.lww.com/jpojournal/pages/default.aspx).
Correspondence to: Daniel Joseph Lee, PT, DPT, GCS, University of Hartford, 200 Bloomfield Ave, Dana Hall 312A West, Hartford, CT 06117; email: email@example.com