Development and Usability Testing of a Web-Based and Therapist-Assisted Coping Skills Program for Managing Psychosocial Problems in Individuals With Hand and Upper Limb Injuries: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Ineffective coping has been linked to prolonged pain, distress, anxiety, and depression after a hand and upper limb injury. Evidence shows that interventions based on cognitive behavioral therapy (CBT) may be effective in improving treatment outcomes, but traditional psychological interventions are resource intensive and unrealistic in busy hand therapy practices. Developing web-based, evidence-based psychological interventions specifically for hand therapy may be feasible in clinical practice and at home with reduced training and travel costs. Hand Therapy Online Coping Skills (HOCOS) is a program developed to supplement traditional hand therapy with therapist-assisted coping skills training based on principles from CBT and the Technology Acceptance Model. OBJECTIVE: This study aimed to describe the development and assess the usability of HOCOS to support hand therapists in the management of psychosocial problems. METHODS: The ADDIE model (Analysis, Design, Development, Implementation, and Evaluation) of system design was applied to create HOCOS. The usability testing of HOCOS involved a 2-stage process. In the first step, heuristic testing with information and communications technology (ICT) experts was completed using two sets of heuristics: Monkman heuristics and the Health Literacy Online (HLO) checklist. The second step involved user testing with hand therapists performing a series of online and face-to-face activities, completing 12 tasks on the website using the think-aloud protocol, completing the system usability scale (SUS) questionnaire, and a semistructured feedback interview in 2 iterative cycles. Descriptive statistics and content analyses were used to organize the data. RESULTS: In total, 4 ICT experts and 12 therapists completed usability testing. The heuristic evaluation revealed 15 of 35 violations on the HLO checklist and 5 of 11 violations on the Monkman heuristics. Initially, hand therapists found 5 tasks to be difficult but were able to complete all 12 tasks after the second cycle of testing. The cognitive interview findings were organized into 6 themes: task performance, navigation, design esthetics, content, functionality and features, and desire for future use. Usability issues identified were addressed in two iterative cycles. There was good agreement on all items of the SUS. Overall, therapists found that HOCOS was a detailed and helpful learning resource for therapists and patients. CONCLUSIONS: We describe the development and usability testing of HOCOS; a new web-based psychosocial intervention for individuals with a hand and upper limb injuries. HOCOS targets psychosocial problems linked to prolonged pain and disability by increasing access to therapist-guided coping skills training. We actively involved target users in the development and usability evaluation of the website. The final website was modified to meet the needs and preferences of the participants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".