Use of an iPad App (Aid for Decision-making in Occupational Choice) for Collaborative Goal Setting in Interprofessional Rehabilitation: Qualitative Descriptive Study
Bibliographic record
Abstract
BACKGROUND: Goal setting is a key part of the rehabilitation process. The use of technology and electronic tools such as smartphone apps and websites has been suggested as a way of improving the engagement of users in meaningful goal setting and facilitating shared decision-making between patients and health professionals. OBJECTIVE: This study aims to describe experiences of health professionals and patients in the use of the English language version of the iPad app Aid for Decision-making in Occupational Choice (ADOC) to facilitate collaborative goal setting in rehabilitation. METHODS: We recruited participants from 3 acute and postacute care rehabilitation wards in both public and private organizations in New Zealand. Participants were registered allied health professionals, including physiotherapists, occupational therapists, and speech-language therapists, who engage in goal setting as part of their normal work, and their adult patients. We collected data via semistructured interviews to gather information about the experiences of the participants in the use of ADOC for goal setting. Data were analyzed with thematic analysis. RESULTS: A total of 8 health professionals and 8 patients participated in the study. Six main themes emerged from the data: changing patients' perspective on what is possible, changing health professionals' perspective on what is important, facilitating shared decision-making, lack of guides for users, logistic and organizational barriers, and app-related and technical issues. CONCLUSIONS: Health professionals and patients found ADOC to be a valuable tool when setting shared rehabilitation goals. The use of ADOC promoted a patient-centered approach that empowered patients to engage in collaborative goal setting. The technological limitations of the app that negatively impacted experiences can be addressed in the future implementation of ADOC in rehabilitation settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".