Clinical utility, validity and reliability of the IPad application for goal-setting: The aid for decision-making in occupation choice-2
Bibliographic record
Abstract
ObjectiveTo evaluate the clinical utility, reliability, and validity of the second-generation aid for decision-making in occupation choice-2 (ADOC2), an iPad application designed for client-centred and occupation-centred goal setting.DesignThis study consisted of two components: (1) The development and refinement of the ADOC2 application, focusing on user interface design and structured goal-setting functionality; and (2) the clinical evaluation of its utility, validity, and reliability.SettingEleven rehabilitation facilities in Japan (10 hospitals, 1 home-based setting).ParticipantsA total of 116 occupational therapy clients and 56 occupational therapists participated in the study.Main measuresClinical utility was assessed using a structured questionnaire previously validated for the original ADOC. Validity was examined through correlations with the Canadian Occupational Performance Measure (COPM) and the EuroQol 5-Dimension 5-Level (EQ-5D-5L). Test-retest reliability of satisfaction and performance scores was analysed using weighted kappa coefficients.ResultsOver 90% of participants reported positive experiences with ADOC2 during the goal-setting process. The COPM scores showed strong correlations with ADOC2 ratings, while EQ-5D-5L scores showed weaker but expected correlations. Weighted kappa analyses indicated substantial to almost perfect agreement for test-retest reliability.ConclusionsADOC2 is a clinically useful, valid, and reliable tool for facilitating client-centred goal setting in occupational therapy practice.
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".