Contributions of a time use perspective in community mental health practice: a scoping review
Bibliographic record
Abstract
Introduction: Time use is an important indicator of health and well-being. Exploration of time use can provide in-depth information about individuals' activity patterns including routines and structure, the experience of activities, personal priorities and challenges. People experiencing severe mental illness may be at particular risk for time use patterns associated with poor health and wellbeing. Methods: This scoping review aimed to identify and map the evidence about how a time use perspective informs assessment and intervention in community mental health practice. Electronic databases and hand-searches were used to identify relevant studies involving people with severe mental illness, and focused on time use applications in practice. Twenty-nine studies were included in this review, data-extracted and synthesized with reference to the review question. Results: Of the twenty-nine identified studies, seven described development and psychometric testing of time use assessments; twelve used time use tools to measure outcomes; and ten described or evaluated time use intervention approaches. The identified time use assessments typically involved retrospective diaries completed before or during structured interviews, and an Experience Sampling Method using smart technology to gather activity data in real time. Both psychosocial and occupational interventions used time use to measure outcomes relevant to activity engagement, social functioning, and personal recovery. The identified time use interventions originated in occupational therapy; included structured manuals and workbooks to enable reflection on daily time use; individual or group sessions to collaborate in identifying priorities, goal planning and supporting desired changes to activity patterns. These interventions were viewed favorably overall, with improved activity engagement, quality of life, and personal recovery reported. Discussion: Time use assessments evaluate outcomes of importance to personal recovery and community inclusion. Time use interventions address activity patterns associated with poor health and wellbeing, using collaborative and supported activity engagement approaches, and contribute to emerging evidence on interventions that support personal recovery. Furthering peer involvement in developing and delivering these interventions will bring important insights to time use practice and research, while the social forces that marginalize or constrain activity participation for people with severe mental illness also need to be addressed to advance time use and other approaches that aim to support community inclusion.
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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 | 0.035 | 0.136 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.031 | 0.033 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".