A Qualitative Study Exploring Facilitators for Improved Health Behaviors and Health Behavior Programs: Mental Health Service Users’ Perspectives
Bibliographic record
Abstract
OBJECTIVE: Mental health service users experience high rates of cardiometabolic disorders and have a 20-25% shorter life expectancy than the general population from such disorders. Clinician-led health behavior programs have shown moderate improvements, for mental health service users, in managing aspects of cardiometabolic disorders. This study sought to potentially enhance health initiatives by exploring (1) facilitators that help mental health service users engage in better health behaviors and (2) the types of health programs mental health service users want to develop. METHODS: A qualitative study utilizing focus groups was conducted with 37 mental health service users attending a psychosocial rehabilitation center, in Northern British Columbia, Canada. RESULTS: Four major facilitator themes were identified: (1) factors of empowerment, self-value, and personal growth; (2) the need for social support; (3) pragmatic aspects of motivation and planning; and (4) access. Participants believed that engaging with programs of physical activity, nutrition, creativity, and illness support would motivate them to live more healthily. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Being able to contribute to health behavior programs, feeling valued and able to experience personal growth are vital factors to engage mental health service users in health programs. Clinicians and health care policy makers need to account for these considerations to improve success of health improvement initiatives for this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".