A meaningful focus: Investigating the impact of involvement in a participatory video program on the recovery of participants with severe mental illness.
Bibliographic record
Abstract
OBJECTIVE: The overall aim of the present paper is to elicit the subjective perceptions and experiences of people with Severe Mental Illness (SMI) involved in a Participatory Video project, with a focus on self-reported impact on recovery. There are 2 subobjectives, namely (a) to document which specific aspects (if any) of Participatory Video project participation are reported to positively influence recovery; and (b) to assess the impact of project involvement on specific dimensions of recovery. METHOD: = 20) took part in an in-depth semistructured qualitative interview at project end to understand their experience in the project, especially impact on recovery. Data was analyzed using thematic analysis techniques. RESULTS: At completion, participants had made 26 videos and organized 49 community screenings reaching over 1,500 people. Participants reported that regular involvement in this project fostered their recovery in a variety of ways, imparting multiple psychosocial benefits, which are summarized in 5 themes: (a) skill-acquisition, (b) platform and voice, (c) connectedness, (d) a meaningful focus, and (e) personal development. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Participatory Video is a powerful group intervention which positively benefits workgroup participants. Importantly, results overlap with other research indicating that grassroots-produced mental health themed videos can educate viewers and reduce public stigma. As such, psychiatric rehabilitation organizations should consider initiating similar projects in their own locales. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".