The Online Citizens Project: Effects oftransitional peer support groups facilitated by peer support workers for persons living with severe mental illness in times of the Covid-19 pandemic
Bibliographic record
Abstract
From August to November 2020, the Online Citizens Project has been offered as a transitional peer support group to persons living with Serious Mental Illness (SMI) in the province of Quebec, Canada. The Citizens’ Project is a support group where participants share their challenges and accomplishments with each other and receive honest and confidential feedback. These groups had a personal-civic recovery focus and consisted of a series of 10 weekly 90-minute online workshops. To evaluate the impact of the intervention on the participants' sense of citizenship, all study participants completed the 23-item French version of the Citizenship Measure before (T1) and after (T2) the intervention (≤14 weeks between T1 and T2). The mean and standard deviation differences between the two measurement times were compared between the experimental group and the control group. The mean score to the Citizenship Measure for the experimental group varied by -0.4%. The mean score for the experimental group varied by -5.5%. For the control group, there was a decrease in the means for each of the 5 sub-scales of the Citizenship Measure. In total, the difference was statistically significant (P=.04). Results suggest that the Online Citizens Project had a protective effect on the sense of citizenship of the participants living with SMI in the experimental group compared to those in the control group. The Citizenship Measure can be used to gauge the effects of such an online intervention, intentionally designed to promote the exercise of citizenship, namely the Citizens Project.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".