Testing Online Men’s Groups to Promote Psychological Well-Being and Reduce Despair During the COVID-19 Pandemic
Bibliographic record
Abstract
Abstract Suicide prevention is a healthcare and social justice priority. Older adults have the highest rates of suicide and the highest COVID-19 fatality rates in North America. The combined impacts of social isolation, fear of infection, apathy, and hopelessness could amplify suicide risk among older adults, as appears to have been the case during the 2003 SARS epidemic in Hong Kong. Innovative interventions are thus needed to promote social interaction and reduce risk for suicide in these challenging times. We are currently testing an online version of our Meaning-Centered Men’s Group (MCMG; Heisel et al., 2020), an upstream psychological intervention designed to promote psychological well-being and reduce suicide risk among men struggling with the transition to retirement, in the context of pandemic-related public health restrictions. This presentation will focus on adaptations to MCMG for online delivery, and share participant experiences and findings on positive and negative psychological outcomes.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.009 | 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".