A Vision to Enhance Trust Requirements for Peer Support Systems by Revisiting Trust Theories
Bibliographic record
Abstract
This vision paper focuses on the mental health crisis impacting healthcare workers (HCWs), which exacerbated by the COVID-19 pandemic, leads to increased stress and psychological issues like burnout. Peer Support Programs (PSP) are a recognized intervention for mitigating these issues. These programs are increasingly being delivered virtually through Peer Support Systems (PSS) for increased convenience and accessibility. However, HCWs' perception of these systems results in fear of information sharing, perceived lack of safety, and low participation rate, which challenges these systems' ability to achieve their goals. In line with the rich body of research on the requirements and properties of trustworthy systems, we posit that increasing HCWs' trust in PSS could address these challenges. However, extant research focuses on objectively defined trustworthiness rather than perceptual trust because trustworthy requirements are viewed as more controllable and easier to operationalize. This study proposes a novel approach to elicit perceptual trust requirements by proposing a trust framework anchored in recognized trust theories from different disciplines that unpacks trust into its recognized types and their antecedents. This approach allows the identification of trust requirements beyond those already proposed for trustworthy systems, providing a strong foundation for improving the effectiveness of PSS for HCWs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".