A scoping review of decision-aid tools for disclosure and help-seeking of mental health concerns
Bibliographic record
Abstract
Globally, there is a large discrepancy between the prevalence of mental health concerns and the proportion of people who disclose or seek help for their mental health. As such, decision-aid tools have recently emerged in the mental health context to facilitate the disclosure and help-seeking process. Given recent developments in this field, a synthesis of the literature is needed to consolidate existing decision-aid tools and assess their effectiveness, particularly in facilitating the disclosure or help-seeking process. This scoping review aimed to capture and synthesise the growing literature on decision-aid tools designed to support people in the decision to disclose or seek help for their mental health concerns. The review considered empirical studies, including theses and dissertations that matched the following criteria: 1) focused on populations with a mental health concern, 2) reported the development and/or evaluation of a decision-aid tool, and 3) assessed a tool specifically designed to facilitate the disclosure or help-seeking process, or reported on at least one disclosure or help-seeking related outcome. The review was guided by Arksey and O'Malley's framework and the Joanna Briggs Institute's guidelines for scoping reviews. The findings of the review indicate that decision-aid tools can support various cognitive-emotional processes relevant to decision-making. There was also evidence demonstrating the effectiveness of decision-aid tools in increasing the rates of disclosure and help-seeking behaviours for mental health concerns. Overall, decision-aid tools appear to be a promising approach to enhance the effectiveness of disclosure and help-seeking decisions in the mental health context.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".