EXPLORING THE SCOPE AND EVALUATION APPROACHES FOR MENTAL HEALTH APPS IMPLEMENTED IN WORKPLACE SETTINGS
Bibliographic record
Abstract
Background: Mental health conditions are one of the leading causes of disability in Canada and worldwide, causing significant financial burdens to individuals, workplaces and the economy. This emphasizes the need to provide accessible support in the workplace to prevent, promote and manage the mental health of the workforce. Mental health apps present a promising medium to scale mental health interventions across the workplace. However, evidence related to how studies are evaluating mental health apps in complex, real-world settings requires careful examination. Purpose: The purpose of this program of research was to synthesize the current state of evidence on the evaluation of mental health apps in the workplace, including an assessment of their effectiveness and to systematically examine the implementation of a mental health app in a workplace as a case study. The first study was a scoping review examining the different approaches studies have used to evaluate mental health apps in the workplace. The second study was a systematic review and meta-analysis examining the effectiveness of mental health apps in the workplace. The third study was a mixed-method case study, informed by an implementation science theory to examine factors influencing the uptake and implementation of a mental health app in a mid-sized hospital. Findings: In total, 54 studies were included in the scoping review with main outcomes being: 1. Usage and feedback of the app, 2. Effects of mental health and workplace outcomes or 3. Implementation process. The systematic review and meta-analysis of 21 studies demonstrated the effectiveness of mental health apps in improving symptoms of distress, depression and anxiety, stress, wellbeing and burnout. mental health as compared to usual care. Findings from the case study indicated the need to carefully consider implementation planning, contextual factors and a fit between the app and the needs of the workers. Implications: This thesis identifies the potential of mental health apps for workplaces and highlights future directions for research to optimize their use and effects.
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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 | 0.330 | 0.414 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.017 | 0.008 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".