Impact of Connected Mental Health on the Work Environment of Mental Health Clinicians: Protocol for a Systematic Literature Review
Bibliographic record
Abstract
BACKGROUND: Many mental health professionals face work-related stress due to high job demands, limited control, and inadequate institutional support. Connected mental health (CMH) technologies such as mobile apps and teletherapy platforms are increasingly being proposed as tools to alleviate these job demands. However, their actual influence on clinicians' work environments-here understood as the organizational, social, and psychological conditions that shape their workload, job demands, autonomy, and overall well-being-remains underexplored. Existing reviews have primarily focused on traditional organizational interventions, leaving a critical gap in understanding how CMH technologies specifically influence the work environment of mental health clinicians. OBJECTIVE: This systematic literature review aims to identify and summarize knowledge about the impact of CMH on the work environment of mental health clinicians. METHODS: A systematic literature review will be performed. The review follows PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and has been registered in PROSPERO on April 23, 2025. A comprehensive search strategy was developed using the population, intervention, comparison, and outcome (PICO) framework in collaboration with an academic librarian. Studies will be sourced from the PubMed, Scopus, IEEE Xplore, and ACM Digital Library databases. Inclusion criteria are limited to empirical studies involving mental health clinicians using CMH tools, where outcomes explicitly relate to the work environment (eg, job demands, workload, autonomy, stress, or well-being). Eligible studies must be published in English. Data extraction will include publication trends, study methods, and types of CMH technologies. Additionally, the extraction will capture the study results, including qualitative and quantitative findings, along with the measurement instruments used. Two reviewers will independently select articles for review and extract data. Conflicts will be discussed, and a third reviewer will be consulted if a consensus cannot be reached. Descriptive statistics and thematic analysis (via NVivo) will be used to synthesize the findings. RESULTS: This systematic literature review seeks to explore and synthesize existing research on how CMH technologies affect clinicians' work environments and is expected to be completed by December 2025. CONCLUSIONS: This review will offer a comprehensive overview of how CMH technologies affect the professional work environment of clinicians. TRIAL REGISTRATION: PROSPERO CRD420251018685; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251018685. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/76668.
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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 | 0.077 | 0.072 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.019 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.071 | 0.010 |
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".