Evidence map›Paper›PMID 41143459›Full record

ArticleJMIR research protocols2025

Impact of Connected Mental Health on the Work Environment of Mental Health Clinicians: Protocol for a Systematic Literature Review.

Shweta Premanandan, Sofia Ouhbi, Magdalena Ramstedt Stadin, Charlotte Blease, Åsa Cajander, Maria Hägglund

Abstract read
In one paragraph

Article in JMIR research protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Shweta PremanandanDivision of Computing Science, Department of Information Technology, Uppsala University, Uppsala, Sweden.ORCID 0000-0003-0732-7009
Sofia OuhbiDivision of Computing Science, Department of Information Technology, Uppsala University, Uppsala, Sweden.ORCID 0000-0001-7614-9731
Magdalena Ramstedt StadinVi3, Department of Information Technology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-8196-1289
Charlotte BleaseParticipatory eHealth and Health Data Research Group, Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.ORCID 0000-0003-3657-2476
Åsa CajanderVi3, Department of Information Technology, Uppsala University, Uppsala, Sweden.ORCID 0000-0001-7472-2215
Maria HägglundParticipatory eHealth and Health Data Research Group, Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-6839-3651

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany 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.

objectiveThis systematic literature review aims to identify and summarize knowledge about the impact of CMH on the work environment of mental health clinicians.

methodsA 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.

resultsThis 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.

conclusionsThis review will offer a comprehensive overview of how CMH technologies affect the professional work environment of clinicians.

trial registrationPROSPERO CRD420251018685; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251018685. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/76668.

Indexed as

Health PersonnelMental HealthWorkplaceHumansOccupational StressResearch DesignSystematic Reviews as TopicWorking ConditionsWorkloadartificial intelligenceburnoutconnected mental healthdigital mental health applicationsmental health clinicianssystematic literature reviewwork environment

Identifiers

PMID41143459
PMCPMC12603581

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.