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Record W2904771409 · doi:10.21037/mhealth.2018.12.01

A scoping review of mental health mobile apps for use by the military community

2018· review· en· W2904771409 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuemHealth · 2018
Typereview
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsQueen's University
Fundersnot available
KeywordsMental healthDoorsMental health careMilitary personnelPsychologyHealth careMobile appsMedical educationNursingMedicineEngineeringPsychiatryPolitical scienceComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Advancements in technology have opened doors to new directions in mental health care, including the emergence of mobile health applications. Such apps are helping to make mental health care more accessible to those who face barriers to care, such as military personnel. We conducted a scoping review to map the existing literature on mental health-related apps intended for use by military personnel/veterans. As a result, we identified several themes from the literature. We also discuss how apps are being developed and tested for use by the military community and provide suggestions for future research directions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.258
GPT teacher head0.550
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it