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Record W4321138177 · doi:10.1108/jpmh-09-2022-0096

Utilization of the mental health first aid ALGEE action plan: a longitudinal study

2023· article· en· W4321138177 on OpenAlexaboutno aff
Kimberly R. Laurene, Godslove Bonnah, Sweta Patel, Deric R. Kenne

Bibliographic record

VenueJournal of Public Mental Health · 2023
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthDistressPsychologyMental distressAction planQuarter (Canadian coin)Social supportMedicineGerontologyClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Purpose Mental health training programs exist to assist the public with aiding people experiencing mental distress. This study aims to examine the five steps of the Mental Health First Aid (MHFA) ALGEE action plan to assess which steps were used most frequently and how personal characteristics were associated with utilization. Design/methodology/approach Individuals completing MHFA either at public schools with students ranging in age from 5 to 18 or at a university in the Northern central area of the USA were invited to participate. Prior to MHFA, participants completed an initial questionnaire, which included demographic questions and questions assessing the use of the MHFA ALGEE action plan, which is a plan to provide help to someone experiencing mental distress. Follow-up questionnaires were completed every quarter to assess the ALGEE action plan utilization at three-, six- and nine-months after completion of MHFA. A comparison group of individuals, not completing MHFA, was also included. Findings After completing MHFA, individuals demonstrated an increase in using the ALGEE action plan at three- and six-months, but by nine-months there was a reduction in utilization. In general, age, gender and race did not usually influence the usage of the ALGEE action plan. Originality/value Although other studies have measured the efficacy of MHFA, those studies have focused on participant predicted behaviors. The present study measured self-reported behavior and compared the behaviors to a comparison group over time.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.282
GPT teacher head0.481
Teacher spread0.198 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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