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Record W2172080256 · doi:10.7205/milmed-d-12-00549

NATO Survey of Mental Health Training in Army Recruits

2013· article· en· W2172080256 on OpenAlexaff
Amy B. Adler, Roos Delahaij, Suzanne Bailey, Carlo Van den Berge, Merle Parmak, Barend van Tussenbroek, José M. Puente, Sandra Landratova, Pavel Král, Guenter Kreim, Deirdre Rietdijk, Dennis McGurk, Carl A. Castro

Bibliographic record

VenueMilitary Medicine · 2013
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsCanadian Armed Forces
Fundersnot available
KeywordsNorth Atlantic TreatyMental healthTraining (meteorology)Coping (psychology)Military medicineMilitary personnelPsychologyMedical educationPsychological resilienceMedicineApplied psychologyClinical psychologyPsychiatrySocial psychologyPolitical scienceGeographyPolitics

Abstract

fetched live from OpenAlex

To-date, there has been no international review of mental health resilience training during Basic Training nor an assessment of what service members perceive as useful from their perspective. In response to this knowledge gap, the North Atlantic Treaty Organization (NATO) Human Factors & Medicine Research & Technology Task Group "Mental Health Training" initiated a survey and interview with seven to twenty recruits from nine nations to inform the development of such training (N = 121). All nations provided data from soldiers joining the military as volunteers, whereas two nations also provided data from conscripts. Results from the volunteer data showed relatively consistent ranking in terms of perceived demands, coping strategies, and preferences for resilience skill training across the nations. Analysis of data from conscripts identified a select number of differences compared to volunteers. Subjects also provided examples of coping with stress during Basic Training that can be used in future training; themes are presented here. Results are designed to show the kinds of demands facing new recruits and coping methods used to overcome these demands to develop relevant resilience training for NATO nations.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.113
GPT teacher head0.434
Teacher spread0.320 · 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.

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

Citations19
Published2013
Admission routes1
Has abstractyes

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