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Record W2153889893 · doi:10.7205/milmed-d-09-00059

An Exploratory Investigation of Relationships Among Mental Skills and Resilience in Warrior Transition Unit Cadre Members

2010· article· en· W2153889893 on OpenAlexaboutno aff
Michael A. Pickering, Jon Hammermeister, Carl Ohlson, Bernie Holliday, Graham Ulmer

Bibliographic record

VenueMilitary Medicine · 2010
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMental toughnessMental healthPsychologyPsychological resilienceResilience (materials science)StressorConstruct (python library)Clinical psychologyApplied psychologyCognitionScale (ratio)Cognitive skillDevelopmental psychologySocial psychologyMedicinePsychiatryGeographyComputer science

Abstract

fetched live from OpenAlex

Warrior transition unit (WTU) cadre members are exposed to a variety of stressors that put them at risk for adverse conditions and events. Resilience may be a construct capable of moderating some of these potential negative outcomes. In turn, mental toughness is a concept associated with resilience that may provide a unique framework from which to train resilient behavior. This article explored associations between resilience and several mental skills that are assumed to be related to mental toughness, in a sample (n = 27) of WTU cadre members in the U.S. Army. Instruments included the Ottawa Mental Skills Inventory (OMSAT-3) and the Resilience Scale (RS). Both cognitive mental skills and emotion management skills were positively associated with resilience. Results also indicated a model specifying emotion management as a mediator of the relationship between cognitive skills and resilience was consistent with the study data.

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)0.001
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 score0.173
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.339
Teacher spread0.309 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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