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Record W2039439371 · doi:10.7205/milmed-d-11-00060

The Influence of Mental Skills on Motivation and Psychosocial Characteristics

2012· article· en· W2039439371 on OpenAlexaboutno aff
Leigh McGraw, Michael A. Pickering, Carl Ohlson, Jon Hammermeister

Bibliographic record

VenueMilitary Medicine · 2012
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
FundersU.S. Department of Defense
KeywordsMental healthPsychosocialLonelinessPsychologyUCLA Loneliness ScaleClinical psychologyAngerAnxietyScale (ratio)Psychiatry

Abstract

fetched live from OpenAlex

The purpose of this observational, cross-sectional study was to assess psychosocial characteristics and intrinsic motivation in a convenience sample of Army soldiers with different mental skills profiles. Participants were recruited immediately before or immediately following regular training activities. Anonymous surveys were completed and collected in the training area. Instruments used in this study included the Ottawa Mental Skills Assessment Tool-3 Revised for Soldiers; Rosenberg Self-esteem Scale; Depression Anxiety Stress Scale-21; University of California, Los Angeles, Loneliness Scale; Beck Hopelessness Scale; Intrinsic Motivation Inventory; and an anger measure. Soldiers with strong mental skill profiles were more intrinsically motivated and psychosocially healthier than their peers with weaker mental skill profiles. It is recommended that a proactive approach to psychological health promotion practices in soldiers be sought rather than reactive treatment plans to psychological sequelae. Future research must examine the role of psychosocial fitness and adaptability to enhance mental skills fitness.

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)0.000
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 score0.274
Threshold uncertainty score0.166

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.017
GPT teacher head0.366
Teacher spread0.349 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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