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Record W2336338787

Impact of military life stressors on health and well-being of single-parent military families

2015· article· en· W2336338787 on OpenAlexaboutno aff
Alla Skomorovsky, Filsan Hujaleh

Bibliographic record

VenueEuropean Health Psychologist · 2015
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStressorRelocationPsychologyMilitary personnelSoftware deploymentCoping (psychology)Military deploymentClinical psychologyPolitical scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Background: Single-parent military families experience various unique stressors associated with the demands of military life. However, there has been minimal research examining the impact of military life on the well-being of single-parent military families in Canada. Methods: An electronic survey was completed by single Canadian Armed Forces members (N = 552) who had dependents of 19 years old or younger. Findings: This study showed that CAF single-parent families encounter many challenges, including financial strain, stressors related to relocation and deployment, and poor work-life balance. Moreover, military stressors have a negative impact on the health and well-being of both single parents and children. However, important protective factors were also identified, including the availability of peer and organizational social support and active parental coping. Discussion: This research will allow the military organization to help families to maintain and even enhance resiliency in the face of the stressors associated with military life. Various recommendations for mitigating the impact of military-life-related stressors, such as increasing awareness of family assistance programs and developing a policy that establishes consistent practices for flexible work arrangements, are offered.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.167
GPT teacher head0.462
Teacher spread0.294 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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