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Record W3190023794 · doi:10.3138/jmvfh-2021-0023

Work-family conflict and subsequent depressive symptoms among war-exposed post-9/11 U.S. military Veterans

2021· article· en· W3190023794 on OpenAlexvenueno aff
Shelby Borowski, Brian N. Smith, Juliette McClendon, Dawne Vogt

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsMilitary serviceFeelingService memberPsychologyVeterans AffairsMilitary personnelFamily conflictMental healthDepressive symptomsDepression (economics)Work (physics)Work–family conflictService (business)PsychiatryGerontologyMedicineSocial psychologyPolitical scienceAnxiety

Abstract

fetched live from OpenAlex

LAY SUMMARY Veterans may struggle with the conflicts that arise from juggling competing work and family demands after they leave military service. Over time, these feelings of conflict can have a negative impact on their mental health. The current study sought to explore the impact of conflict between work and family roles on war-zone-deployed U.S. Veterans’ depressive symptoms 1.5 years later. Men and women were examined separately. Results showed that when family responsibilities interfered with work responsibilities both men and women had higher levels of depressive symptoms 1.5 years later. However, when work responsibilities interfered with family responsibilities, only men reported higher levels of depressive symptoms 1.5 years later. The current findings support the importance of programs that can help both female and male Veterans readjust to changing life roles when they leave military service. Both types of conflict are modifiable, and these findings suggest the importance of workplace and Veterans Affairs programs that can help military Veterans manage changing responsibilities and demands upon reintegration.

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 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 score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.033
GPT teacher head0.296
Teacher spread0.263 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

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