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Record W2070078342 · doi:10.1037/a0024525

The case for treating depression in military spouses.

2011· review· en· W2070078342 on OpenAlexaff
Helen Verdeli, Charles Baily, Eleni Vousoura, Alexander Belser, Daisy R. Singla, Gail H. Manos

Bibliographic record

VenueJournal of Family Psychology · 2011
Typereview
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsMcGill University
FundersBureau of Medicine and SurgeryNational Institute of Mental Health
KeywordsService memberDepression (economics)Software deploymentMental healthMilitary personnelStressorMilitary servicePsychologyMilitary deploymentPsychiatryAdaptation (eye)Political science

Abstract

fetched live from OpenAlex

The increased operational tempo associated with current deployments to Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) is placing considerable strain on military families. Among other sequelae of OIF and OEF deployment, findings from recent studies suggest high rates of depression in spouses of service members. This review presents a rationale for targeting depression among military spouses. It examines how stressors relating to the deployment cycle may contribute to depression in spouses and outlines the effects of spousal depression on the mental health of service members and their children. Mental health services currently available to military spouses as well as barriers to their care are also described. Considerations for the adaptation of treatment to their unique circumstances and needs are discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.330
GPT teacher head0.530
Teacher spread0.199 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations83
Published2011
Admission routes1
Has abstractyes

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