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Record W2127659310 · doi:10.1521/pdps.2013.41.4.541

The Psychodynamic Psychotherapist's Guide to the Interaction among Sex, Genes, and Environmental Adversity in the Etiology of Depression for Women

2013· article· en· W2127659310 on OpenAlexaff
Simone N. Vigod, Valerie H. Taylor

Bibliographic record

VenuePsychodynamic Psychiatry · 2013
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of TorontoWomen's College Hospital
Fundersnot available
KeywordsPsychologyDepression (economics)PsychosocialStressorClinical psychologyPsychodynamicsDysfunctional familyInterpersonal communicationPsychiatrySocioeconomic statusDevelopmental psychologyPsychotherapistMedicinePopulationSocial psychology

Abstract

fetched live from OpenAlex

From menarche to menopause, women are highly vulnerable to major depression. While biological and psychosocial differences between men and women have been established, the reason for the preponderance of depression in women has yet to be fully elucidated. Women may be predisposed to depressive illness because of biological factors related to brain structure, function, and the impact of reproductive life stages. They may also be at increased risk because they are differentially disadvantaged with respect to environmental stressors including interpersonal violence, socioeconomic instability, and caregiving burden, among others. However, not all women develop depression, nor do all individuals who suffer from adverse life events. This narrative review focuses on emerging research related to the interaction between sex, genetics, and environmental factors that may help offer clues about why some individuals suffer from depression, and why others may be resilient to this outcome. While many questions remain unanswered, the psychodynamic psychotherapist can use this information to help patients suffering from depression understand some of the complexities of the determinants of risk and resilience, with the goal of moving forward toward recovery.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.521

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 science0.0010.000
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 head0.007
GPT teacher head0.268
Teacher spread0.261 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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