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Record W2060486493 · doi:10.1016/j.jmwh.2005.08.002

Perceptions of Predisposing and Protective Factors for Perinatal Depression in Same‐Sex Parents

2005· article· en· W2060486493 on OpenAlexaff
Lori E. Ross, Leah S. Steele, Beth Sapiro

Bibliographic record

VenueJournal of Midwifery & Women s Health · 2005
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsLesbianPsychologySocial supportDevelopmental psychologyContext (archaeology)Mental healthQualitative researchPopulationDepression (economics)Clinical psychologyMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Increasing numbers of women are choosing to have children in the context of same-sex relationships or as "out" lesbian or bisexual individuals. This study used qualitative methods to assess perceived predisposing and protective factors for perinatal depression in lesbian, gay, bisexual, and queer (LGBQ) women. Two focus groups with LGBQ women were conducted: 1) biological parents of young children and 2) nonbiological parents of young children or whose partners were currently pregnant. Three major themes emerged. Issues related to social support were primary, particularly related to disappointment with the lack of support provided by members of the family of origin. Participants also described issues related to the couple relationship, such as challenges in negotiating parenting roles. Finally, legal and policy barriers (e.g., second parent adoption) were identified as a significant source of stress during the transition to parenthood. Both lack of social support and relationship problems have previously been identified as risk factors for perinatal depression in heterosexual women, and legal and policy barriers may represent a unique risk factor for this population. Therefore, additional study of perinatal mental health among LGBQ women is warranted.

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)0.001
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 score0.094
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.388
Teacher spread0.358 · 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

Citations42
Published2005
Admission routes1
Has abstractyes

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