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Record W3188337563 · doi:10.2196/28080

The Chicago Health and Life Experiences of Women Couples Study: Protocol for a Study of Stress, Hazardous Drinking, and Intimate Partner Aggression Among Sexual Minority Women and Their Partners

2021· article· en· W3188337563 on OpenAlexvenueno aff
Cindy B. Veldhuis, Lauren Porsch, Lauren Bochicchio, Jacquelyn Campbell, Timothy P. Johnson, Allen J. LeBlanc, Kenneth E. Leonard, Melanie M. Wall, Sharon C. Wilsnack, Mariah Xu, Tonda L. Hughes

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
FundersNational Institute on Alcohol Abuse and AlcoholismNational Institutes of Health
KeywordsPsychologySexual minorityLesbianMinority stressPopulationStressorSocial psychologyMental healthAngerDomestic violencePoison controlSexual orientationSuicide preventionClinical psychologyMedicinePsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Large gaps exist in research on alcohol use and intimate partner aggression (IPA) among sexual minority women (SMW; eg, lesbian, bisexual). Dyadic research with SMW and their partners can illuminate how couple-level factors operate in conjunction with individual-level factors to shape well-being in this understudied and vulnerable population. Given the traditionally gendered lens with which women are primarily viewed as victims and men as perpetrators, understanding the dynamics of IPA in same-sex female couples can also advance research and practice related to IPA more generally. OBJECTIVE: Guided by a recent extension of the minority stress model that includes relational (couple-level) sexual minority stress and the I-cubed theoretical perspective on IPA, we will collect individual and dyadic data to better characterize the links between hazardous drinking and IPA among SMW and their partners. First, this study aims to examine the associations among minority stress, hazardous drinking, and IPA in SMW and their partners. Minority stressors will be assessed as both individual and couple-level constructs, thus further extending the minority stress model. Second, we aim to examine potential mediators and moderators of the associations among minority stress, hazardous drinking, and IPA. Finally, we aim to test models guided by the I-cubed theoretical perspective that includes instigating (eg, relationship conflict), impelling (eg, negative affect and trait anger), and inhibiting (eg, relationship commitment and emotion regulation) or disinhibiting (eg, hazardous drinking) influences on IPA perpetration. METHODS: This United States National Institutes of Health-funded project will draw from a large and diverse cohort of SMW currently enrolled in the Chicago Health and Life Experiences of Women (CHLEW) study-a 21-year longitudinal study of risk factors and consequences associated with SMW hazardous drinking. SMW currently enrolled in the CHLEW and their partners will be invited to participate in the CHLEW Couples Study. By analyzing dyadic data using actor-partner interdependence models, we will examine how each partner's minority stress, hazardous drinking, and IPA experiences are associated with both her own and her partner's minority stress, hazardous drinking, and IPA perpetration. RESULTS: Data collection began in February 2021 and will likely continue through 2023. Initial results should be available by mid-2024. CONCLUSIONS: The CHLEW Couples Study will fill important gaps in knowledge and provide the basis for future research aimed at clarifying the causal pathways linking hazardous drinking and IPA among SMW. This will support the development of culturally appropriate targeted individual and dyadic prevention and intervention strategies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/28080.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.060
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.016
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0030.004
Science and technology studies0.0060.002
Scholarly communication0.0030.003
Open science0.0030.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0600.011

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 head0.213
GPT teacher head0.579
Teacher spread0.366 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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
Published2021
Admission routes1
Has abstractyes

Explore more

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