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Record W2941377710 · doi:10.1001/jama.2019.3211

Effect of Addition of an Intimate Partner Violence Intervention to a Nurse Home Visitation Program on Maternal Quality of Life

2019· article· en· W2941377710 on OpenAlexaff
Susan M. Jack, Michael Boyle, Christine McKee, Marilyn Ford‐Gilboe, C. Nadine Wathen, Philip V. Scribano, Danielle M. Davidov, Diane B. McNaughton, Ruth O’Brien, Carolyn Johnston, Mariarosa Gasbarro, Masako Tanaka, Melissa Kimber, Jeffrey H. Coben, David L. Olds, Harriet L. MacMillan

Bibliographic record

VenueJAMA · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsWestern UniversityMcMaster UniversityImpact
FundersNational Institute of General Medical Sciences
KeywordsMedicineDomestic violenceQuality of life (healthcare)ReferralPsychological interventionNursingIntervention (counseling)Randomized controlled trialPoison controlDisadvantagedSuicide preventionFamily medicineEnvironmental health

Abstract

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Importance: Intimate partner violence (IPV) is a public health problem with significant adverse consequences for women and children. Past evaluations of a nurse home visitation program for pregnant women and first-time mothers experiencing social and economic disadvantage have not consistently shown reductions in IPV. Objective: To determine the effect on maternal quality of life of a nurse home visitation program augmented by an IPV intervention, compared with the nurse home visitation program alone. Design, Setting, and Participants: Cluster-based, single-blind, randomized clinical trial at 15 sites in 8 US states (May 2011-May 2015) enrolling 492 socially disadvantaged pregnant women (≥16 years) participating in a 2.5-year nurse home visitation program. Interventions: In augmented program sites (n = 229 participants across 7 sites), nurses received intensive IPV education and delivered an IPV intervention that included a clinical pathway to guide assessment and tailor care focused on safety planning, violence awareness, self-efficacy, and referral to social supports. The standard program (n = 263 participants across 8 sites) included limited questions about violence exposure and information for abused women but no standardized IPV training for nurses. Main Outcomes and Measures: The primary outcome was quality of life (WHOQOL-BREF; range, 0-400; higher score indicates better quality of life) obtained through interviews at baseline and every 6 months until 24 months after delivery. From 17 prespecified secondary outcomes, 7 secondary end points are reported, including scores on the Composite Abuse Scale, SPAN (Startle, Physiological Arousal, Anger, and Numbness), Prime-MD Patient Health Questionnaire, TWEAK (Tolerance/Worry About Drinking/Eye-Opener/Amnesia/C[K]ut Down on Drinking), Drug Abuse Severity Test, and the 12-Item Short-Form Health Survey (physical and mental health), version 2. Results: Among 492 participants enrolled (mean age, 20.4 years), 421 (86%) completed the trial. Quality of life improved from baseline to 24 months in both groups (change in WHOQOL-BREF scores from 299.5 [SD, 54.4] to 308.2 [SD, 52.6] in the augmented program group vs from 293.6 [SD, 56.4] to 316.4 [SD, 57.5] in the standard program group). Based on multilevel growth curve analysis, there was no statistically significant difference between groups (modeled score difference, -4.9 [95% CI, -16.5 to 6.7]). There were no statistically significant differences between study groups in any of the secondary participant end points. There were no adverse events recorded in either group. Conclusions and Relevance: Among pregnant women experiencing social and economic disadvantage and preparing to parent for the first time, augmentation of a nurse home visitation program with a comprehensive IPV intervention, compared with the home visitation program alone, did not significantly improve quality of life at 24 months after delivery. These findings do not support the use of this intervention. Trial Registration: ClinicalTrials.gov Identifier: NCT01372098.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.017
GPT teacher head0.391
Teacher spread0.374 · 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

Citations49
Published2019
Admission routes1
Has abstractyes

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