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Record W1995198689 · doi:10.5539/gjhs.v4n3p117

Violence against Women Living with HIV: A Cross Sectional Study in Nepal

2012· article· en· W1995198689 on OpenAlexvenueno aff
Nirmal Aryal, Pramod Regmi, Nabaraj Mudwari

Bibliographic record

VenueGlobal Journal of Health Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)HumiliationMedicineCross-sectional studyDomestic violenceEnvironmental healthPublic healthDemographyPoison controlSuicide preventionGerontologyPsychologyFamily medicineSocial psychologyNursingSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Violence against Women (VAW) and Human Immunodeficiency Virus (HIV) both constitute major public health issues and there is an increasing evidence of their intersection. Data are sparse on the intersection of VAW and HIV in South Asia region. We aimed to identify different forms and magnitude of violence incurred by women living with HIV, and analyse causes and consequences. METHODS: A cross-sectional study was conducted among 43 HIV positive women in three districts of Nepal, in the period of March-May 2008. Data was collected through semi-structured interview questionnaire. RESULTS: The vast majority of the participants (93.02%) had suffered from at least one form of the violence. The prevalence of violence rose up sharply after being diagnosed with HIV positive than before (93.02% vs.53.5%). Forty-five percent of the participants reported their husbands being main perpetrator of violence. Self-humiliation and health and treatment problem were the major consequences of violence as reported by 90% and 77.5% of the participants respectively. CONCLUSION: Violence was observed to be highly prevalent among women living with HIV in Nepal. Further larger and nationally representative researches are imperative to better understand the cross-section between VAW and HIV. Our finding recommends to prioritizing programs on social aspects of HIV such as violence.

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)0.012
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 score0.012
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
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 head0.032
GPT teacher head0.392
Teacher spread0.360 · 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

Citations20
Published2012
Admission routes1
Has abstractyes

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