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Record W2102136565 · doi:10.5539/gjhs.v6n5p132

Exploring Needs and Expectations of Spouses of Addicted Men in Iran: A Qualitative Study

2014· article· en· W2102136565 on OpenAlexvenueno aff
Soodabeh Joolaee, Naeemeh Seyed Fatemi, Mohammad Hassan Meshkibaf, Jila Mirlashari

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersFasa University of Medical SciencesIran University of Medical Sciences
KeywordsAddictionQualitative researchContext (archaeology)PsychologyAffect (linguistics)Government (linguistics)PsychiatryClinical psychology

Abstract

fetched live from OpenAlex

Addiction is one of the major problems that affect everyone in the society especially the spouses of addicted men who have to face a large number of problems which are the consequences of their husband's addiction. This qualitative study was conducted to explore the needs and expectations of women who are living with their addicted husband in Iran. Twenty-four spouses of addicted men participated in this study. The participants were interviewed and each interview was analyzed via the content analysis method. The results of this study showed that the women's difficulties were related to their approach to the treatment, or their husbands' response to the treatment, financial constraints and emotional and informational needs. Moreover, these Iranian women expected more stringent control by the government on the phenomenon of addiction and drug trafficking with a view of having a drug-free country. The needs and expectations of the wives of addicted men are context-based and should be assessed separately between individuals, families, and communities. In addition to the addicted person, it is vitally important that the health of the family members of drug addicts be taken into account and for whom supportive services be provided.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.157
GPT teacher head0.426
Teacher spread0.269 · 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 designQualitative
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

Citations16
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicSubstance Abuse Treatment and OutcomesFrench-language works237,207