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Record W2294515540 · doi:10.5539/gjhs.v8n10p250

Relationship between Quality of Life of Women-Headed Households and Some Related Factors in Iran

2016· article· en· W2294515540 on OpenAlexvenueno aff
Mahnaz Solhi, Marziyeh Shabani Hamedan, Masood Salehi

Bibliographic record

VenueGlobal Journal of Health Science · 2016
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
FundersIran University of Medical Sciences
KeywordsQuality of life (healthcare)Psychological interventionDemographyMedicineAnimal scienceBiologySociology

Abstract

fetched live from OpenAlex

<p><strong>BACKGROUND & AIM</strong><strong>:</strong> Women heading their households are the ones who lead their life alone. Burden of life probably decreases the quality of life of women-headed households. The aim of this study is to determine the relationship between quality of life of women-headed households and some related factors in Iran.</p><p><strong>METHODS</strong><strong>:</strong> The study was a cross-sectional study and 180 women-head households were selected from Welfare Organization, Tehran Province, using stratified random sampling method in 2015(January up to April). Social World Health Organization's quality of life questionnaire was used to gather information. The data were analyzed using SPSS statistical software (15) and suitable descriptive and analytical methods were applied.</p><p><strong>RESULTS: </strong>Quality of life was moderate in the studied women. The <em>highest mean score </em>(50.35) <em>was</em> related to the physical aspect and the lowest <em>mean </em>(37.82) was about the environmental aspect.</p><p><strong>CONCLUSION:</strong> Quality of life of the studied women is not desirable; so, it is necessary to design appropriate interventions to improve their quality of life.</p>

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)0.008
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.141
GPT teacher head0.429
Teacher spread0.288 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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