MétaCan
Menu
Back to cohort
Record W4361768582 · doi:10.4236/psych.2023.143023

Resilience among Women of Childbearing Age from Arequipa, Peru: Psychometric and Associative Analysis

2023· article· en· W4361768582 on OpenAlexaff
Julio César Huamaní Cahua, Walter L. Arias Gallegos, Jesús María Gonzáles Zarate, Mitchell Clark

Bibliographic record

VenuePsychology · 2023
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsMount Royal University
Fundersnot available
KeywordsMarital statusEducational attainmentPsychologyScale (ratio)Psychological resilienceResilience (materials science)PregnancyDevelopmental psychologyDemographySocial psychologyGeographyPopulationSociologyPolitical scienceCartography

Abstract

fetched live from OpenAlex

Resilience is one of the most important variables in the development of healthy pregnancies although there have been limited investigations within local contexts. The present study had a double purpose: first, to analyze the psychometric properties of the Wagnild and Young Resilience Scale, and second, to evaluate the sociodemographic and obstetric variables associated with resilience in fertile-age women from Arequipa City. This is an instrumental and associative study, in which a sample of 248 women who attended a health center located in Alto Selva Alegre district, were assessed using the Wagnild and Young Resilience Scale, and a sociodemographic survey. The results suggest that the resilience scale is valid and reliable. Moreover, 46.8% of the women were assessed as having low resilience. It was also found that resilience was associated with age, educational attainment, marital status, productive activities, the desire for pregnancy, and domestic violence during pregnancy. Educational attainment and domestic violence during pregnancy had a positive impact on resilience.

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)0.001
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 score0.040
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.414
Teacher spread0.378 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePsychologySame topicResilience and Mental HealthFrench-language works237,207