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Record W4396740538 · doi:10.52403/ijhsr.20240516

Evaluating Menstrual Hygiene Practices and School Absenteeism Among Adolescent Girls in Lumbini Province, Nepal

2024· article· en· W4396740538 on OpenAlexaff
Khimananda Bhandari, Rudra Dahal, Yuba Raj Paudel

Bibliographic record

VenueInternational Journal of Health Sciences and Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineAbsenteeismHygieneEnvironmental healthSocial psychology

Abstract

fetched live from OpenAlex

This study applied cross-sectional study design to investigate the relationship between menstrual hygiene practices and school absenteeism among adolescent girls in grades nine and ten in Lumbini Province, Nepal. The research investigated how social norms, religious customs, and the availability of facilities and hygiene products affect girls' involvement in school activities while menstruating. The study used a purposive sampling method to recruit participants and self-administered semi-structured questionnaires to collect the data. Key findings include more than one-third of the participants who experienced menarche at the age of 13 years. Among the total participants, 61% received information about menstruation primarily from friends and family members. Notably, 40% of participants were adversely affected by the lack of safe hygiene facilities and resources at school. Furthermore, 43% reported missing homework submissions and class tests during menstruation, while 32% missed regular learning and extracurricular activities. Additionally, 17% missed final examinations and had to repeat the same class. The study suggests the need for targeted programs to improve school infrastructure and implement additional arrangements for missed assignments and final examinations to address the challenges faced by adolescent girls in Lumbini Province, Nepal. Key words: Menstrual hygiene practices, school absenteeism, adolescent girls, social norms, infrastructure, educational interventions. and Nepal.

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)0.025
metaresearch head score (Gemma)0.003
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 score0.218
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.366
GPT teacher head0.661
Teacher spread0.295 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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