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Exploration of psychosocial and environmental factors that could improve the consumption of iron-rich foods among urban Senegalese adolescent girls

2025· article· en· W4406433273 on OpenAlexafffund
Isabelle Galibois

Bibliographic record

VenuePan African Medical Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversité de MonctonUniversité Laval
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychosocialConsumption (sociology)Environmental healthPsychologyGeographyEnvironmental scienceMedicineSociologyPsychiatry

Abstract

fetched live from OpenAlex

Introduction: anaemia remains a public health issue among adolescent Senegalese girls, and one cause is the low consumption of iron-rich foods. This study used the extended model of the Theory of Planned Behavior (TPB) to explore psychosocial factors and environmental barriers that may influence the daily consumption of iron-rich foods (IRF) among urban Senegalese adolescent girls. Methods: a cross-sectional survey was conducted among 136 girls (13-18 years). Salient beliefs related to each construct of the theory were identified. Using this information, a questionnaire was developed to collect data on each construct and the intention to consume IRF daily. Results: on a scale of -2 to 2, the mean score of the intention was 1.39 ± 0.74 while average scores of direct constructs were 1.60 ± 0.89 for the attitude, 1.29 ± 0.84, for the subjective norm, 0.82 ± 0.91 for the perceived behavioral control, and -0.14 ± 0.86 for the environmental barriers. Overall, 34% of girls reported that it was likely that implementing the behavior would make them gain weight while more than 80% stated that their father/mother/sisters would approve the behavior. Also, 38% of girls did not feel able to perform the behavior if they were not capable of preparing IRF themselves. Half agreed that the high price of these foods was a barrier to their consumption. Conclusion: most adolescent girls intend to consume IRF. To operationalize the intention into a concrete behavior, interventions increasing self-efficacy and improving knowledge about IRF, and their affordability and accessibility could be relevant.

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 score0.030
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.281
Teacher spread0.260 · 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
Published2025
Admission routes2
Has abstractyes

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