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Record W4396704019 · doi:10.5539/gjhs.v16n6p31

Youth Health Risk Behavior Assessment among University Students in Baghdad, Iraq

2024· article· en· W4396704019 on OpenAlexvenueno aff
Yasmin Almualm, Jamal R. Al-Rawi

Bibliographic record

VenueGlobal Journal of Health Science · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental healthHealth behaviorHealth riskPsychologyMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Health risk behavior is one of the leading causes of morbidity and mortality in the world. The social and economic costs associated with these behaviors can be reduced by changes in individuals’ behavior. Health-related behavior can either enhance or damage physical, psychological and social wellbeing. Human behavior is influenced by an individual’s health consciousness. OBJECTIVE is to study health related behavior that includes dietary habits, physical activity, smoking and alcohol consumption, screen time and behavior related to unintentional injury among students attending public universities in Baghdad. METHODS: Study design is Cross Sectional Study; sampling method is multi-stage Cluster sampling. Self-administered questionnaire was used to collect student data, a total of 1836 students participated in the study RESULTS: Among the 1836 students who participated in the study, 21.4% are smokers, only 3.4% use seatbelts while driving, 11% took medicine without prescription and 78% did not perform regular exercise. 85% of students use the internet at least three hours per day. Dietary habits of students were average based on diet recommendation. CONCLUSION: Health related behavior traits were average among university students in Baghdad. Policy changes to reinforce stringent road traffic safety measures and initiate regular health promotion programs in universities to motivate students to be more proactive towards their health and fitness.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.069
GPT teacher head0.524
Teacher spread0.455 · 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.

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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