MétaCan
Menu
Back to cohort
Record W2000744678 · doi:10.1093/eurpub/14.4.366

Are parents aware of their schoolchildren's headaches?

2004· article· en· W2000744678 on OpenAlexaboutno aff
Tayyar Şaşmaz

Bibliographic record

VenueEuropean Journal of Public Health · 2004
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHeadachesMigraineMedicineAffect (linguistics)Logistic regressionFamily historyQuarter (Canadian coin)PediatricsFamily medicinePsychiatryPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: The objective of this study is to determine parents' awareness of their children's headaches and to evaluate some of the factors that affect this awareness. METHODS: The subjects of the study are 2601 children who were diagnosed with headache. Data on the children and the parents was collected using a detailed data form. The diagnosis of headache in children was made on the basis of the criteria of the International Headache Society (IHS). If the parents of a child diagnosed with headache reported that their child had headache, the parent was evaluated to be aware of his/her child's headache. In the statistical analyses, chi-square and binary logistic regression were used. RESULTS: Almost 74% of parents were aware of their children's headache. It was found that migraine type headache, female gender, being the first child of the family, travel sickness of children, the presence of headache history in one of the family members; the number of family members and mother's age are factors that affect the awareness level of parents. It was also revealed that parents who do not work outside are more aware of their children's headache and that educational and financial status do not have any effect on the degree of awareness. CONCLUSIONS: In a city like Mersin, which is economically well developed when compared with the rest of the country, one quarter of the parents are not aware of their children's headache.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.247
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.117
GPT teacher head0.329
Teacher spread0.212 · 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

Citations27
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Public HealthSame topicMigraine and Headache StudiesFrench-language works237,207