Fever among preschool-aged children: a cross-sectional study assessing Lebanese parents’ knowledge, attitudes and practices regarding paediatric fever assessment and management
Bibliographic record
Abstract
OBJECTIVES: This study investigated parental knowledge, attitudes and practices towards fever in preschool children to help address gaps in public health and provide information with the aim of supporting clinical reports for parental education. DESIGN: A cross-sectional study design was used to explore parental experiences with fever. SETTING: Participants were recruited randomly from schools all over Lebanon targeting the preschool divisions. PARTICIPANTS: Parents of children aged 5 years or less. INTERVENTIONS: An electronic self-administered questionnaire was sent to the parents through the schools' emails and e-learning mobile applications. PRIMARY AND SECONDARY OUTCOMES: The primary outcome measure was to assess parental knowledge about the precise definition of fever, correct use of medications and to evaluate the impact of sociodemographic factors on this knowledge. The secondary outcome measures were to assess parental attitudes and practices of fever management, sources of information and reasons to seek primary medical attention. RESULTS: A total of 733 parents were included in the study. Only 44% identified fever correctly according to the recognised definition by international guidelines. A significant association between parents' knowledge of antibiotics and years of parenting experience was found (adjusted OR, ORa=4.23, 95% CI 1.41 to 12.68, p=0.01). Other sociodemographic factors that were significantly associated with parents' knowledge of antibiotics were age (ORa=3.42, 95% CI 1.09 to 10.73, p=0.036) and education level (ORa=7.99, 95% CI 3.71 to 17.23, p<0.001). Greater than 75% usually give their children antipyretics without consulting a doctor. Approximately one-quarter of parents (26.3%) consulted different doctors at the same time, of which more than half (58.4%) had received different medical information. CONCLUSIONS: This research determines deficiencies in parents' knowledge of fever with some malpractices in its management particularly regarding antipyretic use. It provides insight for healthcare providers to empower parental experiences by offering the necessary information to enhance general outcomes of febrile sickness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".