Health Care Seeking Behavior among the Parents for their Autistic Children
Bibliographic record
Abstract
Background: Autism Spectrum Disorders (ASD) are increasing alarmingly in recent times. Objective: The purpose of the present study was to find out the pattern of health care seeking behavior of the parents for their autistic children. Methodology: This cross-sectional study was conducted at Centre for Neurodevelopment and Autism in Children at Bangabandhu Sheikh Mujib Medical University, Dhaka from January to December 2013. The respondents were the parents of autistic children who came to the centres with their children. Results: About 61(66.3%) cases were in 2 to 6 years of age. Among the siblings, 8(8.7%) had autism and relatives of 8(8.7%) children had other developmental disorder. It is revealed that 67(72.8%) consulted specialist doctor, 23(25%) attended special teacher in scientific center. As many as 65(70.7%) were aware about autism and 80(87%) knew about the services provided at scientific centers. About 36(39.1%) had barriers to attend scientific centers. Lack of awareness (18 out of 36) was the most important barrier. Majority of the parents (79.3%) attended regularly to the health care centers for follow up. Conclusion: In conclusion raising awareness, dissemination of information, knowledge about autism including its risk factors and decentralization of health care facilities can overcome the impediment of getting appropriate health care. Journal of Current and Advance Medical Research, July 2022;9(2):83-90
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".