An urgent need for early diagnosis and universal health care: insights from a series of interviews with parents of children living with congenital adrenal hyperplasia in Indonesia
Bibliographic record
Abstract
Congenital adrenal hyperplasia (CAH) presents significant health challenges and requires a timely diagnosis and comprehensive treatment. This qualitative study assessed the experiences of parents of children with CAH in Indonesia, and focused on the challenges associated with delayed diagnosis. In-depth interviews with 40 parents of children with CAH from 9 Indonesian provinces were conducted between December 2022 and January 2023. The results revealed parents experienced challenges due to the absence of a newborn screening program (NBS) and the minimal capacity of healthcare professionals to diagnose CAH. Parents reported having emotional stress, financial challenges, and social stigma. Fludrocortisone and 17-OHP are not covered by the national health insurance, thus financial challenges prevailed. The impact of late diagnosis was also notable in their children; parents reported that their children had tendencies to self-isolate, insecurities, temperamental behavior, and masculine behavior (for females). These findings emphasize the critical need for the NBS to implement early diagnosis, increase healthcare professionals' capacity to diagnose CAH, and ensure accessible and affordable healthcare policies for patients with CAH. Addressing these gaps is essential for improving the quality of life for children with CAH and their families in Indonesia.
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 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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".