Integrating adolescent-friendly health services into the public health system: an experience from rural India
Bibliographic record
Abstract
BACKGROUND: Although India's health policy is directed toward improving adolescent reproductive health, adolescent-friendly health services are scarce. The intervention for "integrating adolescent-friendly health services into the public health system" is an effort to improve the health status of adolescents in rural areas of the Varanasi (Arajiline) and Bangalore (Hosakote) districts in India. The purpose of this article is to describe the features of the intervention and investigate the impact on improving awareness and utilization of services by adolescent as well as quality of ARSH services in the intervention districts. METHODS: Data from project monitoring, community survey (737 adolescents), exit interviews (120 adolescents), assessment of adolescent sexual and reproductive health clinics (n = 4), and health service statistics were used. Descriptive analyses and paired t-tests were used to compare the two intervention districts. RESULTS: Overall, the percentage of adolescents who were aware of the services being offered at a health-care facility was higher in Hosakote (range: 56.2% to 74.7%) as compared to Arajiline (range: 67.3% to 96.9); 23.3% and 42.6% of adolescents in Arajiline and Hosakote typically sought multiple services at any one visit. A large percentage of clients (Arajiline: 81.7%; Hosakote: 95.0%) were satisfied with the services they received from the facility. The relative change in uptake of services from the first quarter (January to March 2009) to the last quarter (October to December 2010) was significantly higher in Arajiline (7.93, P = 0.020) than in Hosakote (0.78, P = 0.007). CONCLUSION: The intervention had positive results for the public health system and the services are being scaled up to different blocks of the districts, under a public-private partnership.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".