A Descriptive Study to Assess the Knowledge regarding prevention of Urinary Tract Infection among adolescent girls in Nanchiyampalayam, Dharapuram, Tamilnadu
Bibliographic record
Abstract
A descriptive study to assess the knowledge regarding prevention of urinary tract infections among adolescent girls in Nanchiyampalayam, Dharapuram, Tamilnadu. The non-experimental research approach was adopted for the study with descriptive research. The sample size was 30. Sample of adolescent girls who met the inclusion criteria were selected for the study by using purposive sampling technique. Structured questionnaire was used to assess the knowledge regarding urinary tract infection. The data were analysed by using both descriptive and inferential statistics. Regarding age, majority 16(53%) belongs to the age group of 15-16 years. Regarding religion, majority 13(44%) of them were Hindus. Regarding Occupation of the father, highest of 11(36%) were coolie workers. Regarding family income per month, majority were belonged to the income group of Rs.5001 and above 14(47%). Regarding education, majority 10(33%) had completed their primary education. Regarding source of information, majority 15(50%) through Health personnel. Regarding the level of knowledge, majority 16(53%) had adequate knowledge. There was significant association between the level of knowledge regarding urinary tract infection with their selected demographic variables among adolescent girls such as age at 0.05 level of significance.
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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".