The effectiveness of an education intervention to prevent chlamydia infection among Greenlandic youth
Bibliographic record
Abstract
The purpose of this study was to implement a sexual health behavioural intervention in Greenland in order to reduce sexually transmitted infection rates among a population of Greenland youth. This behavioural intervention was called Inuulluataarneq (Having the Good Life). Inuulluataarneq's objects included: (1) increase Greenlandic youth's overall knowledge about sexually transmitted infections and sexual health; (2) increase parent/guardian-youth communication about topics related to sexually transmitted infections and sex; and (3) increase consistent condom use among Greenlandic youth. We hypothesised that increased awareness of sexually transmitted infections and sexual health as well as increased communication between parents/guardians and their adolescent children would influence sexual risk behaviour and reduce sexually transmitted infections among our sample population, with a focus on urine samples of chlamydia infection. Results indicate that the influence of having a parent/guardian to speak with about topics related to sex, including the consequences of pregnancy, are key protective factors in reducing sexually transmitted infections among Greenlandic youth. Inuulluataarneq demonstrates that intensive short-term education and skill-building delivered by a trained community member is an effective sexually transmitted infection prevention intervention method among young Inuit populations who live in small isolated Arctic communities.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".