Detecting and addressing adolescent issues and concerns: evaluating the efficacy of a primary care previsit questionnaire.
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy of a previsit questionnaire (PVQ), implemented without formal training, that was designed to screen for biomedical and psychosocial health issues and concerns among adolescent patients in a hospital-based primary care clinic, and to examine the subsequent action taken for health issues and concerns identified with the PVQ. DESIGN: Retrospective review of adolescent medical charts, using a pre-post design. SETTING: An outpatient primary care clinic located in an urban teaching hospital in Montreal, Que. PARTICIPANTS: A total of 210 adolescent patients aged 13 to 19 who visited the clinic between 2000 and 2004. MAIN OUTCOME MEASURES: The type (medical vs psychosocial) and number of issues detected and actions taken by physicians in one-to-one consultations with adolescent patients 2 years before (2000-2002) and 2 years after (2002-2004) PVQ implementation, as noted in the patients' medical charts. RESULTS: In total, 105 charts were reviewed for each group. An increase in the number of psychosocial issues was detected following the introduction of the PVQ. An increase in the frequency of action taken for psychosocial concerns and a decrease in the frequency of medical action taken by physicians were found after PVQ implementation. More notations related to psychosocial concerns were also found in the adolescents' charts after introduction of the PVQ. CONCLUSION: A PVQ is an effective strategy to improve adolescent screening for psychosocial issues and concerns. Implementing such a questionnaire requires no training and can therefore be easily incorporated into clinical practice.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".