Can Experiential–Didactic Training Improve Clinical STD Practices?
Bibliographic record
Abstract
BACKGROUND: High rates of sexually transmitted diseases (STDs) present an ongoing costly public health challenge. One approach to reduce STD transmission is to increase the number of clinicians adopting the Centers for Disease Control and Prevention's STD Treatment Guidelines. This evaluation assesses the effectiveness of a 3-day experiential and didactic training to translate recommendations into practice by increasing clinician knowledge and skills and helping participants anticipate and overcome barriers to implementation. METHODS: Between 2001 and 2004, 110 direct care clinicians from 10 states participated in one of 27 standardized 3-day interactive trainings offered by the Denver STD/human immunodeficiency virus (HIV) Prevention Training Center. STD/HIV knowledge and clinical skills were measured before, immediately after, and 6 months after training. Practice patterns were assessed before training and after 6 months. Structural barriers to implementation were identified 6 months post-training. RESULTS: Trainees demonstrated significant post-training gains in mean knowledge scores immediately post-training (P < 0.001) and 6 months post-training (P = 0.002). After 6 months, self-reported mean skill levels remained significantly improved compared to precourse (P < 0.05) for each of 27 skills including STD risk assessment, clinical examination, diagnosis, and treatment. Self-reported improvement in practice patterns was significant for 23 of 35 practices (P < 0.05) 6 months post-training. Participants indicated that inadequate time (52.9%), facilities/equipment (51.5%), and staffing (47.1%) interfered with implementation of recommended practices. CONCLUSIONS: Experiential-didactic STD/HIV training can modestly improve knowledge, clinical skills, and implementation of STD recommended practices 6 months after training. Further research is needed to identify the impact of improved clinical practices on STD/HIV transmission.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".