Printed educational materials: effects on professional practice and health care outcomes
Bibliographic record
Abstract
BACKGROUND: Printed educational materials (PEMs) are widely used passive dissemination strategies to improve knowledge, awareness, attitudes, skills, professional practice and patient outcomes. Traditionally they are presented in paper formats such as monographs, publication in peer-reviewed journals and clinical guidelines and appear to be the most frequently adopted method for disseminating information. OBJECTIVES: To determine the effectiveness of PEMs in improving process outcomes (including the behaviour of healthcare professionals) and patient outcomes. To explore whether the effect of characteristics of PEMs (e.g., source, content, format, mode of delivery, timing/frequency, complexity of targeted behaviour change) can influence process outcomes (including the behaviour of healthcare professionals and patient outcomes). SEARCH STRATEGY: The following electronic databases were searched up to July 2006: (a) The EPOC Group Specialised Register (including the database of studies awaiting assessment (see 'Specialised Register'under 'Group Details'); (b) The Cochrane Central Register of Controlled Trials (CENTRAL) and the Database of Abstracts of Reviews of Effectiveness; (c) MEDLINE, EMBASE, CINAHL and CAB Health. An updated search of MEDLINE was done in March 2007. SELECTION CRITERIA: We included randomised controlled trials (RCTs) , controlled clinical trials (CCT), controlled before and after studies (CBAs) and interrupted time series analyses (ITS) that evaluated the impact of printed educational materials on healthcare professionals' practice and/or patient outcomes. There was no language restriction. Any objective measure of professional performance (sch as number of tests ordered, prescriptions for a particular drug), or patient health outcomes (e.g., blood pressure, number of caesarean sections) were included. DATA COLLECTION AND ANALYSIS: Four reviewers undertook data abstraction independently using a modified version of the EPOC data collection checklist. Any disagreement was resolved by discussion among the reviewers and arbitrators. Statistical analysis was based upon consideration of dichotomous process outcomes, continuous process outcomes, patient outcome dichotomous measures and patient outcome continuous measures. We presented the results for all comparisons using a standard method of presentation where possible. We reported separately for each study the median effect size for each type of outcome, and the median of these effect sizes across studies. MAIN RESULTS: Twenty-three studies were included for this review. Evidence from this review showed that PEMs appear to have small beneficial effects on professional practice. RCTs comparing PEMs to no intervention observed an absolute risk difference median: +4.3% on categorical process outcomes (e.g., x-ray requests, prescribing and smoking cessation activities) (range -8.0% to +9.6%, 6 studies), and a relative risk difference +13.6% on continuous process outcomes (e.g., medication change, x-rays requests per practice) (range -5.0% to +26.6%, 4 studies). These findings are similar to those reported for the ITS studies, although significantly larger effect sizes were observed (relative risk difference range from 0.07% to 31%). In contrast, the median effect size was -4.3% for patient outcome categorical measures (e.g., screening, return to work, quit smoking) (range -0.4% to -4.6%, 3 studies)). Two studies reported deteriorations in continuous patient outcome data (e.g., depression score, smoking cessation attempts) of -10.0% and -20.5%. One study comparing PEMs with educational workshops observed minimal differences. Two studies comparing PEMs and education outreach did not have statistically significant differences between the groups. It was not possible to explore potential effect modifiers across studies. AUTHORS' CONCLUSIONS: The results of this review suggest that when compared to no intervention, PEMs when used alone may have a beneficial effect on process outcomes but not on patient outcomes. Despite this wide of range of effects reported for PEMs, clinical significance of the observed effect sizes is not known. There is insufficient information about how to optimise educational materials. The effectiveness of educational materials compared to other interventions is uncertain.
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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 | 0.015 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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 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".