Educational interventions to improve the effectiveness in clinical competence of general practitioners: problem-based versus critical reading-based learning.

BACKGROUND: Evidence suggests that continuing medical education improves the clinical competence of general practitioners and the quality of health care services. Thus, we evaluated the relative impact of two educational strategies, critical reading (CR) and problem based learning (PBL), on the clinical competence of general practitioners in a healthcare system characterized by excessive workload and fragmentation into small primary healthcare centers. METHODS: Clinical competence was evaluated in general practitioners assigned to three groups based on the educational interventions used: 1) critical reading intervention; 2) problem based learning intervention; and 3) no intervention (control group, which continued clinical practice as normal). The effect on the clinical competence of general practitioners was evaluated in three dimensions: the cognitive dimension, via a self-administered questionnaire; the habitual behavioral dimension, via information from patient's medical records; and the affective dimension, through interviews with patients. A paired Student´s t-test was used to evaluate the changes in the mean clinical competence scores before and after the intervention, and a 3 x 2 ANOVA was used to analyze groups, times and their interaction. RESULTS: Nine general practitioners participated in the critical reading workshop, nine in the problem-based learning workshop, and ten were assigned to the control group. The participants exhibited no significant differences in clinical competence measures at baseline, or in socio-demographic or job characteristics (p > 0.05). Significant improvements in all three dimensions (cognitive, 45.67 vs 54.89; habitual behavioral, 53.78 vs 82.33; affective, 4.16 vs 4.76) were only observed in the problem-based learning group after the intervention (p > 0.017). CONCLUSIONS: While no differences in post-intervention scores were observed between groups, we conclude that problem-based learning can be effective, particularly in a small-group context. Indeed, problem-based learning was the only strategy to induce a significant difference between pre- and post- intervention scores for all three CC dimensions.

Performance of two questionnaires to measure treatment adherence in patients with Type-2 diabetes.

BACKGROUND: Most valid methods to measure treatment adherence require time and resources, and they are not easily applied in highly demanding Primary Health Care Clinics (PHCC). The objective of this study was to determine sensitivity, specificity, predictive values, likelihood ratios, and post-test probabilities of two novel questionnaires as proxy measurements of treatment adherence in Type-2 diabetic patients. METHODS: Two questionnaires were developed by a group of experts to identify the patient's medical prescription knowledge (knowledge) and their attitudes toward treatment adherence (attitudes) as proxy measurements of adherence. The questionnaires were completed by patients receiving care in PHCC pertaining to the Mexican Institute of Social Security in Aguascalientes (Mexico). Pill count was used as gold standard. Participants were selected randomly, and their oral hypoglycemic prescriptions were studied. The main outcome measures for each questionnaire were sensitivity, specificity, predictive values, likelihood ratios, and post-test probabilities, all as an independent questionnaire test and in a serial analysis. RESULTS: Adherence prevalence was 27.0% using pill count. Knowledge questionnaire showed the highest sensitivity (68.1%) and negative predictive value (82.2%), the lowest negative likelihood ratio (0.58) and post-test probability for a negative result (0.16). Serial analysis showed the highest specificity (77.4%) and positive predictive value (40.1%) as well as the highest positive likelihood ratio (1.8) and post-test probability for a positive result (0.39). CONCLUSION: Medical Prescription Knowledge questionnaire showed the best performance as proxy measurement to identify non-adherence in type 2 diabetic patients regarding negative predictive value, negative likelihood ratio, and post-test probability for a negative result. However, Medical Prescription Knowledge questionnaire performance may change in contexts with higher adherence prevalence. Therefore, more research is needed before using this method in other contexts.

Quality of life associated with treatment adherence in patients with type 2 diabetes: a cross-sectional study.

BACKGROUND: Despite certain contradictions, an association has been identified between adherence to drug treatment and the quality of life in patients with type 2 diabetes. The contradictions observed emphasize the importance of using different methods to measure treatment adherence, or the association of psychological precursors of adherence with quality of life. For this reason, we have used an indirect method to measure adherence (pill count), as well as two adherence behaviour precursors (attitude and knowledge), to assess the association between adherence and the quality of life in type 2 diabetes patients. METHODS: A cross-sectional comparative study on a random sample of 238 type 2 diabetic patients was carried out over one year in four family medicine units of the Mexican Institute of Social Security (IMSS) in Aguascalientes, Mexico. Treatment adherence was measured using the indirect method of pill count to assess adherence behaviour, obtaining information at two home visits. In the first we recorded the medicine prescribed and in the second, we counted the medicine remaining to determine the proportion of the medicine taken. We also assessed two adherence behaviour precursors: the patients' knowledge regarding their medical prescription measured through a structured questionnaire; and attitudes to treatment adherence using a Likert scale. Quality of life was measured through the WHOQOL-100 (the WHO Quality of Life questionnaire). Information concerning both knowledge and attitude was obtained through interviews with the patients. A multiple linear regression model was constructed to establish the relationship between each quality of life domain and the variables related to adherence, controlling for covariates. RESULTS: There was no association between quality of life and treatment adherence behaviour. However, the combination of strong knowledge and a positive attitude was associated with five of the six quality of life domains. CONCLUSION: The results suggest that it is important to explore psychological precursors of treatment adherence behaviour in type 2 diabetic patients. Indeed, we consider that it will be useful to carry out interventions that change negative attitudes towards treatment adherence and that promote medical prescription knowledge, which may help to improve the quality of life of such patients.