Correlation between theoretical knowledge and the difference between self- and teaching doctor-assessment

OBJECTIVES

The right intuition for self-assessment without overestimating or underestimating oneself compared to theoretical knowledge is a skill that requires conscious practice and is very often paradoxically opposed to the level of knowledge. Self-assessment is an essential skill for dental professionals for lifelong learning and improvement. The objective of our study was to assess the correlation between theoretical knowledge and the difference between self- and teaching doctor-assessment.

METHODS

The app "digital course organizer" for organization and assessment was used for the self- and teaching doctor-assessment of students for each day of patient treatment during the clinical courses at a university hospital. The difference between the self- and teaching doctor-assessment was compared to the score of an initial theoretical written test at the beginning of the eighth semester to assess the correlation between overestimation or underestimation and theoretical knowledge.

RESULTS

A total of 309 dental students over four semesters in the clinical study phase (fourth and fifth years; eighth and 10th semesters) participated in the investigation. The overall view of all values showed very low correlations (<0.2) of the assessment difference values of both practical courses for the initial written test.

CONCLUSION

There were very low correlations between the initial written test (theoretical knowledge) and the difference between self- and teaching doctor-assessment as well as no evidence of overestimation and underestimation.

Understanding the interplay of self-regulated learning strategies in medical education: A cross-sectional structural equation modeling study

Background and Aims

Although previous studies have investigated self-regulated learning strategies, a holistic study has not been conducted on note-taking, environmental structuring, self-evaluation, and self-consequence strategies among medical students. The current study focused on the relationships between these four self-regulated learning strategies in a medical context.

Methods

A conceptual model of the four strategies was developed, supported by the relevant literature. This cross-sectional study used an electronic structured questionnaire. The sample consisted of 557 medical undergraduates. The data were analysed using confirmatory factor analysis and structural equation modeling to investigate the hypothetical model.

Results

The conceptual model fits the data well. All relationships between the strategies were significantly positive, except for a regression between environmental structuring and self-evaluation, which was nonsignificant. Self-evaluation strategies represented the highest mean, whereas self-consequence strategies represented the lowest.

Conclusion

The findings of this study have implications for medical students, their teachers, and their universities regarding ways to enhance learners' regulated learning strategies. Future research should be conducted to develop additional statistical and comparison models for use in experimental studies and longitudinal investigations.

What Influences Work Engagement Among Registered Nurses: Implications for Evidence-Based Action

BACKGROUND

Previous studies evaluating work engagement of nurses revealed work-related factors and nurse demographics affecting work engagement. Low work engagement yields a decrease in productivity, high turnover, loss of revenue, and, most importantly, patient safety concerns.

AIM

To investigate the relationship between nurse-related and work-related variables associated with work engagement and provide a model that explains work engagement.

METHOD

This study employed an observational, cross-sectional study design, with 201 registered nurses working in acute care hospitals in the United States participating in the study. Four work-related and five nurse-related variables were evaluated and used in the work engagement model. A standard multiple regression was performed using the work- and nurse-related factors regressed onto work engagement. Structural equation model procedures were performed to examine the association between predictive variables and work engagement.

RESULTS

Of the 201 participants, just over a third of the participants were over 50 years of age (33.5%), female (91.6%), married (68%), had a bachelor of science in nursing (58.1%), and have been a nurse <5 years (42.4%). Five of the variables were found to make a unique statistically significant contribution to the variance in work engagement, age (β = .31, p = .001), workload (β = .30, p < .001), Core Self-Evaluation Scale (β = 0 .22, p = .002), Coping with Change Scale (β = .20, p = .001), and Maslach Burnout Inventory (MBI)-General Scale score (β = -.17, p = .03). The work engagement model indicated a satisfactory overall model fit of the model (GFI = .996; χ2 (2, N = 201) = 4.02, p = .135; RMSEA = .07; CFI = .983; NFI = .976).

LINKING EVIDENCE TO ACTION

The results of this study confirm a work engagement model that incorporates both nurse- and work-related factors. Overall, the results indicate that the level of work engagement is predicted more by nurse-related factors than by work-related factors.