Self-directed learning assessment practices in undergraduate health professions education: a systematic review

PURPOSE

The goal of this systematic review was to examine self-directed learning (SDL) assessment practices in undergraduate health professions education.

METHODS

Seven electronic databases were searched (PubMed, Embase, PsycINFO, ERIC, CINAHL, Scopus, and Web of Science) to retrieve English-language articles published between 2015 and July of 2022, investigating assessment of SDL learning outcomes. Extracted data included the sample size, field of study, study design, SDL activity type, SDL assessment method, number of SDL assessments used, study quality, number of SDL components present utilising the framework the authors developed, and SDL activity outcomes. We also assessed relationships between SDL assessment method and number of SDL components, study quality, field of study, and study outcomes.

RESULTS

Of the 141 studies included, the majority of study participants were medical (51.8%) or nursing (34.8%) students. The most common SDL assessment method used was internally-developed perception surveys (49.6%). When evaluating outcomes for SDL activities, most studies reported a positive or mixed/neutral outcome (58.2% and 34.8%, respectively). There was a statistically significant relationship between both number and type of assessments used, and study quality, with knowledge assessments (median-IQR 11.5) being associated with higher study quality (p < 0.001). Less than half (48.9%) of the studies used more than one assessment method to evaluate the effectiveness of SDL activities. Having more than one assessment (mean 9.49) was associated with higher quality study (p < 0.001).

CONCLUSIONS

The results of our systematic review suggest that SDL assessment practices within undergraduate health professions education vary greatly, as different aspects of SDL were leveraged and implemented by diverse groups of learners to meet different learning needs and professional accreditation requirements. Evidence-based best practices for the assessment of SDL across undergraduate healthcare professions education should include the use of multiple assessments, with direct and indirect measures, to more accurately assess student performance.

Living well: Empirically developed structural equation model for healthy and effective self-regulation

The purpose of this study is to develop and empirically test a structural equation model (SEM) for healthy and effective self-regulation based on the propositions of self-determination theory (SDT). A cross-sectional data sample (N = 6,705) is used to test the model. The results of the SEM demonstrate good to excellent global fit indices (RMSEA = 0.06, SRMR = 0.04 CFI = 0.97, TLI/NNFI = 0.95) and excellent local fit indices (p < 0.001). It is acknowledged that longitudinal and experimental research designs will be necessary to infer causal effects. However, based on the strong theoretical and empirical grounding of the model, indications for causal effects are discussed beyond correlational relations. The local fit indices imply that autonomy of goals, intrinsic values orientation, mindfulness, and the newly integrated construct clarity about personal values positively affect psychological needs satisfaction and facets of subjective and psychological well-being. Additionally, they indicate that mindfulness and clarity about personal values have the greatest benefits on individual health, well-being, and effectiveness. These results are crucial as they emphasize the significant role of mindfulness in healthy and effective self-regulation. Furthermore, they put the spotlight on a rather new construct; clarity about personal values. By having transferred the knowledge base of SDT into an empirically derived model of healthy and effective self-regulation, this study provides well-grounded indications of how health, well-being, and effectiveness in individuals may be fostered. These indications offer new insights for theory building and practical interventions in domains like psychotherapy, healthcare, organizations, sports, and education.

Üniversite Öğrencilerinde Sosyal Medya Bağımlılığını Etkileyen Faktörler ve Sosyal Medya Bağımlılığının Depresyon ve Gelişmeleri Kaçırma Korkusu İle İlişkisi

Amaç: Araştırma üniversite öğrencilerinde sosyal medya bağımlılığını etkileyen faktörleri ve sosyal medya bağımlılığının depresyon, gelişmeleri kaçırma korkusu ile ilişkisini belirlemek amacı ile kesitsel olarak yapılmıştır. Yöntem: Çalışma 448 üniversite öğrencisi ile yapılmıştır. Veriler; anket formu, Sosyal Medya Bağımlılığı Ölçeği-Yetişkin Formu (SMBÖ-YF), Üsküdar Gelişmeleri Kaçırma Korkusu Ölçeği (ÜGKKÖ) ve Beck Depresyon Ölçeği (BDÖ) kullanılarak toplanmıştır. Bulgular: Kadın öğrencilerin SMBÖ-YF puan ortalamalarının erkek öğrencilere göre yüksek olduğu ve yaş arttıkça SMBÖ-YF puanının azaldığı görülmüştür. Annenin sosyal medya kullanımının artması, öğrencilerin uyuşturucu madde kullanması, sosyal medya kullanım sıklığının ve tek oturumda sosyal medya kullanım süresinin artması, sosyal medyaya akıllı telefon ile bağlanmak, sosyal medyayı paylaşımda bulunmak amacıyla kullanmak SMBÖ-YF puanını arttırmaktadır. Öğrencilerin SMBÖ-YF puanları ile BDÖ puanları arasında pozitif yönde zayıf düzeyde, SMBÖ-YF puanları ile ÜGKKÖ puanları arasında pozitif yönde orta düzeyde anlamlı ilişki saptanmıştır. Sosyal medya bağımlılığının artmasındaki en güçlü 3 etken sırasıyla; ÜGKKÖ puanı, günlük 3 saatten fazla sosyal medya kullanımı ve BDÖ puanıdır. Sonuç: Öğrencilerin orta düzeyde sosyal medya bağımlılığına sahip olduğu bulunmuştur. Depresyon ve sosyal medya bağımlılığı birbirlerini çift taraflı olarak etkilemektedir. Aynı şekilde gelişmeleri kaçırma korkusu ve sosyal medya bağımlılığı da birbirlerini çift taraflı olarak etkilemektedir. Öğrencilerin sosyal medya bağımlılığının olumsuz sonuçları ve sosyal medya okuryazarlığı hakkında bilgilendirilmesi, bağımlılık ile ilgili kamu spotlarının sosyal medya üzerinden yayınlanmasının sağlanması önerilebilir.

A comparative study of eight COVID-19 protective measures and their impact on Swiss tourists' travel intentions

A comparative vignette-based experimental survey design incorporating various socio-psychological factors, linked to the Theory of Planned Behavior (TPB), the Health Belief Model (HBM) and the Domain-Specific Risk-Taking scale (DOSPERT) was carried out to test variations in eight travel-related COVID-19 protective measures on Swiss tourists' travel intentions. Among the tested measures, vaccination passports, surgical masks and quarantining are those that stand out the most, with surgical masks having the greatest acceptance and willingness to adopt while traveling. Quarantining, on the other hand, appears to have a deterrent influence on travel intentions, and vaccination passports have the lowest perceived barriers during travel, but the highest perceived benefits in mitigating the spread of the infection. The discussion of individual differences has specific implications for tourism management against the background of our empirical findings.

Kill chaos with kindness: Agreeableness improves team performance under uncertainty

Teams are central to human accomplishment. Over the past half-century, psychologists have identified the Big-Five cross-culturally valid personality variables: Neuroticism, Extraversion, Openness, Conscientiousness, and Agreeableness. The first four have shown consistent relationships with team performance. Agreeableness (being harmonious, altruistic, humble, and cooperative), however, has demonstrated a non-significant and highly variable relationship with team performance. We resolve this inconsistency through computational modelling. An agent-based model (ABM) is used to predict the effects of personality traits on teamwork, and a genetic algorithm is then used to explore the limits of the ABM in order to discover which traits correlate with best and worst performing teams for a problem with different levels of uncertainty (noise). New dependencies revealed by the exploration are corroborated by analyzing previously unseen data from one of the largest datasets on team performance to date comprising 3698 individuals in 593 teams working on more than 5000 group tasks with and without uncertainty, collected over a 10-year period. Our finding is that the dependency between team performance and Agreeableness is moderated by task uncertainty. Combining evolutionary computation with ABMs in this way provides a new methodology for the scientific investigation of teamwork, making new predictions, and improving our understanding of human behaviors. Our results confirm the potential usefulness of computer modelling for developing theory, as well as shedding light on the future of teams as work environments are becoming increasingly fluid and uncertain.

Review of Probability Elicitation and Examination of Approaches for Large Bayesian Networks

Probability elicitation is the process of formulating a person's knowledge and beliefs about one or more uncertain quantities into a joint probability distribution for those quantities. The important point is that the goal of elicitation is to capture a person's knowledge and beliefs based upon their current state of information. Consequently, the results of elicitation need be only good enough to make reasoned decisions or reasonable inferences. This chapter identifies how to elicit probabilities for large conditional probability tables in Bayesian networks. This chapter looks at Bayesian networks which are statistical models to describe and visualize in a compact graphical form the probabilistic relationships between variables of interest; the nodes of a graphical structure correspond to the variables, while directed edges between the nodes encode conditional independence relationships between them.