Objective: The purpose of this study was to test the validity of a model of professional development that was based on occupational adaptation. This model proposes that students have three classes of adaptive response behaviors available for use: primitive, transitional, and mature.
Method: Eight Level II fieldwork students were assigned to the Department of Veterans Affairs Medical Center, Dallas, Texas, for 12 weeks. Experienced fieldwork supervisors at the medical center developed a taxonomy of behavioral statements consistent with the developmental model's three classes of adaptive response behaviors. This taxonomy was converted to a student log in which supervisors rated the frequency with which the Level II fieldwork students exhibited these behaviors.
Results: The patterns of behaviors, which were represented graphically for each of the students, generally supported the predictions of the model. Students demonstrated all three classes of behaviors. Primitive and transitional behaviors emerged when the students experienced increased or unusual demands, even when the students' model behavior was mature. Students temporarily reverted to lower level behaviors when faced with situations that they perceived as too difficult or as too unfamiliar.
Conclusion: This model of professional development facilitates an understanding of students' development during their transition from classroom to practice setting. Generalization to other settings will require validation of the student log.
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http://dx.doi.org/10.5014/ajot.49.2.119 | DOI Listing |
J Med Internet Res
January 2025
Department of Engineering Management and Systems Engineering, George Washington University, Washington, DC, United States.
Background: Large language model (LLM) artificial intelligence chatbots using generative language can offer smoking cessation information and advice. However, little is known about the reliability of the information provided to users.
Objective: This study aims to examine whether 3 ChatGPT chatbots-the World Health Organization's Sarah, BeFreeGPT, and BasicGPT-provide reliable information on how to quit smoking.
J Glob Health
January 2025
Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Background: The prevalence of antibiotic prescribing among total prescriptions, the percentage of combined antibiotic prescribing among prescriptions containing at least one antibiotic, and factors influencing hospital antibiotic prescribing are currently unknown. In this systematic review, we aimed to summarise antibiotic prescribing in hospitals worldwide and identify the associated factors.
Methods: We searched PubMed/MEDLINE, Ovid/Embase, and the Web of Science for articles published between 1 January 2000 and 28 February 2023 that reported antibiotic prescribing in hospitals or the associated factors.
PLoS One
January 2025
University of Birmingham, Birmingham, United Kingdom.
Grounded in Duda's integrated model of the motivational climate, the current study examined the hypothesized mediating role of motivation quality in the relationships between empowering and disempowering teacher-created motivational climates and indicators of quality engagement in secondary school physical education (PE). The hypothesised model was tested cross-sectionally and longitudinally in two separate samples of students. Data were collected via questionnaires measuring the motivational climate, autonomous and controlled motivation and indicators of engagement (enjoyment, concentration and boredom).
View Article and Find Full Text PDFJ Am Med Inform Assoc
January 2025
Institute of Intelligent Rehabilitation Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Background: With the global population aging and advancements in the medical system, long-term care in healthcare institutions and home settings has become essential for older adults with disabilities. However, the diverse and scattered care requirements of these individuals make developing effective long-term care plans heavily reliant on professional nursing staff, and even experienced caregivers may make mistakes or face confusion during the care plan development process. Consequently, there is a rigid demand for intelligent systems that can recommend comprehensive long-term care plans for older adults with disabilities who have stable clinical conditions.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Ronald O. Perelman Department of Emergency Medicine, New York University Langone Health, New York.
Importance: Increasing underrepresented in medicine (URIM) physicians among historically underserved communities helps reduce health disparities. The concordance of URIM physicians with their communities improves access to care, particularly for American Indian and Alaska Native, Black, and Hispanic or Latinx individuals.
Objectives: To explore county-level racial and ethnic representation of US internal medicine (IM) residents, examine racial and ethnic concordance between residents and their communities, and assess whether representation varies by presence of academic institutions or underserved settings.
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