Triggers of Lapse and Relapse of Diet and Exercise in Behavioral Weight Loss.

OBJECTIVE: This study aimed to (1) develop instruments to evaluate situations that lead to lapse and relapse in diet and exercise and (2) prospectively investigate when and which psychosocial situations predict failure to lose weight in a clinical trial of intentional weight loss. METHODS: Participants were 469 individuals with overweight or obesity participating in a behavioral weight loss program (age: mean = 53.6 years, SD = 11.4; BMI: mean = 35.7 kg/m2 , SD = 6.5). RESULTS: The Cronbach alphas for the Diet Lapse and Relapse Triggers Scale and the Exercise Lapse and Relapse Triggers Scale were 0.93 and 0.91, respectively. Subscale alphas ranged from 0.60 to 0.96. Lapse and relapse were assessed at 3 and 9 months for associations with weight loss at 12 months. At 9 months, diet triggers were negative emotional states (beta = 0.11, P = 0.02) and urges (beta = 0.14, P = 0.01). Predicted social situations showed the opposite (beta = -0.09, P = 0.02). Exercise subscales were all nonsignificant. CONCLUSIONS: Findings suggest the ongoing importance of addressing negative emotional states and the contributing influence of urges. The novel finding that participants whose difficulties arise in social situations may do better over time requires further study.

Weight change, psychological well-being, and vitality in adults participating in a cognitive-behavioral weight loss program.

OBJECTIVE: Excess weight has been associated with numerous psychological problems, including depression and anxiety. This study examined the impact of intentional weight loss on the psychological well-being of adults participating in three clinical weight loss interventions. METHODS: This population consisted of 588 overweight or obese individuals randomized into one of three weight loss interventions of incremental intensity for 12 months. Psychological well-being was measured at baseline and 6, and 12 months using the Psychological Well-Being Index. RESULTS: Mean weight loss was 5.0 pounds at 12 months. Weight change at 12 months was associated with higher overall psychological well-being (r = -.20, p < .001), lower levels of anxiety (r = -.16, p = .001) and depression (r = -.13, p = .004), and higher positive well-being (r = -.19, p < .001), self-control (r = -.13, p = .004), and vitality (r = -.22, p < .001). Vitality was found to be the best predictor of weight change at 12 months (p < .001). CONCLUSIONS: Weight loss was associated with positive changes in psychological well-being. Increased vitality contributed the largest percentage of variance to this change.

Health information technology and the medical school curriculum.

Medical schools must teach core biomedical informatics competencies that address health information technology (HIT), including explaining electronic medical record systems and computerized provider order entry systems and their role in patient safety; describing the research uses and limitations of a clinical data warehouse; understanding the concepts and importance of information system interoperability; explaining the difference between biomedical informatics and HIT; and explaining the ways clinical information systems can fail. Barriers to including these topics in the curricula include lack of teachers; the perception that informatics competencies are not applicable during preclinical courses and there is no place in the clerkships to teach them; and the legal and policy issues that conflict with students' need to develop skills. However, curricular reform efforts are creating opportunities to teach these topics with new emphasis on patient safety, team-based medical practice, and evidence-based care. Overarching HIT competencies empower our students to be lifelong technology learners.

Semi automatic indexing of PostScript files using Medical Text Indexer in medical education.

At Albert Einstein College of Medicine a large part of online lecture materials contain PostScript files. As the collection grows it becomes essential to create a digital library to have easy access to relevant sections of the lecture material that is full-text indexed; to create this index it is necessary to extract all the text from the document files that constitute the originals of the lectures. In this study we present a semi automatic indexing method using robust technique for extracting text from PostScript files and National Library of Medicine's Medical Text Indexer (MTI) program for indexing the text. This model can be applied to other medical schools for indexing purposes.