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Distracted driving is responsible for nearly 1 million crashes each year in the United States alone, and a major source of driver distraction is handheld phone use. We conducted a randomized, controlled trial to compare the effectiveness of interventions designed to create sustained reductions in handheld use while driving (NCT04587609). Participants were 1,653 consenting Progressive® Snapshot® usage-based auto insurance customers ages 18 to 77 who averaged at least 2 min/h of handheld use while driving in the month prior to study invitation. They were randomly assigned to one of five arms for a 10-wk intervention period. Arm 1 (control) got education about the risks of handheld phone use, as did the other arms. Arm 2 got a free phone mount to facilitate hands-free use. Arm 3 got the mount plus a commitment exercise and tips for hands-free use. Arm 4 got the mount, commitment, and tips plus weekly goal gamification and social competition. Arm 5 was the same as Arm 4, plus offered behaviorally designed financial incentives. Postintervention, participants were monitored until the end of their insurance rating period, 25 to 65 d more. Outcome differences were measured using fractional logistic regression. Arm 4 participants, who received gamification and competition, reduced their handheld use by 20.5% relative to control (P < 0.001); Arm 5 participants, who additionally received financial incentives, reduced their use by 27.6% (P < 0.001). Both groups sustained these reductions through the end of their insurance rating period. [ABSTRACT FROM AUTHOR]

Connected healthcare is a form of health delivery that connects patients and providers through connected health devices, allowing providers to monitor patient behavior and proactively intervene before an adverse event occurs. Unlike the costs, the benefits of connected healthcare in improving patient behavior and health outcomes are usually difficult to determine. In this study, we examine the efficacy of a connected health system that aimed to reduce readmissions through improved medication adherence. Specifically, we study 975 patients with heart disease who received electronic pill bottles that tracked medication adherence. Patients who were nonadherent received active social support that involved different types of feedback, such as text messages and calls. By integrating data on adherence, intervention, and readmission, we aim to (1) investigate the efficacy of connected healthcare in promoting medication adherence, (2) examine the relationship between medication adherence and readmission, and (3) develop a dynamic readmission risk-scoring model that considers medication adherence and use the model to better target nonadherent patients. Our findings suggest that patients are more likely to become adherent when they or their partners receive high levels of intervention that involve personalized feedback and when the intervention is escalated quickly and consistently. We also find that long-term adherence to three common heart medications is strongly associated with reduced readmission risk. Lastly, using counterfactual simulation, we apply the dynamic readmission risk-scoring model to our setting and find that, when using an intervention strategy that prioritizes high-risk patients, we obtain 10% fewer readmissions while using the same effort level from the patient support team. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: The randomized, controlled trial was funded by the Center for Medicare & Medicaid Innovation [Healthcare Innovation Award 1C1CMS331009]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4865. [ABSTRACT FROM AUTHOR]

This article discusses the use of behavioral science to improve cardiovascular health. It highlights the importance of understanding human behavior and decision-making processes in order to design effective programs that promote healthier choices without limiting freedom of choice. The article also explores the role of financial incentives, defaults, and nudges in influencing behavior and improving adherence to recommended treatments. Additionally, it discusses the potential of social incentives, gamification, and access to healthy food in promoting healthy behaviors. The article emphasizes the need for training clinicians in behavioral economics to positively influence clinician and patient behavior and ultimately improve health outcomes. [Extracted from the article]

PurposeTo determine whether the 2003 Accreditation Council for Graduate Medical Education (ACGME) duty hours reform affected medical knowledge as reflected by written board scores for internal medicine (IM) residents.MethodThe authors conducted a retrospective cohort analysis of postgraduate year 1 (PGY-1) Internal Medicine residents who started training before and after the 2003 duty hour reform using a merged data set of American Board of Internal Medicine (ABIM) Board examination and the National Board of Medical Examiners (NMBE) United States Medical Licensing Examination (USMLE) Step 2 Clinical Knowledge test scores. Specifically, using four regression models, the authors compared IM residents beginning PGY-1 training in 2000 and completing training unexposed to the 2003 duty hours reform (PGY-1 2000 cohort, n = 5,475) to PGY-1 cohorts starting in 2001 through 2005 (n = 28,008), all with some exposure to the reform.ResultsThe mean ABIM board score for the unexposed PGY-1 2000 cohort (n = 5,475) was 491, SD = 85. Adjusting for demographics, program, and USMLE Step 2 exam score, the mean differences (95% CI) in ABIM board scores between the PGY-1 2001, 2002, 2003, 2004 and 2005 cohorts minus the PGY-1 2000 cohort were -5.43 (-7.63, -3.23), -3.44 (-5.65, -1.24), 2.58 (0.36, 4.79), 11.10 (8.88, 13.33) and 11.28 (8.98, 13.58) points respectively. None of these differences exceeded one-fifth of an SD in ABIM board scores.ConclusionsThe duty hours reforms of 2003 did not meaningfully affect medical knowledge as measured by scores on the ABIM board examinations.

In efforts to combat tobacco dependence, most smoking cessation programs offer individuals who smoke the choice of a target quit date. However, it is uncertain whether the time to the selected quit date is associated with participants' chances of achieving sustained abstinence. In a pre-specified secondary analysis of a randomized clinical trial of four financial-incentive programs or usual care to encourage smoking cessation (Halpern et al. in N Engl J Med 372(22):2108-2117, doi:10.1056/NEJMoa1414293, 2015 (See CR8)), study participants were instructed to select a quit date between 0 and 90 days from enrollment. Among those who selected a quit date and provided complete baseline data (n = 1848), we used multivariable logistic regression to evaluate the association of the time to the selected quit date with 6- and 12-month biochemically-confirmed abstinence rates. In the fully adjusted model, the probability of being abstinent at 6 months if the participant selected a quit date in weeks 1, 5, 10, and 13 were 39.6, 22.6, 10.9, and 4.3%, respectively., Author(s): George L. Anesi [sup.1] [sup.2] [sup.3] , Scott D. Halpern [sup.1] [sup.2] [sup.3] [sup.4] , Michael O. Harhay [sup.2] [sup.3] [sup.5] , Kevin G. Volpp [sup.3] [sup.4] [sup.5] [sup.6] [...]

Background: Financial incentives and peer networks could be delivered through eHealth technologies to encourage older adults to walk more. Methods: We conducted a 24-week randomized trial in which 92 older adults with a computer and Internet access received a pedometer, daily walking goals, and weekly feedback on goal achievement. Participants were randomized to weekly feedback only (Comparison), entry into a lottery with potential to earn up to $200 each week walking goals were met (Financial Incentive), linkage to four other participants through an online message board (Peer Network), or both interventions (Combined). Main outcomes were the proportion of days walking goals were met during the 16-week intervention and 8-week follow-up. We conducted a content analysis of messages posted by Peer Network and Combined arm participants. Results: During the 16-week intervention, there were no differences in the proportion of days walking goals were met in the Financial Incentive (39.7%; p = 0.78), Peer Network (24.9%; p = 0.08), and Combined (36.0%; p = 0.77) arms compared with the Comparison arm (36.0%). During 8 weeks of follow-up, the proportion of days walking goals were met was lower in the Peer Network arm (18.7%; p = 0.025) but not in the Financial Incentive (29.3%; p = 0.50) or Combined (24.8%; p = 0.37) arms, relative to the Comparison arm (34.5%). Messages posted by participants focused on barriers to walking and provision of social support. Conclusions: Financial incentives and peer networks delivered through eHealth technologies did not result in older adults walking more. [This article is part of an open access supplement "Fostering Engagement and Independence: Opportunities and Challenges for an Aging Society," published in SOPHE's "Health Education & Behavior." This supplement was supported by funding provided by the Centers for Disease Control and Prevention's (CDC) National Center for Chronic Disease Prevention and Health Promotion, Healthy Aging Program (Cooperative Agreement #U38HM000454) via the Association of State and Territorial Health Officials, and from a grant provided by the Retirement Research Foundation.]