Context Identifying effective strategies for treating obesity is both a clinical challenge and a public health priority due to the health consequences of obesity. Objective To determine whether common decision errors identified by behavioral economists such as prospect theory, loss aversion, and regret could be used to design an effective weight loss intervention. Design 3-arm randomized controlled trial in which participants were randomized to either usual care (weigh ins once a month) or one of two financial incentives arms. One incentive arm used deposit contracts in which participants put their own money at risk (matched 1:1 by the study) which they would lose if they failed to lose weight. The second used lottery-based incentives in which participants who met the weight loss target had each day a 1 in 5 chance of winning a small reward ($10) and a 1 in 100 chance of winning a large reward ($100). All participants were given a weight loss goal of 1 pound per week for 16 weeks, and results were analyzed using intention-to-treat analysis of variance models. Setting Philadelphia Veterans Affairs Medical Center. Patients 57 patients with BMIs between 30-40 aged between 30 and 70, with no contraindications for study participation. Main Outcome Measures Weight loss after 16 weeks. Results Participants in both incentive groups lost significantly more weight than participants in the control group (3.9 pounds); (Lottery = 13.1 lbs; p-value for lottery vs. control .014; deposit contract = 14.0 lbs, p-value vs. control .003). 47.4% of deposit contract participants and 52.6% of lottery arm participants met the 16-pound weight loss goal compared to 10.5% in the control group (p-value 0.014.). By the end of 7 months, substantial amounts of weight were regained; however, incentive participants weighed significantly less than they did at the study start whereas controls did not. Low lost to follow-up rates (7.0%) during the weight loss phase of the study suggest that both incentive systems were successful in keeping participants engaged in the study. Conclusions Incentive approaches based on behavioral economic concepts could have a major impact in reducing the incidence of obesity-related illnesses.

burned. Underlying differences in device accuracy may be compounded in these measures.Our study is limited by being conducted with young, healthy volunteers in a controlled setting with a convenience sample of a small number of applications and devices. Results should be confirmed in other settings and with other devices.Increased physical activity facilitated by these devices could lead to clinical benefits not realized by low adoption of pedometers. Our findings may help reinforce individuals' trust in using smartphone applications and wearable devices to track health behaviors, which could have important implications for strategies to improve population health. Role of the Funder/Sponsor: The National Institute on Aging, the US Department of Veteran Affairs, and the Robert Wood Johnson Foundation had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Meredith COMMENT & RESPONSE Treating Chronic Knee Pain With AcupunctureTo the Editor In the randomized clinical trial of acupuncture for chronic knee pain, 1 the acupuncture treatment design appeared flawed. Specifically, the acupuncture points were nonstandardized and the study lacked the details necessary to ascertain whether the provided interventions were representative of acupuncture sessions appropriate for chronic knee pain. First, the acupuncture regimen was not consistent in the study, with some patients receiving less than 1 treatment per week, some patients receiving 1 treatment per week, and others receiving 2 treatments per week for 12 weeks. Dr Hinman and colleagues failed to report how many patients received 1 or 2 treatments per week. The commonly used frequency of acupuncture treatments for chronic knee pain due to osteoarthritis is 2 treatments per week for 8 weeks, followed by 2 weeks of 1 treatment per week, then 4 weeks of 1 treatment every other week, and finally 12 weeks of 1 treatment per month.2 Furthermore, no details were provided regarding depth of insertion or whether subjective deqi sensation was experienced by the patient. Deqi has been shown to be important to differential neurophysiological analgesic mechanisms in responders vs nonresponders to acupuncture.3 Hinman and colleagues also did not provide acupuncture with electrical stimulation, which not only has a dose-dependent effect on the degree of analgesia but also induces differential neurotransmitter responses depending on the electrical frequency used. 2,4The only conclusion that can be drawn from this study is that unsystematic acupuncture regimens did not result in significant clinical benefit to patients with chronic knee pain.

No abstract

BACKGROUND: Previous efforts to use incentives for weight loss have resulted in substantial weight regain after 16 weeks. OBJECTIVE: To evaluate a longer term weight loss intervention using financial incentives. DESIGN: A 32-week, three-arm randomized controlled trial of financial incentives for weight loss consisting of a 24-week weight loss phase during which all participants were given a weight loss goal of 1 pound per week, followed by an 8-week maintenance phase. PARTICIPANTS: Veterans who were patients at the Philadelphia Veterans Affairs Medical Center with BMIs of 30-40. INTERVENTION: Participants were randomly assigned to participate in either a weight-monitoring program involving a consultation with a dietician and monthly weigh-ins (control condition), or the same program with one of two financial incentive plans. Both incentive arms used deposit contracts (DC) in which participants put their own money at risk (matched 1:1), which they lost if they failed to lose weight. In one incentive arm participants were told that the period after 24 weeks was for weight-loss maintenance; in the other, no such distinction was made. MAIN MEASURE: Weight loss after 32 weeks. KEY RESULTS: Results were analyzed using intention-to-treat. There was no difference in weight loss between the incentive arms (P=0.80). Incentive participants lost more weight than control participants [mean DC = 8.70 pounds, mean control = 1.17, P= 0.04, 95% CI of the difference in means (0.56, 14.50)]. Follow-up data 36 weeks after the 32-week intervention had ended indicated weight regain; the net weight loss between the incentive and control groups was no longer significant (mean DC = 1.2 pounds, 95% CI, -2.58-5.00; mean control = 0.27, 95% CI, -3.77-4.30, P=0.76). CONCLUSIONS: Financial incentives produced significant weight loss over an 8-month intervention; however, participants regained weight post-intervention.

Background Financial incentive designs to increase physical activity have not been well-examined. Objective To test the effectiveness of 3 methods to frame financial incentives to increase physical activity among overweight and obese adults. Design Randomized, controlled trial. (ClinicalTrials.gov: NCT 02030119) Setting University of Pennsylvania. Participants 281 adult employees (body mass index ≥27 kg/m2). Intervention 13-week intervention. Participants had a goal of 7000 steps per day and were randomly assigned to a control group with daily feedback or 1 of 3 financial incentive programs with daily feedback: a gain incentive ($1.40 given each day the goal was achieved), lottery incentive (daily eligibility [expected value approximately $1.40] if goal was achieved), or loss incentive ($42 allocated monthly upfront and $1.40 removed each day the goal was not achieved). Participants were followed for another 13 weeks with daily performance feedback but no incentives. Measurements Primary outcome was the mean proportion of participant-days that the 7000-step goal was achieved during the intervention. Secondary outcomes included the mean proportion of participant-days achieving the goal during follow-up and the mean daily steps during intervention and follow-up. Results The mean proportion of participant-days achieving the goal was 0.30 (95% CI, 0.22 to 0.37) in the control group, 0.35 (CI, 0.28 to 0.42) in the gain-incentive group, 0.36 (CI, 0.29 to 0.43) in the lottery-incentive group, and 0.45 (CI, 0.38 to 0.52) in the loss-incentive group. In adjusted analyses, only the loss-incentive group had a significantly greater mean proportion of participant-days achieving the goal than control (adjusted difference, 0.16 [CI, 0.06 to 0.26]; P = 0.001), but the adjusted difference in mean daily steps was not significant (861 [CI, 24 to 1746]; P = 0.056). During follow-up, daily steps decreased for all incentive groups and were not different from control. Limitation Single employer. Conclusion Financial incentives framed as a loss were most effective for achieving physical activity goals. Primary Funding Source National Institute on Aging.

IMPORTANCE Gamification, the application of game design elements such as points and levels in nongame contexts, is often used in digital health interventions, but evidence on its effectiveness is limited.OBJECTIVE To test the effectiveness of a gamification intervention designed using insights from behavioral economics to enhance social incentives within families to increase physical activity. DESIGN, SETTING, AND PARTICIPANTSThe Behavioral Economics Framingham Incentive Trial (BE FIT) was a randomized clinical trial with a 12-week intervention period and a 12-week follow-up period. The investigation was a community-based study between December 7, 2015, and August 14, 2016. Participants in the modified intent-to-treat analysis were adults enrolled in the Framingham Heart Study, a long-standing cohort of families.INTERVENTIONS All participants tracked daily step counts using a wearable device or a smartphone, established a baseline, selected a step goal increase, and received daily individual feedback on goal performance by text message or email for 24 weeks. Families in the gamification arm could earn points and progress through levels based on physical activity goal achievement during the 12-week intervention. The game design was meant to enhance collaboration, accountability, and peer support. MAIN OUTCOMES AND MEASURESThe primary outcome was the proportion of participant-days that step goals were achieved during the intervention period. Secondary outcomes included the proportion of participant-days that step goals were achieved during the follow-up period and the change in the mean daily steps during the intervention and follow-up periods. RESULTS Among 200 adults comprising 94 families, the mean age was 55.4 years, and 56.0% (n = 112) were female. During the intervention period, participants in the gamification arm achieved step goals on a significantly greater proportion of participant-days (0.53 vs 0.32; adjusted difference, 0.27; 95% CI, 0.20-0.33; P < .001) and had a significantly greater increase in the mean daily steps compared with baseline (1661 vs 636; adjusted difference, 953; 95% CI, 505-1401; P < .001) than the control arm. During the follow-up period, physical activity in the gamification arm declined but remained significantly greater than that in the control arm for the proportion of participant-days achieving step goals (0.44 vs 0.33; adjusted difference, 0.12; 95% CI, 0.05-0.19; P < .001) and the mean daily steps compared with baseline (1385 vs 798; adjusted difference, 494; 95% CI, 170-818; P < .01).CONCLUSIONS AND RELEVANCE Gamification designed to leverage insights from behavioral economics to enhance social incentives significantly increased physical activity among families in the community. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT02531763

for all ACGME-accredited residency programs. 2,3 Work limitations for residents included no more than 80 hours per week, with 1 day in 7 free of all duties, averaged over 4 weeks; no more than 24 continuous hours with an additional 6 hours for education and transfer of care; in-house call no more frequently than every third night; and at least 10 hours of rest between duty periods. 2 Although there is extensive scientific evidence linking fatigue and impaired cognitive performance, 4-9 little empirical data guided the design of the duty hour regulations, 10,11 and the design itself remains controversial, 12,13 with contrasting views as to whether the duty See also pp 984 and 1055.

A multipayer medical home pilot, in which participating practices adopted new structural capabilities and received NCQA certification, was associated with limited improvements in quality and was not associated with reductions in utilization of hospital, emergency department, or ambulatory care services or total costs over 3 years. These findings suggest that medical home interventions may need further refinement.