Laurie Norton
University of Pennsylvania
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JAMA | 2008
Kevin G. Volpp; Leslie K. John; Andrea B. Troxel; Laurie Norton; Jennifer E. Fassbender; George Loewenstein
CONTEXT Identifying effective obesity treatment 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, SETTING, AND PARTICIPANTS Fifty-seven healthy participants aged 30-70 years with a body mass index of 30-40 were randomized to 3 weight loss plans: monthly weigh-ins, a lottery incentive program, or a deposit contract that allowed for participant matching, with a weight loss goal of 1 lb (0.45 kg) a week for 16 weeks. Participants were recruited May-August 2007 at the Philadelphia VA Medical Center in Pennsylvania and were followed up through June 2008. MAIN OUTCOME MEASURES Weight loss after 16 weeks. RESULTS The incentive groups lost significantly more weight than the control group (mean, 3.9 lb). Compared with the control group, the lottery group lost a mean of 13.1 lb (95% confidence interval [CI] of the difference in means, 1.95-16.40; P = .02) and the deposit contract group lost a mean of 14.0 lb (95% CI of the difference in means, 3.69-16.43; P = .006). About half of those in both incentive groups met the 16-lb target weight loss: 47.4% (95% CI, 24.5%-71.1%) in the deposit contract group and 52.6% (95% CI, 28.9%-75.6%) in the lottery group, whereas 10.5% (95% CI, 1.3%-33.1%; P = .01) in the control group met the 16-lb target. Although the net weight loss between enrollment in the study and at the end of 7 months was larger in the incentive groups (9.2 lb; t = 1.21; 95% CI, -3.20 to 12.66; P = .23, in the lottery group and 6.2 lb; t = 0.52; 95% CI, -5.17 to 8.75; P = .61 in the deposit contract group) than in the control group (4.4 lb), these differences were not statistically significant. However, incentive participants weighed significantly less at 7 months than at the study start (P = .01 for the lottery group; P = .03 for the deposit contract group) whereas controls did not. CONCLUSIONS The use of economic incentives produced significant weight loss during the 16 weeks of intervention that was not fully sustained. The longer-term use of incentives should be evaluated. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00520611.
Annals of Internal Medicine | 2013
Jeffrey T. Kullgren; Andrea B. Troxel; George Loewenstein; David A. Asch; Laurie Norton; Lisa Wesby; Yuanyuan Tao; Jingsan Zhu; Kevin G. Volpp
BACKGROUND Data on the effectiveness of employer-sponsored financial incentives for employee weight loss are limited. OBJECTIVE To test the effectiveness of 2 financial incentive designs for promoting weight loss among obese employees. DESIGN Randomized, controlled trial. (ClinicalTrials.gov: NCT01208350) SETTING Childrens Hospital of Philadelphia. PARTICIPANTS 105 employees with a body mass index between 30 and 40 kg/m2. INTERVENTION 24 weeks of monthly weigh-ins (control group; n = 35); individual incentive, designed as
JAMA | 2012
Kevin G. Volpp; Judy A. Shea; Dylan S. Small; Mathias Basner; Jingsan Zhu; Laurie Norton; Adrian J. Ecker; Cristina Novak; Lisa M. Bellini; C. Jessica Dine; Daniel J. Mollicone; David F. Dinges
100 per person per month for meeting or exceeding weight-loss goals (n = 35); and group incentive, designed as
JAMA Internal Medicine | 2017
Kevin G. Volpp; Andrea B. Troxel; Shivan J. Mehta; Laurie Norton; Jingsan Zhu; Raymond Lim; Wenli Wang; Noora Marcus; Christian Terwiesch; Kristen Caldarella; Tova Levin; Mike Relish; Nathan S. Negin; Aaron Smith-McLallen; Richard Snyder; Claire M. Spettell; Brian M. Drachman; Daniel M. Kolansky; David A. Asch
500 per month split among participants within groups of 5 who met or exceeded weight-loss goals (n = 35). MEASUREMENTS Weight loss after 24 weeks (primary outcome) and 36 weeks and changes in behavioral mediators of weight loss (secondary outcomes). RESULTS Group-incentive participants lost more weight than control participants (mean between-group difference, 4.4 kg [95% CI, 2.0 to 6.7 kg]; P < 0.001) and individual-incentive participants (mean between-group difference, 3.2 kg [CI, 0.9 to 5.5 kg]; P = 0.008). Twelve weeks after incentives ended and after adjustment for 3-group comparisons, group-incentive participants maintained greater weight loss than control group participants (mean between-group difference, 2.9 kg [CI, 0.5 to 5.3 kg]; P = 0.016) but not greater than individual-incentive participants (mean between-group difference, 2.7 kg [CI, 0.4 to 5.0 kg]; P = 0.024). LIMITATION Single employer and short follow-up. CONCLUSION A group-based financial incentive was more effective than an individual incentive and monthly weigh-ins at promoting weight loss among obese employees at 24 weeks. PRIMARY FUNDING SOURCE National Institute on Aging.
Sleep | 2017
Mathias Basner; David F. Dinges; Judy A. Shea; Dylan S. Small; Jingsan Zhu; Laurie Norton; Adrian J. Ecker; Cristina Novak; Lisa M. Bellini; Kevin G. Volpp
CONTEXT A 2009 Institute of Medicine report recommended protected sleep periods for medicine trainees on extended overnight shifts, a position reinforced by new Accreditation Council for Graduate Medical Education requirements. OBJECTIVE To evaluate the feasibility and consequences of protected sleep periods during extended duty. DESIGN, SETTING, AND PARTICIPANTS Randomized controlled trial conducted at the Philadelphia VA Medical Center medical service and Oncology Unit of the Hospital of the University of Pennsylvania (2009-2010). Of the 106 interns and senior medical students who consented, 3 were not scheduled on any study rotations. Among the others, 44 worked at the VA center, 16 at the university hospital, and 43 at both. INTERVENTION Twelve 4-week blocks were randomly assigned to either a standard intern schedule (extended duty overnight shifts of up to 30 hours; equivalent to 1200 overnight intern shifts at each site), or a protected sleep period (protected time from 12:30 AM to 5:30 AM with handover of work cell phone; equivalent to 1200 overnight intern shifts at each site). Participants were asked to wear wrist actigraphs and complete sleep diaries. MAIN OUTCOME MEASURES Primary outcome was hours slept during the protected period on extended duty overnight shifts. Secondary outcome measures included hours slept during a 24-hour period (noon to noon) by day of call cycle and Karolinska sleepiness scale. RESULTS For 98.3% of on-call nights, cell phones were signed out as designed. At the VA center, participants with protected sleep had a mean 2.86 hours (95% CI, 2.57-3.10 hours) of sleep vs 1.98 hours (95% CI, 1.68-2.28 hours) among those who did not have protected hours of sleep (P < .001). At the university hospital, participants with protected sleep had a mean 3.04 hours (95% CI, 2.77-3.45 hours) of sleep vs 2.04 hours (95% CI, 1.79-2.24) among those who did not have protected sleep (P < .001). Participants with protected sleep were significantly less likely to have call nights with no sleep: 5.8% (95% CI, 3.0%-8.5%) vs 18.6% (95% CI, 13.9%-23.2%) at the VA center (P < .001) and 5.9% (95% CI, 3.1%-8.7%) vs 14.2% (95% CI, 9.9%-18.4%) at the university hospital (P = .001). Participants felt less sleepy after on-call nights in the intervention group, with Karolinska sleepiness scale scores of 6.65 (95% CI, 6.35-6.97) vs 7.10 (95% CI, 6.85-7.33; P = .01) at the VA center and 5.91 (95% CI, 5.64-6.16) vs 6.79 (95% CI, 6.57-7.04; P < .001) at the university hospital. CONCLUSIONS For internal medicine services at 2 hospitals, implementation of a protected sleep period while on call resulted in an increase in overnight sleep duration and improved alertness the next morning. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00874510.
American Journal of Health Promotion | 2016
Jeffrey T. Kullgren; Andrea B. Troxel; George Loewenstein; Laurie Norton; Dana Gatto; Yuanyuan Tao; Jingsan Zhu; Heather Schofield; Judy A. Shea; David A. Asch; Thomas Pellathy; Jay Driggers; Kevin G. Volpp
Importance Adherence to medications prescribed after acute myocardial infarction (AMI) is low. Wireless technology and behavioral economic approaches have shown promise in improving health behaviors. Objective To determine whether a system of medication reminders using financial incentives and social support delays subsequent vascular events in patients following AMI compared with usual care. Design, Setting, and Participants Two-arm, randomized clinical trial with a 12-month intervention conducted from 2013 through 2016. Investigators were blinded to study group, but participants were not. Design was a health plan–intermediated intervention for members of several health plans. We recruited 1509 participants from 7179 contacted AMI survivors (insured with 5 large US insurers nationally or with Medicare fee-for-service at the University of Pennsylvania Health System). Patients aged 18 to 80 years were eligible if currently prescribed at least 2 of 4 study medications (statin, aspirin, &bgr;-blocker, antiplatelet agent), and were hospital inpatients for 1 to 180 days and discharged home with a principal diagnosis of AMI. Interventions Patients were randomized 2:1 to an intervention using electronic pill bottles combined with lottery incentives and social support for medication adherence (1003 patients), or to usual care (506 patients). Main Outcomes and Measures Primary outcome was time to first vascular rehospitalization or death. Secondary outcomes were time to first all-cause rehospitalization, total number of repeated hospitalizations, medication adherence, and total medical costs. Results A total of 35.5% of participants were female (n = 536); mean (SD) age was 61.0 (10.3) years. There were no statistically significant differences between study arms in time to first rehospitalization for a vascular event or death (hazard ratio, 1.04; 95% CI, 0.71 to 1.52; P = .84), time to first all-cause rehospitalization (hazard ratio, 0.89; 95% CI, 0.73 to 1.09; P = .27), or total number of repeated hospitalizations (hazard ratio, 0.94; 95% CI, 0.60 to 1.48; P = .79). Mean (SD) medication adherence did not differ between control (0.42 [0.39]) and intervention (0.46 [0.39]) (difference, 0.04; 95% CI, −0.01 to 0.09; P = .10). Mean (SD) medical costs in 12 months following enrollment did not differ between control (
Academic Medicine | 2014
Judy A. Shea; David F. Dinges; Dylan S. Small; Mathias Basner; Jingsan Zhu; Laurie Norton; Adrian J. Ecker; Cristina Novak; Lisa M. Bellini; C. Jessica Dine; Daniel J. Mollicone; Kevin G. Volpp
29 811 [
Journal of Graduate Medical Education | 2014
Judy A. Shea; Lisa M. Bellini; David F. Dinges; Meredith L. Curtis; Yuanyuan Tao; Jingsan Zhu; Dylan S. Small; Mathias Basner; Laurie Norton; Cristina Novak; C. Jessica Dine; Ilene M. Rosen; Kevin G. Volpp
74 850]) and intervention (
American Heart Journal | 2016
Andrea B. Troxel; David A. Asch; Shivan J. Mehta; Laurie Norton; Devon K. Taylor; Tirza A. Calderón; Raymond Lim; Jingsan Zhu; Daniel M. Kolansky; Brian M. Drachman; Kevin G. Volpp
24 038 [
Journal of General Internal Medicine | 2011
Leslie K. John; George Loewenstein; Andrea B. Troxel; Laurie Norton; Jennifer E. Fassbender; Kevin G. Volpp
66 915]) (difference, −