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Brady LM, Wang C, Griffiths C, Yang J, Markus HR, Fryberg SA. A leadership-level culture cycle intervention changes teachers' culturally inclusive beliefs and practices. Proc Natl Acad Sci U S A 2024; 121:e2322872121. [PMID: 38857405 PMCID: PMC11194553 DOI: 10.1073/pnas.2322872121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 04/08/2024] [Indexed: 06/12/2024] Open
Abstract
Despite an abundance of support for culturally inclusive learning environments, there is little consensus regarding how to change educational contexts to effectively and sustainably foster cultural inclusion. To address this gap, we report findings from a research-practice partnership that leveraged the Culture Cycle Framework (CCF) to expand educators' praxis to include both independent and interdependent models of self. Most U.S. schools validate independent cultural models (i.e., those that prioritize individuality, uniqueness, and personal agency) and overlook interdependent models (i.e., those that prioritize connectedness, relationality, and collective well-being), which are more common among students from marginalized racial and socioeconomic backgrounds. Using a quasi-experimental longitudinal design, we trained school leadership to integrate ideas about cultural inclusion (i.e., validating the importance of both independent and interdependent cultural models) into school-wide flagship practices. We assessed downstream indicators of culture change by surveying teachers and students across the district and found that a) leadership-level training enhanced school-wide beliefs about cultural inclusion, b) teachers' endorsement of culturally inclusive beliefs predicted their use of culturally inclusive practices, and c) teachers' use of culturally inclusive practices predicted enhanced psychosocial and academic outcomes among students. This research represents a comprehensive culture change effort using the CCF and illustrates a means of fostering inclusion-focused educational culture change and assessing downstream consequences of culture change initiatives.
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Affiliation(s)
- Laura M. Brady
- Department of Psychology, University of Michigan, Ann Arbor, MI48109
| | - Cong Wang
- Department of Psychology, Northwestern University, Evanston, IL60208
| | | | - Jenny Yang
- Department of Psychology, Stanford University, Stanford, CA94305
| | - Hazel R. Markus
- Department of Psychology, Stanford University, Stanford, CA94305
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Arundel CE, Clark L. Do recruitment SWAT interventions have an impact on participant retention in randomised controlled trials? A systematic review. Clin Trials 2024; 21:233-241. [PMID: 37877371 PMCID: PMC11005310 DOI: 10.1177/17407745231206283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
BACKGROUND Evidence-based methods for randomised controlled trial recruitment and retention are extremely valuable. Despite increased testing of these through studies within a trial, there remains limited high-certainty evidence for effective strategies. In addition, there has been little consideration as to whether recruitment interventions also have an impact on participant retention. METHODS A systematic review was conducted. Studies were eligible if they were randomised controlled trials using a recruitment intervention and which also assessed the impact of this on retention at any time point. Searches were conducted through MEDLINE, EMBASE, Cochrane Library, and the Northern Ireland Hub for Trials Methodology Research SWAT Repository. Two independent reviewers screened the search results and extracted data for eligible studies using a piloted extraction form. RESULTS A total of 7815 records were identified, resulting in 10 studies being included in the review. Most studies (n = 6, 60%) focussed on the information given to participants (n = 6, 60%), with two (20%) focussing on incentives, and two focussing on trial design and recruiter interventions. Due to intervention heterogeneity, none of the interventions could be meta-analysed. Only one study found any statistically significant effect of letters including a photograph (odds ratio: 5.40, 95% CI 1.12-26.15, p = 0.04). CONCLUSION Assessment of the impacts of recruitment strategies, evaluated in a SWAT, on retention of participants in the host trial remains limited. Assessment of the impact of recruitment interventions on retention is recommended to minimise future research costs and waste.
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Affiliation(s)
- Catherine E Arundel
- York Trials Unit, Department of Health Sciences, University of York, York, UK
| | - Laura Clark
- York Trials Unit, Department of Health Sciences, University of York, York, UK
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Williams PA, Rotunda W, Porterfield D, Skeete RA, Smith AD, Proia KK. Implementation of Session Zero as a Recruitment Strategy in the National Diabetes Prevention Program's Lifestyle Change Program. Sci Diabetes Self Manag Care 2024; 50:74-86. [PMID: 38158815 PMCID: PMC10995983 DOI: 10.1177/26350106231215767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
PURPOSE The purpose of the study was to understand the extent to which organizations offering the Centers for Disease Control and Prevention's (CDC) National Diabetes Prevention Program (National DPP) lifestyle change program implement session zero (a pre-enrollment session designed to recruit, engage, and enroll participants in programs), the stated purpose(s) for offering session zero, the content of session zero, and best practices for using session zero for recruitment. METHODS Researchers conducted a survey of all organizations offering the National DPP lifestyle change program that were registered with the CDC's Diabetes Prevention Recognition Program and their affiliated delivery locations. RESULTS Most (79.5%) delivery locations reported implementing session zero; of these, most used session zero as a recruitment strategy (81.1%) and orientation session (72.8%), whereas few (17.7%) used session zero solely to complete participant enrollment paperwork. Most (60.7%) delivery locations that implement session zero offer all their sessions at the same location, offer one session per upcoming participant cohort (66.7%), and use a consistent agenda (83.0%). Out of a list of activities informed by behavior change theory, the most common was offering an opportunity to enroll in the year-long lifestyle change program at the end of session zero (71.1%). CONCLUSIONS Most National DPP delivery locations implement session zero as a recruitment and orientation session. Most delivery locations reported including some activities informed by behavior change theory, but delivery locations could offer more theoretically informed activities during their session zero. The findings provide practice-based considerations for implementing session zero for recruitment into lifestyle change programs.
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Affiliation(s)
| | - Wendi Rotunda
- RTI International, Research Triangle Park, North Carolina
| | | | | | - Akimi D Smith
- Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Krista K Proia
- Centers for Disease Control and Prevention, Atlanta, Georgia
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Ivanov A, Mukherjee UK, Bose S, Seshadri S, Watkins R, England AC, Suriano J, Ahsen ME, Souyris S. COVID-19 test-to-stay program for K-12 schools: Opt-in versus opt-out consent model. iScience 2024; 27:108770. [PMID: 38261919 PMCID: PMC10797182 DOI: 10.1016/j.isci.2023.108770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/10/2023] [Accepted: 12/18/2023] [Indexed: 01/25/2024] Open
Abstract
The Centers for Disease Control and Prevention promoted the Test-to-Stay (TTS) program to facilitate in-person instruction in K-12 schools during COVID-19. This program delineates guidelines for schools to regularly test students and staff to minimize risks of infection transmission. TTS enrollment can be implemented via two different consent models: opt-in, in which students do not test regularly by default, and the opposite, opt-out model. We study the impacts of the two enrollment approaches on testing and positivity rates with data from 259 schools in Illinois. Our results indicate that after controlling for other covariates, schools following the opt-out model are associated with 84% higher testing rate and 30% lower positivity rate. If all schools adopted the opt-out model, 20% of the total lost school days could have been saved. The lower positivity rate among the opt-out group is largely explained by the higher testing rate in these schools, a manifestation of status quo bias.
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Affiliation(s)
- Anton Ivanov
- Department of Business Administration, University of Illinois at Urbana-Champaign, Champaign, IL 61821, USA
| | - Ujjal Kumar Mukherjee
- Department of Business Administration, University of Illinois at Urbana-Champaign, Champaign, IL 61821, USA
- Health Innovation Professor Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, USA
| | - Subhonmesh Bose
- Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL 61821, USA
| | - Sridhar Seshadri
- Department of Business Administration, University of Illinois at Urbana-Champaign, Champaign, IL 61821, USA
- Health Innovation Professor Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, USA
| | - Ronald Watkins
- Shield Illinois, University of Illinois System, Champaign, IL 61821, USA
| | | | - Jacqueline Suriano
- Shield Illinois, University of Illinois System, Champaign, IL 61821, USA
| | - Mehmet Eren Ahsen
- Department of Business Administration, University of Illinois at Urbana-Champaign, Champaign, IL 61821, USA
- Health Innovation Professor Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, USA
| | - Sebastian Souyris
- Lally School of Management, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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West AB, Guo YV, Bucher A. Leveraging behavioral science and artificial intelligence to support mental health in the workplace: a pilot study. Front Psychiatry 2023; 14:1219229. [PMID: 37928926 PMCID: PMC10620519 DOI: 10.3389/fpsyt.2023.1219229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 10/04/2023] [Indexed: 11/07/2023] Open
Abstract
Introduction Many American employers seek to alleviate employee mental health symptoms through resources like employee assistance programs (EAPs), yet these programs are often underutilized. This pilot study explores the design of a behavioral science-based email campaign targeting engagement with stress management and mental health resources via an EAP, among employees of a large home builder in the Southeastern US. Methods Behavioral designers created a behavioral science intervention using a multi-step design approach and evidence based behavioral strategies. For this pilot intervention, employees received either a treatment message [i.e., behavioral science message assembled and delivered via the behavioral reinforcement learning (BRL) agent] or a control message (i.e., a single generic, supportive message with a stock photo) with a call to action to utilize their EAP. Results A total of 773 employees received emails over the course of 1 year. Engagement was high, with an 80% email open rate. Over 170 employees (22%, 159 treatment and 14 control) clicked the CTA and logged into the EAP site at least once. Discussion This pilot study suggests that using behavioral science and artificial intelligence can improve employee usage of EAP, specifically with the intention of exploring mental health and stress management resources, compared to benchmark rates of 5% per year.
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Affiliation(s)
- Ashley B. West
- Lirio, LLC, Knoxville, TN, United States
- Behavioral Reinforcement Learning Lab, Lirio, LLC, Knoxville, TN, United States
| | | | - Amy Bucher
- Lirio, LLC, Knoxville, TN, United States
- Behavioral Reinforcement Learning Lab, Lirio, LLC, Knoxville, TN, United States
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Dobson R, Uri A, Whittaker R, Evison K, Umali E, McRobbie H. Is opt-out enrolment acceptable for low-risk digital health services? J Prim Health Care 2022; 14:368-371. [PMID: 36592779 DOI: 10.1071/hc22088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/06/2022] [Indexed: 12/24/2022] Open
Abstract
Introduction Digital health programmes not only complement existing services, but have the potential to reach populations that existing services are not reaching. Many of these services require people to opt-in to receive them, which presents significant barriers to access. An alternative is to make low-risk digital services opt-out, ensuring appropriate members of the target audience are signed up for a service unless they select to not receive it. Aim This study aimed to investigate how changing enrolment in a low-risk digital health programme from opt-in to opt-out would impact on enrolment and dropout rates. Methods This study involved the retrospective analysis of registration data from txtpēpi, a maternal and child health text-message programme. System-recorded data from enrolments during a 12-month period were obtained. In the first 6 months, users had to opt-in to the service (Period 1), but in the following 6 months, an opt-out process was implemented (Period 2). Results There was a 77% increase in enrolments in Period 2 (n = 113) compared to Period 1 (n = 64) and no significant change in the proportion of enrolments of Māori between time periods (P = 0.508). There was no significant difference in withdrawal rates between time periods at either 2 weeks (5% vs 6%, P = 0.676) or 1 month (9% vs 9%, P = 0.907). Discussion This study has shown switching from an opt-in to an opt-out option resulted in an increase in enrolments in an mHealth programme, but had no impact on withdrawals. This indicates that employing opt-out enrolment for low-risk evidence-based interventions is acceptable and a potential way to make these services more accessible.
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Affiliation(s)
- Rosie Dobson
- National Institute for Health Innovation, University of Auckland, Auckland, Aotearoa New Zealand; and Te Whatu Ora - Waitemata, Auckland, Aotearoa New Zealand
| | - Amanda Uri
- National Institute for Health Innovation, University of Auckland, Auckland, Aotearoa New Zealand; and Te Arawa Whanau Ora, Rotorua, Aotearoa New Zealand
| | - Robyn Whittaker
- National Institute for Health Innovation, University of Auckland, Auckland, Aotearoa New Zealand; and Te Whatu Ora - Waitemata, Auckland, Aotearoa New Zealand
| | - Karen Evison
- Te Whatu Ora - Lakes, Rotorua, Aotearoa New Zealand
| | - Elaine Umali
- National Institute for Health Innovation, University of Auckland, Auckland, Aotearoa New Zealand
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Lynch TV, Beach IR, Kajtezovic S, Larkin OG, Rosen L. Step Siblings: a Novel Peer-Mentorship Program for Medical Student Wellness During USMLE Step 1 Preparation. MEDICAL SCIENCE EDUCATOR 2022; 32:803-810. [PMID: 35729988 PMCID: PMC9189789 DOI: 10.1007/s40670-022-01571-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/29/2022] [Indexed: 06/15/2023]
Abstract
INTRODUCTION The US Medical Licensing Examination (USMLE) Step 1 exam has proven a difficult stressor for medical students during their training, even with the advent of pass-fail scoring. The preparation period before the exam places students at high risk for burnout and depression, leading to impaired exam performance and other serious consequences including suicide. Many medical schools already provide academic support for students during USMLE Step 1 preparation, yet to date, there are no published programs specifically geared towards mental health support during this time. METHODS Students from the Larner College of Medicine at the University of Vermont developed the "Step-Siblings" program to partner pre-clinical level students preparing for Step 1 (Little Sibs) with clinical-level students (Big Sibs) in an effort to promote near-peer mentorship and support for those studying. Big Sibs were trained to offer emotional support and wellness advice, but specifically not to provide academic counselling. The pilot program was evaluated by student surveys. RESULTS Our program successfully paired Little Sibs (n = 125) with Big Sibs (n = 75) several months preceding the Step 1 dedicated study period, achieving the intended effect of reducing burnout and fostering a supportive community during a notoriously isolating and emotionally challenging time. Survey results indicated that a majority of Little and Big Sibs found the program helpful. CONCLUSIONS This student-driven mentorship model is simple to implement, easily generalizable to other medical schools and other board exams, and bears the lasting benefit of combatting the stress and burnout so prevalent in medical education. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40670-022-01571-4.
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Affiliation(s)
- Tierra V. Lynch
- Larner College of Medicine, University of Vermont, Burlington, VT USA
| | - Isidora R. Beach
- Larner College of Medicine, University of Vermont, Burlington, VT USA
| | - Sidika Kajtezovic
- Larner College of Medicine, University of Vermont, Burlington, VT USA
| | - Olivia G. Larkin
- Larner College of Medicine, University of Vermont, Burlington, VT USA
| | - Lee Rosen
- Larner College of Medicine, University of Vermont, Burlington, VT USA
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Misuraca R, Teuscher U, Scaffidi Abbate C, Ceresia F, Roccella M, Parisi L, Vetri L, Miceli S. Can We Do Better Next Time? Italians' Response to the COVID-19 Emergency through a Heuristics and Biases Lens. Behav Sci (Basel) 2022; 12:39. [PMID: 35200290 PMCID: PMC8869375 DOI: 10.3390/bs12020039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/24/2022] [Accepted: 02/01/2022] [Indexed: 02/05/2023] Open
Abstract
During the outbreak of COVID-19 in Italy, people often failed to adopt behaviors that could have stopped, or at least slowed down, the spread of this deadly disease. We offer cognitive explanations for these decisions, based on some of the most common heuristics and biases that are known to influence human judgment and decision-making, especially under conditions of high uncertainty. Our analysis concludes with the following recommendations: policymakers can and should take advantage of this established science, in order to communicate more effectively and increase the likelihood that people choose responsible actions in a public health crisis.
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Affiliation(s)
- Raffaella Misuraca
- Department of Political Science and International Relations (DEMS), University of Palermo, 90134 Palermo, Italy;
| | - Ursina Teuscher
- Department of Psychology, Portland State University, Portland, OR 97207, USA;
| | - Costanza Scaffidi Abbate
- Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy; (C.S.A.); (M.R.); (L.P.); (S.M.)
| | - Francesco Ceresia
- Department of Political Science and International Relations (DEMS), University of Palermo, 90134 Palermo, Italy;
| | - Michele Roccella
- Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy; (C.S.A.); (M.R.); (L.P.); (S.M.)
| | - Lucia Parisi
- Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy; (C.S.A.); (M.R.); (L.P.); (S.M.)
| | - Luigi Vetri
- OASI, Research Institute-IRCCS, 94018 Troina, Italy;
| | - Silvana Miceli
- Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy; (C.S.A.); (M.R.); (L.P.); (S.M.)
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Abstract
PURPOSE OF REVIEW Behavioral economics represents a promising set of principles to inform the design of health-promoting interventions. Techniques from the field have the potential to increase quality of cardiovascular care given suboptimal rates of guideline-directed care delivery and patient adherence to optimal health behaviors across the spectrum of cardiovascular care delivery. RECENT FINDINGS Cardiovascular health-promoting interventions have demonstrated success in using a wide array of principles from behavioral economics, including loss framing, social norms, and gamification. Such approaches are becoming increasingly sophisticated and focused on clinical cardiovascular outcomes in addition to health behaviors as a primary endpoint. Many approaches can be used to improve patient decisions remotely, which is particularly useful given the shift to virtual care in the context of the COVID-19 pandemic. Numerous applications for behavioral economics exist in the cardiovascular care delivery space, though more work is needed before we will have a full understanding of ways to best leverage such applications in each clinical context.
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Wintheiser GA, Ruddy KJ, Herrin J, Rahman PA, Pachman DR, Leppin AL, Rutten LJF, Lee MK, Griffin JM, Tofthagen C, Chlan LL, Ridgeway JL, Mitchell SA, Cheville AL. Receptivity to a Nurse-Led Symptom Management Intervention Amongst Highly Symptomatic Patients with Cancer. J Natl Cancer Inst 2021; 114:458-466. [PMID: 34508602 PMCID: PMC8902324 DOI: 10.1093/jnci/djab172] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/09/2021] [Accepted: 09/08/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The symptom burden associated with cancer and its treatment can negatively impact patients' quality of life and survival. Symptom-focused collaborative care model (CCM) interventions can improve outcomes, but only if patients engage with them. We assessed the receptivity of severely symptomatic oncology patients to a remote nurse-led CCM intervention. METHODS In a pragmatic, cluster-randomized, stepped wedge trial conducted as part of the NCI IMPACT Consortium (E2C2, NCT03892967), patients receiving cancer care were asked to rate their sleep disturbance, pain, anxiety, emotional distress, fatigue, and limitations in physical function. Patients reporting at least one severe symptom (≥7/10) were offered phone consultation with a nurse symptom care manager (RN SCM). Initially, patients had to "opt-in" to receive a call, but the protocol was later modified so they had to "opt-out" if they did not want a call. We assessed the impact of opt-in vs. opt-out framing and patient characteristics on receptiveness to RN SCM calls. All statistical tests were 2-sided. RESULTS Of the 1204 symptom assessments (from 864 patients) on which at least one severe symptom was documented, 469 (39.0%) indicated receptivity to an RN SCM phone call. The opt-out period (odds ratio [OR] = 1.61, 95% confidence interval [CI] = 1.12 to 2.32, p=.01), receiving care at a tertiary care center (OR = 3.59, 95% CI = 2.18 to 5.91, p<.001), and having severe pain (OR = 1.80, 95% CI = 1.24 to 2.62, p=.002), were associated with statistically significantly greater willingness to receive a call. CONCLUSION Many severely symptomatic patients were not receptive to an RN SCM phone call. Better understanding of reasons for refusal and strategies for improving patient receptivity are needed.
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Affiliation(s)
| | - Kathryn J Ruddy
- Division of Medical Oncology, Mayo Clinic, Rochester, MN, USA
| | - Jeph Herrin
- Yale University School of Medicine, New Haven, CT, USA
| | - Parvez A Rahman
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | | | - Aaron L Leppin
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Division of Health Care Delivery Research, Mayo Clinic, Rochester, MN, USA
| | - Lila J Finney Rutten
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Division of Health Care Delivery Research, Mayo Clinic, Rochester, MN, USA
| | - Minji K Lee
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Joan M Griffin
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Division of Health Care Delivery Research, Mayo Clinic, Rochester, MN, USA
| | - Cindy Tofthagen
- Department of Nursing, Nursing Research Division, Mayo Clinic, Jacksonville, FL, USA
| | - Linda L Chlan
- Department of Nursing, Nursing Research Division, Mayo Clinic, Rochester, MN, USA
| | - Jennifer L Ridgeway
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Sandra A Mitchell
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrea L Cheville
- Division of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
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Oakes AH, Epstein JA, Ganguly A, Park SH, Evans CN, Patel MS. Effect of Opt-In vs Opt-Out Framing on Enrollment in a COVID-19 Surveillance Testing Program: The COVID SAFE Randomized Clinical Trial. JAMA Netw Open 2021; 4:e2112434. [PMID: 34081141 PMCID: PMC8176333 DOI: 10.1001/jamanetworkopen.2021.12434] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 04/07/2021] [Indexed: 11/14/2022] Open
Affiliation(s)
- Allison H. Oakes
- VA Health Services Research & Development Center for Health Equity Research and Promotion, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
- Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia
| | | | - Arupa Ganguly
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Genetic Diagnostic Laboratory, Department of Genetics, University of Pennsylvania, Philadelphia
| | - Sae-Hwan Park
- Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia
| | | | - Mitesh S. Patel
- VA Health Services Research & Development Center for Health Equity Research and Promotion, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
- Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Wharton School, University of Pennsylvania, Philadelphia
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Gillies K, Kearney A, Keenan C, Treweek S, Hudson J, Brueton VC, Conway T, Hunter A, Murphy L, Carr PJ, Rait G, Manson P, Aceves-Martins M. Strategies to improve retention in randomised trials. Cochrane Database Syst Rev 2021; 3:MR000032. [PMID: 33675536 PMCID: PMC8092429 DOI: 10.1002/14651858.mr000032.pub3] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Poor retention of participants in randomised trials can lead to missing outcome data which can introduce bias and reduce study power, affecting the generalisability, validity and reliability of results. Many strategies are used to improve retention but few have been formally evaluated. OBJECTIVES To quantify the effect of strategies to improve retention of participants in randomised trials and to investigate if the effect varied by trial setting. SEARCH METHODS We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Scopus, PsycINFO, CINAHL, Web of Science Core Collection (SCI-expanded, SSCI, CPSI-S, CPCI-SSH and ESCI) either directly with a specified search strategy or indirectly through the ORRCA database. We also searched the SWAT repository to identify ongoing or recently completed retention trials. We did our most recent searches in January 2020. SELECTION CRITERIA We included eligible randomised or quasi-randomised trials of evaluations of strategies to increase retention that were embedded in 'host' randomised trials from all disease areas and healthcare settings. We excluded studies aiming to increase treatment compliance. DATA COLLECTION AND ANALYSIS We extracted data on: the retention strategy being evaluated; location of study; host trial setting; method of randomisation; numbers and proportions in each intervention and comparator group. We used a risk difference (RD) and 95% confidence interval (CI) to estimate the effectiveness of the strategies to improve retention. We assessed heterogeneity between trials. We applied GRADE to determine the certainty of the evidence within each comparison. MAIN RESULTS We identified 70 eligible papers that reported data from 81 retention trials. We included 69 studies with more than 100,000 participants in the final meta-analyses, of which 67 studies evaluated interventions aimed at trial participants and two evaluated interventions aimed at trial staff involved in retention. All studies were in health care and most aimed to improve postal questionnaire response. Interventions were categorised into broad comparison groups: Data collection; Participants; Sites and site staff; Central study management; and Study design. These intervention groups consisted of 52 comparisons, none of which were supported by high-certainty evidence as determined by GRADE assessment. There were four comparisons presenting moderate-certainty evidence, three supporting retention (self-sampling kits, monetary reward together with reminder or prenotification and giving a pen at recruitment) and one reducing retention (inclusion of a diary with usual follow-up compared to usual follow-up alone). Of the remaining studies, 20 presented GRADE low-certainty evidence and 28 presented very low-certainty evidence. Our findings do provide a priority list for future replication studies, especially with regard to comparisons that currently rely on a single study. AUTHORS' CONCLUSIONS Most of the interventions we identified aimed to improve retention in the form of postal questionnaire response. There were few evaluations of ways to improve participants returning to trial sites for trial follow-up. None of the comparisons are supported by high-certainty evidence. Comparisons in the review where the evidence certainty could be improved with the addition of well-done studies should be the focus for future evaluations.
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Affiliation(s)
- Katie Gillies
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Anna Kearney
- Dept. of Health Data Science, University of Liverpool, Liverpool, UK
| | - Ciara Keenan
- Campbell UK & Ireland, Centre for Evidence and Social Innovation, Queen's University, Belfast, UK
| | - Shaun Treweek
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Jemma Hudson
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Valerie C Brueton
- Department of Adult Nursing, Florence Nightingale Faculty of Nursing Midwifery and Palliative Care, King's College, London, UK
| | - Thomas Conway
- Clinical Research Facility Galway, National University of Ireland Galway, Galway, Ireland
| | - Andrew Hunter
- School of Nursing and Midwifery, National University of Ireland Galway, Galway, Ireland
| | - Louise Murphy
- School of Nursing and Midwifery, National University of Ireland Galway, Galway, Ireland
| | - Peter J Carr
- School of Nursing and Midwifery, National University of Ireland Galway, Galway, Ireland
| | - Greta Rait
- Research Department of Primary Care and Population Health, University College London, London, UK
| | - Paul Manson
- Health Services Research Unit (HSRU), University of Aberdeen, Aberdeen, UK
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Brunet J, Price J, Delluc C. An exercise trial for adults undergoing neoadjuvant chemoradiotherapy for rectal cancer proves not feasible: recommendations for future trials. Trials 2021; 22:26. [PMID: 33407782 PMCID: PMC7789730 DOI: 10.1186/s13063-020-04958-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 12/09/2020] [Indexed: 01/12/2023] Open
Abstract
Background The aim of this paper is to share the methodological problems of an unsuccessful prospective single-arm feasibility trial conducted to evaluate the safety and feasibility of a 12-week progressive exercise intervention for adults undergoing neoadjuvant chemoradiotherapy for rectal cancer, as well as offer recommendations for future trials. Methods The initial plan was to recruit adults diagnosed with rectal cancer and scheduled for neoadjuvant chemoradiotherapy over a 12-month period. The exercise intervention was to consist of supervised exercise sessions delivered three times per week by a trained exercise specialist. Feasibility (i.e., recruitment, adherence, and compliance rates) and safety (i.e., adverse events) were to be assessed throughout the trial, and patient-reported and physical health outcomes were to be assessed pre- and post-intervention. After 8 months of open recruitment, we had been unable to successfully enroll patients into our trial. We therefore modified our eligibility criteria to increase the number of patients that could be recruited into our trial, and in turn increase our recruitment rate. We also amended our recruitment procedures to ensure we could reach patients who were either awaiting treatment, receiving treatment, or had completed treatments in the past 5 years. In doing so, we added a research objective, namely to determine the optimal timing of conducting an exercise intervention with adults diagnosed with rectal cancer (i.e., during neoadjuvant treatment, after surgery, during adjuvant treatment, or post-treatment). Results Many problems continued to hinder the progress of our trial, particularly the low recruitment rate and the failure to enroll the required sample size that would make our results reliable. Conclusion This led us to conclude that our trial was not feasible and that it is advisable to consider some elements carefully (e.g., recruitment strategies, communication, and trial location) before designing and conducting future trials. If one or more of these elements still proves to be problematic, trial results risk being compromised and alternative approaches should be considered. Trial registration ClinicalTrials.gov NCT03049124. Registered on 02 September 2017
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Affiliation(s)
- Jennifer Brunet
- School of Human Kinetics, University of Ottawa, 125 University Private, Montpetit Hall, Room 339, Ottawa, Ontario, K1N 6N5, Canada. .,Cancer Therapeutics Program, Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, Ontario, Canada. .,Institut du savoir Montfort, Hôpital Montfort, Ottawa, Ontario, Canada.
| | - Jenson Price
- School of Human Kinetics, University of Ottawa, 125 University Private, Montpetit Hall, Room 339, Ottawa, Ontario, K1N 6N5, Canada
| | - Céline Delluc
- Institut du savoir Montfort, Hôpital Montfort, Ottawa, Ontario, Canada
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14
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Long T, Rowland A, Cotterill S, Woby S, Heal C, Garratt N, Brown S, Roland D. Opt-out Consent in Children's Emergency Medicine Research. Compr Child Adolesc Nurs 2020; 45:1-12. [PMID: 32936676 DOI: 10.1080/24694193.2020.1812766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/16/2020] [Indexed: 10/23/2022]
Abstract
There is global acceptance that individuals should be allowed to decide whether or not to take part in research studies, and to do so after being informed about the nature of the research and the risk that might attach to participation. The process of providing detailed information before seeking consent (formalized by signatures) in advance of undertaking research procedures may not be possible in some circumstances, and sometimes an amended approach may be adopted. The use of opt-out consent has been recognized as a valid and ethical means of recruiting participants to studies particularly with large samples and where the risk to participants is small. However, it is sometimes misunderstood and can be a problematic factor in being accepted by research ethics committees and governing authorities. This may be due partly to differing expectations of the amount of information and support offered, together with the nature of the process that is adopted to ensure that a decision has been made rather than consent simply being assumed. In accordance with ongoing discussions with young people, and following consultation with parents, an opt-out consent strategy including varied means of providing information was employed in a large study of 44,501 cases of children attending emergency or urgent care departments. The study was conducted over more than 12 months in dissimilar emergency departments and an urgent care unit, and was designed to support better decision-making in pediatric emergency departments about whether children need to be admitted to hospital or can be discharged home safely. Robust analysis of the factors that exerted the greatest impact on predicting the need to admit or the safety of discharging children led to a revised version of an existing tool. In this article, we review approaches to consent in research, the nature and impact of opt-out consent, the factors that made this an effective strategy for this study, but also more recent concerns which may make opt-out consent no longer acceptable.
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Affiliation(s)
- Tony Long
- School of Health & Society, University of Salford, Salford, UK
| | - Andrew Rowland
- School of Health & Society, University of Salford, Salford, UK
- Emergency Department, North Manchester General Hospital, The Pennine Acute Hospitals NHS Trust, Manchester, UK
| | - Sarah Cotterill
- Centre for Biostatistics, School of Health Sciences, University of Manchester, Manchester, UK
| | - Steve Woby
- School of Health & Society, University of Salford, Salford, UK
- Northern Care Alliance NHS Group, Salford, UK
| | - Calvin Heal
- Centre for Biostatistics, School of Health Sciences, University of Manchester, Manchester, UK
| | | | - Steve Brown
- Children's Emergency Department, Leicester Royal Infirmary, Leicester, UK
| | - Damian Roland
- Children's Emergency Department, Leicester Royal Infirmary, Leicester, UK
- Paediatric Emergency Medicine, SAPPHIRE Group, University of Leicester, Leicester, UK
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15
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Soofi M, Najafi F, Karami-Matin B. Using Insights from Behavioral Economics to Mitigate the Spread of COVID-19. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2020; 18:345-350. [PMID: 32435987 PMCID: PMC7239690 DOI: 10.1007/s40258-020-00595-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
The outbreak of 2019 coronavirus disease (COVID-19) has become a public health emergency of international concern. The number of COVID-infected individuals and related deaths continues to rise rapidly. Encouraging people to adopt and sustain preventive behaviors is a central focus of public health policies that seek to mitigate the spread of COVID-19. Public health policy needs improved methods to encourage people to adhere to COVID-19-preventive behaviors. In this paper, we introduce a number of insights from behavioral economics that help explain why people may behave irrationally during the COVID-19 pandemic. In particular, present bias, status quo bias, framing effect, optimism bias, affect heuristic, and herding behavior are discussed. We hope this paper will shed light on how insights from behavioral economics can enrich public health policies and interventions in the fight against COVID-19.
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Affiliation(s)
- Moslem Soofi
- Social Development and Health Promotion Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Farid Najafi
- Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Behzad Karami-Matin
- Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.
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16
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Montoy JCC, Coralic Z, Herring AA, Clattenburg EJ, Raven MC. Association of Default Electronic Medical Record Settings With Health Care Professional Patterns of Opioid Prescribing in Emergency Departments: A Randomized Quality Improvement Study. JAMA Intern Med 2020; 180:487-493. [PMID: 31961377 PMCID: PMC6990860 DOI: 10.1001/jamainternmed.2019.6544] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
IMPORTANCE Prescription opioids play a significant role in the ongoing opioid crisis. Guidelines and physician education have had mixed success in curbing opioid prescriptions, highlighting the need for other tools that can change prescriber behavior, including nudges based in behavioral economics. OBJECTIVE To determine whether and to what extent changes in the default settings in the electronic medical record (EMR) are associated with opioid prescriptions for patients discharged from emergency departments (EDs). DESIGN, SETTING, AND PARTICIPANTS This quality improvement study randomly altered, during a series of five 4-week blocks, the prepopulated dispense quantities of discharge prescriptions for commonly prescribed opioids at 2 large, urban EDs. These changes were made without announcement, and prescribers were not informed of the study itself. Participants included all health care professionals (physicians, nurse practitioners, and physician assistants) working clinically in either of the 2 EDs. Data were collected from November 28, 2016, through July 9, 2017, and analyzed from July 16, 2017, through May 14, 2018. INTERVENTIONS Default quantities for opioids were changed from status quo quantities of 12 and 20 tablets to null, 5, 10, and 15 tablets according to a block randomization scheme. Regardless of the default quantity, each health care professional decided for whom to prescribe opioids and could modify the quantity prescribed without restriction. MAIN OUTCOMES AND MEASURES The primary outcome was the number of tablets of opioid-containing medications prescribed under each default setting. RESULTS A total of 104 health care professionals wrote 4320 prescriptions for opioids during the study period. Using linear regression, an increase of 0.19 tablets prescribed (95% CI, 0.15-0.22) was found for each tablet increase in default quantity. When evaluating each of the 15 pairwise comparisons of default quantities (eg, 5 vs 15 tablets), a lower default was associated with a lower number of pills prescribed in more than half (8 of the 15) of the pairwise comparisons; there was a higher quantity in 1 and no difference in 6 comparisons. CONCLUSIONS AND RELEVANCE These findings suggest that default settings in the EMR may influence the quantity of opioids prescribed by health care professionals. This low-cost, easily implementable, EMR-based intervention could have far-reaching implications for opioid prescribing and could be used as a tool to help combat the opioid epidemic. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT04155229.
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Affiliation(s)
| | - Zlatan Coralic
- Department of Emergency Medicine, University of California, San Francisco
| | - Andrew A Herring
- Department of Emergency Medicine, Highland Hospital-Alameda Health System, Oakland, California
| | - Eben J Clattenburg
- Department of Emergency Medicine, Highland Hospital-Alameda Health System, Oakland, California.,Tuba City Regional Health Care Corporation, Tuba City, Arizona
| | - Maria C Raven
- Department of Emergency Medicine, University of California, San Francisco
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17
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Waddell KJ, Shah PD, Adusumalli S, Patel MS. Using Behavioral Economics and Technology to Improve Outcomes in Cardio-Oncology. JACC CardioOncol 2020; 2:84-96. [PMID: 34396212 PMCID: PMC8352113 DOI: 10.1016/j.jaccao.2020.02.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 02/03/2020] [Indexed: 12/20/2022] Open
Abstract
Patients with cancer are often at elevated risk for cardiovascular disease due to overlapping risk factors and cardiotoxic anticancer treatments. Their cancer diagnoses may be the predominant focus of clinical care, with less of an emphasis on concurrent cardiovascular risk management. Widely adopted technology platforms, including electronic health records and mobile devices, can be leveraged to improve the cardiovascular outcomes of these patients. These technologies alone may be insufficient to change behavior and may have greater impact if combined with behavior change strategies. Behavioral economics is a scientific field that uses insights from economics and psychology to help explain why individuals are often predictably irrational. Combining insights from behavioral economics with these scalable technology platforms can positively impact medical decision-making and sustained healthy behaviors. This review focuses on the principles of behavioral economics and how "nudges" and scalable technology can be used to positively impact clinician and patient behaviors.
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Affiliation(s)
- Kimberly J. Waddell
- Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
- Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Payal D. Shah
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Srinath Adusumalli
- Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mitesh S. Patel
- Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
- Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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18
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Garabedian LF, Ross-Degnan D, LeCates RF, Wharam JF. Uptake and use of a diabetes management program with a mobile glucometer. Prim Care Diabetes 2019; 13:549-555. [PMID: 31097343 DOI: 10.1016/j.pcd.2019.03.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 03/26/2019] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Innovative mobile health technologies (mHealth) may facilitate self-management of blood glucose. This study evaluates uptake, use, and predictors of uptake and long-term use of a diabetes mHealth intervention, which comprises an FDA-approved mobile glucometer and nurse coaching, in a real-world setting. METHODS n = 4438 commercially-insured adults with diabetes were recruited from 2014 to 2015 via an opt-in, phone-based process. In this post-only study, we obtained data on recruitment, glucometer use, demographics, and insurance and employer characteristics. We calculated percent uptake and reasons for unsuccessful recruitment. We used logistic regression to model predictors of uptake and survival analysis to examine duration of testing and predictors of discontinuation. RESULTS Of the recruited members, 556 (12.5%) signed up for the mHealth program and 324 (7.3%) began testing. Of those who did not sign up, the majority (70.6%) were unable to be reached by phone. Male (OR = 1.60, 95% CI: 1.25, 2.03) and Spanish-speaking (OR = 8.34, 95% CI: 5.40, 12.88) members were more likely to start testing. Two-thirds (66.2%) of those who started testing had a first test value that indicated hyperglycemia; 97% tested more than once and the median time between first and last test was 407 days. Older age was the only significant predictor of long-term use. CONCLUSIONS Although uptake of the mHealth program was low, most members who started testing had initial glucose values that indicated a need for better glucose management and the majority of patients engaged with the program for over a year. Male and Spanish-speaking members were more likely to initiate the program.
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Affiliation(s)
- Laura F Garabedian
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA 02215, United States.
| | - Dennis Ross-Degnan
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA 02215, United States.
| | - Robert F LeCates
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA 02215, United States.
| | - James F Wharam
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA 02215, United States.
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19
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Affiliation(s)
- Mitesh S Patel
- Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia, PA, USA. .,CMC VA Medical Center, Philadelphia, PA, USA.
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20
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Using Nudges to Improve Value by Increasing Imaging-Based Cancer Screening. J Am Coll Radiol 2019; 17:38-41. [PMID: 31541658 DOI: 10.1016/j.jacr.2019.08.025] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 08/25/2019] [Indexed: 11/21/2022]
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21
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Mehta SJ, Khan T, Guerra C, Reitz C, McAuliffe T, Volpp KG, Asch DA, Doubeni CA. A Randomized Controlled Trial of Opt-in Versus Opt-Out Colorectal Cancer Screening Outreach. Am J Gastroenterol 2018; 113:1848-1854. [PMID: 29925915 PMCID: PMC6768589 DOI: 10.1038/s41395-018-0151-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Accepted: 05/14/2018] [Indexed: 12/11/2022]
Abstract
OBJECTIVES METHODS:: RESULTS:: Patients randomized to opt-in agreed to participate 23.1% of the time, and only 2.5% of those in opt-out chose not to participate. FIT kits were mailed to 22.4% and 93% of patients in opt-in and opt-out arms, respectively. In intention-to-screen analysis, patients in the opt-out arm had a higher FIT completion rate (29.1%) than in the opt-in arm (9.6%) (absolute difference 19.5%; 95% confidence interval, 10.9-27.9%; P < .001). Results were similar in subgroup analysis of those sent initial messaging through the EHR portal (9.5% opt-in versus 37.5% in opt-out). CONCLUSIONS .
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Affiliation(s)
- Shivan J Mehta
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Tanya Khan
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Carmen Guerra
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Catherine Reitz
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Timothy McAuliffe
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Kevin G Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - David A Asch
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Chyke A Doubeni
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Incentives and Behavioral Economics, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. Leonard and Madlyn Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA. Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Center for Health Equity Research and Promotion, Philadelphia VA Medical Center, Philadelphia, PA, USA
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22
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Cash incentives versus defaults for HIV testing: A randomized clinical trial. PLoS One 2018; 13:e0199833. [PMID: 29979742 PMCID: PMC6034801 DOI: 10.1371/journal.pone.0199833] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 06/14/2018] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Tools from behavioral economics have been shown to improve health-related behaviors, but the relative efficacy and additive effects of different types of interventions are not well established. We tested the influence of small cash incentives, defaults, and both in combination on increasing patient HIV test acceptance. METHODS AND FINDINGS We conducted a randomized clinical trial among patients aged 13-64 receiving care in an urban emergency department. Patients were cross-randomized to $0, $1, $5, and $10 incentives, and to opt-in, active-choice, and opt-out test defaults. The primary outcome was the proportion of patients who accepted an HIV test. 4,831 of 8,715 patients accepted an HIV test (55.4%). Those offered no monetary incentive accepted 51.6% of test offers. The $1 treatment did not increase test acceptance (increase 1%; 95% confidence interval [CI] -2.0 to 3.9); the $5 and $10 treatments increased test acceptance rates by 10.5 and 15 percentage points, respectively (95% CI 7.5 to 13.4 and 11.8 to 18.1). Compared to opt-in testing, active-choice testing increased test acceptance by 11.5% (95% CI 9.0 to 14.0), and opt-out testing increased acceptance by 23.9 percentage points (95% CI 21.4 to 26.4). CONCLUSIONS Small incentives and defaults can both increase patient HIV test acceptance, though when used in combination their effects were less than additive. These tools from behavioral economics should be considered by clinicians and policymakers. How patient groups respond to monetary incentives and/or defaults deserves further investigation for this and other health behaviors.
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