David A Asch

University of Pennsylvania, Filadelfia, Pennsylvania, United States

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Publications (274)2396.25 Total impact

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    ABSTRACT: Background: Determination of comparative effectiveness in a randomized controlled trial requires consideration of an intervention's comparative uptake (or acceptance) among randomized participants and the intervention's comparative efficacy among participants who use their assigned intervention. If acceptance differs across interventions, then simple randomization of participants can result in post-randomization losses that introduce bias and limit statistical power. Methods: We develop a novel preference-adaptive randomization procedure in which the allocation probabilities are updated based on the inverse of the relative acceptance rates among randomized participants in each arm. In simulation studies, we determine the optimal frequency with which to update the allocation probabilities based on the number of participants randomized. We illustrate the development and application of preference-adaptive randomization using a randomized controlled trial comparing the effectiveness of different financial incentive structures on prolonged smoking cessation. Results: Simulation studies indicated that preference-adaptive randomization performed best with frequent updating, accommodated differences in acceptance across arms, and performed well even if the initial values for the allocation probabilities were not equal to their true values. Updating the allocation probabilities after randomizing each participant minimized imbalances in the number of accepting participants across arms over time. In the smoking cessation trial, unexpectedly large differences in acceptance among arms required us to limit the allocation of participants to less acceptable interventions. Nonetheless, the procedure achieved equal numbers of accepting participants in the more acceptable arms, and balanced the characteristics of participants across assigned interventions. Conclusions: Preference-adaptive randomization, coupled with analysis methods based on instrumental variables, can enhance the validity and generalizability of comparative effectiveness studies. In particular, preference-adaptive randomization augments statistical power by maintaining balanced sample sizes in efficacy analyses, while retaining the ability of randomization to balance covariates across arms in effectiveness analyses.
    Trials 12/2015; 16(1). DOI:10.1186/s13063-015-0592-6 · 2.12 Impact Factor
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    ABSTRACT: We describe young adults' perspectives on health insurance and HealthCare.gov, including their attitudes toward health insurance, health insurance literacy, and benefit and plan preferences. We observed young adults aged 19-30 years in Philadelphia from January to March 2014 as they shopped for health insurance on HealthCare.gov. Participants were then interviewed to elicit their perceived advantages and disadvantages of insurance and factors considered important for plan selection. A 1-month follow-up interview assessed participants' plan enrollment decisions and intended use of health insurance. Data were analyzed using qualitative methodology, and salience scores were calculated for free-listing responses. We enrolled 33 highly educated young adults; 27 completed the follow-up interview. The most salient advantages of health insurance for young adults were access to preventive or primary care (salience score .28) and peace of mind (.27). The most salient disadvantage was the financial strain of paying for health insurance (.72). Participants revealed poor health insurance literacy with 48% incorrectly defining deductible and 78% incorrectly defining coinsurance. The most salient factors reported to influence plan selection were deductible (.48) and premium (.45) amounts as well as preventive care (.21) coverage. The most common intended health insurance use was primary care. Eight participants enrolled in HealthCare.gov plans: six selected silver plans, and three qualified for tax credits. Young adults' perspective on health insurance and enrollment via HealthCare.gov can inform strategies to design health insurance plans and communication about these plans in a way that engages and meets the needs of young adult populations. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
    Journal of Adolescent Health 06/2015; DOI:10.1016/j.jadohealth.2015.04.017 · 2.75 Impact Factor
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    ABSTRACT: Primary care provider (PCP) turnover is common and can disrupt patient continuity of care. Little is known about the effect of PCP turnover on patient care experience and quality of care. To measure the effect of PCP turnover on patient experiences of care and ambulatory care quality. Observational, retrospective cohort study of a nationwide sample of primary care patients in the Veterans Health Administration (VHA). We included all patients enrolled in primary care at the VHA between 2010 and 2012 included in 1 of 2 national data sets used to measure our outcome variables: 326 374 patients in the Survey of Healthcare Experiences of Patients (SHEP; used to measure patient experience of care) associated with 8441 PCPs and 184 501 patients in the External Peer Review Program (EPRP; used to measure ambulatory care quality) associated with 6973 PCPs. Whether a patient experienced PCP turnover, defined as a patient whose provider (physician, nurse practitioner, or physician assistant) had left the VHA (ie, had no patient encounters for 12 months). Five patient care experience measures (from SHEP) and 11 measures of quality of ambulatory care (from EPRP). Nine percent of patients experienced a PCP turnover in our study sample. Primary care provider turnover was associated with a worse rating in each domain of patient care experience. Turnover was associated with a reduced likelihood of having a positive rating of their personal physician of 68.2% vs 74.6% (adjusted percentage point difference, -5.3; 95% CI, -6.0 to -4.7) and a reduced likelihood of getting care quickly of 36.5% vs 38.5% (adjusted percentage point difference, -1.1; 95% CI, -2.1 to -0.1). In contrast, PCP turnover was not associated with lower quality of ambulatory care except for a lower likelihood of controlling blood pressure of 78.7% vs 80.4% (adjusted percentage point difference, -1.44; 95% CI, -2.2 to -0.7). In 9 measures of ambulatory care quality, the difference between patients who experienced no PCP turnover and those who had a PCP turnover was less than 1 percentage point. These effects were moderated by the patients' continuity with their PCP prior to turnover, with a larger detrimental effect of PCP turnover among those with higher continuity prior to the turnover. Primary care provider turnover was associated with worse patient experiences of care but did not have a major effect on ambulatory care quality.
    JAMA Internal Medicine 05/2015; DOI:10.1001/jamainternmed.2015.1853 · 13.25 Impact Factor
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    ABSTRACT: Background Financial incentives promote many health behaviors, but effective ways to deliver health incentives remain uncertain. Methods We randomly assigned CVS Caremark employees and their relatives and friends to one of four incentive programs or to usual care for smoking cessation. Two of the incentive programs targeted individuals, and two targeted groups of six participants. One of the individual-oriented programs and one of the group-oriented programs entailed rewards of approximately $800 for smoking cessation; the others entailed refundable deposits of $150 plus $650 in reward payments for successful participants. Usual care included informational resources and free smoking-cessation aids. Results Overall, 2538 participants were enrolled. Of those assigned to reward-based programs, 90.0% accepted the assignment, as compared with 13.7% of those assigned to deposit-based programs (P<0.001). In intention-to-treat analyses, rates of sustained abstinence from smoking through 6 months were higher with each of the four incentive programs (range, 9.4 to 16.0%) than with usual care (6.0%) (P<0.05 for all comparisons); the superiority of reward-based programs was sustained through 12 months. Group-oriented and individual-oriented programs were associated with similar 6-month abstinence rates (13.7% and 12.1%, respectively; P=0.29). Reward-based programs were associated with higher abstinence rates than deposit-based programs (15.7% vs. 10.2%, P<0.001). However, in instrumental-variable analyses that accounted for differential acceptance, the rate of abstinence at 6 months was 13.2 percentage points (95% confidence interval, 3.1 to 22.8) higher in the deposit-based programs than in the reward-based programs among the estimated 13.7% of the participants who would accept participation in either type of program. Conclusions Reward-based programs were much more commonly accepted than deposit-based programs, leading to higher rates of sustained abstinence from smoking. Group-oriented incentive programs were no more effective than individual-oriented programs. (Funded by the National Institutes of Health and CVS Caremark; ClinicalTrials.gov number, NCT01526265 .).
    New England Journal of Medicine 05/2015; 372(22). DOI:10.1056/NEJMoa1414293 · 54.42 Impact Factor
  • Mitesh S Patel, David A Asch, Kevin G Volpp
    JAMA The Journal of the American Medical Association 05/2015; 313(18):1865-1866. DOI:10.1001/jama.2015.3542 · 30.39 Impact Factor
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    ABSTRACT: Objective . To evaluate the use of behavioral economics to design financial incentives to promote health behavior change and to explore associations with demographic characteristics. Data Source . Studies performed by the Center for Health Incentives and Behavioral Economics at the University of Pennsylvania published between January 2006 and March 2014. Study Inclusion and Exclusion Criteria . Randomized, controlled trials with available participant-level data. Studies that did not use financial incentives to promote health behavior change were excluded. Data Extraction . Participant-level data from seven studies were pooled. Data Synthesis . Meta-analysis on the pooled sample using a random-effects model with interaction terms to examine treatment effects and whether they varied by incentive structure or demographic characteristics. Results . The pooled study sample comprised 1403 participants, of whom 35% were female, 70% were white, 24% were black, and the mean age was 48 years (standard deviation 11.2 years). In the fully adjusted model, participants offered financial incentives had higher odds of behavior change (odds ratio [OR]: 3.96; p < .01) when compared to control. There were no significant interactions between financial incentives and gender, age, race, income, or education. When further adjusting for incentive structure, blacks had higher odds than whites of achieving behavior change (OR: 1.67; p < .05) with a conditional payment. Compared to lower-income participants, higher-income participants had lower odds of behavior change (OR: 0.46; p = .01) with a regret lottery. Conclusion . Financial incentives designed using concepts from behavioral economics were effective for promoting health behavior change. There were no large and consistent relationships between the effectiveness of financial incentives and observable demographic characteristics. Second-order examinations of incentive structure suggest potential relationships among the effectiveness of financial incentives, incentive structure, and the demographic characteristics of race and income.
    American journal of health promotion: AJHP 05/2015; 29(5):314-23. DOI:10.4278/ajhp.140714-LIT-333 · 2.37 Impact Factor
  • Journal of Adolescent Health 02/2015; 56(2):S1. DOI:10.1016/j.jadohealth.2014.10.004 · 2.75 Impact Factor
  • Peter A Ubel, David A Asch
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    ABSTRACT: As hard as it may be for clinicians to adopt new practices, it is often harder for them to "de-innovate," or give up old practices, even when new evidence reveals that those practices offer little value. In this article we explore recent controversies over screening for breast and prostate cancer and testing for sleep disorders. We show that these controversies are not caused solely by a lack of clinical data on the harms and benefits of these tests but are also influenced by several psychological biases that make it difficult for clinicians to de-innovate. De-innovation could be fostered by making sure that advisory panels and guideline committees include experts who have competing biases; emphasizing evidence over clinical judgment; resisting "indication creep," or the premature extension of innovations into unproven areas; and encouraging clinicians to explicitly consider how their experiences bias their interpretations of clinical evidence. Project HOPE—The People-to-People Health Foundation, Inc.
    Health Affairs 02/2015; 34(2):239-44. DOI:10.1377/hlthaff.2014.0983 · 4.32 Impact Factor
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    ABSTRACT: We tested whether providing adults with obstructive sleep apnea (OSA) with daily Web-based access to their positive airway pressure (PAP) usage over 3 mo with or without a financial incentive in the first week improves adherence and functional outcomes. Academic- and community-based sleep centers. One hundred thirty-eight adults with newly diagnosed OSA starting PAP treatment. Participants were randomized to: usual care, usual care with access to PAP usage, or usual care with access to PAP usage and a financial incentive. PAP data were transmitted daily by wireless modem from the participants' PAP unit to a website where hours of usage were displayed. Participants in the financial incentive group could earn up to $30/day in the first week for objective PAP use ≥ 4 h/day. Mean hours of daily PAP use in the two groups with access to PAP usage data did not differ from each other but was significantly greater than that in the usual care group in the first week and over 3 mo (P < 0.0001). Average daily use (mean ± standard deviation) during the first week of PAP intervention was 4.7 ± 3.3 h in the usual care group, and 5.9 ± 2.5 h and 6.3 ± 2.5 h in the Web access groups with and without financial incentive respectively. Adherence over the 3-mo intervention decreased at a relatively constant rate in all three groups. Functional Outcomes of Sleep Questionnaire change scores at 3 mo improved within each group (P < 0.0001) but change scores of the two groups with Web access to PAP data were not different than those in the control group (P > 0.124). PAP adherence is significantly improved by giving patients Web access to information about their use of the treatment. Inclusion of a financial incentive in the first week had no additive effect in improving adherence. © 2014 Associated Professional Sleep Societies, LLC.
    Sleep 01/2015; · 5.06 Impact Factor
  • Mitesh S Patel, David A Asch, Kevin G Volpp
    JAMA The Journal of the American Medical Association 01/2015; 313(5). DOI:10.1001/jama.2014.14781 · 30.39 Impact Factor
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    ABSTRACT: William Howard Taft was obsessed with his health—an observation many will find surprising given that he is remembered as the nation’s most obese president. But Taft kept a detailed diary of his diet, exercise, reflux symptoms, and bowel movements. He shared his logs with his personal physician, who used the information to provide feedback and, with this support, Taft lost nearly sixty pounds.1Now, close to 70 % of Americans track some form of health-related behavior.2 The traditional leather-bound diaries of Taft’s era are less common, but personal journals are more popular than ever in the form of blogs, social media posts, and other online activities. A growing number of sensors, including wearable devices and smartphone apps, collect biometric data passively or with minimal inputs from users, supporting what is called “the quantified self,” with assessments of blood sugar, heart rhythm, or peak respiratory flow.3 The majority of these platforms and devices are never intended to be s ...
    Journal of General Internal Medicine 12/2014; 30(6). DOI:10.1007/s11606-014-3145-x · 3.42 Impact Factor
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    ABSTRACT: Adoption of electronic health record systems has increased the availability of patient-level electronic health information. To examine public support for secondary uses of electronic health information under different consent arrangements. National experimental survey to examine perceptions of uses of electronic health information according to patient consent (obtained vs. not obtained), use (research vs. marketing), and framing of the findings (abstract description without results vs. specific results). Nationally representative survey. 3064 African American, Hispanic, and non-Hispanic white persons (response rate, 65%). Appropriateness of health information use described in vignettes on a scale of 1 (not at all appropriate) to 10 (very appropriate). Mean ratings ranged from a low of 3.81 for a marketing use when consent was not obtained and specific results were presented to a high of 7.06 for a research use when consent was obtained and specific results were presented. Participants rated scenarios in which consent was obtained as more appropriate than when consent was not obtained (difference, 1.01 [95% CI, 0.69 to 1.34]; P < 0.001). Participants rated scenarios in which the use was marketing as less appropriate than when the use was research (difference, -2.03 [CI, -2.27 to -1.78]; P < 0.001). Unconsented research uses were rated as more appropriate than consented marketing uses (5.65 vs. 4.52; difference, 1.13 [CI, 0.87 to 1.39]). Participants rated hypothetical scenarios. Results could be vulnerable to nonresponse bias despite the high response rate. Although approaches to health information sharing emphasize consent, public opinion also emphasizes purpose, which suggests a need to focus more attention on the social value of information use. National Human Genome Research Institute.
    Annals of internal medicine 12/2014; 161(12):855-62. DOI:10.7326/M14-1118 · 16.10 Impact Factor
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    ABSTRACT: Use of social media has become widespread across the United States. Although businesses have invested in social media to engage consumers and promote products, less is known about the extent to which hospitals are using social media to interact with patients and promote health. The aim was to investigate the relationship between hospital social media extent of adoption and utilization relative to hospital characteristics. We conducted a cross-sectional review of hospital-related activity on 4 social media platforms: Facebook, Twitter, Yelp, and Foursquare. All US hospitals were included that reported complete data for the Centers for Medicare and Medicaid Services Hospital Consumer Assessment of Healthcare Providers and Systems survey and the American Hospital Association Annual Survey. We reviewed hospital social media webpages to determine the extent of adoption relative to hospital characteristics, including geographic region, urban designation, bed size, ownership type, and teaching status. Social media utilization was estimated from user activity specific to each social media platform, including number of Facebook likes, Twitter followers, Foursquare check-ins, and Yelp reviews. Adoption of social media varied across hospitals with 94.41% (3351/3371) having a Facebook page and 50.82% (1713/3371) having a Twitter account. A majority of hospitals had a Yelp page (99.14%, 3342/3371) and almost all hospitals had check-ins on Foursquare (99.41%, 3351/3371). Large, urban, private nonprofit, and teaching hospitals were more likely to have higher utilization of these accounts. Although most hospitals adopted at least one social media platform, utilization of social media varied according to several hospital characteristics. This preliminary investigation of social media adoption and utilization among US hospitals provides the framework for future studies investigating the effect of social media on patient outcomes, including links between social media use and the quality of hospital care and services.
    Journal of Medical Internet Research 11/2014; 16(11):e264. DOI:10.2196/jmir.3758 · 4.67 Impact Factor
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    ABSTRACT: In October 2013, multiple United States (US) federal health departments and agencies posted on Twitter, "We're sorry, but we will not be tweeting or responding to @replies during the shutdown. We'll be back as soon as possible!" These "last tweets" and the millions of responses they generated revealed social media's role as a forum for sharing and discussing information rapidly. Social media are now among the few dominant communication channels used today. We used social media to characterize the public discourse and sentiment about the shutdown. The 2013 shutdown represented an opportunity to explore the role social media might play in events that could affect health. (Am J Public Health. Published online ahead of print October 16, 2014: e1-e3. doi:10.2105/AJPH.2014.302118).
    American Journal of Public Health 10/2014; DOI:10.2105/AJPH.2014.302118 · 4.23 Impact Factor
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    ABSTRACT: Objectives. We sought to explore the feasibility of using a crowdsourcing study to promote awareness about automated external defibrillators (AEDs) and their locations. Methods. The Defibrillator Design Challenge was an online initiative that asked the public to create educational designs that would enhance AED visibility, which took place over 8 weeks, from February 6, 2014, to April 6, 2014. Participants were encouraged to vote for AED designs and share designs on social media for points. Using a mixed-methods study design, we measured participant demographics and motivations, design characteristics, dissemination, and Web site engagement. Results. Over 8 weeks, there were 13 992 unique Web site visitors; 119 submitted designs and 2140 voted. The designs were shared 48 254 times on Facebook and Twitter. Most designers-voters reported that they participated to contribute to an important cause (44%) rather than to win money (0.8%). Design themes included: empowerment, location awareness, objects (e.g., wings, lightning, batteries, lifebuoys), and others. Conclusions. The Defibrillator Design Challenge engaged a broad audience to generate AED designs and foster awareness. This project provides a framework for using design and contest architecture to promote health messages. (Am J Public Health. Published online ahead of print October 16, 2014: e1-e7. doi:10.2105/AJPH.2014.302211).
    American Journal of Public Health 10/2014; DOI:10.2105/AJPH.2014.302211 · 4.23 Impact Factor
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    ABSTRACT: Background. Financial incentives and peer networks could be delivered through eHealth technologies to encourage older adults to walk more. Methods. We conducted a 24-week randomized trial in which 92 older adults with a computer and Internet access received a pedometer, daily walking goals, and weekly feedback on goal achievement. Participants were randomized to weekly feedback only (Comparison), entry into a lottery with potential to earn up to $200 each week walking goals were met (Financial Incentive), linkage to four other participants through an online message board (Peer Network), or both interventions (Combined). Main outcomes were the proportion of days walking goals were met during the 16-week intervention and 8-week follow-up. We conducted a content analysis of messages posted by Peer Network and Combined arm participants. Results. During the 16-week intervention, there were no differences in the proportion of days walking goals were met in the Financial Incentive (39.7%; p = .78), Peer Network (24.9%; p = .08), and Combined (36.0%; p = .77) arms compared with the Comparison arm (36.0%). During 8 weeks of follow-up, the proportion of days walking goals were met was lower in the Peer Network arm (18.7%; p = .025) but not in the Financial Incentive (29.3%; p = .50) or Combined (24.8%; p = .37) arms, relative to the Comparison arm (34.5%). Messages posted by participants focused on barriers to walking and provision of social support. Conclusions. Financial incentives and peer networks delivered through eHealth technologies did not result in older adults walking more.
    Health Education &amp Behavior 10/2014; 41(1 Suppl):43S-50S. DOI:10.1177/1090198114540464 · 1.54 Impact Factor
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    ABSTRACT: Aim: To characterize defibrillation and cardiac arrest survival outcomes in movies. Methods: Movies from 2003 to 2012 with defibrillation scenes were reviewed for patient and rescuer characteristics, scene characteristics, defibrillation characteristics, additional interventions, and cardiac arrest survival outcomes. Resuscitation actions were compared with chain of survival actions and the American Heart Association (AHA) Emergency Cardiovascular Care (ECC) 2020 Impact Goals. Cardiac arrest survival outcomes were compared with survival rates reported in the literature and targeted by the AHA ECC 2020 Impact Goals. Results: Thirty-five scenes were identified in 32 movies. Twenty-five (71%) patients were male, and 29 (83%) rescuers were male. Intent of defibrillation was resuscitation in 29 (83%) scenes and harm in 6 (17%) scenes. Cardiac arrest was the indication for use in 23 (66%) scenes, and the heart rhythm was made known in 18 scenes (51%). When the heart rhythm was known, defibrillation was appropriately used for ventricular tachycardia or ventricular fibrillation in 5 (28%) scenes and inappropriately used for asystole in 7 (39%) scenes. In 8 scenes with in-hospital cardiac arrest, 7 (88%) patients survived, compared to survival rates of 23.9% reported in the literature and 38% targeted by an AHA ECC 2020 Impact Goal. In 12 movie scenes with out-of-hospital cardiac arrest, 8 (67%) patients survived, compared to survival rates of 7.9-9.5% reported in peer-reviewed literature and 15.8% targeted by an AHA ECC 2020 Impact Goal. Conclusion: In movies, defibrillation and cardiac arrest survival outcomes are often portrayed inaccurately, representing missed opportunities for public health education.
    Resuscitation 09/2014; 85(12). DOI:10.1016/j.resuscitation.2014.09.005 · 3.96 Impact Factor
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    ABSTRACT: The purpose of this study was to describe clinicians' perceptions of interprofessional collaboration in the intensive care unit and identify factors associated with interprofessional collaboration. We performed 64 semi-structured interviews in seven hospitals with ICU nurses, physicians, respiratory therapists, nurse managers, clinical pharmacists, and dieticians. ICU clinicians perceived two distinct types of facilitators to interprofessional collaboration in critical care: cultural and structural. In the critical care setting, cultural and structural facilitators worked independently as well as in concert to create effective interprofessional collaboration. Initiatives aimed at creating and facilitating interprofessional collaboration should focus attention on cultural and structural facilitators to improve patient care and team effectiveness. © 2014 Wiley Periodicals, Inc.
    Research in Nursing & Health 08/2014; 37(4). DOI:10.1002/nur.21607 · 1.16 Impact Factor
  • David A Asch, Debra F Weinstein
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    ABSTRACT: On July 29, 2014, the Institute of Medicine (IOM) released its report on the governance and financing of graduate medical education (GME).(1) An important incidental finding of the IOM's study was that the evidence base available to inform future directions for the substance, organization, and financing of GME is quite limited. The limited evidence reflects a systematic lack of research investment in an area of health care that we believe deserves better. Our nation's lack of research in medical education contrasts starkly with the large and essential commitment to biomedical research funded by industry, philanthropic organizations, and the public. No . . .
    New England Journal of Medicine 07/2014; 371(9). DOI:10.1056/NEJMp1407463 · 54.42 Impact Factor
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    ABSTRACT: Social media has been embraced as a tool for public health promotion.(1-6) However, effective strategies for harnessing the capabilities of social media remain unclear.(7-9) For example, many state and local health departments have adopted Facebook and Twitter accounts, yet public engagement with these accounts varies.(10-12) Several Web-based interventions for smoking cessation have been developed, but few tobacco prevention Web sites allow users to share links via social media.(13,14) While YouTube videos with health messages have amassed millions of views, such as a popular video targeting soft drink consumption, their long-term impact is difficult to evaluate.(15,16) In general, innovative approaches to disseminating health information must be developed to match the behavior and expectations of the public.(17) (Am J Public Health. Published online ahead of print July 17, 2014: e1-e3. doi:10.2105/AJPH.2014.302088).
    American Journal of Public Health 07/2014; 104(9):e1-e3. DOI:10.2105/AJPH.2014.302088 · 4.23 Impact Factor

Publication Stats

7k Citations
2,396.25 Total Impact Points

Institutions

  • 1993–2015
    • University of Pennsylvania
      • • "Leonard Davis" Institute of Health Economics Center for Health Incentives and Behavioral Economics
      • • Department of Medicine
      • • Division of General Internal Medicine
      • • Center for Health Equity Research
      • • Center for Clinical Epidemiology and Biostatistics
      Filadelfia, Pennsylvania, United States
  • 1991–2014
    • William Penn University
      Filadelfia, Pennsylvania, United States
  • 2013
    • Treatment Research Institute, Philadelphia PA
      Filadelfia, Pennsylvania, United States
  • 2007–2013
    • Cornell University
      • Department of Policy Analysis and Management
      Ithaca, New York, United States
    • U.S. Department of Veterans Affairs
      • Center for Health Equity Research and Promotion (CHERP)
      Washington, D. C., DC, United States
  • 2012
    • Dartmouth College
      Hanover, New Hampshire, United States
  • 2011
    • University of Pittsburgh
      Pittsburgh, Pennsylvania, United States
  • 2001–2009
    • University of Michigan
      • Division of Pulmonary and Critical Care Medicine
      Ann Arbor, MI, United States
    • The Philadelphia Center
      • Philadelphia Veterans Administration Medical Center
      Philadelphia, Pennsylvania, United States
  • 2008
    • University of Texas - Pan American
      • Department of Economics & Finance
      Edinburg, Texas, United States
  • 2006
    • National Institute on Aging
      Baltimore, Maryland, United States
  • 2005
    • Temple University
      Filadelfia, Pennsylvania, United States
  • 2004
    • University of Toledo
      • Department of Psychology
      Toledo, Ohio, United States
  • 2003
    • Johns Hopkins University
      Baltimore, Maryland, United States
  • 1998–2003
    • Carnegie Mellon University
      • • Department of Social and Decision Sciences
      • • Department of Engineering and Public Policy
      Pittsburgh, Pennsylvania, United States
  • 1999
    • University of Toronto
      Toronto, Ontario, Canada
  • 1997
    • Hospital of the University of Pennsylvania
      • Department of Obstetrics and Gynecology
      Philadelphia, Pennsylvania, United States
  • 1996
    • Minneapolis Veterans Affairs Hospital
      Minneapolis, Minnesota, United States
    • University of Miami
      • Department of Management
      Coral Gables, FL, United States
  • 1995
    • University of Chicago
      • Section of General Internal Medicine
      Chicago, IL, United States
  • 1990
    • Robert Wood Johnson Foundation
      Princeton, New Jersey, United States