The field of behavioral science has produced myriad data on health behavior change strategies and leveraged such data into effective human-delivered interventions to improve health. Unfortunately, the impact of traditional health behavior change interventions has been heavily constrained by patient and provider burden, limited ability to measure and intervene upon behavior in real time, variable adherence, low rates of implementation, and poor third-party coverage. Digital health technologies, including mobile phones, sensors, and online social networks, by being available in real time, are being explored as tools to increase our understanding of health behavior and to enhance the impact of behavioral interventions. The recent explosion of industry attention to the development of novel health technologies is exciting but has far outpaced research. This Special Section of Translational Behavioral Medicine, Smartphones, Sensors, and Social Networks: A New Age of Health Behavior Change features a collection of studies that leverage health technologies to measure, change, and/or understand health behavior. We propose five key areas in which behavioral science can improve the impact of digital health technologies on public health. First, research is needed to identify which health technologies actually impact behavior and health outcomes. Second, we need to understand how online social networks can be leveraged to impact health behavior on a large scale. Third, a team science approach is needed in the developmental process of health technologies. Fourth, behavioral scientists should identify how a balance can be struck between the fast pace of innovation and the much slower pace of research. Fifth, behavioral scientists have an integral role in informing the development of health technologies and facilitating the movement of health technologies into the healthcare system.
BACKGROUND: Physicians have limited time for weight-loss counseling, and there is a lack of resources to which they can refer patients for assistance with weight loss. Weight-loss mobile applications (apps) have the potential to be a helpful tool, but the extent to which they include the behavioral strategies included in evidence-based interventions is unknown.
PURPOSE: The primary aims of the study were to determine the degree to which commercial weight-loss mobile apps include the behavioral strategies included in evidence-based weight-loss interventions, and to identify features that enhance behavioral strategies via technology.
METHODS: Thirty weight-loss mobile apps, available on iPhone and/or Android platforms, were coded for whether they included any of 20 behavioral strategies derived from an evidence-based weight-loss program (i.e., Diabetes Prevention Program). Data on available apps were collected in January 2012; data were analyzed in June 2012.
RESULTS: The apps included on average 18.83% (SD=13.24; range=0%-65%) of the 20 strategies. Seven of the strategies were not found in any app. The most common technology-enhanced features were barcode scanners (56.7%) and a social network (46.7%).
CONCLUSIONS: Weight-loss mobile apps typically included only a minority of the behavioral strategies found in evidence-based weight-loss interventions. Behavioral strategies that help improve motivation, reduce stress, and assist with problem solving were missing across apps. Inclusion of additional strategies could make apps more helpful to users who have motivational challenges.
Education, income, and incident heart failure in post-menopausal women: the Women's Health Initiative Hormone Therapy Trials
OBJECTIVES: The purpose of this study is to estimate the effect of education and income on incident heart failure (HF) hospitalization among post-menopausal women.
BACKGROUND: Investigations of socioeconomic status have focused on outcomes after HF diagnosis, not associations with incident HF. We used data from the Women's Health Initiative Hormone Trials to examine the association between socioeconomic status levels and incident HF hospitalization.
METHODS: We included 26,160 healthy, post-menopausal women. Education and income were self-reported. Analysis of variance, chi-square tests, and proportional hazards models were used for statistical analysis, with adjustment for demographics, comorbid conditions, behavioral factors, and hormone and dietary modification assignments.
RESULTS: Women with household incomes $50,000 a year (16.7/10,000 person-years; p < 0.01). Women with less than a high school education had higher HF hospitalization incidence (51.2/10,000 person-years) than college graduates and above (25.5/10,000 person-years; p < 0.01). In multivariable analyses, women with the lowest income levels had 56% higher risk (hazard ratio: 1.56, 95% confidence interval: 1.19 to 2.04) than the highest income women; women with the least amount of education had 21% higher risk for incident HF hospitalization (hazard ratio: 1.21, 95% confidence interval: 0.90 to 1.62) than the most educated women.
CONCLUSIONS: Lower income is associated with an increased incidence of HF hospitalization among healthy, post-menopausal women, whereas multivariable adjustment attenuated the association of education with incident HF. Elsevier Inc. All rights reserved.
Antidepressant use and risk of incident cardiovascular morbidity and mortality among postmenopausal women in the Women's Health Initiative study
BACKGROUND: Antidepressants are commonly prescribed medications, but their effect on cardiovascular morbidity and mortality remains unclear.
METHODS: Prospective cohort study of 136 293 community-dwelling postmenopausal women in the Women's Health Initiative (WHI). Women taking no antidepressants at study entry and who had at least 1 follow-up visit were included. Cardiovascular morbidity and all-cause mortality for women with new antidepressant use at follow-up (n = 5496) were compared with those characteristics for women taking no antidepressants at follow-up (mean follow-up, 5.9 years).
RESULTS: Antidepressant use was not associated with coronary heart disease (CHD). Selective serotonin reuptake inhibitor (SSRI) use was associated with increased stroke risk (hazard ratio [HR],1.45, [95% CI, 1.08-1.97]) and all-cause mortality (HR,1.32 [95% CI, 1.10-1.59]). Annualized rates per 1000 person-years of stroke with no antidepressant use and SSRI use were 2.99 and 4.16, respectively, and death rates were 7.79 and 12.77. Tricyclic antidepressant (TCA) use was associated with increased risk of all-cause mortality (HR,1.67 [95% CI, 1.33-2.09]; annualized rate, 14.14 deaths per 1000 person-years). There were no significant differences between SSRI and TCA use in risk of any outcomes. In analyses by stroke type, SSRI use was associated with incident hemorrhagic stroke (HR, 2.12 [95% CI, 1.10-4.07]) and fatal stroke (HR, 2.10 [95% CI, 1.15-3.81]).
CONCLUSIONS: In postmenopausal women, there were no significant differences between SSRI and TCA use in risk of CHD, stroke, or mortality. Antidepressants were not associated with risk of CHD. Tricyclic antidepressants and SSRIs may be associated with increased risk of mortality, and SSRIs with increased risk of hemorrhagic and fatal stroke, although absolute event risks are low. These findings must be weighed against quality of life and established risks of cardiovascular disease and mortality associated with untreated depression.
OBJECTIVE: To describe the development of measures of worksite descriptive social norms for weight loss, physical activity, and eating behaviors.
METHODS: Three surveys were tested in 844 public high school employees. Factor analysis, Cronbach alpha, and tests of association with other worksite social contextual measures and behaviors were performed.
RESULTS: Each survey demonstrated high internal consistency and was associated with measures of social support and behaviors. Confirmatory factor analysis supported the reliability of the weight-loss and eating-behavior norms surveys, but not the physical-activity norms survey.
CONCLUSIONS: The weight-loss and eating norms surveys are reliable, valid measures.
Roles and strategies of state organizations related to school-based physical education and physical activity policies
School-based physical education (PE) and physical activity (PA) policies can improve PA levels of students and promote health. Studies of policy implementation, communication, monitoring, enforcement, and evaluation are lacking. To describe how states implement, communicate, monitor, enforce, and evaluate key school-based PE and PA policies, researchers interviewed 24 key informants from state-level organizations in 9 states, including representatives from state departments of health and education, state boards of education, and advocacy/professional organizations. These states educate 27% of the US student population. Key informants described their organizations' roles in addressing 14 school-based PE and PA state laws and regulations identified by the Bridging the Gap research program and the National Cancer Institute's Classification of Laws Associated with School Students (C.L.A.S.S.) system. On average, states had 4 of 14 school-based PE and PA laws and regulations, and more than one-half of respondents reported different policies in practice besides the "on the books" laws. Respondents more often reported roles implementing and communicating policies compared with monitoring, enforcing, and evaluating them. Implementation and communication strategies used included training, technical assistance, and written communication of policy to local education agency administrators and teachers. State-level organizations have varying roles in addressing school-based PE and PA policies. Opportunities exist to focus state-level efforts on compliance with existing laws and regulations and evaluation of their impact.
Inhibiting food reward: delay discounting, food reward sensitivity, and palatable food intake in overweight and obese women
Overeating is believed to result when the appetitive motivation to consume palatable food exceeds an individual's capacity for inhibitory control of eating. This hypothesis was supported in recent studies involving predominantly normal weight women, but has not been tested in obese populations. The current study tested the interaction between food reward sensitivity and inhibitory control in predicting palatable food intake among energy-replete overweight and obese women (N = 62). Sensitivity to palatable food reward was measured with the Power of Food Scale. Inhibitory control was assessed with a computerized choice task that captures the tendency to discount large delayed rewards relative to smaller immediate rewards. Participants completed an eating in the absence of hunger protocol in which homeostatic energy needs were eliminated with a bland preload of plain oatmeal, followed by a bogus laboratory taste test of palatable and bland snacks. The interaction between food reward sensitivity and inhibitory control was a significant predictor of palatable food intake in regression analyses controlling for BMI and the amount of preload consumed. Probing this interaction indicated that higher food reward sensitivity predicted greater palatable food intake at low levels of inhibitory control, but was not associated with intake at high levels of inhibitory control. As expected, no associations were found in a similar regression analysis predicting intake of bland foods. Findings support a neurobehavioral model of eating behavior in which sensitivity to palatable food reward drives overeating only when accompanied by insufficient inhibitory control. Strengthening inhibitory control could enhance weight management programs.
Clinical characteristics and outcomes of acute coronary syndrome patients with left anterior hemiblock
OBJECTIVE: We aimed to study the relationships between left anterior hemiblock (LAHB) and the patient characteristics, management, and clinical outcomes in the setting of acute coronary syndromes (ACS).
METHODS: Admission ECGs of patients enrolled in the Global Registry of Acute Coronary Events (GRACE) ECG substudy, and the Canadian ACS Registry I, were analysed independently at a blinded core laboratory. Multivariable logistic regression analysis was performed to assess the independent associations between LAHB on the admission ECG and in-hospital and 6-month mortality.
RESULTS: Of the 11 820 eligible ACS patients, 692 (5.9%) patients had LAHB. The presence of LAHB on admission was associated with older age, male sex, prior myocardial infarction, prior heart failure, worse Killip class, higher creatinine level, and higher GRACE risk score (all p<0.01). Patients with LAHB less frequently underwent cardiac catheterisation, coronary revascularisation or reperfusion therapy (all p<0.05). The LAHB group had higher in-hospital (6.9% vs 3.9%, p<0.001) and 6-month mortality (12.5% vs 7.7%, p<0.001). However, after adjusting for the known predictors of mortality in the GRACE risk models, LAHB was not independently associated with in-hospital death (OR 1.07, 95% CI 0.76 to 1.52, p=0.70), or death at 6 months (OR 1.00, 95% CI 0.75 to 1.34, p=0.99).
CONCLUSIONS: Across the broad spectrum of ACS, LAHB was associated with significant comorbidities, high-risk clinical features on presentation, and worse unadjusted outcomes. However, LAHB was not an independent predictor of in-hospital and 6-month mortality and did not carry incremental prognostic value beyond the known prognosticators in the GRACE risk models.
BACKGROUND: Congestive heart failure (CHF) is a common and preventable complication of acute coronary syndrome (ACS). Nevertheless, ACS risk scores have not been shown to predict CHF risk. We investigated whether the at-discharge Global Registry of Acute Coronary Events (GRACE) score predicts heart failure admission following ACS.
METHODS AND RESULTS: Five-year mortality and hospitalization data were obtained for patients admitted with ACS from June 1999 to September 2009 to a single centre of the GRACE registry. CHF was defined as any admission assigned WHO International Classification of Diseases 10 diagnostic code I50. The hazard ratio (HR) for CHF according to GRACE score was estimated in Cox models adjusting for age, gender and the presence of CHF on index admission. Among 1,956 patients, CHF was recorded on index admission in 141 patients (7%), and 243 (12%) were admitted with CHF over 3.8 median years of follow-up. Compared to the lowest quintile, patients in the highest GRACE score quintile had more CHF admissions (116 vs 17) and a shorter time to first admission (1.2 vs 2.0 years, HR 9.87, 95% CI 5.93-16.43). Per standard deviation increment in GRACE score, the instantaneous risk was more than two-fold higher (HR 2.28; 95% CI 2.02-2.57), including after adjustment for CHF on index admission, age and gender (HR 2.49; 95% CI 2.06-3.02). The C-statistic for CHF admission at 1-year was 0.74 (95% CI 0.70-0.79).
CONCLUSIONS: The GRACE score predicts CHF admission, and may therefore be used to target ACS patients at high risk of CHF with clinical monitoring and therapies.