Social cognitive determinants of nutrition and physical activity among web-health users enrolling in an online intervention: the influence of social support, self-efficacy, outcome expectations, and self-regulation.

BACKGROUND: The Internet is a trusted source of health information for growing majorities of Web users. The promise of online health interventions will be realized with the development of purely online theory-based programs for Web users that are evaluated for program effectiveness and the application of behavior change theory within the online environment. Little is known, however, about the demographic, behavioral, or psychosocial characteristics of Web-health users who represent potential participants in online health promotion research. Nor do we understand how Web users' psychosocial characteristics relate to their health behavior-information essential to the development of effective, theory-based online behavior change interventions. OBJECTIVE: This study examines the demographic, behavioral, and psychosocial characteristics of Web-health users recruited for an online social cognitive theory (SCT)-based nutrition, physical activity, and weight gain prevention intervention, the Web-based Guide to Health (WB-GTH). METHODS: Directed to the WB-GTH site by advertisements through online social and professional networks and through print and online media, participants were screened, consented, and assessed with demographic, physical activity, psychosocial, and food frequency questionnaires online (taking a total of about 1.25 hours); they also kept a 7-day log of daily steps and minutes walked. RESULTS: From 4700 visits to the site, 963 Web users consented to enroll in the study: 83% (803) were female, participants' mean age was 44.4 years (SD 11.03 years), 91% (873) were white, and 61% (589) were college graduates; participants' median annual household income was approximately US $85,000. Participants' daily step counts were in the low-active range (mean 6485.78, SD 2352.54) and overall dietary levels were poor (total fat g/day, mean 77.79, SD 41.96; percent kcal from fat, mean 36.51, SD 5.92; fiber g/day, mean 17.74, SD 7.35; and fruit and vegetable servings/day, mean 4.03, SD 2.33). The Web-health users had good self-efficacy and outcome expectations for health behavior change; however, they perceived little social support for making these changes and engaged in few self-regulatory behaviors. Consistent with SCT, theoretical models provided good fit to Web-users' data (root mean square error of the approximation [RMSEA] < .05). Perceived social support and use of self-regulatory behaviors were strong predictors of physical activity and nutrition behavior. Web users' self-efficacy was also a good predictor of healthier levels of physical activity and dietary fat but not of fiber, fruits, and vegetables. Social support and self-efficacy indirectly predicted behavior through self-regulation, and social support had indirect effects through self-efficacy. CONCLUSIONS: Results suggest Web-health users visiting and ultimately participating in online health interventions may likely be middle-aged, well-educated, upper middle class women whose detrimental health behaviors put them at risk of obesity, heart disease, some cancers, and diabetes. The success of Internet physical activity and nutrition interventions may depend on the extent to which they lead users to develop self-efficacy for behavior change, but perhaps as important, the extent to which these interventions help them garner social-support for making changes. Success of these interventions may also depend on the extent to which they provide a platform for setting goals, planning, tracking, and providing feedback on targeted behaviors.

Web-based guide to health: relationship of theoretical variables to change in physical activity, nutrition and weight at 16-months.

BACKGROUND: Evaluation of online health interventions should investigate the function of theoretical mechanisms of behavior change in this new milieu. OBJECTIVES: To expand our understanding of how Web-based interventions influence behavior, we examined how changes at 6 months in participants' psychosocial characteristics contributed to improvements at 16 months in nutrition, physical activity (PA), and weight management as a result of the online, social cognitive theory (SCT)-based Guide to Health intervention (WB-GTH). METHODS: We conducted recruitment, enrollment, and assessments online with 272 of 655 (41.5%) participants enrolling in WB-GTH who also completed 6- and 16-month follow-up assessments. Participants' mean age was 43.68 years, 86% were female, 92% were white, mean education was 17.45 years, median income was US $85,000, 84% were overweight or obese, and 73% were inactive. Participants received one of two equally effective versions of WB-GTH. Structural equation analysis of theoretical models evaluated whether psychosocial constructs targeted by WB-GTH contributed to observed health behavior changes. RESULTS: The longitudinal model provided good fit to the data (root mean square error of approximation <.05). Participants' weight loss at 16 months was predicted by improvements in their PA (beta(total) = -.34, P = .01), consumption of fruits and vegetables (F&V) (beta(total) = -.20, P = .03) and calorie intake (beta(total) = .15, P = .04). Improvements at 6 months in PA self-efficacy (beta(total) = -.10, P = .03), PA self-regulation (beta(total) = -.15, P = .01), nutrition social support (beta(total) = -.08, P = .03), and nutrition outcome expectations (beta(total) = .08, P = .03) also contributed to weight loss. WB-GTH users with increased social support (beta(total) = .26, P = .04), self-efficacy (beta(total) = .30, P = .01), and self-regulation (beta(total) = .45, P = .004) also exhibited improved PA levels. Decreased fat and sugar consumption followed improved social support (beta(total) = -.10, P = .02), outcome expectations (beta(total) = .15, P = .007), and self-regulation (beta(total) = -.14, P = .008). Decreased calorie intake followed increased social support (beta(total) = -.30, P < .001). Increased F&V intake followed improved self-efficacy (beta(total) = .20, P = .01), outcome expectations (beta(total) = -.29, P = .002), and self-regulation (beta(total) = .27, P = .009). Theorized indirect effects within SCT variables were also supported. CONCLUSIONS: The WB-GTH influenced behavior and weight loss in a manner largely consistent with SCT. Improving social support, self-efficacy, outcome expectations, and self-regulation, in varying combinations, led to healthier diet and exercise habits and concomitant weight loss. High initial levels of self-efficacy may be characteristic of Web-health users interested in online interventions and may alter the function of SCT in these programs. Researchers may find that, although increased self-efficacy enhances program outcomes, participants whose self-efficacy is tempered by online interventions may still benefit. TRIAL REGISTRATION: Clinicaltrials.gov NCT00128570; http://clinicaltrials.gov/ct2/show/NCT00128570 (Archived by WebCite at http://www.webcitation.org/5vgcygBII).

A Retrospective Comparison of Home Telehealth and Nursing Care With or Without Rehabilitation Therapy on Rehospitalization Rates of Individuals With Heart Failure.

PURPOSE: Congestive heart failure (CHF) is the most common reason for rehospitalization among the aging population, accounting for one-fifth of all hospital admissions. To date, there is no research comparing the rehospitalization rates between patients with CHF (PWCHF) who receive telehealth and home health nursing care versus a multidisciplinary team consisting of telehealth, home nursing, physical therapy (PT), and/or occupational therapy (OT). METHODS: A retrospective analysis was performed with 132 Medicare Part A home health patients discharged from an inpatient setting with a primary or secondary diagnosis of CHF receiving daily telehealth over the course of 1 year. Allscripts Home Care and Lifestream software was used to query data from patient records. Rehospitalization rates were analyzed using Cochran-Mantel-Haenszel tests. Patients were divided into 3 groups: (1) nursing only; (2) nursing and PT or OT; or (3) nursing, PT, and OT. RESULTS: A total of 41 of the 132 patients (31.06%) were rehospitalized during their home health 60-day episode of care. This percentage includes all-cause rehospitalizations. Cochran-Mantel-Haenszel tests indicated there were no differences in rehospitalization rates between the 3 groups after controlling for the confounding variables: (1) multiple hospitalizations (P = .15); (2) history of falls (P = .16); or (3) depression (P = .18). CONCLUSIONS: There was no statistically significant difference between the 3 groups for all-cause rehospitalization rates. Further prospective research is required to determine best practices and multidisciplinary protocols to further reduce rehospitalization rates in this population.

Development of advanced signal processing and source imaging methods for superparamagnetic relaxometry.

Superparamagnetic relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using super-conducting quantum interference device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: (1) remove trials contaminated with artifacts, (2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, (3) automatically detect and correct flux jumps, and (4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings.

Magnetic relaxometry as applied to sensitive cancer detection and localization.

BACKGROUND: Here we describe superparamagnetic relaxometry (SPMR), a technology that utilizes highly sensitive magnetic sensors and superparamagnetic nanoparticles for cancer detection. Using SPMR, we sensitively and specifically detect nanoparticles conjugated to biomarkers for various types of cancer. SPMR offers high contrast in vivo, as there is no superparamagnetic background, and bones and tissue are transparent to the magnetic fields. METHODS: In SPMR measurements, a brief magnetizing pulse is used to align superparamagnetic nanoparticles of a discrete size. Following the pulse, an array of superconducting quantum interference detectors (SQUID) sensors detect the decaying magnetization field. NP size is chosen so that, when bound, the induced field decays in seconds. They are functionalized with specific biomarkers and incubated with cancer cells in vitro to determine specificity and cell binding. For in vivo experiments, functionalized NPs are injected into mice with xenograft tumors, and field maps are generated to localize tumor sites. RESULTS: Superparamagnetic NPs developed here have small size dispersion. Cell incubation studies measure specificity for different cell lines and antibodies with very high contrast. In vivo animal measurements verify SPMR localization of tumors. Our results indicate that SPMR possesses sensitivity more than 2 orders of magnitude better than previously reported.

Dairy intake and related self-regulation improved in college students using online nutrition education.

BACKGROUND: Dairy intake by college students is markedly lower than recommendations. Interventions to improve dairy intake based on Social Cognitive Theory (SCT) have potential to successfully change behavior by improving mediators that influence dietary choices. OBJECTIVE: We aimed to use SCT to improve social support, self-efficacy, outcome expectations, self-regulation, and behavior related to dairy intake in college students. DESIGN: We conducted a randomized nutrition education intervention. PARTICIPANTS/SETTING: Participants included 211 college students (mean age 20.2 ± 0.1 years; 63% women and 37% men) recruited from a university campus. Participants in the intervention group (n=107) and comparison group (n=104) received an 8-week dairy intake or stress management intervention, respectively, via electronic mail. Data collection included dairy intake from 7-day food records and SCT variables from questionnaires administered during January 2008 and April 2008. MAIN OUTCOME MEASURES: Changes in dairy intake and SCT variables (ie, social support, self-efficacy, outcome expectations, and self-regulation). STATISTICAL ANALYSES PERFORMED: Multivariate analysis of covariance, with age and sex as covariates (P<0.05). RESULTS: Ninety-one percent of participants (n=97 intervention, n=94 comparison) provided data; complete data were analyzed for 85% of participants (n=90 intervention, n=89 comparison). Participants in the intervention group reported higher intake of total dairy foods (P=0.012) and improved use of self-regulation strategies for consuming three servings per day of total dairy (P=0.000) and low-fat dairy foods (P=0.002) following the intervention. CONCLUSIONS: Nutrition education via electronic mail based on an SCT model improved total dairy intake and self-regulation. Participants reported increased dairy intake and better use of self-regulation strategies. Future interventions should focus on benefits of consuming low-fat vs higher-fat dairy foods.

Aging and the social cognitive determinants of physical activity behavior and behavior change: evidence from the guide to health trial.

Part one of this study investigated the effect of aging on social-cognitive characteristics related to physical activity (PA) among adults in the baseline phase of a health promotion intervention. Participants' questionnaire responses and activity logs indicated PA levels and self-efficacy declined with age, while social support and the use of self-regulatory behaviors (e.g., goal setting, planning, and keeping track) increased. With age participants were also less likely to expect PA to interfere with their daily routines and social obligations. Part two of the study was among overweight/obese, inactive participants completing the intervention; it examined whether improvements in psychosocial variables might counteract declining PA associated with age. After treatment, participants were more active and decreased body weight regardless of age, and improved self-efficacy, outcome expectations, and self-regulatory behaviors. In a causal model, increases in self-efficacy at 7-months lead to increased PA levels and, albeit marginally, weight loss at 16 months; increased PA was associated with greater weight loss. Aging adults who were more confident exercised more and as a result lost more weight. This longitudinal study suggests interventions that offset the effect of aging on self-efficacy may be more successful in helping older participants become more active and avoid weight gain.

Collaborative care and motivational interviewing: improving depression outcomes through patient empowerment interventions.

Patient empowerment interventions have demonstrated significant success in the treatment of several chronic conditions. Recently, 2 such interventions, collaborative care and motivational interviewing, have been employed in the treatment of depression with promise in the managed care setting. Collaborative care initiatives feature a multidisciplinary team of providers to deliver such services as patient education, thorough follow-up, and case management. Motivational interviewing employs specifically tailored dialogue to encourage patients to take an active role in their therapy. Through increased treatment adherence and improved outcomes, these interventions have the potential to decrease the significant overall healthcare costs associated with depression.

HEDIS antidepressant medication management measures and performance-based measures: an opportunity for improvement in depression care.

Using the Health Plan Employer Data and Information Set (HEDIS), the National Committee for Quality Assurance partners with more than 90% of the nation's managed care organizations to collect, audit, and report performance on a range of standardized healthcare quality measures. Many HEDIS measures have been useful in promoting population health, such as rate of beta-blocker use after myocardial infarction or rate of cervical cancer screening. Other measures, such as those for Antidepressant Medication Management (AMM), have been less successful. Several trends are occurring within behavioral health management that attempt to improve depression treatment outcomes, including the implementation of performance-based initiatives using the HEDIS AMM measures and the 9-item Patient Health Questionnaire. Ultimately, linking quality measures to clinical strategies is critical for achieving successful depression treatment outcomes.