NURS 6208-90L Cell Phone Intervention for you

NURS 6208-90L Cell Phone Intervention for you NURS 6208-90L Cell Phone Intervention for you POWER POINT: Cell Phone Intervention for You (CITY): A Randomized, Controlled Trial of Behavioral Weight Loss Intervention for Young Adults Using Mobile Technology ARTICLE SUMMARY GRADING CRITERIA: ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS Category Scoring Criteria Total Points Score Organization (20 points) Ideas are clearly organized and developed. Main points are emphasized. The conclusion is satisfying and relates back to the introduction. 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Contradictions, gaps, inconsistencies, and any unanswered questions left in the article are identified. 10 Summary includes the relevance of this topic to nursing, nursing education, nursing research, nursing practice, client safety, and overall healthcare. 15 Material included is relevant to the overall message/purpose. Identifies future trends or issues based on the topic. 10 Appropriate amount of material is prepared, and points made reflect well their relative importance. 5 There is an obvious conclusion summarizing the presentation. 5 Presentation (25 points) Speaker uses a clear, audible voice, at an understandable pace, and does not merely read the slides. Presentation is well-rehearsed. Limited use of filler words (“umm,” “like,” etc.) Speaker is within time limits. 5 Delivery is poised, controlled, and smooth. 2.5 Good language skills and pronunciation are used. 2.5 PowerPoint presentation is well prepared, informative, effective, and not distracting (i.e., too much information on slides). Information was well communicated. NURS 6208-90L Cell Phone Intervention for you 5 Length of presentation is within the assigned time limits. 5 Presentation posted on Discussion Board on time. Speaker invites the audience members to review presentation and post any questions on the Discussion Board. 2.5 Each group member evaluates their peers and submits the Work Group Evaluation Form to instructor. Evaluation by peers will be worth 10% of Course grade. 2.5 Total Points 100 Score cell_phone_interven Cell Phone Intervention for You (CITY): A Randomized, Controlled Trial of Behavioral Weight Loss Intervention for Young Adults Using Mobile Technology Laura P. Svetkey1,2, Bryan C. Batch3, Pao-Hwa Lin1,2, Stephen S. Intille4,5, Leonor Corsino3, Crystal C. Tyson1, Hayden B. Bosworth6,7,8,9, Steven C. Grambow10, Corrine Voils6,9, Catherine Loria11, John A. Gallis10, Jenifer Schwager1,2, and Gary B. Bennett12,13 Objective: To determine the effect on weight of two mobile technology-based (mHealth) behavioral weight loss interventions in young adults. Methods: Randomized, controlled comparative effectiveness trial in 18- to 35-year-olds with BMI25 kg/m2 (overweight/obese), with participants randomized to 24 months of mHealth intervention delivered by interactive smartphone application on a cell phone (CP); personal coaching enhanced by smartphone self-monitoring (PC); or Control. Results: The 365 randomized participants had mean baseline BMI of 35 kg/m2. Final weight was meas ured in 86% of participants. CP was not superior to Control at any measurement point. PC participants lost significantly more weight than Controls at 6 months (net effect 21.92 kg [CI 23.17, 20.67], P 5 0.003), but not at 12 and 24 months. Conclusions: Despite high intervention engagement and study retention, the inclusion of behavioral princi ples and tools in both interventions, and weight loss in all treatment groups, CP did not lead to weight loss, and PC did not lead to sustained weight loss relative to Control. Although mHealth solutions offer broad dissemination and scalability, the CITY results sound a cautionary note concerning intervention deliv ery by mobile applications. Effective intervention may require the efficiency of mobile technology, the social support and human interaction of personal coaching, and an adaptive approach to intervention design. Obesity (2015) 23, 2133-2141. doi:10.1002/oby.21226 INTRODUCTION Obesity is present in 35% of young adults (defined as age 18-35 years) in the US (1) and deserves attention: Weight gain is most rapid during these years (2,3); increasing body mass index (BMI) in young adulthood increases the risk of developing metabolic syndrome over the subsequent 15 years almost 20-fold (4); and weight gain in early adulthood is also associated with increased coronary calcification in middle age (5), forecasting future cardio vascular disease (CVD) events. These data suggest the need for effective and sustainable weight control strategies early in adult life (6). 1 Division of Nephrology, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA. Correspondence: Laura P. Svetkey ([email protected]) 2 Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology Institute, Durham, North Carolina, USA 3 Division of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA 4 College of Computer and Information Science, Northeastern University, Boston, Massachusetts, USA 5 Bouve College of Health Sciences, Northeastern University, Boston, Massachusetts, USA 6 Division of General Internal Medicine, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA 7 Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, North Carolina, USA 8 School of Nursing, Duke University Medical Center, Durham, North Carolina, USA 9 Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, North Carolina, USA 10 Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA 11 Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA 12 Department of Psychology & Neuroscience, Duke University, Durham, North Carolina, USA 13 Duke Obesity Prevention Program, Duke University Medical Center, Durham, North Carolina, USA. Funding agencies: The CITY study was sponsored by grant number U01HL096720 from the National Heart, Lung, and Blood Institute, a component of the National Institutes of Health (NIH). Disclosure: Dr. Svetkey is a consultant to Oregon Center for Applied Science (ORCAS; Eugene, Oregon), NURS 6208-90L Cell Phone Intervention for you a health innovation company that creates self-management programs to improve physical and emotional well-being. Dr. Grambow is a consultant to Gilead Sciences as a member of multiple DSMBs. Although the relationship is not perceived to represent a conflict with the present work, it has been included in the spirit of full disclosure. Dr. Bennett is a member of the scientific advisory board at Nutrisystem and owns shares in Scale Down, a digital weight loss vendor. Additional Supporting Information may be found in the online version of this article. Received: 21 March 2015; Accepted: 15 June 2015; Published online 4 November 2015. doi:10.1002/oby.21226 Effective behavioral weight loss strategies involve regular personal contact with a trained interventionist using behavioral techniques such as self-monitoring and goal setting (6). Evidencebased obesity treatment recommendations endorse high-intensity intervention: 14 in-person interventionist sessions over 6 months (6). However, the optimal behavioral “dose” is unclear (7), and a smaller effect with lower intensity intervention might be offset by the potential for increased scalability. In addition, trials testing comprehensive behav ioral approaches have primarily included middle-aged adults and suggest that intervention is more effective as age increases (8,9). Thus the potential of personal coaching for weight loss in a younger population is unknown. Similarly, commercial mobile technology mHealth applications (“apps”) are widely downloaded for weight loss but have not been rigorously tested for efficacy or effectiveness. Behavior change tech niques known to produce clinically meaningful weight loss are often absent (10,11), calling into question whether apps can have the desired effect (12,13). Because of the potential for scalability and wide dissemination, we sought to determine the weight loss potential of mobile technology on its own. In order to improve the efficiency of behavior change methods known to be effective, we tested a low-intensity personal coaching intervention enhanced by mobile technology. The Cell Phone Intervention for You (CITY) study was a three-arm random ized trial comparing the effect on weight over 24 months of behavioral intervention that was delivered almost entirely via a smartphone app of our design (CP) or behavioral intervention deliv ered through personal coaching enhanced by self-monitoring via smartphone (PC), each compared to Control. We hypothesized that CP and PC would each be superior to Control. We made no a priori hypothesis about CP relative to PC. METHODS The CITY study was one of seven trials in the Early Adult Reduc tion of weight through LifestYle Intervention (EARLY) consortium, sponsored by NHLBI (1U01HL096720). Each EARLY trial was conducted independently. However, in order to facilitate future com parison, the EARLY trials had common eligibility criteria, measure ment methods, and primary outcome (14). The design of CITY is reported elsewhere (15). STUDY POPULATION CITY was approved by the Duke Institutional Review Board and an NHLBI-appointed Protocol Review Committee/Data and Safety Monitoring Board (DSMB). Enrollment occurred between December 2010 and February 2012. Individuals were eligible if they were aged 25 kg/m2), and used 18-35 years, had overweight or obesity (BMI a mobile telephone. For logistical reasons, participants were required to receive service from either Verizon or AT&T. Individuals were excluded if they were taking weight loss medica tions or corticosteroids, had weight loss surgery, weighed more than 440 lbs (the limit of study scales), or had any condition deemed unsafe for the study. NURS 6208-90L Cell Phone Intervention for you Recruitment occurred primarily by advertising and mass mailings. Pre-screening assessment occurred by participants’ choice of tele phone, interactive voice response (IVR), short message service (SMS), or online survey. Participants were further screened by telephone followed by a face-to-face visit, during which all partici pants provided written informed consent. Randomization occurred at a separate face-to-face visit within 10 weeks of screening, at which baseline weight was obtained. Randomization was stratified by gender and BMI (overweight [BMI 30 kg/m2]) with equal allo cation to each treatment group. Intervention lasted 24 months, with data collection at 6, 12, and 24 months post-randomization. 25 and <30 kg/m2] vs. obese [BMI OUTCOMES The primary outcome was weight change in kilograms (kg) at 24 months. Secondary outcomes included weight changes at 6 and 12 months, percent change in weight at each time point, and weight changes in subgroups defined by self-identified race, sex, and age. Other pre-specified outcomes include change in dietary pattern and physical activity (PA) (15). INTERVENTIONS Both the cell phone (CP) and personal coaching (PC) interventions were designed by our research team, based on social cognitive theory (16) and the transtheoretical model (17). Both interventions used techniques of behavioral self-management (18) and motiva tional enhancement (19). Targeted goals and behaviors included mod erate calorie restriction, healthy dietary pattern (based on the Dietary Approaches to Stop Hypertension [DASH] dietary pattern) (20), 180 min/week of moderate PA, limited alcohol intake, and frequent self-monitoring of weight, diet, and PA (6). Both interventions were designed with input from the target population obtained through focus groups that were conducted in the year before the trial began (21). The major difference between CP and PC was the source of interven tion delivery and the use of the smartphone. In CP, the smartphone was used for both intervention delivery and self-monitoring. Specifi cally, the intervention was delivered exclusively through an investigator-designed smartphone app which included goal setting, challenge games, and social support through a “buddy system” that allowed exchange of pre-determined messages to a randomly assigned buddy participant. Self-management behaviors for CP were regularly and frequently prompted by the app according to a protocol-driven schedule; participants did not have a choice in the timing or frequency of prompts. Tailoring within the CP intervention occurred mainly via setting personal goals. Selfmonitoring by smartphone was achieved by tracking weight, dietary intake, and physical activity, with frequent prompts to self-monitor and feedback on the results. In contrast, the PC intervention was delivered primarily by an interven tionist during six weekly group sessions followed by monthly phone contacts. Intervention elements such as goal setting, challenges, and social support were delivered through these personal coaching interac tions, with extensive tailoring during the conversations with the inter ventionist. The smartphone was used exclusively for self-monitoring, with tracking of weight, dietary intake, and physical activity initiated by the participant (i.e., without smartphone prompts), transmitted to the interventionist, and incorporated by the interventionist into the coaching sessions. The PC interventionists were dietitians trained in Motivational Figure 1 CONSORT diagram. *1 additional Control participant did not have 24-month weight but contributed data for other outcomes. ^Includes: weight loss surgery, program, intervention study (n 5 20); BMI<25 kg/m2 (n 5 7); >15 lbs weight loss in last 3 months (n 5 2). ‡Participants were eligible at time in screening process when they declined. Interviewing.NURS 6208-90L Cell Phone Intervention for you Fidelity to the intervention protocol was monitored by the intervention director (P-HL) during regular observation of the group sessions and review of audiotaped monthly calls. In both CP and PC, participants received an Android smart phone, and their personal phone number was transferred to the CITY phone. Participants were expected to use the CITY phone as their sole per sonal phone. Because text and data service were required for both interventions, participants were reimbursed for this portion of their phone bill. Participants were also provided a Bluetoothenabled scale (Tanita HD-351BT) for weight self-monitoring, which automatically transmitted weight through their smartphone to the study database. Participants randomized to the Control group were given three hand outs on healthy eating and physical activity from the Eat Smart Move More NC program ( but otherwise received no intervention and were not asked to self monitor. Use of these materials was not monitored. MEASUREMENTS Study measurements were collected on-site in all randomized partic ipants at baseline and at 6, 12, and 24 months by trained, certified study personnel. Weight was measured in duplicate to the nearest 0.1 lb, with the par ticipant in light indoor clothes without shoes, using a high-quality calibrated digital scale. Height was measured in duplicate to the nearest 0.1 cm, with the participant shoeless using a wallmounted stadiometer. BMI was calculated as weight [kg]/height [m]2. Waist circumference was measured in duplicate to the nearest 0.1 cm, at the level of the upper iliac crest at the end of a normal exhalation. Dietary intake was assessed by duplicate self-administered 24-h die tary recall (22). Data are summarized as the Healthy Eating Index (HEI), reflecting adherence to DASH (23) and future health out comes (24). Each of the above duplicate measures was averaged at each visit. Physical activity (PA) in kilocalories per week was assessed by the Paffenbarger questionnaire (25). Statistical analysis The primary analysis was based on intention-to-treat principles. The outcome for the two main study hypotheses (CP vs. Control and PC vs. Control) was absolute weight change in kilograms from baseline to 24 months. A constrained longitudinal data analysis model (cLDA) was used to estimate changes in absolute weight over time and test the primary hypotheses (26). The variables in the model 25 to <30 vs. included dichotomous stratification factors (BMI BMI 30 kg/m2, and male vs. female), a time effect, and the TABLE 1 Baseline characteristics Overall Control CP PC Total, no. Age (years), mean (SD) Female, no. (%) Race category, no. (%) White Black Other Hispanic ethnicity, no. (%) Education level, no. (%) Some college or less College degree or higher Personal income category, no. (%) <24,999 25,000-49,999 50,000 In committed relationship, no. (%) Student, no. (%) Working, no. (%) Weight in kg, mean (SD) Body mass index (kg/m2), mean (SD) [min, max] BMI category, no. (%) Overweight, 25-29.99 kg/m2 Class I obese, 30-34.99 kg/m2 Class II obese, 35-39.99 kg/m2 Class III obese, 401 kg/m2 Waist circumference in cm, mean (SD) Males Females Hypertensiona, no. (%) HEIb Score, mean (SD) Leisure-time physical activity (kcal/week), mean (SD)c 365 29.4 (4.3) 254 (69.6) 205 (56.2) 132 (36.2) 28 (7.7) 21 (5.8) 130 (35.6) 235 (64.4) 121 (34.0) 150 (42.1) 85 (23.9) 217 (59.8) 124 (34.3) 308 (85.1) 101.0 (23.7) 35.2 (7.8) [24.9, 62.4] 109 (29.9) 110 (30.1) 52 (14.2) 94 (25.8) 111.7 (16.3) 108.2 (16.8) 59 (16.2) 51.0 (4.1) 879.7 (1,134.2) 123 29.6 (4.3) 85 (69.1) 72 (58.5) 42 (34.1) 9 (7.3) 5 (4.1) 40 (32.5) 83 (67.5) 43 (35.5) 50 (41.3) 28 (23.1) 72 (59.0) 42 (34.1) 96 (79.3) 101.3 (22.6) 35.1 (7.5) [25.3, 61.6] 38 (30.9) 33 (26.8) 19 (15.4) 33 (26.8) 109.8 (14.6) 107.9 (15.7) 20 (16.3) 50.7 (4.4) 865.9 (1,133.9) 122 29.2 (4.2) 84 (68.9) 68 (55.7) 42 (34.4) 12 (9.8) 9 (7.4) 39 (32.0) 83 (68.0) 38 (31.9) 55 (46.2) 26 (21.8) 72 (59.0) 43 (35.8) 107 (88.4) 102.4 (25.2) 35.7 (8.2) [25.1, 62.4] 36 (29.5) 34 (27.9) 16 (13.1) 36 (29.5) 113.8 (17.9) 109.3 (18.4) 20 (16.4) 51.6 (4.2) 1,009.3 (1,346.4) 120 29.4 (4.3) 85 (70.8) 65 (54.2) 48 (40.0) 7 (5.8) 7 (5.8) 51 (42.5) 69 (57.5) 40 (34.5) 45 (38.8) 31 (26.7) 73 (61.3) 39 (32.8) 105 (87.5) 99.3 (23.4) 34.9 (7.5) [24.9, 58.9] 35 (29.2) 43 (35.8) 17 (14.2) 25 NURS 6208-90L Cell Phone Intervention for you (20.8) 111.5 (16.4) 107.4 (16.4) 19 (15.8) 50.8 (3.6) 756.0 (846.1) There were no significant differences among treatment groups CP, cell phone intervention; PC, personal coaching intervention; SD, standard deviation; BMI, body mass index, calculated as weight in kilograms divided by height in meters squared; HEI, Healthy Eating Index. Missing values: income:9; relationship status:2; student:3; work:3; hei:32; physical activity:18. aHypertension defined as SBP> 140 or DBP> 90 mmHg or taking BP meds. bHealthy Eating Index (HEI2005) ( cReports of >10 flights climbed per day were considered implausible and excluded from analysis. treatment-by-time interaction. The Holm sequential testing procedure (27) maintained an overall type I error rate of 0.05 for the analysis of the primary hypotheses. Secondary study outcomes were analyzed similarly. Models evaluat ing effects in pre-specified race, sex, and age subgroups as well as post hoc subgroups based on baseline BMI category, income, and education also include the subgroup variable and its interaction with treatment, with a nominal type I error rate of 0.05. Missing data was addressed in our primary statistical modeling approach by maximum likelihood methods (28). Sensitivity analyses included multiple imputation and a “benchmark” not missing at ran dom (NMAR) analysis that assumes that CP and PC missing values are similar to those of nonmissing Controls. Power and sample size calculations were based on estimates from previous behavioral weight loss trials (29,30): estimated common standard deviation of weight of 16.6 kg at baseline, 0.8 correlation between weight measurements within individuals, and 25% attrition; and weight gain of 1.5 kg/year in Controls (3). With these assump tions, a projected sample size of 120 participants per group (N 5 360) provided greater than 80% power at alpha 0.025 to detect a difference in weight change of 5 kg. TABLE 2 Intervention adherence 0-6 months 7-12 months 13-24 months CP, N (% of randomized) Self-weighing, mean times/week (SD) Number of interactionsa with CITY app, MEAN PER PERSON PER DAY (SD) PC, N (% of randomized) Self-weighing, mean times/week (SD) Number of interactionsa with CITY app, MEAN PER PERSON PER DAY (SD) Percent of contacts completedb (SD) 121 (99) 4.0 (1.7) 4.6 (3.0) 115 (96) 2.2 (1.6) 1.8 (1.5) 93.0 (16.4) 115 (94) 3.3 (1.9) 1.5 (1.4) 113 (94) 1.3 (1.4) 0.8 (1.1) 92.3 (20.8) 105 (86) 2.1 (1.7) 0.7 (0.7) 108 (90) 1.0 (1.2) 0.4 (0.6) 87.8 (21.2) CP, cell phone intervention; PC, personal coaching intervention; SD, standard deviation. aInteractions include any usage of the CITY app except self-weighing. Total number of app components tracked in the CP and PC intervention was 31 and 24, respectively. b0- to 6-month data includes completion percentage for six weekly group sessions. RESULTS A total of 365 individuals were randomized. Figure 1 shows the flow of participants through the study. Weight was obtained at 24 months in 86%. (Those without 24-month data reported slightly higher income and perceived stress but were otherwise similar to the overall randomized population.) Study population (Table 1). At entry, mean age was 29.4 years, 69.6% were women, 43.9% were non-White race (36.2% of total were Black), and 5.8% were Hispanic ethnicity. The majority were college-educated and employed. Mean baseline BMI was 35.2 kg/m2. 25 to One-fourth of study participants were overweight (BMI <30 kg/m2); one-fourth had class III obesity (BMI 40 kg/m2). Intervention adherence (Table 2). The CP group self-weighed an average of 4.0 times/week for the first 6 months and continued at 2.1 times/week during months 13 through 24. CP participants inte … Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10

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