Browsing by Subject "mobile health"
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Item Open Access A Mobile Health Intervention to Sustain Recent Weight Loss(2012) Shaw, Ryan J.Background: Obesity is the number one health risk facing Americans. The obesity epidemic in America is attributed to physical inactivity, unhealthy food choices, and excessive food intake. Structured weight loss programs have been successful in initiating behavior change and weight loss; however, weight is almost always regained over time. The rate of weight gain is highest immediately after cessation of a structured weight loss program. Thus, effective interventions are needed that can successfully be used following a structured weight loss program to sustain weight loss and prevent weight relapse. Due to low cost, ubiquity, and ease of use, healthcare communicated through mobile technology, or "mHealth", may be able to serve as an effective medium to reach a large number of people to facilitate weight loss behaviors. Short message service (SMS), also known as text messaging, is easy to use, ubiquitous, affordable, and can target people directly where they are regardless of geographic location, socioeconomic status, or demographic factors. A review of the literature demonstrated limited information regarding message content, timing and frequency of message delivery and only 3 of 14 SMS-related interventions reviewed demonstrated a statistically significant effect on weight loss, diet or exercise. Additionally, information on how to integrate and leverage SMS as a health promotion tool for weight loss was also limited in the literature.
The Behavior Change Process model was used as a guide to understand how to develop an intervention to help people sustain recent weight loss. Furthermore, research suggests interventions that target and frame messages about how people reach goals in their life through either a prevention or promotion focus may be beneficial at motivating people to self-regulate and sustain recent behavioral changes. The goal of this study was to design an intervention that would help people stay in the continued response phase of the Behavior Change Process and help prevent weight relapse. Using the Behavior Change Process and regulatory focus theory, an intervention was developed that leveraged short message service (SMS) to deliver messages to people who have recently lost weight in attempt to help them sustain weight loss and prevent relapse.
Methods: First, a pilot study was conducted to inform the development of a SMS software application, the development of message content and the frequency and timing of message delivery. Second, an exploratory 3-arm mixed methods randomized controlled trial was conducted to test the feasibility, acceptability, perception of the usefulness, and efficacy of a weight loss sustaining mHealth SMS intervention among people with obesity. Participants (N=120) were randomized to a promotion message group, a prevention message group, or an attention-control general health message group. Participants completed baseline assessments, and reported their weight at 1 and 3 months post-baseline to assess efficacy of the intervention on sustaining weight loss. In addition, participants partook in a phone interview follow completion of the intervention to assess acceptability and usefulness.
Results: Participants found the message content and intervention acceptable and a majority perceived value in receiving messages via SMS that promote weight loss sustaining behaviors. Interview data implied that the intervention served as a reminder and daily cue to action. Participants were favorable towards receiving a daily reminder, which they noted helped them to stay focused, and in some cases to keep them motivated to continue losing weight. And a majority, 42 (91%) who participated in a telephone interview said that they preferred to get messages on their cell phone due to accessibility and convenience. A minimum of one message per day delivered at approximately 8:00 A.M. was deemed the optimal delivery time and frequency. This was particularly true for weight loss, which many participants reported as a daily struggle that begins every morning. With regards to sustaining weight loss, there was a statistical trend in sustained weight loss at months 1 and 3 in the promotion and prevention framed message groups compared to the control group in both the intent-to-treat and evaluable case analyses. Clinically, there was a significant decrease in mean weight of approximately 5 pounds at month 3 in the promotion and prevention groups compared to the control. Additionally, effect sizes indicated a large effect of the intervention on sustaining weight loss in the promotion and prevention groups relative to the control group.
Conclusion: Overall results showed that at the continued response phase of the behavioral change process, it was feasible to design an application to deliver promotion and prevention framed weight loss sustaining messages. In particular, prevention framed messages may have been more useful in helping participants sustain weight loss. Though there was less than 80% power to detect a statistically significant difference, the observed effect sizes in this study were significant and demonstrated a large effect of the promotion and prevention interventions on sustaining weight loss relative to control. Furthermore, there was a clinically significant increase in mean weight loss and in the number of people who sustained weight loss in the promotion and prevention intervention groups compared to control.
These findings may serve as a reference for future interventions designed to help people thwart relapse and transition from a state of sustaining recent weight loss behaviors to a state of maintenance. Technological tools such as this SMS intervention that are constructed and guided by evidence-based content and theoretical constructs show promise in helping people sustain healthy behaviors that can lead to improved health outcomes.
Item Open Access Acquisition, Analysis, and Sharing of Data in 2015 and Beyond: A Survey of the Landscape: A Conference Report From the American Heart Association Data Summit 2015.(J Am Heart Assoc, 2015-11-05) Antman, Elliott M; Benjamin, Emelia J; Harrington, Robert A; Houser, Steven R; Peterson, Eric D; Bauman, Mary Ann; Brown, Nancy; Bufalino, Vincent; Califf, Robert M; Creager, Mark A; Daugherty, Alan; Demets, David L; Dennis, Bernard P; Ebadollahi, Shahram; Jessup, Mariell; Lauer, Michael S; Lo, Bernard; MacRae, Calum A; McConnell, Michael V; McCray, Alexa T; Mello, Michelle M; Mueller, Eric; Newburger, Jane W; Okun, Sally; Packer, Milton; Philippakis, Anthony; Ping, Peipei; Prasoon, Prad; Roger, Véronique L; Singer, Steve; Temple, Robert; Turner, Melanie B; Vigilante, Kevin; Warner, John; Wayte, Patrick; American Heart Association Data Sharing Summit AttendeesBACKGROUND: A 1.5-day interactive forum was convened to discuss critical issues in the acquisition, analysis, and sharing of data in the field of cardiovascular and stroke science. The discussion will serve as the foundation for the American Heart Association's (AHA's) near-term and future strategies in the Big Data area. The concepts evolving from this forum may also inform other fields of medicine and science. METHODS AND RESULTS: A total of 47 participants representing stakeholders from 7 domains (patients, basic scientists, clinical investigators, population researchers, clinicians and healthcare system administrators, industry, and regulatory authorities) participated in the conference. Presentation topics included updates on data as viewed from conventional medical and nonmedical sources, building and using Big Data repositories, articulation of the goals of data sharing, and principles of responsible data sharing. Facilitated breakout sessions were conducted to examine what each of the 7 stakeholder domains wants from Big Data under ideal circumstances and the possible roles that the AHA might play in meeting their needs. Important areas that are high priorities for further study regarding Big Data include a description of the methodology of how to acquire and analyze findings, validation of the veracity of discoveries from such research, and integration into investigative and clinical care aspects of future cardiovascular and stroke medicine. Potential roles that the AHA might consider include facilitating a standards discussion (eg, tools, methodology, and appropriate data use), providing education (eg, healthcare providers, patients, investigators), and helping build an interoperable digital ecosystem in cardiovascular and stroke science. CONCLUSION: There was a consensus across stakeholder domains that Big Data holds great promise for revolutionizing the way cardiovascular and stroke research is conducted and clinical care is delivered; however, there is a clear need for the creation of a vision of how to use it to achieve the desired goals. Potential roles for the AHA center around facilitating a discussion of standards, providing education, and helping establish a cardiovascular digital ecosystem. This ecosystem should be interoperable and needs to interface with the rapidly growing digital object environment of the modern-day healthcare system.Item Open Access Defining a Mobile Health Roadmap for Cardiovascular Health and Disease.(J Am Heart Assoc, 2016-07-12) Eapen, Zubin J; Turakhia, Mintu P; McConnell, Michael V; Graham, Garth; Dunn, Patrick; Tiner, Colby; Rich, Carlo; Harrington, Robert A; Peterson, Eric D; Wayte, PatrickItem Open Access The Association Between Engagement and Weight Loss Through Personal Coaching and Cell Phone Interventions in Young Adults: Randomized Controlled Trial.(JMIR mHealth and uHealth, 2018-10) Lin, Pao-Hwa; Grambow, Steven; Intille, Stephen; Gallis, John A; Lazenka, Tony; Bosworth, Hayden; Voils, Corrine L; Bennett, Gary G; Batch, Bryan; Allen, Jenifer; Corsino, Leonor; Tyson, Crystal; Svetkey, LauraBackground
Understanding how engagement in mobile health (mHealth) weight loss interventions relates to weight change may help develop effective intervention strategies.Objective
This study aims to examine the (1) patterns of participant engagement overall and with key intervention components within each intervention arm in the Cell Phone Intervention For You (CITY) trial; (2) associations of engagement with weight change; and (3) participant characteristics related to engagement.Methods
The CITY trial tested two 24-month weight loss interventions. One was delivered with a smartphone app (cell phone) containing 24 components (weight tracking, etc) and included prompting by the app in predetermined frequency and forms. The other was delivered by a coach via monthly calls (personal coaching) supplemented with limited app components (18 overall) and without any prompting by the app. Engagement was assessed by calculating the percentage of days each app component was used and the frequency of use. Engagement was also examined across 4 weight change categories: gained (≥2%), stable (±2%), mild loss (≥2% to <5%), and greater loss (≥5%).Results
Data from 122 cell phone and 120 personal coaching participants were analyzed. Use of the app was the highest during month 1 for both arms; thereafter, use dropped substantially and continuously until the study end. During the first 6 months, the mean percentage of days that any app component was used was higher for the cell phone arm (74.2%, SD 20.1) than for the personal coaching arm (48.9%, SD 22.4). The cell phone arm used the apps an average of 5.3 times/day (SD 3.1), whereas the personal coaching participants used them 1.7 times/day (SD 1.2). Similarly, the former self-weighed more than the latter (57.1% days, SD 23.7 vs 32.9% days, SD 23.3). Furthermore, the percentage of days any app component was used, number of app uses per day, and percentage of days self-weighed all showed significant differences across the 4 weight categories for both arms. Pearson correlation showed a negative association between weight change and the percentage of days any app component was used (cell phone: r=-.213; personal coaching: r=-.319), number of apps use per day (cell phone: r=-.264; personal coaching: r=-.308), and percentage of days self-weighed (cell phone: r=-.297; personal coaching: r=-.354). None of the characteristics examined, including age, gender, race, education, income, energy expenditure, diet quality, and hypertension status, appeared to be related to engagement.Conclusions
Engagement in CITY intervention was associated with weight loss during the first 6 months. Nevertheless, engagement dropped substantially early on for most intervention components. Prompting may be helpful initially. More flexible and less intrusive prompting strategies may be needed during different stages of an intervention to increase or sustain engagement. Future studies should explore the motivations for engagement and nonengagement to determine meaningful levels of engagement required for effective intervention.Trial registration
ClinicalTrials.gov NCT01092364; https://clinicaltrials.gov/ct2/show/NCT01092364 (Archived by WebCite at http://www.webcitation.org/72V8A4e5X).