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BackgroundAdvancements in mobile technology allow innovative data collection techniques such as measuring time use (ie, how individuals structure their time) for the purpose of improving health behavior change interventions.ObjectiveThe aim of this study was to examine the acceptability of a 5-day trial of the Life in a Day mobile phone app measuring time use in breast cancer survivors to advance technology-based measurement of time use.MethodsAcceptability data were collected from participants (N=40; 100% response rate) using a self-administered survey after 5 days of Life in a Day use.ResultsOverall, participants had a mean age of 55 years (SD 8) and completed 16 years of school (SD 2). Participants generally agreed that learning to use Life in a Day was easy (83%, 33/40) and would prefer to log activities using Life in a Day over paper-and-pencil diary (73%, 29/40). A slight majority felt that completing Life in a Day for 5 consecutive days was not too much (60%, 24/40) or overly time-consuming (68%, 27/40). Life in a Day was rated as easy to read (88%, 35/40) and navigate (70%, 32/40). Participants also agreed that it was easy to log activities using the activity timer at the start and end of an activity (90%, 35/39). Only 13% (5/40) downloaded the app on their personal phone, whereas 63% (19/30) of the remaining participants would have preferred to use their personal phone. Overall, 77% (30/39) of participants felt that the Life in a Day app was good or very good. Those who agreed that it was easy to edit activities were significantly more likely to be younger when compared with those who disagreed (mean 53 vs 58 years, P=.04). Similarly, those who agreed that it was easy to remember to log activities were more likely to be younger (mean 52 vs 60 years, P<.001). Qualitative coding of 2 open-ended survey items yielded 3 common themes for Life in a Day improvement (ie, convenience, user interface, and reminders).ConclusionsA mobile phone app is an acceptable time-use measurement modality. Improving convenience, user interface, and memory prompts while addressing the needs of older participants is needed to enhance app utility.Trial RegistrationClinicalTrials.gov NCT00929617; https://clinicaltrials.gov/ct2/show/NCT00929617 (Archived by WebCite at http://www.webcitation.org/6z2bZ4P7X)

Women in midlife experience health risks that could be mitigated by regular physical activity and reduced sedentary time, but this population rarely achieves physical activity levels that would protect their health. As a result, many behavioral interventions are designed to promote physical activity in this population, which are purportedly guided by theoretical models of health behavior (change) and activate an associated set of behavior change techniques (BCTs). The efficacy and effectiveness of these interventions appear to be limited, however, raising questions about their design and adaptation for women in midlife. Several aspects of these interventions are currently unclear. Specifically, which women they target (i.e., how “midlife” and “sedentary” or “inactive” are defined), which theoretical models or behavior BCTs are used, and how BCTs are activated in such interventions. A synthesis of this information would be useful as an initial step toward improving physical activity interventions for this at-risk group, and thus, represented the goal of the present scoping review. Eligibility required publication in a peer-reviewed journal in English between 2000 and 2021, inclusion of only women in midlife who did not have any medical or other restrictions on their physical activity (e.g., cancer diagnosis), and free-living physical activity or sedentary behavior as the target outcome (with associated assessment). Of the 4,410 initial results, 51 articles met inclusion criteria, and these described 36 unique interventions. More than half of the articles (59%) named an underlying theoretical model and interventions included an average of 3.76 identifiable BCTs (range 1–11). However, descriptions of many interventions were limited and did not provide enough detail to determine whether or how specific BCTs were activated. Interventions also used a wide range of inclusion criteria for age range and starting activity level, which has implications for targeting/tailoring and effectiveness, and many interventions focused on marginalized populations (e.g., women from racial/ethnic minority backgrounds, those un- or under-insured). The present review identifies some strengths and highlights important limitations of existing literature, as well as key opportunities for advancing the design and potential utility of physical activity interventions for women in midlife.Systematic review registrationhttps://osf.io/g8tuc.

Background Midlife women are at an elevated risk for cardiovascular disease (CVD) and associated mortality. Those who have additional risk conditions such as obesity or hypertension report specific barriers to engaging in cardioprotective behaviors such as physical activity (PA). Considerable effort has been devoted to understanding PA determinants and designing interventions for midlife women, although with suboptimal success, as increasing PA could meaningfully attenuate CVD risk. An updated approach to understanding PA among midlife women could improve upon existing resources by focusing on novel psychosocial influences on PA in this population (ie, body satisfaction, social interactions, social comparisons, mood state) and within-person relations between these influences and PA in the natural environment. Objective The overarching goal of Project WHADE (Women’s Health And Daily Experiences) is to use an ecological momentary assessment (EMA) approach to capture ecologically valid relations between midlife women’s psychosocial experiences and PA as they engage in their normal daily activities. The primary aim of the study is to identify within-person psychosocial predictors of variability in PA (ie, experiences associated with higher vs lower PA for a given individual). Methods Midlife women (aged 40-60 years) with one or more additional risk markers for CVD (eg, hypertension) will be recruited from primary care clinics and the general community (target n=100). Eligible women will complete an initial survey and a face-to-face baseline session before engaging in a 10-day EMA protocol. Psychosocial experiences will be assessed using a brief self-report via a smartphone 5 times per day, and PA will be assessed throughout waking hours using a research-grade monitor. Participants will return for a brief exit interview at the end of 10 days. Multilevel models that address the nested structure of EMA data will be used to evaluate the study aims. Results Recruitment and enrollment are ongoing, and a total of 75 women have completed the protocol to date. Data collection is expected to be completed in Fall 2020. Conclusions Project WHADE is designed to identify naturally occurring psychosocial experiences that predict short-term variability in midlife women’s PA. As such, the results of this study should advance the current understanding of PA among midlife women by providing further insight into within-person psychosocial influences on PA in this group. In the future, this information could help inform the design of interventions for this population. International Registered Report Identifier (IRRID) DERR1-10.2196/19044

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Background Women in midlife are vulnerable to developing cardiovascular disease, particularly those who have conditions such as hypertension. Physical activity (PA) can reduce risk, but efforts to promote PA in this population have been only modestly effective. More attention to social influences on PA behavior may be useful, particularly social support and social comparison processes. Activating these processes with digital tools can provide easy access that is flexible to the needs of women in midlife. Objective This paper describes the user-centered design processes of developing and conducting initial evaluation of a personalized and adaptive web application, tailored to the social needs of women in midlife. The goal was to gather feedback from the population of interest, before and during the design process. Methods This study was conducted in 4 stages. The first and second authors (DA and AFL) developed technical specifications, informed by their experience with the population of interest. We collected feedback on potential content for the web application with women in midlife using both interviews (5/10, 50%; mean age 47.4, SD 6.66 years; mean BMI 35.3, SD 9.55 kg/m2) and surveys (5/10, 50%; mean age 51, SD 6.60 years; mean BMI 32.7, SD 8.39 kg/m2). We used their feedback to inform support messages and peer profiles (ie, sources of social comparison information). Nine members of the behavioral science team and 3 testers unfamiliar with the web application completed internal testing. We conducted naturalistic functionality testing with a different group of women in midlife (n=5; mean age 50, SD 6.26 years; mean BMI 30.1, SD 5.83 kg/m2), who used the web application as intended for 4 days and provided feedback at the end of this period. Results Iterative storyboard development resulted in programming specifications for a prototype of the web application. We used content feedback to select and refine the support messages and peer profiles to be added. The following 2 rounds of internal testing identified bugs and other problems regarding the web application’s functioning and full data collection procedure. Problems were addressed or logged for future consideration. Naturalistic functionality testing revealed minimal further problems; findings showed preliminary acceptability of the web application and suggested that women may select different social content across days. Conclusions A multidisciplinary and user-centered design approach led to a personalized and adaptive web application, tailored to the social needs of women in midlife. Findings from testing with this population demonstrated the feasibility and acceptability of the new application and supported further development toward its use in daily life. We describe several potential uses of the web application and next steps for its development. We also discuss the lessons learned and offer recommendations for future collaborations between behavioral and computer scientists to develop similar tools.