Mobile App-Based Small-Group Physical Activity Intervention for Young African American Women: a Pilot Randomized Controlled Trial

Zhang, Jingwen; Jemmott, John B.

doi:10.1007/s11121-019-01006-4

Cited by 38 publications

(27 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The four high-level components are specified in sequence to guide the design and evaluation of chatbots. This proposed model is based on reviewing relevant chatbot studies, recent developments in human-AI communication research, and innovations in NLP, as well as our own clinical and research experience and findings [ 23 , 49 - 54 ].…”

Section: Resultsmentioning

confidence: 99%

“…Our proposed theoretical framework is the first step to conceptualize the scope of the work and to synthesize all possible dimensions of chatbot features to inform intervention design. However, when applied in specific contexts, researchers and practitioners can prioritize certain features that are mostly relevant to the target population, according to initial formative research conducted with the target population [ 54 ]. In essence, we encourage researchers to select and design chatbot features through working with the target communities using stakeholder-inclusive and participatory design approaches [ 109 , 110 ].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Zhang¹,

Oh²,

Lange³

et al. 2020

J Med Internet Res

Self Cite

195

116

View full text Add to dashboard Cite

Background Chatbots empowered by artificial intelligence (AI) can increasingly engage in natural conversations and build relationships with users. Applying AI chatbots to lifestyle modification programs is one of the promising areas to develop cost-effective and feasible behavior interventions to promote physical activity and a healthy diet. Objective The purposes of this perspective paper are to present a brief literature review of chatbot use in promoting physical activity and a healthy diet, describe the AI chatbot behavior change model our research team developed based on extensive interdisciplinary research, and discuss ethical principles and considerations. Methods We conducted a preliminary search of studies reporting chatbots for improving physical activity and/or diet in four databases in July 2020. We summarized the characteristics of the chatbot studies and reviewed recent developments in human-AI communication research and innovations in natural language processing. Based on the identified gaps and opportunities, as well as our own clinical and research experience and findings, we propose an AI chatbot behavior change model. Results Our review found a lack of understanding around theoretical guidance and practical recommendations on designing AI chatbots for lifestyle modification programs. The proposed AI chatbot behavior change model consists of the following four components to provide such guidance: (1) designing chatbot characteristics and understanding user background; (2) building relational capacity; (3) building persuasive conversational capacity; and (4) evaluating mechanisms and outcomes. The rationale and evidence supporting the design and evaluation choices for this model are presented in this paper. Conclusions As AI chatbots become increasingly integrated into various digital communications, our proposed theoretical framework is the first step to conceptualize the scope of utilization in health behavior change domains and to synthesize all possible dimensions of chatbot features to inform intervention design and evaluation. There is a need for more interdisciplinary work to continue developing AI techniques to improve a chatbot’s relational and persuasive capacities to change physical activity and diet behaviors with strong ethical principles.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Zhang¹,

Oh²,

Lange³

et al. 2020

J Med Internet Res

Self Cite

195

116

View full text Add to dashboard Cite

show abstract

“…Evidence accumulated over the past decade has shown that PA interventions delivered through mobile and smartphone devices (commonly referred to as mobile health [mHealth] PA interventions) are effective for promoting PA [10][11][12]. However, few mHealth PA interventions have focused on African American women [13][14][15][16], and even fewer have included midlife or older African American women [14,15]. This represents a missed public health opportunity, given the low PA levels, high cardiometabolic disease burden, and high level of smartphone use among African American women (recent data show that 79% of adults between the ages of 50 and 65 years own a smartphone, with limited or no differences by sex, race, or ethnicity [17]).…”

Section: Introductionmentioning

confidence: 99%

Results of a Culturally Tailored Smartphone-Delivered Physical Activity Intervention Among Midlife African American Women: Feasibility Trial

Joseph¹,

Ainsworth²,

Hollingshead³

et al. 2021

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

Background Regular aerobic physical activity (PA) is an important component of healthy aging. However, only 27%-40% of African American women achieve national PA guidelines. Available data also show a clear decline in PA as African American women transition from young adulthood (ie, 25-44 years) into midlife. This decline in PA during midlife coincides with an increased risk for African American women developing cardiometabolic disease conditions, including obesity, type 2 diabetes, and cardiovascular disease. Thus, effective efforts are needed to promote PA among sedentary African American women during midlife. Objective This study aims to examine the acceptability and feasibility of a culturally tailored, smartphone-delivered PA intervention, originally developed to increase PA among African American women aged 24-49 years, among a slightly older sample of midlife African American women aged 50-65 years. Methods A single-arm pretest-posttest study design was implemented. In total, 20 insufficiently active African American (ie, ≤60 min per week of PA) women between the ages of 50-65 years participated in the 4-month feasibility trial. The Smart Walk intervention was delivered through the study Smart Walk smartphone app and text messages. Features available on the Smart Walk app include personal profile pages, multimedia PA promotion modules, discussion board forums, and an activity tracking feature that integrates with Fitbit activity monitors. Self-reported PA and social cognitive theory mediators targeted by the intervention (ie, self-regulation, behavioral capability, outcome expectations, self-efficacy, and social support) were assessed at baseline and at 4 months. Feasibility and acceptability were assessed using a postintervention satisfaction survey that included multiple-choice and open-ended questions evaluating participant perceptions of the intervention and suggestions for intervention improvement. Wilcoxon signed-rank tests were used to examine pre- and postintervention changes in the PA and social cognitive theory variables. The effect size estimates were calculated using the Pearson r test statistic. Results Participants increased moderate-to-vigorous PA (median 30 minutes per week increase; r=0.503; P=.002) and reported improvements in 2 theoretical mediators (self-regulation: r=0.397; P=.01; behavioral capability: r=0.440; P=.006). Nearly all participants (14/15, 93% completing the satisfaction survey) indicated that they would recommend the intervention to a friend. Participants’ suggestions for improving the intervention included enhancing the intervention’s provisions of social support for PA. Conclusions The results provide preliminary support for the feasibility of the smartphone-based approach to increase PA among midlife African American women. However, before larger-scale implementation among midlife African American women, enhancements to the social support components of the intervention are warranted. Trial Registration ClinicalTrials.gov NCT04073355; https://clinicaltrials.gov/ct2/show/NCT04073355

show abstract

“…The PennFit study is an app-based physical activity intervention for young African American women (Zhang, 2017), a population at high risk for the deleterious consequences of physical inactivity (American Cancer Society, 2013; Centers for Disease Control and Prevention, 2011; Go et al, 2013; Murphy, Xu, & Kochanek, 2013). The study aimed to assist young African American women in establishing physical activity routines in their daily life.…”

Section: Case Study: An App-based Physical Activity Intervention Amonmentioning

confidence: 99%

Advantages and challenges in using mobile apps for field experiments: A systematic review and a case study

Zhang

Calabrese

Ding

et al. 2017

Mobile Media & Communication

Self Cite

View full text Add to dashboard Cite

As smartphone’s computing power continues to grow and as mobile applications (apps) continue to dominate digital engagement, apps have become a new frontier for advancing field experiment methodology. Using apps may help researchers to scale up the reach, precisely control randomization and experiment materials, collect a variety of objective and self-reported data over time, and more conveniently replicate and adapt an experiment. We performed a systematic review on field experiments involving apps published between 2007 and 2017. Seven databases were scanned using a predefined search strategy. The database search retrieved 4,810 citations; 101 articles met the inclusion criteria. Our review suggests that scholars have only started to employ apps in field experiments in the last 4 years. Most studies only used apps as an experiment treatment instead of an experiment platform; therefore, researchers have yet to fully leverage the advantages. Almost all studies were from the health research domain and 77.2% used randomized controlled trial design. Only 7 studies utilized smartphone sensors for collecting data. Only one study reported cost and ethical concerns regarding using apps for the experiment. Given these findings, we reported a case study that targeted a minority racial group and leveraged the advantages of apps as an experiment platform and as a data collection tool to illustrate practical challenges and lessons learned regarding time, financial cost, and technical support. In conclusion, we suggest apps provide new ways to study causal mechanisms with experiment big data. Limitations of generalizability, retention, and design quality were discussed as well.

show abstract

Mobile App-Based Small-Group Physical Activity Intervention for Young African American Women: a Pilot Randomized Controlled Trial

Cited by 38 publications

References 48 publications

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint

Results of a Culturally Tailored Smartphone-Delivered Physical Activity Intervention Among Midlife African American Women: Feasibility Trial

Advantages and challenges in using mobile apps for field experiments: A systematic review and a case study

Contact Info

Product

Resources

About