Effectiveness of a Web- and Mobile Phone-Based Intervention to Promote Physical Activity and Healthy Eating in Middle-Aged Males: Randomized Controlled Trial of the ManUp Study

Abstract

BackgroundThe high number of adult males engaging in low levels of physical activity and poor dietary practices, and the health risks posed by these behaviors, necessitate broad-reaching intervention strategies. Information technology (IT)-based (Web and mobile phone) interventions can be accessed by large numbers of people, yet there are few reported IT-based interventions targeting males’ physical activity and dietary practices.ObjectiveThis study examines the effectiveness of a 9-month IT-based intervention (ManUp) to improve the physical activity, dietary behaviors, and health literacy in middle-aged males compared to a print-based intervention.MethodsParticipants, recruited offline (eg, newspaper ads), were randomized into either an IT-based or print-based intervention arm on a 2:1 basis in favor of the fully automated IT-based arm. Participants were adult males aged 35-54 years living in 2 regional cities in Queensland, Australia, who could access the Internet, owned a mobile phone, and were able to increase their activity level. The intervention, ManUp, was based on social cognitive and self-regulation theories and specifically designed to target males. Educational materials were provided and self-monitoring of physical activity and nutrition behaviors was promoted. Intervention content was the same in both intervention arms; only the delivery mode differed. Content could be accessed throughout the 9-month study period. Participants’ physical activity, dietary behaviors, and health literacy were measured using online surveys at baseline, 3 months, and 9 months.ResultsA total of 301 participants completed baseline assessments, 205 in the IT-based arm and 96 in the print-based arm. A total of 124 participants completed all 3 assessments. There were no significant between-group differences in physical activity and dietary behaviors (P≥.05). Participants reported an increased number of minutes and sessions of physical activity at 3 months (exp(β)=1.45, 95% CI 1.09-1.95; exp(β)=1.61, 95% CI 1.17-2.22) and 9 months (exp(β)=1.55, 95% CI 1.14-2.10; exp(β)=1.51, 95% CI 1.15-2.00). Overall dietary behaviors improved at 3 months (exp(β)=1.07, 95% CI 1.03-1.11) and 9 months (exp(β)=1.10, 95% CI 1.05-1.13). The proportion of participants in both groups eating higher-fiber bread and low-fat milk increased at 3 months (exp(β)=2.25, 95% CI 1.29-3.92; exp(β)=1.65, 95% CI 1.07-2.55). Participants in the IT-based arm were less likely to report that 30 minutes of physical activity per day improves health (exp(β)=0.48, 95% CI 0.26-0.90) and more likely to report that vigorous intensity physical activity 3 times per week is essential (exp(β)=1.70, 95% CI 1.02-2.82). The average number of log-ins to the IT platform at 3 and 9 months was 6.99 (SE 0.86) and 9.22 (SE 1.47), respectively. The average number of self-monitoring entries at 3 and 9 months was 16.69 (SE 2.38) and 22.51 (SE 3.79), respectively.ConclusionsThe ManUp intervention was effective in improving physical activity and dietary behaviors in middle-aged males with no ...

Characteristics of Smartphone Applications for Nutrition Improvement in Community Settings: A Scoping Review

“…This finding was also identified in a systematic review of applications for obesity prevention that focuses on user-centered design (9). Bugs and application functionality problems (such as requiring an internet connection) that would undoubtedly have been illuminated in consumer testing reportedly needlessly influenced application engagement in a number of trials (39,42,51,57,60). Reasons provided for not conducting user testing included practical timing and resource and funding constraints of studies (57); however, most reports provided no reasoning.…”

“…Of the 4818 titles identified from the database search, 64 articles were included: 9 reporting dietary self-monitoring trials (38)(39)(40)(41)(42)(43)(44)(45)(46), 18 reporting nutritionimprovement trials (36,(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58)(59)(60)(61)(62)(63), 30 reporting applicationdevelopment projects (37,, and 7 reporting qualitative studies with consumers (93)(94)(95)(96)(97)(98)(99). Five reports were published in 2016, 16 each in 2015 and 2014, 11 in 2013, and 16 between 2008 and 2012.…”

“…Personalized settings and the ability to turn off features were considered important across population groups (74,90,93). Personalization of goals and challenges, and feedback based on these, was considered important by overweight and general adult populations (39,41,74,80,88). Similarly, using culturally relevant and favorite foods within games was desirable for low-SES populations (50,79,89) and enabled transfer of learning to real life (85).…”

Persuasive Technology in Mobile Applications Promoting Physical Activity: a Systematic Review

“…Figure 2 trial or outcome studies, five articles focused on software design and evaluation and the remaining articles are on focus groups and interview studies on stakeholders' opinions on smart phone apps for physical activity (see Table 1). [25] × × [26] × [27] × × × × × × × × × [28] × × × × × × × × [29] × × × × [30] × × × [31] × [32] × × × × × × × × × × × × [33] × × [34] × × × × × × × [35] × × × × [36] × × × × × × [37] × [38] × × × [39] × × × × × [40] × [41] × [42] × × × × [43] × × [44] Illustrations in figure 2 and table 2 show features that are highly present in articles on physical activity intervention studies, those features that were occasionally mentioned, or those that were not cited often in these articles. Visualisation of persuasive features is presented to provide more insights about the highlights, 9 gaps and blank spots [45] in current mobile application persuasive design features on physical activity.…”

“…Self-monitoring was implemented in the form of manual logging [27] or automatic tracking of physical activity [30], either in terms of step count [29], distance travelled [30], active time [31] or sedentary time [25], or other self-evaluation criteria. A qualitative study of user's attitudes towards mobile application promoting physical activity indicated that selfmonitoring is considered to be an important tool in behaviour modification [28].…”