Mobile Health Physical Activity Intervention Preferences in Cancer Survivors: A Qualitative Study

Abstract

BackgroundCancer survivors are at an elevated risk for several negative health outcomes, but physical activity (PA) can decrease those risks. Unfortunately, adherence to PA recommendations among survivors is low. Fitness mobile apps have been shown to facilitate the adoption of PA in the general population, but there are limited apps specifically designed for cancer survivors. This population has unique needs and barriers to PA, and most existing PA apps do not address these issues. Moreover, incorporating user preferences has been identified as an important priority for technology-based PA interventions, but at present there is limited literature that serves to establish these preferences in cancer survivors. This is especially problematic given the high cost of app development and because the majority of downloaded apps fail to engage users over the long term.ObjectiveThe aim of this study was to take a qualitative approach to provide practical insight regarding this population’s preferences for the features and messages of an app to increase PA.MethodsA total of 35 cancer survivors each attended 2 focus groups; a moderator presented slide shows on potential app features and messages and asked open-ended questions to elicit participant preferences. All sessions were audio recorded and transcribed verbatim. Three reviewers independently conducted thematic content analysis on all transcripts, then organized and consolidated findings to identify salient themes.ResultsParticipants (mean age 63.7, SD 10.8, years) were mostly female (24/35, 69%) and mostly white (25/35, 71%). Participants generally had access to technology and were receptive to engaging with an app to increase PA. Themes identified included preferences for (1) a casual, concise, and positive tone, (2) tools for personal goal attainment, (3) a prescription for PA, and (4) an experience that is tailored to the user. Participants reported wanting extensive background data collection with low data entry burden and to have a trustworthy source translate their personal data into individualized PA recommendations. They expressed a desire for app functions that could facilitate goal achievement and articulated a preference for a more private social experience. Finally, results indicated that PA goals might be best established in the context of personally held priorities and values.ConclusionsMany of the desired features identified are compatible with both empirically supported methods of behavior change and the relative strengths of an app as a delivery vehicle for behavioral intervention. Participating cancer survivors’ preferences contrasted with many current standard practices for mobile app development, including value-based rather than numeric goals, private socialization in small groups rather than sharing with broader social networks, and interpretation of PA data rather than merely providing numerical data. Taken together, these insights may help increase the acceptability of theory-based mHealth PA interventions in cancer survivors.

Physical Activity and Sedentary Behavior in Older Gastrointestinal Cancer Survivors: Need and Acceptability of Digital Health Interventions

“…Approximately a quarter of the sample reported interest in digital health tools for both PA and SB. Consistent with our results, younger survivors from other cancer survivor populations have expressed greater interest than older survivors in digital health interventions [14]. At present, it appears that digital tools should not be used as a sole behavioral intervention modality with older GI cancer survivors.…”

“…Digital interventions for lifestyle behavior change show promise for increasing PA in cancer survivors and represent a potential solution for reaching survivors without access to specialty care [13]. Interest in digital interventions among cancer survivors is generally positive, with a recent study finding 97% of survivors expressed interest in mobile and internet technologies [14]. Yet technology adoption rates are limited among older adults so it is not clear whether older cancer survivors would accept digital tools for modifying activity-related behaviors [15].…”

Development of the mHealth App Trustworthiness checklist

“…38 Overall, 15 peer-reviewed Englishlanguage studies published between 2008-2018 were included in this review. [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53] Based on the abovedescribed inclusion criteria, each of the 15 studies provided details about the features of physical activity apps that enhanced end-users' experience. In Table 1, we show the condensed themes designed for the focus group discussions.…”

3MD for Chronic Conditions, a Model for Motivational mHealth Design: Embedded Case Study (Preprint)

“…The use of instant feedback and positive reinforcement from learning theories are common use in mHealth applications [29,47]; Health Belief Model (HBM) has been used in mHealth interventions for self-management and health promotion [52][53][54]; the Transtheoretical Model (TTM) has been used in mobile solutions for smoke cessation and other addictive behaviors [55][56][57][58]; physical activity and fitness interventions use the Theory of Planned Behavior (TPB) [29,50,59], as well as self-regulation theories [29,[60][61][62][63]. The basis for Social Cognitive Theories (SCT) can be found in many interventions using health apps for disease management [64][65][66] and goal setting is very often used in mHealth apps [60,67].…”