The rise in Smartphone use and the advances in app and internet use on such devices create a viable mode for survey data collection that now needs to be formally investigated. The Smartphone offers a multimode device that can be accessed via voice, text or internet and can make use of synchronous multimedia messaging. As form factors continue to increase in size, these handheld devices may also replace handheld personal data assistants for in-person data collection. Clearly best practices and current research related to online survey development can serve as a basis for such design and implementation. However, differences in processing, form factors and variability among platforms suggest that these best practices must be adapted, expanded and modified for surveys on mobile devices. The first part of this paper presents comprehensive results from one of the first smartphone mode experiments (The Got Healthy Apps Study) conducted within the U.S. In particular, this study randomized iPhone owners who were members of an online computer web-panel to complete the survey about health behaviors and health related app usage via their iPhone (221 completes) or computer (209 completes). We report differences in survey completion times, recency/primacy effects, back button use frequency, open-ended data entry and overall app and smartphone usage across the modes.

The second part of this paper focuses on one of the defining features of smartphones – the applications (APPS). Currently, health, survey, market and other researchers have begun to deploy smartphone apps as a means of intervention, data collection and marketing. What has lagged behind in the research literature is how smartphone users refer to, describe or recognize the apps they use- either by icon or by name? This feature is important if phone surveys are to be deployed as a mode of inquiry regarding smartphone app use (i.e. how should interviewers refer to these apps- by description or by name?). The second part of this study presents the results from a within-person app recognition experiment that randomized respondents to one of two presentation orders (app icon images followed by app names or vice-versa) and to one of two app lists (each contained eight of the most popular apps from overall, lifestyle and game categories). Using a mixed effects model, we examine differences in app recognition rates by mode across these two random effects. We also provide a brief description of how the iPhone survey was developed and deployed.