JMIR Publications

ABSTRACT

Background:

Poor diet, alcohol use and tobacco smoking have been identified as strong determinants of chronic disease, such as cardiovascular disease, diabetes and cancers. Smartphones have the potential to provide a real-time, pervasive, unobtrusive and cost-effective way to measure these health behaviours and deliver instant feedback to users. Despite this, the validity of using smartphones to measure these behaviours is largely unknown.

Objective:

The aim of our review was to identify existing smartphone—based approaches to measure these health behaviours and critically appraise the quality of their measurement properties.

Methods:

We conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsychINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Studies that were written in English, reported measuring diet, alcohol use and/or tobacco use via a smartphone, and reported on at least one measurement property (eg validity, reliability and/or responsiveness) were eligible. Outcomes were summarised in a narrative synthesis. This systematic review is registered with PROSPERO, identifier CRD42019122242.

Results:

Of 12,261 records, 72 studies describing the measurement properties of smartphone—based approaches to measure diet (n=48), alcohol use (n=16) and tobacco use (n=8) were identified and included in the current review. Across the health behaviours, 18 different measurement techniques were used within smartphones. The measurement properties most commonly examined were construct validity, measurement error and criterion validity. Results varied by behaviour and measurement approach and the methodological quality of studies varied widely. Most studies investigating the measurement of diet and alcohol received ‘very good’ or ‘adequate’ methodological quality ratings (72.9%, 35/48, and 68.8%, 11/16, respectively), while only one study (12.5%, 1/8) investigating the measurement of tobacco use received a ‘very good’ or ‘adequate’ rating.

Conclusions:

This review is the first to bring together evidence regarding the different types of smartphone—based approaches currently used to measure key behavioural risk factors for chronic disease (diet, alcohol use and tobacco use) and the quality of their measurement properties. Nineteen measurement techniques were identified, the majority of which assessed dietary behaviours (67%, n=48/72). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviours, however results varied by behaviour and measurement approach. The methodological quality of included studies also varied. Overall, more high-quality studies validating smartphone based approaches against criterion measures are needed. More research investigating the use of smartphones to assess alcohol and tobacco use, and objective measurement approaches is also needed.