Characteristics of smartphone-based dietary assessment tools: a systematic review

ABSTRACT

Smartphones have become popular in assessing eating behaviour in real-life and real-time. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured. Seven databases from behavioural, social and computer science were searched in March 2020. All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), and classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and framework of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants’ willingness to record their behaviour to ultimately improve the quality of smartphone-based dietary assessment for health research.

KEYWORDS:

• Ecological momentary assessment
• smartphone
• mhealth
• diet
• eating behaviour
• dietary assessment

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

A list of all full texts screened and the raw data extracted from the included publications can be obtained from https://osf.io/xg8s6/. The search strategy, a list of all extracted information, and a summary of the included data can be found in the online supplement.

Notes

1 Deviation from the preregistered protocol.

2 Deviation from the preregistered protocol.

3 Data on user experience metrics were extracted; however, they were only reported for 24 of the included tools. The extracted information can be found in column BH in the raw data file provided on https://osf.io/xg8s6/.

Additional information

Funding

This research was funded by a German Research Foundation (DFG) [Deutsche Forschungsgemeinschaft] research fellowship granted to LK (KO 6018/1-1).