Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence

• Published in: BMC psychiatry 2022-06, Vol.22 (1), p.1-421, Article 421
• Main Authors: Zarate, Daniel, Stavropoulos, Vasileios, Ball, Michelle, de Sena Collier, Gabriel, Jacobson, Nicholas C
• Format: Article
• Language: English
• Subjects: Ambulatory assessment; Analysis; Behavior; Biomarkers; Care and treatment; Cellular telephones; Circadian rhythm; Circadian rhythms; Data collection; Data entry; Depression; Depression, Mental; Diagnosis; Digital phenotype; Digital technology; Ecological momentary assessment; Electronic records; Experience sampling; Genotype & phenotype; Health aspects; Kinematics; Literature reviews; Medical laboratory technology; Medical records; Medical technology; Mental depression; Mental disorders; Mental health; Methods; Mobile applications; Passive sensing; Phenotyping; Psychiatry; Risk factors; Systematic review; Terminology
• ISSN: 1471-244X; 1471-244X
• DOI: 10.1186/s12888-022-04013-y

Background This PRISMA systematic literature review examined the use of digital data collection methods (including ecological momentary assessment [EMA], experience sampling method [ESM], digital biomarkers, passive sensing, mobile sensing, ambulatory assessment, and time-series analysis), emphasizing on digital phenotyping (DP) to study depression. DP is defined as the use of digital data to profile health information objectively. Aims Four distinct yet interrelated goals underpin this study: (a) to identify empirical research examining the use of DP to study depression; (b) to describe the different methods and technology employed; (c) to integrate the evidence regarding the efficacy of digital data in the examination, diagnosis, and monitoring of depression and (d) to clarify DP definitions and digital mental health records terminology. Results Overall, 118 studies were assessed as eligible. Considering the terms employed, "EMA", "ESM", and "DP" were the most predominant. A variety of DP data sources were reported, including voice, language, keyboard typing kinematics, mobile phone calls and texts, geocoded activity, actigraphy sensor-related recordings (i.e., steps, sleep, circadian rhythm), and self-reported apps' information. Reviewed studies employed subjectively and objectively recorded digital data in combination with interviews and psychometric scales. Conclusions Findings suggest links between a person's digital records and depression. Future research recommendations include (a) deriving consensus regarding the DP definition and (b) expanding the literature to consider a person's broader contextual and developmental circumstances in relation to their digital data/records. Keywords: Digital phenotype, Ecological momentary assessment, Experience sampling, Passive sensing, Ambulatory assessment, Depression, PRISMA, Systematic literature review