{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T12:31:47Z","timestamp":1780576307672,"version":"3.54.1"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T00:00:00Z","timestamp":1705017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Access Publication Fund of the University of Wuerzburg"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As mobile devices have become a central part of our daily lives, they are also becoming increasingly important in research. In the medical context, for example, smartphones are used to collect ecologically valid and longitudinal data using Ecological Momentary Assessment (EMA), which is mostly implemented through questionnaires delivered via smart notifications. This type of data collection is intended to capture a patient\u2019s condition on a moment-to-moment and longer-term basis. To collect more objective and contextual data and to understand patients even better, researchers can not only use patients\u2019 input via EMA, but also use sensors as part of the Mobile Crowdsensing (MCS) approach. In this paper, we examine how researchers have embraced the topic of MCS in the context of EMA through a systematic literature review. This PRISMA-guided review is based on the databases PubMed, Web of Science, and EBSCOhost. It is shown through the results that both EMA research in general and the use of sensors in EMA research are steadily increasing. In addition, most of the studies reviewed used mobile apps to deliver EMA to participants, used a fixed-time prompting strategy, and used signal-contingent or interval-contingent self-assessment as sampling\/assessment strategies. The most commonly used sensors in EMA studies are the accelerometer and GPS. In most studies, these sensors are used for simple data collection, but sensor data are also commonly used to verify study participant responses and, less commonly, to trigger EMA prompts. Security and privacy aspects are addressed in only a subset of mHealth EMA publications. Moreover, we found that EMA adherence was negatively correlated with the total number of prompts and was higher in studies using a microinteraction-based EMA (\u03bcEMA) approach as well as in studies utilizing sensors. Overall, we envision that the potential of the technological capabilities of smartphones and sensors could be better exploited in future, more automated approaches.<\/jats:p>","DOI":"10.3390\/s24020472","type":"journal-article","created":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T07:47:16Z","timestamp":1705045636000},"page":"472","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Mobile Crowdsensing in Ecological Momentary Assessment mHealth Studies: A Systematic Review and Analysis"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0657-3232","authenticated-orcid":false,"given":"Robin","family":"Kraft","sequence":"first","affiliation":[{"name":"Institute of Databases and Information Systems, Ulm University, 89081 Ulm, Germany"},{"name":"Department of Clinical Psychology and Psychotherapy, Ulm University, 89081 Ulm, Germany"},{"name":"Institute of Clinical Epidemiology and Biometry, University of W\u00fcrzburg, 97070 W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2536-4153","authenticated-orcid":false,"given":"Manfred","family":"Reichert","sequence":"additional","affiliation":[{"name":"Institute of Databases and Information Systems, Ulm University, 89081 Ulm, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1522-785X","authenticated-orcid":false,"given":"R\u00fcdiger","family":"Pryss","sequence":"additional","affiliation":[{"name":"Institute of Clinical Epidemiology and Biometry, University of W\u00fcrzburg, 97070 W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,12]]},"reference":[{"key":"ref_1","unstructured":"Mehl, M.R., and Conner, T.S. 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