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Nevertheless, especially when self\u2010reports are used during the data collection process, there are difficulties in balancing data quality and the burden placed on the subject. In this paper, we address this problem for a specific EMA setting that aims to submit a demanding task to subjects at high\/low values of a self\u2010reported variable. We adopt a dynamic approach inspired by control chart methods and design optimization techniques to obtain an EMA triggering mechanism for data collection that considers both the individual variability of the self\u2010reported variable and of the adherence. We test the algorithm in both a simulation setting and with real, large\u2010scale data from a tinnitus longitudinal study. A Wilcoxon signed rank test shows that the algorithm tends to have both a higher <jats:italic>F<\/jats:italic><jats:sub>1<\/jats:sub> score and utility than a random schedule and a rule\u2010based algorithm with static thresholds, which are the current state\u2010of\u2010the\u2010art approaches. In conclusion, the algorithm is proven effective in balancing data quality and the burden placed on the participants, especially in studies where data collection is impacted by\u00a0adherence.<\/jats:p>","DOI":"10.1002\/bimj.202200203","type":"journal-article","created":{"date-parts":[[2023,4,22]],"date-time":"2023-04-22T03:05:38Z","timestamp":1682132738000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Adaptive data collection for intraindividual studies affected by adherence"],"prefix":"10.1002","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4677-4661","authenticated-orcid":false,"given":"Greta","family":"Monacelli","sequence":"first","affiliation":[{"name":"School of Computing Dublin City University Dublin Ireland"},{"name":"Insight SFI Research Centre for Data Analytics Dublin Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lili","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computing Dublin City University Dublin Ireland"},{"name":"Insight SFI Research Centre for Data Analytics Dublin Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Winfried","family":"Schlee","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Psychotherapy University of Regensburg Regensburg Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Berthold","family":"Langguth","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Psychotherapy University of Regensburg Regensburg Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom\u00e1s E.","family":"Ward","sequence":"additional","affiliation":[{"name":"School of Computing Dublin City University Dublin Ireland"},{"name":"Insight SFI Research Centre for Data Analytics Dublin Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5668-7046","authenticated-orcid":false,"given":"Thomas B.","family":"Murphy","sequence":"additional","affiliation":[{"name":"Insight SFI Research Centre for Data Analytics Dublin Ireland"},{"name":"School of Mathematics and Statistics University College Dublin Dublin Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,4,21]]},"reference":[{"key":"e_1_2_8_2_1","first-page":"53","volume-title":"Progress in brain research","author":"Ahn W. 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