2020
DOI: 10.2196/16480
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Electronic Data Capture Versus Conventional Data Collection Methods in Clinical Pain Studies: Systematic Review and Meta-Analysis

Abstract: Background The most commonly used means to assess pain is by patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil, telephone, or in-person methods, which may limit the validity of the collected data. Electronic data capture methods represent a potential way to validly, reliably, and feasibly collect pain-related data from patients in both clinical and research settings. Objective The aim of this study was to… Show more

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Cited by 29 publications
(18 citation statements)
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References 79 publications
(93 reference statements)
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“…Erroneous data entry (i.e., a source of measurement error) and missing data are common sources of bias in RCT study designs [ 15 ]. These are more likely to occur when using traditional data collection methods, compared to electronic data capturing tools [ 16 , 17 ]. Additionally, even though researchers can use analytic approaches to deal with missing data, preventing missing data at data collection phase is a more favorable approach because the analytical approaches rely on uncheckable assumptions [ 15 ].…”
Section: Introductionmentioning
confidence: 99%
“…Erroneous data entry (i.e., a source of measurement error) and missing data are common sources of bias in RCT study designs [ 15 ]. These are more likely to occur when using traditional data collection methods, compared to electronic data capturing tools [ 16 , 17 ]. Additionally, even though researchers can use analytic approaches to deal with missing data, preventing missing data at data collection phase is a more favorable approach because the analytical approaches rely on uncheckable assumptions [ 15 ].…”
Section: Introductionmentioning
confidence: 99%
“…ICTs are becoming widely used tools for research and clinical data collection ( 42 ). They allow incorporating social media, biosensing, and artificial intelligence in the collection and analysis of health data ( 43 ), thus increasing efficiency in the accumulation and analysis of large datasets for digital phenotyping ( 44 ) in fields as diverse as behavioral neuroscience and computational sociology.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, the use of electronic methods for painrelated data collection in musculoskeletal pain conditions, including FM, has increased (see review by Jibb et al, 2020). For example, García-Palacios et al (2014) used an ED evaluating pain intensity, fatigue intensity and mood, and found more accurate and complete ratings of the ED compared to a paper diary, and utility of the ED for the evaluation of FM, even in patients with low familiarity with technology.…”
Section: Introductionmentioning
confidence: 99%