2020
DOI: 10.2196/preprints.20037
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Barriers to and facilitators for using nutrition apps: a scoping review and conceptual framework (Preprint)

Abstract: BACKGROUND Nutrition apps are a prototypical mobile health (mHealth) technology supporting healthy eating behavior that are seen as promising tools for health promotion by policy makers. Although nutrition apps are increasingly popular, wide-spread adoption is yet to be achieved. Hence, profound knowledge regarding factors motivating and hindering (long-term) nutrition app use is crucial for developing design guidelines aiming at supporting uptake and prolonged use of nutrition apps. … Show more

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Cited by 4 publications
(5 citation statements)
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“…A protocol was prepared and published on the Open Science Framework [ 27 ] prior to completion of data extraction. This review reports on the generation of an overview of the evidence.…”
Section: Methodsmentioning
confidence: 99%
“…A protocol was prepared and published on the Open Science Framework [ 27 ] prior to completion of data extraction. This review reports on the generation of an overview of the evidence.…”
Section: Methodsmentioning
confidence: 99%
“…Similarly, smartphone-based dietary assessment tools may differentially impact participants' willingness to take part in research and their willingness and ability to reliably record food intake. For instance, this might impact conclusions about frequency and timing of eating episodes as well as the amount of energy consumed per day (33,34). A previous review has already outlined potential differences in willingness to use food tracking apps based on the design of features, such as the food database (34).…”
Section: Features To Collect Dietary Datamentioning
confidence: 99%
“…For instance, this might impact conclusions about frequency and timing of eating episodes as well as the amount of energy consumed per day (33,34). A previous review has already outlined potential differences in willingness to use food tracking apps based on the design of features, such as the food database (34). For instance, if the food database is too extensive, searching for the correct food item might be too burdensome.…”
Section: Features To Collect Dietary Datamentioning
confidence: 99%
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