biostudies-literatureVan Rhoon LIrish Research CouncilNational University of Ireland, Galway2055207620914427https://www.ebi.ac.uk/biostudies/studies/S-EPMC7093696biostudies-literatureUnknown6<h4>Objectives</h4>Our aim was to conduct a systematic review to determine which technology-driven diabetes prevention interventions were effective in producing clinically significant weight loss, and to identify the behaviour change techniques and digital features frequently used in effective interventions.<h4>Methods</h4>We searched five databases (CINAHL, EMBASE, MEDLINE, PsychINFO, and Pubmed) from inception to September 2018 and reviewed 19 experimental and non-experimental studies of 21 technology-driven diet plus physical activity interventions for adults (≥18 years) at risk of developing type 2 diabetes. Behaviour change techniques were coded using the BCT taxonomy v1, and digital features were identified via thematic analysis of intervention descriptions.<h4>Results</h4>Sixty-threDigital healthA systematic review of the behaviour change techniques and digital features in technology-driven type 2 diabetes prevention interventions.PMC7093696Hardiman ScholarshipGOIPG/2019/1355Byrne MMorrissey EMcSharry JMurphy JVan Rhoon LfalseA systematic review of the behaviour change techniques and digital features in technology-driven type 2 diabetes prevention interventions.<h4>Objectives</h4>Our aim was to conduct a systematic review to determine which technology-driven diabetes prevention interventions were effective in producing clinically significant weight loss, and to identify the behaviour change techniques and digital features frequently used in effective interventions.<h4>Methods</h4>We searched five databases (CINAHL, EMBASE, MEDLINE, PsychINFO, and Pubmed) from inception to September 2018 and reviewed 19 experimental and non-experimental studies of 21 technology-driven diet plus physical activity interventions for adults (≥18 years) at risk of developing type 2 diabetes. Behaviour change techniques were coded using the BCT taxonomy v1, and digital features were identified via thematic analysis of intervention descriptions.<h4>Results</h4>Sixty-thre2020-01-01T00:00:00Z2020 Jan-Dec2025-04-18T20:09:54.107Z2020-05-22T16:31:45ZS-EPMC70936963226983010.1177/2055207620914427