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. 2019 Feb 5:5:2055207619826685.
doi: 10.1177/2055207619826685. eCollection 2019 Jan-Dec.

A systematic review of tailored eHealth interventions for weight loss

Affiliations

A systematic review of tailored eHealth interventions for weight loss

Kathleen Ryan et al. Digit Health. .

Abstract

Objective: The aim of this study is to review the evidence for tailored eHealth weight-loss interventions, describing in detail: 1. how tailoring was implemented in these studies and 2. whether these tailored approaches were effective in producing weight loss compared with generic or inactive controls.

Methods: A systematic review was carried out. Five databases were searched up until 15 March, 2018, including: EBSCO, Science Direct, Pubmed, EMBASE and Web of Science, using combinations of the concepts 'tailoring', 'eHealth' and 'overweight'.

Results: Eight articles relating to six interventions were accepted. Tailoring was carried out in a number of ways, based on, for example, anthropometric data, health-related behaviours (e.g. dietary intake, physical activity), goals (e.g. weight goal), theoretical determinants (e.g. confidence/willingness to change behaviours), psychosocial factors (e.g. social support) and participant location. Systems acquired data using strategies that ranged from online questionnaire administration, to the dynamic gathering of data from web-based diaries, websites, mobile applications and SMS messaging. Tailored interventions were more effective in supporting weight loss than generic or waitlist controls in four of the six articles. Effect sizes were very small to moderate, with evidence for fluctuations in effect sizes and differences of effect between tailoring and non-tailoring interventions, and between tailoring types, over time.

Conclusions: We contribute an enhanced understanding of the variety of methods used for the tailoring of eHealth interventions for weight loss and propose a model for categorising tailoring approaches.

Keywords: Tailoring; eHealth; engagement; health behaviour change; obesity; personalisation; systematic review; weight loss.

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Figures

Figure 1.
Figure 1.
PRISMA flow diagram.
Figure 2.
Figure 2.
Risk of bias graph for quantitative articles (n = 6). (a) Summary of included articles using Cochrane’s Risk of Bias tool. (b) Summary of risk of bias across studies.
Figure 3.
Figure 3.
Model of tailoring depth.

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