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Adaptive E-Learning to Improve Dietary Behaviour: A Systematic Review and Cost-Effectiveness Analysis

Health Technology Assessment, No. 15.37

J Harris, L Felix, A Miners, E Murray, S Michie, E Ferguson, C Free, K Lock, J Landon, and P Edwards.

Author Information

J Harris,1 L Felix,1 A Miners,2 E Murray,3 S Michie,4 E Ferguson,1 C Free,1 K Lock,2 J Landon,5 and P Edwards1,*.

1 Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
2 Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK
3 Research Department of Primary Care and Population Health, University College London, London, UK
4 Research Department of Clinical, Educational & Health Psychology, University College London, London, UK
5 National Heart Forum, London, UK
* Corresponding author
Southampton (UK): NIHR Journals Library; 2011 Oct.
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Abstract

Background:

UK public health policy strongly advocates dietary change for the improvement of population health and emphasises the importance of individual empowerment to improve health. A new and evolving area in the promotion of dietary behavioural change is ‘e-learning’, the use of interactive electronic media to facilitate teaching and learning on a range of issues including health. The high level of accessibility, combined with emerging advances in computer processing power, data transmission and data storage, makes interactive e-learning a potentially powerful and cost-effective medium for improving dietary behaviour.

Objective:

This review aims to assess the effectiveness and cost-effectiveness of adaptive e-learning interventions for dietary behaviour change, and also to explore potential psychological mechanisms of action and components of effective interventions.

Data sources:

Electronic bibliographic databases (Cumulative Index to Nursing and Allied Health Literature, The Cochrane Library, Dissertation Abstracts, EMBASE, Education Resources Information Center, Global Health, Health Economic Evaluations Database, Health Management Information Consortium, MEDLINE, PsycINFO and Web of Science) were searched for the period January 1990 to November 2009. Reference lists of included studies and previous reviews were also screened; authors were contacted and trial registers were searched.

Review methods:

Studies were included if they were randomised controlled trials, involving participants aged ≥ 13 years, which evaluated the effectiveness of interactive software programs for improving dietary behaviour. Primary outcomes were measures of dietary behaviours, including estimated intakes or changes in intake of energy, nutrients, dietary fibre, foods or food groups. Secondary outcome measures were clinical outcomes such as anthropometry or blood biochemistry. Psychological mediators of dietary behaviour change were also investigated. Two review authors independently screened results and extracted data from included studies, with any discrepancies settled by a third author. Where studies reported the same outcome, the results were pooled using a random-effects model, with weighted mean differences (WMDs), and 95% confidence intervals (CIs) were calculated. Cost-effectiveness was assessed in two ways: through a systematic literature review and by building a de novo decision model to assess the cost-effectiveness of a ‘generic’ e-learning device compared with dietary advice delivered by a health-care professional.

Results:

A total of 36,379 titles were initially identified by the electronic searches, of which 43 studies were eligible for inclusion in the review. All e-learning interventions were delivered in high-income countries. The most commonly used behavioural change techniques reported to have been used were goal setting; feedback on performance; information on consequences of behaviour in general; barrier identification/problem solving; prompting self-monitoring of behaviour; and instruction on how to perform the behaviour. There was substantial heterogeneity in the estimates of effect. E-learning interventions were associated with a WMD of +0.24 (95% CI 0.04 to 0.44) servings of fruit and vegetables per day; −0.78 g (95% CI −2.5 g to 0.95 g) total fat consumed per day; −0.24 g (95% CI −1.44 g to 0.96 g) saturated fat intake per day; −1.4% (95% CI −2.5% to −0.3%) of total energy consumed from fat per day; +1.45 g (95% CI −0.02 g to 2.92 g) dietary fibre per day; +4 kcal (95% CI −85 kcal to 93 kcal) daily energy intake; −0.1 kg/m2 (95% CI −0.7 kg/m2 to 0.4 kg/m2) change in body mass index. The base-case results from the E-Learning Economic Evaluation Model suggested that the incremental cost-effectiveness ratio was approximately £102,112 per quality-adjusted life-year (QALY). Expected value of perfect information (EVPI) analysis showed that although the individual-level EVPI was arguably negligible, the population-level value was between £37M and £170M at a willingness to pay of £20,000–30,000 per additional QALY.

Limitations:

The limitations of this review include potential reporting bias, incomplete retrieval of completed research studies and data extraction errors.

Conclusion:

The current clinical and economic evidence base suggests that e-learning devices designed to promote dietary behaviour change will not produce clinically significant changes in dietary behaviour and are at least as expensive as other individual behaviour change interventions.

Future work recommendations:

Despite the relatively high EVPI results from the cost-effectiveness modelling, further clinical trials of individual e-learning interventions should not be undertaken until theoretically informed work that addresses the question of which characteristics of the target population, target behaviour, content and delivery of the intervention are likely to lead to positive results, is completed.

Funding:

The National Institute for Health Research Health Technology Assessment programme.

Suggested citation:

Harris J, Felix L, Miners A, Murray E, Michie S, Ferguson E, et al. Adaptive e-learning to improve dietary behaviour: a systematic review and cost-effectiveness analysis. Health Technol Assess 2011;15(37).

Declared competing interests of authors: none

The research reported in this issue of the journal was commissioned by the HTA programme as project number 08/57/02. The contractual start date was in April 2009. The draft report began editorial review in October 2010 and was accepted for publication in January 2011. As the funder, by devising a commissioning brief, the HTA programme specified the research question and study design. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HTA editors and publisher have tried to ensure the accuracy of the authors' report and would like to thank the referees for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this report.

The views expressed in this publication are those of the authors and not necessarily those of the HTA programme or the Department of Health.

© 2011, Crown Copyright.

Included under terms of UK Non-commercial Government License.

PMID: 22030014

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