Can stand-alone computer-based interventions reduce alcohol consumption?

1. Can stand-alone computer-based interventions reduce alcohol consumption? Zarnie Khadjesari (PhD student) Elizabeth Murray (Director e-Health Unit) e-Health Unit, University College London Christine Godfrey (Head of Department) Catherine Hewitt (Research Fellow) Dept. Health Sciences, University of York Suzanne Hartley (Senior Trial Coordinator) CTRU, University of Leeds

2. Background • Alcohol misuse is a major public health concern • Gap between need and access • Internet interventions • Convenient, confidential, and comparatively low cost • Scalability and personalised approach • Recent reviews • Elliot 2008 (computer-based interventions for college drinkers) • Bewick 2008 (Internet interventions) • Riper 2009 (personalised feedback interventions – any modality)

3. Why conduct this review? • All designs of computer-based intervention • All computer-based (on- and off-line) • All adult populations • Meta-analysis

4. Aim • To determine the effectiveness of computer-based interventions aimed at reducing alcohol consumption • Computer-based interventions compared with either: • Minimally active comparator (e.g. assessment-only, information-only website) • Active comparator (e.g. face-to-face motivational interview)

5. Inclusion criteria • Study design: RCT • Population: Adults (excl. dependent drinkers) • Intervention: • Computer-based interventions aimed at reducing alcohol intake • Definition: behavioural interventions, adapted for computer • Stand-alone: no expert facilitation • Outcome: Alcohol consumption • Grams per week • Frequency of binges / week

6. 10 databases searched 8,084 references Full paper ordered 154 Excluded 7,930 Included publications 36 Excluded 119 Individual studies 23 Search results Databases searched from inception – end 2008 Medline Embase Web of Science Cochrane Library PsycINFO Cinahl ERIC ISI Proceedings IBSS Index to Theses

7. Characteristics of included studies (1)

8. Characteristics of included studies (2)

9. Characteristics of included studies (3)

10. Results Comparison: minimally active comparator (n=2,425) Outcome: g/wk

11. Sub-group analysis - population

12. Results Comparison: minimally active comparator (n=848) Outcome: binge frequency / wk

13. Results Comparison: active comparator (n=457) Outcome: g/wk

14. Further analyses • Skewed data • Baseline risk • Loss to follow-up

15. Summary of findings • Computer-based interventions appear: • more effective than minimally active comparator • as effective as alternative treatment approaches • Findings support continued development and evaluation of computer-based interventions for reducing alcohol intake

16. Limitations of this review • Restricted to stand-alone interventions • Different types of computer-based interventions • Two measures of alcohol consumption • Mediators of drinking outcomes, s/a motivation, normative perceptions. • Dose response

17. Gaps in the literature • Few comparisons with conventional approaches • Few studies in non-student adult populations • Few studies outside the US • Few studies measuring long-term effectiveness

18. Thank you for listeningQuestions, comments, suggestions?