Drug and Alcohol Findings home page in a new window EFFECTIVENESS BANK BULLETIN 8 May 2012

The entries below are our accounts of documents collected by Drug and Alcohol Findings as relevant to improving outcomes from drug or alcohol interventions in the UK. The original documents were not published by Findings; click on the Titles to obtain copies. Free reprints may also be available from the authors. If displayed, click prepared e-mail to adapt the pre-prepared e-mail message or compose your own message. The Summary is intended to convey the findings and views expressed in the document. Below may be a commentary from Drug and Alcohol Findings.


Contents

Dutch suite of web-based alcohol interventions

From overlapping teams of authors based in the Netherlands, all the studies in this bulletin concern a suite of web-based alcohol interventions developed for Dutch heavy drinking adults. At the lowest level of intervention intensity and problem severity is a 10-minute brief intervention for risky drinkers. Stepping up problem and intensity ranges is a four-step cognitive-behavioural intervention (this entry is repeated from an earlier bulletin). At the apex is the only one to feature interaction with a therapist, in this case via text-chat over seven sessions, intended to extend treatment to more problem drinkers than attend face-to-face therapy. The Dutch team also reviewed the evidence from their own and other studies, and devised a mathematical model which simulates the health gains and costs of incorporating these new technologies in a health care system. Applied to the Netherlands and using the tested interventions, it predicted a more cost-effective alcohol health care system. Together this work has comprehensively mapped and evaluated internet alcohol intervention possibilities in a UK-like context, leading to the conviction that while these cannot replace therapists, they can extend their reach and curb drinking further down the severity/complexity range, at the level conventionally addressed by brief interventions in general medical care.

10-minute web alcohol check-up and advice leads 1000s to cut back ...

CBT programme for harmful drinkers passes lab and real-world tests ...

Too soon to get rid of the therapists ...

Internet self-help low-cost way to extend public health impact of alcohol interventions ...

On-line alcohol interventions would improve health care value for money ...


Curbing alcohol use in male adults through computer generated personalized advice: randomized controlled trial.

Boon B., Risselada A., Huiberts A. et al.
Journal of Medical Internet Research: 2011, 13(2), e43.
Unable to obtain a copy by clicking title? Try asking the author for a reprint by adapting this prepared e-mail or by writing to Dr Boon at bboon@trimbos.nl. You could also try this alternative source.

Spending just ten minutes each on a drinking feedback and advice web site is leading over 2000 heavy drinking Dutch men a year to reduce to safer levels was the implication of this randomised trial from the Netherlands.

Summary Face-to-face interventions are limited by the shortage of suitable professionals, and heavy drinkers may be reluctant to discuss their drinking, meaning most remain untreated. In contrast, on-line interventions need require no therapist time and users can engage in them whenever they wish and in the privacy of their homes without fear of stigmatisation. This study aimed to examine the effect of DrinkTest, an on-line intervention targeting heavy drinking adults in the Netherlands by offering personalised feedback Personalised feedback is assumed to be more effective than general information because the information is perceived as more personal and therefore more relevant, meaning the recipient pays more attention to the key message. about each user's drinking pattern.

Such interventions have proven a feasible way to reach heavy drinkers and are generally well received. However, beyond student samples, results are not yet conclusive. An analysis synthesising the results of on-line alcohol and tobacco interventions included only three studies of drinking among general adult populations. Another research synthesis focused on drinking reported an overall medium effect size A standard way of expressing the magnitude of a difference (eg, between outcomes in control and intervention groups) applicable to most quantitative data. Enables different measures taken in different studies to be compared or (in meta-analyses) combined. Based on expressing the difference in the average outcomes between control and experimental groups as a proportion of how much the outcome varies across both groups. The most common statistic used to quantify this difference is called Cohen's d. Conventionally this is considered to indicate a small effect when no greater than 0.2, a medium effect when around 0.5, and a large effect when at least 0.8. for nine randomised controlled trials, including the present study, but most of the on-line interventions were fairly time consuming, ranging from one 90-minute session to a 10-week programme, and some required therapist involvement.

Developed by the Netherlands Institute for Health Promotion and Disease Prevention, DrinkTest is delivered in a single 10-minute session with no therapist involvement. It asks the user about their usual weekly alcohol intake and their intentions to change their drinking. Based on this it offers feedback on their intake and associated health risks compared to other Dutch residents of the same age and sex. Users who score as heavy drinkers (by design, all did in the current study) are further quizzed about their drinking occasions and patterns, how confident they feel in their ability to change, and their attitudes and intentions with regard to reducing alcohol intake. Based on their answers, respondents receive personalised feedback on how to reduce alcohol intake in their specific situation, which in the study they could print and take home.

An initial study found DrinkTest worked for women but not men, leading to the revision tailored to men tested by the featured study. Participants were recruited via an on-line screening questionnaire sent to around 9000 men on two survey panels and through national newspaper adverts. In all 887 respondents whose drinking exceeded Dutch guidelines Men who consumed more than 200gm of alcohol per week and/or more than 50gm on a single occasion on at least one day per week. but had not recently been treated for this were invited to take part in the study. Of these 450 agreed and were randomly allocated to the DrinkTest intervention or (the control A group of people, households, organisations, communities or other units who do not participate in the intervention(s) being evaluated. Instead, they receive no intervention or none relevant to the outcomes being assessed, carry on as usual, or receive an alternative intervention (for the latter the term comparison group may be preferable). Outcome measures taken from the controls form the benchmark against which changes in the intervention group(s) are compared to determine whether the intervention had an impact and whether this is statistically significant. Comparability between control and intervention groups is essential. Normally this is best achieved by randomly allocating research participants to the different groups. Alternatives include sequentially selecting participants for one then the other group(s), or deliberately selecting similar set of participants for each group. group) to read and if they wished take home a standard brochure on the biological effects of alcohol and healthy and unhealthy drinking patterns. Rather than the study's true objective, participants were told they were in a study of healthy lifestyle education and had happened to be allocated to the alcohol topic. Both the on-line intervention and reading the brochure were completed at research offices rather than at home.

On average the sample was 40 years of age and drank about 315gm alcohol a week or 39 UK units, and most were employed and well educated.

Main findings

% drinking above Dutch low-risk guidelines

Of primary interest was the proportion of men who cut their drinking to below Dutch guidelines for low-risk drinking. One month after working through DrinkTest, 42% had compared to 31% who had read the brochure. The proportions equated to one person becoming a 'safe' drinker for every nine allocated to DrinkTest. This difference remained statistically significant when another method was used to estimate the drinking of participants who did not complete the follow-ups and when the analysis was confined only to respondents.

Six months after the interventions, still more had become 'safe' drinkers, but the gap had shrunk to 46% v. 37% and now narrowly missed remaining statistically significant chart (this recalculates the figures to the proportions still drinking excessively). Assuming a real impact at six months, the difference equated to one person becoming a 'safe' drinker for every 12 allocated to DrinkTest.

Impacts of the interventions did not significantly differ for people of different ages, educational attainment, or average weekly drinking.

The authors' conclusions

At least in the short-term, computer-based personalised feedback led more male heavy drinkers to cut their intake to safer levels than a standard alcohol information brochure. These findings derive from a study with a high follow-up rate and were robust under alternative analytic methods. The initial impact was comparable to that found after a more intensive on-line, four-step cognitive behavioural intervention also directed at the Dutch general adult population.

The intervention web site attracts about 90,000 men a year of whom 70% score as heavy drinkers. Four of ten complete the test and presumably receive tailored feedback. To estimate the potential impact, it is assumed that this usage is maintained and that the impact at six months in the study is a valid indicator of the impact in the home setting. Then each year 2117 men would cut their alcohol intake for at least six months as a consequence of spending 10 minutes on DrinkTest. In turn this suggests that offering personalised feedback through highly accessible web sites can efficiently and economically contribute to generating health gains at the population level. This suggestion is reinforced by a study modelling the potential impact in the Netherlands of alcohol eHealth interventions such as DrinkTest. Moreover, DrinkTest's impact was consistent across different types of heavy drinkers, again a finding which replicates that for another Dutch on-line alcohol intervention.

Of note is that even in the control condition many participants curbed their drinking. High levels of motivation among those who agreed to participate seems an unlikely explanation as they thought they were engaging in a lifestyle education study, not one specifically to do with drinking. Perhaps repeated questions about drinking at different time points had an impact. If so, the on-line intervention still exerted an extra impact.

While effectiveness has been demonstrated in 'laboratory' conditions, it remains to be seen whether these results hold up when the intervention is (as normally it would be) engaged in at home, where web site users might not complete it or pay as much attention to its advice. A hopeful sign is that a synthesis of similar studies did not find on-line alcohol interventions any less effective when undertaken at home as opposed to other locations. Moreover, any such effect could be expected to also increase the impact of reading the brochure.


Findings logo commentary A rigorous analysis with little loss to follow-up gives confidence that the outcomes represent a valid extra impact on the participants recruited to the study of the on-line intervention relative to reading a brochure, in the context of a study which virtually ensured full attention to both. The main questions ( below) are over whether this impact would be replicated among the general run of heavy drinkers accessing the service in the normal way at home.

As acknowledged by the researchers, the home environment differs from the soundproofed-room research setting where participants sat with no distractions and only one task before them – to complete the on-line intervention or read the brochure, paying attention in expectation that their views would be sought as part of the study they had committed to. It is reasonable, as the authors point out, to suggest that if this magnified the impact of the interventions, it would have done so for both, yet still the on-line process led to greater drinking reductions. But it is also the case that if the on-line process had an advantage, this would itself probably have been magnified. Already in the study the advantage is quite small and possibly fleeting. In normal circumstances, it might be still less convincing.

A second concern is that a direct approach to 9000 people plus national newspaper ads netted just 413 who completed the one-month follow-up. Moreover, presumably they joined the study not because they were concerned or curious about their drinking – why people might visit the DrinkTest site or read a brochure – but because they wanted to help with a lifestyle education study. Whether how they reacted to the interventions represents how the general heavy-drinking adult Dutch population would react is an open question. It is, of course, entirely open in respect of women. They reacted well to the previous version of the on-line intervention, but it cannot be presumed they will still react well to the new male-adjusted version; if men reacted differently to the two versions, so too may women.

None of this is to seriously cast doubt on the validity of the impacts on the people who did participate in the study, or to deny the probability that others interested enough to access the intervention would respond similarly. However, it could be that rather than a resource accessed widely enough to have an impact on public health across a country, internet-based alcohol applications become one more niche option attracting and/or having a beneficial impact on a rather different population to conventional care.

Some of the limitations of the featured study broadly applied also to the evaluation of a Canadian version of a very similar 10-minute web-based intervention. The main exception was that this did test the intervention in the conditions in which it would normally be used: without face-to-face guidance and in the user's own home, or wherever else they chose. This too found initially promising results, but by 12 months later drinkers allocated to the intervention were drinking the same amount as those who had not been, and the significant extra drinking reductions seen earlier had disappeared. As well as confirming the fleeting nature of these reductions, that study offered an alternative explanation for the early findings: that intervention participants, having been alerted and sensitised to their excessive drinking, then under-reported it, creating the illusion that they had but back more than the control group.

The featured intervention was among those whose impacts were simulated for the Netherlands, the results of which suggested that national health would improve and/or intervention costs be reduced if on-line brief interventions and therapy were added to or replaced conventional alcohol-related health care. The other interventions were:
DrinkingLess, an on-line four-step cognitive behavioural intervention involving exploring one's alcohol use, setting goals, changing behaviour, and maintenance of behaviour change;
OnlineTreatment, an on-line therapist-led treatment for problem drinking; communication between participant and therapist is conducted over the internet in seven chat sessions of 45 minutes each covering setting goals, self-control techniques, monitoring, recognising relapse-precipitating situations, and relapse prevention techniques.

Since these three eHealth interventions increase in intensity, it was suggested that they could be used in a stepped-care framework, starting with the least intensive intervention, the DrinkTest, and if needed moving up to the more intensive levels of DrinkingLess and OnlineTreatment.

See other Findings analyses for a review of computer-delivered self-help interventions for drinking and smoking and a review focused on drinking. Both analyses include further commentary on the role of computer delivery and on UK findings.

Thanks for their comments on this entry in draft to John Cunningham of the Centre for Addiction and Mental Health in Toronto in Canada. Commentators bear no responsibility for the text including the interpretations and any remaining errors.

Last revised 05 May 2012

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REVIEW 2011 Effectiveness of e-self-help interventions for curbing adult problem drinking: a meta-analysis





Translating effective web-based self-help for problem drinking into the real world.

Riper H., Kramer J., Conijn B. et al.
Alcoholism: Clinical and Experimental Research: 2009, 33(8), p. 1401–1408.
Unable to obtain a copy by clicking title? Try asking the author for a reprint by adapting this prepared e-mail or by writing to Dr Riper at hriper@trimbos.nl. You could also try this alternative source.

Combining a randomised trial with a 'real-world' test, studies of the Dutch Drinking Less programme have gone further than any others to establish the beneficial impacts of web-based alcohol self-help interventions.

Summary The study was a 'real-world' test of a promising Dutch internet-based self-help intervention for problem drinking. A previous randomised trial employing the methodological safeguards possible in tightly controlled research (particularly the recruitment of a comparison group not given access to the intervention) had established that the intervention reduced drinking. At issue in the featured study was whether similar drinking reductions would be seen when the intervention was made freely available to the general public. If they were, then the assumption could be made that these too were caused by having access to the intervention.

Home page of Drinking Less web site

Drinking Less is an on-line, interactive programme with no personal therapist input. Aimed at risky drinkers among the general adult population, the intervention is based on principles derived from motivational interviewing, cognitive-behavioural therapies and self-control training. Its home page ( right) offers links to alcohol-related information, treatment services, a discussion forum, and the Drinking Less self-help programme, the core of the intervention. Over a recommended six weeks (though this is entirely up to the user) the programme guides visitors in preparing to change Involving assessing the severity of their drinking problems, the positive and negative consequences, and their motivation to change. their drinking, setting goals , implementing change, and finally sustaining it, preferably by drinking within recommended limits.

The earlier trial had found that six months later, at least 17% of adult problem drinkers randomly allocated to this intervention had reduced their drinking to within Dutch guidelines, compared to just 5% allocated to an on-line alcohol education brochure. Before the study, both groups had averaged about 55 UK units 440g alcohol. a week. At follow-up, the Drinking Less group had cut consumption to about 36 UK units 287g alcohol. a week, but the brochure group had barely changed.

The featured study monitored what happened when over 10 months spanning 2007 and 2008 the web site was advertised to the Dutch public. During this time round 27,500 The featured report says: "An average of 2,750 unique visitors accessed the website's homepage per month (with the notable exception of January 2008 when nearly 6,000 visited the site, probably as a result of New Year's resolutions)." people visited the site, of whom 1625 signed up for the self-help programme, accessing it on average 23 times. Typically they were well educated, employed, middle-aged men. On average they drank about 50 UK units 396g alcohol. a week, and nearly all who completed the on-line AUDIT screening questionnaire scored in a range indicative of alcohol abuse or dependence.

During the first seven of the 10 months, 378 of site visitors who signed up to the Drinking Less programme also agreed to participate in research to assess its impact. On average they drank roughly the same amount (95% exceeded Dutch guidelines) as all 1625 who signed up and were also similar in age, sex, employment, and motivation to change. Despite some statistically significant differences, they were also broadly similar to participants in the earlier randomised trial. Over 8 in 10 had never received professional help for their drinking. A few weeks later a survey To which about half the baseline sample responded. suggested that after signing up, nearly 9 in 10 went on to use the programme, though generally only a few times.

Of the 378 in the baseline sample, 153 responded to an on-line follow-up survey six months later. Before signing up to the programme, just 4% had confined their drinking within Dutch guidelines; Excessive or hazardous drinking is defined as drinking more than 210g (men) or 140g (women) of alcohol in the past week and/or drinking at least 60g (men) or 40g (women) on an average of one or more days week over the previous three months. six month later, 39% did so. They had also nearly halved their average consumption from 50 UK units 400g alcohol. to 27. 218g alcohol. On the 'fail-safe' assumption that the intervention had no impact on people who were not followed up, still the drinking reductions were statistically significant; from 5%, the proportion drinking within guidelines rose to 19%, and consumption fell from 51 UK units 409g alcohol. to 42. 335g alcohol.

Next the analysts compared these results By design, everyone in the randomised trial had exceeded Dutch drinking guidelines, so the comparison excluded the few people in the featured study who did not also exceed the guidelines. with those from the six-month follow-up in the randomised trial. Based only on respondents to the follow-up surveys, and adjusting for differences between the samples, in the 'real-world' test over twice as many (unadjusted figures 36% v. 19%) people moved to drinking within Dutch guidelines. When the assumption was made that in both trials the intervention had no impact on people not followed up, the figures still favoured the 'real-world' test (15% v. 10%), but the difference was no longer statistically significant.

The researchers concluded that the featured study had shown that the benefits established by the randomised controlled trial would be sustained when the intervention was made routinely and generally available to the public. The expected throughput of 3000 Drinking Less programme users a year would amount to nearly 3% of the country's problem drinkers who would otherwise not have received professional help. Probably because they require the drinker to take the initiative and visit the site, such interventions reach people who, compared to the totality of problem drinkers, are more likely to be women, employed, highly educated, and motivated to change their drinking. Given its low cost per user, this type of intervention seems to have a worthwhile place in a public health approach to reducing alcohol-related problems.


Findings logo commentary Though only a minority of site visitors may sign up for web-based alcohol programmes, nevertheless the numbers engaged can be very large, and the risk-reductions seem of the order typical in studies of brief advice to drinkers identified in health care settings. In these settings screening programmes typically identify people who are not actually seeking help for drinking problems – 'pushing' them towards intervention and change – while web sites 'pull' in people already curious or concerned about their drinking. As such these two gateways can play complementary roles in improving public health and offering change opportunities to people who would not present to alcohol treatment services. However, in Britain and elsewhere, both tactics reach only small fractions of the population who drinking excessively, leaving the bulk of the public health work to be done by interventions which drinkers generally cannot avoid and do not have seek out, such as price increases and availability restrictions.

With its combination of a randomised trial and a 'real-world' test, the featured research programme has gone further than any other in establishing the beneficial impacts of web-based alcohol interventions. However, largely because many site users do not complete research surveys, it remains impossible to be sure that the results seen in such studies will be replicated across the entire usership of the sites. Details below.

Strengths and limitations of the featured study

The featured study's combination of a randomised trial with all its methodological safeguards, and a 'real-world' trial approximating normal conditions, affords what seems to be the best indication to date of the contribution web-based self-help interventions could make to reducing heavy drinking and associated health risks. However, its twin pillars are weakened by the fact that many people either did not join the studies or did not supply follow-up data; those who did may not have been typical of all the people who might access such sites. In the randomised trial, 40% of the baseline sample did not complete the six-month follow-up survey, and in the featured study, nearly 60%. Though on the measures taken by the study the respondents generally seemed typical of the baseline sample, clearly something was sufficiently different to cause them to respond while the others did not. In both studies this problem was catered for by assuming that non-responders were also non-changers. Though this almost certainly underestimated the impact of the intervention, still in both there remained significant and worthwhile improvements.

What could not be catered for in either study was the degree to which people who join such studies differ from the much greater number who would use the web sites, but decline participation in research. This problem was especially apparent in the featured study, in which it seems that around 6% of site visitors signed up for the self-help programme. Of these, perhaps a third or slightly more Assuming sign-ups were evenly spread, each month 1625/10 signed up, amounting over the seven months of the recruitment period to 1138 people. Of these, 378 or 33% agreed to participate in the research. However, we know that site visits and presumably sign-ups were not evenly spread. Site visits were unusually numerous in the following January, meaning that the average sign-up rate was probably lower during the seven-month recruitment period; in turn this would mean that the recruitment rate was greater than the estimate of 33%. of the people who signed up for the programme during the relevant period also agreed to participate in the research. In some important ways (including amount drunk and motivation to change) they seemed similar to the bulk of programme sign-ups, though the researchers suspect they were more likely to have engaged with the programme.

Opening more doors to change for more people

A review of computer-based alcohol services for the general public has rehearsed the advantages: immediate, convenient access for people (the majority in developed nations) connected to the internet; consequently able to capitalise on what may be fleeting resolve; anonymous services sidestep the embarrassment or stigma which might deter help-seeking; such services are available to people unwilling or less able to talk about their problems to a stranger; generally they are free and entail no travel costs or lost income due to time off work; very low operating cost per user if widely accessed; easily updated. In consumption terms, the drinking problems of web site users are comparable to those of drinkers who seek treatment, yet few have received professional help, perhaps partly because their higher socioeconomic status and greater resources have enabled them to restrict the consequential damage. People who actually engage with web-based assessments of their drinking problems have more severe problems than those who just visit and leave. Including the randomised trial which paved the way for the featured study, the review found eight studies which evaluated the effectiveness of computer-based interventions for the general public. In all but one the users significantly improved on at least one of the alcohol-related measures recorded by the studies.

A particular role for alcohol self-help sites may be to offer an easy, quick and accessible way to for drinkers to actualise their desire to tackle their problems, especially when that desire is allied with the resources to implement and sustain improvements without face-to-face or comprehensive assistance. After conducting the Project MATCH trial, some of the world's leading alcohol treatment researchers argued that "access to treatment may be as important as the type of treatment available". The implication is that in cultures which accept 'treatment' as a route to resolving unhealthy and/or undesirable drinking, having convincing-looking and accessible 'treatment doors' to go through may be more important than what lies behind those doors, as long as this fulfils the expectations of the client or patient. This is likely to be especially the case for people who retain a stake in conventional society in the form of marriages, jobs, families, and a reputation to lose. These populations – the kind the featured study suggests are attracted to self-help alcohol therapy web sites – have more of the 'recovery capital' resources needed to themselves do most of the work in curbing their drinking.

The British Down Your Drink site

The best known British alcohol self-help web site is the Down Your Drink site run by a team based at University College London, an initiative originally funded by the Alcohol Education and Research Council and now by the Medical Research Council's National Prevention Research Initiative. In 2007 this was revised to offer set programmes from a one-hour brief intervention to several weeks, but also to generally give the user greater control over the use they made of the site. The approach remained based on principles and techniques derived from motivational interviewing and cognitive-behavioural therapies.

The previous version had been structured as six consecutive modules to be accessed weekly. An analysis of data provided by the first 10,000 people who registered at the site after piloting ended in September 2003 revealed that most were in their 30s and 40s, half were women, nearly two-thirds were married or living with a partner, just 4% were unemployed, and most reported occupations from higher socioeconomic strata. As an earlier study commented, site users were predominantly middle class, middle aged, white and European. Six in 10 either did not start the programme, or completed just the first week. About 17% completed the six weeks. Of these, 57% returned an outcome questionnaire. Compared to their pre-programme status, on average they were now at substantially lower risk, and functioning better and living much improved lives. The sample had been recruited over about 27 months, a registration rate of about 4500 a year. By way of comparison, in England during 2008/09, around 100,000 adults were treated Statistics from the National Alcohol Treatment Monitoring System (NATMS) 1st April 2008 – 31st March 2009. Department of Health and National Treatment Agency for Substance Misuse, 2010. for their alcohol problems at conventional services. User profile and site usage had been similar during the earlier pilot phase. Results from surveys sent to pilot programme completers indicated that three quarters had never previously sought help for their drinking.

Thanks for their comments on this entry in draft to Heleen Riper of the Trimbos Institute in the Netherlands. Commentators bear no responsibility for the text including the interpretations and any remaining errors.

Last revised 19 May 2010

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Top 10 most closely related documents on this site. For more try a subject or free text search

REVIEW 2011 Effectiveness of e-self-help interventions for curbing adult problem drinking: a meta-analysis

STUDY 2011 Modeling the cost-effectiveness of health care systems for alcohol use disorders: how implementation of eHealth interventions improves cost-effectiveness

STUDY 2011 Internet therapy versus internet self-help versus no treatment for problematic alcohol use: a randomized controlled trial

REVIEW 2012 Computer based alcohol interventions

HOT TOPIC 2015 Computerising therapy and advice increases access – but is effectiveness sacrificed?

STUDY 2011 ModerateDrinking.com and Moderation Management: outcomes of a randomized clinical trial with non-dependent problem drinkers

STUDY 2010 Personality-targeted interventions delay uptake of drinking and decrease risk of alcohol-related problems when delivered by teachers

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Internet therapy versus internet self-help versus no treatment for problematic alcohol use: a randomized controlled trial.

Blankers M., Koeter M.W.J., Schippers G.M.
Journal of Consulting and Clinical Psychology: 2011, 79(3), p. 330–341.
Unable to obtain a copy by clicking title? Try asking the author for a reprint by adapting this prepared e-mail or by writing to Dr Blankers at m.blankers@amc.uva.nl. You could also try this alternative source.

From the Netherlands, the first randomised controlled trial to evaluate internet-based therapy for problem drinking via text-chat conversations with a real therapist found this improved on an automated self-help option; on average alcohol intake was cut by nearly two-thirds.

Summary The burden of ill health due to drinking partly results from the fact that most problem drinkers do not enter treatment, even though there are effective approaches. In particular, those whose problem drinking is recent and/or relatively less severe receive little attention. This 'treatment gap' can be bridged by innovative treatment options which access and work with these currently under-served populations at the lowest possible cost. Internet-based interventions are one class of such innovations, seen as attractive to otherwise 'hidden' drinkers with relatively mild alcohol-related difficulties.

Rather than an automated process, the most intensively resourced of internet-based interventions employ therapists to offer individualised feedback and therapeutic programmes in interaction with the client. This may be via successive e-mails or texts, or in 'real time' through text-based 'chat' conversations, internet telephone , or videoconferencing. The featured study conducted in the Netherlands was the first randomised controlled trial to evaluate real-time, internet-based therapy via text-chat conversations, comparing it both to no intervention and to automated and briefer on-line self-help with no therapist contact. More so than phone or video contact, the chat medium promotes frank communication due to a high degree of perceived anonymity, enables participants to re-read and further benefit from the interaction between themselves and their therapists, and automatically documents the therapeutic process.

The interventions

Both interventions were text-based and derived from a Dutch treatment manual which embodied cognitive-behavioural therapy and motivational interviewing, the two most prominent 'talking' therapies for substance use problems.

The automated self-help program helps the user monitor their drinking, become aware of related thoughts and feelings, set drinking goals, and identify relapse-precipitating situations. Feedback is offered on their drinking-related contexts and inner states and their alcohol consumption, comparing the latter with their goal. To help reach this goal, the user is educated and trained in skills related to coping with craving, drinking lapses, peer pressure, and how to stay motivated in risky situations. Another strand in the intervention offers social support from other participants through an internet-based forum. Participants can access the service on demand; it is suggested they use it daily for at least four weeks, but few do so.

The therapist-led option uses similar but more extended cognitive-behavioural exercises offered over seven 40-minute text-based chat-therapy sessions, each preceded by a homework assignment. The successive themes are: introduction; pros and cons of drinking, how to monitor it and set goals; self-control; risky situations; craving and how feelings can influence drinking; lapse, relapse, and 'pro-lapse'; overall review. Therapists are psychologists from the collaborating substance abuse treatment centre, trained and experienced in delivering face-to-face cognitive-behavioural therapy for drinkers and further trained in internet-based delivery using chat conversations.

Visitors seeking to "reduce your alcohol intake or quit drinking" were recruited via the web site of Jellinek/Arkin, the collaborating substance abuse treatment centre. Interested visitors could complete a screening survey to determine their eligibility for the study, for which the main criteria were that they were adult drinkers living in the Netherlands who scored above the AUDIT questionnaire's threshold A score of 8. For the featured study this had to be exceeded. for risky drinking and on average drank over 140gm alcohol a week, but had not previously been treated for substance use problems, were not or had not been seriously ill in certain ways, A history of alcohol delirium or drug overdose, severe coronary or intestinal disease, schizophrenia, epilepsy, or suicidal tendencies in the last 12 months. and had not had used illegal drugs at significant levels. Such criteria correspond to those used to allocate patients to low-intensity outpatient treatment at the collaborating centre.

Eligible and consenting participants were randomly In a way which as far as possible engineered equivalence in sex ratios, AUDIT scores, and years of alcohol problems – variables potentially related to outcomes. allocated either to one of the two interventions or to a three-month waiting period, after which they could access the therapist-led intervention. This meant that for the first three months, offering the internet-based interventions could be compared against offering no intervention. A further follow-up at six months checked for any persisting effects and differences between the two active interventions. It was expected that the study sample would benefit most from the most intensive (ie, the therapist-led) intervention and least from being placed on the waiting list.

In 2008–2009 1720 people completed the screening questionnaire, of whom 832 were eligible for the study and 205 decided to participate and were randomly allocated to the three arms. Averaging 42 years of age, half were women and around 8 in 10 were employed, typically in white-collar jobs. AUDIT scores averaged nearly 20 20 is considered indicative of dependence. and they drank nearly every day, totalling about 450gm alcohol or 56 UK units, figures indicative of significant drink problems. They also scored as suffering from (relative to the general Dutch population) troubling psychological problems. Around 70% completed the three-month follow-up assessments and 60% those at six months.

Main findings

Weekly alcohol consumption in gm

All four main outcomes (weekly drinking amount, AUDIT score representing drink-related problems, and two measures of quality of life) were significantly affected by the interventions.

Detailed analyses showed that while at three months weekly drinking amounts had on average fallen across the board, the fall was (as expected) greatest among patients allocated to the therapist-led intervention (down on average from 466gm to 224gm), somewhat less among those allocated to the self-help option (from 436gm to 270gm), and least among those placed on the waiting list (472gm to 355gm) chart. For both interventions the falls were significantly greater than after simply being placed on a waiting list, but not significantly different from each other. This pattern was replicated for other three-month outcomes. Among these was a combination intended to represent a good response to treatment: drinking below risky levels without any substantial deterioration in drink-related or psychological problems or quality of life. For every five people allocated to the therapist-led intervention, one achieved a good treatment response who would not have done so had they been placed on the waiting list.

By six months benefits from the therapist-led intervention had further increased but those from the self-help option had stayed more or less the same. The result was that the superiority of the therapist-led intervention had become more apparent and statistically significant in respect of drinking amount (down to 180gm per week versus 260gm), drink problems and quality of life, and narrowly missing being significant in respect of response to treatment.

The authors' conclusions

Both internet-based therapy and internet-based self-help reduced problem drinking, but the therapist-led option was the more effective of the two, especially at the longer (six-month) follow-up. Not just drinking was beneficially affected but also alcohol-related problems and quality of life. Advantages of the self-help option include minimal or no costs per participant, while the therapy option could help equalise access to therapists in areas where therapist availability is limited, and to currently under-served drinkers, especially women and people in work. Both have the potential to dramatically extend access to cognitive-behavioural therapies.

These findings were derived from a sample selected to be risky drinkers but not necessarily suffering from an alcohol use disorder. They were also relatively well-educated and generally employed full time, exemplifying the 'new population' of problem drinkers who can be reached with internet-based interventions. Within these parameters, the sample was diverse.

According to their AUDIT profiles, drinkers who had been invited to participate but declined were not markedly different from those who did participate in the study, suggesting that they too might respond well to the interventions. Loss to follow-up reaching 40% at six months raises concerns over the validity of the findings, but measures were taken to estimate what the outcomes of the missing participants would have been, and an analysis based only on those followed up produced similar results.


Findings logo commentary The consistency and magnitude of the findings favouring the interventions and especially the therapist-led option are indicative of a real and worthwhile impact, even if some of the findings of statistical significance might not have survived a stricter interpretation. It seems that no adjustment was made for the multiple outcomes tested in the study to reduce the possibility that one or more was found statistically significant purely by chance. Especially if multiple outcomes tend not to covary, the more are measured, the more likely it is that some will reach the threshold for a statistically significant difference purely due to chance variations in the samples rather than any real impact of the interventions being tested. For example, by convention, if a difference would happen only 1 in 20 times by chance, it is considered a non-chance occurrence possibly due to the intervention. But if, say, 20 independent outcomes are measured, more often than not one would cross this threshold purely by chance. To cater for this, it is recommended1 that researchers consider raising the threshold (in the example, according to some adjustment methods to as high as 1 in 400) before each of the outcomes is considered to have reflected a statistically significant difference.

Additionally the study used one-tailed tests of significance which effectively double the chances of findings significant result by assuming that any results in the opposite direction to that expected must be meaningless flukes.2 It is not clear that this could be said of the two interventions and especially of the contrast between the two.

1 International Conference on Harmonisation Of Technical Requirements for Registration of Pharmaceuticals for Human Use. "ICH harmonised tripartite guideline statistical principles for clinical trials." Statistics in Medicine: 1999, 18, p. 1905–1942.
2 Abelson R.P. Statistics as principled argument. Lawrence Erlbaum Associates, 1995.

It is however of concern that so few people (1 in 8) who completed screening on the web site went on to participate in the study and that just 1 in 14 were represented in the six-month follow-up. Despite any similarities on the measures assessed by the study (especially AUDIT scores), clearly people who are eligible for and then go on join and comply with a study differ in some ways from those who do not. Outside a research context, free and ungated access over the internet might result in a different mix of intervention participants, and so too might the impacts of the interventions differ. For example, participants might have more serious substance use and psychiatric problems, some of which led web visitors to be excluded from the study. They might also be less interested in research and therefore perhaps less well educated and with less in the way of resources to aid their recovery.

None of this is to seriously cast doubt on the validity of the impacts on the people who did participate in the study, or to deny the probability that others interested enough to access the interventions would respond similarly. However, it could be that rather than a resource accessed widely enough to have an impact on public health across a country, internet-based alcohol treatment applications become one more niche option attracting and/or having a beneficial impact on a rather different population to conventional care.

The featured therapy-led intervention was among those whose impacts were simulated for the Netherlands, the results of which suggested that national health would improve and/or health care costs be reduced if on-line brief interventions and therapy were added to or partly replaced conventional alcohol-related care. The other interventions were:
DrinkTest, a 10-minute, on-line intervention which assesses one's alcohol use and gives automated personalised advice;
DrinkingLess, an on-line four-step cognitive behavioural intervention involving exploring one's alcohol use, setting goals, changing behaviour, and maintenance of behaviour change.

The second of these seems similar to the self-help option tested in the featured study. Since these three eHealth interventions increase in intensity, it was suggested that they could be used in a stepped-care framework, starting with the least intensive intervention, the DrinkTest, then if needed moving up to the more intensive levels of DrinkingLess and the on-line treatment tested in the featured study.

See other Findings analyses for a review of computer-delivered self-help interventions for drinking and smoking and a review focused on drinking. Both analyses include further commentary on the role of computer delivery and on UK findings.

Last revised 05 May 2012

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Top 10 most closely related documents on this site. For more try a subject or free text search

REVIEW 2011 Effectiveness of e-self-help interventions for curbing adult problem drinking: a meta-analysis

STUDY 2011 Modeling the cost-effectiveness of health care systems for alcohol use disorders: how implementation of eHealth interventions improves cost-effectiveness

HOT TOPIC 2015 Computerising therapy and advice increases access – but is effectiveness sacrificed?

REVIEW 2012 Computer based alcohol interventions

STUDY 2012 Alcohol screening and brief intervention in primary health care

STUDY 2012 Alcohol screening and brief intervention in emergency departments

STUDY 2013 Effectiveness of screening and brief alcohol intervention in primary care (SIPS trial): pragmatic cluster randomised controlled trial

STUDY 2012 Alcohol screening and brief intervention in probation

REVIEW 2010 Computer-delivered interventions for alcohol and tobacco use: a meta-analysis

STUDY 2009 Randomized controlled trial of cognitive-behavioural therapy for coexisting depression and alcohol problems: short-term outcome





Effectiveness of e-self-help interventions for curbing adult problem drinking: a meta-analysis.

Riper H., Spek V., Boon B. et al.
Journal of Medical Internet Research: 2011, 13(2), e42.
Unable to obtain a copy by clicking title? Try asking the author for a reprint by adapting this prepared e-mail or by writing to Dr Riper at h.riper@psy.vu.nl. You could also try this alternative source.

This synthesis of nine relevant studies of non-student adult samples confirmed that computer-delivered self-help interventions offer a low-cost way to extend the public health impact of interventions for risky drinkers. Yet to be shown is that they can replace therapists for severely dependent individuals seeking treatment.

Summary Computer-delivered self-help interventions offer a low-cost way to extend intervention to risky and problem drinkers. Stigmatisation concerns are reduced because there need be no face-to-face contact, often the recipient retains anonymity, and they can access the intervention free of charge. Automation assures treatment is consistently delivered as intended.

Such interventions can be divided in to:
• alternatives to face-to-face 'brief interventions', typically for people whose drinking has been identified by screening, and consisting of a single session featuring 'normative feedback' on how the drinker's consumption compares with low-risk drinking guidelines and with usual drinking levels in their own cohort or peer group; and
• alternatives to more extended face-to-face therapy for people who have sought treatment themselves or been referred for help; recommended to span at least six weeks, typically these consist of protocol-driven therapeutic programmes based on principles of behavioural self-control, cognitive-behavioural therapy, motivational interviewing, or a combination of these.

This analysis is the first to meta-analytically A study which uses recognised procedures to combine quantitative results from several studies of the same or similar interventions to arrive at composite outcome scores. Usually undertaken to allow the intervention's effectiveness to be assessed with greater confidence than on the basis of the studies taken individually. combine findings from studies of computer-delivered e-self-help interventions (either web-based or packaged on a CD-ROM) for adult risky or problem drinkers versus no intervention. Included were studies available up to February 2010 which randomly allocated adults (other than students in college and university settings) whose drinking exceeded When other drinkers or non-drinkers were included in the study they were excluded from the featured analysis. low-risk guidelines to e-self-help involving no therapist contact, or to a no-intervention control A group of people, households, organisations, communities or other units who do not participate in the intervention(s) being evaluated. Instead, they receive no intervention or none relevant to the outcomes being assessed, carry on as usual, or receive an alternative intervention (for the latter the term comparison group may be preferable). Outcome measures taken from the controls form the benchmark against which changes in the intervention group(s) are compared to determine whether the intervention had an impact and whether this is statistically significant. Comparability between control and intervention groups is essential. Normally this is best achieved by randomly allocating research participants to the different groups. Alternatives include sequentially selecting participants for one then the other group(s), or deliberately selecting similar set of participants for each group. group, and assessed the impacts on their drinking.

Nine trials were found involving 1553 participants, all conducted in high-income countries: the United States, Canada, the Netherlands, and Germany. Five tested single-session personalised normative feedback interventions, four more extended programmes. All the studies involved non-clinical samples recruited usually through media adverts.

Main findings

Substantial differences in the results of the studies meant it was advisable to analyse them on the assumption that there was no single 'true' impact of e-self-help, but that this varied across the studies. On this basis, across all the studies the impact of e-self-help on drinking amounted to a statistically significant moderate effect size A standard way of expressing the magnitude of a difference (eg, between outcomes in control and intervention groups) applicable to most quantitative data. Enables different measures taken in different studies to be compared or (in meta-analyses) combined. Based on expressing the difference in the average outcomes between control and experimental groups as a proportion of how much the outcome varies across both groups. The most common statistic used to quantify this difference is called Cohen's d. Conventionally this is considered to indicate a small effect when no greater than 0.2, a medium effect when around 0.5, and a large effect when at least 0.8. Hedges' 'g' statistic (used in the featured study) adjusts d for sample size; 0 to 0.32 may be interpreted as a small effect, 0.33 to 0.55 as moderate, and 0.56 to 1.20 as large. of 0.44 adjusted for sample size.

One 'outlier' study found an atypically large and another a small negative impact. Excluding these (slightly reducing the effect size to 0.39) or excluding the largest single study barely affected the overall picture. The findings were equivalent to needing to intervene with five excessive drinkers in order for one to achieve the desired reduction in drinking sustained over the next six to nine months. These results did not seem likely to be changed by unpublished studies or any missed by the search.

Excluding outlier studies, the three studies of extended self-help interventions registered a large and significantly greater effect size (0.61) than the four of (0.27) brief interventions, though both exerted statistically significant impacts. However, no significant differences in impact were related to whether the intervention was delivered at home or elsewhere, Research, health care, or workplace settings. how the control group was constructed, the size of the sample, or whether only people who actually participated in the intervention were included in the analysis.

The authors' conclusions

Up to six to nine months later, e-health interventions for adult problem drinking in the general population have resulted in a moderate reduction in consumption compared to offering no intervention. Such an impact could cumulate to major health benefits if similar interventions were (as in many countries they could be) accessed across a population. E-self-help interventions might also be an effective first-line choice in a 'stepped-care' approach to problem drinking, followed only if needed by more extensive or expensive interventions. Requiring no face-to-face contact, in economic terms they have considerable promise compared to other approaches with relatively high implementation costs.

The impact of extended therapy programmes was significantly greater than that of brief interventions, suggesting the former are more effective. Impacts beyond nine months have not been sufficiently investigated, but two studies suggest a diminished effect by one year.

The medium-size omnibus effect registered in this analysis is larger than those in other similar analyses, possibly because these variously included studies which compared computer-based intervention to other treatments rather than none, included younger people and student populations, or focused on brief interventions. A medium impact also compares well with the impacts of face-to-face brief interventions for adults primary care patients, postal self-help interventions, and brief interventions for risky drinkers not seeking help, but identified through screening or some other means. Similarity in impact suggests that computer-based intervention can extend the array of public health services to combat problem drinking,

Because of the studies from which they were derived, the results can only be considered applicable to self-referred adult problem drinkers in high-income countries recruited via the media – samples likely to be ready and motivated to curb their drinking. To a degree too, the results can only be considered applicable to people who complete the interventions and/or the study's assessments; many do not.


Findings logo commentary Though only a minority of site visitors may sign up for web-based alcohol programmes, nevertheless the numbers engaged can be large, and the risk-reductions seem of the order typical in studies of brief advice to drinkers identified in health care settings. In these settings screening programmes typically identify people who are not actually seeking help for drinking problems – 'pushing' them towards intervention and change – while web sites 'pull' in people already curious or concerned about their drinking. As such these two gateways can play complementary roles in improving public health and offering change opportunities to people who would not present to alcohol treatment services. However, in Britain and elsewhere, both tactics reach only small fractions of the population who drink excessively, leaving the bulk of the public health work to be done by interventions which drinkers generally cannot avoid and do not have seek out, such as price increases and availability restrictions.

About the featured analysis

The studies included in the featured analysis did not test computer-delivered therapy as an alternative to face-to face therapy for people attending alcohol treatment services, whose problems are typically much more severe and resources less than those of respondents to the adverts which recruited most study participants. For this role they are as yet unproven. The conclusion that extended interventions were more effective than brief interventions requires testing in studies intended for this purpose. For example, it could be that people prepared to participate in studies which involve a longer-term commitment have both more scope and more motivation to improve. Generally studies of brief alcohol interventions which have included longer and shorter versions have found these equivalent (for example, see this study of hospital inpatients and this of emergency department patients), but sometimes the offer of extra sessions has been found critical to the impact.

Stepped care of the kind recommended in the featured analysis has been evaluated in Germany, where a computerised intervention incorporating feedback on the patient's risky drinking was followed by up three 40-minute telephone calls depending on the success of the first-line intervention. Stepped-care patients absorbed roughly half the number of intervention minutes as those automatically offered full intervention yet did just as well, and better than patients offered no intervention.

The outlier study which found an atypically strong impact from computerised intervention tested a series of five psychoeducational TV programmes sent to participants as DVDs but intended to be normally broadcast. These were backed by an internet site but few of the sample accessed it and the study was seen by its evaluators as one of a TV intervention rather than a computer-based one. The study exemplifies the probability that people who agree to participate in such studies are unusual. It was nationally advertised in the Netherlands yet just 210 people participated.

The other outlier study said to have found a counterproductive effect of ehealth intervention was considered unusual partly because the emergency department patients were "given an e-self-help intervention that did not address alcohol as such, but provided general lifestyle advice". The alcohol content of the intervention was though typical of those in other studies (normative feedback), and was embedded in information about other lifestyle risks simply to avoid arousing the patients' resistance or stigmatising them. More importantly, rather than a negative impact, "patients who received the tailored, computerized intervention had a greater reduction in weekly alcohol intake than controls at both six- and twelve-month follow-up".

Opening more doors to change for more people

A particular role for alcohol self-help web sites may be to offer an easy, quick and accessible way for drinkers to actualise their desires to tackle their problems, especially when motivation is allied with the resources to implement and sustain improvements without face-to-face or comprehensive assistance. After conducting the Project MATCH trial, some of the world's leading alcohol treatment researchers argued that "access to treatment may be as important as the type of treatment available". The implication is that in cultures which accept 'treatment' as a route to resolving unhealthy and/or undesirable drinking, having convincing-looking and accessible 'treatment doors' to go through may be more important than what lies behind those doors, as long as this fulfils the expectations of the client or patient. As web services penetrate more aspects of life including social and health-related, they too may take their place among culturally accepted routes to overcoming unhealthy substance use. Self-help alcohol therapy web sites particularly attract people who retain a stake in mainstream society in the form of relationships, jobs, families, and a reputation to lose. These populations have more of the 'recovery capital' resources needed to themselves do most of the work in curbing their drinking.

British alcohol self-help sites

The best researched British alcohol self-help web site is the Down Your Drink site run by a team based at University College London, an initiative originally funded by Alcohol Research UK and then by the Medical Research Council's National Prevention Research Initiative. In 2007 this was revised to offer set programmes from a one-hour brief intervention to several weeks, but also to generally give the user greater control over the use they made of the site. The approach remained based on principles and techniques derived from motivational interviewing and cognitive-behavioural therapies.

The previous version had been structured as six consecutive modules to be accessed weekly. An analysis of data provided by the first 10,000 people who registered at the site after piloting ended in September 2003 revealed that most were in their 30s and 40s, half were women, nearly two-thirds were married or living with a partner, just 4% were unemployed, and most reported occupations from higher socioeconomic strata. As an earlier study commented, site users were predominantly middle class, middle aged, white and European. Six in 10 either did not start the programme, or completed just the first week. About 17% completed the six weeks. Of these, 57% returned an outcome questionnaire. Compared to their pre-programme status, on average they were now at substantially lower risk, and functioning better and living much improved lives. The sample had been recruited over about 27 months, a registration rate of about 4500 a year. By way of comparison, in England during 2008/09, around 100,000 adults were treated Statistics from the National Alcohol Treatment Monitoring System (NATMS) 1st April 2008 – 31st March 2009. Department of Health and National Treatment Agency for Substance Misuse, 2010. for their alcohol problems at conventional services. User profile and site usage had been similar during the earlier pilot phase. Results from surveys sent to pilot programme completers indicated that three quarters had never previously sought help for their drinking.

Also available is an NHS site on which users can monitor their alcohol intake, check whether it is placing them at risk, and get tips on how to cut down.

Without the benefit of the featured review, in 2012 NHS Scotland looked at computer-based alcohol interventions as possible ways to extend the reach of treatment and of Scotland's national brief intervention programme to people drinking at hazardous or harmful levels, in particular those unlikely to attend traditional health care services but who might turn to the internet for advice and information, such as women and young adults. The report found evidence that computer-based alcohol interventions are more effective than no treatment or assessment only and just as effective as conventional approaches including brief interventions. But it also found this evidence insufficient to sustain a definite conclusion on the impact among non-student samples and in the British context, and whether such interventions truly are cost-effective. Worth trying but unproven and need evaluating was the core message. The findings of the featured analysis, focused as it was on non-student samples, might in this respect at least have helped firm up the review's conclusions.

Thanks for their comments on this entry in draft to Heleen Riper of the Leuphana University in Germany and the Vrije Universiteit in the Netherlands. Commentators bear no responsibility for the text including the interpretations and any remaining errors.

Last revised 02 May 2012

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Top 10 most closely related documents on this site. For more try a subject or free text search

STUDY 2011 Modeling the cost-effectiveness of health care systems for alcohol use disorders: how implementation of eHealth interventions improves cost-effectiveness

HOT TOPIC 2015 Computerising therapy and advice increases access – but is effectiveness sacrificed?

STUDY 2011 Internet therapy versus internet self-help versus no treatment for problematic alcohol use: a randomized controlled trial

REVIEW 2010 Computer-delivered interventions for alcohol and tobacco use: a meta-analysis

REVIEW 2012 Computer based alcohol interventions

STUDY 2012 Alcohol screening and brief intervention in primary health care

STUDY 2012 Alcohol screening and brief intervention in emergency departments

STUDY 2012 Alcohol screening and brief intervention in probation

STUDY 2013 Effectiveness of screening and brief alcohol intervention in primary care (SIPS trial): pragmatic cluster randomised controlled trial

STUDY 2009 Translating effective web-based self-help for problem drinking into the real world





Modeling the cost-effectiveness of health care systems for alcohol use disorders: how implementation of eHealth interventions improves cost-effectiveness.

Smit F., Lokkerbol J., Riper H. et al.
Journal of Medical Internet Research: 2011, 13(3), e56.
Unable to obtain a copy by clicking title? Try asking the author for a reprint by adapting this prepared e-mail or by writing to Dr Smit at fsmit@trimbos.nl. You could also try this alternative source.

Computer simulation suggests that health would improve and/or costs be reduced if on-line brief interventions and therapy were added to or replaced conventional alcohol-related health care; these results for the Netherlands are based on a simulation model applicable as an aid to national policymaking in other countries.

Summary Emergence of evidence-based eHealth technologies offers opportunities to reach population segments hitherto not reached because they live in rural areas or have shied away from face-to-face services out of fear of stigma. The new technologies are also very scalable and could be cost-effective, especially when offered as well-structured self-help interventions or as interventions with (minimal) therapist support. Given the global health gap with regard to alcohol use disorders, these developments could become quite important. However, to date there is only limited evidence for their cost-effectiveness.

The featured analysis aimed to address this gap by conducting a population-level evaluation of the possible health gains and costs of adding new eHealth technologies to an existing 'base-case' health care system for alcohol use disorders. The aim is to enable planners to select the optimal mix of interventions to cost-effectively advance public health. An optimal health care system might meet the following criteria:
• acceptable to recipients;
• scalable to absorb increasing demands for health care;
• effectively generates the required health gains; and
• sufficiently inexpensive to be sustainable.

With these aims in mind, we developed a mathematical model (ALCMOD) of how a mix of alcohol interventions might affect public health in a country and how much they would cost. ALCMOD is programmed in Microsoft Excel, available on most computers. An important limitation is the model's focus on short-term impacts up to one year. This avoids making some unproven assumptions and simplifies the model but also limits its ability to fully represent health gains and costs. Strengths include its ability to evaluate combinations of interventions, adaptability to different populations and settings, its capacity to handle uncertainty, and the way it incorporates coverage (the proportion of the target population reached by the intervention) and adherence rates (the proportion of the reached population who complete the intervention) for each of the modelled interventions.

The Netherlands is used an example to illustrate how one might compute the impact of changes in alcohol health care, in this case by augmenting or partially replacing the current system with three eHealth interventions:
DrinkTest, a brief on-line intervention consisting of screening one's alcohol use followed by automated personalised advice;
DrinkingLess, an on-line four-step cognitive-behavioural intervention involving exploring one's alcohol use, setting goals, changing behaviour, and maintenance of behaviour change;
OnlineTreatment, an on-line therapist-led treatment for problem drinking; communication between participant and therapist is conducted over the internet in seven chat sessions of 45 minutes each covering setting goals, self-control techniques, monitoring, recognising relapse-precipitating situations, and relapse prevention techniques.

These three eHealth interventions increase in intensity and could be used in a stepped-care framework, starting with the least intensive intervention, the DrinkTest, and if needed moving up to the more intensive levels of DrinkingLess and OnlineTreatment.

How ALCMOD works

Given the country, ALCMOD automatically uploads the age and sex distribution of the population and corresponding mortality rates. ALCMOD needs to be told the size of the target population (in the Netherlands, 993,200 male and 222,800 female adult problem drinkers) and how they score on the AUDIT screening questionnaire for risky drinking. By default, the model assumes a range of face-to-face and eHealth interventions for heavy, hazardous, and harmful alcohol use and alcohol dependence, which can be changed to represent the current situation and the envisaged changes.

For each intervention the model needs the coverage rate and adherence rates and the full per-participant costs Based on the amount of resources (labour, facilities, and supplies) used for offering the intervention during its post-implementation stage. These assessments can be carried out with the help of an auxiliary costing tool, for example Cost It, available from WHO's CHOICE website at http://www.who.int/choice/en/. Neither costs nor effects are discounted because ALCMOD takes a short-term (12-month) perspective. – in the example, expressed in €s (euros) for the Netherlands for the year 2009.

The impacts of these interventions on health-related quality of life are calculated from the effect sizes A standard way of expressing the magnitude of a difference (eg, between outcomes in control and intervention groups) applicable to most quantitative data. Enables different measures taken in different studies to be compared or (in meta-analyses) combined. Based on expressing the difference in the average outcomes between control and experimental groups as a proportion of how much the outcome varies across both groups. The most common statistic used to quantify this difference is called Cohen's d. Conventionally this is considered to indicate a small effect when no greater than 0.2, a medium effect when around 0.5, and a large effect when at least 0.8. of their impacts on the severity of drinking, using the conversion formula that an effect size shift of 1 results in a quality of life shift of 0.18 on a scale of 0 to 1. Impacts in terms of the % reduction in alcohol intake are used to model effects on mortality, effects attenuated somewhat by the persisting effects of pre-intervention drinking. In the example, effect sizes were extracted from research findings, but all interventions were assumed to reduce alcohol intake by 20%, the effects of which on mortality were attenuated by 20% for pre-intervention drinking. Another assumption (the adherence rate) was that half the people reached by an intervention completed it.

Together impacts on health and deaths can be used to calculate savings in disability adjusted life years (DALYs – a combination of lost years of life due to problem drinking and quality detriments during life) generated by a new mix of interventions as opposed to the current situation. In turn these savings can be expressed as a ratio of the difference in costs to arrive at the incremental cost-effectiveness ratio (ICER). In one figure, this expresses whether the envisaged health care system offers better value for money (saves a disability adjusted life year at lower cost) than the current system.

Main findings

This model was applied to a scenario in the Netherlands in which eHealth alcohol interventions were added to conventional care in different mixes depending on the severity of the user's drinking, from heavy (in excess of guidelines but not yet substantially risking health) through to dependent. The (unrealistic) assumption was made that the new delivery vehicles would attract new segments of each of these target populations to alcohol-related health care. DrinkTest was assumed to impact on heavy and hazardous drinkers, DrinkingLess on hazardous and harmful drinkers, and OnlineTreatment on harmful and dependent drinkers.

The model calculated total current alcohol health care costs at €233 million. Adding the eHealth interventions would raise this to €319 million, but at the same time increase the saving in disability adjusted life years from 5022 to 10,319 (including avoiding 32 alcohol-related deaths). In turn this means each extra disability adjusted life year costs about an extra €16,000. For other disorders, the Netherlands is prepared to pay at least €20,000 to save an extra year, making the addition of alcohol eHealth interventions an acceptable expense.

Taking in to account a degree of uncertainty in the figures, it can be calculated that if each saved year is considered worth at least €30,000, the new eHealth-supplemented health care system is virtually certain to be more cost-effective than the current system. Assuming that each saved year is 'worth' €50,000 – the lowest figure customarily accepted in the Netherlands – the current alcohol health care system saves €1.08 for each € spent, but the new system would save €1.62.

It is also possible to make the same calculations on the assumption that instead of supplementing current interventions, eHealth interventions partially replace them. That is, instead of engaging new populations in health care, the same populations as before are engaged by a mix of eHealth and conventional interventions. Then the model calculates that virtually the same number of disability adjusted life years are saved but for €68 million less in health care costs, meaning that (again assuming each year is worth €50,000) a saving of €1.06 per € spent rises to €1.52.

The authors' conclusions

ALCMOD's simulations suggest that added to conventional care, widespread implementation of eHealth interventions for alcohol use disorders would substantially increase population health in the Netherlands, albeit at higher costs as more people become the recipients of the expanded system. The cost-effectiveness of the Dutch health system would also substantially improve if the new interventions partially replaced some current face-to-face interventions. The actual result is probably somewhere between these extremes, because it is unlikely that the new eHealth interventions would exclusively recruit people who would not otherwise have received conventional health care, or, at the other extreme, only such people. But whatever the mix, widespread introduction of eHealth technologies would substantially increase the efficiency of the Dutch health care system.

While such calculations will aid decision-makers, they are not the whole story. Most fundamentally, setting priorities for health care delivery is about acceptability and equity as well as cost-effectiveness. Also, ALCMOD only models clinical interventions, disregarding other public health options such as banning alcohol advertising, taxing, restricting access to alcoholic beverages, and improving road safety. Correspondingly, it is also concerned solely with costs incurred by the health care system. Within this limited remit, the model takes no account of start-up costs or delays in impact or less or un-predictable consequences of introducing the new technologies, such as perhaps an increased demand for conventional health care. On the other side, ALCMOD ignores the longer-term impacts of the modelled interventions on quality of life, mortality, and health care utilisation. In other words, ALCMOD only models incremental health gains and health care delivery costs over a short time horizon, assuming a steady state in the modelled health care systems.


Findings logo commentary The key figures The assumption of a 20% reduction in drinking across all interventions equalises the impact on mortality, which is in any event minimal over the year span of the analysis. generating the results of the analysis are the costs of the different interventions and their relative effectiveness in terms of impacts on problem drinking and thereby quality of life. While costs can be estimated on a comparable basis, the same is not necessarily the case for effectiveness. On these grounds it can be questioned whether the featured analysis – though a valid illustration of the use of the model – has returned a valid result in terms of the benefits of introducing on-line therapies in the Netherlands. Details below.

Standing out is the presumed effectiveness of OnlineTreatment, an on-line therapist-led treatment for problem drinking. Based on a single Dutch study, the intervention is modelled as around twice as effective as comparator face-to-face treatments. For example, the effect size A standard way of expressing the magnitude of a difference (eg, between outcomes in control and intervention groups) applicable to most quantitative data. Enables different measures taken in different studies to be compared or (in meta-analyses) combined. Based on expressing the difference in the average outcomes between control and experimental groups as a proportion of how much the outcome varies across both groups. The most common statistic used to quantify this difference is called Cohen's d. Conventionally this is considered to indicate a small effect when no greater than 0.2, a medium effect when around 0.5, and a large effect when at least 0.8. of 0.59 for dependent patients appears to contrast well with the 0.32 of a comparator cognitive-behavioural programme. However, the contrast is of the classic 'apples and pears' variety. Firstly, the comparator's impact is derived not from a single study in the same country as the on-line option, but from a synthesis of mainly US studies. For the on-line option, the effect size reflected its benefits in relation to offering no intervention but placing patients on a waiting list. In contrast, the comparator effect size cited in the featured analysis includes studies comparing the face-to-face approach to another active treatment as well as to no treatment. Yet, like the on-line alternative, face-to-face therapy was significantly more effective when contrasted to no treatment than to another treatment; on this yardstick, its effect size was 0.94 – not almost half the impact of the on-line treatment, but nearly 60% greater. Though this figure did not derive specifically from dependent drinkers, across all the studies the impact of the face-to-face approach was virtually identical for dependent versus problem drinkers.

See other Findings analyses for a review of computer-delivered self-help interventions for drinking and smoking and a review focused on drinking. These analyses offer further commentary on the role of computer delivery and on UK findings.

Last revised 05 May 2012

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