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This entry is our analysis of a review or synthesis of research findings considered particularly relevant to improving outcomes from drug or alcohol interventions in the UK. The original review was not published by Findings; click Title to order a copy. Free reprints may be available from the authors – click prepared e-mail. Links to other documents. Hover over for notes. Click to highlight passage referred to. Unfold extra text Unfold supplementary text The Summary conveys the findings and views expressed in the review. Below is a commentary from Drug and Alcohol Findings.

Title and link for copying Comment/query to editor

Using correlational evidence to select youth for prevention programming.

Derzon H.
Journal of Primary Prevention: 2007, 28, p. 421–447.
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 Derzon at derzonj@battelle.org. You could also try this alternative source.

Is it best to focus prevention efforts on youngsters most likely to use substances - or will that miss out many future users who could have benefited from these efforts? This well informed and clear analysis concludes that we just can't predict well enough to risk leaving some youngsters out.

Summary In a period of increased accountability and reduced prevention resources, the effective targeting of those limited resources is critical. One way limited resources are focused is to identify and provide services to those most at risk for later substance use. Risk status, or propensity, is typically estimated from correlational evidence. Using meta-analytic techniques, this paper examines the evidence that 29 of the 35 constructs specified by the risk and protective factor model developed by the Communities that Care project are related to alcohol, tobacco, or cannabis use. It finds that while these factors are generally predictive of substance use, the strength of the relations are modest. Ten factors show a significantly different strength of relation with tobacco than with alcohol or cannabis. Selection of 'high risk' youngsters for targeting does raise the proportion receiving services who are likely to benefit from them. But given the correlations observed and the rate of substance use in the population, providing only selective intervention services is likely to miss the majority who will later use substances. Given typical base and selection rates, though the average effect of an intervention may be reduced by universal as opposed to selective application, these smaller effects applied across the board may keep a greater number of youth from becoming involved with alcohol, tobacco, or cannabis. The journal editor commented that "The data make a strong and provocative argument for primary prevention of youth substance abuse that should be heard by policymakers and service providers involved in strategic planning and appropriate deployment of resources".


Findings logo commentary This unusually well constructed paper will not settle the issue of whether the balance of the prevention effort is best focused on high-risk youngsters or spread across the board, but it certainly makes an important contribution to that debate. Its strength is that it drew on an archive of reports from 940 studies which tracked the development of cohorts of young people, and related other factors in their lives to their current or later 60% of the relationships were between substance use and concurrently measured factors, but the study observes that "No systematic differences in effect size strength were noted between cross-sectional and prospective estimates" – that is, it made little difference whether substance use was assessed at the same time as, or some time after, the factors to which it was related. involvement in substance use. This data was then used to test whether the risk and protective factors identified by the Communities that Care (CTC) project really are related to alcohol, tobacco, or cannabis use. CTC's model is a well developed and influential way to assess the propensity for substance use problems in a community as means of prioritising prevention activities. 29 of CTC's 35 factors could be tested. Most were indeed related to substance use, some fairly strongly. For example for drinking, the top four were having few opportunities for conventional involvement, sensation seeking tendencies, positive attitudes towards substance use, and early initiation of problem behaviour. But on average relationships were weak, some factors were not related to use, and a few were related in the 'wrong' direction. This predictive weakness is the fundamental reason why the paper advocates persisting with universal prevention efforts.

However, its outcome measures were to do with substance use, not necessarily substance use problems. Some forms of early experimentation with substances are normative and not indicative of psychological or social risk or lack of resilience. In turn this could be why in some studies early substance use is poorly related to adult substance use or problems, while early regular use is a more reliable predictor. Given this background, it is no surprise that the featured study found substance use itself poorly predicted by many of the CTC factors.

The interesting observation that smoking is often differently related to risk and protective factors than drinking or cannabis use chimes with the common finding that preventive interventions also affect smoking differently from other forms of substance use. Several studies have found significant preventive impacts on smoking not found (or not to a statistically significant degree) for other substances.

Thanks for their comments on this entry in draft to Jim Derzon of the Battelle Centers for Public Health Research and Evaluation. Commentators bear no responsibility for the text including the interpretations and any remaining errors.

Last revised 28 December 2008

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