John W. Finney

Bio: John W. Finney is an academic researcher from VA Palo Alto Healthcare System. The author has contributed to research in topics: Poison control & Substance abuse. The author has an hindex of 58, co-authored 156 publications receiving 11334 citations. Previous affiliations of John W. Finney include Veterans Health Administration & Stanford University.

Brief interventions for alcohol problems: a meta‐analytic review of controlled investigations in treatment‐seeking and non‐treatment‐seeking populations

Abstract: Brief interventions for alcohol use disorders have been the focus of considerable research. In this meta-analytic review, we considered studies comparing brief interventions with either control or extended treatment conditions. We calculated the effect sizes for multiple drinking-related outcomes at multiple follow-up points, and took into account the critical distinction between treatment-seeking and non-treatment-seeking samples. Most investigations fell into one of two types: those comparing brief interventions with control conditions in non-treatment-seeking samples (n = 34) and those comparing brief interventions with extended treatment in treatment-seeking samples (n = 20). For studies of the first type, small to medium aggregate effect sizes in favor of brief interventions emerged across different follow-up points. At follow-up after > 3-6 months, the effect for brief interventions compared to control conditions was significantly larger when individuals with more severe alcohol problems were excluded. For studies of the second type, the effect sizes were largely not significantly different from zero. This review summarizes additional positive evidence for brief interventions compared to control conditions typically delivered by health-care professionals to non-treatment-seeking samples. The results concur with previous reviews that found little difference between brief and extended treatment conditions. Because the evidence regarding brief interventions comes from different types of investigation with different samples, generalizations should be restricted to the populations, treatment characteristics and contexts represented in those studies.

Contingency management for treatment of substance use disorders: a meta-analysis.

Abstract: Aims To examine the effectiveness of contingency management (CM) techniques in treating substance use disorders (i.e. illicit drugs, alcohol, tobacco). Design Meta-analysis was used to determine the average effect size and potential moderators in 47 comparisons of the effectiveness of CM from studies based on a treatment–control group design and published between 1970 and 2002. Findings The mean effect size (ES) of CM was positive, with a magnitude of d = 0.42 using a fixed effects model. The magnitude of the ES declined over time, following treatment. CM was more effective in treating opiate use (d = 0.65) and cocaine use (d = 0.66), compared with tobacco (d = 0.31) or multiple drugs (d = 0.42). Larger effect sizes were associated with higher researcher involvement, earlier studies and shorter treatment duration. Conclusions Study findings suggest that CM is among the more effective approaches to promoting abstinence during the treatment of substance use disorders. CM improves the ability of clients to remain abstinent, thereby allowing them to take fuller advantage of other clinical treatment components.

Alcoholism Treatment: Context, Process, and Outcome

Abstract: PART I. A SYSTEMS EVALUATION OF ALCOHOLISM TREATMENT: Evaluating and improving alcoholism treatment programs Objectives, methods, and assessment of treatment implementation Short-term outcome and patient prognosis The process and effects of treatment Gender and marital status in treatment and outcome PART II. EXTRATREATMENT FACTORS AND THE RECOVERY PROCESS: Life stressors, social resources, and coping responses Context, coping, and treatment outcome The process of recovery and relapse PART III. ALCOHOLISM AND THE FAMILY: Spouses of alcoholic partners Children of alcoholic parents PART IV. PRACTICAL APPLICATIONS: Improving treatment, work, and family settings Implications for treatment and program evaluation Index.

Meta‐analysis of naltrexone and acamprosate for treating alcohol use disorders: when are these medications most helpful?

Abstract: Aims Although debates over the efficacy of oral naltrexone and acamprosate in treating alcohol use disorders tend to focus on their global efficacy relative to placebo or their efficacy relative to each other, the underlying reality may be more nuanced. This meta-analysis examined when naltrexone and acamprosate are most helpful by testing: (1) the relative efficacy of each medication given its presumed mechanism of action (reducing heavy drinking versus fostering abstinence) and (2) whether different ways of implementing each medication (required abstinence before treatment, detoxification before treatment, goal of treatment, length of treatment, dosage) moderate its effects.

Twelve-Step and Cognitive-Behavioral Treatment for Substance Abuse A Comparison of Treatment Effectiveness

Abstract: The comparative effectiveness of 12-step and cognitive-behavioral (C-B) models of substance abuse treatment was examined among 3,018 patients from 15 programs at U.S. Department of Veterans Affairs Medical Centers. Across program types, participants showed significant improvements in functioning from treatment admission to a 1-year follow-up. Although 12-step patients were somewhat more likely to be abstinent at the 1-year follow-up, 12-step, C-B, and combined 12-Step-C-B treatment programs were equally effective in reducing substance use and improving most other areas of functioning. The finding of equal effectiveness was consistent over several treatment subgroups: Patients attending the "purest" 12-step and C-B treatment programs, and patients who had received the "full dose" of treatment. Also, patients with only substance abuse diagnoses, those with concomitant psychiatric diagnoses, and patients who were mandated to treatment showed similar improvement at the 1-year follow-up, regardless of type of treatment received. These data provide important new evidence supporting the effectiveness of 12-step treatment.

The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations.

Abstract: In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.

Social Relationships and Mortality Risk: A Meta-analytic Review

Abstract: Background The quality and quantity of individuals' social relationships has been linked not only to mental health but also to both morbidity and mortality. Objectives This meta-analytic review was conducted to determine the extent to which social relationships influence risk for mortality, which aspects of social relationships are most highly predictive, and which factors may moderate the risk. Data Extraction Data were extracted on several participant characteristics, including cause of mortality, initial health status, and pre-existing health conditions, as well as on study characteristics, including length of follow-up and type of assessment of social relationships. Results Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period. Significant differences were found across the type of social measurement evaluated (p<0.001); the association was strongest for complex measures of social integration (OR = 1.91; 95% CI 1.63 to 2.23) and lowest for binary indicators of residential status (living alone versus with others) (OR = 1.19; 95% CI 0.99 to 1.44). Conclusions The influence of social relationships on risk for mortality is comparable with well-established risk factors for mortality. Please see later in the article for the Editors' Summary

Statistical difficulties of detecting interactions and moderator effects

Abstract: Although interaction effects are frequently found in experimental studies, field researchers report considerable difficulty in finding theorized moderator effects. Previous discussions of this discrepancy have considered responsible factors including differences in measurement error and use of nonlinear scales. In this article we demonstrate that the differential efficiency of experimental and field tests of interactions is also attributable to the differential residual variances of such interactions once the component main effects have been partialed out. We derive an expression for this residual variance in terms of the joint distribution of the component variables and explore how properties of the distribution affect the efficiency of tests of moderator effects. We show that tests of interactions in field studies will often have less than 20% of the efficiency of optimal experimental tests, and we discuss implications for the design of field studies.

Evaluating non-randomised intervention studies.

Abstract: OBJECTIVES: To consider methods and related evidence for evaluating bias in non-randomised intervention studies. DATA SOURCES: Systematic reviews and methodological papers were identified from a search of electronic databases; handsearches of key medical journals and contact with experts working in the field. New empirical studies were conducted using data from two large randomised clinical trials. METHODS: Three systematic reviews and new empirical investigations were conducted. The reviews considered, in regard to non-randomised studies, (1) the existing evidence of bias, (2) the content of quality assessment tools, (3) the ways that study quality has been assessed and addressed. (4) The empirical investigations were conducted generating non-randomised studies from two large, multicentre randomised controlled trials (RCTs) and selectively resampling trial participants according to allocated treatment, centre and period. RESULTS: In the systematic reviews, eight studies compared results of randomised and non-randomised studies across multiple interventions using meta-epidemiological techniques. A total of 194 tools were identified that could be or had been used to assess non-randomised studies. Sixty tools covered at least five of six pre-specified internal validity domains. Fourteen tools covered three of four core items of particular importance for non-randomised studies. Six tools were thought suitable for use in systematic reviews. Of 511 systematic reviews that included non-randomised studies, only 169 (33%) assessed study quality. Sixty-nine reviews investigated the impact of quality on study results in a quantitative manner. The new empirical studies estimated the bias associated with non-random allocation and found that the bias could lead to consistent over- or underestimations of treatment effects, also the bias increased variation in results for both historical and concurrent controls, owing to haphazard differences in case-mix between groups. The biases were large enough to lead studies falsely to conclude significant findings of benefit or harm. Four strategies for case-mix adjustment were evaluated: none adequately adjusted for bias in historically and concurrently controlled studies. Logistic regression on average increased bias. Propensity score methods performed better, but were not satisfactory in most situations. Detailed investigation revealed that adequate adjustment can only be achieved in the unrealistic situation when selection depends on a single factor. CONCLUSIONS: Results of non-randomised studies sometimes, but not always, differ from results of randomised studies of the same intervention. Non-randomised studies may still give seriously misleading results when treated and control groups appear similar in key prognostic factors. Standard methods of case-mix adjustment do not guarantee removal of bias. Residual confounding may be high even when good prognostic data are available, and in some situations adjusted results may appear more biased than unadjusted results. Although many quality assessment tools exist and have been used for appraising non-randomised studies, most omit key quality domains. Healthcare policies based upon non-randomised studies or systematic reviews of non-randomised studies may need re-evaluation if the uncertainty in the true evidence base was not fully appreciated when policies were made. The inability of case-mix adjustment methods to compensate for selection bias and our inability to identify non-randomised studies that are free of selection bias indicate that non-randomised studies should only be undertaken when RCTs are infeasible or unethical. Recommendations for further research include: applying the resampling methodology in other clinical areas to ascertain whether the biases described are typical; developing or refining existing quality assessment tools for non-randomised studies; investigating how quality assessments of non-randomised studies can be incorporated into reviews and the implications of individual quality features for interpretation of a review's results; examination of the reasons for the apparent failure of case-mix adjustment methods; and further evaluation of the role of the propensity score.

Drug Dependence, a Chronic Medical Illness: Implications for Treatment, Insurance, and Outcomes Evaluation

Abstract: The effects of drug dependence on social systems has helped shape the generally held view that drug dependence is primarily a social problem, not a health problem. In turn, medical approaches to prevention and treatment are lacking. We examined evidence that drug (including alcohol) dependence is a chronic medical illness. A literature review compared the diagnoses, heritability, etiology (genetic and environmental factors), pathophysiology, and response to treatments (adherence and relapse) of drug dependence vs type 2 diabetes mellitus, hypertension, and asthma. Genetic heritability, personal choice, and environmental factors are comparably involved in the etiology and course of all of these disorders. Drug dependence produces significant and lasting changes in brain chemistry and function. Effective medications are available for treating nicotine, alcohol, and opiate dependence but not stimulant or marijuana dependence. Medication adherence and relapse rates are similar across these illnesses. Drug dependence generally has been treated as if it were an acute illness. Review results suggest that long-term care strategies of medication management and continued monitoring produce lasting benefits. Drug dependence should be insured, treated, and evaluated like other chronic illnesses.