THE EFFICACY AND EFFECTIVENESS OF MARITAL AND FAMILY THERAPY: A PERSPECTIVE FROM META-ANALYSIS

This article reviews the major findings from a multiproject meta-analysis of the effects of marital and family therapy (MFT). Across 163 randomized trials, MFT demonstrates moderate, statistically significant, and often clinically significant effects. No orientation is yet demonstrably superior to any other, nor is MFT superior to individual therapy. Cost effectiveness information is scant in these 163 studies, but supportive. Randomized experiments yield very different answers from nonrandomized experimental studies of the effects of MFT, calling into question whether we should mix the two in reviews. We have also found several new differences in the ways that marital therapy (MT) and family therapy (FT) studies are conducted, making them harder to compare. Finally, important questions still exist about whether any psychotherapy, including MFT, yet has sufficient information about how well research generalizes to everyday clinical practice.     

Meta-analysis of MFT interventions

This article briefly reviews 20 meta-analyses of marital and family interventions. These meta-analyses support the efficacy of both MFT for distressed couples, and martial and family enrichment. Those effects are slightly reduced at follow-up, but still significant. Differences among kinds of marital and family interventions tend to be small. MFT produce clinically significant results in 40-50% of those treated, but the effects of MFT in clinically representative settings have not been much studied. The article also introduces the concept of meta-analytically supported treatments (MASTs), which are treatments that meet certain criteria for efficacy in meta-analysis, and which remedy certain problems in the empirically supported treatment (EST) literature. The article concludes with recommendations for doing better meta-analyses.     

The effects of family therapies for adolescent delinquency and substance abuse: a meta-analysis

This meta-analysis summarizes results from k = 24 studies comparing either Brief Strategic Family Therapy, Functional Family Therapy, Multidimensional Family Therapy, or Multisystemic Therapy to either treatment-as-usual, an alternative therapy, or a control group in the treatment of adolescent substance abuse and delinquency. Additionally, the authors reviewed and applied three advanced meta-analysis methods including influence analysis, multivariate meta-analysis, and publication bias analyses. The results suggested that as a group the four family therapies had statistically significant, but modest effects as compared to treatment-as-usual (d = 0.21; k = 11) and as compared to alternative therapies (d = 0.26; k = 11). The effect of family therapy compared to control was larger (d = 0.70; k = 4) but was not statistically significant probably because of low power. There was insufficient evidence to determine whether the various models differed in their effectiveness relative to each other. Influence analyses suggested that three studies had a large effect on aggregate effect sizes and heterogeneity statistics. Moderator and multivariate analyses were largely underpowered but will be useful as this literature grows.     

Increasing the degrees of freedom in existing group randomized trials: the df* approach

This study describes a method for incorporating external estimates of intraclass correlation to improve the precision for the analysis of an existing group-randomized trial. The authors use a random-effects meta-analytic approach to pool the information across studies, which takes into account any interstudy heterogeneity that may exist. This approach can be used in several different situations to estimate the degrees of freedom available for an adjusted test of the intervention effect in a study where the challenges of group-randomized trials were not fully considered when the study was planned. The authors discuss the limitations of this approach and the circumstances in which it is likely to be helpful.     

Increasing the degrees of freedom in future group randomized trials: the df* approach

This article builds on the previous article by Blitstein et al. (2005), which showed how external estimates of intraclass correlation can be used to improve the precision for the analysis of an existing group randomized trial. The authors extend that work to sample size estimation and power analysis for future group-randomized trials. Often this approach will allow a smaller study than would otherwise be possible without sacrificing statistical power. Such studies are needed, for example, as pilot studies to help plan for a full-scale efficacy trial, as replication studies, or in situations in which resource constraints prohibit a larger trial. The authors discuss the circumstances under which this strategy will be most helpful and the risks associated with conducting smaller studies.     

Propensity scores: an introduction and experimental test

Propensity score analysis is a relatively recent statistical innovation that is useful in the analysis of data from quasi-experiments. The goal of propensity score analysis is to balance two non-equivalent groups on observed covariates to get more accurate estimates of the effects of a treatment on which the two groups differ. This article presents a general introduction to propensity score analysis, provides an example using data from a quasi-experiment compared to a benchmark randomized experiment, offers practical advice about how to do such analyses, and discusses some limitations of the approach. It also presents the first detailed instructions to appear in the literature on how to use classification tree analysis and bagging for classification trees in the construction of propensity scores. The latter two examples serve as an introduction for researchers interested in computing propensity scores using more complex classification algorithms known as ensemble methods.     

The subjective well-being of mental patients in nursing homes.

This article reports a survey of self-reports of well-being by chronic mental patients in nursing homes. Patients reported lower levels of well-being than the general population, but not lower than other socially disadvantaged groups including urban renewal blacks. Nursing home mental patients reported levels of well-being that were generally similar to mental patients in other settings, including day hospital patients, participants in an innovative community care program, and patients receiving traditional hospital and follow-up care. These reports were mostly unrelated to levels of symptomatology or social integration, but were strongly related to patient perceptions of the quality of the environment. Results have important implications concerning the justifications for community care goals like noninstitutional care, reduction of symptomatology, and the fostering of social integration.