Interpreting the Clinical Importance of Treatment Outcomes in Chronic Pain Clinical Trials: IMMPACT Recommendations

One can classify ways to establish the interpretability of quality-of-life measures as anchor based or distribution based. Anchor-based measures require an independent standard or anchor that is itself interpretable and at least moderately correlated with the instrument being explored. One can further classify anchor-based approaches into population-focused and individual-focused measures. Population-focused approaches are analogous to construct validation and rely on multiple anchors that frame an individual's response in terms of the entire population (eg, a group of patients with a score of 40 has a mortality of 20%). Anchors for population-based approaches include status on a single item, diagnosis, symptoms, disease severity, and response to treatment. Individual-focused approaches are analogous to criterion validation. These methods, which rely on a single anchor and establish a minimum important difference in change in score, require 2 steps. The first step establishes the smallest change in score that patients consider, on average, to be important (the minimum important difference). The second step estimates the proportion of patients who have achieved that minimum important difference. Anchors for the individual-focused approach include global ratings of change within patients and global ratings of differences between patients. Distribution-based methods rely on expressing an effect in terms of the underlying distribution of results. Investigators may express effects in terms of between-person standard deviation units, within-person standard deviation units, and the standard error of measurement. No single approach to interpretability is perfect. Use of multiple strategies is likely to enhance the interpretability of any particular instrument.

Methods to explain the clinical significance of health status measures.

Measuring the whole or the parts?: Validity, reliability, and responsiveness of the disabilities of the arm, shoulder and hand outcome measure in different regions of the upper extremity

Social and demographic trends are placing an increasing number of adults at risk for loneliness, an established risk factor for physical and mental illness. The growing costs of loneliness have led to a number of loneliness reduction interventions. Qualitative reviews have identified four primary intervention strategies: (a) improving social skills, (b) enhancing social support, (c) increasing opportunities for social contact, and (d) addressing maladaptive social cognition. An integrative meta-analysis of loneliness reduction interventions was conducted to quantify the effects of each strategy and to examine the potential role of moderator variables. Results revealed that single-group pre-post and nonrandomized comparison studies yielded larger mean effect sizes relative to randomized comparison studies. Among studies that used the latter design, the most successful interventions addressed maladaptive social cognition. This is consistent with current theories regarding loneliness and its etiology. Theoretical and methodological issues associated with designing new loneliness reduction interventions are discussed.

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A Meta-Analysis of Interventions to Reduce Loneliness:

This article provides a critical review of the assumptions and findings of studies used to establish psychotherapies as empirically supported. The attempt to identify empirically supported therapies (ESTs) imposes particular assumptions on the use of randomized controlled trial (RCT) methodology that appear to be valid for some disorders and treatments (notably exposure-based treatments of specific anxiety symptoms) but substantially violated for others. Meta-analytic studies support a more nuanced view of treatment efficacy than implied by a dichotomous judgment of supported versus unsupported. The authors recommend changes in reporting practices to maximize the clinical utility of RCTs, describe alternative methodologies that may be useful when the assumptions underlying EST methodology are violated, and suggest a shift from validating treatment packages to testing intervention strategies and theories of change that clinicians can integrate into empirically informed therapies.

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The empirical status of empirically supported psychotherapies: assumptions, findings, and reporting in controlled clinical trials.

This article summarizes and scrutinizes the growth of the development of clinically relevant and psychometrically sound approaches for determining the clinical significance of treatment effects in mental health research by tracing its evolution, by examining modifications in the method, and by discussing representative applications. Future directions for this methodology are proposed.

Lisa J. Roberts

Papers

Methods for defining and determining the clinical significance of treatment effects: description, application, and alternatives.