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      Placebo effects on cutaneous pain and itch: a systematic review and meta-analysis of experimental results and methodology

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          Abstract

          Placebo effects, positive treatment outcomes that go beyond treatment processes, can alter sensations through learning mechanisms. Understanding how methodological factors contribute to the magnitude of placebo effects will help define the mechanisms by which these effects occur. We conducted a systematic review and meta-analysis of experimental placebo studies in cutaneous pain and itch in healthy samples, focused on how differences in methodology contribute to the resulting placebo effect magnitude. We conducted meta-analyses by learning mechanism and sensation, namely, for classical conditioning with verbal suggestion, verbal suggestion alone, and observational learning, separately for pain and itch. We conducted subgroup analyses and meta-regression on the type of sensory stimuli, placebo treatment, number of acquisition and evocation trials, differences in calibrated intensities for placebo and control stimuli during acquisition, age, and sex. We replicated findings showing that a combination of classical conditioning with verbal suggestion induced larger placebo effects on pain ( k = 68, g = 0 .59) than verbal suggestion alone ( k = 39, g = 0.38) and found a smaller effect for itch with verbal suggestion alone ( k = 7, g = 0.14). Using sham electrodes as placebo treatments corresponded with larger placebo effects on pain than when topical gels were used. Other methodological and demographic factors did not significantly affect placebo magnitudes. Placebo effects on pain and itch reliably occur in experimental settings with varied methods, and conditioning with verbal suggestion produced the strongest effects. Although methods may shape the placebo effect to some extent, these effects appear robust overall, and their underlying learning mechanisms may be harnessed for applications outside the laboratory.

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          The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

          Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate
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            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              Statistical Power Analysis for the Behavioral Sciences

              <i>Statistical Power Analysis</i> is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: <br> * a chapter covering power analysis in set correlation and multivariate methods;<br> * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and;<br> * expanded power and sample size tables for multiple regression/correlation.<br>
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                Author and article information

                Contributors
                Journal
                Pain
                Pain
                JPAIN
                JOP
                Pain
                Wolters Kluwer (Philadelphia, PA )
                0304-3959
                1872-6623
                June 2023
                16 November 2022
                : 164
                : 6
                : 1181-1199
                Affiliations
                [a ]Health, Medical and Neuropsychology Unit, Leiden University, Leiden, the Netherlands
                [b ]Leiden Institute for Brain and Cognition, Leiden, the Netherlands
                [c ]Medical Delta Healthy Society, Leiden University, Technical University Delft, and Erasmus University Rotterdam, Rotterdam, the Netherlands
                [d ]Department of Psychiatry, Leiden University Medical Centre, Leiden, the Netherlands
                Author notes
                [* ]Corresponding author. Address: Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Wassennaarseweg 52, 2333 AK Leiden, the Netherlands. Tel.: +31 071 527 3035; fax: +31 071-527 36 19. E-mail address: j.s.blythe@ 123456fsw.leidenuniv.nl (J.S. Blythe).
                Author information
                https://orcid.org/0000-0003-0649-5721
                https://orcid.org/0000-0002-2237-9459
                https://orcid.org/0000-0001-7622-1166
                https://orcid.org/0000-0001-6932-9283
                https://orcid.org/0000-0001-9046-1019
                https://orcid.org/0000-0002-0090-5091
                Article
                PAIN-D-22-00445 00002
                10.1097/j.pain.0000000000002820
                10184563
                36718994
                3460e923-540a-4240-863d-334fd08d6d0a
                Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.

                This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 May 2022
                : 14 September 2022
                : 20 October 2022
                Categories
                Systematic Review and Meta-Analysis
                Custom metadata
                TRUE
                T

                Anesthesiology & Pain management
                placebo effects,pain,itch,conditioning,verbal suggestion,observational learning

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