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      A methodological review of resilience measurement scales

      research-article
      1 , , 2 , 3
      Health and Quality of Life Outcomes
      BioMed Central

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          Abstract

          Background

          The evaluation of interventions and policies designed to promote resilience, and research to understand the determinants and associations, require reliable and valid measures to ensure data quality. This paper systematically reviews the psychometric rigour of resilience measurement scales developed for use in general and clinical populations.

          Methods

          Eight electronic abstract databases and the internet were searched and reference lists of all identified papers were hand searched. The focus was to identify peer reviewed journal articles where resilience was a key focus and/or is assessed. Two authors independently extracted data and performed a quality assessment of the scale psychometric properties.

          Results

          Nineteen resilience measures were reviewed; four of these were refinements of the original measure. All the measures had some missing information regarding the psychometric properties. Overall, the Connor-Davidson Resilience Scale, the Resilience Scale for Adults and the Brief Resilience Scale received the best psychometric ratings. The conceptual and theoretical adequacy of a number of the scales was questionable.

          Conclusion

          We found no current 'gold standard' amongst 15 measures of resilience. A number of the scales are in the early stages of development, and all require further validation work. Given increasing interest in resilience from major international funders, key policy makers and practice, researchers are urged to report relevant validation statistics when using the measures.

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          Most cited references21

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          Development of a new resilience scale: the Connor-Davidson Resilience Scale (CD-RISC).

          Resilience may be viewed as a measure of stress coping ability and, as such, could be an important target of treatment in anxiety, depression, and stress reactions. We describe a new rating scale to assess resilience. The Connor-Davidson Resilience scale (CD-RISC) comprises of 25 items, each rated on a 5-point scale (0-4), with higher scores reflecting greater resilience. The scale was administered to subjects in the following groups: community sample, primary care outpatients, general psychiatric outpatients, clinical trial of generalized anxiety disorder, and two clinical trials of PTSD. The reliability, validity, and factor analytic structure of the scale were evaluated, and reference scores for study samples were calculated. Sensitivity to treatment effects was examined in subjects from the PTSD clinical trials. The scale demonstrated good psychometric properties and factor analysis yielded five factors. A repeated measures ANOVA showed that an increase in CD-RISC score was associated with greater improvement during treatment. Improvement in CD-RISC score was noted in proportion to overall clinical global improvement, with greatest increase noted in subjects with the highest global improvement and deterioration in CD-RISC score in those with minimal or no global improvement. The CD-RISC has sound psychometric properties and distinguishes between those with greater and lesser resilience. The scale demonstrates that resilience is modifiable and can improve with treatment, with greater improvement corresponding to higher levels of global improvement. Copyright 2003 Wiley-Liss, Inc.
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            Resilience in developing systems: progress and promise as the fourth wave rises.

            Ann Masten (2007)
            Perspectives based on the first three waves of resilience research are discussed with the goal of informing the fourth wave of work, which is characterized by a focus on multilevel analysis and the dynamics of adaptation and change. Resilience is defined as a broad systems construct, referring to the capacity of dynamic systems to withstand or recover from significant disturbances. As the systems perspective on resilience builds strength and technologies of measuring and analyzing multiple levels of functioning and their interactions improve, it is becoming feasible to study gene-environment interactions, the development of adaptive systems and their role in resilience, and to conduct experiments to foster resilience or reprogram the fundamental adaptive systems that protect development in the context of adversity. Hot spots for future research to study and integrate multiple levels of analysis are delineated on the basis of evidence gleaned from the first waves of resilience research.
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              Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change

              Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.
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                Author and article information

                Journal
                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central
                1477-7525
                2011
                4 February 2011
                : 9
                : 8
                Affiliations
                [1 ]Dementia Services Development Centre, Institute of Medical and Social Care Research, Bangor University, Ardudwy, Holyhead Road, Bangor, LL56 2PX Gwynedd, UK
                [2 ]School of Psychology, University of Liverpool, Eleanor Rathbone Building, Bedford Street South, Liverpool, Merseyside L69 7ZA UK
                [3 ]Centre for Health Related Research, Bangor University, Fron Heulog, Ffriddoed Road Bangor Gwynedd LL57 2EF, UK
                Article
                1477-7525-9-8
                10.1186/1477-7525-9-8
                3042897
                21294858
                945c5b4a-c0a4-4630-8188-f7e715df7855
                Copyright ©2011 Windle et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 August 2010
                : 4 February 2011
                Categories
                Research

                Health & Social care
                Health & Social care

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