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      Relationship between Resilience, Psychological Distress and Physical Activity in Cancer Patients: A Cross-Sectional Observation Study

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          Abstract

          Objective

          Psychological distress remains a major challenge in cancer care. The complexity of psychological symptoms in cancer patients requires multifaceted symptom management tailored to individual patient characteristics and active patient involvement. We assessed the relationship between resilience, psychological distress and physical activity in cancer patients to elucidate potential moderators of the identified relationships.

          Method

          A cross-sectional observational study to assess the prevalence of symptoms and supportive care needs of oncology patients undergoing chemotherapy, radiotherapy or chemo-radiation therapy in a tertiary oncology service. Resilience was assessed using the 10-item Connor-Davidson Resilience Scale (CD-RISC 10), social support was evaluated using the 12-item Multidimensional Scale of Perceived Social Support (MSPSS) and both psychological distress and activity level were measured using corresponding subscales of the Rotterdam Symptom Checklist (RSCL). Socio-demographic and medical data were extracted from patient medical records. Correlation analyses were performed and structural equation modeling was employed to assess the associations between resilience, psychological distress and activity level as well as selected socio-demographic variables.

          Results

          Data from 343 patients were included in the analysis. Our revised model demonstrated an acceptable fit to the data (χ 2(163) = 313.76, p = .000, comparative fit index (CFI) = .942, Tucker-Lewis index (TLI) = .923, root mean square error of approximation (RMSEA) = .053, 90% CI [.044.062]). Resilience was negatively associated with psychological distress ( β = -.59), and positively associated with activity level ( β = .20). The relationship between resilience and psychological distress was moderated by age ( β = -0.33) but not social support ( β = .10, p = .12).

          Conclusion

          Cancer patients with higher resilience, particularly older patients, experience lower psychological distress. Patients with higher resilience are physically more active. Evaluating levels of resilience in cancer patients then tailoring targeted interventions to facilitate resilience may help improve the effectiveness of psychological symptom management interventions.

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          Most cited references23

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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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            Exploratory structural equation modeling: an integration of the best features of exploratory and confirmatory factor analysis.

            Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), path analysis, and structural equation modeling (SEM) have long histories in clinical research. Although CFA has largely superseded EFA, CFAs of multidimensional constructs typically fail to meet standards of good measurement: goodness of fit, measurement invariance, lack of differential item functioning, and well-differentiated factors in support of discriminant validity. Part of the problem is undue reliance on overly restrictive CFAs in which each item loads on only one factor. Exploratory SEM (ESEM), an overarching integration of the best aspects of CFA/SEM and traditional EFA, provides confirmatory tests of a priori factor structures, relations between latent factors and multigroup/multioccasion tests of full (mean structure) measurement invariance. It incorporates all combinations of CFA factors, ESEM factors, covariates, grouping/multiple-indicator multiple-cause (MIMIC) variables, latent growth, and complex structures that typically have required CFA/SEM. ESEM has broad applicability to clinical studies that are not appropriately addressed either by traditional EFA or CFA/SEM.
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              Measuring psychological and physical distress in cancer patients: structure and application of the Rotterdam Symptom Checklist.

              Use of the Rotterdam Symptom Checklist (RSCL) to measure psychological and physical distress as experienced by cancer patients, is discussed in this paper. The stability of the structure of the RSCL was assessed in principal component analyses in three studies: one concerning cancer patients during either chemotherapy or follow-up (n = 86), one done in patients undergoing chemotherapy for advanced ovarian cancer (n = 56), and the third dealing with cancer patients under treatment, disease-free 'patients', and 'normal' controls (n = 611). The psychological dimension proved to be stable across populations. A scale based on this factor was highly reliable (Cronbach's alpha 0.88-0.94). The physical distress is reflected by several dimensions in a homogeneous population (pain, fatigue, gastrointestinal complaints) and undimensionally in a heterogeneous population. Reliability of the physical distress scales is good (0.71-0.88). The current components of the RSCL and the use of individual and disease specific symptoms are discussed.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 April 2016
                2016
                : 11
                : 4
                : e0154496
                Affiliations
                [1 ]Department of Nursing Science, University of Vienna, Vienna, Austria
                [2 ]School of Health Fribourg, University of Applied Sciences and Arts Western Switzerland, Fribourg, Switzerland
                [3 ]Institute for Health and Nursing Science, Nursing Research Unit, University Hospital Halle (Saale), Halle (Saale), Germany
                [4 ]Directorate of Nursing, Department of Organizational Development, Vienna General Hospital, Vienna, Austria
                [5 ]Institute of Higher Education and Research in Nursing. Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
                The George Institute for Global Health, INDIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: HM ME MM SKH SS. Performed the experiments: SKH. Analyzed the data: CMP. Wrote the paper: CD CMP HM ME MM PJ SKH SS. Interpretation of data: CD CMP ME MM PJ.

                Article
                PONE-D-15-53110
                10.1371/journal.pone.0154496
                4849643
                27124466
                b8746256-4882-4d38-b61c-1a2abd3579f6
                © 2016 Matzka et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 December 2015
                : 14 April 2016
                Page count
                Figures: 3, Tables: 2, Pages: 13
                Funding
                The study was supported by a grant from the Felix Mandl Fund (Scientific Fund of the city of Vienna). HM received the funding on behalf of the researchers involved. No grant numbers are issued by the fund. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Oncology
                Cancer Treatment
                Medicine and Health Sciences
                Oncology
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                Medicine and Health Sciences
                Oncology
                Cancer Detection and Diagnosis
                Medicine and Health Sciences
                Oncology
                Cancer Treatment
                Chemotherapy
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Oncology
                Chemotherapy
                Medicine and Health Sciences
                Oncology
                Clinical Oncology
                Chemotherapy
                Medicine and Health Sciences
                Pharmaceutics
                Drug Therapy
                Chemotherapy
                Research and Analysis Methods
                Research Design
                Observational Studies
                Medicine and Health Sciences
                Health Care
                Patients
                Biology and Life Sciences
                Psychology
                Emotions
                Anxiety
                Social Sciences
                Psychology
                Emotions
                Anxiety
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. Additional data may be requested from the corresponding author (MM).

                Uncategorized
                Uncategorized

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