Elsevier

Journal of Affective Disorders

Volume 168, 15 October 2014, Pages 262-268
Journal of Affective Disorders

Research report
Resilience to affective disorders: A comparative validation of two resilience scales

https://doi.org/10.1016/j.jad.2014.07.010Get rights and content

Abstract

Background

Resilience to affective disorders in rehabilitating patients or in individuals with a severe disability is of special research interest. However, there is no gold standard for measuring resilience. We aimed to test the accuracy of the Dutch translation of the Brief Resilience Scale (BRSnl) and of the Resilience Scale (RSnl) in recognizing rehabilitating patients without anxiety and depression, and to determine the reliability and construct validity of both scales.

Methods

A within-subjects longitudinal study with six assessments, each one week apart. Forty residents of a nursing home rehabilitating unit were interviewed to assess resilience (BRSnl and RSnl), optimism and pessimism (LOT-R), depression and anxiety (HADS), positive and negative affect (PANAS), and pain (VAS).

Results

Receiver operating characteristic analyses for recognizing the absence of depression and anxiety (HADS-score≤7) revealed better accuracy (P=0.038) for the BRSnl (AUC=0.84; p<0.0001) than for the RSnl (AUC=0.68; P=0.017). The scales correlated moderately at baseline (rs=0.35; p=0.026), and at four-week follow-up (rs=0.50; p=0.004). The RSnl was positively associated with positive outcomes (optimism and positive affect), and the BRSnl positively with positive outcomes, and negatively with negative outcomes (pessimism, anxiety and negative affect). The RSnl showed a better four-week test–retest reliability (ICC, 0.94; 95% CI, 0.87 to 0.97) than the BRSnl (0.66; 95% CI, 0.29 to.83).

Limitations

Short study duration, a relatively small sample.

Conclusion

The BRSnl showed better performance in detecting people without depression and anxiety than the RSnl, and performed better on construct validity.

Introduction

More than half of all adults will experience at least one traumatic event during their lifetime, such as a violent or life-threatening situation, or an incident that involves intense fear, helplessness, or horror (Ozer et al., 2003). Nevertheless, most of those individuals will not develop clinical psychopathology such as posttraumatic stress disorder (PTSD) or depression after exposure to this trauma (Ozer et al., 2003, Shalev et al., 1998). In light of the shifting paradigm in mental health care from a problem-oriented approach to one of nurturing strengths and positive qualities, resistance to risk factors across the lifespan has increasingly become the focus of research. Resilience has been seen as the key phenomenon to explain non-pathological development after traumas (Windle et al., 2011).

The resilience phenomenon is of special research interest in patients who are severely ill or suffer from a physical injury that results in chronic disability. In rehabilitation settings, the most common trajectory (54% of the cases) was found to be the resilience trajectory, which is characterized by the absence or minimum of depressive symptoms, anxiety and negative affect (Quale and Schanke, 2010). From the perspective of the positive psychology movement, it is important to distinguish those patients with a high degree of resilience. This may help researchers and professionals to both monitor and gain insight into the protective factors that support recovery and rehabilitation. In clinical practice, detecting those with low resilience is important for individualizing rehabilitation programs. However, there is still controversy in the literature about how resilience should be defined and measured, and whether it is a personal quality, a process, an outcome, or a motivational force (Ahern et al., 2008, Richardson, 2002). Furthermore, as a characteristic of the individual, it can be seen as fixed or variable across different contexts or throughout the life span. At this moment, there are different approaches to conceptualizing and quantifying resilience and a variety of instruments exist while there is no ‘gold standard’.

In a recent systematic review on resilience scales, 15 original measures of resilience were discussed, 14 of which assess the availability of protective factors or resources that facilitate resistance to pathology (Windle et al., 2011). The fifteenth scale, Brief Resilience Scale (BRS)(Smith et al., 2008), in contrast, does not explain the resources and assets that could facilitate positive outcomes, but it can be useful for health professionals who focus on the ability of the patient to ‘bounce back’, recover from stress or to resist the negative influence of significant events, including disability. Together with three other reviewed scales, the BRS received the best psychometric ratings on several quality criteria (Windle et al., 2011); it contains six items and requires less completion time than the other extensive instruments.

This study aimed at validating a Dutch translation of the BRS (BRSnl, nl=Netherlands) in patients rehabilitating from a disabling condition. To the best of our knowledge, there is a paucity of literature comparing the performance of different resilience scales. Therefore, we aimed to compare the BRSnl with another, more comprehensive scale, a validated Dutch–Flemish translation of the Resilience Scale (RSnl) (Portzky et al., 2010). To date, the RSnl is the only resilience scale rated by the Committee on Tests and Testing of the Dutch Association of Psychologists, and is widely used in practice. Our comparative validation is not only important because of the scarcity of validation research of resilience scales in the Netherlands, but it can also contribute to the ongoing discussion on resilience because the scales assess different concepts: a general ability to ‘bounce back’ (BRSnl), versus various protective factors facilitating resilience (RSnl).

Our first aim was to compare the accuracy of the RSnl and our Dutch translation of the BRS scale in recognizing individuals with a high level of resilience, conceptualized as the absence of clinical relevant depressive and anxious features during rehabilitation (Quale and Schanke, 2010). Our second aim was to assess the scales׳ reliability, and construct validity.

Section snippets

Design

In this study, a within-subjects design was used with a baseline assessment and five subsequent follow-up assessments, each one week apart.

Setting and participants

Newly admitted residents from a rehabilitation unit of a nursing home in Dordrecht, the Netherlands, were invited to participate in the study. Inclusion criteria were: (i) recently admitted to the nursing home; (ii) Dutch-speaking and (iii) being able to provide informed consent. Exclusion criteria were: (i) unable to communicate; (ii) known diagnosis of

Results

In total, 56 residents were admitted to the rehabilitation unit from November 2012 until June 2013. Forty-four residents met the inclusion criteria (9 were excluded due to dementia, and 3 due to psychotic problems), and 40 provided informed consent. One respondent withdrew consent and was excluded from the study after two assessments. Discharge from the rehabilitation unit accounts for the other dropouts (n=3 after the second, 2 after the third, and 7 after the fifth assessment). Of the 40

Discussion

The BRSnl performed moderate to well, and the RSnl weakly in recognizing persons with high resilience conceptualized as the absence of depression and anxiety. Our analyses revealed that the BRSnl was more accurate than the RSnl. Furthermore, all BRSnl items, but only three out of 25 RSnl items, showed acceptable accuracy in distinguishing individuals without mental health problems from those who may have mental health problems. In contrast to the BRSnl, our analyses did not reveal cut-off

Conclusions

The BRSnl showed better performance in recognizing patients without depression and anxiety than the RSnl on the item level and as a whole scale. While it is possible that the BRSnl assesses a more dynamic construct related to both positive characteristics such as optimism and positive affect, and to negative characteristics such as pessimism and negative affect, our results indicated that the RSnl assesses a more stable personal characteristic. This personal characteristic is related to

Role of funding source

None

Conflict of interest

The authors have reported no conflicts of interest.

Acknowledgments

We would like to thank the study participants and all of the nursing home personnel who contributed to the study.

References (27)

  • I. Bjelland et al.

    The validity of the Hospital Anxiety and Depression Scale. An updated literature review

    J. Psychosom. Res.

    (2002)
  • A.P. Wingo et al.

    Moderating effects of resilience on depression in individuals with a history of childhood abuse or trauma exposure

    J. Affect. Disord.

    (2010)
  • N.R. Ahern et al.

    Resilience and coping strategies in adolescents

    Paediatr. Nurs.

    (2008)
  • APA

    Diagnostic and Statistical Manual of Mental Disorder

    (2000)
  • J. Block et al.

    IQ and ego-resiliency: conceptual and empirical connections and separateness

    J. Personal. Soc. Psychol.

    (1996)
  • K.M. Connor et al.

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

    Depress Anxiety

    (2003)
  • J.R. Crawford et al.

    The positive and negative affect schedule (PANAS): construct validity, measurement properties and normative data in a large non-clinical sample

    Br. J. Clin. Psychol.

    (2004)
  • U. Engelen et al.

    Verdere validering van de Positive en Negative Affect Scale en vergelijking van twee Nederlandstalige versies

    Psychol. gezondh.

    (2006)
  • F. Faul et al.

    Statistical power analyses using GPower 3.1: tests for correlation and regression analyses

    Behav. Res. Methods

    (2009)
  • J.E. Fischer et al.

    A readers’ guide to the interpretation of diagnostic test properties: clinical example of sepsis

    Intensive Care Med.

    (2003)
  • J.A. Hanley et al.

    The meaning and use of the area under a receiver operating characteristic (ROC) curve

    Radiology

    (1982)
  • G.A. Hawker et al.

    Measures of adult pain

    Arthritis Care Res.

    (2011)
  • S. Jackson

    Research methods and statistics: a critical thinking approach

    (2008)
  • Cited by (0)

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