Skip to main content
Download PDF

Psychometric evaluation of the Connor-Davidson Resilience Scale among Iranian population

BMC Psychiatry volume 23, Article number: 92 (2023) Cite this article

Abstract

Background

The resilience construct is considered a personal trait composed of multiple aspects. Connor–Davidson Resilience Scale is a standard tool composed of five factors and 25 items. This study aimed to determine the psychometric properties of this scale.

Methods

In this cross-sectional study, after the scale translation, the factorial structural validity was assessed via the confirmatory factor analysis with 70 180 samples. Internal consistency, composite reliability, convergent validity were assessed by calculating Cronbach’s alpha, composite reliability, maximum reliability, and Average Variance Extracted. The discriminant validity was assessed using Heterotrait-monotrait ratio of correlations matrix and also, measure invariance was evaluated.

Results

The original five-factor model had good model fit indices but due to low factor loading of item 2 and 20, the model was modified. The Cronbach’s alpha and composite reliability for four factors were above 0.7 (except for factor 5). The convergent validity for all five factors were achieved. Between factors 1 with 2 and 4, 2 with 3 and 4 discriminant validity was not established (correlations > 0.9) and the results suggested that there might be a second-order latent construct behind these factors. Therefore, a second-order assessment was performed. The results of the second-order latent construct assessment showed a good goodness-of fit and strong measurement invariance for both men and women.

Conclusion

The 23-item version of Connor-Davidson Resilience Scale is a reliable and valid scale to measure resilience as a complex construct in the Iran context.

Peer Review reports

Introduction

Stress is an unavoidable part of life in the modern era, and according to estimates, the prevalence of traumatic events is nearly 71% in the life course [1]. Therefore adapting to challenging circumstances and crises is essential for the well-being of the general population as part of human development [2]. The resilience construct is recognized as having a significant potential benefit for health promotion in the life course and is a considerable indicator in developing research, policies, and practices on mental health [3].

Some researchers have conceptualized resilience as an individual trait or capacity, but others consider it as an outcome or dynamic process [4]. Despite available definitions, all researchers aim to understand how people could persist against pressures or respond efficiently to trauma and shocking events without having a harmful impacts on health; or even achieving inner growth and thrive [5, 6]. The Coronavirus disease of 2019 (COVID-19) pandemic was a traumatic event that had extreme drawbacks that affected the general population worldwide [7, 8]. Being under severe stress due to an unpredictable disease, disruption in living conditions, healthcare services and communications, and fear of loss and damages (life and economic issues) were all severe threats to different populations, especially for those with limited resources [7].

One strategy to protect mental health globally against this crisis was focusing on individual’s strengths, such as resilience to increase their endurance against adversities [3]. Measuring the resilience in such situations is order valuable in to recognizing individuals at risk, as mental problems could be prevented or reversed through effective interventions and policies [9].

However, finding a standard measure is difficult due to the complexity of characteristics constituting the resilience construct among diverse populations in a different cultures like Iran [10,11,12]. The Connor-Davidson Resiliency Scale (CD-RISC) identifies a comprehensive and valid measure of resiliency both for the general population and clinical groups in different populations and languages [6, 13, 14].

CD-RISC is a standard tool composed of five factors and 25 items, that is used most often [9]. Based on CD-RISC, the resilience construct is considered a personal trait composed of multiple aspects, including competence, tolerance, accepting or adapting to change, confidence in relationships, power to control, spiritual strength, and thriving after stress) [15].

Therefore, our study question is, does the CD-RISC 25 have acceptable reliability and validity in the general Iranian population during COVID-19?

Methods

Design and participants

This study used a cross-sectional design. The online survey was conducted in March 2020 through an Iranian survey platform named Uniform Resource Locator (URL). The survey was distributed via social media and Iranian population were invited to complete the online questionnaire using a convenience sampling. The independent t-test and one-way analysis of variance (ANOVA) test were used to compare the resilience score in different groups based on demographic characteristics.

Translation

After obtaining written permission from the developer of the scale, according to the guideline proposed by Beaton et al. [16] the CD-RISC was translated to Farsi. The two independent translators translated the CD-RISC into a Farsi version. Afterwards, these two Farsi versions of the CD-RISC were assessed by a group of experts, to develop a single Farsi version of the CD-RISC. Finally, the single Farsi version of CD-RISC was back-translated to English by a Farsi–English translator. The same group of experts confirmed the final version of the scale.

Factorial structural validity

This study conducted confirmatory factor analysis (CFA) to identify the factorial structure as well as the construct validity and reliability of the Farsi version of CD-RISC using AMOS version 27. The CFA was conducted using maximum likelihood. The model fit was assessed through a number of fit indices, such as Chi-square (χ2) test, χ2/degree of freedom(df) ratio < 4, comparative fit index (CFI) > 0.90, normed fit index (NFI) > 0.90, and Tucker–Lewis index (TLI) > 0.90, standardized root mean square residual (SRMR) < 0.09, and root mean square error of approximation (RMSEA) < 0.08 [17,18,19].

Construct validity and reliability

The internal consistency (Cronbach’s alpha), composite reliability (CR), and maximum reliability (MaxR), and Average Variance Extracted (AVE) were assessed. To achieve acceptable construct reliability, Cronbach’s alpha, CR, and MaxR should be greater than 0.7. For convergent validity, CR should be higher than 0.7, and AVE should be greater than 0.5 [17, 18]. Moreover, the discriminant validity was assessed using Heterotrait-monotrait ratio of correlations (HTMT) matrix, and all values in the HTMT matrix should be less than 0.85 to achieve discriminat validity [20].

Multivariate normality and outliers

The univariate distributions were tested for outliers, skewness, and kurtosis. The normality of the multivariate distribution was assessed using Mardia’s coefficient of multivariate kurtosis, and the Mardia’s coefficient (> 7.98). Moreover, the outliers of the multivariate distribution were detected using Mahalanobis distance (p < 0.001) [21].

Measurement invariance for gender

Measurement invariance was analyzed by comparing a set of increasing constrained models for men and women: from no constraint to factor loading and intercepts (configural invariance), constrained factor loadings for men and women (metric or weak invariance), and constrained factor loadings and intercepts for men and women (scalar or strong invariance). The Δχ2, ΔCFI and ΔRMSEA from two consecutive models were used for evidence of invariance when Δχ2 was not significant and/or ΔCFI and ΔRMSEA were less than 0.01 [22].

Results

Demographic

A total of 70 180 Iranian individuals completed the online questionnaire. As shown in Table 1, the sample of this study consisted of 25 037 (35.7%) men and 45 143 women (64.3%) with a mean age of 41.24 (SD = 11.71) years. Older adults had higher levels of resilience than younger adults and these differences were significant (p < 0.001). Also, there was a statistically difference between men and women’s mean score of resilience (p < 0.001). Most participants were married (75.8%) and had a moderate or poor economic status (93.7%). Married individuals were also those with moderate to poor economic status, and they had higher mean score in resilience and they were statistically significant (p < 0.001). With respect to the level of education, 63.4% of the total respondents held a bachelor’s degree. Individuals with higher education had higher level of resilience and these differences were also statistically significant (p < 0.001). As for the disease history, 80.9% of the participants reported no disease history. The details of the participants’ demographic profile are shown in Table 1.

Table 1 Characteristics of participants according to the demographic variables and resilience (n = 70 180)
Full size table

Evidence for factorial structural validity

The maximum likelihood CFA was performed to validity and confirmed the psychometric properties of the original five-factor structure of CD-RISC using the Iranian population. Results of the several model fit indices showed that the five-factor model fits the data well as evidenced by an acceptable goodness-of-fit (CFI = 0.917, NFI = 0.916, TLI = 0.906, SRMR = 0.036, RMSEA (90% C.I.) = 0.059 [0.059, 0.059]). However, results showed that the factor loading for item 2 and item 20 were less than 0.5. Therefore, to enhance the psychometric qualities of the Iranian-CD-RISC, the original five-factor model was slightly modified by removing item 2 and item 20 and co-variating the error terms of three pairs of the items (between item 10 and item 11, item 24 and item 25, item 6 and item 7, item 14 and 19, and item 21 and item 22) following the modification indices (Fig. 1). The modified five-factor structure of the Iranian-CD-RISC demonstrated a good mode fit (CFI = 0.937, NFI = 0.937, TLI = 0.926, SRMR = 0.033, RMSEA (90% C.I.) = 0.057 [0.057, 0.058]).

Fig. 1
figure 1

The results of the confirmatory factor analysis for first-order model (n = 70 108)

Full size image

Construct reliability and validity

The results showed that the five-factor Iranian-CD-RISC has an acceptable internal consistency and construct reliability. As shown in Table 2, Cronbach’s alpha for Factor 1 (0.869), Factor 2 (0.811), Factor 3 (0.762), and factor 4 (0.761) were greater than 0.7, indicating good internal consistency. As for Factor 5, the Cronbach’s alpha (0.681) was slightly less than 0.7, it is still acceptable for psychological construct when the value is greater than 0.6 [23, 24], the reason of lower Cronbach’s alpha for Factor 3 could be due to fewer items of this construct. Moreover, the CR (Factor 1: 0.869; Factor 2: 0.804; Factor 3: 0.770; Factor 4: 0.773; Factor 5: 0.697) and MaxR (Factor 1: 0.878; Factor 2: 0.810; Factor 3: 0.793; Factor 4: 0.784; Factor 5: 0.747) for all five factors showed good construct reliability. As for convergent validity, only AVE for Factor 4 and Factor 5 were greater than 0.5. However, Factor 1 (0.458), Factor 2 (0.408), Factor 3 (0.460) were slightly less than 0.5, AVE is a strict measurement for convergent validity, using CR more than 0.7 alone can assess convergent validity in psychological studies [18, 24]. Therefore, following the results of the CR and MaxR, the convergent validity for all five factors was achieved. With respect to discriminant validity, the results of HTMT correlation analysis showed that the acceptabe discreminat validty between Factor 1 and Factor 3 (0.884), Factor 1 and Factor 5 (0.512), Factor 2 and Factor 5 (0.441), Fatcor 3 and Factor 4 (0.884), Factor 3 and Factor 5 (0.541), and Factor 4 and Factor 5 (0.525). However, the discriminant validity between Factor 1 and Factor 2 (0.926), Fatcor 1 and Factor 4 (0.956), Factor 2 and Factor 3 (0.932), and Factor 2 and Factor 4 (0.906) were not estabilihsed since there was a strong correlation between those factors in the Iranian-CD-RISC first-order model. Hence, the results suggested that there might be a second-order latent construct contained within these factors [25]. Therefore, we performed a second-order assessment to conform the Iranian-CD-RISC.

Table 2 The results of the internal consistency, construct reliability, and convergent validity
Full size table

Second-order construct

The results of the second-order latent construct assessment showed a strong goodness-of fit (CFI = 0.923, NFI = 0.923, TLI = 0.913, SRMR = 0.034, RMSEA (90% C.I.) = 0.057 [0.056, 0.057]). As shown in Fig. 2, factor loadings of each item of the first-order construct were greater than 0.5 and statistically significant. Moreover, the results showed that the CR (0.945) and MaxR (0.982) of the second-order construct more than 0.7, and AVE of the second-order construct was 0.782 which is more than the cult-off value of 0.5, indicating good construct reliability and validity of the second-order construct.

Fig. 2
figure 2

The results of the confirmatory factor analysis for second-order model (n = 70 108)

Full size image

Measurement invariance for gender

Analysis of measurement invariance for gender revealed both metric invariance (Δχ2 (22) = 194.62; p < 0.001, ΔCFI = 0.001 and ΔRMSEA = -0.001) and scalar invariance (Δχ2 (22) = 1943.82; p < 0.001, ΔCFI = -0.003 and ΔRMSEA = 0.001) according to the ΔCFI and ΔRMSEA criteria but not according to the Δχ2 criterium. However, it is well known that the χ2 statistic is inflated by large sample sizes as is the case in this study. This leads researchers to devalue this statistic when evaluating invariance (see, e.g.,[22]).

Discussion

Resilience is a complex concept influenced by internal strengths and external capacities; thus, different definitions and constructs have been developed based on researchers’ perspectives and disciplines [26, 27]. Previous studies regarding the relationship between resilience and demographic characteristics have presented different results. Most of the studies on resilience have been conducted on specific populations and limited studies have been conducted on the general population. The results of different research have created two different paths regarding the relationship between age and resilience. Some researchers believe that with increasing age, resilience decreases due to the reduction of physical and mental strength, and alternatively, researchers believe that with increasing age and gaining more experience and strengthening adaptation strategies, increases resilience [28]. In the current research, in line with this second approach, resilience has increased with age. In term of the relationship between gender and resilience, researchers reported different results. Some studies reported higher levels of resilience score in women [29, 30] and others found higher resilience in men [31,32,33,34]. The result of this study is in line with the latter. The higher level of resilience in men may be related to the socio-cultural context of Iran in which men have greater opportunities and social interactions. In this study, married people had higher resilience than single people. This result is in line with results of some others studies [30, 32, 35], and may be because married people have better support networks than single people. On the other hand, researchers show that people with higher education had higher resilience scores [29, 30, 35, 36], the results of this confirmed this finding, too. In term of economic status, the result of this study showed that people with good economic status had higher level of resilience which is line of the Kocalevent et al. [33]; whose study had a large sample size. Further studies are need to analyze the relationship between resilience and educational level and economic status.

There are 15 questionnaires and scales available that assess resilience, according to a report of one systematic review. Some of these scales with high scores in terms of psychometric properties are [3] the Resilience Scale for Adults [37], the Brief Resilience Scale [38], and the CD-RISC. The resilience scale for adults was designed to examine protective factors (intrapersonal and interpersonal) that facilitate adaptation to psychosocial stresses. The Brief Resilience Scale was designed to assess the ability to recover from stress but the CD-RISC was designed to assess the ability to cope with stress [3].

Connor-Davidson’s resilience scale has been used in different languages and cultures and has been psychometrically evaluated in Iranian adolescents with cancer [14, 39]. However, adolescents and the general population are different in cognitive and language development [40]. Furthermore, their perception of stress and reactions would be different. Our study aimed to assess the psychometric properties of this scale in a large sample of the general population during COVID-19. The study results showed that the five-factor Iranian-Connor-Davidson Resilience scale has acceptable internal consistency, construct reliability, and convergent validity after removing items 2 and 20. Nevertheless, discriminant validity between factors was not established, as a strong correlation was found among the factors in the Iranian-CD-RISC first-order model. Therefore, to confirm the Iranian-CD-RISC, we performed a second-order assessment indicating good construct reliability and validity. A Chinese study on adolescents is consistent with ours in that the 5-factor structure model has better fit indices than the 3-factor model [41].

Whereas other studies have presented a four-factor [42,43,44], a three-factor [45, 46], and two-factor structures [47, 48] that is differ from the original scale and ours.

A variety of factors or items might be due to different contexts (culture and population) as they could influence the meaning and perception of the resilience of individuals [47]. Differences in personal characteristics and perception of the resilience concept or having diverse interpretations from scale items as well as using various strategies to deal with adversities may explain the differences in the models [41].

Based on some evidence, resilience is a dynamic concept that transforms during the development stages of the life course; therefore, variations in factors and items of the previous studies may be due to having different samples (adolescents) from ours (general population) [40]. Furthermore, the approach (orthogonal or oblique rotation method) may have been associated with obtaining different study results.

Our confirmed 5-factor model had more strong indices, including RMSEA (0.59), compared to the CFA results of the other studies in which RMSEA was obtained at less than 0.50 [41, 47].

This study was conducted in a large and non-clinical sample that facilitated performing CFA to propose a 5-factor model of CD-RISC. Under these conditions, we were able to evaluate the relationships between factors and individual characteristics during a pandemic. Therefore, our study results could help identify at-risk populations in Iran who need help and psychosocial support.

Analysis of measurement invariance indicated that the Farsi version of the Connor-Davidson Resilience Scale displayed strong scalar invariance; and it can thus be used to measure resilience in both men and women ensuring the validity and reliability of gender comparisons in adult Iranians.

This study has some limitations. One of these limitations is that data were gathered via online questionnaires, and we could not include individuals in the same quota from all parts of the country and obtain diverse demographic characteristics. Therefore, the generalizability of our data needs to be considered carefully. Nevertheless, our study has multiple strength: We had a very large sample size; also, the assessment of discriminant validity and measurement invariance for gender are other strengths of this study.

Conclusions

Despite limitations mentioned, the present investigation shows that the 23-item version of CD-RISC is a reliable and valid scale to measure resilience as a complex construct in an Iranian population. This scale can be used in the general population for screening individuals for their resiliency. This predictive validity is of great importance for our study. Future research can reevaluate the discriminant validity of the scale.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

CD-RISC:

Connor-Davidson Resilience Scale

COVID-19:

Coronavirus disease of 2019

URL:

Uniform Resource Locator

ANOVA:

One-Way Analysis of Variance

CFA:

Confirmatory Factor Analysis

CFI:

Comparative Fit Index

NFI:

Normed Fit Index

TLI:

Tucker–Lewis index

SRMR:

Standardized Root Mean Square Residual

RMSEA:

Root Mean Square Error of Approximation

CR:

Composite Reliability

MaxR:

Maximum Reliability

AVE:

Average Variance Extracted

HTMT:

Heterotrait-monotrait ratio of correlations

C.I:

Confidence Interval

References

  1. Knipscheer J, Sleijpen M, Frank L, de Graaf R, Kleber R, ten Have M, et al. Prevalence of Potentially Traumatic Events, Other Life Events and Subsequent Reactions Indicative for Posttraumatic Stress Disorder in the Netherlands: A General Population Study Based on the Trauma Screening Questionnaire. Int J Environ Res Public Health. 2020;17(5):1725. https://doi.org/10.3390/ijerph17051725. (PubMed PMID).

    Article  Google Scholar 

  2. Liu JJW, Reed M, Fung KP. Advancements to the Multi-System Model of Resilience: updates from empirical evidence. Heliyon. 2020;6(9):e04831.

    Article  Google Scholar 

  3. Windle G, Bennett KM, Noyes J. A methodological review of resilience measurement scales. Health Qual Life Outcomes. 2011;9(1):8.

    Article  Google Scholar 

  4. Ayed N, Toner S, Priebe S. Conceptualizing resilience in adult mental health literature: A systematic review and narrative synthesis. Psychol Psychother Theory Res Pract. 2019;92(3):299–341.

    Article  Google Scholar 

  5. Zautra AJ, Hall JS, Murray KE. The Resilience Solutions G. Resilience: a new integrative approach to health and mental health research. Health Psychol Rev. 2008;2(1):41–64.

    Article  Google Scholar 

  6. Salisu I, Hashim N. A critical review of scales used in resilience research. IOSR J Bus Manag. 2017;19(4):23–33.

    Article  Google Scholar 

  7. Moshtagh M, Mirlashari J, Amiri R. Global collaboration and social practices to mitigate impacts of COVID-19 in the world: a lived experience of infecting. Qual Soc Work. 2021;20(1–2):366–74 (PubMed PMID: 34253980).

    Article  Google Scholar 

  8. Sharif Nia H, Akhlaghi E, Torkian S, Khosravi V, Etesami R, Froelicher ES, et al. Predictors of Persistence of Anxiety, Hyperarousal Stress, and Resilience During the COVID-19 Epidemic: A National Study in Iran. Frontiers in psychology. 2021;12:671124 (PubMed PMID: 34658994. Pubmed Central PMCID: PMC8511821. Epub 2021/10/19. eng).

    Article  Google Scholar 

  9. Kuiper H, van Leeuwen CCM, Stolwijk-Swüste JM, Post MWM. Measuring resilience with the Connor-Davidson Resilience Scale (CD-RISC): which version to choose? Spinal Cord. 2019;57(5):360–6.

    Article  Google Scholar 

  10. Kaplan HB. Toward an Understanding of Resilience. In: Glantz MD, Johnson JL, editors. Resilience and Development: Positive Life Adaptations. Boston, MA: Springer, US; 2002. p. 17–83.

    Chapter  Google Scholar 

  11. Masten AS. Resilience in developing systems: Progress and promise as the fourth wave rises. Dev Psychopathol. 2007;19(3):921–30 (Epub 08/20).

    Article  Google Scholar 

  12. Robinson JS, Larson CL, Cahill SP. Relations between resilience, positive and negative emotionality, and symptoms of anxiety and depression. Psychol Trauma Theory Res Pract Policy. 2014;6(S1):S92.

    Article  Google Scholar 

  13. Martinez S, Jones JD, Brandt L, Hien D, Campbell ANC, Batchelder S, et al. Factor structure and psychometric properties of the Connor-Davidson resilience scale (CD-RISC) in individuals with opioid use disorder. Drug Alcohol Depend. 2021;221:108632.

    Article  Google Scholar 

  14. Tsigkaropoulou E, Douzenis A, Tsitas N, Ferentinos P, Liappas I, Michopoulos I. Greek Version of the Connor-Davidson Resilience Scale: Psychometric Properties in a Sample of 546 Subjects. In Vivo. 2018;32(6):1629.

    Article  Google Scholar 

  15. Connor KM, Davidson JRT. Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC). Depress Anxiety. 2003;18(2):76–82.

    Article  Google Scholar 

  16. Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine (Phila Pa 1976). 2000;25(24):3186–91 (PubMed PMID: 11124735. eng).

    Article  CAS  Google Scholar 

  17. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariat Data Analysis. 7th Editio ed: Pearson Education Limited. 2014.

    Google Scholar 

  18. Pahlevan Sharif SP, Mostafiz I, Guptan V. A systematic review of structural equation modelling in nursing research. Nurse Res. 2019;26(2):28–31.

    Article  Google Scholar 

  19. She L, Ma L, Khoshnavay Fomani F. The Consideration of Future Consequences Scale Among Malaysian Young Adults: A Psychometric Evaluation. Frontiers in psychology. 2021;12:770609 (PubMed PMID: 34955987. Pubmed Central PMCID: PMC8695613. Epub 2021/12/28. eng.).

    Article  Google Scholar 

  20. Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Market Sci. 2015;43(1):115–35.

    Article  Google Scholar 

  21. Kline RB. Principles and practice of structural equation modeling: Guilford publications. 2015.

    Google Scholar 

  22. Cheung GW, Rensvold RB. Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance. Structur Equation Model Multidisciplin J. 2002;9(2):233–55.

    Article  Google Scholar 

  23. Yaghoobzadeh A, Pahlevan Sharif S, Ong FS, Soundy A, Sharif Nia H, Moradi Bagloee M, et al. Cross-Cultural Adaptation and Psychometric Evaluation of the Herth Hope Index Within a Sample of Iranian Older Peoples. Int J Aging Human Dev. 2019;89(4):356–71.

    Article  Google Scholar 

  24. Sharif Nia H, She L, Fomani FK, Kaur H, Sánchez-Teruel D, Froelicher ES, et al. Psychometric Evaluation of the Persian Version of Religious Orientation Scale in Iranian Patients with Cancer. J Religion Health. 2021;60(5):3658–74.

    Article  Google Scholar 

  25. Rahmatpour P, Peyrovi H, Sharif Nia H. Development and psychometric evaluation of postgraduate nursing student academic satisfaction scale. Nursing Open. 2021;8(3):1145–56.

    Article  Google Scholar 

  26. Luthar SS, Cicchetti D, Becker B. The Construct of Resilience: A Critical Evaluation and Guidelines for Future Work. Child Dev. 2000;71(3):543–62.

    Article  CAS  Google Scholar 

  27. Vella S-LC, Pai NB. A theoretical review of psychological resilience: Defining resilience and resilience research over the decades. Arch Med Health Sci. 2019;7(2):233.

    Article  Google Scholar 

  28. Cohen M, Baziliansky S, Beny A. The association of resilience and age in individuals with colorectal cancer: an exploratory cross-sectional study. J Geriatr Oncol. 2014;5(1):33–9 (PubMed PMID: 24484716. Epub 20130910. eng).

    Article  Google Scholar 

  29. Linnemann P, Wellmann J, Berger K, Teismann H. Effects of age on trait resilience in a population-based cohort and two patient cohorts. J Psychosom Res. 2020;136:110170 (PubMed PMID: 32623191. Epub 20200612. eng).

    Article  Google Scholar 

  30. Weitzel EC, Glaesmer H, Hinz A, Zeynalova S, Henger S, Engel C, et al. What Builds Resilience? Sociodemographic and Social Correlates in the Population-Based LIFE-Adult-Study. Int J Environ Res Public Health. 2022;19(15):1–11. PubMed PMID: 35954965. Pubmed Central PMCID: PMC9368156. Epub 20220804. eng.

  31. Campbell-Sills L, Forde DR, Stein MB. Demographic and childhood environmental predictors of resilience in a community sample. J Psychiatr Res. 2009;43(12):1007–12 (PubMed PMID: 19264325. Epub 20090304. eng).

    Article  Google Scholar 

  32. Chernova A, Frajo-Apor B, Pardeller S, Tutzer F, Plattner B, Haring C, et al. The Mediating Role of Resilience and Extraversion on Psychological Distress and Loneliness Among the General Population of Tyrol, Austria Between the First and the Second Wave of the COVID-19 Pandemic. Front Psychiatry. 2021;12:766261 (PubMed PMID: 34777068. Pubmed Central PMCID: PMC8578839. Epub 20211027. eng).

    Article  Google Scholar 

  33. Kocalevent R-D, Zenger M, Heinen I, Dwinger S, Decker O, Brähler E. Resilience in the General Population: Standardization of the Resilience Scale (RS-11). PLoS ONE. 2015;10(11):e0140322.

    Article  Google Scholar 

  34. Singh R, Mahato S, Singh B, Thapa J, Gartland D. Resilience In Nepalese Adolescents: Socio-Demographic Factors Associated With Low Resilience. J Multidiscip Healthc. 2019;12:893–902 (PubMed PMID: 31806987. Pubmed Central PMCID: PMC6844232. Epub 2019/12/07. eng).

    Article  Google Scholar 

  35. Ang SY, Uthaman T, Ayre TC, Mordiffi SZ, Ang E, Lopez V. Association between demographics and resilience - a cross-sectional study among nurses in Singapore. Int Nurs Rev. 2018;65(3):459–66 (PubMed PMID: 29517143. Epub 20180308. eng).

    Article  CAS  Google Scholar 

  36. Perna L, Mielck A, Lacruz ME, Emeny RT, Holle R, Breitfelder A, et al. Socioeconomic position, resilience, and health behaviour among elderly people. Int J Public Health. 2012;57(2):341–9 (PubMed PMID: 21912944. Epub 20110913. eng).

    Article  Google Scholar 

  37. Friborg O, Hjemdal O, Rosenvinge JH, Martinussen M. A new rating scale for adult resilience: what are the central protective resources behind healthy adjustment? Int J Methods Psychiatr Res. 2003;12(2):65–76 (PubMed PMID: 12830300. Pubmed Central PMCID: PMC6878238. Epub 2003/06/28. eng).

    Article  Google Scholar 

  38. Smith BW, Dalen J, Wiggins K, Tooley E, Christopher P, Bernard J. The brief resilience scale: Assessing the ability to bounce back. Int J Behav Med. 2008;15(3):194–200.

    Article  Google Scholar 

  39. Ahangarzadeh Rezaei S, Rasoli M. Psychometric properties of the Persian version of "Connor-Davidson Resilience Scale" in adolescents with cancer. J Urmia Nurs Midwife Fac. 2015;13(9 (74)).

  40. Ahern NR. Adolescent Resilience: An Evolutionary Concept Analysis. J Pediatr Nurs. 2006;21(3):175–85.

    Article  Google Scholar 

  41. Yu X-n, Lau JTF, Mak WWS, Zhang J, Lui WWS, Zhang J. Factor structure and psychometric properties of the Connor-Davidson Resilience Scale among Chinese adolescents. Compr Psychiatry. 2011;52(2):218–24.

    Article  Google Scholar 

  42. Gillespie BM, Chaboyer W, Wallis M. The influence of personal characteristics on the resilience of operating room nurses: A predictor study. Int J Nurs Stud. 2009;46(7):968–76.

    Article  Google Scholar 

  43. Wu L, Tan Y, Liu Y. Factor structure and psychometric evaluation of the Connor-Davidson resilience scale in a new employee population of China. BMC Psychiatry. 2017;17(1):49.

    Article  Google Scholar 

  44. Lamond AJ, Depp CA, Allison M, Langer R, Reichstadt J, Moore DJ, et al. Measurement and predictors of resilience among community-dwelling older women. J Psychiatr Res. 2008;43(2):148–54.

    Article  Google Scholar 

  45. Yu X, Zhang J. Factor analysis and psychometric evaluation of the Connor-Davidson Resilience Scale (CD-RISC) with Chinese people. Soc Behav Personal Int J. 2007;35(1):19–30.

    Article  Google Scholar 

  46. Karaırmak Ö. Establishing the psychometric qualities of the Connor-Davidson Resilience Scale (CD-RISC) using exploratory and confirmatory factor analysis in a trauma survivor sample. Psychiatry Res. 2010;179(3):350–6.

    Article  Google Scholar 

  47. Jorgensen IE, Seedat S. Factor structure of the Connor-Davidson Resilience Scale in South African adolescents. Int J Adolesc Med Health. 2008;20(1):23–32.

    Article  Google Scholar 

  48. Green KT, Hayward LC, Williams AM, Dennis PA, Bryan BC, Taber KH, et al. Examining the Factor Structure of the Connor-Davidson Resilience Scale (CD-RISC) in a Post-9/11 U.S. Military Veteran Sample. Assessment. 2014;21(4):443–51.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Dr. Elham Akhlaghi and the Mazandaran University of Medical Sciences.

Funding

This study was had no funder.

Author information

Authors and Affiliations

  1. Traditional and Complementary Medicine Research Center, Addiction Institute, Mazandaran University of Medical Sciences, Sari, Iran

    Hamid Sharif Nia

  2. Faculty of Business, Design and Arts, Swinburne University of Technology, Sarawak, Malaysia

    Long She

  3. Department of Physiological Nursing, Schools of Nursing, Department of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, CA, 94143-0610, USA

    Erika Sivarajan Froelicher

  4. William James Centre for Research. ISPA - Instituto Universitário, Lisbon, Portugal

    João Marôco

  5. Faculty of Health, Social Determinants of Health Research Centre, Birjand University of Medical Sciences, Ghaffari Street, Birjand, Iran

    Mozhgan Moshtagh

  6. Department of Nursing, Bojnurd Faculty of Nursing, North Khorasan University of Medical Sciences, Shahriar Street, Bojnurd, North Khorasan, Iran

    Sima Hejazi

Authors
  1. Hamid Sharif Nia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Long She
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erika Sivarajan Froelicher
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. João Marôco
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mozhgan Moshtagh
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sima Hejazi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

HShN led the conceptualization, designing and data collection of the study. HShN, LS and JM analyzed data. HShN and ESF substantively revised the study. MM and SH wrote the first draft of the manuscript and HShN, LS, ESF and JM critically reviewed and provided comments to improve it. All Authors read and approved the final manuscript and have agreed on both to be personally accountable for the author's contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. All authors have read and approved the manuscript.

Corresponding authors

Correspondence to Mozhgan Moshtagh or Sima Hejazi.

Ethics declarations

Ethics approval and consent to participate

The questionnaires were completed anonymously, and the participants were assured about the confidentiality of their information. Informed consent was obtained from all subjects or their legal guardian. All methods were performed in accordance with the relevant guidelines and regulations. The Ethics Committee of Mazandaran University of Medical Sciences (IR.MAZUMS.REC.1401.238) approved this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sharif Nia, H., She, L., Froelicher, E.S. et al. Psychometric evaluation of the Connor-Davidson Resilience Scale among Iranian population. BMC Psychiatry 23, 92 (2023). https://doi.org/10.1186/s12888-023-04580-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12888-023-04580-8

Keywords

  • Psychological resilience
  • Questionnaire design
  • Connor-Davidson Resilience Scale
  • Psychometric
  • Iran

BMC Psychiatry

ISSN: 1471-244X

Contact us