Cross-Cultural Adaptation and Validation of the 10-Item Conjoint Community Resiliency Assessment Measurement in a Community-Based Sample in Southwest China

Ke Cui , Ziqiang Han

International Journal of Disaster Risk Science ›› 2019, Vol. 10 ›› Issue (4) : 439 -448.

PDF
International Journal of Disaster Risk Science ›› 2019, Vol. 10 ›› Issue (4) : 439 -448. DOI: 10.1007/s13753-019-00240-2
Article

Cross-Cultural Adaptation and Validation of the 10-Item Conjoint Community Resiliency Assessment Measurement in a Community-Based Sample in Southwest China

Author information +
History +
PDF

Abstract

Community resilience has received growing attention in disaster risk management policies and practices, especially in China. However, few applicable instruments are available as a baseline for profiling and estimating a community’s resiliency in the face of disasters. The purpose of this study is to cross-culturally adapt and validate the original version of the 10-Item Conjoint Community Resiliency Assessment Measurement (CCRAM-10) in China. Our study further investigates if and to what extent community members translate their participation in disaster risk reduction (DRR) activities into perceived community resilience. A Chinese version of CCRAM-10 was generated and applied to 369 participants from a rural and an urban community in southwest China affected by the 2008 Wenchuan Earthquake. Internal consistency reliability and confirmatory factor analyses were performed to test the assessment instrument’s applicability. The Communities Advancing Resilience Toolkit Assessment Survey was used to establish the convergent validity for the Chinese version of CCRAM-10. Multiple linear regression models were used to explore the correlations between respondents’ participation in activities and their perception of community resilience, while controlling for basic socio-demographic variables. Analysis results demonstrated good internal consistency reliability (Cronbach’s alpha = 0.85) and satisfactory convergent validity for the Chinese version of the CCRAM-10. Construct validity was also confirmed (χ2/df = 2.161; CFI = 0.977; GFI = 0.971; NFI = 0.958; RMSEA = 0.056; SRMR = 0.030). The regression analysis results indicated that respondents’ participation in DRR activities was positively correlated with their perception of community resilience. This study contributes to the wider collection of disaster studies by providing a tested tool for assessing community resilience in the context of China. Community workers and practice researchers may be interested in applying CCRAM-10 to evaluate the effect of specific DRR programmatic activities for improving community resilience.

Keywords

Assessment survey / CCRAM-10 / China / Community resilience / Disaster risk management

Cite this article

Download citation ▾
Ke Cui, Ziqiang Han. Cross-Cultural Adaptation and Validation of the 10-Item Conjoint Community Resiliency Assessment Measurement in a Community-Based Sample in Southwest China. International Journal of Disaster Risk Science, 2019, 10(4): 439-448 DOI:10.1007/s13753-019-00240-2

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Aka FT, Buh GW, Fantong WY, Issa I, Zouh T, Djomou SLB, Ghogomu RT, Gibson T Disaster prevention, disaster preparedness and local community resilience within the context of disaster risk management in Cameroon. Natural Hazards, 2017, 86(1): 57-88

[2]

Baxter H. Creating the conditions for community resilience: Aberdeen, Scotland—An example of the role of community planning groups. International Journal of Disaster Risk Science, 2019, 10(2): 244-260

[3]

Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine, 2000, 25(24): 3186-3191

[4]

Bolarinwa O. Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Nigerian Postgraduate Medical Journal, 2015, 22(4): 195-201

[5]

Burton CG. A validation of metrics for community resilience to natural hazards and disasters using the recovery from hurricane Katrina as a case study. Annals of the Association of American Geographers, 2015, 105(1): 67-86

[6]

Cavallo A. Integrating disaster preparedness and resilience: A complex approach using System of Systems. Australian Journal of Emergency Management, 2014, 29(3): 46-51.

[7]

Cha BS, Lawrence RI, Bliss JC, Wells KB, Chandra A, Eisenman DP. The road to resilience: Insights on training community coalitions in the Los Angeles county community disaster resilience project. Disaster Medicine and Public Health Preparedness, 2016, 10(6): 812-821

[8]

Chan Eric K. H.. Standards and Guidelines for Validation Practices: Development and Evaluation of Measurement Instruments. Validity and Validation in Social, Behavioral, and Health Sciences, 2014, Cham: Springer International Publishing 9-24.

[9]

Chandra A, Williams M, Plough A, Stayton A, Wells KB, Horta M, Tang J. Getting actionable about community resilience: The Los Angeles county community disaster resilience project. American Journal of Public Health, 2013, 103(7): 1181-1189

[10]

Cohen J. Statistical power analysis for the behavioral sciences, 1988, Hillsdale, NJ: Routledge

[11]

Cohen O, Leykin D, Lahad M, Goldberg A, Aharonson-Daniel L. The conjoint community resiliency assessment measure as a baseline for profiling and predicting community resilience for emergencies. Technological Forecasting and Social Change, 2013, 80(9): 1732-1741

[12]

Cui Ke, Han Ziqiang, Wang Dongming. Resilience of an Earthquake-Stricken Rural Community in Southwest China: Correlation with Disaster Risk Reduction Efforts. International Journal of Environmental Research and Public Health, 2018, 15(3): 407

[13]

Cui K, Sim T. Older people’s psychosocial needs in a post-disaster rural community of China: An exploratory study. Natural Hazards, 2017, 85(3): 1577-1590

[14]

Cutter SL. The landscape of disaster resilience indicators in the USA. Natural Hazards, 2016, 80(2): 741-758

[15]

Cutter SL, Ash KD, Emrich CT. Urban—rural differences in disaster resilience. Annals of the American Association of Geographers, 2016, 106(6): 1236-1252

[16]

Cutter SL, Barnes L, Berry M, Burton C, Evans E, Tate E, Webb J. A place-based model for understanding community resilience to natural disasters. Global Environmental Change, 2008, 18(4): 598-606

[17]

Cutter, S.L., C.G. Burton, and C.T. Emrich. 2010. Disaster resilience indicators for benchmarking baseline conditions. Journal of Homeland Security and Emergency Management 7(1): Article 51.

[18]

Eisenman DP, Adams RM, Rivard H. Measuring outcomes in a community resilience program: A new metric for evaluating results at the household level. PLoS Currents, 2016

[19]

Han Z, Wang H, Du Q, Zeng Y. Natural hazards preparedness in Taiwan: A comparison between households with and without disabled members. Health Security, 2017, 15(6): 575-581

[20]

Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 1999, 6(1): 1-55

[21]

Hu M, Hao Y, Ning N, Wu Q, Han X, Zheng B, Yu Y, Chen Z. Reliability and validity of the communities advancing resilience toolkit (CART) Chinese version. Chinese Journal of Public Health, 2017, 33(5): 707-710 (in Chinese)

[22]

Kaufman EA, Xia M, Fosco G, Yaptangco M, Skidmore CR, Crowell SE. The difficulties in emotion regulation scale short form (DERS-SF): Validation and replication in adolescent and adult samples. Journal of Psychopathology and Behavioral Assessment, 2016, 38(3): 443-455

[23]

Lei Y, Wang J, Yue Y, Zhou H, Yin W. Rethinking the relationships of vulnerability, resilience, and adaptation from a disaster risk perspective. Natural Hazards, 2014, 70(1): 609-627

[24]

Leykin D, Lahad M, Cohen O, Goldberg A, Aharonson-Daniel L. Conjoint community resiliency assessment measure-28/10 items (CCRAM28 and CCRAM10): A self-report tool for assessing community resilience. American Journal of Community Psychology, 2013, 52(3–4): 313-323

[25]

Li X, Wang L, Liu S. Geographical analysis of community resilience to seismic hazard in southwest China. International Journal of Disaster Risk Science, 2016, 7(3): 257-276

[26]

Liebenberg L, Moore JC. A social ecological measure of resilience for adults: The RRC-ARM. Social Indicators Research, 2018, 136(1): 1-19

[27]

ODI (Overseas Development Institute) Pathways to earthquake resilience in China, 2015, London: Overseas Development Institute

[28]

Pfefferbaum, B., and C.S. North. 2016. Child disaster mental health services: A review of the system of care, assessment approaches, and evidence base for intervention. Current Psychiatry Reports 18(1): Article 5.

[29]

Pfefferbaum B, Weems CF, Scott BG, Nitiéma P, Noffsinger MA, Pfefferbaum RL, Varma V, Chakraburtty A. Research methods in child disaster studies: A review of studies generated by the September 11, 2001, terrorist attacks; the 2004 Indian Ocean tsunami; and hurricane Katrina. Child & Youth Care Forum, 2013, 42(4): 285-337

[30]

Pfefferbaum RL, Pfefferbaum B, Nitiéma P, Houston JB, Van Horn RL. Assessing community resilience: An application of the expanded CART survey instrument with affiliated volunteer responders. American Behavioral Scientist, 2015, 59(2): 181-199

[31]

Qin W, Lin A, Fang J, Wang L, Li M. Spatial and temporal evolution of community resilience to natural hazards in the coastal areas of China. Natural Hazards, 2017, 89(1): 331-349

[32]

Rapaport C, Hornik-Lurie T, Cohen O, Lahad M, Leykin D, Aharonson-Daniel L. The relationship between community type and community resilience. International Journal of Disaster Risk Reduction, 2018, 31: 470-477

[33]

Rocchi S, Ghidelli C, Burro R, Vitacca M, Scalvini S, Della Vedova AM, Roselli G, Ramponi J-P, Bertolotti G. The Walsh family resilience questionnaire: The Italian version. Neuropsychiatric Disease and Treatment, 2017, 13: 2987-2999

[34]

Schumacker RE, Lomax RG. A beginner’s guide to structural equation modeling, 2004 2 London: Lawrence Erlbaum

[35]

Sharifi A. A critical review of selected tools for assessing community resilience. Ecological Indicators, 2016, 69: 629-647

[36]

Shi, P., M. Wang, and Y. Qian. 2014. Achievements, experiences and lessons, challenges and opportunities for China’s 25-year comprehensive disaster reduction. Planet@Risk 2(5): 353–358, Special Issue for the Post-2015 Framework for DRR, Global Risk Forum GRF Davos, Davos. https://planet-risk.org/index.php/pr/article/view/130/257. Accessed 15 Nov 2019.

[37]

Smith GT, Combs JL, Pearson CM. Cooper H. Brief instruments and short forms. APA handbook of research methods in psychology, 2012, Washington, DC: American Psychological Association 395-409.

[38]

UNISDR (United Nations International Strategy for Disaster Reduction) Sendai framework for disaster risk reduction 2015–2030, 2015, Geneva: United Nations

[39]

Wang L, Shi Z, Zhang Y, Zhang Z. Psychometric properties of the 10-item Connor-Davidson Resilience Scale in Chinese earthquake victims. Psychiatry and Clinical Neurosciences, 2010, 64(5): 499-504

[40]

Wu G, Han Z, Xu W, Gong Y. Mapping individuals’ earthquake preparedness in China. Natural Hazards and Earth System Sciences, 2018, 18(5): 1315-1325

[41]

Xue X, Wang L, Yang RJ. Exploring the science of resilience: Critical review and bibliometric analysis. Natural Hazards, 2018, 90(1): 477-510

[42]

Yang S, He S, Du J, Sun XH. Screening of social vulnerability to natural hazards in China. Natural Hazards, 2015, 76(1): 1-18

[43]

Zheng B, Hao YH, Ning N, Xu WL, Hu M, Chen ZQ, Yu Y, Zhao XY. Community resilience to disaster risk in Sichuan Province of China: An analysis of TOPSIS. Chinese Journal of Public Health, 2017, 33(5): 699-702 (in Chinese)

AI Summary AI Mindmap
PDF

335

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/