An Introduction of Quality Classification Tool for Qualitative Evidence—CERQual_Chinese Journal of Evidence-Based Medicine

Authors：

 BAIZheng-gang ^1,2 ^# ,  LIUShao-kun ^1,3 ^# , HUANGChong-fei ^1,2 , CHANGJian-bo ¹ , ZENGXian-tao ^4,5 , WANGQi ¹ , JINYing-hui ^6,7 , CHENYao-long ^1,2 ,  YANGKe-hu ^1,2

1. Evidence-Based Medicine Center of Lanzhou University, Key Laboratory of EBM & Clinical Transformation of Gansu Province, Lanzhou 730000, China;
2. School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China;
3. School of Public Health, Lanzhou University, Lanzhou 730000, China;
4. Center for Evidence-based and Translational Medicine, Zhongnan Hospital, Wuhan University, Wuhan 430071, China;
5. Center for Evidence-Based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China;
6. School of Nursing, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China;
7. Center for Evidenced-based Nursing, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China;

Corresponding author：

YANGKe-hu, Email: yangkh@lzu.edu.cn

Keywords：

Qualitative systematic review; Evidence classification; CERQual

DOI：

10.7507/1672-2531.20150238

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To meet the evidence users' requirement for qualitative systematic review, it is necessary to establish an evidence classification system for it. The Confidence of the Evidence from Reviews of Qualitative research (CERQual) approach was developed for evidence classification of qualitative systematic review. Four components contribute to the assessment in CERQual: (1) Methodological limitations: Refer to problems in the design or conduct of the primary studies which need to be evaluated by specific tools used for methodological assessment of qualitative research. (2) Relevance: Relevance is the extent to which the objective, population etc. of included studies are applicable to the review question. (3) Coherence: It is the extent to which the review finding is consistent with the results in primary studies or the patterns, differences across primary studies, were explained reasonably. (4) Adequacy of data: Refer to the degree of richness and quantity of data supporting a review finding. Finally, integrate each of the components and rate the confidence of individual review finding as high, moderate, low or very low confidence. CERQual provides a transparent method for assessing the confidence of evidence from reviews of qualitative research. It may facilitate the use of qualitative research in evidence-informed decision making and guideline development processes. This article will introduce CERQual approach in detail and give an example to explain how to use it.

Citation： BAIZheng-gang, LIUShao-kun, HUANGChong-fei, CHANGJian-bo, ZENGXian-tao, WANGQi, JINYing-hui, CHENYao-long, YANGKe-hu. An Introduction of Quality Classification Tool for Qualitative Evidence—CERQual. Chinese Journal of Evidence-Based Medicine, 2015, 15(12): 1465-1470. doi: 10.7507/1672-2531.20150238 Copy

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2. Tong A, Flemming K, McInnes E, et al. Enhancing transparency in reporting the synthesis of qualitative research:ENTREQ. BMC Med Res Methodol, 2012, 12:181.
3. Hannes K, Booth A, Harris J, et al. Celebrating methodological challenges and changes:reflecting on the emergence and importance of the role of qualitative evidence in Cochrane reviews. Syst Rev, 2013, 2:84.
4. 刘建平. 定性研究与循证医学. 中国中西医结合杂志, 2008, 28(2): 165-167.
5. Lewin S, Glenton C, Noyes J, et al. CerQual approach:assessing How much certainty to place in findings from qualitative evidence syntheses. 21st Cochrane Colloquium. Quebec, Canada, 2013.
6. World Health Organization. WHO Recommendations:Optimizing Health Worker Roles to Improve Access to Key Maternal and Newborn Health Interventions Through Task Shifting. Geneva: World Health Organization, 2012.
7. Bohren MA, Hunter EC, Munthe-Kaas HM, et al. Facilitators and barriers to facility-based delivery in low-and middle-income countries:a qualitative evidence synthesis. Reprod Health, 2014, 11(1):71.
8. Glenton C, Colvin CJ, Carlsen B, et al. Barriers and facilitators to the implementation of lay health worker programmes to improve access to maternal and child health:qualitative evidence synthesis. Cochrane Database Syst Rev, 2013, 10:CD010414.
9. Colvin CJ, de Heer J, Winterton L, et al. A systematic review of qualitative evidence on barriers and facilitators to the implementation of task-shifting in midwifery services. Midwifery, 2013, 29(10):1211-1221.
10. Lewin S, Glenton C, Munthe-Kaas H, et al. Using Qualitative Evidence in Decision Making for Health and Social Interventions: An Approach to Assess Confidence in Findings from Qualitative Evidence Syntheses (GRADE-CERQual). PLoS Med, 2015, 12(10): e1001895.
11. Guyatt GH, Oxman AD, Kunz R, et al. What is "quality of evidence" and why is it important to clinicians? BMJ, 2008, 336(7651):995-998.
12. Atkins D, Best D, Briss PA, et al. Grading quality of evidence and strength of recommendations. BMJ, 2004, 328(7454):1490.
13. Goldsmith MR, Bankhead CR, Austoker J. Synthesising quantitative and qualitative research in evidence-based patient information. J Epidemiol Community Health, 2007, 61(3):262-270.
14. Critical Appraisal Skills Programme (CASP). QualitativeAppraisal Checklist for Qualitative Research. Available at:http://www.casp-uk.net/.
15. Government Chief Social Researcher's Office. Quality in Qualitative Evaluation:A framework for assessing research evidence. United Kingdom:Cabinet Office, 2003.
16. Ponterotto JG. Brief Note on the Origins, Evolution, and Meaning of the Qualitative Research Concept Thick Description. Qual Rep, 2006, 11(3):538-549.
17. Suri H. Purposeful sampling in qualitative research synthesis. Qual Rep, 2011, 11(2):63-75.
18. Bowen GA. Naturalistic inquiry and the saturation concept:a research note. Qual Rep, 2008, 8(1):137-152.
19. Francis JJ, Johnston M, Robertson C, et al. What is an adequate sample size? Operationalising data saturation for theory-based interview studies. Psychol Health, 2010, 25(10):1229-1245.
20. Guest G, Bunce A, Johnson L. How many interviews are enough? An experiment with data saturation and variability. Field methods, 2006, 18(1):59-82.
21. O'Reilly M, Kiyimba N. 'Unsatisfactory Saturation':a critical exploration of the notion of saturated sample sizes in qualitative research. Qual Rep, 2013, 13(2):190-197.
22. Bohren MA, Vogel JP, Hunter EC, et al. The Mistreatment of Women during Childbirth in Health Facilities Globally:A MixedMethods Systematic Review. PLoS Med, 2015, 12(6):e1001847.
23. Available at:http://gradeworkinggroup.org/toolbox/index.htm.
24. 于河, 刘建平. 定性研究方法及其在医学领域内的应用. 循证医学, 2008(5):292-296, 300.

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