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Do Scores on Three Commonly Used Measures of Critical Thinking Correlate With Academic Success of Health Professions Trainees? A Systematic Review and Meta-analysis

Ross, David MD; Loeffler, Kim MD; Schipper, Shirley MD; Vandermeer, Ben MSc; Allan, G. Michael MD

doi: 10.1097/ACM.0b013e31828b0823

Purpose To determine whether the three commonly used measures of critical thinking correlate with academic success of medical professionals in training.

Method The search for English-language articles (from 1980 to 2011) used Medline, Embase, Scopus, Cochrane Library on Ovid, Proquest Dissertations, Health and Psychosocial Instruments, PsychINFO, and references of included articles. Studies comparing critical thinking with academic success among medical professionals were included. Two authors performed study selection independently, with disagreement resolved by consensus. Two authors independently abstracted data on study characteristics, quality, and outcomes, with disagreement resolved by a third author. Critical thinking tests studied were the California Critical Thinking Skills Test (CCTST), California Critical Thinking Disposition Inventory (CCTDI), and Watson-Glaser Critical Thinking Appraisal. Correlation coefficients were pooled in meta-analysis.

Results The search identified 557 studies: 52 met inclusion for systematic review, 41 of which were meta-analyzed. Critical thinking was positively correlated with academic success, r = 0.31 (95% confidence intervals [CI] 0.26, 0.35), with a moderate statistical heterogeneity (I2 = 67%). In subgroup analysis, only student type had statistical significance for correlation, although bias was likely due to low numbers for some student types. In direct comparison, using studies that employed two critical thinking tests, the CCTDI (r = 0.23, 95% CI 0.15, 0.30) was significantly inferior (P < .001) to the CCTST (r = 0.39, 95% CI 0.33, 0.45).

Conclusions Critical thinking was moderately correlated with academic success of medical professionals in training. The CCTDI was inferior to the CCTST in correlating with academic success.

Dr. Ross is associate professor and assistant residency program director, Department of Family Medicine, University of Alberta Faculty of Medicine and Dentistry, Edmonton, Alberta, Canada.

Dr. Loeffler is assistant clinical professor, Department of Family Medicine, University of Alberta Faculty of Medicine and Dentistry, Edmonton, Alberta, Canada.

Dr. Schipper is associate professor and residency program director, Department of Family Medicine, University of Alberta Faculty of Medicine and Dentistry, Edmonton, Alberta, Canada.

Mr. Vandermeer is biostatistician, Alberta Research Centre for Health Evidence, Department of Pediatrics, University of Alberta Faculty of Medicine and Dentistry, Edmonton, Alberta, Canada.

Dr. Allan is associate professor and director of evidence-based medicine, Department of Family Medicine, University of Alberta Faculty of Medicine and Dentistry, Edmonton, Alberta, Canada.

Correspondence should be addressed to Dr. Allan, Department of Family Medicine, University of Alberta, Room 1706 College Plaza, 8215-112 Street, NW, Edmonton, Alberta, Canada T6G 2C8; telephone: (780) 248-2057; fax: (780) 492-8191; e-mail:

Education of health care practitioners is challenging and costly. To provide high-quality care and minimize errors, health care trainees must learn to perform data collection, clinical reasoning, and sensible management. A great deal of research has been completed to predict and identify trainees who may have difficulty during their education. Some of the previously evaluated predictors include admission tests,1 grade point averages (GPAs),2 socioeconomic characteristics,3 ethnicity,4 and gender.5 However, academic success is multifactorial, and more work is required to determine the factors involved.

An important element of both high-quality care and academic success is critical thinking. Critical thinking is the ability to identify a problem, select and evaluate pertinent information, recognize assumptions, formulate appropriate hypotheses, and draw valid conclusions and critical inferences.6,7 Although medical errors are unfortunately part of practice, clinicians and educators continually strive to reduce their frequency and severity. Mismanagement and diagnostic errors can arise from cognitive errors through incorrect information gathering, interpretation, and assessment.8 Critical thinking ability may help reduce these errors and improve care overall.8

Critical thinking is a highly valued educational outcome throughout the educational spectrum, but particularly in relation to higher and professional education.9 Critical thinking, particularly clinical reasoning, is felt to be an instrumental clinical skill. It has been proposed that critical thinking may improve diagnostic skills and reduce errors in management.8

Studies that examine critical thinking in correlating with academic success in health care trainees have provided conflicting results.10,11 A systematic review of the evidence would help to clarify the issue but has not been done to date. Our objective was to carry out such a review. Specifically, our goal was to determine whether the literature indicates that three commonly used measures of critical thinking correlate with academic success in medical professionals in training.

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Three Commonly Used Measures of Critical Thinking

Critical thinking encompasses six core competencies, which are interpretation, analysis, evaluation, inference, explanation, and self- regulation.12 Several validated tools can measure critical thinking, including the California Critical Thinking Skills Test (CCTST), California Critical Thinking Disposition Inventory (CCTDI), and Watson-Glaser Critical Thinking Appraisal (WGCTA). These validated tools were developed by national experts in critical thinking, are easy to administer, and require minimal time to complete.

The CCTST is a 34-item multiple-choice question quiz, generating six total scores and five subscale scores. The CCTDI assesses the extent to which a person possesses the disposition of the ideal critical thinker and measures affective attitudinal dimensions of critical thinking. This tool has 75 items, generating a total score and seven subscale scores. The WGCTA has 80 items and produces a single score based on the assessment of five critical thinking skills.

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We performed and reported this systematic review according to Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines,13 augmented by the more updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses.14

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Search strategy

A medical research librarian performed all literature searches. The initial search of five databases was performed in June 2010: Medline (from 1950), Health and Psychosocial Instruments (from the beginning of the database), Cochrane Library (from the beginning of the database), Embase (from 1980), and PsychINFO (from 1987). Original search terms were California Critical Thinking Skills Test or CCTST or California Critical Thinking Disposition Inventory or CCTDI, with medic* or doctor* or resident or physician* combined for the PsychINFO database.

For our updated search in November 2011, we broadened our search to six databases: Medline (from 1980), Embase (from 1980), Scopus (from the beginning of the database), Cochrane Library on Ovid (from 1980), Proquest Dissertations (from the beginning of the database), and PsychINFO (from 1980). Updated search terms were California Critical Thinking or Watson Glaser or CCTST or CCTDI or WGCTA. We restricted our search to English-language articles and excluded studies before 1980. The comprehensive search terms and search strings are available from us on request. We also reviewed references from all included studies and contacted selected authors by e-mail.

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Study selection

We included studies in which critical thinking was compared with the academic success of medical professionals in training. Critical thinking could be assessed using the CCTST, CCTDI, or WGCTA. Academic success could be quantified using grades on specific tests or courses, GPAs, or certification exams. Medical professionals in training could include trainee physicians (medical students, residents, or house staff), nurses, dentists, dental assistants/hygienists, pharmacists, chiropractors, dieticians, nutritionists, respiratory technicians, occupational therapists, physiotherapists, physical therapists, emergency medicine technicians, psychotherapists, or veterinarians. We excluded studies with a mixture of students if medical professionals in training could not be separated from nonmedical students. We also excluded studies of undergraduate psychology students because many of these students do not become medical professionals.

Two of us (G.M.A. and S.S.) independently evaluated all identified studies for inclusion, and the two of us resolved any disagreement by consensus. We reviewed abstracts and titles initially and reviewed in full those articles identified for possible inclusion. We then calculated the agreement in study selection between the two independent reviewers.

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Data extraction

For all included studies, data were extracted on study citation (primary author, year published, journal title, volume, pages, journal/thesis), study location/years (country, state/province, urban/rural, years of study), participants (profession, training levels, gender, ethnicity, training site), study method (sample, mode by which the critical thinking test was administered), numbers (number sampled, response rate, number responding), critical thinking assessment (type of test or tests), academic assessment (type of grade/mark), comparison (primary analysis, result, significance, and secondary analysis, result, significance), subgroup findings, mean critical thinking scores, and comments.

All of us reviewed the first study together to confirm an understanding and agreement on the template for extraction. Two of us (D.R. and K.L.) independently completed data extraction on all remaining included studies using a data template created in Excel. We calculated the agreement in data extraction between the two independent reviewers. Another one of us (G.M.A.) resolved any disagreement.

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Risk of bias

There is controversy around quality and bias scoring systems for observational studies.13 For the primary analysis of quality, we assigned “higher risk of bias,” “lower risk of bias,” and “unclear” to the three study characteristics: response rate, sampling method, and mode by which the critical thinking test was administered. Response rates < 60% were assigned a higher risk of bias. Sampling methods using convenience sampling were assigned a higher risk of bias, whereas sampling the entire cohort or a random sample of the cohort was considered a lower risk of bias. Mode of administration of the critical thinking test was assigned a lower risk of bias if the administration of the test was most likely observed, such as in a preexisting class, face-to-face sessions, or a special session. We assigned a higher risk of bias if the tests were mailed to participants or if the test results were retrieved retrospectively.

Additionally, each characteristic was assigned 0 for low risk of bias and 1 for high risk of bias or unclear. Therefore, the quality score for each study could range from 0 to 3, with higher numbers indicating a higher risk of bias.

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The primary analysis included correlation statistics between critical thinking and academic success. When studies used both CCTST and CCTDI, we used CCTST for meta-analysis. When studies used both GPAs and certification results, we used GPAs for meta-analysis. It is well established that meta-analysis of correlations is more accurate on the Fisher z scale than on the actual correlations (r).15 To meta-analyze correlations, data were first converted into Fisher z scale, with variance of z being estimated as V = 1/(n − 3). Two studies did not report a final sample size. We computed the sample size of Allen and Bond16 using its reported P value, whereas the final sample size for Bauwens and Gerhard17 was estimated using its initial sample size multiplied by the average response rate of all the other studies.6,10,11,18–68 We used the DerSimonian-Laird random effects methods to come up with a pooled estimate and 95% confidence interval (CI) of the average Fisher z value across studies. Heterogeneity was assessed using the I2 statistic. We estimated statistical differences between subgroups using the chi-square test.

We examined and compared subgroups by student type (nurse, medical doctor, etc.), publication type (journal or thesis), risk of bias (high, moderate, low), type of critical thinking test (WGCTA, CCTST, CCTDI), year of publication (1981 to 1997, 1998 to present), and measure of academic success (course mark, GPA, certification exam). We also performed subgroup comparisons on studies using two or more critical thinking tests or measures of academic success. This allowed direct comparison of variables within the same studies, reducing bias between study comparisons. Pooled Fisher z values and their 95% CI were transformed back into correlation values (r).

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Figure 1 shows the search results and process of selecting the studies. The search located 557 studies after duplicates were removed. Fifty-six studies6,10,11,16–68 met inclusion, including 4 studies published as both journal articles and in thesis form, leaving 52 unique studies. Agreement by reviewers was 95% for study selection and 94% for data abstraction.

Figure 1

Figure 1

Table 1 shows the characteristics of the 52 included studies. Although 1 study16 did not include participant numbers, there were a total of 6,631 participants in the remaining 51 studies. Almost all studies were done in the United States (50 of 52). One of the remaining 2 was done in China,33 and the other was done in both Australia and the United States.27 Studies were of nursing, pharmacy, medical doctor, dental hygiene, physiotherapy, dentistry, and veterinarian students/trainees, with the majority of studies (41 of 52) being of nursing students. Thirty-five studies provided gender information, with 79% of participants being women.

Table 1

Table 1

Appendix 1 shows the quality assessment of included studies. There was a low risk of bias for sampling method in 28 studies (54%), for mode of critical thinking test administration in 28 studies (54%), and for response rate in 38 studies (73%). Overall, 12 studies (23%) had low risk of bias in all three areas. High or unclear risk of bias was found in two areas for 14 studies (27%) and in three areas for 4 studies (8%).

Appendix 1

Appendix 1

Eleven studies were not meta-analyzed, as 9 did not report correlation statistics and 253,60 did not provide adequate data for inclusion. Five of the 9 studies using t test, ANOVA, regression, chi-square, and ANCOVA reported statistically significant associations between critical thinking and academic success.

Figure 2 shows the primary meta-analysis of 41 studies using Pearson correlation (or Spearman correlation in 1 study). Critical thinking had a positive correlation to academic success, r = 0.31 (95% CI 0.26, 0.35), with a moderate statistical heterogeneity (I2 = 67%).

Figure 2

Figure 2

Figure 3 shows the subgroup and sensitivity meta-analysis. Because compared groups could include different studies, we considered these indirect comparisons. The correlation results did vary significantly by the type of student (subgroup difference, chi-square = 19.32, P = .002). This result should be interpreted with caution because three of the student types (dental hygienists, physiotherapists, and mixed) had only one study each, and the remaining three groups (doctors, pharmacists, and nurses) had overlapping CIs. Correlation results did not vary significantly by publication type, risk of bias, type of critical thinking test, year of publication, measure of academic success, or risk of bias. The subgroup differences were close to significant (P ≤ .1) for critical thinking test, year of publication, and measure of academic success.

Figure 3

Figure 3

Figure 4A shows the direct comparison of CCTST and CCTDI using the six studies that included both critical thinking tests. The correlation to academic success was higher for CCTST (r = 0.39, CI 0.33, 0.45) than CCTDI (r = 0.23, CI 0.15, 0.30), with a statistically significant subgroup difference (chi-square 11.93, P < .001). Figure 4B shows the direct comparisons of GPAs and certification exams in the five studies that used both outcomes. There were no differences between the correlations of critical thinking to certification exams or GPAs. Weighted mean scores of the CCTST, CCTDI, and WGCTA tests were 16.43, 310.13, and 55.40, respectively, across the studies.

Figure 4

Figure 4

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Critical thinking was moderately correlated to academic success of health care trainees (r = 0.31, CL 0.26, 0.35). The correlation was not influenced by the measure of academic success, study year, study quality, or type of publication. Although there were statistical differences in the correlations of critical thinking to academic success among different professions’ trainees, this was subject to a high risk of bias because many professions had only one study. For those professions with more than one study, the CI of the correlation overlapped substantially, suggesting no reliable difference.

The choice of critical thinking test was the only factor to statistically and meaningfully affect the correlation of critical thinking to academic success. In the primary comparison between studies, the correlations to academic success for CCTST (r = 0.30, CI 0.23, 0.37) and WGCTA (r = 0.33, CI 0.27, 0.38) were very similar. However, for the CCTDI, these values were lower (r = 0.21, CI 0.12, 0.30) than they were for both the CCTST and WGCTA, and the P value for comparisons, although not significant, suggests the trend to a statistical difference. In the direct comparison using studies that measured both CCTST and CCTDI, the values for CCTDI (r = 0.23, CI 0.15, 0.30) were inferior (P < .001) to those for CCTST (r = 0.39, CI 0.33, 0.45). Therefore, when trying to correlate academic success of health care trainees, CCTST (and likely WGCTA) are superior to CCTDI. CCTDI is likely inferior because it was developed to measure the disposition to think critically rather than the ability to think critically.

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Critical thinking and health care training programs

Health care training programs could use critical thinking in a number of ways. Scores on critical thinking tests could be used as part of admission criteria to help select candidates most likely to have academic success in the program. Scores could also be used to identify trainees in programs who are more likely to have difficulty succeeding academically. In that case, resources could be directed earlier to the identified trainees. Because the correlation is at best moderate, scores on critical thinking tests could not be used alone.

Other criteria that we found for predicting academic success (reported in studies that were not part of those found in our systematic review) include the student’s GPA prior to a medical program69,70 and scores on admission tests such as the Medical College Admission Test (MCAT)71 and the multiple mini-interviews (MMIs).72 These investigations were performed for nurses,70 dental hygienists,69 dentists,73 pharmacists,74 and medical doctors.71 In meta-analysis, MCAT scores correlated to preclinical (r = 0.39) and clinical (r = 0.34) GPAs.71 The prior GPA correlated to scores on Step 1 of the United States Medical Licensing Examination (r = 0.34) and to scores on Step 2 of that same examination (r = 0.36).75 The MMI correlated to scores on clinical skills exams, ranging from 0.36 to 0.43.72 In pharmacy, the GPA (r = 0.44) and the score on the Pharmacy College Admission Test (r = 0.32) correlated with academic success.74 Many of these correlation statistics are similar to the numbers found in this meta-analysis.

Most studies assessing variables that may be predictive of academic success have looked at only one variable or assessed variables individually. Studies assessing the contribution of a collection of variables in predicting academic success have found mixed results. For example, within pharmacy students, Kidd and Latif37 found that only CCTST (not admission exam, CCTDI, or essay score) contributed significantly to predicting clerkship GPA. Alternatively, McCall et al45 found that after admission exam, prepharmacy GPA, and age, CCTST did not significantly contribute to a model predicting academic success.

Furthermore, it is likely that some of the variables, like admission exams and critical thinking tests, assess similar characteristics. McCall et al45 found that CCTST correlated with pharmacy admission exam subscores. However, inconsistent results challenge interpretation. For example, Kuykendall39 examined predictors of success on the licensing exam for nurses from two colleges and found that WGCTA added little to the GPA for one school but was helpful for another. At present, information is limited, mixed, and conflicting about the relative importance of difference predictors and their overlap. Future researchers should explore these relationships further; hopefully, a more consistent pattern will emerge to determine the best possible mix of predictors.

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It is unusual that over half (56%) of the included studies came from gray literature (theses). However, sensitivity analysis showed that the results of these studies did not differ from those of published studies. Heterogeneity was high in most of the meta-analyses. Heterogeneity is expected among observational studies,13 and the large number of included studies increased it. We performed sensitivity analyses to explore possible causes of heterogeneity. Although we found that the critical thinking test contributed to heterogeneity, other results were less reliable. However, it is common for all causes of heterogeneity in observational studies to remain unclear, as explained in MOOSE guidelines for systematic review of observational studies.13

We did not perform correction or adjustment for the restricted range of participants (trainees). In most studies of correlations to academic success, study participants are in the professional program rather than from the applicant pool. Thus, the sample is a restricted subgroup and not necessarily representative of program applicants. When the objective is to assess a measure among applicants that could predict academic success in a program, the correlation should be adjusted for this restricted sample. Although some new studies have performed adjustments (e.g., see Meagher et al74), critical thinking studies included in this review have not. Meta-analyses of a predictive variable can also be adjusted (e.g., see Donnon et al71), but this change in correlation is small. We did not perform adjustments. First, we did not have complete information on some study populations. Second, our objective was not only to determine the correlation from applicant to academic success in the program alone but also to determine the correlation of critical thinking at any point (including within the program) to academic success. All adjustments increase the correlation, so the unadjusted correlations in our study are more conservative.

Acknowledgments: The authors would like to thank Sandy Campbell, medical librarian, for her assistance with our detailed search.

Funding/Support: None.

Other disclosures: None.

Ethical approval: Not applicable.

Previous presentations: Some of the findings of this study were presented to the residents and faculty in the Department of Family Medicine at the University of Alberta Faculty of Medicine and Dentistry on Family Medicine Research Day, June 8, 2012.

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