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Abstract

BACKGROUND

Critical thinking is a core goal of medical education, underpinning clinical decision-making and scientific innovation. This study evaluates the current status of the disposition toward critical thinking among postgraduate medical students who intend to pursue careers in clinical practice, research, or public health leadership, and identifies factors associated with its variability.

METHODS

Using convenience and snowball sampling, we conducted a cross-sectional survey using the Short-Form Critical Thinking Disposition Inventory-Chinese Version (SF-CTDI-CV). Participants were medical postgraduate students from 16 universities in China, including Sichuan University, Chongqing Medical University and so on. Univariate analyses and multivariable linear regression with stepwise selection were carried to evaluate associations between SF-CTDI-CV scores and demographics, academic engagement, and training exposures.

RESULTS

The mean SF-CTDI-CV score was 81.8 (SD = 11.44; possible range: 18-108), indicating a generally positive disposition among the participants. Multiple regression analysis revealed that several factors significantly influence critical thinking disposition, including extracurricular reading time, academic ranking, papers read in depth per week, working hours, pre-enrollment background, participation in innovation and entrepreneurship competitions, attendance at academic conferences, Only-child status and frequency of research presentations (model R² = 0.102). Subgroup comparisons indicated that students who are only children, have professional or research experience, and possess a science background tend to achieve higher scores in critical thinking disposition assessments.

CONCLUSIONS

In this study, the Chinese SF-CTDI-CV was used to measure critical thinking disposition. The mean score of 82 (out of 108) indicates a generally positive disposition toward critical thinking among participants. Extracurricular reading time, academic ranking, and research engagement (including papers read, conference attendance, and research presentations) were independently associated with disposition scores. These findings suggest that educational strategies promoting deep reading, research involvement, and academic discussion may help foster critical thinking disposition in postgraduate medical education.

Keywords

critical thinking disposition curriculum postgraduate academic engagement SF-CTDI-CV

Introduction

The term “critical thinking” derives from the Greek “kritikos,” which means discernment, insight, and judgment.¹ It denotes the disciplined appraisal of thought against explicit standards, including clarity, accuracy, precision, consistency, relevance, credible evidence, depth, breadth, and fairness.² Practice involves discerning information, questioning assumptions, analyzing arguments, critiquing evidence, and reflecting on reasoning. These processes strengthen learning, foster innovation, and enhance practical problem-solving. In contemporary contexts, critical thinking also advances youth development, civic responsibility, and professional engagement.³

Global consensus holds that undergraduate medical education must keep pace with evolving healthcare demands.⁴ Accumulating evidence also indicates discipline-specific differences in how critical thinking is assessed among nursing and midwifery undergraduates and pharmacy undergraduates.^5,6 Structured scientific research training mitigates these gaps. It challenges fixed cognitive schemas, fosters inquiry and reflection, and strengthens critical thinking. In turn, it improves students’ capacity to address complex clinical problems and promotes medical innovation.⁷

In this study, we investigate postgraduate medical students (master or above) enrolled at universities in China. This rigorously selected cohort has strong theoretical training and constitutes the pipeline for national clinical care, biomedical research, and public health leadership. Thus, profiling their critical thinking is prospectively important for improving medical education quality and health system performance. By investigating the status and influencing factors of critical thinking disposition among postgraduate medical students at universities in China, this study aims to inform targeted educational measures to enhance critical thinking in postgraduate medical students.

Methods

Participants and Sampling

We conducted a cross-sectional online survey from December 2021 to January 2022 using convenience and snowball sampling. Participants were medical students from 16 institutions, including Sichuan University, Chongqing Medical University and so on. Participant inclusion criteria were as follows: (1) currently majoring in medicine and (2) holders of an undergraduate degree or higher. The Ethics Committee of West China Hospital approved the study (No. 2019-980). All students received study information and provided electronic informed consent.

To mitigate selection bias, we employed a multi-center recruitment strategy involving 16 universities across different regions of China. This diverse sampling frame was intended to capture a broad spectrum of postgraduate medical students with varying academic and demographic backgrounds. Additionally, the survey was advertised through multiple channels (eg, university bulletin boards, WeChat groups, departmental emails) to reach a wider and more varied pool of potential participants.

In total, 1477 students participated (969 females; 508 males). The average completion time was 8 min. The study flowchart summarizing design, recruitment, measures, and analysis is shown in Figure 1.

Figure 1.

Flowchart.

Measures

We assessed the level of critical thinking disposition and its potential determinants among postgraduate medical students. The questionnaire comprised three sections: (1) Basic characteristics (including sex, age, pre-enrollment background, and Work experience); (2) The Short-Form Critical Thinking Disposition Inventory—Chinese Version (SF-CTDI-CV); and (3) Self-developed influencing factors, which included items derived from research reviews and were grouped a priori into three domains: ①Demographic and family factors (eg, age, household registration, only-child status); ②Academic achievement and cognitive engagement (eg, academic ranking, extracurricular reading); and ③Research and practical participation (eg, number of articles read in depth per week, attendance at academic conferences, frequency of research presentations, and participation in innovation and entrepreneurship competitions).

The Short-Form Critical Thinking Disposition Inventory—Chinese Version

Critical thinking disposition was assessed with the SF-CTDI-CV developed and validated by Hwang.⁸ It comprises 18 items across three subscales: systematic analysis (Q1-Q5), thinking within the box (Q6-Q13), and thinking outside the box (Q14-Q18). The systematic analysis subscale assesses an individual's tendency to approach problems in an organized, logical, and analytical manner. The thinking within the box subscale (reverse-coded) measures the disposition to rely on conventional thinking, avoid intellectual challenges, and defer to authority, reflecting a closed-minded approach to reasoning. The thinking outside the box subscale evaluates the inclination toward intellectual curiosity, openness to new ideas, and enjoyment of complex problem-solving. Responses are rated on a six-point Likert scale (1 = strongly disagree to 6 = strongly agree).Total scores range from 18 to 108; scores ≥62 indicate a positive critical thinking disposition. In the present study, the SF-CTDI-CV demonstrated good internal consistency, with a Cronbach's α of 0.87.

Statistical Analysis

We employed analysis of variance for univariate comparisons of critical thinking disposition scores. Subsequently, this study applied multiple linear regression with stepwise selection to identify independent factors associated with critical thinking disposition. Stepwise multiple linear regression (with both forward selection and backward elimination) was used to identify independent factors associated with critical thinking disposition. Variables with P < .10 in univariate analyses were entered into the initial model, along with a priori variables of theoretical interest (eg, age, sex, only-child status). The stepping criteria were as follows: probability of F to enter ≤0.05 and probability of F to remove ≥0.10. Statistical significance was set at α=0.05. As a sensitivity analysis, we also performed binary logistic regression using a dichotomized outcome variable (good disposition: score ≥62 vs poor disposition: score <62) to examine the robustness of the findings from the linear regression model (see Supplemental Material Table 3).

Results

Basic Characteristics of Respondents

Among the 1477 participants, 34.4% were male. The mean age was 26.6 years, and 41.4% were aged 24-26 years. Before enrollment, 96.8% had a science background; 71.8% reported no prior work experience; and 78.3% majored in clinical medicine. Academic and professional degree tracks were approximately balanced. In total, 61.5% held non-agricultural household registration, 39.93% reported parental education at junior high school or below, and 48.5% were only children. Overall, 1436 students (97.22%) achieved a critical thinking score ≥62, with a mean of 81.8 ± 11.44, indicating a generally positive disposition.

Regarding self-reported academic engagement, 45.1% ranked within the 25%-50% of their cohort. Nearly half (49.8%) read 1-2 papers read in depth per week, and 56.4% devoted ≤7 h per week to extracurricular reading. Most had not participated in innovation or entrepreneurship competitions (68.6%) and had not applied for research projects (62.2%). In contrast, 40.1% had authored 1-2 first-author publications. More than half (54.5%) presented at research training sessions 1-2 times per month. Interdisciplinary practice occurred 1-2 times per year for 44.5% of students, and 61.3% attended major academic conferences 1-2 times per year.

Factors Associated with Critical Thinking Disposition

Univariate analyses (Table 1) identified significant differences in critical thinking scores across multiple characteristics (P < .05). Age, pre-enrollment academic background, Work experience, household registration, and only-child status were associated with score variation. The 27-29-year group had the highest mean score (82.9 ± 11.73). Students with a science background outperformed those with a humanities-social science background. Scores declined initially and then increased with longer work experience, peaking in those with >5 years (84.9 ± 12.76). Non-agricultural household registration and only-child status were each linked to higher scores.

Table 1.

One-Way ANOVA of Factors Associated with Critical Thinking Disposition.

Variables	n(%）	Critical Thinking Score Mean (SD)	F	P
Sex			0.078	.781
Female	508 (34.4)	81.7（12.35）
Male	969 (65.6)	81.8（10.94）
Age			3.143	.024
18-23	254 (17.2)	81.2（11.26）
24-26	612 (41.4)	80.9（10.98）
27-29	355 (24.0)	82.9（11.73）
≥30	256 (17.3)	82.8（12.12）
Pre-enrollment academic background			9.725	.002
Science background	1429 (96.8)	82.0（11.41）
Humanities-social science background	48 (3.2)	76.7（11.22）
Work experience (years)			3.418	.017
none	1060 (71.8)	81.6（11.3）
≤3	247 (16.7)	81.1（11.08）
3-5	64 (4.3)	83.2（12.23）
≥5	106 (7.2)	84. 9（12.76）
University(highest-degree institution)			2.65	.071
Double first-class university	1409 (95.4)	81.9（11.43）
First-class discipline university	4 (0.3)	70.8（10.14）
Other universities	64 (4.3)	80.1（11.38）
Major			0.248	.911
Clinical medicine	1156 (78.3)	81.7（11.57）
Medical technology	58 (3.9)	82.2（11.95）
Integrative medicine (TCM & Western)	28 (1.9)	80.4（10.96）
Nursing	93 (6.3)	82.5（11.08）
Other (interdisciplinary)	142 (9.6)	82.0（10.56）
Degree type			3.577	.059
Academic degree	756 (51.2)	82.3（11.56）
Professional degree	721 (48.8)	81.2（11.29）
Household registration
Agricultural	568 (38.5)	80.6（11.13）	10.81	.001
Non-agricultural	909 (61.5)	82.6（11.57）
Highest parental degree
Postgraduate or higher	63 (4.3)	80.8（12.76）	2.318	.074
Bachelor/Associate	403 (27.3)	82.9（11.79）
High school/Vocational	431 (29.2)	81. 9（11.42）
Junior high or below	580 (39.3)	81.0（11.01）
Only-child status			6.253	.013
Yes	716 (48.5)	82.6（11.61）
No	761 (51.5)	81.1（11.24）
Academic ranking			18.431	<.001
Top 25%	533 (36.1)	84.3（11.61）
25%-50%	666 (45.1)	81.1（11.18）
50%-75%	219 (14.8)	79.5（10.34）
Bottom25%	59 (4)	75.6（11.79）
Papers read in depth（/week)			21.009	<.001
≤1	243 (16.5)	77.4（11.18）
1-2	735 (49.8)	81.6（10.84）
3-4	294 (19.9)	84.0（10.91）
≥5	205 (13.9)	84.6（12.90）
Extracurricular reading time（/week)			23.101	<.001
Almost none	297 (20.1)	77.8（11.05）
≤7 h	833 (56.4)	81.9（10.89）
7-14 h	251(17)	85.5（11.26）
≥14 h	96 (6.5)	83.8（13.80）
Participation in innovation and entrepreneurship competitions			1.465	.222
0	1013 (68.6)	81.7（11.09）
1-2	367 (24.8)	82.1（11.87）
3-4	74 (5)	82.5（12.72）
≥5	23 (1.6)	77.1（14.79）
Applications for research projects (top-3 contributors)
0	919 (62.2)	81.4（10.76）	1.897	.128
1-2	420 (28.4)	82.1（12.09）
3-4	102 (6.9)	83.1（13.12）
≥5	36 (2.4)	85.0（14.72）
First-author publications			10.962	<.001
0	392 (26.5)	80.0（10.35）
1-2	592 (40.1)	81.2（11.71）
3-4	264 (17.9)	82.9（11.27）
≥ 5	229 (15.5)	85.1（11.96）
Interdisciplinary practice			9.508	<.001
0	615 (41.6)	80.9（10.74）
1-2	658 (44.5)	81.8（11.69）
3-4	140 (9.5)	82.8（12.20）
≥ 5	64 (4.3)	88.6（11.51）
Presentation frequency during research training（/month)			7.858	<.001
0	363 (24.6)	80.2（10.67）
1-2	805 (54.5)	81.5（11.33）
3-4	247 (16.7)	84.0（11.67）
≥ 5	62 (4.2)	85.5（14.19）
Attendance at academic conferences（/year)			12.827	<.001
0	215 (14.6)	78.2（11.23）
1-2	906 (61.3)	81.7（10.95）
3-4	261 (17.7)	84.5（11.60）
≥ 5	95 (6.4)	83.4（13.74）

ANOVA, analysis of variance.

Academic engagement showed consistent positive associations (P < .05). Higher academic ranking corresponded to higher scores (top group: 84 ± 11.6). Reading more papers in-depth per week and spending more time on extracurricular reading were each associated with higher scores. Participation in manuscript writing, involvement in interdisciplinary activities, more frequent presentations at research training sessions, and more frequent attendance at major academic conferences were also associated with higher critical thinking scores.

Stepwise multiple linear regression identified nine independent predictors of critical thinking scores (Table 2): extracurricular reading time, academic ranking, papers read in depth per week, working hours, pre-enrollment background, participation in innovation and entrepreneurship competitions, attendance at academic conferences, Only-child status and frequency of presentations during research training. The model explained 10.2% of the variance (adjusted R²=0.102) and was significant (F = 19.649, P < .01). Pairwise correlations among predictors are summarized in supplementary martial.

Table 2.

Multivariate Linear Regression of Factors Associated with Critical Thinking Disposition.

Independent Variable	β	95%CI	P
Extracurricular reading time	0.121	(1.015,2.501)	<.001
Academic ranking	−0.170	(−3.12,-1.692)	<.001
Papers read in-depth per week	0.112	(0.755,2.078)	<.001
Work experience	0.069	(0.247,1.568)	.007
Pre-enrollment academic background	−0.077	(−8.121,−1.854)	.002
Participation in innovation and entrepreneurship competitions	−0.087	(−2.413,−0.627)	.001
Attendance at academic conferences	0.068	(0.224,1.859)	.013
Only-child status	−0.056	(−2.409,−0.16)	.025
Presentation frequency during research training	0.054	(0.039,1.591)	.040

Note. Variance inflation factors (VIF) for all predictors in the final model were below 1.3, indicating no concerns regarding multicollinearity.

To assess the robustness of these findings, we conducted a sensitivity analysis using binary logistic regression with the critical thinking disposition score dichotomized at the established cutoff (≥62 indicating a positive disposition). Due to the highly imbalanced distribution (only 2.8% of participants scored below the cutoff), the full model including all nine predictors from the linear regression was estimated (presented in Supplemental Material Table 3). While most predictors did not achieve statistical significance in this analysis—likely due to limited statistical power—the direction of the odds ratios was consistent with the linear regression coefficients.

Discussion

China's medical education system endorses diversified assessment of learning outcomes. Contextualized, individualized, and multimodal evaluation of critical thinking disposition is therefore required to align with the New Medical Education initiative, Excellence in Medicine 2.0, and Healthy China.⁹ The SF-CTDI-CV demonstrated good internal consistency in our sample (Cronbach's α = 0.87), consistent with previous validation studies.⁸ This supports its use as a reliable instrument for assessing critical thinking disposition among postgraduate medical students. Localization of the instrument supports curriculum evaluation and pedagogical optimization, and provides an evidence base for reform in higher medical education.¹⁰

The mean critical thinking score was 81.8, indicating a generally positive disposition. Demographic factors showed limited overall influence. Because age correlated with academic year, we categorized age by common stages of medical training to reduce confounding. Scores followed a non-linear trajectory—an initial decline, a subsequent increase, and a later decline. This pattern is consistent with prior reports by Najafi¹¹ and Huang¹² but differs from findings by Pilevarzadeh.¹³ It is important to note that while our study and those by Najafi and Huang used instruments designed to measure disposition toward critical thinking (eg, the SF-CTDI-CV or CCTDI), Pilevarzadeh et al assessed a different facet of critical thinking, which may partly account for the divergent findings. We hypothesize that these discrepancies could be attributed to differences in measurement tools (disposition vs ability scales) and the distinct educational contexts across studies.¹⁴

The stepwise multiple linear regression explained 10.2% of the variance in critical thinking scores (R²=0.102). This magnitude is typical for cross-sectional behavioral research, where outcomes reflect many diffuse influences. Important determinants—such as developmental history, classroom microclimates, and personality—are not fully captured by self-report questionnaires. Nevertheless, the predictors retained in the model were statistically significant and practically meaningful. They highlight actionable targets for educational intervention and inform hypothesis generation for longitudinal studies.

Given the legacy of China's one-child policy, we included only-child status as a covariate. Only children scored higher on critical thinking disposition than non-only children, and the difference was statistically significant. This finding is consistent with Dang et al¹⁵ and accords with resource-allocation (resource dilution) perspectives, which posit greater parental investment in single-child families. Parenting style and socialization may further contribute. Single-child families often employ democratic, consultative parenting that encourages children to articulate their views, thereby supporting critical thinking development.¹⁶ The absence of siblings also increases early and frequent interactions with adults. These interactions provide richer linguistic input and cognitive stimulation, further promoting critical thinking.¹⁷ Work experience also showed a positive association. Longer weekly working hours correlated with higher critical thinking scores. These results support the value of experiential learning. In the process of cultivating students, incorporating structured work experience sharing and job-skills training into the curriculum can significantly enhance the development of critical thinking.¹⁸ The practical operation phase has been demonstrated to provide a platform for medical students to apply theoretical knowledge to real-world situations. In these settings, students engage in careful observation, analytical reasoning, and systematic problem-solving.¹⁹ During problem-solving, medical students are required to participate in continuous cognitive activities, deliberation, and introspection. These practices facilitate the enhancement of their critical thinking skills.

Students’ learning experiences and disciplinary environments strongly influence critical thinking development, and differences in critical thinking scores across academic majors have been documented in both health-professions and general undergraduate populations.^20,21 This disparity likely reflects differences in epistemic goals, methods of inquiry, and pedagogical styles between natural and social sciences. These patterns have clear instructional implications. Educators should adopt integrated curriculum frameworks, align outcomes with specific dimensions of critical thinking, and map disciplinary affordances to those dimensions. Deliberate sequencing of tasks, embedded formative assessment, and targeted remediation can address areas of relative weakness and improve instructional quality. Reading and writing are central levers. Extracurricular reading time is a robust correlate of critical thinking disposition performance, aligning with previous findings.^22,23 Engaging in structured, critical reading across diverse subject domains is recommended to strengthen nursing students’ critical thinking skills, in line with work emphasizing critical reading and evaluation of varied information sources in nursing education.¹ Accordingly, higher medical education should expand out-of-class learning, offer focused expert seminars, and promote interdisciplinary research practice to reinforce critical thinking skills.

Engaging in research is a significant predictor of students’ critical thinking skills. Empirical studies consistently support this relationship. For example, Shcheglova²⁴ reported that research participation enhances self-reported critical thinking. Qualitative investigations by Sahoo²⁵ and Yuan²⁶ further confirm that research activities foster core critical thinking abilities, including analysis, classification, and interpretation. Research involvement also strengthens critical thinking dispositions. As Yuan²⁶ noted, engagement in research projects promotes intellectual traits such as flexibility, adaptability, and openness. Formal research training systematically develops students’ intellectual curiosity, literature analysis, communication, and systematization skills. Among medical students, positive critical thinking levels have been observed in certain contexts,²¹ particularly following specific innovative assessments.²⁷ Programs like undergraduate innovation and entrepreneurship initiatives (“Da Chuang” projects) significantly enhance comprehensive competencies, including innovation, research, and teamwork. However, this study reveals a nuanced finding: students with extensive competition experience (five or more events) showed lower critical thinking disposition scores. This outcome does not invalidate competitions but suggests potential issues in their current structure or participation models. Several factors may explain this result. First, some students may participate primarily for credential-building, prioritizing resume entries over substantive intellectual engagement. Second, heavy competition commitments can reduce time for deep reading and reflection, which are essential for critical thinking development. Third, evaluation criteria may overemphasize project feasibility and presentation appeal at the expense of logical rigor and evidential depth. These findings suggest that educators should encourage meaningful, high-quality participation rather than frequent involvement.

Our findings reveal a non-linear trajectory in critical thinking disposition scores across different age groups (or academic stages), which both aligns with and diverges from previous research. The initial decline followed by a subsequent increase observed in our cohort is consistent with the longitudinal trends reported by Najafi et al among medical students in Iran,¹¹ and echoes the patterns identified in the mixed-methods study by Huang et al within the Chinese context.¹² However, our results contrast with those of Pilevarzadeh et al,¹³ who found no significant age-related differences among nursing students. We hypothesize that these discrepancies may be attributed to several interrelated factors. First, educational system and curricular design play a pivotal role; variations in the timing and integration of problem-based learning or research components across different institutions and countries can differentially stimulate critical thinking at various stages of training. Second, sociocultural context shapes learning dispositions; the emphasis on didactic teaching and examination performance in some Asian educational settings during early postgraduate years might temporarily suppress inquisitiveness, a phenomenon potentially less pronounced in other cultural contexts. Third, and most critically, differences in measurement tools must be considered. While our study and those by Najafi and Huang utilized instruments specifically designed to measure disposition towards critical thinking (eg, the SF-CTDI-CV or CCTDI), other studies, such as the one by Pilevarzadeh, may employ scales that assess different facets of critical thinking, making direct comparisons inherently complex. This underscores the need for future research to not only account for curricular and cultural variables but also to be precise about whether the outcome of interest is critical thinking ability or disposition.

Conclusions

This cross-sectional study suggests that critical thinking disposition among postgraduate medical students is shaped not only by demographics, but also by academic engagement, and training exposures. Based on the findings of this study, the following recommendations are proposed to enhance critical thinking disposition among medical students from diverse backgrounds: For students from low socioeconomic backgrounds and those who are not only children, it is essential to create more opportunities for academic expression and intellectual exchange through initiatives such as forming study groups and establishing regular reporting systems. Additionally, for all students, it is vital to encourage continuous and in-depth extracurricular reading, while optimizing the guidance mechanisms for innovation and entrepreneurship competitions, highlighting their crucial role as vehicles for mental training.

This study has certain limitations. First, the use of convenience and snowball sampling, combined with the inability to calculate a precise response rate, may have introduced selection bias. Furthermore, the predominance of participants from Double First-Class universities limits the generalizability of our results to other institutional contexts. Second, the cross-sectional design precludes any causal inferences regarding the relationships between the identified factors and critical thinking disposition. Third, it is important to note that the SF-CTDI-CV measures disposition toward critical thinking rather than critical thinking ability itself; therefore, our findings pertain specifically to dispositional tendencies. Fourth, reliance on self-reported data for both the outcome and predictor variables may be subject to recall and social desirability biases. Fifth, despite adjusting for a range of covariates, potential unmeasured confounders—such as personality traits, prior educational experiences, and detailed family socioeconomic status—may have influenced the observed associations. Finally, the highly skewed distribution of disposition scores (only 2.8% of participants scored below the cutoff) resulted in limited statistical power for sensitivity analyses using a dichotomized outcome. Future longitudinal and intervention studies are warranted to establish causal relationships and to explore the developmental trajectories of critical thinking disposition in more diverse medical education settings.

Supplemental Material

sj-docx-1-mde-10.1177_23821205261443552 - Supplemental material for Factors Associated with Critical Thinking Disposition in Postgraduate Medical Students: A Cross-sectional Study

Supplemental material, sj-docx-1-mde-10.1177_23821205261443552 for Factors Associated with Critical Thinking Disposition in Postgraduate Medical Students: A Cross-sectional Study by Jinfeng Chen, Chen Huang, Yuyuan Xiong, Lei Huang, Chenliang Zhang and Yan Huang in Journal of Medical Education and Curricular Development

Footnotes

Acknowledgements

We thank all the participating students in our study, as well as the investigators and staff, for their help and support.

ORCID iD

Yan Huang

Ethical Considerations

This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of West China Hospital, Sichuan University (Approval No. 2019-980).

Consent to Participate

Online informed consent was obtained from all participants prior to data collection. Confidentiality of participant information was maintained throughout the study.

Consent for Publication

Not applicable.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Science and Technology Achievement Transformation Fund of West China Hospital, Sichuan University under Grant (HX-H2406199).

Data Availability

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

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

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