Table_2_Development of social anxiety cognition scale for college students: Basing on Hofmann’s model of social anxiety disorder.docx

IntroductionTo develop the Chinese version of the Social Anxiety Cognition Scale for College Students (SACS-CS) based on Hofmann’s model of social anxiety disorder and examine its reliability and validity.MethodsBased on literature analysis and structured interviews, a theoretical model was constructed and behavioral examples were collected. According to the results of participants’ and experts’ evaluations, the initial SACS-CS was developed. The study data were collected from a total of 500 valid participants, randomly divided into two samples. Sample 1 (n = 200) and sample 2 (n = 300) were considered for exploratory factor analysis and confirmatory factor analysis (CFA), respectively. Internal reliability and validity were examined using all 500 participants, and temporal reliability was established using sample 3 (n = 70), who completed the scale again after 4 weeks.ResultsThe SACS-CS consists of 21 items, grouped under four factors: self-perception, social skills, emotional control, and cost estimation. The four-factor model fits well. The internal consistency coefficient of the scale and the four factors ranged from 0.87 to 0.96, and the test–retest reliability ranged from 0.76 to 0.84. The scores of the scale and the four factors were significantly correlated with the score of the Interaction Anxiousness Scale (r = 0.54–0.64).DiscussionThe SACS-CS possesses good reliability and validity and can be applied in the cognitive assessment of college students’ social anxiety. The scale could help people with different social anxiety disorder conditions receive more personalized interventions.</p

Table_1_Development of social anxiety cognition scale for college students: Basing on Hofmann’s model of social anxiety disorder.docx

IntroductionTo develop the Chinese version of the Social Anxiety Cognition Scale for College Students (SACS-CS) based on Hofmann’s model of social anxiety disorder and examine its reliability and validity.MethodsBased on literature analysis and structured interviews, a theoretical model was constructed and behavioral examples were collected. According to the results of participants’ and experts’ evaluations, the initial SACS-CS was developed. The study data were collected from a total of 500 valid participants, randomly divided into two samples. Sample 1 (n = 200) and sample 2 (n = 300) were considered for exploratory factor analysis and confirmatory factor analysis (CFA), respectively. Internal reliability and validity were examined using all 500 participants, and temporal reliability was established using sample 3 (n = 70), who completed the scale again after 4 weeks.ResultsThe SACS-CS consists of 21 items, grouped under four factors: self-perception, social skills, emotional control, and cost estimation. The four-factor model fits well. The internal consistency coefficient of the scale and the four factors ranged from 0.87 to 0.96, and the test–retest reliability ranged from 0.76 to 0.84. The scores of the scale and the four factors were significantly correlated with the score of the Interaction Anxiousness Scale (r = 0.54–0.64).DiscussionThe SACS-CS possesses good reliability and validity and can be applied in the cognitive assessment of college students’ social anxiety. The scale could help people with different social anxiety disorder conditions receive more personalized interventions.</p

Table_1_A systemic review and meta-analysis comparing the ability of diagnostic of the third heart sound and left ventricular ejection fraction in heart failure.docx

ObjectiveThis study aimed to compare the sensitivity and specificity of diagnosis between the third heart sound (S3) and left ventricular ejection fraction (LVEF) in heart failure (HF).MethodsRelevant studies were searched in PubMed, SinoMed, China National Knowledge Infrastructure, and the Cochrane Trial Register until February 20, 2022. The sensitivity, specificity, likelihood ratio (LR), and diagnostic odds ratio (DOR) were pooled. The symmetric receiver operator characteristic curve (SROC) and Fagan’s nomogram were drawn. The source of heterogeneity was explored by meta-regression and subgroup analysis.ResultsA total of 19 studies, involving 5,614 participants, were included. The combined sensitivity of S3 was 0.23 [95% confidence interval (CI) (0.15–0.33), specificity was 0.94 [95% CI (0.82–0.98)], area under the SROC curve was 0.49, and the DOR was 4.55; while the sensitivity of LVEF was 0.70 [95% CI (0.53–0.83)], specificity was 0.79 [95% CI (0.75–0.82)], area under the SROC curve was 0.79, and the DOR was 8.64. No publication bias was detected in Deeks’ funnel plot. The prospective design, partial verification bias, and blind contributed to the heterogeneity in specificity, while adequate description of study participants contributed to the heterogeneity in sensitivity. In Fagan’s nomogram, the post-test probability was 48% when the pre-test probability was set as 20%, while in LVEF, the post-test probability was 45% when the pre-test probability was set as 20%.ConclusionThe use of S3 alone presented lower sensitivity in diagnosing HF compared with LVEF, whereas it was useful in early pathological assessment.</p

Image_2_A systemic review and meta-analysis comparing the ability of diagnostic of the third heart sound and left ventricular ejection fraction in heart failure.TIF

ObjectiveThis study aimed to compare the sensitivity and specificity of diagnosis between the third heart sound (S3) and left ventricular ejection fraction (LVEF) in heart failure (HF).MethodsRelevant studies were searched in PubMed, SinoMed, China National Knowledge Infrastructure, and the Cochrane Trial Register until February 20, 2022. The sensitivity, specificity, likelihood ratio (LR), and diagnostic odds ratio (DOR) were pooled. The symmetric receiver operator characteristic curve (SROC) and Fagan’s nomogram were drawn. The source of heterogeneity was explored by meta-regression and subgroup analysis.ResultsA total of 19 studies, involving 5,614 participants, were included. The combined sensitivity of S3 was 0.23 [95% confidence interval (CI) (0.15–0.33), specificity was 0.94 [95% CI (0.82–0.98)], area under the SROC curve was 0.49, and the DOR was 4.55; while the sensitivity of LVEF was 0.70 [95% CI (0.53–0.83)], specificity was 0.79 [95% CI (0.75–0.82)], area under the SROC curve was 0.79, and the DOR was 8.64. No publication bias was detected in Deeks’ funnel plot. The prospective design, partial verification bias, and blind contributed to the heterogeneity in specificity, while adequate description of study participants contributed to the heterogeneity in sensitivity. In Fagan’s nomogram, the post-test probability was 48% when the pre-test probability was set as 20%, while in LVEF, the post-test probability was 45% when the pre-test probability was set as 20%.ConclusionThe use of S3 alone presented lower sensitivity in diagnosing HF compared with LVEF, whereas it was useful in early pathological assessment.</p

Image_1_A systemic review and meta-analysis comparing the ability of diagnostic of the third heart sound and left ventricular ejection fraction in heart failure.TIF

ObjectiveThis study aimed to compare the sensitivity and specificity of diagnosis between the third heart sound (S3) and left ventricular ejection fraction (LVEF) in heart failure (HF).MethodsRelevant studies were searched in PubMed, SinoMed, China National Knowledge Infrastructure, and the Cochrane Trial Register until February 20, 2022. The sensitivity, specificity, likelihood ratio (LR), and diagnostic odds ratio (DOR) were pooled. The symmetric receiver operator characteristic curve (SROC) and Fagan’s nomogram were drawn. The source of heterogeneity was explored by meta-regression and subgroup analysis.ResultsA total of 19 studies, involving 5,614 participants, were included. The combined sensitivity of S3 was 0.23 [95% confidence interval (CI) (0.15–0.33), specificity was 0.94 [95% CI (0.82–0.98)], area under the SROC curve was 0.49, and the DOR was 4.55; while the sensitivity of LVEF was 0.70 [95% CI (0.53–0.83)], specificity was 0.79 [95% CI (0.75–0.82)], area under the SROC curve was 0.79, and the DOR was 8.64. No publication bias was detected in Deeks’ funnel plot. The prospective design, partial verification bias, and blind contributed to the heterogeneity in specificity, while adequate description of study participants contributed to the heterogeneity in sensitivity. In Fagan’s nomogram, the post-test probability was 48% when the pre-test probability was set as 20%, while in LVEF, the post-test probability was 45% when the pre-test probability was set as 20%.ConclusionThe use of S3 alone presented lower sensitivity in diagnosing HF compared with LVEF, whereas it was useful in early pathological assessment.</p