Background: The fear of hypoglycemia in type 2 diabetes mellitus (T2DM) patients with hypoglycemia has seriously affected their quality of life. They are always afraid of hypoglycemia and often take excessive action to avoid it. Yet, researchers have investigated the relationship between hypoglycemia worries and excessive avoiding hypoglycemia behavior using total scores on self-report measures. However, network analysis studies of hypoglycemia worries and excessive avoiding hypoglycemia behavior in T2DM patients with hypoglycemia are lacking. Purpose: The present study investigated the network structure of hypoglycemia worries and avoiding hypoglycemia behavior in T2DM patients with hypoglycemia and aimed to identify bridge items to help them correctly treat hypoglycemia and properly deal with hypoglycemia fear. Methods: A total of 283 T2DM patients with hypoglycemia were enrolled in our study. Hypoglycemia worries and avoiding hypoglycemia behavior were evaluated with the Hypoglycemia Fear Scale. Network analyses were used for the statistical analysis. Results: B9 “Had to stay at home for fear of hypoglycemia” and W12 “I am worried that hypoglycemia will affect my judgment” have the highest expected influences in the present network. In the community of hypoglycemia worries, W17 “I worry about hypoglycemia during sleep” has the highest bridge expected influence. And in the community of avoiding hypoglycemia behavior, B9 has the highest bridge expected influence. Conclusion: Complex patterns of associations existed in the relationship between hypoglycemia worries and avoiding hypoglycemia behavior in T2DM patients with hypoglycemia. From the perspective of network analysis, W17 “I worry about hypoglycemia during sleep” aspect of hypoglycemia worries and B9 “Had to stay at home for fear of hypoglycemia” aspect of avoiding hypoglycemia behavior may be the main targets for reducing the fear of hypoglycemia. These results have important implications for clinical practice, which provided potential targets for interventions to reduce hypoglycemia fear and improve the quality of life in T2DM patients with hypoglycemia.
AimOur study aimed to investigate the effect of social responsibility on the subjective well-being of volunteers for COVID-19 and to examine the mediating role of job involvement in this relationship.BackgroundNowadays, more and more people join volunteer service activities. As we all know, volunteer work contributes to society without any return. Volunteers often have a strong sense of social responsibility and reap subjective well-being in their dedication. Although research shows that social responsibility will drive them to participate in volunteer work actively, it is less clear whether job involvement will impact their subjective well-being.MethodsThe data were collected in the precaution zone in Shanghai, China, from April to May 2022. A sample of 302 volunteers for COVID-19 completed the social responsibility scale, subjective well-being scale and job involvement scale in the form of an electronic questionnaire on their mobile phones. A structural equation model was adopted to verify the research hypotheses.ResultsSocial responsibility was significantly and positively related to volunteers’ subjective well-being and job involvement (p < 0.05). Job involvement fully mediates the relationship between volunteers’ social responsibility and subjective well-being.ConclusionSocial responsibility is critical to predicting volunteers’ subjective well-being. Job involvement plays an intervening mechanism in explaining how social responsibility promotes volunteers’ subjective well-being.
OBJECTIVES: This study investigated the effectiveness and identified the cutoff values of the computer-based Farnsworth-Munsell 100-Hue (CFM-100) test for screening color vision deficiencies in the pre-employment examination of civil aviators in China.METHODS: Firstly, subjects were stratified into normal, color weakness, and color blindness with the Ishihara pseudoisochromatic plate test (IPPT) by two ophthalmologists. Then they randomly completed CFM-100 and Farnsworth-Munsell 100-Hue (FM-100) tests. Total error scores (TES) and the time taken for the CFM-100 and FM-100 were analyzed and the cutoff values for the CFM-100 were determined.RESULTS: Of 218 subjects, 159 were normal while 59 were diagnosed with dyschromatopsia. The TES of the CFM-100 were congruent with those of the FM-100 (20.0 ± 18.8 vs. 20.6 ± 17.7, 160.9 ± 66.0 vs. 151.1 ± 66.4). The testing time for the CFM-100, however, was less than the FM-100 (10.3 ± 2.8 min vs. 12.9 ± 2.9 min, 7.8 ± 2.5 min vs. 12.6 ± 3.3 min). The correlation coefficient R was 0.93 and Cohen’s kappa was 0.89 for the two methods. Further analyses defined 34 as the cutoff value to differentiate excellent from fair color discrimination (sensitivity 58.0%, specificity 94.7%) and 101 as the cutoff value to judge fair vs. poor (sensitivity and specificity both 98.8%) for the CFM-100. The cut-off value was 72 for distinguishing normal from defective color vision (sensitivity 96.6%, specificity 98.7%) and 110 was for distinguishing color weakness from color blindness (sensitivity 97.6%, specificity 97.7%) for the CFM-100.CONCLUSIONS: The CFM-100 is an effective method for the diagnosis of dyschromatopsia with high sensitivity in screening airline pilots.Zhang Y, Ma J, Cheng S, Hu W. A computer-based Farnsworth-Munsell 100-Hue (CFM-100) test in pilots’ medical assessments. Aerosp Med Hum Perform. 2022; 93(4):362–367.
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