Editorial
13 February 2024
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Original Research
17 July 2023

Objective: This study aimed to construct a network structure to investigate the connections between alexithymia, depression, anxiety, and stress in Chinese older adults with multiple chronic conditions (MCC), identifying core and bridge symptoms, and comparing the network structure across different levels of alexithymia.

Methods: This study used a cross-sectional survey design and convenience sampling to recruit participants from six cities in Jiangsu Province. The study assessed the levels of alexithymia, depression, anxiety, and stress in older adults with MCC using the Toronto Alexithymia Scale (TAS-20) and the Depression Anxiety and Stress Scale-21 (DASS-21). Network analysis was performed using R language to identify core and bridge symptoms in the network and compare the network structure across different levels of alexithymia.

Results: A total of 662 participants were included in the analysis, including 395 men and 267 women. The mean age was 70.37 ± 6.92 years. The finding revealed that the “Difficulty Identifying Feelings” (DIF) node had the highest strength centrality (strength = 2.49) and predictability (rp = 0.76) in the network. The next highest strength centrality was observed for “Meaningless” (strength = 1.50), “Agitated” (strength = 1.47), “Scared” (strength = 1.42), and “No look forward” (strength = 0.75). They were identified as core symptoms. The bridge strength analysis identified “Panic,” “Scared,” “No wind down,” “No initiative,” and “No positive” as the bridge symptoms. There were notable differences in the overall network structure and specific connections between the groups with and without alexithymia (p < 0.05).

Conclusion: “DIF” is a core node in the network of older adults with MCC, indicating its significance as a potential target for psychological interventions in clinical practice. Preventing and mitigating bridge symptoms such as “panic,” “Scared,” “No wind down,” “No initiative,” and “No positive” can effectively impede the spread of symptom activation, thereby interrupting or severing the connections among comorbidities in older adults. Additionally, compared to non-alexithymia individuals, the psychological issues of older adults with alexithymia require prioritized intervention from healthcare professionals.

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Background: Depression is a common psychiatric health issue affecting an estimated 5% of adults worldwide, and it can lead to disability and increased economic burden. Consequently, identifying the factors associated with depression as early as possible is a vital issue. The aim of this study was to explore these associations in a large cohort of 121,601 Taiwanese participants in the Taiwan Biobank, and also to identify sex differences in the associations.

Methods: The study cohort included 77,902 women and 43,699 men (mean age, 49.9 ± 11.0 years), who were further classified into those with depression (n = 4,362; 3.6%) and those without depression (n = 117,239; 96.4%).

Results: The results of multivariable analysis showed that female sex (vs. male sex; odds ratio = 2.578; 95% confidence interval = 2.319–2.866; p < 0.001) was significantly associated with depression. Older age, diabetes mellitus (DM), hypertension, low systolic blood pressure (SBP), smoking history, living alone, low glycated hemoglobin (HbA1c), high triglycerides, and low uric acid were significantly associated with depression in the men. In the women, older age, DM, hypertension, low SBP, smoking history, alcohol history, education level of middle and high school (vs. lower than elementary school), living alone, high body mass index (BMI), menopause, low HbA1c, high triglycerides, high total cholesterol, low estimated glomerular filtration rate (eGFR), and low uric acid were significantly associated with depression. Further, there were significant interactions between sex and DM (p = 0.047), smoking history (p < 0.001), alcohol use (p < 0.001), BMI (p = 0.022), triglyceride (p = 0.033), eGFR (p = 0.001), and uric acid (p = 0.004) on depression.

Conclusion: In conclusion, our results showed sex differences in depression, and the women were significantly associated with depression compared to men. Furthermore, we also found sex differences among the risk factors associated with depression.

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Frontiers in Public Health

Advances in Artificial Intelligence Applications that Support Psychosocial Health
Edited by MARÍA JOSÉ VÁZQUEZ FIGUEIREDO, Rubén González-Rodríguez, Enrique Costa-Montenegro
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