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The goal was to create a brief temperament inventory grounded in the Regulative Theory of Temperament (FCB-TMI-CC), with a user-friendly, online applicability for studies in different cultures. As the regulative role of temperament is strongly revealed under meaningful stress, the study was planned within the time of the COVID-19 pandemic. To ensure high diversity in terms of culture, economic and environmental conditions, data from nine countries (Poland, United States of America, Italy, Japan, Argentina, South Korea, Ireland, United Kingdom and Kazakhstan) were utilized (min. N = 200 per country). Validation data were gathered on the level of COVID-19 stressors, posttraumatic stress disorder (PTSD), depression, anxiety and stress symptoms, and Big Five personality traits. Multigroup confirmatory factor analysis served as the basis for the inventory's construction. The final culture-common version includes 37 items (5-6 in each of the 7 scales) and covers the core aspects of temperament dimensions. Temperament structure was confirmed to be equivalent across measured cultures. The measurement is invariant at the level of factor loadings and the reliability (internal consistency) and theoretical validity of the scales were at least acceptable. Therefore, the FCB-TMI-CC may serve as a valuable tool for studying temperament across diverse cultures and facilitate cross-cultural comparisons.
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OBJECTIVE: It has been reported that depressive symptoms in older adults are different from those in younger adults, especially when accompanied by cognitive decline. However, few studies have investigated the network structure of depressive symptoms in this population. METHODS: The participants consisted of 627 older adults (>60 yr) who were diagnosed with mild cognitive impairment (MCI) or early stage dementia. Among them, 36.7% were male and the mean age was 76.20±7.71 years. The Korean form of Geriatric Depression Scale (KGDS) was used to evaluate their depressive symptoms and network analyses were performed using bootnet R-package to identify the central features among depressive symptoms. RESULTS: Of all the KGDS items, we found that KGDS 2 (often feel helpless) had the highest node strength followed by KGDS 21 (in good spirits), KGDS 14 (not confident at all), and KGDS 15 (cheerful and happy). In terms of node betweenness, KGDS 2 also showed the highest value. The edge weights of edges connected to node KGDS 2 were strongest in KGDS 3 (restless and fidgety) and KGDS 28 (easily get tired). CONCLUSION: In this study, we presented which symptoms are central among the elderly with MCI and early stage dementia. This result not only increases the understanding of depressive symptoms in this group but would also help determine target symptoms in the treatment program.
RESUMEN
STUDY OBJECTIVES: Various models of insomnia stress the role of cognitive components, such as dysfunctional sleep-related beliefs, in maintenance and exacerbation of insomnia. This study aimed to use network analysis to identify the particular beliefs that are central and have strong associations with insomnia severity. In addition, we aimed to use a relative importance network to map out predictive pathways between types of dysfunctional beliefs and insomnia severity. METHODS: This study was a retrospective study, with data collected from 219 patients with insomnia. Patients' responses to the Dysfunctional Beliefs about Sleep Scale-16 (DBAS-16) and Insomnia Severity Index (ISI) were collected. All network analyses were performed using R Studio to produce 3 networks: (1) DBAS-16 network, (2) DBAS-16 and ISI network, and (3) relative importance network containing DBAS-16 subscales and ISI. RESULTS: Beliefs reflecting overestimation of negative consequences of sleep (eg, "insomnia is ruining life"), loss of ability (eg, "worry about losing abilities to sleep"), and unpredictability (eg, "can't predict sleep quality") were identified as most central and strongly associated with insomnia severity. Worry/helplessness about insomnia had the largest predictive value on insomnia severity, and also acted as a mediator between other subscales and insomnia severity. CONCLUSIONS: The results of our study suggest that overestimation of negative consequences, loss of ability, and unpredictability are key beliefs that exacerbate and maintain insomnia, thus supporting existing cognitive models of insomnia. CITATION: Cha EJ, Hong S, Kim S, Chung S, Jeon HJ. Contribution of dysfunctional sleep-related cognitions on insomnia severity: a network perspective. J Clin Sleep Med. 2024;20(5):743-751.