Agoraphobia is related to demographic characteristics and social roles. To unravel behavioral aspects from demographic characteristics, daily life situations were registered with the Experience Sampling Method for 65 panic patients with and without agoraphobia. Surprisingly, panic patients with and without agoraphobia did not differ as hypothesized in reported frequencies of visits to public places. Panic subjects with agoraphobia did, however, spend significantly more time at home and with their families than did panic patients without agoraphobia and normal controls. When adjusted for demographic variables such as sex, marital status, family life, and employment, no significant differences between panic patients with and without agoraphobia emerged on the avoidance variables of remaining at home or being with a family member. The lack of discrimination of the diagnosis on these crucial behavioral variables highlights the influence of demographic characteristics and social roles on agoraphobia in daily life. Such findings challenge current diagnostic conceptualizations that rely on retrospective reports by patients of the avoidance of public places. Moreover, reliance on retrospective reports obscured the important role of significant others for understanding etiology and course.
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http://dx.doi.org/10.2466/pr0.1993.72.3c.1283 | DOI Listing |
BMC Med
January 2025
Department of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China.
Background: While previous reports characterised global and regional variations in RSV seasonality, less is known about local variations in RSV seasonal characteristics. This study aimed to understand the local-level variations in RSV seasonality and to explore the role of geographical, meteorological, and socio-demographic factors in explaining these variations.
Methods: We conducted a systematic literature review to identify published studies reporting data on local-level RSV season onset, offset, or duration for at least two local sites.
BMC Public Health
January 2025
Faculty of Social Work, University of Toronto, 246 Bloor St W, Toronto, ON, M5S 1V4, Canada.
Background: Loneliness is a public health epidemic in the United States (US), with older adults being vulnerable to experiencing loneliness. Predictors of loneliness are less understood among racial/ethnic groups of US older adults, and few studies have included perceived institutional discrimination (PID), stressful life events (SLE), and perceived neighborhood characteristics (PNC) as antecedent stressors of loneliness in diverse older adult samples. Our study assessed the relationship between these stressors and loneliness among specific racial/ethnic groups of older adults.
View Article and Find Full Text PDFBMC Gastroenterol
January 2025
Department of Nephrology, QingPu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Background: Gallstone disease (GSD) is associated with obesity. The Cardiometabolic Index (CMI), a metric that accurately assesses central adiposity and visceral fat, has not been extensively studied in relation to GSD risk. This study investigates the link between CMI and GSD incidence in U.
View Article and Find Full Text PDFBMC Med Educ
January 2025
La Trobe Rural Health School, La Trobe University, Bendigo, VIC, 3550, Australia.
Background: Most research on tracking practice locations of health students has focused on medical students, particularly the factors influencing their choice to work in rural and remote areas. However, there is limited research on how rural origin and training in regional or rural settings affect the employment destinations of dental and oral health graduates. This paper explores the practice locations of dentistry and oral health therapy (OHT) graduates from rural backgrounds compared to those from metropolitan areas in Australia.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
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