Latent class analysis of the Apathy Scale does not identify subtypes of apathy in general population-based older persons

2016 ◽  
Vol 31 (9) ◽  
pp. 1021-1028 ◽  
Author(s):  
Isis Groeneweg-Koolhoven ◽  
Lotte J. Huitema ◽  
Margot W. M. de Waal ◽  
Max L. Stek ◽  
Jacobijn Gussekloo ◽  
...  
Keyword(s):  
General Population ◽  
Latent Class Analysis ◽  
Older Persons ◽  
Latent Class ◽  
Population Based ◽  
Class Analysis

scholarly journals Somatic symptom profiles in the general population: a latent class analysis in a Danish population-based health survey

2017 ◽  
Vol Volume 9 ◽  
pp. 421-433 ◽  
Author(s):  
Marie Eliasen ◽  
Torben Jørgensen ◽  
Andreas Schröder ◽  
Thomas Meinertz Dantoft ◽  
Per Fink ◽  
...  
Keyword(s):  
General Population ◽  
Latent Class Analysis ◽  
Health Survey ◽  
Somatic Symptom ◽  
Latent Class ◽  
Population Based ◽  
Class Analysis ◽  
Danish Population ◽  
Symptom Profiles

scholarly journals Estimates and Determinants of SARS-Cov-2 Seroprevalence and Infection Fatality Ratio Using Latent Class Analysis: The Population-Based Tirschenreuth Study in the Hardest-Hit German County in Spring 2020

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1118
Author(s):  
Ralf Wagner ◽  
David Peterhoff ◽  
Stephanie Beileke ◽  
Felix Günther ◽  
Melanie Berr ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Care Home ◽  
Case Fatality ◽  
The Elderly ◽  
Population Based ◽  
Class Analysis ◽  
Population Based Study ◽  
Targeted Testing ◽  
June July

SARS-CoV-2 infection fatality ratios (IFR) remain controversially discussed with implications for political measures. The German county of Tirschenreuth suffered a severe SARS-CoV-2 outbreak in spring 2020, with particularly high case fatality ratio (CFR). To estimate seroprevalence, underreported infections, and IFR for the Tirschenreuth population aged ≥14 years in June/July 2020, we conducted a population-based study including home visits for the elderly, and analyzed 4203 participants for SARS-CoV-2 antibodies via three antibody tests. Latent class analysis yielded 8.6% standardized county-wide seroprevalence, a factor of underreported infections of 5.0, and 2.5% overall IFR. Seroprevalence was two-fold higher among medical workers and one third among current smokers with similar proportions of registered infections. While seroprevalence did not show an age-trend, the factor of underreported infections was 12.2 in the young versus 1.7 for ≥85-year-old. Age-specific IFRs were <0.5% below 60 years of age, 1.0% for age 60–69, and 13.2% for age 70+. Senior care homes accounted for 45% of COVID-19-related deaths, reflected by an IFR of 7.5% among individuals aged 70+ and an overall IFR of 1.4% when excluding senior care home residents from our computation. Our data underscore senior care home infections as key determinant of IFR additionally to age, insufficient targeted testing in the young, and the need for further investigations on behavioral or molecular causes of the fewer infections among current smokers.

Empirical derived AUD sub types in the US general population: A latent class analysis

2013 ◽  
Vol 38 (11) ◽  
pp. 2782-2786 ◽  
Author(s):  
Martina Casey ◽  
Gary Adamson ◽  
Maurice Stringer
Keyword(s):  
General Population ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
The Us

scholarly journals Health Information-Seeking Behaviors of a German Speaking Minority in Italy: Latent Class Analysis of a Population-Based Cross-Sectional Survey

2021 ◽  
Author(s):  
Dietmar Ausserhofer ◽  
Wolfgang Wiedermann ◽  
Christian J. Wiedermann ◽  
Ulrich Becker ◽  
Anna Vögele ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Health Information ◽  
Information Seeking ◽  
Latent Class ◽  
Population Based ◽  
Health Information Seeking ◽  
Class Analysis ◽  
Online Class ◽  
German Speaking ◽  
Information Seeking Behaviors

Abstract Latent classes of health information-seeking behaviors of adults in a German-speaking minority of Italy were explored in a population-based, telephone survey on 10 health information sources conducted in South Tyrol, Italy. Data were collected from 504 adults (primary language German 68%, Italian 28%) and analyzed using latent class analysis and latent class multinomial logistic regression models. Three classes of health information-seeking behaviors emerged: “multidimensional” (23.3%), “interpersonal” (38.6%) and “technical/online” (38.1%). Compared to the “technical/online” class, “interpersonal” class members were older, had lower education than high school, and were less likely to be of Italian ethnicity. “Multidimensional” class members were more likely to be female, older, and of German ethnicity than those in the “technical/online” class. Linguistic ethnicity explains membership in classes of health-information-seeking behaviour. Policy makers and healthcare providers need to consider the health information-seeking behaviors of population subgroups to promote the health literacy skills of language minority groups.

scholarly journals Occurence of Internet Addiction in a General Population Sample: A Latent Class Analysis

2013 ◽  
Vol 20 (4) ◽  
pp. 159-166 ◽  
Author(s):  
Hans-Jürgen Rumpf ◽  
Ad A. Vermulst ◽  
Anja Bischof ◽  
Nadin Kastirke ◽  
Diana Gürtler ◽  
...  
Keyword(s):  
General Population ◽  
Latent Class Analysis ◽  
Internet Addiction ◽  
Latent Class ◽  
Population Sample ◽  
Class Analysis ◽  
General Population Sample

A latent class analysis of psychotic symptoms in the general population

2017 ◽  
Vol 52 (6) ◽  
pp. 573-584 ◽  
Author(s):  
Baptiste Pignon ◽  
Hugo Peyre ◽  
Andrei Szöke ◽  
Pierre A Geoffroy ◽  
Benjamin Rolland ◽  
...  
Keyword(s):  
General Population ◽  
Latent Class Analysis ◽  
Mental Health Treatment ◽  
Latent Class ◽  
Psychotic Disorders ◽  
Social Deprivation ◽  
Psychotic Symptoms ◽  
Class Analysis ◽  
Clinical Correlates ◽  
High Prevalence

Objective: Individuals with psychotic symptoms may actually correspond to various subgroups, characterized by different patterns of psychotic symptoms as well as specific sociodemographic and clinical correlates. We aimed to identify groups of individuals from the general population with specific patterns of psychotic symptoms. Methods: In a 38,694-subject survey, a latent class analysis was performed to identify subgroups based on the distribution of seven psychotic symptoms taken from the Mini International Neuropsychiatric Interview. The different classes were subsequently compared according to sociodemographic and clinical correlates. Results: The best fit was obtained with a four-class solution, including the following: (1) a class with a low prevalence of all psychotic symptoms (‘LOW’, 85.9%); (2) a class with a high prevalence of all psychotic symptoms (‘HAL + DEL’, 1.7%); and classes with a high prevalence of (3) hallucinations (‘HAL’, 4.5%) or (4) delusions (‘DEL’, 7.9%). The HAL + DEL class displayed higher rates of history of trauma, social deprivation and migrant status, while the HAL and DEL classes displayed intermediate rates between HAL + DEL and LOW. HAL + DEL displayed the highest rates of psychotic and non-psychotic disorders and the use of mental health treatment, while HAL and DEL displayed intermediate rates of these disorders between HAL + DEL and LOW. In comparison to the HAL class, psychotic and substance use disorders were more frequent in the DEL class, while anxiety and mood disorders were less frequent. Conclusion: These findings support the hypothesis of a continuum model relating the level of psychotic symptoms to the level of global psychopathology.

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