A Latent Class Analysis Approach to Extradyadic Involvement

2018 ◽  
Vol 9 ◽  
Author(s):  
Lindsey M. Rodriguez ◽  
Angelo M. DiBello ◽  
Camilla S. Øverup ◽  
Helen Lee Lin
Keyword(s):  
Latent Class Analysis ◽  
Undergraduate Students ◽  
Romantic Relationship ◽  
Latent Class ◽  
Investment Model ◽  
Relationship Functioning ◽  
Class Analysis ◽  
Sexual Involvement ◽  
Two Samples

Extradyadic involvement — emotional, romantic, or sexual involvement with another person outside of one's romantic relationship — may have serious personal and relational consequences. The current research examines extradyadic involvement in two samples of individuals in relationships and identifies subgroups of people based on their engagement in different types of extradyadic behaviour. To assess involvement in such behaviour, we created a new behavioural inventory intended to broaden the conceptualisation of types of extradyadic behaviours. Subgroups of individuals who engage in these behaviours were extracted using latent class analysis. Study 1 assessed undergraduate students in relationships (N = 339), and results revealed four classes of individuals: loyal, confiding, deceptive, and unfaithful. Follow-up tests demonstrated that these classes of individuals differed significantly in ways that are consistent with the investment model and attachment theory. Study 2 (N = 202) replicated the four-class solution, as well as the group differences in relationship functioning and attachment orientations. Results suggest theoretically consistent typologies of extradyadic behaviour that may be useful in differentiating deceptive behaviour in close relationships in a more precise way.

One-year follow up of cardiac anxiety after a myocardial infarction: A latent class analysis

2012 ◽  
Vol 73 (5) ◽  
pp. 362-368 ◽  
Author(s):  
M.H.C.T. van Beek ◽  
M. Mingels ◽  
R.C. Oude Voshaar ◽  
A.J.L.M. van Balkom ◽  
M. Lappenschaar ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
Cardiac Anxiety ◽  
One Year

Adherence styles of schizophrenia patients identified by a latent class analysis of the Medication Adherence Rating Scale (MARS): A six-month follow-up study

2012 ◽  
Vol 200 (2-3) ◽  
pp. 83-88 ◽  
Author(s):  
Susanne Jaeger ◽  
Carmen Pfiffner ◽  
Prisca Weiser ◽  
Reinhold Kilian ◽  
Thomas Becker ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Rating Scale ◽  
Class Analysis ◽  
Follow Up Study

scholarly journals Sleep disturbance subtypes in Parkinson’s disease based on the cross-culturally validated Korean version of the Parkinson’s Disease Sleep Scale-2

2019 ◽  
Author(s):  
Hui-Jun Yang ◽  
Han-Joon Kim ◽  
Seong-Beom Koh ◽  
Joong-Seok Kim ◽  
Tae-Beom Ahn ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Latent Class Analysis ◽  
Sleep Disturbance ◽  
Latent Class ◽  
Intraclass Correlation ◽  
Class Analysis ◽  
Korean Version ◽  
The Cross

Abstract Background: Sleep-related problems in Parkinson’s disease (PD) have received greater attention in recent years due to their clinical influence on morbidity, disability, and the health-related quality of life (HRQoL) of patients. This study aimed to evaluate the clinimetric properties of the Korean version of the Parkinson’s Disease Sleep Scale-2 (K-PDSS-2), and to analyze whether distinct sleep disturbance subtypes could be empirically identified in patients with PD based on the cross-culturally validated K-PDSS-2. Methods: The internal consistency, test-retest reliability, scale precision, and convergent validity of the K-PDSS-2 were assessed in a nationwide, multicenter study of 122 patients with PD. Latent class analysis (LCA) was used to derive subgroups of patients who experienced similar patterns of sleep-related problems and nocturnal disabilities. Results: The mean total K-PDSS-2 scores were 11.67 ± 9.87 (mean ± standard deviation) at baseline, and 12.61 ± 11.17 upon follow up testing. The Cronbach’s α coefficients of the total K-PDSS-2 score at baseline and at follow up testing were 0.851 and 0.880 respectively. Intraclass correlation coefficient over the 2-week period ranged from 0.672 to 0.848. The total K-PDSS-2 score was strongly correlated to HRQoL measures and other corresponding nonmotor scales. LCA indicated three distinct sleep disturbance classes in the study patients, namely “less troubled sleepers”, “PD-related nocturnal difficulties”, and “disturbed sleepers”. Conclusions: The K-PDSS-2 showed good clinimetric attributes in accordance with prior studies that were using the original version of the PDSS-2, therefore confirming the cross-cultural usefulness of the scale. Further, this study documents the first application of an LCA approach for identifying sleep disturbance subtypes in patients with PD. Keywords: Parkinson’s disease; sleep; PDSS-2; validity; reliability; Korean version; latent class analysis.

scholarly journals Profiles of adversity and resilience resources: A latent class analysis of two samples

2020 ◽  
Vol 111 (2) ◽  
pp. 174-199 ◽  
Author(s):  
Robin L. J. Lines ◽  
Monique Crane ◽  
Kagan J. Ducker ◽  
Nikos Ntoumanis ◽  
Cecilie Thøgersen‐Ntoumani ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
Two Samples

scholarly journals Correction to: Identifying high risk subgroups of MSM: a latent class analysis using two samples

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
M. Kumi Smith ◽  
Gabriella Stein ◽  
Weibin Cheng ◽  
William C. Miller ◽  
Joseph D. Tucker
Keyword(s):  
High Risk ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
Two Samples

scholarly journals The pattern of romantic and sexual related experiences among Chinese young adolescents: an exploration with multi-group latent class analysis

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Chunyan Yu ◽  
Chaohua Lou ◽  
Qiguo Lian ◽  
Xiaowen Tu ◽  
Jiashuai Zhang ◽  
...  
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Latent Class Analysis ◽  
Sex Education ◽  
Romantic Relationship ◽  
Latent Class ◽  
Class Analysis ◽  
Sexual Experiences ◽  
Young Adolescents ◽  
General Group

Abstract Background Studies on very young adolescents’ romantic and sexual experiences would help inform the context in which early sex arises. However, such studies are scant in China due to sparse data and cultural issues. Method This study used the GEAS baseline data conducted among1776 adolescents in Shanghai. Multi-group latent class analysis was used to explore adolescents’ romantic and sexual experiences patterns and subgroups. Multi-nominal logistic regression was performed to identify the factors distinguishing different subgroups subsequently. Results There were gender differences in the lifetime prevalence for very young adolescents’ romantic and sexual-related behaviors. The Multi-group latent class analysis indicated that the participants could be classified into three classes: general group, early romance group, and sex exploratory group. Multi-nominal logistic regression showed youth in the early romance group were more likely to had friends of both gender, ever had a romantic relationship, and had more autonomy in deciding where to go than the general group; while male respondents in the sex exploratory group were older, ever had a romantic relationship, believed that boys should be more sexually active and more proactive than girls, had more autonomy on deciding where to go, and perceived less school connection and neighborhood cohesion. Female respondents in the sex exploratory group were older and less empowered in decision-making than the general group. Conclusions The result provides a picture of romantic and sexual behavior patterns among both gender of very young adolescents in China. Current sex education needs not only to be culturally appropriate but also to address the harm of gender inequality and stereotypes, as well as to provide accessible and supportive services to help young adolescents personalize their received information and strengthen their skills in communication, decision making, and critical thinking.

scholarly journals Subpopulations of Addictive Behaviors in Different Sample Types and Their Relationships with Gender, Personality, and Well-Being: Latent Profile vs. Latent Class Analysis

2021 ◽  
Vol 18 (16) ◽  
pp. 8590
Author(s):  
Paweł A. Atroszko ◽  
Bartosz Atroszko ◽  
Edyta Charzyńska
Keyword(s):  
Latent Class Analysis ◽  
Undergraduate Students ◽  
Latent Profile Analysis ◽  
Latent Class ◽  
Well Being ◽  
Addictive Behaviors ◽  
Class Analysis ◽  
Full Sample ◽  
Theoretical Assumptions ◽  
Latent Profile

Background: Relatively strong theoretical assumptions and previous studies concerning co-occurring addictive behaviors suggest a subpopulation representing general proclivity to behavioral addictions (BAs), and there are gender-specific subpopulations. This study aimed to compare latent profile analysis (LPA) and latent class analysis (LCA) as the methods of investigating different clusters of BAs in the general student population and among students positively screened for at least one BA. Participants and procedure: Analyses of six BAs (study, shopping, gaming, Facebook, pornography, and food) and their potential antecedents (personality) and consequences (well-being) were conducted on a full sample of Polish undergraduate students (N = 1182) and a subsample (n = 327) of students including individuals fulfilling cutoff for at least one BA. Results: LPA on the subsample mostly replicated the previous four profiles found in the full sample. However, LCA on a full sample did not replicate previous findings using LPA and showed only two classes: those with relatively high probabilities on all BAs and low probabilities. LCA on the subsample conflated profiles identified with LPA and classes found with LCA in the full sample. Conclusions: LCA on dichotomized scores (screened positively vs. negatively) were less effective in identifying clear patterns of interrelationships between BAs based on relatively strong theoretical assumptions and found in previous research. BAs can be investigated on the whole spectrum of behavior, and person-centered analyses might be more useful when they are based on continuous scores. This paper provides more detailed analyses of the four basic clusters of BAs, prevalence, and co-occurrence of particular BAs within and between them, their gender and personality risk factors, relationships to well-being, and their interrelationships as emerging from the results of this and previous studies.

scholarly journals Identification of three classes of acute respiratory distress syndrome using latent class analysis

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4592 ◽  
Author(s):  
Zhongheng Zhang
Keyword(s):  
Acute Respiratory Distress Syndrome ◽  
Respiratory Distress Syndrome ◽  
Respiratory Distress ◽  
Latent Class Analysis ◽  
Fluid Balance ◽  
Latent Class ◽  
Distress Syndrome ◽  
Class Analysis ◽  
Class 1

Acute respiratory distress syndrome (ARDS) is a highly heterogeneous syndrome that can exhibit significant differences in the underlying causes, leading to different responses to treatment. It is required to identify subtypes of ARDS to guideline clinical treatment and trial design. The study aimed to identify subtypes of ARDS using latent class analysis (LCA). The study was a secondary analysis of the EDEN study, which was a randomized, controlled, multicenter trial conducted from January 2, 2008 to April 12, 2011. The primary study endpoint was death through 90-day follow up. LCA was performed incorporating variables on day 0 before randomization. The number of classes was chosen by a bootstrapped likelihood ratio test, Bayesian information criterion and the number of patients in each class. A total of 943 patients were enrolled in the study, including 219 (23.2%) non-survivors and 724 (76.8%) survivors. The LCA identified three classes of ARDS. Class 1 (hemodynamically unstable type) had significantly higher mortality rate (p = 0.003) than class 2 (intermediate type) and 3 (stable type) through 90 days follow up. There was significant interaction between cumulative fluid balance and the class (p = 0.02). While more fluid balance was beneficial for class 1, it was harmful for class 2 and 3. In conclusion, the study identified three classes of ARDS, which showed different clinical presentations, responses to fluid therapy and prognosis. The classification system used simple clinical variables and could help to design ARDS trials in the future.

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