The Influence of the Experience of Child Sexual Violence on Suicide Behavior Patterns: A Latent Class Analysis

BackgroundDisrupting women’s employment is a strategy that abusive partners could use to prevent women from maintaining economic independence and stability. Yet, few studies have investigated disruptions in employment among victims of intimate partner violence (IPV) in low-income and middle-income countries. Moreover, even fewer have sought to identify which female victims of IPV are most vulnerable to such disruptions.MethodsUsing baseline data from 947 women in Mexico City enrolled in a randomised controlled trial, multilevel latent class analysis (LCA) was used to classify women based on their reported IPV experiences. Furthermore, multilevel logistic regression analyses were performed on a subsample of women reporting current work (n=572) to investigate associations between LCA membership and IPV-related employment disruptions.ResultsOverall, 40.6% of women who were working at the time of the survey reported some form of work-related disruption due to IPV. LCA identified four distinct classes of IPV experiences: Low Physical and Sexual Violence (39.1%); High Sexual and Low Physical Violence class (9.6%); High Physical and Low Sexual Violence and Injuries (36.5%); High Physical and Sexual Violence and Injuries (14.8%). Compared with women in the Low Physical and Sexual Violence class, women in the High Physical and Sexual Violence and Injuries class and women in the High Physical and Low Sexual Violence and Injuries class were at greater risk of work disruption (adjusted relative risk (ARR) 2.44, 95% CI 1.80 to 3.29; ARR 2.05, 95% CI 1.56 to 2.70, respectively). No other statistically significant associations emerged.ConclusionIPV, and specific patterns of IPV experiences, must be considered both in work settings and, more broadly, by economic development programmes.Trial registration numberNCT01661504.

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Does participation in the workplace spill over into political participation? A latent class analysis approach to patterns of political behavior

Journal of Participation and Employee Ownership ◽

10.1108/jpeo-08-2021-0004 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Jungook Kim

Keyword(s):

Political Participation ◽

Latent Class Analysis ◽

Political Behavior ◽

Latent Class ◽

Political Efficacy ◽

Behavior Patterns ◽

Class Analysis ◽

Social Survey ◽

Content Type ◽

Political Behaviors

PurposeThis study examines Pateman's “spillover thesis” that democratic participation in the workplace will “spill over” into political participation. It applies a latent class analysis (LCA) to identify patterns of political behavior and uses workplace participation and political efficacy as predicting variables of political behavior patterns.Design/methodology/approachThis study analyzed the International Social Survey Programme (ISSP) in 2014 General Social Survey (GSS) data. This study applied a LCA to identify distinct patterns in people's political behaviors and did a multinomial regression analysis to predict the patterns with workplace participation and political efficacy.FindingsThe study found partial support for the spillover thesis. Among three distinct political behavior patterns, two active patterns were associated with political efficacy. However, the mediation from workplace participation to political participation through political efficacy was not supported. Respondents involved in workplace units that collectively make work-related decisions were more likely to be active in political behaviors, but only one set of political activities. Higher political efficacy was found to lead to more active overall political participation of both patterns.Originality/valueUnlike the previous studies of democratic spillover, which treated political behaviors either as independent types of behaviors or as a summative index of such binary coded variables, this study addressed such shortcomings of the previous studies by providing a more complex picture of political behavior patterns and their relationship with workplace participation. Future research can build on this unique methodological endeavor to explore a holistic picture of how workplace practices can influence politics and democracy through individual workers.

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A Study on Daily Physical Activity and Sedentary Behavior Patterns among Senior Regular Short Tennis Players : A Latent Class Analysis Approach

Journal of Japan Society of Sports Industry ◽

10.5997/sposun.26.2_279 ◽

2016 ◽

Vol 26 (2) ◽

pp. 2_279-2_290

Author(s):

Noboru HARADA ◽

Takehiko SANO

Keyword(s):

Physical Activity ◽

Latent Class Analysis ◽

Sedentary Behavior ◽

Latent Class ◽

Daily Physical Activity ◽

Analysis Approach ◽

Behavior Patterns ◽

Class Analysis ◽

Tennis Players

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Exposure to Campus Messages about Dating and Sexual Violence: A Latent Class Analysis

Journal of Interpersonal Violence ◽

10.1177/08862605211005159 ◽

2021 ◽

pp. 088626052110051

Author(s):

Julia O'Connor ◽

Jill Hoxmeier ◽

Sarah McMahon ◽

Julia Cusano ◽

Courtney Wilson

Keyword(s):

Latent Class Analysis ◽

Sexual Violence ◽

Latent Class ◽

Class Analysis ◽

Sources Of Information ◽

High Exposure ◽

Message Source ◽

Several Variables ◽

Low Exposure ◽

Different Sources

This study investigates college students’ exposure to messages about campus dating and sexual violence (DSV) to discover classes of students based on the message source. Latent class analysis was performed with data assessing 5,284 students’ exposure to 16 different sources of information regarding DSV, from having a professor discuss these topics to participating in related campus events. Several variables were included in the analysis to understand students’ class membership in relation to pertinent student demographic factors. The best model indicated that there are five classes of students based on their exposure to messages, with some subgroups of students having high exposure to various sources of messages about DSV while others have low exposure. Still other subgroups are primarily exposed to messages through nonactive or noninstitutional sources of information. Subgroups of students, based on their exposure to DSV messaging, also differ regarding demographic makeup. The implications from these results include the need to tailor DSV programming on campus to subgroups of students based on their varying baseline levels of message exposure. As students are exposed to messaging through differing sources, including passive and noninstitutional, institutions can use this information when designing outreach efforts to better fit with the needs of various subgroups of students.

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Defining Behavior Patterns Towards Exclusive Breastfeeding Using Latent Class Analysis

Journal of Pediatrics Review ◽

10.5812/jpr.10575 ◽

2017 ◽

Vol 6 (1) ◽

Cited By ~ 1

Author(s):

Pryscila de Argolo Cerqueira ◽

Leila D A F Amorim ◽

Tatiana de O Vieira ◽

Janaina S Dias ◽

Heli V Brandao ◽

...

Keyword(s):

Latent Class Analysis ◽

Exclusive Breastfeeding ◽

Latent Class ◽

Behavior Patterns ◽

Class Analysis

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1064 Sleep Patterns Among Urban Haitian Earthquake Survivors Who Experienced the Trauma of Nonpartner Sexual Violence: A Latent Class Analysis Approach

SLEEP ◽

10.1093/sleep/zsaa056.1060 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A405-A405

Author(s):

G J Rahill ◽

M J Joshi ◽

J Blanc ◽

C Rice

Keyword(s):

Latent Class Analysis ◽

Sleep Disturbance ◽

Sexual Violence ◽

Latent Class ◽

Class Analysis ◽

Class Membership ◽

Sleep Health ◽

Class 1 ◽

Earthquake Survivors ◽

Post Disaster

Abstract Introduction Sleep health is crucial to recovery from trauma. Haiti’s Cité Soleil residents (approximately 350,000) live in extreme poverty and regularly experience or witness life-threatening events, including gang and non-partner sexual violence (NPSV). Differences in levels of sleep disturbance among men and women in resource-limited settings who survive disasters as well as NPSV are understudied. In a larger study in which we investigated trauma symptoms among 2010 Haiti earthquake survivors via the Trauma-symptom checklist -40 (N=526; 290 males, 236 females), we also assessed self-reported frequency of sleep disturbance symptoms using the measure’s sleep disturbance subscale, comparing the latter by NPSV victim status and by gender. Methods SAS enabled 3-Class Latent Class Analysis (LCA): Class 1 (“No symptoms”), Class 2 (“Some symptoms”), Class 3 (“All Symptoms)”. Results Distribution of class membership differed by gender (χ2 = 23.9, df = 2, p < .0001). Proportions of respondents assigned to the three classes differed between genders (Females: Class 1, 29.2%; Class 2, 35.5%; Class 3, 35.3%); Males: Class 1, 25.7%; Class 2, 54.4%; Class 3, 19.9%). NPSV status influenced levels of sleep disturbance symptoms, and membership distribution differed across classes by gender (χ2 = 23.9, df = 2, p < .0001). Class 2 membership was greater for men (65.9%), but class 3 membership was greater for women (59.3%). Women who experienced NPSV were statistically more likely members of sleep disturbance symptom classes (Class 2 or Class 3) than Class 1 (χ2= 14.9, df = 2, p = 0.0006). No difference was found in Class membership for men reporting NPSV (χ2= 1.6, df = 2, p = 0.45). Conclusion Investigating the sleep health of Cité Soleil residents adds to the body of literature on sleep health, sleep equity and gendered vulnerability. Findings suggest women in post-disaster settings, especially in LMICs, are at even greater risk for a variety of adverse health outcomes and for suboptimal sleep, even when local men have similar traumatogenic experiences, such as NPSV. Girls and women in post-disaster LMIC settings need trauma-informed sleep health promotion and NPSV-prevention. Support N/A

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