Bystander intentions to intervene and previous sexual violence education: A latent class analysis.

2019 ◽  
Vol 9 (1) ◽  
pp. 117-126
Author(s):  
Sarah McMahon ◽  
Peter Treitler ◽  
N. Andrew Peterson ◽  
Julia O'Connor
Keyword(s):  
Latent Class Analysis ◽  
Sexual Violence ◽  
Latent Class ◽  
Class Analysis

A latent class analysis of the co-occurrence of sexual violence, substance use, and mental health in youth

2019 ◽  
Vol 54 (12) ◽  
pp. 1938-1944 ◽  
Author(s):  
Jordan L. Nelon ◽  
Kris T. De Pedro ◽  
Tamika D. Gilreath ◽  
Megan S. Patterson ◽  
Caitlin B. Holden ◽  
...  
Keyword(s):  
Mental Health ◽  
Substance Use ◽  
Latent Class Analysis ◽  
Sexual Violence ◽  
Latent Class ◽  
Class Analysis

scholarly journals Intimate partner violence against low-income women in Mexico City and associations with work-related disruptions: a latent class analysis using cross-sectional data

2018 ◽  
Vol 72 (7) ◽  
pp. 605-610 ◽  
Author(s):  
Jhumka Gupta ◽  
Tiara C Willie ◽  
Courtney Harris ◽  
Paola Abril Campos ◽  
Kathryn L Falb ◽  
...  
Keyword(s):  
Intimate Partner Violence ◽  
Latent Class Analysis ◽  
Sexual Violence ◽  
Mexico City ◽  
Low Income ◽  
Partner Violence ◽  
Latent Class ◽  
Intimate Partner ◽  
Class Analysis ◽  
Work Related

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.

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

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.

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

SLEEP ◽  
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

Latent Class Analysis of Psychosocial and Psychophysiological Risks for Drinking

2009 ◽  
Author(s):  
Tomoko Udo ◽  
Jennifer F. Buckman ◽  
Marsha E. Bates ◽  
Evgeny Vaschillo ◽  
Bronya Vaschillo ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis
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