Substance Use, PTSD Symptoms, and Suicidal Ideation Among Veteran Psychiatry Inpatients: A Latent Class Trajectory Analysis

2021 ◽  
Vol 82 (6) ◽  
pp. 792-800
Author(s):  
Noel A. Vest ◽  
Fernanda S. Rossi ◽  
Mark Ilgen ◽  
Keith Humphreys ◽  
Christine Timko
Keyword(s):  
Substance Use ◽  
Suicidal Ideation ◽  
Trajectory Analysis ◽  
Latent Class ◽  
Ptsd Symptoms ◽  
Latent Class Trajectory Analysis

scholarly journals Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data

2021 ◽  
Author(s):  
Matthias Pierce ◽  
Sally McManus ◽  
Holly Hope ◽  
Matthew Hotopf ◽  
Tamsin Ford ◽  
...  
Keyword(s):  
Mental Health ◽  
Trajectory Analysis ◽  
Latent Class ◽  
Latent Class Trajectory Analysis

scholarly journals First-grade predictors of mathematical learning disability: A latent class trajectory analysis

2009 ◽  
Vol 24 (4) ◽  
pp. 411-429 ◽  
Author(s):  
David C. Geary ◽  
Drew H. Bailey ◽  
Andrew Littlefield ◽  
Phillip Wood ◽  
Mary K. Hoard ◽  
...  
Keyword(s):  
Learning Disability ◽  
Trajectory Analysis ◽  
Latent Class ◽  
First Grade ◽  
Mathematical Learning ◽  
Latent Class Trajectory Analysis

scholarly journals Trajectories of body mass index before the diagnosis of cardiovascular disease: a latent class trajectory analysis

2016 ◽  
Vol 31 (6) ◽  
pp. 583-592 ◽  
Author(s):  
Klodian Dhana ◽  
Joost van Rosmalen ◽  
Dorte Vistisen ◽  
M. Arfan Ikram ◽  
Albert Hofman ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Body Mass Index ◽  
Body Mass ◽  
Trajectory Analysis ◽  
Latent Class ◽  
Latent Class Trajectory Analysis

scholarly journals Body Composition Growth Patterns in Early Infancy: A Latent Class Trajectory Analysis of the Ethiopian iABC Birth Cohort

Obesity ◽  
2018 ◽  
Vol 26 (7) ◽  
pp. 1225-1233 ◽  
Author(s):  
Gregers Stig Andersen ◽  
Rasmus Wibaek ◽  
Pernille Kaestel ◽  
Tsinuel Girma ◽  
Bitiya Admassu ◽  
...  
Keyword(s):  
Body Composition ◽  
Birth Cohort ◽  
Trajectory Analysis ◽  
Latent Class ◽  
Growth Patterns ◽  
Early Infancy ◽  
Latent Class Trajectory Analysis

A person-centered approach to studying associations between psychosocial vulnerability factors and adolescent depressive symptoms and suicidal ideation in a Canadian longitudinal sample

2020 ◽  
pp. 1-12 ◽  
Author(s):  
Lalou Tisseyre ◽  
Eric Lacourse ◽  
Réal Labelle ◽  
Stéphane Paquin ◽  
Catherine M. Herba
Keyword(s):  
Substance Use ◽  
Depressive Symptoms ◽  
Suicidal Ideation ◽  
Conduct Problems ◽  
Latent Class ◽  
Latent Classes ◽  
Vulnerability Factors ◽  
Psychosocial Vulnerability ◽  
Person Centered Approach

Abstract This study used a person-centered approach to identify subgroups of adolescents who are at risk for depression and suicidal ideation. Latent class analysis was first applied to 1,290 adolescents from a Canadian cohort study in order to identify latent vulnerability subtypes based on 18 psychosocial vulnerability factors. Logistic regression analyses were conducted to study the associations between class membership and depressive symptoms and suicidal ideation 2 years later. The moderating role of sex in the associations between latent classes and depressive symptoms was explored. Five latent classes were identified: Low Vulnerability (42%), Substance Use Only (13%), Moderate Vulnerability (28%), Conduct Problems (8%) and High Vulnerability (9%). Compared with the Low Vulnerability class, the probabilities of presenting depressive symptoms were higher for the Substance Use Only class, OR = 1.93, 95% CI [1.21, 3.06], the Moderate Vulnerability class, OR = 2.96, 95% CI [2.09, 4.20], the Conduct Problems class, OR = 3.03, 95% CI [1.84, 4.98], and the High Vulnerability class, OR = 5.4, 95% CI [3.42, 8.53]. Furthermore, interaction effects with sex were identified in relation to depressive symptoms only. The probability of presenting suicidal ideation was higher only for the High Vulnerability class, OR = 4.51, 95% CI [2.41, 8.43]. This study highlights the importance of a person-centered perspective that considers both vulnerability subtypes and sex because these associations are complex rather than linear or additive.

First-Year Trajectories of Medical Cannabis Use Among Adults Taking Opioids for Chronic Pain: An Observational Cohort Study

Pain Medicine ◽  
2021 ◽  
Author(s):  
Jonathan Ross ◽  
Deepika E Slawek ◽  
Chenshu Zhang ◽  
Joanna L Starrels ◽  
Frances R Levin ◽  
...  
Keyword(s):  
New York ◽  
Chronic Pain ◽  
Trajectory Analysis ◽  
Latent Class ◽  
Cannabis Use ◽  
First Year ◽  
Medical Cannabis ◽  
Use Patterns ◽  
Race Ethnicity ◽  
Latent Class Trajectory Analysis

Abstract Objective To describe first-year trajectories of medical cannabis use and identify characteristics associated with patterns of use in a cohort of adults using opioids for chronic pain. Design Latent class trajectory analysis of a prospective cohort study using data on the 14-day frequency of medical cannabis use. Setting A large academic medical center and four medical cannabis dispensaries in the New York City metropolitan area. Subjects Adults with chronic pain using opioids and newly certified for medical cannabis in New York between 2018 and 2020. Methods Using latent class trajectory analysis, we identified clusters of participants based on the 14-day frequency of medical cannabis use. We used logistic regression to determine factors associated with cluster membership, including sociodemographic characteristics, pain, substance use, and mental health symptoms. Results Among 99 participants, the mean age was 53 years; 62% were women, and 52% were White. We identified three clusters of medical cannabis use: infrequent use (n = 30, mean use = 1.5 days/14-day period), occasional use (n = 28, mean = 5.7 days/14-day period), and frequent use (n = 41, mean = 12.1 days/14-day period). Within clusters, use patterns did not vary significantly over 52 weeks. Differences were observed in two sociodemographic variables: Frequent (vs infrequent) use was associated with non-Hispanic White race/ethnicity (adjusted odds ratio 4.54, 95% confidence interval 1.49–14.29), while occasional (vs infrequent) use was associated with employment (adjusted odds ratio 13.84, 95% confidence interval 1.21–158.74). Conclusions Three clusters of medical cannabis use patterns emerged and were stable over time. Results suggest that structural factors related to race/ethnicity and employment may be major drivers of medical cannabis use, even among adults certified for its use.

scholarly journals Latent Class Trajectory Analysis of Risk Factors Uncovers Progression to Type 2 Diabetes

2021 ◽  
Vol 3 (1) ◽  
pp. 26-35
Author(s):  
Qilu Yu ◽  
Maurice C. Johnson ◽  
Howard A. Fishbein ◽  
Rebecca J. Birch ◽  
Xiaoshu Zhu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Trajectory Analysis ◽  
Latent Class ◽  
P Value ◽  
Blood Pressures ◽  
Adjusted Rate ◽  
Rate Ratios ◽  
Latent Class Trajectory Analysis

We identified trajectories of diabetes risk factors in the Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) cohort analyzing 8 years of electronic health records on 1.4 million patients, and investigated associations between trajectories and progression to new onset Type 2 diabetes. Design and Methods: Analyzing LEADR data (2010-2016), we applied Latent Class Trajectory Analysis (LCTA) to classify patterns of risk factor change. There were 824,043 patients with BMIs; 955,128 patients with systolic blood pressures; 957,491 patients with diastolic blood pressures; 300,137 patients with HDLs; 267,553 patients with non-HDL cholesterols; and 297,026 patients with triglycerides. Patients had to have data for all risk factors being assessed. Association between trajectories and incidence of type 2 diabetes for 94,551 patients was assessed using negative binomial regression analysis. Results: Compared to a static BMI trajectory, those with a sustained weight increase (25%+ from starting BMI) were at higher risk of type 2 diabetes over 4.8 years of follow-up (range 2.0 to 8.0 years) (adjusted rate ratios ranged 1.53-1.62, p-value<0.05). Patients with a BMI decrease trajectory (of ~10%), were at reduced risk of diabetes (adjusted rate ratios ranged 0.54-0.74, p-value<.05). BP and lipid trajectories had significant associations with diabetes onset. Conclusions: Regardless of the starting BMI, those who increased their BMI by 25% within two years and maintained the higher weight were significantly at increased risk of type 2 diabetes. Monitoring BMI change and other known risk factor trajectories, BP and lipids, are additional tools for identifying patients at risk for type 2 diabetes.

Different Mental Health Responses to the COVID-19 Pandemic: Latent Class Trajectory Analysis Using Longitudinal UK Data

2021 ◽  
Author(s):  
Matthias Pierce ◽  
Sally McManus ◽  
Holly Hope ◽  
Matthew Hotopf ◽  
Tamsin Ford ◽  
...  
Keyword(s):  
Mental Health ◽  
Trajectory Analysis ◽  
Latent Class ◽  
Latent Class Trajectory Analysis
Sign in / Sign up

Export Citation Format

Share Document