Analysis of multivariate longitudinal substance use outcomes using multivariate mixed cumulative logit model

Background Longitudinal assessments of usage are often conducted for multiple substances (e.g., cigarettes, alcohol and marijuana) and research interests are often focused on the inter-substance association. We propose a multivariate longitudinal modeling approach for jointly analyzing the ordinal multivariate substance use data. Methods We describe how the binary random slope logistic regression model can be extended to the multi-category ordinal outcomes. We also describe how the proportional odds assumption can be relaxed by allowing differential covariate effects on different cumulative logits for multiple outcomes. Data are analyzed from a P01 study that evaluates the usage levels of cigarettes, alcohol and marijuana repeatedly across 8 measurement waves during 7 consecutive years. Results 1263 subjects participated in the study with informed consent, among whom 56.6% are females. Males and females show significant differences in terms of the time trend for substance use. Specifically, males showed steeper trends on cigarette and marijuana use over time compared to females, while less so for alcohol. For all three substances, age effects appear to be different for different cumulative logits, indicating the violation of proportional odds assumption. Conclusions The multivariate mixed cumulative logit model offers the most flexibility and allows one to examine the inter-substance association when proportional odds assumption is violated.

Suicidality Among Young Adolescents in Secondary Schools in Hong Kong

Background:Despite concerted effort in suicide research and prevention across countries, youth suicide remains a significant public health concern in Hong Kong and nationwide. This study examined the prevalence and correlates of suicidality among secondary school students in Hong Kong. Methods:Data were derived from the 2016 Youth Sexuality Survey initiated by the Family Planning Association of Hong Kong using a stratified random sample of 3,672 secondary school students aged 12 to 18 years in Hong Kong. Suicidality was measured in four progressive levels (suicidal ideation, suicidal plan, suicidal attempts and suicidal attempts requiring medical attention). Multivariable cumulative logit model analysis was used to identify significant risk factors of suicidality.Results:Female students reported more suicidality than their male counterparts (28.0% versus 17.0%, respectively). Multivariable cumulative logit model analysis showed that female gender, age, unhappy school life, disharmony with classmates, unhappy family life, living with mother, acceptance of mothers’ discipline, not sleeping for more than 9 hours on weekdays, alcohol consumption, non-suicidal self-injury, and dissatisfaction with life were significantly associated with suicidality. Limitations:Due to cross-sectional design, causality between suicidality, individual psychosocial and psychological characteristics cannot be established.Conclusions:Suicidal behaviour among Chinese young adolescents remains prevalent in Hong Kong. Family disintegration, school-related problems, and life satisfaction are significant predictors of suicidal behaviour in this study. There is a pressing need to restore optimal mental health among youth adolescents via interdisciplinary collaboration among schools, healthcare providers, stakeholders and mental health experts. The involvement of stakeholders in the community in suicide research and prevention is pivotal in mental health promotion for young adolescents.

Factors Affecting Levels of Antiretroviral Drug Adherence among Adult Patient Living with HIV in Public Health Facilities of Arba Minch Town, Southern Ethiopia: Using Cumulative Logit Model

Background: Adherence to antiretroviral therapy is essential to reduce the multiplication of the virus and improve disease outcomes. The studies have reported a range of factors influencing antiretroviral therapy adherence at various levels. Almost all studies were modeling the factors based on binary categorization of the adherence. Objective: This study intended to determine the adherence level and its associated factors to antiretroviral therapy among adult people living with human immunodeficiency virus. Methods: This study was a cross-sectional study that employed among 391 adult patients that were selected by simple random sampling. The cumulative Logit model was used to examine the associations between the outcome of antiretroviral therapy adherence and independent variables. Results: The study participants with good level of antiretroviral therapy adherence (67.77%) were approximately four times higher than study participants with fair (17.39%) and good (14.83%) adherence levels. As the duration on ART changed from ≤12 months to >12 months, the odds of high adherence/less adherence increased with approximately 61% (p = 0.0347) across the full scale of adherence levels. The estimated odds of patients with a CD4 ≥ 200cells/mm3 was 1.65 (p = 0.0279) times toward poor level of antiretroviral therapy adherence than the estimated odds of patients with CD4 < 200cells/mm3. Study participants who have single marital status tending to have more poor level of adherence to antiretroviral therapy than patients with married marital status (p = 0.0003). Conclusion: Levels of adherence to the antiretroviral therapy is significantly determined by the duration on antiretroviral therapy, the number of CD4 counts, the types of initial antiretroviral therapy regimens and the marital status of adult people living with HIV/AIDS.

Bayesian Approaches to Assessing the Parallel Lines Assumption in Cumulative Ordered Logit Models

We first review existing literature on cumulative logit models along with various ways to test the parallel lines assumption. Building on the traditional frequentist framework, we introduce a method of Bayesian assessment of null values to provide an alternative way to examine the parallel lines assumption using highest density intervals and regions of practical equivalence. Second, we propose a new hyperparameter cumulative logit model that can improve upon existing ones in addressing several challenges where traditional modeling techniques fail. We use two empirical examples from health research to showcase the Bayesian approaches.

Modelling world energy security data from multinomial distribution by generalized linear model under different cumulative link functions

Energy securityis one of the major components of energy sustainability in the world’s energy performance. In this study,energy securityis taken as an ordinal response variable coming from the multinomial distribution with the energy grade levelsA,B,C, andD. Thereafter, the worldenergy securitydata is tried to be statistically modelled by usinggeneralized linear model (GLM)approach for the ordinal response variable under different cumulative link functions. The cumulative link functions comparatively used in this study are cumulative logit, cumulative probit, cumulative complementary log-log, cumulative Cauchit, and cumulative negative log-log. In order to avoid a multicollinearity problem in the data structure, principal component analysis (PCA) technique is integrated with theGLMapproach for the ordinal response variable. In this study, statistically, the importance of determining the best cumulative link function on the accuracy of parameter estimates, confidence intervals, and hypothesis tests in theGLMfor the multinomially distributed response variable is highlighted. In terms of energy evaluation, by usingcumulative logitas the best cumulative link function,energy sources consumptions,electricity productions from nuclear energy,natural gas,oil,coal,and hydroelectric,energy use per capita and energy importsare found to have statistically significant effects onenergy securityin the world’s energy performance.

Determinants of antimicrobial use practices among veterinary clinicians at The University of Tennessee Veterinary Medical Center

Background. Antimicrobial drugs in veterinary medical practice are primarily prescribed for the purposes of maintaining or improving health and increasing productivity. However, their value is being eroded by antimicrobial resistance (AMR). Indiscriminate use of antimicrobial drugs is suggested as one of the modifiable factors contributing to the development of AMR. To reduce indiscriminate use and to improve antimicrobial use, veterinary practices are encouraged to adopt good stewardship practices. Therefore, the objectives of this study were: to identify factors influencing clinician decisions to begin using antimicrobials as well as the choice of antimicrobials used at The University of Tennessee Veterinary Medical Center (UTVMC); to evaluate the practices, perceptions, opinions and concerns of veterinary clinicians at UTVMC concerning antimicrobial use, antimicrobial stewardship, and AMR. Methods. This study’s protocol was approved by the University of Tennessee Knoxville IRB for the Protection of Human Subjects in Research. Survey software was used to send a questionnaire to 121 eligible participants, where all were UTVMC faculty with clinical appointments and house officers. Cumulative logit models were fitted to investigate associations between categorical explanatory variables and ordinal response variables. Results. A response rate of 51.24% was achieved. Of the 62 respondents, 47 (75.81%) reported that bacteriological culture and antimicrobial susceptibility test results were extremely important in their antimicrobial prescription decision-making. Thirty-two (51.61%) respondents believed antimicrobials are being over-prescribed. The cephalosporin class was the most preferred antimicrobial class, while the lincosamide class was the least preferred. From the multivariable cumulative logit model, year of graduation from veterinary school (P = 0.034) and clinicians’ primary patient load (P = 0.009) were significantly associated with clinicians’ degree of concern about AMR. Conclusions and clinical relevance. The findings suggest a need for more awareness about AMR among veterinary clinicians. Improvements in antimicrobial stewardship are needed, especially among veterinary clinicians who graduated after 1999. Educational practices that target modification of antimicrobial prescription practices of veterinary clinicians would likely improve a Good Stewardship Practice (GSP) mindset. GSP is important in prolonging the efficacy of currently available antimicrobial drugs.

Determinants of antimicrobial use practices among veterinary clinicians at The University of Tennessee Veterinary Medical Center

Background. Antimicrobial drugs in veterinary medical practice are primarily prescribed for the purposes of maintaining or improving health and increasing productivity. However, their value is being eroded by antimicrobial resistance (AMR). Indiscriminate use of antimicrobial drugs is suggested as one of the modifiable factors contributing to the development of AMR. To reduce indiscriminate use and to improve antimicrobial use, veterinary practices are encouraged to adopt good stewardship practices. Therefore, the objectives of this study were: to identify factors influencing clinician decisions to begin using antimicrobials as well as the choice of antimicrobials used at The University of Tennessee Veterinary Medical Center (UTVMC); to evaluate the practices, perceptions, opinions and concerns of veterinary clinicians at UTVMC concerning antimicrobial use, antimicrobial stewardship, and AMR. Methods. This study’s protocol was approved by the University of Tennessee Knoxville IRB for the Protection of Human Subjects in Research. Survey software was used to send a questionnaire to 121 eligible participants, where all were UTVMC faculty with clinical appointments and house officers. Cumulative logit models were fitted to investigate associations between categorical explanatory variables and ordinal response variables. Results. A response rate of 51.24% was achieved. Of the 62 respondents, 47 (75.81%) reported that bacteriological culture and antimicrobial susceptibility test results were extremely important in their antimicrobial prescription decision-making. Thirty-two (51.61%) respondents believed antimicrobials are being over-prescribed. The cephalosporin class was the most preferred antimicrobial class, while the lincosamide class was the least preferred. From the multivariable cumulative logit model, year of graduation from veterinary school (P = 0.034) and clinicians’ primary patient load (P = 0.009) were significantly associated with clinicians’ degree of concern about AMR. Conclusions and clinical relevance. The findings suggest a need for more awareness about AMR among veterinary clinicians. Improvements in antimicrobial stewardship are needed, especially among veterinary clinicians who graduated after 1999. Educational practices that target modification of antimicrobial prescription practices of veterinary clinicians would likely improve a Good Stewardship Practice (GSP) mindset. GSP is important in prolonging the efficacy of currently available antimicrobial drugs.