Trends in college students’ mental health diagnoses and utilization of services, 2009–2015

Abstract

Objective: To examine changes in diagnoses/treatment for 12 mental health (MH) conditions, previous use of campus MH services, and willingness to seek MH services in the future. Participants: ACHA–NCHA II participants from 2009 to 2015 (n?=?454,029). Methods: Hierarchical binary logistic regression with step 1 controlling for demographics and step 2 considering time. Results: Time was significant except for bipolar disorder, bulimia, and schizophrenia with increases for all conditions except substance abuse. Anxiety (OR?=?1.68), panic attacks (OR?=?1.61), and ADHD (OR?=?1.40) had the highest odd ratios. Use of MH services at current institution (OR?=?1.30) and willingness to utilize services in the future (OR?=?1.37) also increased over time. Conclusions: Based on a national sample, self-reported diagnoses/treatment of several MH conditions are increasing among college students. This examination of a variety of MH issues can aid college health professionals to engage institutional stakeholders regarding the resources needed to support college students’ MH.     

Help-seeking behaviors and attitudes of emerging adults: How college students reporting recent suicidal ideation utilize the internet compared to traditional resources

Abstract

Objective: Suicide is the second leading cause of death among emerging adults, yet little is known regarding their online help-seeking. Participants: The National Research Consortium of Counseling Centers in Higher Education's dataset (N=26,292). Methods: Students across the United States were recruited from 73 four-year institutions to participate during the 2010–2011 school year. Results: Observed the effectiveness of online and traditional help-seeking stratified by recent suicidal ideation related to their most distressful period in the past year. Females and younger students endorsed both types of help-seeking, yet those with recent ideation were less likely to disclose any help-seeking. Among those reporting recent ideation, only females reported that traditional supports were more than moderately helpful. Regardless of whether students endorsed ideation, students who were younger, engaged in risky behaviors and identified as females reported that online resources were more than moderately helpful. Conclusions: Online resources could potentially bridge barriers to traditional help-seeking for those reluctant to seek out care, yet traditional resources were reported to be the most effective among this sample.     

Psychometric validation of the PERMA-profiler as a well-being measure for student veterans

Abstract

Objective: The current study aims to validate the PERMA-Profiler, a well-known well-being measure, among a sample of student veterans. Participants: A sample of 205 student veterans were recruited from universities across the United States. Method: Cross-sectional research design was used in this study. Measurement structure of the PERMA-Profiler was evaluated using exploratory factor analysis (EFA). Convergent, divergent, and criterion-related validity was tested using Pearson correlation coefficients and Kruskal-Wallis test. Results: The EFA results yielded a two-factor solution for student veterans. Factors are named as emotional character strengths and performance character strengths. Conclusions: The PERMA-Profiler is a multidimensional scale with good reliability and acceptable levels of convergent, divergent, and criterion-related validity. The PERMA-Profiler can help researchers and practitioners better gauge well-being in student veterans. Implications will be discussed.     

Adverse childhood experiences,post-traumatic stress disorder symptoms,and self-reported stress among traditional and nontraditional college students

Abstract

Objective: To investigate the relationships between adverse childhood experiences (ACEs), post-traumatic stress disorder symptoms (PTSD-S), and self-reported stress among college students. Participants: A total of 236 undergraduate students enrolled in nursing courses participated. Method: Using a correlational design, participants completed questionnaires online. To examine PTSD moderation between ACE and self-reported stress, multiple regression was employed. Stress outcomes were examined using a 4-group variable. Mean differences in stress response between these four groups were examined. Differences in ACE, PTSD-S, and stress response between traditional and nontraditional students were also examined. Results: PTSD-S moderated the relationship between ACEs, and self-reported stress. This indicates that students who report PTSD-S following childhood adversity perceive higher levels of stress. Nontraditional and traditional students differed in their responses to the ICLRE scale. Conclusion: Individuals who report PTSD-S following childhood adversity perceive higher levels of stress later in life. Stress reduction programs may be beneficial for students.     

Public Support for Sickle-Cell Disease Funding: Does Race Matter?

Despite the fact that sickle-cell disease (SCD) is perhaps the most “racialized” medical condition in the USA, very little is known about how “race” impacts public support for health policies related to the condition. We embedded an experiment within the 2011 Cooperative Congressional Election Study in order to assess perceptions about SCD among 1250 participants from diverse backgrounds and evaluate the extent to which these perceptions were associated with support for government spending on SCD-related benefits. We manipulated the racial phenotype of SCD advocates who requested additional government funding and asked participants to indicate how much the government should provide. Overall, participants expressed moderately positive attitudes about SCD, and there were no differences in funding support based on the race of the advocate. However, white participants supported less funding compared to nonwhite participants, even after adjusting for a number of demographic and attitudinal covariates. These findings suggest that a complex relationship between racial identification and implicit racism may shape public perceptions about SCD that negatively influences perceivers’ support for SCD-related policy.     

Improving logistic regression on the imbalanced data by a novel penalized log-likelihood function

Logistic regression is estimated by maximizing the log-likelihood objective function formulated under the assumption of maximizing the overall accuracy. That does not apply to the imbalanced data. The resulting models tend to be biased towards the majority class (i.e. non-event), which can bring great loss in practice. One strategy for mitigating such bias is to penalize the misclassification costs of observations differently in the log-likelihood function. Existing solutions require either hard hyperparameter estimating or high computational complexity. We propose a novel penalized log-likelihood function by including penalty weights as decision variables for observations in the minority class (i.e. event) and learning them from data along with model coefficients. In the experiments, the proposed logistic regression model is compared with the existing ones on the statistics of area under receiver operating characteristics (ROC) curve from 10 public datasets and 16 simulated datasets, as well as the training time. A detailed analysis is conducted on an imbalanced credit dataset to examine the estimated probability distributions, additional performance measurements (i.e. type I error and type II error) and model coefficients. The results demonstrate that both the discrimination ability and computation efficiency of logistic regression models are improved using the proposed log-likelihood function as the learning objective.     

A Joint Modeling Approach for Longitudinal Outcomes and Non-ignorable Dropout under Population Heterogeneity in Mental Health Studies

The paper proposes a joint mixture model to model non-ignorable drop-out in longitudinal cohort studies of mental health outcomes. The model combines a (non)-linear growth curve model for the time-dependent outcomes and a discrete-time survival model for the drop-out with random effects shared by the two sub-models. The mixture part of the model takes into account population heterogeneity by accounting for latent subgroups of the shared effects that may lead to different patterns for the growth and the drop-out tendency. A simulation study shows that the joint mixture model provides greater precision in estimating the average slope and covariance matrix of random effects. We illustrate its benefits with data from a longitudinal cohort study that characterizes depression symptoms over time yet is hindered by non-trivial participant drop-out.KEYWORDS: Latent growth curve, MNAR drop-out, survival analysis, finite mixture model, mental health     

Regression models using the LINEX loss to predict lower bounds for the number of points for approximating planar contour shapes

Researchers in statistical shape analysis often analyze outlines of objects. Even though these contours are infinite-dimensional in theory, they must be discretized in practice. When discretizing, it is important to reduce the number of sampling points considerably to reduce computational costs, but to not use too few points so as to result in too much approximation error. Unfortunately, determining the minimum number of points needed to achieve sufficiently approximate the contours is computationally expensive. In this paper, we fit regression models to predict these lower bounds using characteristics of the contours that are computationally cheap as predictor variables. However, least squares regression is inadequate for this task because it treats overestimation and underestimation equally, but underestimation of lower bounds is far more serious. Instead, to fit the models, we use the LINEX loss function, which allows us to penalize underestimation at an exponential rate while penalizing overestimation only linearly. We present a novel approach to select the shape parameter of the loss function and tools for analyzing how well the model fits the data. Through validation methods, we show that the LINEX models work well for reducing the underestimation for the lower bounds.     

Disentangling the Governance Configurations of Strategic Spatial Plan-Making in European Urban Regions

This paper is aimed at assessing and disentangling how territorial governance configurations influence contemporary practices in strategic plan-making in 14 European urban regions. The findings allow us to distinguish three dominant practices: i) plan-making shaped by consensus building and multilevel government cooperation; ii) plan-making shaped by the involvement of profit-oriented actors and negotiations, and iii) plan-making shaped by consolidated planning practice. To truly grasp plan-making practice, it is necessary to scrutinize who rules and who is ruled while negotiations are unfolding, as well as the extent to which private actors’ interests influence how spatial development goals and strategies are defined.     

Evaluation of Proactive and Reactive Strategies for Polio Eradication Activities in Pakistan and Afghanistan

Only Pakistan and Afghanistan reported any polio cases caused by serotype 1 wild polioviruses (WPV1s) in 2017. With the dwindling cases in both countries and pressure to finish eradication with the least possible resources, a danger exists of inappropriate prioritization of efforts between the two countries and insufficient investment in the two countries to finish the job. We used an existing differential‐equation‐based poliovirus transmission and oral poliovirus (OPV) evolution model to simulate a proactive strategy to stop transmission, and different hypothetical reactive strategies that adapt the quality of supplemental immunization activities (SIAs) in response to observed polio cases in Pakistan and Afghanistan. To account for the delay in perception and adaptation, we related the coverage of the SIAs in high‐risk, undervaccinated subpopulations to the perceived (i.e., smoothed) polio incidence. Continuation of the current frequency and quality of SIAs remains insufficient to eradicate WPV1 in Pakistan and Afghanistan. Proactive strategies that significantly improve and sustain SIA quality lead to WPV1 eradication and the prevention of circulating vaccine‐derived poliovirus (cVDPV) outbreaks. Reactive vaccination efforts that adapt moderately quickly and independently to changes in polio incidence in each country may succeed in WPV1 interruption after several cycles of outbreaks, or may interrupt WPV1 transmission in one country but subsequently import WPV1 from the other country or enable the emergence of cVDPV outbreaks. Reactive vaccination efforts that adapt independently and either more rapidly or more slowly to changes in polio incidence in each country may similarly fail to interrupt WPV1 transmission and result in oscillations of the incidence. Reactive strategies that divert resources to the country of highest priority may lead to alternating large outbreaks. Achieving WPV1 eradication and subsequent successful OPV cessation in Pakistan and Afghanistan requires proactive and sustained efforts to improve vaccination intensity in under‐vaccinated subpopulations while maintaining high population immunity elsewhere.