Factors related to employment among chronically mentally ill patients

A descriptive study of demographic and psychosocial factors believed to be associated with employment was carried out through face-to-face interviews with 417 chronically mentally-ill patients. Subjects had been hospitalized a minimum of two times for psychiatric treatment, had been discharged from at least one of these hospitalizations in the two years prior to the study, and were currently residing within a specific community mental health center catchment area in Texas. The study group ranged in age from 16 to 68 years and over one-half had chart diagnoses of schizophrenia.^ A structured interview was developed which addressed current employment status, length of current employment, job title of current or last job, and detailed work history for the prior five years. Four measures of social support were included in the interview. Each subject was asked to identify one recent work and one recent non-work situation which had been stressful or very demanding. A coping questionnaire was verbally administered to measure the ways in which subjects had coped with these specific stressful situations.^ Analysis of results revealed that 27 percent of the sample was gainfully employed at time of interview. Differences between the employed and unemployed groups were analyzed by t-test an chi square. The employed demonstrated significantly more weeks of employment in the prior five years than the unemployed. The current jobs of the employed required a significantly higher relationship to "things" or inanimate objects than the last jobs of the unemployed. Subjects diagnosed as schizophrenic were significantly less likely to be employed than subjects with other diagnoses.^ Employed subjects scored significantly higher on three of four measures of social support than unemployed subjects, including reported frequency of social group attendance and/or meetings with mental health professionals. Problem-focused coping was used significantly more by the employed than by the unemployed to deal with stressful situations in the work, but not the non-work, context. ^

Procedure for the identification of population characteristics for targeting intervention services on the basis of outcome-goal priorities: Case management services for the chronic mentally ill

Although the processes involved in rational patient targeting may be obvious for certain services, for others, both the appropriate sub-populations to receive services and the procedures to be used for their identification may be unclear. This project was designed to address several research questions which arise in the attempt to deliver appropriate services to specific populations. The related difficulties are particularly evident for those interventions about which findings regarding effectiveness are conflicting. When an intervention clearly is not beneficial (or is dangerous) to a large, diverse population, consensus regarding withholding the intervention from dissemination can easily be reached. When findings are ambiguous, however, conclusions may be impossible.^ When characteristics of patients likely to benefit from an intervention are not obvious, and when the intervention is not significantly invasive or dangerous, the strategy proposed herein may be used to identify specific characteristics of sub-populations which may benefit from the intervention. The identification of these populations may be used both in further informing decisions regarding distribution of the intervention and for purposes of planning implementation of the intervention by identifying specific target populations for service delivery.^ This project explores a method for identifying such sub-populations through the use of related datasets generated from clinical trials conducted to test the effectiveness of an intervention. The method is specified in detail and tested using the example intervention of case management for outpatient treatment of populations with chronic mental illness. These analyses were applied in order to identify any characteristics which distinguish specific sub-populations who are more likely to benefit from case management service, despite conflicting findings regarding its effectiveness for the aggregate population, as reported in the body of related research. However, in addition to a limited set of characteristics associated with benefit, the findings generated, a larger set of characteristics of patients likely to experience greater improvement without intervention. ^

Biomarker circadian rhythm profiles in critically ill mechanically ventilated patients

Objective: To explore the natural trajectory of core body temperature (CBT) and cortisol (CORT) circadian rhythms in mechanically ventilated intensive care unit (MV ICU) patients. ^ Design: Prospective, observational, time-series pilot study. ^ Setting: Medical-surgical and pulmonary ICUs in a tertiary care hospital. ^ Sample: Nine (F = 3, M = 6) adults who were mechanically ventilated within 12 hrs of ICU admission with mean ± SD age of 65.2 ± 14 years old. ^ Measurements: Core body temperature and environmental measures of light, sound, temperature, and relative humidity were logged in 1-min intervals. Hourly urine specimens and 2-hr interval blood specimens were collected for up to 7 consecutive days for CORT assay. Mechanical ventilation days, ICU length of stay, and ICU mortality were documented. Acute Physiology and Chronic Health Evaluation (APACHE) II scores were computed for each study day. The data of each biologic and environmental variable were analyzed using single cosinor analysis of 24-hr serial segments. One patient did not complete the study because mortality occurred within 8 hrs of enrollment. Nine ICU patients completed the study in 1.6 to 7.0 days. ^ Results: No normal circadian rhythm pattern was found when the cosinor-derived parameters of amplitude (one-half the peak-trough variability) and acrophase (peak time) were compared with cosinor-derived parameter reference ranges of healthy, diurnally active humans, although 83% of patient-day CBT segments showed statistically significant (p ≤ .05) and biologically meaningful (R2≥ 0.30) 24-hr rhythms with abnormal cosinor parameters. Cosinor parameters of the environmental temporal profiles showed 27% of light, 76% of ambient temperature, and 78% of relative humidity serial segments had a significant and meaningful 24-hr diurnal pattern. Average daily light intensity varied from 34 to 187 lx with a maximum light exposure of 1877 lx. No sound measurement segment had a statistically significant cosine pattern, and numerous 1-minute interval peaks ≥ 60 dB occurred around the clock. Average daily ambient temperature and relative humidity varied from 19 to 24°C and from 25% to 61%, respectively. There was no statistically significant association between CBT or clinical outcomes and cosinor-derived parameters of the environmental variables. Circadian rhythms of urine and plasma CORT were deferred for later analysis. ^ Conclusions: The natural trajectory of the CBT circadian rhythm in MV ICU patients demonstrated persistent cosinor parameter alteration, even when a significant and meaningful 24-hr rhythm was present. The ICU environmental measures showed erratic light and sound exposures. Room temperature and relative humidity data produced the highest rate of significant and meaningful diurnal 24-hr patterns. Additional research is needed to clarify relations among the CBT biomarker of the circadian clock and environmental variables of MV ICU patients. ^

Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

The New Futuro College Plan: Facilitating College Access

Built on a free, bilingual, "high-touch, high-tech" platform, New Futuro has created a robust community of Latino students and parents, non-profit organizations, education institutions, government agencies, and corporations to connect those that need help with those that provide it. One of the resources developed by New Futuro is a proprietary 10-Steps College Plan that provides structured information targeted to Latino students and families to help them prepare, apply and pay for college.

When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students

In 1998, Texas initiated a bold new statewide university admission policy aimed at increasing college access for traditionally underserved students in the state. House Bill 588 (known as the Texas Top 10 Percent Plan (TTPP)) guaranteed automatic admission to the college or university of their choice for all top performing students in Texas public high schools. Fourteen years after the plan’s implementation, we see great strides and complexities in understanding student outcomes as a result of the percent plan. However, the legal controversy over the percent plan both in Texas and other states incorporating similar yet distinctly motivated alternative admissions plans continues to play out from institutional decision boards to the highest court in the nation. This study seeks to add to that discussion by exploring two questions. Descriptively, what are the admission and enrollment patterns within racial/ethnic groups of percent plan eligible students, over time, for Texas elite, emergent elite, and remaining public institutions? Given that all eligible percent plan students may enter the institution of choice in Texas, does which type of institution a TTPP student chooses relate to their race/ethnicity? The descriptive story told by the admission and enrollment distributions of equally eligible TTPP students is a complex but compelling one. Fundamentally, it identifies that statistically different application and enrollment patterns exist for Hispanic and especially African American TTPP beneficiaries relative to their White and Asian American counterparts.

Commentary on "When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students"

Invited commentary on "When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students" by Catherine Horn and Stella Flores.

Predictive validity of the personal background and preparation survey and effectiveness of targeted interventions among health science community college students

Existing data, collected from 1st-year students enrolled in a major Health Science Community College in the south central United States, for Fall 2010, Spring 2011, Fall 2011 and Spring 2012 semesters as part of the "Online Navigational Assessment Vehicle, Intervention Guidance, and Targeting of Risks (NAVIGATOR) for Undergraduate Minority Student Success" with CPHS approval number HSC-GEN-07-0158, was used for this thesis. The Personal Background and Preparation Survey (PBPS) and a two-question risk self-assessment subscale were administered to students during their 1st-year orientation. The PBPS total risk score, risk self-assessment total and overall scores, and Under Representative Minority Student (URMS) status were recorded. The purpose of this study is to evaluate and report the predictive validity of the indicators identified above for Adverse Academic Status Events (AASE) and Nonadvancement Adverse Academic Status Events (NAASE) as well as the effectiveness of interventions targeted using the PBPS among a diverse population of health science community college students. The predictive validity of the PBPS for AASE has previously been demonstrated among health science professions and graduate students (Johnson, Johnson, Kim, & McKee, 2009a; Johnson, Johnson, McKee, & Kim, 2009b). Data will be analyzed using binary logistic regression and correlation using SPSS 19 statistical package. Independent variables will include baseline- versus intervention-year treatments, PBPS, risk self-assessment, and URMS status. The dependent variables will be binary AASE and NAASE status. ^ The PBPS was the first reliable diagnostic and prescriptive instrument to establish documented predictive validity for student Adverse Academic Status Events (AASE) among students attending health science professional schools. These results extend the documented validity for the PBPS in predicting AASE to a health science community college student population. Results further demonstrated that interventions introduced using the PBPS were followed by approximately one-third reduction in the odds of Nonadvancement Adverse Academic Status Events (NAASE), controlling for URMS status and risk self-assessment scores. These results indicate interventions introduced using the PBPS may have potential to reduce AASE or attrition among URMS and nonURMS attending health science community colleges on a broader scale; positively impacting costs, shortages, and diversity of health science professionals.^