Dan L. Tweed

Depression and health-related quality of life.

Chronic medical conditions drastically affect the lives of those afflicted, leading to pain, disability, and disruption. Comorbid depression can exacerbate the effects of medical illness and may be an independent source of suffering and disability. Data from the Epidemiological Follow-Up Study (NHEFS) of the first National Health and Nutrition Examination Survey (NHANES I) are used to examine the manner in which depression and comorbid medical conditions interact to affect health-related quality of life (HRQOL). The findings suggest a) that the effects of depression are comparable with those of arthritis, diabetes, and hypertension; and b) that depression and chronic medical illnesses interact to amplify the effects of the medical illness. The data also support the merit of adopting a multidimensional approach to HRQOL rather than treating it unidimensionally.

Insurance Coverage and Mental Health Service Use by Adolescents with Serious Emotional Disturbance

This paper examines the relationships between insurance coverage, need, and mental health services in a community-based sample of 1,015 youths who were 9, 11, and 13 years old at the beginning of the study. They were followed over a two-year period. A strong measure of need based on a standardized diagnostic interview was available and repeated over three annual waves. Data on service use was collected quarterly across two years. Major findings included: (a) high need (serious emotional disturbance [SED]) was strongly related to use of any mental health services; (b) services use was much more likely to occur with public (Medicaid) insurance coverage than either private or no insurance; (c) considerable unmet need was observed even for youths with SED; (d) school-based mental health services potentially substituted for professional mental health services; and (e) there was little unnecessary use of mental health services in the low need group. The major policy implication of these findings is that the regulation of insurance benefits should be based on level of need, rather than on arbitrary limits which are likely to either reduce the probability of or appropriate amount of care for youths who most need mental health services.

Depression-related impairment: estimating concurrent and lingering effects

This article examines the effects of depression in the sphere of social functioning. On the basis of previous research, it is hypothesized that a major depressive episode has both concurrent and lingering effects and that these effects are a function of the clinical features associated with the episode. This hypothesis is examined using a large community sample and a non-linear model containing both concurrent and lingering effect parameters. The results corroborate the hypothesized effects. Limitations of the current study are discussed and suggestions are offered regarding appropriate research designs. It is suggested that the most general limitation is theoretical. The existence of lingering effects is a phenomenon which presents a theoretical challenge that may prove strategic in understanding the nature and course of depression.

I. Validation of indirect methods to estimate need for mental health services: Concepts, strategy, and general conclusions

Abstract This first of six articles presents a summary and overview of a large-scale needs-assessment research project in Colorado. Its primary goal was to test empirically the validity of a number of statistical procedures or “models” currently available for indirectly estimating the need for alcohol, drug abuse, and mental health (ADM) services in an entire state or region and across its geographic subareas. The models examined included both “social-indicator” and “syntheticestimation” types, several of which are currently used by state public mental health systems as part of their mental health services planning and funding procedures. The validating criteria of need, against which predictions of the various models were tested, were provided by the Colorado Social Health Survey (CSHS), a household-based probability sample of 4,745 adults aged 18 and over. The survey used three different measures of need: (1) diagnosable disorders as assessed by the Diagnostic Interview Schedule, (2) project-developed scales for dysfunction in everyday living, and (3) “demoralization” as assessed with the Center for Epidemiologic Studies — Depression (CES-D) Scale. These assessments were intercorrelated only slightly, suggesting multiple types or components of need for ADM services and indicating an overall current prevalence rate of 26.5% for all categories of need for services. While few of the models as originally constructed performed well in predicting to different categories of need for services across the 48 Colorado subareas surveyed, most displayed considerable potential for improving the accuracy of needs estimation when compared to using a uniform or “flat” rate of need for services in all subareas. After model parameters were adjusted to provide the best possible fit with survey results, two existing models and two new models were selected as most promising for use by states and others interested in indirectly estimating need for ADM services. Use of such models for making the best available estimates of need is strongly recommended.

Hospital Stressors Experienced by Elderly Medical Inpatients: Developing a Hospital Stress Index

Objective: To develop a long and short version of an index to measure experiences during hospitalization perceived by elderly patients as stressful. Samples and Methods: Consecutive patients aged sixty or over admitted to a university teaching hospital were assessed for hospital-related stressors during two separate studies. In the first study, seventy-six patients were asked an open-ended question exploring what they found most stressful about being in the hospital. Responses were grouped into major categories, and questions were developed to address concerns in each category; the resulting forty items were called the Hospital Stress Index (HSI). The HSI was then administered to a separate group of ninety-two patients; data were also collected on functional disability (impaired ADLs), dysfunctional attitudes (DAS), and depressive symptoms (CES-D). Results: Spontaneously reported hospital stressors were grouped into seven categories: 1) adverse effects of diagnostic or therapeutic procedures/treatments, 2) forced life-style changes, 3) relationships with staff, 4) individual psychiatric issues, 5) understanding diagnosis/prognosis, 6) family issues, and 7) the physical environment. The largest category of stressors concerned relationships with doctors and nurses. High HSI scores were significantly more common among Whites than Blacks and among patients with high CES-D, high DAS, or impaired ADLs scores. A number of potentially modifiable hospital-related stressors and individual patient issues were identified. Finally, an abbreviated fifteen-item HSI was developed to maximize patient discriminability, highlight individual differences, and enhance the detection of modifiable stressors. Conclusions: Hospital-reported stressors may contribute to the emotional distress that elderly inpatients experience. We have developed an index to identify such stressors.

VI. Implementing indirect needs-assessment models for planning state mental health and substance abuse services☆☆☆

Abstract This article addresses several services-planning issues necessary for successful implementation of an indirect needs-assessment model to estimate geographic differences in the prevalence of needs for alcohol, drug abuse, and mental health (ADM) services. These include: (1) definition and selection of appropriate ADM services need categories as “target groups”, (2) selection of a model that can validly estimate the prevalence of those need categories, and (3) understanding the data requirements, calculation procedures, and limitations on the generalizability of selected models. A strategy for making the best possible use of indirect needs-assessment models, additional research findings to buttress the validity of selected models, and procedures for model implementation in a state are also presented. A key to effective use of such procedures is clear identification of the target groups to be estimated, ranging from the broadest and most prevalent to highly specialized, low-prevalence need groups. Because predictive models are weaker with narrowly defined, low-prevalence need categories than with larger ones, and because of the importance of presenting a full picture of the ADM needs of a state, it is recommended that states employ a series of “nested” target groups that represent the full range of population needs. While the originally proposed models studied here would be useful with higher-prevalence need categories, only two newly developed models that involve the poverty social indicator could successfully predict to low-prevalence surveyed “chronic mental illness” in this study. Enough is now known about indirect needs-assessment models to warrant implementation by states of one of the better-performing models. The results presented strongly support the validity and potential utility of specific models for estimating varieties of need for ADM services at both state and subarea levels.

IV. Social-indicator models for indirectly assessing mental health service needs: Epidemiologic and statistical properties

Abstract In this fourth of a six-article series, six existing statistical procedures or “models” for indirectly estimating the prevalence of need for alcohol, drug abuse, and mental health (ADM) services in a large region or state and across its smaller subareas are described and critiqued in terms of their epidemiologic and statistical characteristics. These models capitalize upon demonstrated or assumed epidemiologic relationships between the predictor variables and different categories or components of need for ADM services, at least in clinical patient groups. Five of the six models reviewed produce quantitative estimates of general-population prevalence rates for ADM service needs in different subregions or subareas, while the sixth provides only a ranking of subareas with respect to need. This analytic review and critique indicated that several of the models were impressive with respect to their basic methodology and epidemiologic sophistication. However, they all displayed some shortcomings, ranging from minor problems such as reliance upon potentially outdated decennial census data to more serious ones involving the methodological core of the procedure and/or miscalibration of the models parameters. The least problematic model on an a priori basis appeared to be a Synthetic Estimation procedure, although several other models were felt to have greater potential for improvement in predictive accuracy. Specific advantages and disadvantages of each model are listed and summarized for consideration by ADM services planners, both to encourage implementation of such models for indirectly assessing need for ADM services across a number of regions or state subareas, and to facilitate selection by state or local planners of one or more models appropriate to their particular situation.

The Colorado homeless mentally ill: Users and nonusers of services: An empirical investigation of “difficult to treat” characteristics

This study examines the mental health problems of a selected case sample of homeless mentally ill (HMI) men and women in Colorado. The HMI sample was selected to compare those HMI who utilize mental health services (N = 46) with those who do not (N = 50) with respect to psychopathology and to characteristics related to being “difficult to treat.” Findings show that although the HMI current users are slightly more dysfunctional than the non-users, the rates of serious disorders are high among both HMI groups. HMI current users of mental health services, particularly voluntary users, were found to have fewer “difficult to treat” characteristics than the nonusers.

V. Empirical validity of indirect mental health needs-assessment models in Colorado☆

This article presents the results of empirical validation studies of six statistical models currently available for indirectly estimating the need for alcohol, drug abuse, and mental health (ADM) services across a large geographic area such as a state. Initial analyses show that the basic assumptions regarding geographic variations in need which are shared by all such models can be substantiated by data from the Colorado Social Health Survey (CSHS) of diagnosable disorders, dysfunction in everyday living, and demoralization. Next, the performance of the original versions of the six models on three statistical tests of the match between model predictions and surveyed ADM service needs is presented. The tests show how well each models predictions of need prevalence in 48 small subareas of Colorado compared with surveyed needs in those same areas. Results indicate that in their original form, none of the models were accurate predictors of surveyed need for ADM services in Colorado, but that they did show predictive potential in terms of their epidemiologic relationships with surveyed need. Following “optimization” of the model equations by adjusting their parameters to best fit the CSHS data, repeated analyses indicated that all models except one were considerably more accurate predictors than a flat-rate model based on the assumption of equal need across all subareas. A modified two-variable linear regression model developed by Stem was the best all-around performer on the evaluations of prediction accuracy, followed by the Synthetic Estimation model. Two “experimental” regression models containing the better predictors found among the original models (poverty and divorce rates) also performed very well. The demonstrated performance of these optimized and experimental models provides additional evidence of the utility of selected models as services planning and budgeting tool for states. These models are further evaluated with respect to frequently designated high-priority “target” populations in the next article.