James A. McRae

Barriers to care among american indians in public health care programs

Objective:We sought to examine the extent to which reported barriers to health care services differ between American Indians (AIs) and non-Hispanic Whites (Whites). Methods:A statewide stratified random sample of Minnesota health care program enrollees was surveyed. Responses from AI and White adult enrollees (n = 1281) and parents of child enrollees (n = 572) were analyzed using logistic regression models that account for the complex sample design. Barriers examined include: financial, access, and cultural barriers, confidence/trust in providers, and discrimination. Results:Both AIs and Whites report barriers to health care access. However, a greater proportion of AIs report barriers in most categories. Among adults, AIs are more likely to report racial discrimination, cultural misunderstandings, family/work responsibilities, and transportation difficulties, whereas Whites are more likely to report being unable to see their preferred doctor. A higher proportion of adult enrollees compared with parents of child enrollees report barriers in most categories; however, differences between parents of AIs and White children are more substantial. In addition to racial discrimination and cultural misunderstandings, parents of AI children are more likely than parents of White enrollees to report limited clinic hours, lack of respect for religious beliefs, and mistrust of their childs provider as barriers. Conclusions:Although individuals have enrolled in health care programs and have access to care, barriers to using these services remain. Significant differences between AIs and Whites involve issues of trust, respect, and discrimination. Providers must address barriers experienced by AIs to improve accessibility, acceptability, and quality of care for AI health care consumers.

The effects of data collection mode and disclosure on adolescent reporting of health behavior

This study examined how information obtained from an adolescent screening instrument administered in a medical clinic is affected by the method of data collection and knowledge that a summary report would be given to the provider. The Adolescent Health Review (AHR) was administered to 610 adolescent patients randomly assigned to 1 of 3 conditions to test the effect of mode of administration (paper vs. computer) and disclosure of results to the provider versus only to researchers (using the computer version). The AHR obtained information on mental health, sexual experiences, and use of psychoactive substances. Response patterns varied by mode of administration, with the paper version generally eliciting higher, and arguably more accurate, rates of disclosure. Knowing that the results would be provided to the doctor further attenuated disclosure. Results suggest that the paper versions higher rates of reporting must be weighed against the computer versions benefits of automated scoring and reporting.

A Comparison of Self-Reported Use of Behavioral Health Services With Medicaid Agency Records in Minnesota

OBJECTIVE This study examined how well recipients of psychiatric or substance abuse services self-report their care. METHODS Self-reported use of behavioral health services, as reported by 1,012 respondents to a survey mailed to Minnesota Medicaid managed care enrollees receiving services with a behavioral health diagnosis other than severe mental illness in 2000, was compared with Medicaid agency records. RESULTS Overall, 15 percent of respondents said they had not received services, although administrative data indicated otherwise. In bivariate analyses, failure to report treatment was associated with gender, age, education, and diagnosis but not with race or ethnicity or with residence. The effects of gender and diagnosis were insignificant after analyses controlled for age and education. CONCLUSIONS Self-reports of behavioral health service use are a relatively accurate method of obtaining information on use. The finding that underreporting of receipt of behavioral health services was not random suggests that reporting errors could introduce bias when comparing groups that differ on age or education.

Rasch measurement and differences between women and men in self-esteem☆

Abstract Most researchers who investigate sociological influences on emotional well-being or distress employ correlational methods as justification for the scales used as measures of distress (factor analysis) and to describe the effects of various factors on distress (regression). This paper suggests that log-linear and related models offer certain advantages over the linear model which have largely been ignored. An analysis of the cross-classification of items included in a widely used measure of self-esteem suggests that one of the items must be eliminated to approximately achieve measurement as defined by Rasch. The resultant latent variable shows no difference in self-esteem between women and men. An analysis of the additive index which includes all of the items, however, reveals that women have lower self-esteem than do men. This apparent difference results solely from a difference on the discrepant item: women are less likely than men to report that they often, rather than sometimes or rarely, can do things as well as most other people.

Estimating the Prevalence of Substance Abuse with Social Indicators

Governments are increasingly interested in estimating the prevalence of substance abuse with social indicators, largely because of the high cost of estimating prevalence with surveys of random samples of the population. With both the individual and county as the unit, we regress measures of the use of alcohol, marijuana, and other drugs on social indicators that fall into three categories: demographics, measures of social disorganization, and measures more directly related to the use of substances. The measures of explained variance are fairly low, but even more troubling is that the effects of several social indicators are in the “wrong” direction. Reliance on social indicator data to supplant survey estimates of the prevalence of substance abuse requires further validation, attention to sources of bias in the indicator data, and replication of the models over time.