Ruth M. Mickey

Mental health of lesbian, gay, bisexual, and heterosexual siblings: effects of gender, sexual orientation, and family.

Self-identified lesbian, gay male, and bisexual (LGB) individuals were recruited via convenience sampling, and they in turn recruited their siblings (79% heterosexual, 19% LGB). The resulting sample of 533 heterosexual, 558 lesbian or gay male, and 163 bisexual participants was compared on mental health variables and their use of mental health services. Multilevel modeling analyses revealed that sexual orientation predicted suicidal ideation, suicide attempts, self-injurious behavior, use of psychotherapy, and use of psychiatric medications over and above the effects of family adjustment. Sexual orientation was unrelated to current psychological distress, psychiatric hospitalizations, and self-esteem. This is the 1st study to model family effects on the mental health of LGB participants and their siblings.

Brothers and Sisters of Lesbians, Gay Men, and Bisexuals as a Demographic Comparison Group An Innovative Research Methodology to Examine Social Change

This study provides an innovative methodology to study social issues across sexual orientations. Lesbians, gay men, and bisexualwomen and men (LGB) were recruited via LGB periodicals and organizations, and they in turn recruited their siblings. Results of female participants indicate that lesbians are more highly educated, have occupations with greater status, are less religious, and are more geographically mobile than are heterosexual women. Heterosexual women are more similar to census data in terms of marriage, children, religion, and homemaker status. Gay men have moved to large cities and are more highly educated than are heterosexual men. In general, bisexual women are more comparable demographically to lesbians, whereas bisexual men are more similar to heterosexual men. Limiting the sample to paired comparisons between lesbian-heterosexual sisters and gay-heterosexual brothers generally yielded similar means on demographic variables.

DETERMINANTS OF WOOD THRUSH NEST SUCCESS: A MULTI-SCALE, MODEL SELECTION APPROACH

Abstract We collected data on 212 wood thrush (Hylocichla mustelina) nests in central New York from 1998 to 2000 to determine the factors that most strongly influence nest success. We used an information–theoretic approach to assess and rank 9 models that examined the relationship between nest success (i.e., the probability that a nest would successfully fledge at least 1 wood thrush offspring) and habitat conditions at different spatial scales. We found that 4 variables were significant predictors of nesting success for wood thrushes: (1) total core habitat within 5 km of a study site, (2) distance to forest–field edge, (3) total forest cover within 5 km of the study site, and (4) density and variation in diameter of trees and shrubs surrounding the nest. The coefficients of these predictors were all positive. Of the 9 models evaluated, amount of core habitat in the 5-km landscape was the best-fit model, but the vegetation structure model (i.e., the density of trees and stems surrounding a nest) was also supported by the data. Based on AIC weights, enhancement of core area is likely to be a more effective management option than any other habitat-management options explored in this study. Bootstrap analysis generally confirmed these results; core and vegetation structure models were ranked 1, 2, or 3 in over 50% of 1,000 bootstrap trials. However, bootstrap results did not point to a decisive model, which suggests that multiple habitat factors are influencing wood thrush nesting success. Due to model uncertainty, we used a model averaging approach to predict the success or failure of each nest in our dataset. This averaged model was able to correctly predict 61.1% of nest outcomes.

Predicting Minimum Habitat Characteristics for the Indiana Bat in the Champlain Valley

Abstract Predicting potential habitat across a landscape for rare species is extremely challenging. However, partitioned Mahalanobis D2 methods avoid pitfalls commonly encountered when surveying rare species by using data collected only at known species locations. Minimum habitat requirements are then determined by examining a principal components analysis to find consistent habitat characteristics across known locations. We used partitioned D2 methods to examine minimum habitat requirements of Indiana bats (Myotis sodalis) in the Champlain Valley of Vermont and New York, USA, across 7 spatial scales and map potential habitat for the species throughout the same area. We radiotracked 24 female Indiana bats to their roost trees and across their nighttime foraging areas to collect habitat characteristics at 7 spatial scales: 1) roost trees, 2) 0.1-ha circular plots surrounding the roost trees, 3) home ranges, and 4–7) 0.5-km, 1-km, 2-km, and 3-km buffers surrounding the roost tree. Roost trees (n = 50) typically were tall, dead, large-diameter trees with exfoliating bark, located at low elevations and close to water. Trees surrounding roosts typically were smaller in diameter and shorter in height, but they had greater soundness than the roost trees. We documented 14 home ranges in areas of diverse, patchy land cover types that were close to water with east-facing aspects. Across all landscape extents, area of forest within roost-tree buffers and the aspect across those buffers were the most consistent features. Predictive maps indicated that suitable habitat ranged from 4.7–8.1% of the area examined within the Champlain Valley. These habitat models further understanding of Indiana bat summer habitat by indicating minimum habitat characteristics at multiple scales and can be used to aid management decisions by highlighting potential habitat. Nonetheless, information on juvenile production and recruitment is lacking; therefore, assessments of Indiana bat habitat quality in the region are still incomplete.

Comparability of Telephone and Household Breast Cancer Screening Surveys with Differing Response Rates

We compared telephone and household surveys as methods for obtaining information about breast cancer screening. The study population was comprised of women age 40 years or older who were permanent residents of two large areas of Florida. We contacted women using random digit dialing for the telephone survey. We used a stratified multistage design for the household survey. Response rates were 49% (telephone) and 77% (household). Distributions of most screening (mammography, clinical examination, and breast self-examination) and demographic variables were comparable for the two surveys; income was higher in the telephone survey. Both surveys underestimated the proportion of older women, based on 1990 Census data.

An immunogenetic study of suppressor cell activity in autoimmune chronic active hepatitis

Some patients with autoimmune chronic active hepatitis as well as their disease-free first degree relatives show decreased suppressor cell activity of peripheral blood T lymphocytes. Studies were therefore undertaken in families ascertained by the presence of a single chronic active hepatitis patient to determine if this abnormality of immune regulation represents a genetic phenotype simply controlled by a gene or genes at a putative disease susceptibility locus and, further, if this locus showed linkage to either the HLA or the immunoglobulin constant region loci. In addition to determining circulating autoantibody status and genotyping for HLA and immunoglobulin allotypes, suppressor T cells were evaluated by surface markers and by determining their ability to suppress IgG secretion in vitro. The results suggest that immunoregulatory dysfunction in autoimmune chronic active hepatitis is a familial abnormality, but that this abnormality occurs independent of circulating autoantibody status and of the segregation of genes for HLA or immunoglobulin allotypes.

Assessment of self-reward strategies for maintenance of breast self-examination.

This study examined the relative impact of different self-reward strategies on maintenance of breast self-examination (BSE) practice among 1649 women trained to do BSE. Training groups were randomized into four conditions: (a) self-reward instructions and materials delivered at the end of the BSE training session; (b) self-reward suggestions delivered through the mail each month, contingent upon the BSE performance; (c) external monetary rewards and self-reward suggestions delivered through the mail each month on an intermittent schedule, contingent upon BSE practice; and (d) a no-reward control condition. Follow-up assessments 12 months following training revealed a pattern of evidence in support of the benefits of external monetary rewards and self-reward prompts on BSE frequency and quality; however, it is likely that the value of that condition lies in the external reward component.

Analysis of multiple outcome variables measured longitudinally

Abstract We present methods for the analysis of multiple outcome variables collected longitudinally. We provide a multivariate version of the two stage random effects model described by Harville (J. Amer. Statist. Assoc. 72, 1977) and Laird and Ware (Biometrics 38, 1982) as well as the computational details for maximum likelihood estimation of model parameters using the EM algorithm. Further summarization of the outcome variables in terms of their linear combination is investigated. Two general criteria are considered for determining the coefficients: maximization of the variance of the linear combination and maximization of the fit of the model. Principal components analysis is used to identify combinations with maximum variance while other eigensystem procedures are used to find combinations with maximum fit. These two selection criteria may be used in various ways to determine the coefficients. We illustrate the application of the model and alternative ways of determining the linear combination of three lung function measures obtained repeatedly from sarcoidosis patients.

Assessment of three way interaction in 2 x J x K tables

Abstract The power of a test for no three way interaction in 2 × J × K tables, performed by partitioning the K strata into two groups was investigated by simulation. Mantel-Haenszel estimation techniques were used to calculate the test statistic. The power was compared with that of Pearsons X 2 and the likelihood ratio G 2 . The partition test had substantially greater power than either X 2 or G 2 in cases most favorable to the partition test and somewhat greater power for cases moderately favorable to it. The greater power can be explained by the smaller degrees of freedom for the partition test ( J − 1 vs ( J − 1)( K − 1) for X 2 and G 2 ). The results also suggest that the distribution of the test statistic more closely follows a non-central chi square distribution in non-null cases for the partition test. If an appropriate partitioning of the strata can be made, the partitioning test would be preferable to the widely used X 2 and G 2 tests.

Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the Northeastern United States

Landscape connectivity is integral to the persistence of metapopulations of wide ranging carnivores and other terrestrial species. The objectives of this research were to investigate the landscape characteristics essential to use of areas by lynx and bobcats in northern New England, map a habitat availability model for each species, and explore connectivity across areas of the region likely to experience future development pressure. A Mahalanobis distance analysis was conducted on location data collected between 2005 and 2010 from 16 bobcats in western Vermont and 31 lynx in northern Maine to determine which variables were most consistent across all locations for each species using three scales based on average 1) local (15 minute) movement, 2) linear distance between daily locations, and 3) female home range size. The bobcat model providing the widest separation between used locations and random study area locations suggests that they cue into landscape features such as edge, availability of cover, and development density at different scales. The lynx model with the widest separation between random and used locations contained five variables including natural habitat, cover, and elevation—all at different scales. Shrub scrub habitat—where lynx’s preferred prey is most abundant—was represented at the daily distance moved scale. Cross validation indicated that outliers had little effect on models for either species. A habitat suitability value was calculated for each 30 m2 pixel across Vermont, New Hampshire, and Maine for each species and used to map connectivity between conserved lands within selected areas across the region. Projections of future landscape change illustrated potential impacts of anthropogenic development on areas lynx and bobcat may use, and indicated where connectivity for bobcats and lynx may be lost. These projections provided a guide for conservation of landscape permeability for lynx, bobcat, and species relying on similar habitats in the region.