Biomedical subjects

Gitta H Lubke

Publications and source records attributed to Gitta H Lubke.

5 recordsLinked to original sources

PubMed2006

Relationship of family environment and parental psychiatric diagnosis to impairment in ADHD.

OBJECTIVE: Family environmental factors as well as parental attention-deficit/hyperactivity disorder (ADHD) status have shown associations with variability in ADHD. The purpose of the present study was to examine the links among family environment, parental psychiatric diagnosis, and child impairment within a sample of ADHD-affected sibling pairs (ASPs) ages 5 to 18 years. METHOD: Parents in 220 ASP families completed a measure of family functioning, the Family Environment Scale. Children's impairment was measured by clinical ratings of global functioning and by maternal ratings of behavior. RESULTS: Parents of children with ADHD rate their families as higher in conflict and lower in achievement and organization than normative samples. High family conflict is significantly associated with impairment in ADHD ASPs accounting for approximately 40% of the sibling similarity in impairment. Parental psychiatric diagnosis revealed no significant direct link to sibling impairment, but rather a significant indirect link to impairment mediated by family conflict. Direct associations with parental diagnosis depend on birth order of the ASP members despite the comparable mean impairment scores for older and younger ADHD siblings. CONCLUSIONS: There are strong links between impairment in children with ADHD and family environment. Different processes and mechanisms may contribute to impairment in different children in the same family.

Adolescent↗

PubMed2005

Investigating population heterogeneity with factor mixture models.

Sources of population heterogeneity may or may not be observed. If the sources of heterogeneity are observed (e.g., gender), the sample can be split into groups and the data analyzed with methods for multiple groups. If the sources of population heterogeneity are unobserved, the data can be analyzed with latent class models. Factor mixture models are a combination of latent class and common factor models and can be used to explore unobserved population heterogeneity. Observed sources of heterogeneity can be included as covariates. The different ways to incorporate covariates correspond to different conceptual interpretations. These are discussed in detail. Characteristics of factor mixture modeling are described in comparison to other methods designed for data stemming from heterogeneous populations. A step-by-step analysis of a subset of data from the Longitudinal Survey of American Youth illustrates how factor mixture models can be applied in an exploratory fashion to data collected at a single time point.

Child↗

PubMed2004

Implications of absence of measurement invariance for detecting sex limitation and genotype by environment interaction.

Using univariate sum scores in genetic studies of twin data is common practice. This practice precludes an investigation of the measurement model relating the individual items to an underlying factor. Absence of measurement invariance across a grouping variable such as gender or environmental exposure refers to group differences with respect to the measurement model. It is shown that a decomposition of a sum score into genetic and environmental variance components leads to path coefficients of the additive genetic factor that are biased differentially across groups if individual items are non-invariant. The arising group differences in path coefficients are identical to what is known as "scalar sex limitation" when gender is the grouping variable, or as "gene by environment interaction" when environmental exposure is the grouping variable. In both cases the interpretation would be in terms of a group-specific effect size of the genetic factor. This interpretation may be incorrect if individual items are non-invariant.

Algorithms↗

PubMed2003

Weak measurement invariance with respect to unmeasured variables: an implication of strict factorial invariance.

Measurement bias refers to systematic differences across subpopulations in the relation between observed test scores and the latent variant underlying the test scores. Comparisons of subpopulations with the same score on the latent variable can be expected to have the same observed test score. Measurement invariance is therefore one of the key issues in psychological testing. It has been established that strict factorial invariance (SFI) with respect to a selection variable V almost certainly implies weak measurement invariance with respect to V: given SFI, means and variances of observed scores do not depend on V. It is shown that this result can be extended. SFI in groups derived by selection on V has implications not only for V but also for potentially biasing variables W, if W and the selection variable V and/or if W and the factor underlying the observed test scores are statistically dependent. Given SFI with respect to V and prior knowledge concerning these dependencies, it is not necessary to measure and model variables W in order to exclude them as potentially biasing variables if the investigation focuses on groups selected on V.

Analysis of Variance↗

PubMed2002

Memory function during propofol and alfentanil anesthesia: predictive value of individual differences.

BACKGROUND: Conscious recall and implicit memory have been shown to depend on hypnotic state as measured by electroencephalographic (EEG) bispectral index (BIS). A third expression of memory (unconscious-controlled memory) was recently observed after moderate to light sedation (BIS, 70-80). The present study investigated memory function during deep sedation (BIS, 60-70). As memory effects are small, the authors studied potential predictors of individual differences in memory performance. METHODS: Memory function and speed of information processing were assessed in 56 outpatients before surgery. During propofol anesthesia supplemented with alfentanil, patients heard a series of words while anesthesia was titrated to BIS, 60-70. In between words, response to command was assessed using the Isolated Forearm Technique. The authors tested memory with a word stem completion task and process dissociation procedure to distinguish explicit from implicit effects. RESULTS: Mean (+/- SD) BIS during word presentation was 64.0 +/- 3. Patients with conscious recall of verbal commands (n = 9) did not recall or recognize presented words. Even so, the process dissociation procedure revealed evidence of memory by a significantly higher hit rate in the inclusion condition (0.26) than in the exclusion condition (0.12). Patients without conscious recall showed no evidence of memory for presented words. Hit scores correlated significantly with scores in the preoperative memory test (r = 0.35). CONCLUSIONS: The authors found evidence of weak explicit memory function during anesthesia titrated to BIS, 60-70. The observations strongly suggest that postoperative memory relates to awareness during anesthesia, but the nature of this relation remains unclear. Memory seems more likely in patients with good preoperative memory performance.

Adult↗