Bibliography of Bioethics and Index Medicus: comparison of coverage, publication delay, and ease of recall for journal articles on bioethics

Citations selected from the bibliographies of recent texts, a specialized subject bibliography, and review articles were checked in both Cumulated Index Medicus (IM) and the Bibliography of Bioethics (BB) to compare coverage, publication delay, probable causes of indexing and retrieval failure, and the ease with which relevant citations were retrieved. The study also attempted to determine whether BB included appropriate articles from the MEDLINE database in a timely and systematic manner. While 98% of the IM citations appeared within a year of publication, 79% of the BB citations appeared two to three years after their publication dates. The average citation appeared twice as frequently in IM as in BB.     

Australian PhDs by LIS educators, researchers and practitioners: Depicting diversity and demise

Analyses of more than 73,000 PhD thesis records in a comprehensive database of bibliographic records from all Australian universities from 1948 to 2006 demonstrate that PhDs on LIS-related topics reveal not only diversity of content, but also the diverse nature of the researcher's academic disciplines. This diversity includes researchers from within and outside LIS who bring to LIS–or take away–a variety of methods, approaches, theories and understandings. With 27 of Australia's 39 universities having produced LIS-related PhD graduates, the distribution through the Australian university system is evident and emphasizes the transferability of skills and knowledge which graduates bring to their work. It is possible that the diversity of researcher's disciplines, combined with the dangerously low numbers of LIS graduations, may also threaten the future of LIS research and education in Australia. Based on the findings of this study, the sustainability of LIS research and research training for the next generation in Australia is under threat.     

Overcoming problems in doctoral writing through the use of visualisations: telling our stories

Doctoral students experience many challenges on the long journey towards completion. Common problems include: synthesising data, working at a conceptual level, clarifying the relationship of the parts of the thesis to the whole, finding a voice and completing a viva successfully. Few authors have addressed the use of visualisations to meet these challenges. This paper focuses on the use of visualisations in doctoral writing. It presents narratives about seven ways that visualisations can help students to make breakthroughs in their writing, namely, as an organiser of the relationships of the parts of the thesis to the whole, a trigger for peer discourse, a vehicle for conceptual work, a metaphor to express key concepts, a trigger for professional development, a visual aid for the viva and as a prompt for freedrawing and freewriting.     

The role of learned resourcefulness in helping female undergraduates deal with unwanted sexual activity

We examined the relationship between learned resourcefulness skills and the manner in which undergraduate heterosexual women handle unwanted sexual advances/activity. Participants consisted of 150 females completing a set of questionnaires assessing general learned resourcefulness, sexual giving-in experience, sexual resourcefulness, sexual self-efficacy and reasons for consent. The hypothesis that possessing a higher general repertoire of learned resourcefulness skills would uniquely predict greater sexual self-control with unwanted sexual advances was supported. Physical contact with men, greater sexual victimization, more reasons for consenting, and less use of sexual resourcefulness skills all directly contributed to voluntarily giving-in behavior. Implications for sexuality education and counseling are discussed.     

Developing Expertise With Classroom Assessment in K–12 Science: Learning to Interpret Student Work. Interim Findings From a 2-Year Study

This article reports findings on growth in 3 science teachers' expertise with interpretation of student work over 1 year of participation in a program. The program was designed to strengthen classroom assessment. Using a framework for classroom assessment expertise, we analyze patterns of teacher learning, and the roles of the professional program and the quality of the assessments provided with teachers' instructional materials.     

A multivariate latent growth curve analysis of adolescent substance use

This article demonstrates a multivariate latent growth curve methodology (LGM) for analyzing longitudinal adolescent substance use data. Hypotheses concerning the form of growth in substance use, individual differences in the common trajectory over time, and covariates influencing growth were tested. Significant linear increases existed for alcohol, cigarette, and marijuana use. Second‐order multivariate extensions of LGM indicated that associations among the individual differences parameters of the various substances could be adequately modeled by a higher order substance use construct. Family status, parent‐child conflict, peer encouragement for substance use, parent substance use, and age significantly influenced initial levels of use. Peer encouragement, change in peer encouragement, change in parent‐child conflict, age, and gender significantly influenced development of use. These findings support the influence of families and peers on the development of adolescent substance use and demonstrate the utility of multivariate extensions of LGM in the analysis of longitudinal data.     

Longitudinal confirmatory factor analysis: Common,time‐specific,item‐specific,and residual‐error components of variance

Following Cronbach (1970) and others, it is useful to decompose test score variation into common factor, time‐specific, item‐specific, and residual components. In the traditional approach to factor analysis, only two sources of variance can be estimated: common factor variance and a uniqueness term that confounds specific sources of variation and residual error. When the same items are measured on different occasions, however, it is possible to separate specific variance and residual error. Two approaches, the first‐order approach described by Raffalovich and Bohrnstedt (1987) and a second‐order approach based on Jöreskog and Sörbom (1989; Jöreskog, 1974) are considered initially. The two approaches, although based on different rationales, both suffer a similar weakness in that two of the four sources of variance are confounded. In the Raffalovich and Bohrnstedt approach, time‐specific variance is confounded with common factor variance that generalizes across items and time. In the second‐order approach based on Jöreskog and Sörbom, time‐specific variance is confounded with residual error. Here we demonstrate that by combining features from both approaches we can eliminate these weaknesses and estimate all four of Cronbach's sources of variance, and that this combined approach is easily generalized to a wide variety of applications.     

Unconstrained Structural Equation Models of Latent Interactions: Contrasting Residual- and Mean-Centered Approaches

Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual centering for estimating latent interaction effects as an alternative to the mean-centered approach proposed by Marsh, Wen, and Hau (2004, 2006). Little et al. also differed from Marsh et al. in the number of indicators used to infer the latent interaction factor and how they were represented, but this issue is separate from the mean versus residual centering distinction that was their primary focus. However, their implementation of the Marsh et al. mean-centered approach failed to incorporate the mean structure that Marsh et al. argued was necessary to obtain unbiased estimates. One might suppose that their new approach would suffer this same problem, an issue not addressed by Little et al. However, we demonstrate here why the Little et al. approach obviates this requirement that heretofore was thought to be necessary for all constrained, partially constrained, and unconstrained approaches. Both the Marsh et al. and Little et al. unconstrained approaches typically result in similar results and are much easier to implement than traditional constrained approaches. They differ primarily in that the Little et al. approach is a 2-step approach involving a potentially large number of separate analyses prior to estimating the structural equation model that apparently does not require the estimation of a mean structure, whereas the Marsh et al. approach is a 1-step approach that includes a mean structure.