Larry E. Toothaker

Bio: Larry E. Toothaker is an academic researcher. The author has contributed to research in topics: Segmented regression & Regression diagnostic. The author has an hindex of 1, co-authored 1 publications receiving 11971 citations.

Multiple Regression: Testing and Interpreting Interactions

Abstract: (1994). Multiple Regression: Testing and Interpreting Interactions. Journal of the Operational Research Society: Vol. 45, No. 1, pp. 119-120.

User acceptance of information technology: toward a unified view

Abstract: Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Technology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted R2 of 70 percent). UTAUT thus provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement of the core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use.

The Benefits of Being Present: Mindfulness and Its Role in Psychological Well-Being

Abstract: Mindfulness is an attribute of consciousness long believed to promote well-being. This research provides a theoretical and empirical examination of the role of mindfulness in psychological well-being. The development and psychometric properties of the dispositional Mindful Attention Awareness Scale (MAAS) are described. Correlational, quasi-experimental, and laboratory studies then show that the MAAS measures a unique quality of consciousness that is related to a variety of well-being constructs, that differentiates mindfulness practitioners from others, and that is associated with enhanced selfawareness. An experience-sampling study shows that both dispositional and state mindfulness predict self-regulated behavior and positive emotional states. Finally, a clinical intervention study with cancer patients demonstrates that increases in mindfulness over time relate to declines in mood disturbance and stress. Many philosophical, spiritual, and psychological traditions emphasize the importance of the quality of consciousness for the maintenance and enhancement of well-being (Wilber, 2000). Despite this, it is easy to overlook the importance of consciousness in human well-being because almost everyone exercises its primary capacities, that is, attention and awareness. Indeed, the relation between qualities of consciousness and well-being has received little empirical attention. One attribute of consciousness that has been much-discussed in relation to well-being is mindfulness. The concept of mindfulness has roots in Buddhist and other contemplative traditions where conscious attention and awareness are actively cultivated. It is most commonly defined as the state of being attentive to and aware of what is taking place in the present. For example, Nyanaponika Thera (1972) called mindfulness “the clear and single-minded awareness of what actually happens to us and in us at the successive moments of perception” (p. 5). Hanh (1976) similarly defined mindfulness as “keeping one’s consciousness alive to the present reality” (p. 11). Recent research has shown that the enhancement of mindfulness through training facilitates a variety of well-being outcomes (e.g., Kabat-Zinn, 1990). To date, however, there has been little work examining this attribute as a naturally occurring characteristic. Recognizing that most everyone has the capacity to attend and to be aware, we nonetheless assume (a) that individuals differ in their propensity or willingness to be aware and to sustain attention to what is occurring in the present and (b) that this mindful capacity varies within persons, because it can be sharpened or dulled by a variety of factors. The intent of the present research is to reliably identify these inter- and intrapersonal variations in mindfulness, establish their relations to other relevant psychological constructs, and demonstrate their importance to a variety of forms of psychological well-being.

Experimental Design and Data Analysis for Biologists

Abstract: An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being.

Abstract: Five studies tested two general hypotheses: Individuals differ in their use of emotion regulation strategies such as reappraisal and suppression, and these individual differences have implications for affect, well-being, and social relationships. Study 1 presents new measures of the habitual use of reappraisal and suppression. Study 2 examines convergent and discriminant validity. Study 3 shows that reappraisers experience and express greater positive emotion and lesser negative emotion, whereas suppressors experience and express lesser positive emotion, yet experience greater negative emotion. Study 4 indicates that using reappraisal is associated with better interpersonal functioning, whereas using suppression is associated with worse interpersonal functioning. Study 5 shows that using reappraisal is related positively to well-being, whereas using suppression is related negatively.

Addressing Moderated Mediation Hypotheses: Theory, Methods, and Prescriptions.

Abstract: This article provides researchers with a guide to properly construe and conduct analyses of conditional indirect effects, commonly known as moderated mediation effects. We disentangle conflicting definitions of moderated mediation and describe approaches for estimating and testing a variety of hypotheses involving conditional indirect effects. We introduce standard errors for hypothesis testing and construction of confidence intervals in large samples but advocate that researchers use bootstrapping whenever possible. We also describe methods for probing significant conditional indirect effects by employing direct extensions of the simple slopes method and Johnson-Neyman technique for probing significant interactions. Finally, we provide an SPSS macro to facilitate the implementation of the recommended asymptotic and bootstrapping methods. We illustrate the application of these methods with an example drawn from the Michigan Study of Adolescent Life Transitions, showing that the indirect effect of intrinsic student interest on mathematics performance through teacher perceptions of talent is moderated by student math self-concept.