Cognitive and behavioral predictors of light therapy use

Objective: Although light therapy is effective in the treatment of seasonal affective disorder (SAD) and other mood disorders, only 53-79% of individuals with SAD meet remission criteria after light therapy. Perhaps more importantly, only 12-41% of individuals with SAD continue to use the treatment even after a previous winter of successful treatment. Method: Participants completed surveys regarding (1) social, cognitive, and behavioral variables used to evaluate treatment adherence for other health-related issues, expectations and credibility of light therapy, (2) a depression symptoms scale, and (3) self-reported light therapy use. Results: Individuals age 18 or older responded (n = 40), all reporting having been diagnosed with a mood disorder for which light therapy is indicated. Social support and self-efficacy scores were predictive of light therapy use (p's<.05). Conclusion: The findings suggest that testing social support and self-efficacy in a diagnosed patient population may identify factors related to the decision to use light therapy. Treatments that impact social support and self-efficacy may improve treatment response to light therapy in SAD. © 2012 Roecklein et al

Decisional and emotional forgiveness scales: Psychometric validity and correlates with personality and vengeance.

Forgiveness is an internal process to overcome negative aspects (e.g., anger, bitterness, resentment) towards an offender, being associated to a range of variables (e.g., well-being, quality of loving relationships, resilience). Forgiveness can happen through two different types: (1) decisional, which is a behavioural modification to reduce direct hostility; and (2) emotional, which is a transformation of negative emotions into positive. The current research aimed to gather psychometric evidences for the Decisional Forgiveness Scale (DFS) and the Emotional Forgiveness Scale (EFS), using a Brazilian sample. Two studies were conducted. In Study 1 (n = 181), the bifactorial structures were replicated, also providing satisfactory reliability levels. Through Item Response Theory, results indicated good discrimination, difficulty levels, and considerable information to all the items from both measures. In Study 2 (n = 220), confirmatory factor analyses confirmed their structure, presenting good model fit. The measures were also invariant regarding participants’ gender. Finally, the measures presented significant results when correlated to personality and vengeance. In sum, the instruments demonstrated satisfactory psychometric properties, evidencing the possibility of their use in the respective context.The authors acknowledge financial support from the CAPES Foundation (Brazil, http://www.capes.gov.br/) for the Ph.D. scholarship to the second author. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

A Spoonful of Math Helps the Medicine Go Down: An Illustration of How Healthcare can Benefit from Mathematical Modeling and Analysis

<p>Abstract</p> <p>Objectives</p> <p>A recent joint report from the Institute of Medicine and the National Academy of Engineering, highlights the benefits of--indeed, the need for--mathematical analysis of healthcare delivery. Tools for such analysis have been developed over decades by researchers in Operations Research (OR). An OR perspective typically frames a complex problem in terms of its essential mathematical structure. This article illustrates the use and value of the tools of operations research in healthcare. It reviews one OR tool, queueing theory, and provides an illustration involving a hypothetical drug treatment facility.</p> <p>Method</p> <p>Queueing Theory (QT) is the study of waiting lines. The theory is useful in that it provides solutions to problems of waiting and its relationship to key characteristics of healthcare systems. More generally, it illustrates the strengths of modeling in healthcare and service delivery.</p> <p>Queueing theory offers insights that initially may be hidden. For example, a queueing model allows one to incorporate randomness, which is inherent in the actual system, into the mathematical analysis. As a result of this randomness, these systems often perform much worse than one might have guessed based on deterministic conditions. Poor performance is reflected in longer lines, longer waits, and lower levels of server utilization.</p> <p>As an illustration, we specify a queueing model of a representative drug treatment facility. The analysis of this model provides mathematical expressions for some of the key performance measures, such as average waiting time for admission.</p> <p>Results</p> <p>We calculate average occupancy in the facility and its relationship to system characteristics. For example, when the facility has 28 beds, the average wait for admission is 4 days. We also explore the relationship between arrival rate at the facility, the capacity of the facility, and waiting times.</p> <p>Conclusions</p> <p>One key aspect of the healthcare system is its complexity, and policy makers want to design and reform the system in a way that affects competing goals. OR methodologies, particularly queueing theory, can be very useful in gaining deeper understanding of this complexity and exploring the potential effects of proposed changes on the system without making any actual changes.</p

Faith and Fair Trade: The Moderating Role of Contextual Religious Salience

Normative and historical arguments support the idea that religion potentially shapes decisions to support fair trade products. That said, the question of how religion influences organizational decision-makers to purchase fair trade products in a business-to-business context has remained largely unaddressed. This research examines the interactive effect of individual religious commitment and contextual religious salience on an individual's willingness to pay a price premium for a fair trade product, when buying on behalf of an organization. Findings from two experimental studies (involving 75 and 87 working individuals, respectively) reveal that the effect of a decision-maker's religious commitment on his or her willingness to pay a price premium, for the purchase of a fair trade product on behalf of an organization, is moderated by the contextual salience of religion. Specifically, when religion is highly salient in the organizational context, religious commitment is positively related to the decision-maker's willingness to pay a premium for the fair trade product; when contextual religious salience is low, religious commitment and willingness to pay a premium are unrelated. Implications for theory and practice are presented. © 2013 Springer Science+Business Media Dordrecht

A common biological basis of obesity and nicotine addiction

J. Kaprio ja J. Tuomilehto työryhmien jäseniä (yht. 281).Peer reviewe