‘Show me the money and the party!’ – variation in Facebook and Twitter adoption by politicians

Our study explores the adoption of Facebook and Twitter by candidates in the 2013 German Federal elections. Utilizing data from the German Longitudinal Election Study candidate survey fused with data gathered on the Twitter and Facebook use of candidates, we draw a clear distinction between Facebook and Twitter. We show that adoption of both channels is primarily driven by two factors: party and money. But the impact of each plays out differently for Facebook and Twitter. While the influence of money is homogenous for Facebook and Twitter with the more resources candidates have, the more likely they are to adopt, the effect is stronger for Facebook. Conversely, a party’s impact on adoption is heterogeneous across channels, a pattern we suggest is driven by the different audiences Facebook and Twitter attract. We also find candidates’ personality traits only correlate with Twitter adoption, but their impact is minimal. Our findings demonstrate that social media adoption by politicians is far from homogenous, and that there is a need to differentiate social media channels from one another when exploring motivations for their use.     

Technological forecasting as a guide for managerial planning

The author discusses the limitations of statistical forecasting as a guide to managerial planning, with specific reference to technological and market changes in the glass industry. He advocates the use of a Forecast Adjustment Matrix as a framework for identifying marketing and technological factors which might produce significant deviations from established trends. Finally, he suggests that the analysis and adjustment of technological and market trends should be made periodically. The whole technological forecasting operation should be formalized and it should be made the specific responsibility of one organizational unit within the company.     

An evaluation of collaborative interventions to improve chronic illness care. Framework and study design

The author's dual-purpose evaluation assesses the effectiveness of formal collaboratives in stimulating organizational changes to improve chronic illness care (the chronic care model or CCM). Intervention and comparison sites are compared before and after introduction of the CCM. Multiple data sources are used to measure the degree of implementation, patient-level processes and outcomes, and organizational and team factors associated with success. Despite challenges in timely recruitment of sites and patients, data collection on 37 participating organizations, 22 control sites, and more than 4,000 patients with diabetes, congestive heart failure, asthma, or depression is nearing completion. When analyzed, these data will shed new light on the effectiveness of collaborative improvement methods and the CCM.     

Comparisons of Test Statistics Arising from Marginal Analyses of Multivariate Survival Data

We investigate the properties of several statistical tests for comparing treatment groups with respect to multivariate survival data, based on the marginal analysis approach introduced by Wei, Lin and Weissfeld [Regression Analysis of multivariate incomplete failure time data by modelling marginal distributians, JASA vol. 84 pp. 1065–1073]. We consider two types of directional tests, based on a constrained maximization and on linear combinations of the unconstrained maximizer of the working likelihood function, and the omnibus test arising from the same working likelihood. The directional tests are members of a larger class of tests, from which an asymptotically optimal test can be found. We compare the asymptotic powers of the tests under general contiguous alternatives for a variety of settings, and also consider the choice of the number of survival times to include in the multivariate outcome. We illustrate the results with simulations and with the results from a clinical trial examining recurring opportunistic infections in persons with HIV.     

Comparative Potency Method for Cancer Risk Assessment: Application to Diesel Particulate Emissions1

An estimation of the human lung cancer “unit risk” from diesel engine particulate emissions has been made using a comparative potency approach. This approach involves evaluating the tumorigenic and mutagenic potencies of the particulates from four diesel and one gasoline engine in relation to other combustion and pyrolysis products (coke oven, roofing tar, and cigarette smoke) that cause lung cancer in humans. The unit cancer risk is predicated on the linear nonthreshold extrapolation model and is the individual lifetime excess lung cancer risk from continuous exposure to 1 μg carcinogen per m³ inhaled air. The human lung cancer unit risks obtained from the epidemiologic data for coke oven workers, roofing tar applicators, and cigarette smokers were, respectively, 9.3 × 10^?4, 3.6 × 10^?4, and 2.2 × 10^?6 per μg particulate organics per m³ air. The comparative potencies of these three materials and the diesel and gasoline engine exhaust particulates (as organic extracts) were evaluated by in vivo tumorigenicity bioassays involving skin initiation and skin carcinogenicity in SENCAR mice and by the in vitro bioassays that proved suitable for this analysis: Ames Salmonella microsome bioassay, L5178Y mouse lymphoma cell mutagenesis bioassay, and sister chromatid exchange bioassay in Chinese hamster ovary cells. The relative potencies of the coke oven, roofing tar, and cigarette smoke emissions, as determined by the mouse skin initiation assay, were within a factor of 2 of those determined using the epidemiologic data. The relative potencies, from the in vitro bioassays as compared to the human data, were similar for coke oven and roofing tar, but for the cigarette smoke condensate the in vitro tests predicted a higher relative potency. The mouse skin initiation bioassay was used to determine the unit lung cancer risk for the most potent of the diesel emissions. Based on comparisons with coke oven, roofing tar, and cigarette smoke, the unit cancer risk averaged 4.4 × 10^?4. The unit lung cancer risks for the other, less potent motor-vehicle emissions were determined from their comparative potencies relative to the most potent diesel using three in vitro bioassays. There was a high correlation between the in vitro and in vivo bioassays in their responses to the engine exhaust particulate extracts. The unit lung cancer risk per μg particulates per m³ for the automotive diesel and gasoline exhaust particulates ranged from 0.20 × 10^?4 to 0.60 × 10^?4; that for the heavy-duty diesel engine was 0.02 × 10^?4. These unit risks provide the basis for a future assessment of human lung cancer risks when combined with human population exposure to automotive emissions.     

"Languaging" factors affecting clients' acceptance of forgiveness intervention in marital therapy

Forgiveness is a significant intervention for healing interpersonal injury. Yet therapists do not often use forgiveness intervention. Employing a semantic perspective and a survey design (n = 307), this study investigated whether the language used to rationalize forgiveness intervention (set at five levels: personal growth, relationship reconciliation, spiritual issue, others' growth, and pardoning/condoning) may affect its acceptability. Gender, problem type, and choice were also included in the analyses. Overall, forgiveness was found to be an acceptable intervention. A pardoning/condoning rationale led to significantly lower acceptability ratings. Other results are discussed. We conclude that therapists should be less apprehensive about using forgiveness, but need to inform themselves better concerning its purpose, process, and articulation.     

Why mentoring in the workplace works

Workplaces are ideal contexts for mentoring relationships between adults and older youth. To teach the competencies required in contemporary workplaces (many of which are equally useful in other settings), mentors need to use sophisticated teaching behaviors, which the authors characterize as reflective questioning and problem solving.