Invisible social control as predictor of daily negative affect and smoking after a self-set quit date

The dual-effects model of social control proposes that social control leads to increased psychological distress but also to better health practices. However, findings are inconsistent, and recent research suggests that the most effective control is unnoticed by the receiver (i. e., invisible). Yet, investigations of the influence of invisible control on daily negative affect and smoking have been limited. Using daily diaries, we investigated how invisible social control was associated with negative affect and smoking. Overall, 100 smokers (72.0 % men, age M = 40.48, SD = 9.82) and their nonsmoking partners completed electronic diaries from a self-set quit date for 22 consecutive days, reporting received and provided social control, negative affect, and daily smoking. We found in multilevel analyses of the within-person process that on days with higher-than-average invisible control, smokers reported more negative affect and fewer cigarettes smoked. Findings are in line with the assumptions of the dual-effects model of social control: Invisible social control increased daily negative affect and simultaneously reduced smoking at the within-person level.

Daily negative affect and smoking after a self-set quit attempt: The role of dyadic invisible social support in a daily diary study

Objectives Social support receipt from one's partner is assumed to be beneficial for successful smoking cessation. However, support receipt can have costs. Recent research suggests that the most effective support is unnoticed by the receiver (i.e., invisible). Therefore, this study examined the association between everyday levels of dyadic invisible emotional and instrumental support, daily negative affect, and daily smoking after a self-set quit attempt in smoker–non-smoker couples. Methods Overall, 100 smokers (72.0% men, mean age M = 40.48, SD = 9.82) and their non-smoking partners completed electronic diaries from a self-set quit date on for 22 consecutive days, reporting daily invisible emotional and instrumental social support, daily negative affect, and daily smoking. Results Same-day multilevel analyses showed that at the between-person level, higher individual mean levels of invisible emotional and instrumental support were associated with less daily negative affect. In contrast to our assumption, more receipt of invisible emotional and instrumental support was related to more daily cigarettes smoked. Conclusions The findings are in line with previous results, indicating invisible support to have beneficial relations with affect. However, results emphasize the need for further prospective daily diary approaches for understanding the dynamics of invisible support on smoking cessation.

Examining invisible social control as predictor of daily smoking and negative affect after a self-set quit date

Objectives: The dual-effects model of social control proposes that social control leads to better health practices, but also arouses psychological distress. However, findings are inconsistent in relation to health behavior and psychological distress. Recent research suggests that the most effective control is unnoticed by the receiver (i.e., invisible). There is some evidence that invisible social control is beneficial for positive and negative affective reactions. Yet, investigations of the influence of invisible social control on daily smoking and distress have been limited. In daily diaries, we investigated how invisible social control is associated with number of cigarettes smoked and negative affect on a daily basis. Methods: Overall, 99 smokers (72.0% men, mean age M = 40.48, SD = 9.82) and their non-smoking partners completed electronic diaries from a self-set quit date for 22 consecutive days within the hour before going to bed, reporting received and provided social control, daily number of cigarettes smoked, and negative affect. Results: Multilevel analyses indicated that between-person levels of invisible social control were associated with lower negative affect, whereas they were unrelated to number of cigarettes smoked. On days with higher-than-average invisible social control, smokers reported less cigarettes smoked and more negative affect. Conclusions: Between-person level findings indicate that invisible social control can be beneficial for negative affect. However, findings on the within-person level are in line with the assumptions of the dual-effects model of social control: Invisible social control reduced daily smoking and simultaneously increased daily negative affect within person.

Measurement of the TeV atmospheric muon charge ratio with the complete OPERA data set

The OPERA detector, designed to search for νμ → ντ oscillations in the CNGS beam, is located in the underground Gran Sasso laboratory, a privileged location to study TeV-scale cosmic rays. For the analysis here presented, the detector was used to measure the atmospheric muon charge ratio in the TeV region. OPERA collected chargeseparated cosmic ray data between 2008 and 2012. More than 3 million atmospheric muon events were detected and reconstructed, among which about 110000 multiple muon bundles. The charge ratio Rμ ≡ Nμ+/Nμ− was measured separately for single and for multiple muon events. The analysis exploited the inversion of the magnet polarity which was performed on purpose during the 2012 Run. The combination of the two data sets with opposite magnet polarities allowedminimizing systematic uncertainties and reaching an accurate determination of the muon charge ratio. Data were fitted to obtain relevant parameters on the composition of primary cosmic rays and the associated kaon production in the forward fragmentation region. In the surface energy range 1–20 TeV investigated by OPERA, Rμ is well described by a parametric model including only pion and kaon contributions to themuon flux, showing no significant contribution of the prompt component. The energy independence supports the validity of Feynman scaling in the fragmentation region up to 200 TeV/nucleon primary energy.

Variance estimation in ranked set sampling using a concomitant variable

We propose a nonparametric variance estimator when ranked set sampling (RSS) and judgment post stratification (JPS) are applied by measuring a concomitant variable. Our proposed estimator is obtained by conditioning on observed concomitant values and using nonparametric kernel regression.