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The purpose was to analyze a large-scale database, a national sample of 1,108 heads of households collected by AT&T, to show that behavioral frequencies of the activities of consumer diary panelists may regress toward the population mean during the diary-keeping period given social desirability bias produced by the conditioning effect of keeping diaries. This effect is distinguished from regression toward the mean, a statistical phenomenon reflecting happenstance of extreme initial values. Social desirability bias is demonstrated in two ways--by observing decreasing coefficients of variation over time and by detecting a greater proportion of panelists' behavioral frequencies moving toward the population mean than moving away from it. Both cannot be explained by regression toward the mean. Social desirability bias was manifest only during the early stages of the diary-keeping period and only for activities high in involvement. The presence of social desirability bias in diary panels implies that, when people are subjected to observation, diary observations may be contaminated, leading to the mistaken impression that the population is more homogeneous than it actually is. Thus it is important for researchers to monitor the diary panel carefully to detect social desirability bias when engaged in longitudinal studies.

This paper analyses the impact of questionnaire design and length of participation on item non-response and panel attrition. Based upon the results of previous studies, the authors propose a framework [...]

Using a large real-life corporate database initially consisting of 3,990 heads of households stratified on the basis of various demographic and geographic variables, and whose communication activities (long distance telephone calls, letters, cards, and visits) were surveyed and monitored, this study investigated the direction as well as magnitude of estimation errors in survey responses and diary entries. Supporting the 1994 Fiedler and Armbruster psychometric formulation and conjecture, we show that estimation errors in reports of the frequency and duration of people's own communication activities exhibit a consistent tendency to regress toward the mean. This regressive estimation is greater for those who are further away from the mean in actual behavior and is proportional to the actual deviation from the mean. Furthermore, this regressive estimation is inversely related to the average frequency across behavioral categories. An important implication of our findings is that the distribution of estimated behavioral frequencies and durations appear more concentrated in surveys than they actually are in the general population, although the general shape of the distribution is unaffected.

The atrium is one of the most preferred design features in modern large buildings, but the thermal performance of an atrium space is a growing concern. Computational fluid dynamics (CFD) and field measurements have usually been employed to assess the complex thermal performance in an atrium. However, these conventional approaches require significant effort. This paper presents a simplified approach employing the thermal response factor method for prediction of temperature distribution in a mechanically ventilated atrium. Full scale measurements were performed in an existing atrium building over a summer period and were used for validation of a CFD simulation. As a result, the thermal response factors obtained by the simplified numerical method were applied to predict the thermal behaviours in the mechanically ventilated atrium. Moreover, airflow patterns were identified by Archimedes Number. [ABSTRACT FROM AUTHOR]

BackgroundThe National Comprehensive Cancer Network Breast Cancer Guidelines Committee suggests that the omission of adjuvant radiation therapy (RT) after breast-conserving surgery can be a reasonable option among older women with low-risk breast cancer (early-stage, estrogen receptor-positive, and node-negative) if they are treated with endocrine therapy. However, RT usage in this group of women still exceeds 50%. Conversely, older women tend to forego RT (even when necessary) due to cost, inconvenience, and potential adverse responses associated with RT. Understanding health-related quality of life (HRQOL) change with receipt of RT among older women in the modern era is limited due to the under-representation of this population in clinical trials. ObjectiveThe proposed study aims to examine the associations of RT with HRQOL trajectories as well as survival outcomes among older women with 5-10 years of follow-up. We will also assess whether prediagnosis comorbidity burden influences receipt of RT and whether the associations between RT and HRQOL trajectory and survival outcomes are modified by the comorbidity burden. MethodsWe will use a retrospective cohort study design with the population-based Surveillance, Epidemiology, and End-Results database linked to the Medicare Health Outcomes Survey (SEER-MHOS). Older women (≥65 years) who were diagnosed with low-risk breast cancer in 1998-2014, received breast-conserving surgery, and participated in MHOS 1998-2016 are eligible for this analysis. The latent class analysis clustering method will be used to identify each patient’s prediagnosis comorbidity burden, and HRQOL will be evaluated using the Short Form 36/Veterans RAND 12-Item Health Survey scales. The inverse-weighted estimates of the probability of treatment will be included to control for treatment selection bias and confounding effects in subsequent analysis. The association of RT with HRQOL trajectory will be evaluated using inverse-weighted multilevel growth mixture models. The inverse-weighted Cox regression model will be used to obtain hazard ratios with 95% CIs for the association of RT with survival outcomes. Differential effects of RT on both outcomes according to comorbidity burden class will also be evaluated. ResultsAs of October 2020, the study was approved by the institutional review board, and SEER-MHOS data were obtained from the National Cancer Institute. Women with low-risk breast cancer who met inclusion and exclusion criteria have been identified, and prediagnosis comorbidity burden class has been characterized using latent class analysis. Further data analysis will begin in November 2020, and the first manuscript will be submitted in a peer-reviewed journal in February 2021. ConclusionsThis research can potentially improve clinical outcomes of older women with low-risk breast cancer by providing them additional information on the HRQOL trajectories when they make RT treatment decisions. It will facilitate informed, shared treatment decision making and cancer care planning to ultimately improve the HRQOL of older women with breast cancer. International Registered Report Identifier (IRRID)DERR1-10.2196/18056