Effects of electronic personal health information technology on American women's cancer screening behaviors mediated through cancer worry: Differences and similarities between 2017 and 2020.

Backgrounds: Thanks to their accessibility and low cost, electronic personal health information (ePHI) technologies have been widely used to facilitate patient-physician communication and promote health prevention behaviors (e.g. cancer screening). Despite that empirical evidence has supported the association between ePHI technology use and cancer screening behaviors, the underlying mechanism through which ePHI technology use influences cancer screening behaviors remains a topic of discussion. Objective: This study investigates the relationship between ePHI technology uses and cancer screening behaviors of American women and examines the mediating role of cancer worry. Methods: Data for this study were from the Health Information National Trends Survey (HINTS) collected in 2017 (HINTS 5 Cycle 1) and 2020 (HINTS 5 Cycle 4). The final sample included 1914 female respondents in HINTS 5 Cycle 1 and 2204 in HINTS 5 Cycle 4. Mann-Whitney U test, two-sample t-test, and mediation analysis were performed. We also referred to the regression coefficients generated by min-max normalization as percentage coefficients (bp) for the comparison. Results: This study reports increased usage of ePHI technologies (from 1.41 in 2017 to 2.19 to 2020), increased cancer worry (from 2.60 in 2017 to 2.84 in 2020), and a stable level of cancer screening behaviors (from 1.44 in 2017 to 1.34 in 2020) among American women. Cancer worry was found to mediate the ePHI effect on cancer screening behaviors (bp = 0.005, 95% confidence interval [0.001, 0.010]) in a positive complementary mediation in 2020. Conclusions: The research findings support a positive association between ePHI technology use and cancer screening behaviors, and cancer worry has been identified as a salient mediator. An understanding of the mechanism that prompts US women's cancer screening practices provides practical implications for health campaign practitioners.

Effects of rhetorical devices on audience responses with online videos: An augmented elaboration likelihood model.

The way in which information is linguistically presented can impact audience attention, emotion, and cognitive responses, even if the content remains unchanged. The present study aims to examine the effects of rhetorical devices on audience responses by introducing a new theoretical framework, the augmented elaboration likelihood model (A-ELM), which integrates elements of the Elaboration Likelihood Model and narrative theory. The results show that the mediation effects of attention on the relationships between rhetorical devices and affective and cognitive elaborations are moderated by involvement. Nonnarrative evidence, combined narrative and numerical evidence, source credibility, and tropes versus the lack of figures of speech, elicit better audience responses in low-involvement situations, whereas numerical evidence outperforms narratives in high-involvement situations. This study not only offers a novel theoretical framework in the form of A-ELM, but also has important implications for advancing methodologies and practical applications.

Interrater reliability estimators tested against true interrater reliabilities.

BACKGROUND: Interrater reliability, aka intercoder reliability, is defined as true agreement between raters, aka coders, without chance agreement. It is used across many disciplines including medical and health research to measure the quality of ratings, coding, diagnoses, or other observations and judgements. While numerous indices of interrater reliability are available, experts disagree on which ones are legitimate or more appropriate. Almost all agree that percent agreement (ao), the oldest and the simplest index, is also the most flawed because it fails to estimate and remove chance agreement, which is produced by raters' random rating. The experts, however, disagree on which chance estimators are legitimate or better. The experts also disagree on which of the three factors, rating category, distribution skew, or task difficulty, an index should rely on to estimate chance agreement, or which factors the known indices in fact rely on. The most popular chance-adjusted indices, according to a functionalist view of mathematical statistics, assume that all raters conduct intentional and maximum random rating while typical raters conduct involuntary and reluctant random rating. The mismatches between the assumed and the actual rater behaviors cause the indices to rely on mistaken factors to estimate chance agreement, leading to the numerous paradoxes, abnormalities, and other misbehaviors of the indices identified by prior studies. METHODS: We conducted a 4 × 8 × 3 between-subject controlled experiment with 4 subjects per cell. Each subject was a rating session with 100 pairs of rating by two raters, totaling 384 rating sessions as the experimental subjects. The experiment tested seven best-known indices of interrater reliability against the observed reliabilities and chance agreements. Impacts of the three factors, i.e., rating category, distribution skew, and task difficulty, on the indices were tested. RESULTS: The most criticized index, percent agreement (ao), showed as the most accurate predictor of reliability, reporting directional r2 = .84. It was also the third best approximator, overestimating observed reliability by 13 percentage points on average. The three most acclaimed and most popular indices, Scott's π, Cohen's κ and Krippendorff's α, underperformed all other indices, reporting directional r2 = .312 and underestimated reliability by 31.4 ~ 31.8 points. The newest index, Gwet's AC1, emerged as the second-best predictor and the most accurate approximator. Bennett et al's S ranked behind AC1, and Perreault and Leigh's Ir ranked the fourth both for prediction and approximation. The reliance on category and skew and failure to rely on difficulty explain why the six chance-adjusted indices often underperformed ao, which they were created to outperform. The evidence corroborated the notion that the chance-adjusted indices assume intentional and maximum random rating while the raters instead exhibited involuntary and reluctant random rating. CONCLUSION: The authors call for more empirical studies and especially more controlled experiments to falsify or qualify this study. If the main findings are replicated and the underlying theories supported, new thinking and new indices may be needed. Index designers may need to refrain from assuming intentional and maximum random rating, and instead assume involuntary and reluctant random rating. Accordingly, the new indices may need to rely on task difficulty, rather than distribution skew or rating category, to estimate chance agreement.

Antecedents and Consequences of Smoking Cessation Intention in the Context of the Global COVID-19 Infodemic.

A growing body of scientific studies has been published to inform responses to the ongoing coronavirus pandemic, and some have claimed that cigarette smoking has a beneficial or mixed effect on the prevention and treatment of COVID-19. The presentation of such findings, unfortunately, has created an infodemic. This study integrated the theory of planned behavior and the health belief model and incorporated findings on addiction from the medical literature to predict cessation intention and support for tobacco control measures in the context of the COVID-19 infodemic. The study found that cessation intention partially mediated the effect of perceived severity and fully mediated the effects of perceived benefits, self-efficacy, and addiction on support for control measures. In addition, a positively-valenced message of the effect of smoking on the prevention and treatment of COVID-19 vs. a mixedly-valenced message was significant in predicting cessation intention, and the positively-valenced message of smoking indirectly predicted support for tobacco control measures. Perceived susceptibility, barriers, and subjective norms, however, exerted neither direct nor indirect effects on the two outcome variables.

A Model-Based Meta-Analysis of Willingness to Participate in Cancer Screening.

Although early screening tests are beneficial for the detection and treatment of cancers, many people have failed to participate in screening tests. The present study aims to explore the theoretical underpinning of low participation in screening programs using the method of meta-analytic structural equation modeling. It was found that the health belief model is the most adopted theoretical framework. Moreover, the intended uptake of screening was positively predicted only by cues to action, health literacy, and perceived susceptibility. As a result, a health intention model, including the three significant variables, is proposed. The practical implications of the findings are that health communication campaigns should focus on enlightening and engaging the public through all necessary means to raise awareness and transfer knowledge in relation to screening procedures as well as cancers per se.