Principal components analysis to identify influences on research communication and engagement during an environmental disaster

Predicting Churn in Online Games by Quantifying Diversity of Engagement

Understanding engagement patterns of users in online platforms, may it be games, online social networks, or academic websites, is a widely studied topic with many real-world applications and economic consequences. A holy grail in this area of research is to develop an automatic prediction algorithm for when a user is going to leave the platform and devise proper intervention. In this work, we study online recreational games and propose to model the engagement patterns of players through an unsupervised learning framework. We think of engagement as a continuous temporal process, measured along specific axes derived from gaming users' data using principal component analysis. We track the overall trend of the projection of the data along the significant principal components. We find that the geometric variability of the trajectory is a good predictor of the users' engagement level. Users characterized by a time series with large variability are users with higher engagement; namely, they will continue playing the game for prolonged periods of time. We evaluated our methodology on two data sets of very different game types and compared the performance of our method with state-of-the-art black-box machine learning algorithms. Our results were fairly competitive with these methods, and we conclude that churn can be predicted using an explainable, intuitive, and white-box decision-rule algorithm.

Validity and reliability study of clinician attitude towards rural health extension program in Ethiopia: exploratory and confirmatory factor analysis

BACKGROUND

The Ethiopian health extension program (HEP) is an innovative community-based strategy aimed at disease prevention and health promotion. While health extension workers (HEWs) are its front-line workers, the involvement of clinicians remains an integral part. The goals of this study were to: (1) assess the correlation of clinician attitude with predictors and (2) assess the reliability and validity of the survey instrument.

METHODS

A cross-sectional study design was utilized to collect data from a sample of 1239 clinicians using 28 items of attitude questions. Exploratory factor analysis (EFA) was applied to create the latent variables. Oblique Promax type rotation with factor loading (> 0.5) was used. Cronbach's alpha was used to assess reliability, with a level of > 0.7 suggesting good reliability. Confirmatory factor analysis (CFA) was undertaken, with the values of Root Mean Square Error Administration (RMSEA) < 0.08, Standardized Root Mean Square Residual (SRMR) < 0.05, comparative fit index (CFI) 0.9-0.95, and Tucker-Lewis index (TLI) 0.9-0.95 suggesting acceptable model fit. A linear regression analysis was conducted.

RESULTS

EFA produced two latent variables which explained 93.2% of the total variance. The latent variables were labeled as perceived attitude towards the skill of HEWs (F1), and perceived attitude towards the impact of HEP (F2). Internal reliability for the 28 items was reported with a Cronbach's alpha of 0.94, and for F1 and F2 it was 0.91 and 0.90, respectively. CFA was done and RMSEA was reported at 0.04, SRMR was 0.03, and CFI and TLI were each 0.97. The value of clinician attitude increased by 3.5, 95% CI (1.5, 5.3), P-value < 0.001 for those who have been exposed to the HEP program than non-exposed. Similarly, clinician attitude was lower for degree holders compared to those with diplomas by - 2.7, 95% CI (- 4.4, - 0.94), P-value < 0.002.

CONCLUSION

Clinician attitude increased as exposure to HEP increased. Clinician attitude towards HEP has two latent variables. Furthermore, the assessment tool demonstrated good reliability and validity. In conclusion, it is worthy valued for clinicians to receive orientation about HEP, and researchers and program evaluators can use this assessment tool.

A Comparison of Environmental Concerns in Two Disparate Montana and Nevada Communities

Asbestos refers to six fibrous minerals that occur naturally in the environment in the United States and throughout the world. Deposits may be found in soil, rocks, and deposits of other minerals such as vermiculite and talc. These naturally occurring asbestos (NOA) minerals belong to the serpentine and amphibole family of minerals. This chapter reports shared components of community-driven environmental concerns related to exposure to NOA in a rural Montana and a suburban Nevada community. The specific aim is to establish an understanding of the community and community member's primary concern(s) related to NOA in both communities. The knowledge that NOA is commonly found in areas across the United States supports the need for additional research into the health effects of environmental exposure and best-practices to reduce exposure risk while allowing communities to thrive economically.