The Positive Thinking Skills Scale: A Screening Measure for Early Identification of Depressive Thoughts

Background Depression is currently considered the second leading cause of disability worldwide. Positive thinking is a cognitive process that helps individuals to deal with problems more effectively, and has been suggested as a useful strategy for coping with adversity, including depression. The Positive Thinking Skills Scale (PTSS) is a reliable and valid measure that captures the frequency of use of positive thinking skills that can help in the early identification of the possibility of developing depressive thoughts. However, no meaningful cutoff score has been established for the PTSS. Aim To establish a cutoff score for the PTSS for early identification of risk for depression. Methods This study used a receiver operating characteristic (ROC) curve to establish a PTSS cutoff score for risk for depression, using the Center for Epidemiological Studies–Depression Scale (CES-D) as the gold standard measure. Results In a sample of 109 caregivers, the ROC showed that the cutoff score of PTSS that best classify the participants is 13.5. With this PTSS score, 77.8% of the subjects with low CES-D are classify correctly, and 69.6% of the subjects with high CES-D are classify correctly. Since the PTSS score should be integer numbers, functionally the cutoff would be 13. Conclusion The study showed that a cut off score of 13 is a point at which referral, intervention, or treatment would be recommended. Consequently, this can help in the early identification of depressive symptoms that might develop because of the stress of caregiving

Predeath Grief, Resourcefulness, and Perceived Stress Among Caregivers of Partners With Young-Onset Dementia

More than 200,000 Americans are currently diagnosed with young-onset dementia (YOD). YOD is dementia diagnosed prior to the age of 65. Most persons of YOD are cared for by their partners. Using the theoretical framework of Resilience Theory, this cross-sectional, correlational study examined the moderating effects of personal and social resourcefulness on the relationship between predeath grief and perceived stress among 104 YOD caregiving partners (life partners/spouses) using an online survey platform. Results indicated a large positive correlation between predeath grief and caregiver perceived stress (r = .65; p \u3c .001). Together predeath grief, personal resourcefulness and social resourcefulness explained 51.5% of the variance in perceived stress. Personal resourcefulness did not moderate the relationship. Social resourcefulness did positively moderate this relationship between predeath grief and perceived stress. These findings allow for a better understanding of the caregiving experience for a partner with YOD and creates opportunities for future research studies

Factor Structure and Psychometric Properties of Cognitive-Behavioral Scales in Caregivers of Persons with Dementia

Background/Purpose Caregiving can be costly to dementia caregivers\u27 well-being. Assessing the factor structure and psychometric properties of Cognitive-Behavioral Scales in dementia caregivers is an essential step in addressing the gap in the current state of research. Specifically, it is essential to determine first whether the factorial structure of the three measures used in this study namely, the Positive Thinking Skills Scale, the Revised Memory and Behavior Problems Checklist, and the Zarit Burden Interview are good representation of the data by studying the good model fit. Next, evaluating the reliability of each factor of the three measures used are essential to learn about the precision of the factors. Lastly, it is vital to study the factor correlation and its relevance to the theory used to determine the validity of the factors. Methods A descriptive, correlational, cross-sectional design in a convenience sample of 100 caregivers. Results Results indicated that the factorial structure of the three scales is a good representation of the data; an acceptable reliability of each factor of the three measures; and the factors correlated as expected and showed their relevance to the underlying theory. Conclusions Future studies might consider studying the mediating/moderating effects of positive thinking on care-recipients challenging behavior problems. The findings can be used as a guide to provide a positive thinking training intervention among caregivers

Effects of Positive Thinking on Dementia Caregivers’ Burden and Care-Recipients’ Behavioral Problems

Most dementia care is provided at home by family members. This caregiving places an additional burden on the family members, which can negatively impact their physical and psychological well-being. The caregivers’ burden can also contribute to behavioral problems in the care-recipients. The purpose of this study was to examine the mediating/moderating effects of positive thinking (PT) on the relationship between caregivers’ burden (embarrassment/anger, patient’s dependency, and self-criticism) and their care-recipients’ behavioral problems (memory, depression, and disruption) in a sample of 100 dementia caregivers. Results indicated that caregivers’ embarrassment, self-criticism, and perception of patient dependency predicts depression in care-recipients, and these relationships are moderated by PT. Results also indicated that as PT increases, the relationship between embarrassment and disruption goes down as well as does the relationship between self-criticism and depression. The study provided direction for the development of a PT training intervention to help caregivers to combat their burden

The impact of social and temporal job demands and resources on emotional exhaustion and turnover intention among flight attendants

Based on a survey among flight attendants from a DACH-country-based airline, this study examines the effects and relative importance of social and temporal determinants of emotional exhaustion and turnover intention. Results suggest that scheduling satisfaction is the most influential predictor of both emotional exhaustion and turnover intention, followed by time pressure and surface acting for emotional Exhaustion and surface acting and organizational support for turnover intention. From a practical standpoint, these results thus suggest that the most important predictors of emotional exhaustion and turnover intention can be shaped and influenced quite well by management

Handling missing data in structural equation models in R. A replication study for applied researchers

Introduction. Multiple imputation (MI) is one of the most highly recommended methods for replacing missing values in research data. The scope of this paper is to demonstrate missing data handling in SEM by analyzing two modified data examples from educational psychology, and to give practical recommendations for applied researchers.Method. We provide two examples (N = 589 and N = 621, respectively) based on previous studies of students’ self-concepts, mastery goals and performance avoidance goals, and a 7- step tutorial. Then, we produced 20% and 40% missing data under three missing mechanisms by these complete, genuine data sets. The resulting datasets were then analyzed by (1) listwise deletion and structural equation models (SEM), (2) full information maximum likelihood (FIML) with SEM, and (3) MI combined with SEM and pooling. Thus, the results stem from 2 × 3 × 3 conditions.Results. Previous research was replicated by illustrating a practical way to combine MI with SEM and pooling. The assumed factor structure was depicted in both examples with multiply imputed values applied.Discussion. We suggest adding variables to clarify the missing data mechanism, especially for dependent variables as motivation. Such variables might indicate whether missing values in dependent variables are correlated with independent variables (e.g., interest) or the dependent variable itself (e.g. lack of motivation independently of interest). </jats:p

Improving Multiple-Group confirmatory factor analysis in R – A tutorial in measurement invariance with continuous and ordinal indicators

Multiple-group confirmatory factor analysis (MG-CFA) is among the most productive extensions of.structural equation modeling. Many researchers conducting cross-cultural or longitudinal studies are interested in testing for measurement and structural invariance. The aim of the present paper is to provide a tutorial in MG-CFA using the freely available R-packages lavaan, semTools, and semPlot. The combination of these packages enable a highly efficient analysis of the measurement models both for normally distributed as well as ordinal data. Data from two freely available datasets – the first with continuous the second with ordered indicators - will be used to provide a walk-through the individual steps. Accessed 20,554 times on https://pareonline.net from July 09, 2014 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

A Computational Model of Trust Based on Dynamic Interaction in the Stack Overflow Community

A member’s reputation in an online community is a quantified representation of their trustworthiness within the community. Reputation is calculated using rules-based algorithms which are primarily tied to the upvotes or downvotes a member receives on posts. The main drawback of this form of reputation calculation is the inability to consider dynamic factors such as a member’s activity (or inactivity) within the community. The research involves the construction of dynamic mathematical models to calculate reputation and then determine to what extent these results compare with rules-based models. This research begins with exploratory research of the existing corpus of knowledge. Constructive research in the building of mathematical dynamic models and then empirical research to determine the effectiveness of the models. Data collected from the Stack Overflow (SO) database is used by models to calculate a rule-based and dynamic member reputation and then using statistical correlation testing methods (i.e., Pearson and Spearman) to determine the extent of the relationship. Statistically significant results with moderate relationship size were found from correlation testing between rules-based and dynamic temporal models. The significance of the research and its conclusion that dynamic and temporal models can indeed produce results comparative to that of subjective vote-based systems is important in the context of building trust in online communities. Developing models to determine reputation in online communities based upon member post and comment activity avoids the potential drawbacks associated with vote-based reputation systems