Life satisfaction and positive and negative feelings of workers: a systematic review protocol

Bounded rationality in healthcare: unraveling the psychological factors behind patient satisfaction in China

Introduction

Patient satisfaction is a crucial metric to gauge the quality of medical services, but the psychological factors influencing patient satisfaction remain insufficiently explored.

Methods

This study examines these psychological factors by applying the theory of bounded rationality to 1,442 inpatients in Hangzhou, China, whose data were collected using a questionnaire. One-way ANOVA, correlation analysis, and hierarchical regression were used to analyze patient satisfaction and its associated factors. Additionally, the path analysis of the structural equation model revealed the mechanisms behind the key psychological factors that influenced patient satisfaction.

Results

Medical risk perception, the social cognition of the medical environment, and social desirability bias had significant positive impacts on patient satisfaction. By contrast, negative emotions had a significant negative impact on patient satisfaction. Notably, patients' negative emotions had both a suppressive effect and a positive moderating effect on the relationship between medical risk perception and patient satisfaction. Similarly, social desirability bias had a suppressive effect on the correlation between the social cognition of the medical environment and patient satisfaction, albeit with a negative moderating effect.

Discussion

These results suggest that when evaluating and improving patient satisfaction, accounting only for the factors that directly influence medical service quality is insufficient, as the indirect and moderating effects of patients' negative emotions and the social cognition of the medical environment must also be considered. Medical service providers should thus address patients' negative emotions, establish good doctor-patient relationships, optimize service environments, provide managers with medical risk education and training on negative emotions, and prioritize patient-centered care. Additionally, the government and relevant health departments should optimize medical policies, enhance fairness and accessibility, and create a positive social cognitive environment through public education and awareness campaigns.

Fuzzy Approach to Computational Classification of Burnout—Preliminary Findings

There is a common belief that medical professions generate more work-related stress and earlier job burnout. We tested two groups: study group 1: medical (physical therapists, n = 30), and study group 2: non-medical (informaticians, n = 30). The purpose of this study was to find new, more reliable models for calculating work-related stress and burnout in the two aforementioned different professional groups. In the paper, we focused on a new model of algorithm based on AI methods that extends the interpretability of the scale of results obtained using the MBI test. The outcomes of the Maslach Burnout Inventory (MBI) were analysed in both study groups. These became the starting point for the development of three different fuzzy models, from which, after comparison, the one best suited to the study groups and the way they were evaluated was selected. Among the patients participating in the study, the following results were obtained: MBI values expressed as median values were significantly higher in group 2 than in group 1. The computational analysis showed that the contribution of the different parts of the MBI test to the final score was unequal in both groups. AI allowed for optimal selection of the model parameters for the study group, from which an algorithm was created to optimise the selection of tools or their parameters. A computational tool can do this faster, more accurately, and more efficiently, becoming an important supporting tool. In the medical context, the main benefit of the results presented in this paper is the definition of an evaluation model that transforms the MBI test scores into a universal percentage scale while preserving the properties of the guidelines underlying the MBI. An additional advantage of the proposed solution is the readability and flexibility resulting from the linguistic rules underlying the model.

Methodological quality of case series studies: an introduction to the JBI critical appraisal tool

INTRODUCTION

Systematic reviews provide a rigorous synthesis of the best available evidence regarding a certain question. Where high-quality evidence is lacking, systematic reviewers may choose to rely on case series studies to provide information in relation to their question. However, to date there has been limited guidance on how to incorporate case series studies within systematic reviews assessing the effectiveness of an intervention, particularly with reference to assessing the methodological quality or risk of bias of these studies.

METHODS

An international working group was formed to review the methodological literature regarding case series as a form of evidence for inclusion in systematic reviews. The group then developed a critical appraisal tool based on the epidemiological literature relating to bias within these studies. This was then piloted, reviewed, and approved by JBI's international Scientific Committee.

RESULTS

The JBI critical appraisal tool for case series studies includes 10 questions addressing the internal validity and risk of bias of case series designs, particularly confounding, selection, and information bias, in addition to the importance of clear reporting.

CONCLUSION

In certain situations, case series designs may represent the best available evidence to inform clinical practice. The JBI critical appraisal tool for case series offers systematic reviewers an approved method to assess the methodological quality of these studies.

Development and Validation of a Comprehensive Well-Being Scale for People in the University Environment (Pitt Wellness Scale) Using a Crowdsourcing Approach: Cross-Sectional Study

Background

Well-being has multiple domains, and these domains are unique to the population being examined. Therefore, to precisely assess the well-being of a population, a scale specifically designed for that population is needed.

Objective

The goal of this study was to design and validate a comprehensive well-being scale for people in a university environment, including students, faculty, and staff.

Methods

A crowdsourcing approach was used to determine relevant domains for the comprehensive well-being scale in this population and identify specific questions to include in each domain. A web-based questionnaire (Q1) was used to collect opinions from a group of university students, faculty, and staff about the domains and subdomains of the scale. A draft of a new well-being scale (Q2) was created in response to the information collected via Q1, and a second group of study participants was invited to evaluate the relevance and clarity of each statement. A newly created well-being scale (Q3) was then used by a third group of university students, faculty, and staff. A psychometric analysis was performed on the data collected via Q3 to determine the validity and reliability of the well-being scale.

Results

In the first step, a group of 518 university community members (students, faculty, and staff) indicated the domains and subdomains that they desired to have in a comprehensive well-being scale. In the second step, a second group of 167 students, faculty, and staff evaluated the relevance and clarity of the proposed statements in each domain. In the third step, a third group of 546 students, faculty, and staff provided their responses to the new well-being scale (Pitt Wellness Scale). The psychometric analysis indicated that the reliability of the well-being scale was high.

Conclusions

Using a crowdsourcing approach, we successfully created a comprehensive and highly reliable well-being scale for people in the university environment. Our new Pitt Wellness Scale may be used to measure the well-being of people in the university environment.

Mediating role of coping style on the relationship between job stress and subjective well-being among Korean police officers

Background

Police officers have long been known to have one of the most stressful occupations. This study investigates their stress levels, coping styles, and subjective well-being, including affect and life satisfaction. We also explore the interrelationships of these factors to determine how coping style influences a police officer’s subjective well-being.

Methods

We used a convenience sampling method for 112 police officers in a metropolitan area in South Korea. Data were collected using self-administered questionnaires. The questionnaires consisted of the following scales: job stress, coping style, positive/negative affect, and life satisfaction that measured subjective well-being. Descriptive statistics, a correlation analysis and Hayes’ PROCESS macro, and bootstrap analysis were performed.

Results

The level of job stress for the participants was moderate, with an average of 43.57 out of 100. The mean scores of positive affect was 17.38 out of 40, 8.50 out of 40 for negative affect, and 20.76 out of 35 for life satisfaction. Job stress and coping were significantly correlated with subjective well-being, and problem-solving style mediated stress, positive affect, and life satisfaction. Lastly, assistance pursuit style mediated stress and positive affect.

Conclusions

Participants’ problem-solving and assistance pursuit coping styles were shown as important mediating factors for stress and subjective well-being, especially positive affect. These findings need to be considered when planning interventions and implementing strategies focusing on the psychosocial health of the improvement of police officers’ well-being.