A Unified Survey of Treatment Effect Heterogeneity Modelling and Uplift Modelling

A central question in many fields of scientific research is to determine how an outcome is affected by an action, i.e., to estimate the causal effect or treatment effect of an action. In recent years, in areas such as personalised healthcare, sociology, and online marketing, a need has emerged to estimate heterogeneous treatment effects with respect to individuals of different characteristics. To meet this need, two major approaches have been taken: treatment effect heterogeneity modelling and uplifting modelling. Researchers and practitioners in different communities have developed algorithms based on these approaches to estimate the heterogeneous treatment effects. In this article, we present a unified view of these two seemingly disconnected yet closely related approaches under the potential outcome framework. We provide a structured survey of existing methods following either of the two approaches, emphasising their inherent connections and using unified notation to facilitate comparisons. We also review the main applications of the surveyed methods in personalised marketing, personalised medicine, and sociology. Finally, we summarise and discuss the available software packages and source codes in terms of their coverage of different methods and applicability to different datasets, and we provide general guidelines for method selection.

FAMILY SUPPORT-BASED PSYCHOEDUCATION IN CARING SCHIZOPHRENIC PATIENTS: A LITERATURE REVIEW

Background: The burden of family in caring a schizophrenia impacts on psychological shock and emotional burden; lack of disease knowledge and care skills; poor patient medication adherence; the difficulty of getting along with patients; conflict in the family or at work; financial burden; and need adequate social support. Aim: This study discussed how family support takes care of people with schizophrenia with a psychoeducational approach in mental health service settings. Method: A non-systematic literature review was carried out using the PICO (Population, Intervention, Comparison, Outcome) framework utilizing Scopus, CINAHL, and ProQuest databases in the last 5 years, searching with keywords: Family Support AND Schizophrenia OR Family Psychoeducation. Results: Families with schizophrenia experience the most potent stressors on the burden of care borne, in addition to stigma and the frequency of relapse of sufferers. Community care providers can involve the family in various ways, such as providing psychoeducation, supporting the family's physical, emotional and social needs, and behavioral family assessment or family therapy. Conclusion: Mental health services must develop and imply family psychoeducation training.

Discovery of Genes Positively Modulating Treatment Effect Using Potential Outcome Framework and Bayesian Update

BackgroundThe recent explosion of cancer genomics provides extensive information about mutations and gene expression changes in cancer. However, most of the identified gene mutations are not clinically utilized. It remains uncertain whether the presence of a certain genetic alteration will affect treatment response. Conventional statistics have limitations for causal inferences and are hard to gain sufficient power in genomic datasets. Here, we developed and evaluated an algorithm for searching the causal genes that maximize the effect of the treatment.MethodsThe algorithm was developed based on the potential outcome framework and Bayesian posterior update. The precision of the algorithm was validated using a simulation dataset. The algorithm was implemented to a cBioPortal dataset. The genes discovered by the algorithm were externally validated within CancerSCAN screening data from Samsung Medical Center.ResultsSimulation data analysis showed that the C-search algorithm was able to identify nine causal genes out of ten. The C-search algorithm shows the discovery rate rapidly increasing until the 1500 number of data. Meanwhile, the log-rank test shows a slower increase in performance. The C-search algorithm was able to suggest nine causal genes from the cBioPortal Metabric dataset. Treating the patients with the causal genes are associated with better survival outcome in both the cBioPortal dataset and the CancerSCAN dataset which is used for external validation.ConclusionsOur C-search algorithm demonstrated better performance to identify causal effects of the genes than multiple rog-rank test analysis especially within a limited number of data. The result suggests that the C-search can discover the causal genes from various genetic datasets, where the number of samples is limited compared to the number of variables.

Consensus statement on safety measures for pressurized intraperitoneal aerosol chemotherapy

Objectives Pressurized intraperitoneal aerosol chemotherapy (PIPAC) is a promising treatment for peritoneal cancer that entails, however, potential risks for the caregivers in the operating room (OR). This study aimed to reach a consensus within the PIPAC community on a comprehensive safety protocol. Methods Active PIPAC centers were invited to participate in a two-round Delphi process on 43 predefined items: concise summaries of the existing evidence were presented together with questions formulated using the population, intervention, comparator, and outcome framework. According to the Grading of Recommendations Assessment, Development, and Evaluation, the strength of recommendation was voted by panelists, accepting a consensus threshold of ≥50% of the agreement for any of the four grading options, or ≥70% in either direction. Results Forty-seven out of 66 invited panelists answered both rounds (response rate 76%). The consensus was reached for 41 out of 43 items (95.3%). Strong and weak recommendations were issued for 30 and 10 items, respectively. A positive consensual recommendation was issued to activate laminar airflow without specific strength, neither strong nor weak. No consensus was reached for systematic glove change for caregivers with a high risk of exposure and filtering facepiece mask class 3 for caregivers with low risk of exposure. Conclusions A high degree of consensus was reached for a comprehensive safety protocol for PIPAC, adapted to the risk of exposure for the different caregivers in the OR. This consensus can serve as a basis for education and help reach a high degree of adherence in daily practice.

Causation and causal inference

This chapter provides an introduction to causal inference theory for public health research. Causal inference can be viewed as a prediction problem, addressing the question of what the likely outcome will be under one action vs. an alternative action. To answer this question usefully requires clarity and precision in both the statement of the causal hypothesis and the techniques used to attempt an answer. This chapter reviews considerations that have been invoked in discussions of causality based on epidemiologic evidence. It then describes the potential-outcome (counterfactual) framework for cause and effect, which shows how measures of effect and association can be distinguished. The potential-outcome framework illustrates problems inherent in attempts to quantify the changes in health expected under different actions or interventions. The chapter concludes with a discussion of how research findings may be translated into policy.

A Systematic Literature Review of Quality Management Initiatives in Dental Clinics

By considering the recently proposed definitions and metrics, oral healthcare quality management (OHQM) emerges as a distinct field in the wider healthcare area. The goal of this paper is to systematically review quality management initiatives (QMIs) implementation by dental clinics. The research methodology approach is a review of 72 sources that have been analyzed using the Context–Intervention–Mechanism–Outcome Framework (CIMO). The analysis identifies five mechanisms that explain how quality management initiatives are implemented by dental clinics. The simplest QMIs implementations are related to (1) overall quality. The next ones, in terms of complexity, are related to (2) patient satisfaction, (3) service quality, (4) internal processes improvement, and (5) business outcomes. This paper is the first attempt to provide a critical review of this topic and represents an important advancement by providing a theoretical framework that explains how quality management is implemented by practitioners in this field. The results can be used by scholars for advancing their studies related to this emerging research area and by healthcare managers in order to better implement their quality management initiatives.

The New Progression Model of Entrepreneurial Education—Guideline for the Development of an Entrepreneurial University with a Sustainability Approach

Entrepreneurship is becoming understood as a set of competencies needed for many professions and, as a result, requires to be integrated into higher education even in such seemingly distant areas as, e.g., public administration, sport, agriculture, tourism, etc. Therefore, there is a need for research-based guidance on how to introduce and develop entrepreneurial education as an enabling approach to the transition in higher education that could serve as an integral part of a paradigm shift towards an entrepreneurial university. This paper aims to support that transition and to address related challenges by the presentation of a new progression model, which provides guidelines for the development of courses at the tertiary level with an entrepreneurial university approach. The construction of the new applicable model is central to the purpose of this study and based on a systematized literature review. Additionally, the input–process–output–outcome framework, originally constructed for the evaluation of educational programs, was adapted to the incorporation of an overall framework into the new model. In the results, the paper redefines some of the relevant core terms, such as “entrepreneurial education” and its “progression model”. The research outcomes offer broad practical and theoretical applicability to a range of stakeholders—educators, students/learners, industry/business, policy makers, and researchers.

Flooded with too many messages? Predictors and consequences of instant messaging fatigue

PurposeDuring the digital media era with an explosion of messages, the prevalence of what is known as “message fatigue” has grown. However, there is a lack of understanding toward message fatigue in using instant messengers. Based on the stressor-strain-outcome framework, this study provides a theoretical model to explore possible predictors and consequences of instant messaging fatigue.Design/methodology/approachThe hypothesized model includes communication overload, social overload, instant messaging fatigue, technology and behavioral intention to use instant messaging. Three hundred and eleven responses are collected using an online survey. The authors conduct structural equation modeling to evaluate the hypothesized model and test the hypotheses.FindingsThis study reveals that (1) communication overload and social overload are positively associated with instant messaging fatigue and technostress; (2) higher levels of instant messaging fatigue and technostress are also related to a higher level of intention to discontinue usage; (3) technostress significantly mediates the relationship between instant messaging fatigue and intention to discontinue usage of instant messaging.Research limitations/implicationsThis study is limited to collect data from one university in the United States with a cross-sectional design. Future research should include other countries, different age groups and longitudinal methods to examine instant messaging fatigue.Originality/valueThis study extends existing findings on fatigue in using mobile communication by applying the stressor-strain-outcome framework to IM fatigue and improves the understanding of the potential negative aspects of instant messaging.

The Integration of Lean and Resilience Paradigms: A Systematic Review Identifying Current and Future Research Directions

Integration of the lean and resilience paradigms has attracted increasing attention among scientists and practitioners. In an interconnected world, the need to be resilient involves increased readiness to deal with risks from both outside and inside an enterprise, and to be lean involves maximizing value while minimizing waste. The combination of these requirements has been the catalyst for a move towards lean–resilience operations. To better understand this trend, which seeks to help firms retain a competitive position and survive disruptions, this paper provides a systematic literature review of 53 articles identified through the C-I-M-O (context-intervention-mechanism-outcome) framework and examines them using descriptive and content analysis. The results trace the growth of lean–resilience research from its infancy to its current advanced state. This paper also identifies for the first time the lack of structured research on the number and categories of implemented practices and their associated benefits. To address this deficiency, a concept map is developed to provide guidance on the topic, identify gaps and inconsistencies in the literature, understand the state of development and suggest future research directions. The results are used to identify four dominant streams: application, compatibility, integration, and impact assessment in the context of the supply chain, conceptual development and operational research of various organizational and industry sectors. Further topics for investigation are recommended in the form of research questions. The proposed concept map is intended to assist researchers and practitioners to develop knowledge about the integration of lean and resilience paradigms in new contexts and formulate more effective deployment strategies.