Statistical Methods in Aging Research: Improving Current Practices and Embracing Emerging Approaches

The Delphi method is a structured process used to obtain expert input on the development of evidence-based tools and resources like quality indicators and clinical guidelines. Despite an estimated 250% increase in the number of studies utilizing the Delphi method since 2014, no published literature has explored its use in aging research. The goals of this scoping review were to characterize applications of the Delphi method in aging research and identify areas for improvement in its application. We searched multiple databases for published literature from January 2018 through November 2024, identified eligible studies using predefined criteria, and extracted key information (e.g., scientific topics and alignment with best practices). We identified 89 Delphi studies in aging research that met inclusion criteria. The most frequent topics included models of care (n = 9), technology (n = 8), and bone health (n = 7). Delphi studies were seldom used to develop materials for subpopulations of older adults (e.g., racial/ethnic minority groups). Experts were mostly clinicians/care providers (n = 78) and researchers (n = 52); older adults (n = 8), unpaid caregivers (n = 3), and advocacy and education groups (n = 5) were least represented. Few studies (n = 9) adhered to guidance on Delphi best practices (e.g., CREDES), highlighting that most studies omitted checklists used to ensure transparent reporting of Delphi conduct. Our findings document trends in use of the Delphi method in aging research and document gaps in representation of experts and focal populations. Opportunities to improve Delphi application in aging research include identification and promotion of best practices for researchers and journals focused on aging.

Research methodology has recently been reduced to using research methods and techniques that are perceived only as ready-to-use tools. Paradigmatic issues become of secondary importance and left unsaid in research work or replaced by a multi-paradigm approach characterised by pluralist ontology and epistemology. The paradigm consists of assumptions and fundamental beliefs and represents a worldview that defines the nature of the world. It helps to justify the use of selected methods and techniques. The article aims to present the social constructionism paradigm and its application in old age and aging research.

Rationale: Observational studies report a significant protective effect of antifibrotics on mortality among patients with idiopathic pulmonary fibrosis (IPF). Many of these studies, however, were subject to immortal time bias because of the mishandling of delayed antifibrotic initiation. Objectives: To evaluate the antifibrotic effect on mortality among patients with IPF using appropriate statistical methods that avoid immortal time bias. Methods: Using a large administrative database, we identified 10,289 patients with IPF, of whom 2,300 used antifibrotics. Treating delayed antifibrotic initiation as a time-dependent variable, three statistical methods were used to control baseline characteristics and avoid immortal time bias. Stratified analysis was performed for patients who initiated antifibrotics early and those who initiated treatment late. For comparison, methods that mishandle immortal time bias were performed. A simulation study was conducted to demonstrate the performance of these models in a wide range of scenarios. Results: All three statistical methods yielded nonsignificant results for the antifibrotic effect on mortality, with the stratified analysis for patients with early antifibrotic initiation suggesting evidence for reduced mortality risk (for all patients, hazard ratio, 0.89; 95% confidence interval, 0.79-1.01; P = 0.08; for patients who were 65 years or older, hazard ratio, 0.85; 95% confidence interval, 0.73-0.98; P = 0.03). Methods that mishandle immortal time bias demonstrated significantly lower mortality risk for antifibrotic users. Bias of these methods was evident in the simulation study, where appropriate methods performed well with little to no bias. Conclusions: Findings in this study did not confirm an association between antifibrotics and mortality, with a stratified analysis showing support for a potential treatment effect with early treatment initiation.

Comparative differences between species provide a powerful source of information that may inform our understanding of the aging process. However, two problems regularly attend such analyses. The co-variation of traits with body mass is frequently ignored, along with the lack of independence of the data due to a shared phylogenetic history. These problems undermine the use of simple correlations between various factors and maximum lifespan potential (MLSP) across different species as evidence that the factors in question have causal effects on aging. Both of these problems have been widely addressed by comparative biologists working in fields other than aging research, and statistical solutions to these issues are available. Using these statistical approaches, of making analyses of residual traits with the effects of body mass removed, and deriving phylogenetically independent contrasts, will allow analyses of the relationships between physiology and maximum lifespan potential to proceed unhindered by these difficulties, potentially leading to many useful insights into the aging process.

Causal inference in population health research on aging is critical for understanding determinants of healthy aging and informing potential avenues of intervention. Such research faces a number of methodological challenges including data availability, detection bias, selection bias, confounding, and reverse causation. Novel statistical methods and approaches to leveraging data have been developed to address these issues. This session features cutting-edge research that incorporates novel methods and data to address key methodological challenges in aging research. Speakers will address (1) the use of hypothetical intervention approaches to address confounding and reverse causation to understand the impact of loneliness on memory function in older adults, (2) a multiple-exposure data reduction approach to identify important determinants of exercise in an aging population, (3) ways to uncover and account for detection bias in electronic health record studies of dementia, (4) pooling of cohorts to address gaps in data availability across the lifecourse, and (5) challenges and opportunities related to extending findings from selected aging samples to broader populations of interest. Epidemiology of Aging Interest Group Sponsored Symposium

Historical milestones in basic research on aging include (1) the demonstration that caloric res-triction (CR) increases average and maximum lifespan in rodents; (2) the proposal that oxidative stress is a major risk factor in the development of age-related pathology; and (3) the demonstration that human fibroblasts grown in culture have a finite lifespan. Thus, although research related to aging has been going on for well over 50 years, particularly on the age-related pathologies associated with aging, serious efforts to understand what factors modulate longevity are fairly new, and progress in this area is due primarily to the identification of genes that modulate longevity in short-lived animal models. Prior to 1980, the main focus was on describing aging phenomena in humans and rodents, and testing the various theories of aging resulting from these early observations. As the techniques of molecular biology were increasingly incorporated into aging-related research, it became possible to ask more mechanistic questions, and considerable progress was made during the period 1980–2000, largely because of the development of short-lived fruit fly and nematode models in which to study aging, followed by the sequencing of the genomes of these organisms. For example, this work quickly led to the discovery that the insulin-signalling pathway plays a major role in modulating longevity, not only in these organisms, but also in rodents and probably primates.

Chapter 3 - Omics approaches in aging research

The essay compares the five studies published in this special issue of The Journal of Applied Communication Research with previous research in communication and aging, noting changes in research methods and topics of investigation.

Chava Frankfort-Nachmias et al.’s eighth edition of the commended, ‘Research Methods in the Social Sciences’ aims to offer researchers a thorough and logical guide to undertaking social research. This edition includes new studies in respect to conducting research in a digital age, computer software packages and more up-todate examples on conducting social science research. The text is comprehensive and student-friendly, covering seven main areas of social science research: the scientific approach; the relationship between theory and research; ethics; research design; measurement and quantification; sampling; data collection; and data processing and analysis.

Due to the convenience of survey approaches, empirical aging research largely became a science of questionnaires that has limited its investigation of behavior to the boxes participants tick in a survey. In doing so, scholars have equated what people report they (or others) do with what actually happens. Although survey-based research can provide valuable insights into younger and older employees’ perceptions of their own and others’ behaviors, these perceptions are often biased and inaccurately reflect actual behavior. We argue that age and work research as well as practice could benefit from combining questionnaires with more objective methods to capture behavior. Accordingly, the purpose of this chapter is to stimulate scholars to conceptually think about research questions that can be answered at the fine-grained level of behavioral building blocks and to provide inspiration about research designs and methods that can be employed to study these questions. Specifically, we provide an overview of (dis-)advantages of several behavior-focused research methods and a classification of time-theoretical levels at which research questions can be answered. We conclude by outlining exemplary topics in research on age and work that we consider suitable for the application of behavior-focused methods.

Background: The evidence on the association between benevolent childhood experience (BCE) and depressive symptoms in students is complex. This study aims to explore the underlying mediation mechanism of BCE toward depressive symptoms and whether this link was moderated by the family relationship among Chinese undergraduates.Methods: From March 2021 to May 2021, a cross-sectional study was conducted in China, and 1821 undergraduates were recruited in this study. Participants were asked to complete a self-reported electronic questionnaire. The software SPSS PROCESS macro was used to test the mediation and mediated moderated modeling analysis.Results: Mediation analysis indicated that uncertainty stress (US) partly mediated the link between BCE and depressive symptoms (indirect effect = −0.47, 95% bootstrap CI = −0.55, −0.39). The indirect effect of the US accounted for 39.63% of the total variance in depression. Moderation analysis indicated that the association between the US and depressive symptoms was significantly modified by family relationships (interact effect = −0.019, P < 0.001). An integrative moderated mediation analysis indicated that the indirect effect from BCE to depressive symptoms through the US was also moderated by family relationships (interact effect = −0.012, P = 0.014).Conclusion: Uncertainty stress plays a key role in bridging BCE and depressive symptoms while the family relationship can buffer the impact of the US on depressive symptoms among Chinese undergraduates. Enhancing tolerance of uncertainty and improving family relationships are needed to protect undergraduates from depressive symptoms.

Drivers of Consumers’ Behaviour to Recycle Smartphones

This study aims to examine trends and future tasks of the Korean language education researches which use quantitative research methods and quantitative analysis in particular. In this study quantitative research methods are understood as statistical analysis-based research methods. In the quantitative analysis-based researches numerical materials are collected (characteristic aspect of the materials) and the materials are processed using statistical methods (processing aspect of the materials). The following points are examined. Firstly, a problem of subclassification of the quantitative method-based Korean language education researches is dealt with. Secondly, the two aspects, i.e. the collection of numerical materials in the Korean language education researches and the statistical processing of them are presented and a typical order of their statistical processing is examined. Thirdly, a problem of the quantitative indicator playing an important role in the collection of quantified materials is examined. The problem refers to what kind of quantitative indicators are used in corpus studies, and what kind of studies can be used in order to implement new quantitative indicators. Lastly, the study is concluded with a question on how the quantitative studies should deal with criticism on the quantitative analysis-based studies stating that the studies conducted in an artificial environment with restricted variables have difficulties in properly explaining complicated teaching-learning conditions. In order to examine recent trends in the quantitative analysis-based Korean language education studies this study examined research methods used in articles from three academic journals on Korean language education published in the last five years (from 2010 to September 2015). The examination revealed that 185 papers used quantitative analysis. Among them studies utilizing descriptive statistics were most common. In case of studies utilizing inferential statistics, comparative studies verifying differences between groups or variables, correlative studies showing relations between variables, effect relationship studies showing effect relations between variables and classification studies classifying variables or groups were distinguished.

Immortal Time Bias in Post-Operative Radiation Studies Utilizing the National Cancer Data Base

Gatekeeper trainings have been increasingly utilized in response to rising suicide rates in youths. However, the extent to which common factors inherent to gatekeeper trainings impact training outcomes is largely understudied. As such, the present study explored how factors such as training size and trainer engagement abilities influenced trainee participation and outcomes (i.e. changes in attitudes, perceived behavioral control (PBC), and knowledge regarding suicide prevention). All trainees participated in a gatekeeper training; trainers were not randomly assigned. Mediation and moderation analyses were completed using the PROCESS macro for SPSS (Hayes in Introduction to mediation, moderation, and conditional process analysis: a regression-based approach, Guilford Press, New York, 2013). Trainee participation in a training was examined as a mediator of the relationship between the training size and training outcomes, while trainer engagement was examined as a moderator of the relationship between size of training and trainee participation. Size of training was significantly related to lower changes in participant knowledge, along with lower trainee participation in gatekeeper trainings. Trainee participation significantly mediated the relationship between size of training, attitudes, and PBC. Additionally, trainer engagement significantly moderated the association between size of training and trainee participation. The results of this study suggest that general gatekeeper training-related variables may influence participant outcomes, specifically through trainee participation.