Utility Of Research Research Articles

Adapting rapid ethnographic research in an evolving emergency: Generalizable lessons in resilience

AbstractTo ensure the real‐world utility of emergency ethnographic research, plans must evolve as circumstances shift. The CommuniVax coalition's work provides a case study of this scenario. Using rapid ethnographic interviews, focus groups, and other methods, the six local CommuniVax teams sought to comprehend and improve COVID‐19 vaccine access and uptake. To this end, they responded nimbly to varying community priorities, the pandemic's shifting nature, evolving bureaucratic mechanisms, and political fluctuations. This paper provides specific examples of such instances, highlighting some of the critical decision points that emerged, demonstrating the flexibility needed for effective rapid community‐based research, reiterating the importance of a bottom‐up orientation, and elaborating on the trade‐offs that occurred in decision‐making regarding how best to move forward. This discussion is relevant to tackling any narrowly defined research problem, emergency‐related or not, as well as research seeking actionable answers to specific questions that have practical bearing on human lives.

Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging

Introduction:We propose a novel approach for the non-invasive quantification of dynamic PET imaging data, focusing on the arterial input function (AIF) without the need for invasive arterial cannulation. Methods:Our method utilizes a combination of three-dimensional depth-wise separable convolutional layers and a physically informed deep neural network to incorporatea priori knowledge about the AIF’s functional form and shape, enabling precise predictions of the concentrations of [11C]PBR28 in whole blood and the free tracer in metabolite-corrected plasma. Results:We found a robust linear correlation between our model’s predicted AIF curves and those obtained through traditional, invasive measurements. We achieved an average cross-validated Pearson correlation of 0.86 for whole blood and 0.89 for parent plasma curves. Moreover, our method’s ability to estimate the volumes of distribution across several key brain regions – without significant differences between the use of predicted versus actual AIFs in a two-tissue compartmental model – successfully captures the intrinsic variability related to sex, the binding affinity of the translocator protein (18 kDa), and age. Conclusions:These results not only validate our method’s accuracy and reliability but also establish a foundation for a streamlined, non-invasive approach to dynamic PET data quantification. By offering a precise and less invasive alternative to traditional quantification methods, our technique holds significant promise for expanding the applicability of PET imaging across a wider range of tracers, thereby enhancing its utility in both clinical research and diagnostic settings.

The potential of residual clinical Group B Streptococcus swabs for assessing the vaginorectal microbiome in late pregnancy

The maternal pregnancy microbiome (including genitourinary and gut) has been linked to important pregnancy/birth and later childhood health outcomes. However, such sampling as part of large population cohort studies is logistically and financially challenging. Many countries routinely collect vaginal or vaginal-rectal swabs in late pregnancy for Group B Streptococcus (GBS) screening, but their utility for population-based research is still unclear. As part of planning for the Generation Victoria population-based cohort study beginning in pregnancy, we assessed the utility and reliability of residual clinical GBS vaginal/vaginal-rectal swabs for generating late pregnancy microbiome data. We carried out a two-phased pilot study. Phase one assessed the level of microbial diversity apparent in ‘residual’ clinical vaginal/vaginal-rectal swabs post clinical testing and storage for 7–10 days at 4 °C (routine clinical practice). Phase two directly assessed the impact of storage time and temperature on the microbial composition of vaginal/vaginal-rectal swabs collected specifically for research purposes. The microbiota composition in the ‘residual’ clinical swabs aligned with published studies. The ‘research’ swabs, stored at 4 °C for up to ten days, showed minimal changes in microbiota profile, compared to swabs examined on the day of collection. In contrast, significant variation in diversity was seen in swabs stored at room temperature for up to 48 h. Residual clinical material from swabs collected primarily for GBS screening in late pregnancy represent a reliable and abundant source of material for assessing the late pregnancy maternal microbiome for research purposes. This represents a low-burden opportunity for population-representative pregnancy studies to assess the potential of late pregnancy microbiome for prediction and understanding maternal and child health outcomes.

Stable germline transgenesis using the Minos Tc1/mariner element in the sea urchin Lytechinus pictus.

Stable transgenesis is a transformative tool in model organism biology. Although the sea urchin is one of the oldest animal models in cell and developmental biology, studies in this animal have largely relied on transient manipulation of wild animals, without a strategy for stable transgenesis. Here, we build on recent progress to develop a more genetically tractable sea urchin species, Lytechinus pictus, and establish a robust transgene integration method. Three commonly used transposons (Minos, Tol2 and piggyBac) were tested for non-autonomous transposition, using plasmids containing a polyubiquitin promoter upstream of a H2B-mCerulean nuclear marker. Minos was the only transposable element that resulted in significant expression beyond metamorphosis. F0 animals were raised to sexual maturity, and spawned to determine germline integration and transgene inheritance frequency, and to characterize expression patterns of the transgene in F1 progeny. The results demonstrate transgene transmission through the germline, the first example of a germline transgenic sea urchin and, indeed, of any echinoderm. This milestone paves the way for the generation of diverse transgenic resources that will dramatically enhance the utility, reproducibility and efficiency of sea urchin research.

Extensions of open science for applied behavior analysis: Preregistration for single-case experimental designs.

Open science practices are designed to enhance the utility, integrity, and credibility of scientific research. This article highlights how preregistration in open science practice can be leveraged to enhance the rigor and transparency of single-case experimental designs within an applied behavior analysis framework. We provide an overview of the benefits of preregistration including increased transparency, reduced risk of researcher bias, and improved replicability, and we review the specific contexts under which these practices most benefit the proposed framework. We discuss potential concerns with and unique considerations for preregistering experiments that use single-case designs, with practical guidance for researchers who are seeking to preregister their studies. We present a checklist as a tool for researchers in applied behavior analysis to use for preregistration and provide recommendations for our field to strengthen the contingencies for open science practices that include preregistration.

Explainable ensemble learning framework for estimating corrosion rate in suspension bridge main cables

Ensuring the safe operation of suspension bridges is paramount to prevent unwanted events that can cause failures. Therefore, it is crucial to continuously monitor their operational status to uphold safety and reliability levels. However, natural deterioration caused by the surrounding environment, primarily due to corrosion, inevitably impacts these structures over time, particularly the main cables made of steel. In this study, a robust framework is proposed to predict the annual corrosion rate in main cables of suspension bridges, while investigating the impact of the surrounding environmental factors on this process. To do so, the implementation of four regression models and four machine learning techniques are used in the first phase for modeling the annual corrosion rate based on a comprehensive database containing various environmental factors. The modeling performance is evaluated through a range of statistical and graphical metrics. After that, Shapley Additive Explanations (SHAP) is utilized to explain the model and to extract the impact of each variable on the final modeling results. Overall, the findings demonstrate the effectiveness of the proposed framework for addressing this issue. The Extreme Gradient Boosting (XGB) emerged as the top-performing model, achieving an overall R2 of 0.982. Moreover, the SHAP findings highlight the impact of CL− on the annual corrosion rate as the factor with the highest influence during the modeling process. The high performance of the proposed model suggests its potential utility in further research concerning the reliability of suspension bridge main cables.

Droplet-enabled controllable manipulation of tribo-charges from liquid-solid interface

Efficient utilization of electrostatic charges is paramount for numerous applications, from printing to kinetic energy harvesting. However, existing technologies predominantly focus on the static qualities of these charges, neglecting their dynamic capabilities as carriers for energy conversion. Herein, we report a paradigm-shifting strategy that orchestrates the swift transit of surface charges, generated through contact electrification, via a freely moving droplet. This technique ingeniously creates a besptengngoke charged surface which, in tandem with a droplet acting as a transfer medium to the ground, facilitates targeted charge displacement and amplifies electrical energy collection. The spontaneously generated electric field between the charged surface and needle tip, along with the enhanced water ionization under the electric field, proves pivotal in facilitating controlled charge transfer. By coupling the effects of charge self-transfer, contact electrification, and electrostatic induction, a dual-electrode droplet-driven triboelectric nanogenerator (DD–TENG) is designed to harvest the water-related energy, exhibiting a two-order-of-magnitude improvement in electrical output compared to traditional single-electrode systems. Our strategy establishes a fundamental groundwork for efficient water drop energy acquisition, offering deep insights and substantial utility for future interdisciplinary research and applications in energy science.

Liars know they are lying: differentiating disinformation from disagreement

Mis- and disinformation pose substantial societal challenges, and have thus become the focus of a substantive field of research. However, the field of misinformation research has recently come under scrutiny on two fronts. First, a political response has emerged, claiming that misinformation research aims to censor conservative voices. Second, some scholars have questioned the utility of misinformation research altogether, arguing that misinformation is not sufficiently identifiable or widespread to warrant much concern or action. Here, we rebut these claims. We contend that the spread of misinformation—and in particular willful disinformation—is demonstrably harmful to public health, evidence-informed policymaking, and democratic processes. We also show that disinformation and outright lies can often be identified and differ from good-faith political contestation. We conclude by showing how misinformation and disinformation can be at least partially mitigated using a variety of empirically validated, rights-preserving methods that do not involve censorship.

The Race-Gender-Equity-Leadership Matrix: Intersectionality and Its Application in Higher Education Literature

Intersectionality is a proven theoretical framework, offering a lens to explore how multiple identities and interlocking systems of power influence equity for historically underserved groups. This paper, with its unique focus on Black/African American women as a unilateral demographic, applies the multi-level intersectionality model to elucidate how race and gender converge to impact the educational and leadership experiences of Black/African Diasporan women. By illustrating the model’s utility in research, policy, and practice, it not only sheds light on how systems of privilege shape opportunities and (in)equities for underrepresented groups, particularly within the context of higher education and leadership, but also provides actionable insights that empower policymakers and practitioners to make a difference. Framed within the context of higher education in the United States, this research underscores the need for more attention to race-gender diversity in higher education, as education and leadership are, in many ways, a manifestation of attainment and self-actualization. These insights can guide the development of effective policies and practices that promote equity and diversity in higher education, offering tangible solutions to the persistent challenges faced by Black/African American women in these spheres.

Pregnancy episodes in All of Us: harnessing multi-source data for pregnancy-related research.

The National Institutes of Health's All of Us Research Program addresses gaps in biomedical research by collecting health data from diverse populations. Pregnant individuals have historically been underrepresented in biomedical research, and pregnancy-related research is often limited by data availability, sample size, and inadequate representation of the diversity of pregnant people. All of Us integrates a wealth of health-related data, providing a unique opportunity to conduct comprehensive pregnancy-related research. We aimed to identify pregnancy episodes with high-quality electronic health record (EHR) data in All of Us Research Program data and evaluate the program's utility for pregnancy-related research. We used a previously published algorithm to identify pregnancy episodes in All of Us EHR data. We described these pregnancies, validated them with All of Us survey data, and compared them to national statistics. Our study identified 18970 pregnancy episodes from 14234 participants; other possible pregnancy episodes had low-quality or insufficient data. Validation against people who reported a current pregnancy on an All of Us survey found low false positive and negative rates. Demographics were similar in some respects to national data; however, Asian-Americans were underrepresented, and older, highly educated pregnant people were overrepresented. Our approach demonstrates the capacity of All of Us to support pregnancy research and reveals the diversity of the pregnancy cohort. However, we noted an underrepresentation among some demographics. Other limitations include measurement error in gestational age and limited data on non-live births. The wide variety of data in the All of Us program, encompassing EHR, survey, genomic, and fitness tracker data, offers a valuable resource for studying pregnancy, yet care must be taken to avoid biases.

FragHub: A Mass Spectral Library Data Integration Workflow.

Open mass spectral libraries (OMSLs) are critical for metabolite annotation and machine learning, especially given the rising volume of untargeted metabolomic studies and the development of annotation pipelines. Despite their importance, the practical application of OMSLs is hampered by the lack of standardized file formats, metadata fields, and supporting ontology. Current libraries, often restricted to specific topics or matrices, such as natural products, lipids, or the human metabolome, may limit the discovery potential of untargeted studies. The goal of FragHub is to provide users with the capability to integrate various OMSLs into a single unified format, thereby enhancing the annotation accuracy and reliability. FragHub addresses these challenges by integrating multiple OMSLs into a single comprehensive database, supporting various data formats, and harmonizing metadata. It also proposes some generic filters for the mass spectrum using a graphical user interface. Additionally, a workflow to generate in-house libraries compatible with FragHub is proposed. FragHub dynamically segregates libraries based on ionization modes and chromatography techniques, thereby enhancing data utility in metabolomic research. The FragHub Python code is publicly available under a MIT license, at the following repository: https://github.com/eMetaboHUB/FragHub. Generated data can be accessed at 10.5281/zenodo.11057687.

FDI: A MATLAB tool for computing the fractal dimension index of sources reconstructed from EEG data

BackgroundThe fractal dimension (FD) is a valuable tool for analysing the complexity of neural structures and functions in the human brain. To assess the spatiotemporal complexity of brain activations derived from electroencephalogram (EEG) signals, the fractal dimension index (FDI) was developed. This measure integrates two distinct complexity metrics: 1) integration FD, which calculates the FD of the spatiotemporal coordinates of all significantly active EEG sources (4DFD); and 2) differentiation FD, determined by the complexity of the temporal evolution of the spatial distribution of cortical activations (3DFD), estimated via the Higuchi FD [HFD(3DFD)]. The final FDI value is the product of these two measurements: 4DFD × HFD(3DFD). Although FDI has shown utility in various research on neurological and neurodegenerative disorders, existing literature lacks standardized implementation methods and accessible coding resources, limiting wider adoption within the field. MethodsWe introduce an open-source MATLAB software named FDI for measuring FDI values in EEG datasets. ResultsBy using CUDA for leveraging the GPU massive parallelism to optimize performance, our software facilitates efficient processing of large-scale EEG data while ensuring compatibility with pre-processed data from widely used tools such as Brainstorm and EEGLab. Additionally, we illustrate the applicability of FDI by demonstrating its usage in two neuroimaging studies. Access to the MATLAB source code and a precompiled executable for Windows system is provided freely. ConclusionsWith these resources, neuroscientists can readily apply FDI to investigate cortical activity complexity within their own studies.

The Cancer Clinical Library Database (CCLD) from the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) Project.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea's cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Lithium Bis(Trifluoromethanesulfonyl)Imide (LiTFSI): A Prominent Lithium Salt in Lithium‐Ion Battery Electrolytes – Fundamentals, Progress, and Future Perspectives

AbstractLithium bis(trifluoromethanesulfonyl)imide (LiTFSI) is a widely used lithium (Li) salt that is extensively studied in the field of electrolytes for Li‐ion batteries (LIBs) to improve their performance. A thorough understanding of its underlying mechanisms in LIBs is crucial for gaining deeper insights into its future development. This paper provides an extensive review of the role of LiTFSI in enhancing battery performance, including its benefits for negative electrode protection, the facilitation of fast charging capabilities, and the promotion of battery operation across a wide temperature range. It also highlights the specific drawbacks of LiTFSI in the electrolyte domain and examines potential solutions. By leveraging the unique properties of LiTFSI, the strategies for its effective utilization in current research are outlined. Finally, the paper discusses the lack of research into the mechanism of LiTFSI in interface protection, particularly the evolution mechanisms of multi‐component Li salts at the positive and negative electrode interfaces, and it reasonably anticipates the potential applications of LiTFSI in the realm of non‐liquid batteries. This study not only provides a more comprehensive and profound understanding of LiTFSI but also aids in the exploration of novel electrolyte systems.

Conceptualization and validation of the TILT questionnaire: relationship with IGD and life satisfaction.

Currently, the study of esports is growing within the field of psychology. Among the different variables attracting interest - including stress or psychological factors associated with performance - an emerging concept known as tilt is gaining prominence in the literature. However, this construct has yet to be operationalized or defined. Thus, the present study aims to address this gap by defining and conceptualizing TILT while devising and validating a questionnaire to measure the construct in esports players. The initial phase of the study comprised 27 interviews conducted with professional players (n = 6), semi-professionals (n = 8), amateurs (n = 8), and coaches (n = 5) to characterize the concept of tilt. Following these interviews, a definition of tilt was formulated, and a panel of five experts in sports psychology and esports proposed a comprehensive set of 53 items. A total of 488 participants (278 males, 210 females), aged 18-50 (mean age = 26.9 years, SD = 7.57), completed the survey, including the 53 tilt items, a questionnaire measuring toxic behavior, and the Internet Gaming Disorder Scale-Short Form (IGDS9-SF). The tilt construct is primarily characterized as a state of frustration escalating into anger, resulting in diminished performance, attention, and recurring negative thoughts about errors. Its onset typically coincides with stressful situations, persisting for approximately 30 min. Through an Exploratory Factor Analysis (EFA), 18 items were retained and categorized into two factors: Causes (7 Items) and Consequences (11 Items) of tilt. The entire questionnaire yielded a Cronbach's α of 0.922, with the first and second factors showing values of 0.854 and 0.890, respectively. Confirmatory factor analysis (CFA) revealed an acceptable fit for the 2-factor solution. Correlations with related constructs, such as Toxic Behavior and IGD, provided preliminary evidence of external validity. Empirical evidence for the validity and internal consistency of the Tilt Scale is robust, indicating its potential utility in future research on the psychological experiences of esports players.

Modular narratives and visual digital culture in contemporary cinema. The case of Open Windows (Nacho Vigalondo, 2014)

In the present day, digital visual and convergence culture permeate the modes of production, circulation, and consumption of audiovisual representations, following the postulates of authors such as A. Darley or H. Jenkins. In this context, A. Cameron defines modular narratives as those in which classical narrative causality is replaced by a database aesthetic, dividing the narrative into discrete elements subject to manipulations of order, frequency, and duration. Focusing on the case of Open Windows (Nacho Vigalondo, 2014), this study aims to explore the imprints of digital visual culture on contemporary Spanish cinema incorporating modular narratives. The methodology employs an analysis model adapted to this narrative and aesthetic specificity within the framework of Computational Media Aesthetics. The film's mechanisms of representation are scrutinized through a multi-screen interface, where simultaneous events are juxtaposed within the same visual field. Finally, the discussion encompasses the necessity of applying such models to the analysis of audiovisual content associated with digital visual culture, as well as their potential utility for future research.

Exploring allelochemicals for cleaner and sustainable agriculture: A bibliometric review on research trends, challenges and future prospective.

Allelopathic research is not getting the intended consideration because of the complexities involved in their isolation, identification, understanding their modes of action, interactions with other environmental factors, impacts on non-target organisms and exploration of their utility in diverse fields. Additionally, their variability and trace availability have presented hurdles in establishing future research utilities and their field applications. Exploring the historical context of allelopathic research is essential for obtaining a more profound understanding of the progression in this research domain and to identify the research gaps and potential future prospectives. Therefore, the current bibliometric review aims to examine the research advancements, trends, hotspots, research gaps and to identify future prospectives in allelopathic research. A Scopus database search was carried out to collect the bibliometric data using the combination of multiple search strings in advance search option. The outcomes of this study revealed a total of 5427 published articles, with an average of 19.12 citations per article. Despite the increasing trend in research and publications on allelopathy/allelochemicals over the last decade, the majority of allelopathic research remains focused on investigating novel allelochemicals and their potential for weed management. Other crucial considerations like their phytotoxicity and ecotoxicity, selectivity for crop growth, interactions with herbicides and their derivatives, biochemical signalling, identification of germplasm in allelopathic plants, inducing allelopathic trait into enhanced cultivars, their ultimate fate in the open environment are sparsely investigated. It is anticipated that this review will draw greater attention to some overlooked domains within allelopathic research.

Clinical utility of the Lumipulse™ immunoassay for plasma neurofilament light chain in multiple sclerosis

ObjectiveBlood neurofilament light chain (NfL) is robustly associated with disease worsening in multiple sclerosis (MS), though potentially affected by concomitant factors also determining neuro-axonal loss. We investigated the association between plasma NfL (pNfL) measured with Lumipulse™ immunoassay and demographic and clinical variables in MS. MethodsThis cross-sectional study included 685 people with MS (age 49.7 ± 12.4 years; sex 65.55% females). On the same day, we collected plasma samples, along with demographics, comorbidities, and clinical variables (MS disease duration, expanded disability status scale (EDSS), Symbol Digit Modalities Test (SDMT), descriptor of disease progression, current disease modifying treatment (DMT), number of previous DMTs, evidence of disease activity in the past year (i.e. relapse or MRI new lesions), EDSS progression). pNfL was evaluated using Lumipulse™ fully automated chemiluminescent enzyme immunoassay. ResultsOn multivariable linear regression model, higher pNfL was associated with higher EDSS (Coeff = 1.73; 95%CI 0.78, 2.68; p < 0.01), recent disease activity (Coeff = 15.70; 95%CI = 5.35, 26.06; p < 0.01), and presence of cardiovascular comorbidity (Coeff = 3.84; 95%CI 0.48, 7.20; p = 0.025). Lower pNfL was found in patients on DMT treatment (Coeff = −10.23; 95%CI -18.42, −2.04; p = 0.015), when compared with no DMT (reference). For 77.81% of our population there was correspondence between pNfL levels and two previously-validated cutoffs. ConclusionspNfL measured using Lumipulse™ confirms known associations with MS activity, disability and treatments, and related confounding (e.g., cardiovascular comorbidity), thus granting further utilization in research and clinical practice.

Return to Work After Breast Cancer Treatment: An Electronic Health Record-based Study in North Norway.

Breast cancer treatment may interfere with work ability. Previous return-to-work studies have often focused on participants who were invited to participate after treatment completion. Participation varied, resulting in potential selection bias. This is a health-record-based study evaluating data completeness, both at baseline and one year after diagnosis. Correlations between baseline variables and return to work were also analyzed. This is a retrospective review of 150 relapse-free survivors treated in Nordland county between 2019 and 2022 (all-comers managed with different types of systemic treatment and surgery). Work status was assessed in the regional electronic patient record (EPR). A 65-years age cut-off was employed to define two subgroups. At diagnosis, occupational status was assessable in all 150 patients. Almost all patients older than 65 years of age were retired (79%) or on disability pension for previously diagnosed conditions (19%). Data completeness one year after diagnosis was imperfect, because the EPR did not contain required information in 19 survivors. The majority of those ≤65 years of age at diagnosis returned to work. Only 14 of 88 patients (16%) did not return to work. Postoperative nodal stage was the only significant predictive factor. Those with pN1-3 had a lower return rate (68%) than their counterparts with lower nodal stage. This pilot study highlights the utility and limitations of EPR-based research in a rural Norwegian setting, emphasizing the need for comprehensive, individualized interventions to support breast cancer survivors in returning to work. The findings underscore the importance of considering diverse sociodemographic and clinical factors, as well as the potential benefits of long-term, population-based studies to address these complex challenges.

Estimating cardiorespiratory fitness in older adults using the international physical activity questionnaire.

Non-exercise estimates of cardiorespiratory fitness hold great utility for epidemiological research and clinical practice. Older adults may yield the greatest benefit from fitness estimates due to limited capacity to undergo strenuous maximal exercise testing, however, few of the previously developed non-exercise equations are suitable for use in older adults. Thus, the current study developed a non-exercise equation for estimating cardiorespiratory fitness in older adults derived from the widely used International Physical Activity Questionnaire (IPAQ). This study was a secondary analysis of baseline data from a randomized controlled trial. Participants were community-dwelling, cognitively unimpaired older adults aged 60-80 years (n = 92). They completed the IPAQ and underwent maximal exercise testing on a cycle ergometer. Stepwise linear regression was used to determine the equation in a randomly selected, sex-balanced, derivation subset of participants (n = 60), and subsequently validated using a second subset of participants (n = 32). The final equation included age, sex, body mass index and leisure time activity from the IPAQ and explained 61% and 55% of the variance in the derivation and validation groups, respectively (standard error of estimates = 3.9, 4.0). Seventy-seven and 81% of the sample fell within ±1SD (5.96 and 6.28 ml·kg-1·min-1) of measured VO2peak for the derivation and validation subgroups. The current equation showed better performance compared to equations from Wier et al. (2006), Jackson et al. (1990), and Schembre & Riebe (2011), although it is acknowledged previous equations were developed for different populations. Using non-exercise, easily accessible measures can yield acceptable estimates of cardiorespiratory fitness in older adults, which should be further validated in other samples and examined in relation to public health outcomes.