Use Of Exploratory Factor Analysis Research Articles

Exploratory Factor Analysis (EFA) in Quantitative Researches and Practical Considerations

Explanatory factor analysis (EFA) is a multivariate statistical method frequently used in quantitative research and has begun to be used in many fields such as social sciences, health sciences and economics. With EFA, researchers focus on fewer items that explain the structure, instead of considering too many items that may be unimportant and carry out their studies by placing these items into meaningful categories (factors). However, for over sixty years, many researchers have made different recommendations about when and how to use EFA. Differences in these recommendations confuse the use of EFA. The main topics of discussion are sample size, number of items, item extraction methods, factor retention criteria, rotation methods and general applicability of the applied procedures. The abundance of these discussions and opinions in the literature makes it difficult for researchers to decide which procedures to follow in EFA. For this reason, it would be beneficial for researchers to gather different information about the general procedures (sample number, rotation methods, etc.) in the use of EFA. This paper aims to provide readers with an overview of what procedures to follow when implementing EFA and share practical information about the latest developments in methodological decisions in the EFA process. It is considered that the study will be an important guide for the researchers in the development of clear decision paths in the use of EFA, with the aspect of presenting the most up-to-date information collectively.

Misbegotten methodologies and forgotten lessons from Tom Swift's electric factor analysis machine: A demonstration with competing structural models of psychopathology.

Confirmatory factor analysis (CFA) and its bifactor models are popular in empirical investigations of the factor structure of psychological constructs. CFA offers straightforward hypothesis testing but has notable pitfalls, such as the imposition of strict assumptions (i.e., simple structure) that obscure unmodeled complexity. Due to the limitations of bifactor CFAs, they have yielded anomalous results across samples and studies that suggest model misspecification (e.g., evaporating specific factors and unexpected loadings). We propose the use of exploratory factor analysis (EFA) to evaluate the structural validity of CFA solutions-either before or after the estimation of more restrictive CFA models-to (a) identify model misspecifications that may drive anomalous estimates and (b) confirm CFA models by examining whether hypothesized structures emerge with limited researcher input. We evaluated the degree to which predominant factor structures were invariant across contexts along the exploratory-confirmatory continuum and demonstrate how poor methodological choices can distort results and impede theory development. All CFA models fit well, but there were numerous differences in replicability and substantive interpretability. Several similarities emerged between bifactor CFA and EFA models, including evidence of overextraction, the collapse of specific factors onto the general factor, and subsequent shifts in how the general factor was defined. We situate these methodological shortcomings within the broader literature on structural models of psychopathology, articulate implications for theories (such as the p-factor) that are borne out of factor analysis, outline several remedies for problems encountered when performing exploratory bifactor analysis, and propose alternative specifications for confirmatory bifactor models. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Methods to develop and evaluate attitudinal scales to measure farmer perceptions: Using sheep scab as an example.

There is limited information on the attitudes and opinions of British sheep farmers when preventing and managing sheep scab in their flocks. Attitudes are examples of latent traits, which are not directly observable. They must be measured indirectly which can be achieved using measurement scales. Attitudinal measurement scales are used frequently in research, but are seldom evaluated prior to use, particularly in veterinary research. Therefore, the aim of this study was to identify and assess latent traits which influence the control of sheep scab with the use of exploratory factor analysis, and then further evaluate these factors with the use of item response theory to determine how they perform as scales. An online survey was completed by 726 British sheep farmers during October 2021 (725 useable responses), which included a section with 37 belief statements related to the opinions and attitudes of sheep farmers around the management of sheep scab. These belief statements were developed and adapted from previous research. During the analysis, they were subjected to exploratory factor analysis, which suggested that the scales performed reasonably well. The scales were then evaluated further by item response theory. The graded response models for each attitudinal scale were assessed by graphical evaluation. They demonstrated that the scales were able to distinguish those respondents with low perceptions of control, responsibility, and trust, and those who had high perceptions of luck. This study provides insights into some of the factors influencing the management of sheep scab, and how well these scales perform. Additionally, it further highlights the importance of evaluating attitudinal scales for use in research, and that exploratory factor analysis alone does not provide enough information on how well they perform.

Factor Structure of ASD Symptoms in Russian 3-4-Year-Olds

The study aims to reveal autism vectors that are inherent in 3-4-year-olds with ASD. Three hundred eighty-three children with ASD took part in the research. An online questionnaire developed earlier by our research group was used. In the first stage, with the repeated use of exploratory factor analysis, the task of identifying the simplest factor structure was solved. As a result, a 7-factor system was obtained, including from 9 to 14 items in each factor (78 items in total): 1) "Persistence on sameness" (Sam); 2) "Emotional dysregulation" (Em); 3) "Alienation" (Al); 4) "Speech understanding" (SU); 5) "Disinhibition/Hyperactivity" (Hyp); 6) "Echolalia" (Ech); 7) "Sensory disintegration" (Sen). Next, a "parcel approach" was applied: binary items included in each factor were randomly distributed into 3 packages, from 3 to 5 items in each box. Thus, instead of 78 binary things, 21 quantitative variables were analyzed. At the second stage, a multi-group confirmatory factor analysis was applied to verify the factor validity and structural and measurement equivalence of the obtained 7-factor model to the parts of the sample that differ by gender (m, f) and age (3 and 4 years). The factor validity of the 7-factor model was confirmed: the factors Em, Al, Su, and Ech correlated with each other (correlations from 0.33 to 0.65), forming a group of communication disorders, the second group consisted of factors Sam and Sen (r = 0.66), the factor Hyp did not correlate with other elements. The equivalence of this 7-factor model was confirmed with respect to samples differing in gender (m, f) and age (3 and 4 years). According to all 7 calculated factors-scales, the example of children with ASD statistically significantly differed from other children with the magnitude of the Coen's d effect from 0.688 to 2.088. However, it can be supposed that the factor dimension of autism symptoms can be even more significant, because the revealed structure is based on 436 initial hypothetical symptoms of autism.

In situ H2O2 treatment of blue-green algae contaminated reservoirs causes significant improvement in drinking water treatability

The evaluation of water quality improvement brought about by in situ treatment of eutrophic water bodies, especially those used for human supply is a challenging task since each water system responds differently. To overcome this challenge, we applied exploratory factor analysis (EFA) to understand the effects of using hydrogen peroxide (H2O2) on eutrophic water used as a drinking water supply. This analysis was used to identify the main factors that described the water treatability after exposing blue-green algae (cyanobacteria) contaminated raw water to H2O2 at both 5 and 10 mg L−1. Cyanobacterial chlorophyll-a was undetectable following the application of both concentrations of H2O2 after four days, while not causing relevant changes to green algae and diatoms chlorophyll-a concentrations. EFA demonstrated that the main factors affected by both H2O2 concentrations were turbidity, pH, and cyanobacterial chlorophyll-a concentration, which are important variables for a drinking water treatment plant. The H2O2 caused significant improvement in water treatability by decreasing those three variables. Finally, the use of EFA was demonstrated to be a promising tool in identifying which limnological variables are most relevant concerning the efficacy of water treatment, which in turn can make water quality monitoring more efficient and less costly.

Confirmatory measurement modeling and longitudinal invariance of the CompACT-15: A short-form assessment of psychological flexibility.

The Comprehensive Assessment of Acceptance and Commitment Therapy Processes (CompACT; Francis et al., 2016) is a recently developed measure of psychological flexibility (PF) possessing several advantages over other measures of PF, including multidimensional assessment and relative brevity. Unfortunately, previous psychometric evaluations of the CompACT have been limited by their use of exploratory factor analysis to assess dimensionality, coefficient α to assess reliability, and a lack of attention to measurement equivalence in assessing change over time. The present study used confirmatory factor analysis (CFA) and item factor analysis (IFA) to examine the dimensionality, factor-specific reliability, longitudinal measurement invariance, and construct validity of the CompACT items in a longitudinal online sample of U.S. adults (N = 523). Converging evidence across CFA and IFA confirmatory latent variable measurement models provides support for the reduction of the 23-item CompACT to a 15-item short form with a more stable factor structure, acceptable reliability over large ranges of its three latent factors, and measurement equivalence of its items in assessing latent change over time. Results also support the construct validity of the CompACT-15 items based on its relations with theoretically relevant measures. Overall, the CompACT-15 appears to be a psychometrically sound instrument with the potential to contribute to research and intervention efforts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Use of Exploratory Factor Analysis to Assess the Fitness Performance of Youth Football Players.

Perroni, F, Castagna, C, Amatori, S, Gobbi, E, Vetrano, M, Visco, V, Guidetti, L, Baldari, C, Luigi Rocchi, MB, and Sisti, D. Use of exploratory factor analysis to assess the fitness performance of youth football players. J Strength Cond Res 37(7): e430-e437, 2023-Football performance involves several physical abilities that range in aerobic, anaerobic, and neuromuscular domains; however, little is known about their interplay in profiling individual physical attributes. This study aimed to profile physical performance in youth football players according to their training status. One hundred seven young male soccer players (age 13.5 ± 1.4 years; height 168 ± 7 cm; body mass 57.4 ± 9.6 kg; and body mass index 20.2 ± 2.1 kg·m -2 ) volunteered for this study. Players' physical performance was assessed with football-relevant field tests for sprinting (10 m sprint), vertical jump (countermovement jump), intermittent high-intensity endurance (Yo-Yo Intermittent Recovery Test Level 1, YYIRT1), and repeated sprint ability (RSA). The training status was assumed as testosterone and cortisol saliva concentrations; biological maturation was estimated using the Pubertal Development Scale. Exploratory factor analysis (EFA) revealed 3 main variables depicting anthropometric (D1, 24.9%), physical performance (D2, 18.8%), and training status (D3, 13.3%), accounting for 57.0% of total variance altogether. The level of significance was set at p ≤ 0.05. The RSA and YYIRT1 performances were largely associated with D2, suggesting the relevance of endurance in youth football. This study revealed that for youth football players, a 3-component model should be considered to evaluate youth soccer players. The EFA approach may help to disclose interindividual differences useful to talent identification and selection.

Grandparents' Professional and Educational Activity: A Positive or Negative Impact on Relationships with Grandchildren?

'Baby boomers' are the first generation whose representatives-both male and female-are, to a great extent, or plan to be, professionally active in their old age. Increased professional activity of this group influences family relations and the perception of the roles of grandmothers and grandfathers. This article attempts to assess the impact of grandparents' professional and educational activity on relationships with grandchildren. The study relies on data from an international comparative survey conducted using the CAWI method in representative groups of Internet users from seven European countries and a proprietary questionnaire. The study was conducted in May 2022, and the total research sample included 3008 people. The analysis covered answers to the questions on the perceived impact of grandparents' activity on the performance of family roles. To analyze the results, tests of the equality of means (t-test, ANOVA) were used to check for differences in assessments due to respondents' characteristics. The use of exploratory factor analysis made it possible to distinguish two groups of factors-those having a positive impact on the relationship with grandchildren and those having a negative one. The SEM (structural equation modeling) model was used to find an answer to the question of which factor-positive or negative-has a greater impact on trust in grandparents as carers. The results of the conducted analyses indicated the existence of statistically significant differences in the perception of the role of grandmothers and grandfathers due to such characteristics of the respondents as age, gender, or country of residence. It is possible to conclude that positive perceptions of grandparents' professional and educational activity encourage greater confidence in them in the context of performing family roles.

The Concept and the measurement of Strategic Leadership. The case of Greek Hotel Employees with the use of Exploratory Factor Analysis

Over the past two decades, scholars and practitioners are interested in the term of Strategic Leadership. Strategic Leadership is a leader’s ability to anticipate, envision, being flexible, and enable others to make strategic changes as required. There are several researches connecting strategic leadership with various variables of the Human Resource Management (HRM), such as: work stress, (Baysak and Yener, 2015), work commitment (Chiang & Wang, 2012) and role conflict (Palomino & Frezatti, 2016). Hence, it is very important to develop a reliable measurement tool which will explore the nature of strategic leadership and map its dimensions. Barbara Davies & Brent Davies (2004) have already developed a model which consists of both the organizational abilities and the individual characteristics of strategic leaders. The main purpose of the current paper is to study the application of Davies & Davies model (2004) in the hospitality industry. More thoroughly, the empirical data used on this paper has derived by a research consisted of 372 participants who work on Greek Hotel Companies. The method used to analyze the connections between the items of the strategic leadership was factor analysis. The findings support that Davies & Davies model (2004) can be used as a measurement tool in the hospitality industry. Thus, the current paper aims to contribute to the comprehension of the nature of strategic leadership on the hospitality and tourism industry, and trigger future empirical research in the field.

Modeling Impacts of COVID-19 in Supply Chain Activities: A Grey-DEMATEL Approach

The purpose of this study was to identify and exhibit the interrelationships among COVID-19’s impacts on supply chain activities. Based on a literature review and the manager’s input, twenty COVID-19 impacts were collected. An integrated approach of exploratory factor analysis (EFA) and grey-decision-making trial and evaluation laboratory (G-DEMATEL) was used to reveal the causal interrelationships among the COVID-19 impacts. Initially, a questionnaire survey was administered among 220 respondents for EFA. Based on the outcome of EFA, the twenty COVID-19 impacts were categorized into seven critical areas. Then, based on the experts’ inputs, G-DEMATEL was utilized to reveal the causal interrelationships among various COVID-19 impacts. The results indicate that disruption management, relationship management, and production management are the top three critical areas that need to be addressed in the COVID-19 crisis. Disruption in supply, ripple effect on supply chain operations, and obsolescence of machines were found to be the most influential impacts while disproportionateness between supply and demand, difficulty in demand forecasting, and reduced cash inflow were found to be the most influenced impacts. This study’s outcomes will help policymakers and supply chain managers develop strategies to restructure supply chain networks. This study is an original contribution to the analysis of COVID-19 impacts in the supply chain activities in India due to the use of EFA and G-DEMATEL. This study considers India only, and hence, the outcomes lack generalizability. A study considering multiple developing countries could generalize these findings.

Development and Initial Validation of the Confidence and Motivation to Teach Primary Physical Education Questionnaire

This research describes the development and psychometric evaluation of the Confidence and Motivation to Teach Primary Physical Education Questionnaire (CMTPPEQ). Phase 1 involved questionnaire development and quantitative analysis of reliability and use of exploratory factor analysis (EFA) to examine factor structure and validity with 161 pre-service teachers. The EFA revealed two confidence factors and five motivation factors. All factors displayed adequate internal consistency and acceptable test-retest reliability for the confidence factors and three motivation factors. In Phase 2, the measure was further evaluated and factor structure refined using confirmatory factor analysis (CFA), with 211 pre-service and 107 in-service teachers. The two-factor confidence structure of Management and Planning and Implementation was confirmed with acceptable levels of fit. Structural changes made to the motivation structure resulted in six factors: Knowledge, Practice, Introjected Performance, Professional Expectations, Student Outcomes, and Disengagement. All factors demonstrated adequate internal consistency.

Structural validity of the Eating Disorder Examination-Questionnaire: A systematic review.

ObjectiveThe main aim was to perform a systematic literature review of studies investigating the factor structure of the Eating Disorder Examination‐Questionnaire (EDE‐Q), a widely used measure of eating pathology. Secondary aims were to summarize the quality of reporting of latent variable (factor) analyses in these studies and review support for different factor solutions.MethodLiterature was identified through Scopus, Medline, PsycInfo, and ProQuest databases published up to February 23, 2022 and outreach via an international listserv. All studies published in English reporting factor analysis of the EDE‐Q were included with few restrictions. Sixty studies including 63,389 participants met inclusion criteria.ResultsThe originally proposed four‐factor solution received little empirical support, although few alternative models have been robustly evaluated. Items assessing shape and weight concerns frequently coalesce in factor solutions, suggesting that these constructs are closely related. Investigations of brief versions of the EDE‐Q have produced more consistent findings, suggesting that these measures, particularly a seven‐item version, might be useful alternatives to the full version. Quality of studies was reasonable, with important methodological elements of factor analysis often reported.DiscussionThe findings are of relevance to practitioners and researchers, suggesting that the “original” factor structure of the EDE‐Q should be reconsidered and that use of a seven‐item version is to be encouraged.Public SignificanceSelf‐report questionnaires are widely used in the assessment of disordered eating. The current study found that there is little consensus about the structure of a common measure of eating psychopathology. There is more consistent support for a brief, seven‐item, version assessing dietary restraint, body dissatisfaction, and overvaluation of weight and shape.

Digital Intellectual Dynamics: A Perspective on Performance at a Brazilian E-Commerce Firm

Using the intellectual capital and dynamic capability literature as known dimensions of organizational performance in digital contexts, this article develops a new testable model that attempts to explain digital intellectual dynamics’ (DID) impact on a Brazilian e-commerce firm’s performance. Using a quantitative methodological approach, an inedited instrument of research is used to gather data from 77 managers, and, through exploratory factor analysis (EFA), a replicability analysis (generalized H (G-H) index) is conducted along with quality and effectiveness assessment through factor score validation in Factor 10 software. Structure Equation Modelling (SEM) is used to test the hypotheses. The results reveal that DID, as a second-order variable, and Digital Human Dynamics and Digital Social Dynamics, as first-order variables, are positively related to firm performance. Digital Structure Dynamics, another first-order variable, has a positive effect on firm performance but not at a statistically significant level. This empirical result brings visibility to the role of DID in firms’ performance, creating a strategic perspective for a firm’s management in digital contexts. Furthermore, digital information systems (DIS) researchers may view these results as a response to digital disruption and a reinvention of core functions in a new strategic approach to support e-commerce transactions and firm performance. On a methodological level, the use of EFA introduces new indexes to measure this innovative instrument, as it is the first time it is used in social science research. Practitioners may use these results to enhance their firm’s performance through DID.

Use of exploratory factor analysis for sustainability determination of fruit tree production: A case study in Hau Giang province, Vietnam

Investigation of morphological, phytochemical, and enzymatic characteristics of Anethum graveolens L. using selenium in combination with humic acid and fulvic acidParviz Samavatipour, Vahid Abdossi, Reza Salehi, Saeed Samavat,Alireza Ladan Moghadam

Identification of factors for assessing credit rating of non-financial companies

Goal: an improvement of the quality and accuracy of credit rating estimation, to add non-financial companies’ characteristics to the assessment, and to compare the importance of factors for different industries and countries. Methodology: the use of exploratory factor analysis and ordered logistic regression models. The study is based on publicly available data on non-financial companies from different industries and countries for the period from 2007 to 2021. Findings: a group of financial variables is the most significant in credit risk assessment for companies from developed countries, for emerging markets, macroeconomic variables mostly determine credit ratings instead. The nonfinancial variables have diverse effects, but as a group increase the accuracy of the credit rating assessment. Originality and contribution of the authors: there is limited research on the topic of credit rating assessment of non-financial companies with the inclusion of non-financial factors. In addition, the presented research contributes to the search for new relevant indicators that can be introduced instead of the qualitative variables used by international rating agencies and requiring expert assessment.

Communities and Cliques in Functional Brain Network Using Multiscale Consensus Approach.

The modular organization of the functional brain connectome implies its functional segregation. Correlation matrices extracted from fMRI data are used as adjacency matrices of the connectome, i.e., the functional connectivity network (FCN). The modular organization of FCN is widely solved using node-community detection methods, albeit with a requirement of edge filtering, mostly. However, network sparsification potentially leads to the loss of correlation information. With no ideal threshold values for edge filtering in literature, there is growing interest in finding communities in the complete weighted network. To address this requirement, we propose the use of exploratory factor analysis (EFA), thus, exploiting the semantics of the correlation matrix. In our recent work on using EFA for FCN analysis, we have proposed a novel consensus-based algorithm using a multiscale approach, where the number of factors nF is treated as the scale. The consensus procedure is employed for transforming the network before performing community detection. Here, we propose a novel extension to our multiscale EFA for finding relevant cliques. We use an ensemble of experiments and extensive quantitative analysis of its outcomes to identify the optimal set of scales for efficient node-partitioning. We perform case studies of datasets of FCN of the human brain at resting state, with different sizes and parcellation atlases (AAL, Schaefer). Our results of consensus communities and cliques correspond to relevant brain activity in its resting state, thus showing the effectiveness of consensus-based multiscale EFA.

A Meta-Theoretical Approach into the Determinants of Internal Psychological Resources for Entrepreneurs

This study, which was conducted in the context of a Small Island Developing state economy, adopts exploratory, meta-theoretical, and inter-disciplinary stances to examine determinants of internal psychological resources for entrepreneurs. It contributes to existing literature and methodology through its innovative interdisciplinary theoretical framework and the use of Exploratory Factor Analysis (EFA) in the field of entrepreneurship. Questionnaires were randomly distributed among 711 entrepreneurs, of which 539 were deemed useful for analytical purposes. EFA was used to identify factors that determine fundamental internal psychological resources for entrepreneurs. The Kaiser-Meyer Olkin coefficient of 0.85 justified the sample size for the use of EFA. The highly significant Barlett’s test (p<0.0001) showed the presence of adequately correlated items to form clusters. A coefficient of 0.00033 on the inverse of correlation matrix ruled out the possibility of multicollinearity issues among the six key EFA constructs of internal psychological resources for entrepreneurs. Inner Strength which originates from the field of medicine is surprisingly revealed as the leading internal psychological resource valued by entrepreneurs, followed by Entrepreneurial Aspirations, Entrepreneurial Alertness, Entrepreneurial Orientation, Self-leadership, and Risk Orientation. Two other concepts (Psychological capital and Sense of Coherence) which were initially included in the theoretical framework were eliminated during the EFA because the Scree plot did not support their retention and contributed to multicollinearity issues. This study has several practical and policy implications which will enable governments and entrepreneurs to contribute more effectively and more accurately to the entrepreneurial process.

Development and Validation of a Chinese Version of a School-to-Work Transition Anxiety Scale for Healthcare Students.

Objective: The aim of this paper was to develop an appropriate scale measuring healthcare students’ anxiety during the transition from school to work. Methods: After an extensive literature review and panel discussion to prove the face validity and content validity, the initial item pool was reduced to 52 items. In a pilot study, a sample of four hundred and twenty-four healthcare students participated, and exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used. Psychometric properties—construct validity, convergent validity, discriminant validity, goodness of fit, and reliabilities—were also analyzed. Results: After the use of EFA, the 52 items were reduced to 31 items in four factors, with 66.70% of the total variance explained. The Cronbach’s alpha values ranged between 0.91 and 0.93. The study also used CFA to validate the EFA model, and the results demonstrated that with the same thirty-one items in a 7-point Likert scale, the model was a better fit in four factors: “inexperience in professional knowledge and skills” (nine items; factor loadings: 0.642–0.867; 43.72% of the variance explained), “fear of death” (eight items; factor loadings: 0.745–0.831; 9.94% of the variance explained), “fear of being infected” (eight items; factor loadings: 0.678–0.866; 7.86% of the variance explained), and “interpersonal interactions” (six items; factor loadings: 0.704–0.913; 5.18% of the variance explained). The CFA model demonstrated a good model fit in the χ2/df ratio (1.17; p = 0.016), CFI (0.99), TFI (0.99), and RMSEA (0.02). The composite reliabilities ranged from 0.89 to 0.92, confirming the StWTA-HS scale’s stability and internal consistency. The convergent validity and discriminant validity were also confirmed. The StWTA-HS scale has been proven to be a stable scale to measure healthcare students’ school-to-work transition anxiety.

Rural revitalization: sustainable strategy for the development of cultural landscape of traditional villages through optimized IPA approach

PurposeThe main purpose of this study is to provide a decision-making basis for the development of a sustainability strategy by importance-performance analysis (IPA) methods. However, traditional and modified IPA methods do not accurately reveal the impact of the various dimensions of sustainable development (SD) on cultural landscape (CL). Based on the structural equation model (SEM), four main dimensions of SD were identified from the available data. This paper conducted an optimized IPA by building three SEMs based on importance, performance and the importance of four dimensions.Design/methodology/approachThis paper proposes the use of exploratory factor analysis (EFA) and SEM to develop the CL characteristic index evaluation model to determine the load of each indicator of importance and performance, and the SD-based measurement model to further determine the weight of the sustainability of each indicator in importance and performance. Afterwards, proposed sustainable strategies to the corresponding index were obtained.FindingsThis study offers useful insights into the actual operation and theoretical aspects of the IPA method.Practical implicationsThis study offers useful insights into the actual operation and theoretical aspects of the IPA method. This can solve the incongruous and uncertainty problem in the sustainable planning strategy, and the case study proves the feasibility of the IPA method combined with the influence of the structural equation.Social implicationsThe research is conducive to acceptance by local people with regard to their preferences in the perspective of sustainable development. It provides a basis for the future use of the IPA method in a comprehensive way based on an administrative angle.Originality/valueThe case study proves the feasibility of the IPA method combined with the influence of the structural equation. This provides a basis for the future use of the IPA method in a comprehensive way based on an administrative angle.

Biomarkers of Kidney Tubule Health, CKD Progression, and Acute Kidney Injury in SPRINT (Systolic Blood Pressure Intervention Trial) Participants

The Systolic Blood Pressure Intervention Trial (SPRINT) compared the effect of intensive versus standard systolic blood pressure targets on cardiovascular morbidity and mortality. In this ancillary study, we evaluated the use of exploratory factor analysis (EFA) to combine biomarkers of kidney tubule health in urine and plasma and then study their role in longitudinal estimated glomerular filtration rate (eGFR) change and risk of acute kidney injury (AKI). Observational cohort nested in a clinical trial. 2,351 SPRINT participants with eGFR< 60 mL/min/1.73 m2 at baseline. Levels of neutrophil gelatinase-associated lipocalin (NGAL), interleukin 18 (IL-18), chitinase-3-like protein (YKL-40), kidney injury molecule 1 (KIM-1), monocyte chemoattractant protein 1 (MCP-1), α1-microglobulin (A1M) and β2-microglobulin (B2M), uromodulin (UMOD), fibroblast growth factor 23 (FGF-23), and intact parathyroid hormone (PTH). Longitudinal changes in eGFR and risk of AKI. We performed EFA to capture different tubule pathophysiologic processes. We used linear mixed effects models toevaluate the association of each factor with longitudinal changes in eGFR. We evaluated the association of the tubular factors scores with AKI using Cox proportional hazards regression. From 10 biomarkers, EFA generated 4 factors reflecting tubule injury/repair (NGAL, IL-18, and YKL-40), tubule injury/fibrosis (KIM-1 and MCP-1), tubule reabsorption (A1M and B2M), and tubule reserve/mineral metabolism (UMOD, FGF-23, and PTH). Each 1-SD higher tubule reserve/mineral metabolism factor score was associated with a 0.58% (95% CI, 0.39%-0.67%) faster eGFR decline independent of baseline eGFR and albuminuria. Both the tubule injury/repair and tubule injury/fibrosis factors were independently associated with future risk of AKI (per 1 SD higher, HRs of 1.18 [95% CI, 1.10-1.37] and 1.23 [95% CI, 1.02-1.48], respectively). The factors require validation in other settings. EFA allows parsimonious subgrouping of biomarkers into factors that are differentially associated with progressive eGFR decline and AKI. These subgroups may provide insights into the pathological processes driving adverse kidney outcomes.