Browsing by Subject "Factor analysis"
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Item Bifactor Structure of the Schizotypal Personality Questionnaire Across the Schizotypy Spectrum(Guilford Press, 2021-08) Moussa-Tooks, Alexandra B.; Bailey, Allen J.; Bolbecker, Amanda R.; Viken, Richard J.; O’Donnell, Brian F.; Hetrick, William P.; Psychiatry, School of MedicineDespite widespread use in schizophrenia-spectrum research, uncertainty remains around an empirically supported and theoretically meaningful factor structure of the Schizotypal Personality Questionnaire (SPQ). Current identified structures are limited by reliance on exclusively nonclinical samples. The current study compared factor structures of the SPQ in a sample of 335 nonpsychiatric individuals, 292 schizotypy-spectrum individuals (schizophrenia, schizoaffective disorder, or schizotypal personality disorder), and the combined group (N = 627). Unidimensional, correlated, and hierarchical models were assessed in addition to a bifactor model, wherein subscales load simultaneously onto a general factor and a specific factor. The best-fitting model across samples was a two-specific factor bifactor model, consistent with the nine symptom dimensions of schizotypy as primarily a direct manifestation of a unitary construct. Such findings, for the first time demonstrated in a clinical sample, have broad implications for transdiagnostic approaches, including reifying schizotypy as a construct underlying diverse manifestations of phenomenology across a wide range of severity.Item DEVELOPMENT AND VALIDATION OF THE ACCULTURATIVE STRESS SCALE FOR CHINESE COLLEGE STUDENTS IN THE UNITED STATES (ASSCS)(2012-12-21) Bai, Jieru; Adamek, Margaret E.; Pike, Cathy K.; Daley, James G.; Rand, Kevin L.; Chan, Cecilia L. W.Chinese students are the biggest ethnic group of international students in the United States. Previous studies have identified many unique problems of Chinese students during their acculturation process and a higher level of acculturative stress than international students from other countries. A systematic review of instruments that assess acculturative stress revealed that none of the existing scales apply to Chinese students in the United States, either because of language issues or validity problems. Thus, this study aims to develop a reliable and valid scale to accurately measure the acculturative stress of Chinese students in the United States. A 72-item pool was generated by interviewing eight Chinese students and borrowing items from existing literature and scales. The item pool was sent online to 607 Chinese students and 267 of them completed the survey. Exploratory Factor Analysis was conducted to empirically derive the factor structure of the Acculturative Stress Scale for Chinese Students (ASSCS). The results produced a 32-item scale in five dimensions, which were Language Insufficiency, Social Isolation, Perceived Discrimination, Academic Pressure, and Guilt toward Family. The ASSCS demonstrated high reliability (Cronbach’s alpha = 0.939) and initial validity by predicting depression (Beta = 0.490, p<.001) and life satisfaction (Beta = -0.505, p<.001). It was the first Chinese scale of acculturative stress developed and validated among a Chinese student sample in the United States. Further studies need to be conducted to provide empirical support and confirm the validity for the scale. In the future, the scale can be used as diagnosing tool and self-assessment tool.Item Dietary Patterns and Hypothyroidism in U.S. Adult Population(MDPI, 2024-01-28) Alkhatib, Dana; Shi, Zumin; Ganji, Vijay; Nutrition and Dietetics, School of Health and Human SciencesThe thyroid gland produces hormones that are essential for various body functions. Hypothyroidism is defined as insufficient thyroid hormone production. Several studies have found associations between specific micronutrients and overall thyroid function; however, the amount of evidence regarding the relationship between dietary patterns and hypothyroidism among the U.S. population is limited. Data from three cycles of National Health and Nutrition Examination Surveys (NHANES), 2007–2008, 2009–2010, and 2011–2012, were used (n = 8317). Subjects with serum thyroid stimulating hormone >4.5 mIU/L or on levothyroxine were considered to have hypothyroidism. Age, sex, race/ethnicity, body mass index, and several lifestyle factors were considered as covariates. Three patterns were extracted using factor analysis. These were labeled as fat–processed grains–sugars–meats (FPSM), oils–nuts–potatoes–low-fat meats (ONPL), and fruits–whole grains–vegetables–dairy (FWVD) patterns. In a weighted multiple logistic regression, FPSM and ONPL were inversely associated with hypothyroidism (OR, 0.75; 95% CI, 0.57–1; p = 0.049 and OR, 0.81; 95% CI, 0.67–0.97; p = 0.025, respectively). However, FWVD demonstrated no association with hypothyroidism (p = 0.63). In conclusion, FPSM and ONPL patterns but not FWVD patterns were associated with hypothyroidism in U.S. adults. Nutrient deficiencies and their interactions may be linked to hypothyroidism.Item Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors(Oxford University Press, 2024) Zhang, Qiyiwen; Chang, Changgee; Shen, Li; Long, Qi; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthThere has been an increasing interest in decomposing high-dimensional multi-omics data into a product of low-rank and sparse matrices for the purpose of dimension reduction and feature engineering. Bayesian factor models achieve such low-dimensional representation of the original data through different sparsity-inducing priors. However, few of these models can efficiently incorporate the information encoded by the biological graphs, which has been already proven to be useful in many analysis tasks. In this work, we propose a Bayesian factor model with novel hierarchical priors, which incorporate the biological graph knowledge as a tool of identifying a group of genes functioning collaboratively. The proposed model therefore enables sparsity within networks by allowing each factor loading to be shrunk adaptively and by considering additional layers to relate individual shrinkage parameters to the underlying graph information, both of which yield a more accurate structure recovery of factor loadings. Further, this new priors overcome the phase transition phenomenon, in contrast to existing graph-incorporated approaches, so that it is robust to noisy edges that are inconsistent with the actual sparsity structure of the factor loadings. Finally, our model can handle both continuous and discrete data types. The proposed method is shown to outperform several existing factor analysis methods through simulation experiments and real data analyses.Item Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup(Wiley, 2021) Faria, Andreia V.; Zhao, Yi; Ye, Chenfei; Hsu, Johnny; Yang, Kun; Cifuentes, Elizabeth; Wang, Lei; Mori, Susumu; Miller, Michael; Caffo, Brian; Sawa, Akira; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthMulti-institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure-based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI-rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure-based analysis showed widespread DTI abnormalities in FEP and rs-fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof-of-concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub-groups.Item Posttraumatic stress disorder and chronic musculoskeletal pain : how are they related?(2014-07-11) Peng, Xiaomei; Bair, Matthew J.; Kroenke, Kurt; Faries, Douglas E.; Mac Kinnon, JoyceSymptoms of post-traumatic stress disorder (PTSD) are a common comorbidity in veterans seeking treatment of chronic musculoskeletal pain (CMP). However, little is known regarding the mutual influence of PTSD and CMP in this population. Using cross-sectional and longitudinal data from a randomized clinical trial evaluating a stepped care intervention for CMP in Iraq/Afghanistan veterans (ESCAPE), this dissertation examined the relationships between PTSD and CMP along with other factors including depression, anxiety, catastrophizing and health-related quality of life. The Classification and Regression Tree (CART) analysis was conducted to identify key factors associated with baseline PTSD besides CMP severity. A series of statistical analyses including logistical regression analysis, mixed model repeated measure analysis, confirmatory factor analysis and cross-lagged panel analysis via structural equation modeling were conducted to test five competing models of PTSD symptom clusters, and to examine the mutual influences of PTSD symptom clusters and CMP outcomes. Results showed baseline pain intensity and pain disability predicted PTSD at 9 months. And baseline PTSD predicted improvement of pain disability at 9 months. Moreover, direct relationships were found between PTSD and the disability component of CMP, and indirect relationships were found between PTSD, CMP and CMP components (intensity and disability) mediated by depression, anxiety and pain catastrophizing. Finally, the coexistence of PTSD and more severe pain was associated with worse SF-36 Physical Component Summary (PCS) and Mental Component Summary (MCS) scores. Together these findings provided empirical support for the mutual maintenance theory.Item Preliminary Validation of the Injustice Experience Questionnaire in Patients with Advanced Cancer(Elsevier, 2023) Secinti, Ekin; Snyder, Stella; Wu, Wei; Mosher, Catherine E.; Psychology, School of ScienceContext: When diagnosed with advanced cancer, patients may perceive their situation as an injustice. The Injustice Experience Questionnaire (IEQ) is a 12-item measure of perceived unfairness originally developed for patients with chronic pain. The factor structure, reliability, and validity of the IEQ in patients with cancer have not been assessed. Objectives: To examine the factor structure, internal consistency, and construct validity of the IEQ in patients with advanced cancer. Methods: Patients with advanced lung or prostate cancer (N = 201) were recruited from academic and public clinics in Indianapolis, IN. Patients completed the 12-item IEQ and other measures of psychological processes and distress. IEQ instructions were modified to focus on cancer-related perceived injustice. Confirmatory factor analysis (CFA) was used to examine the dimensionality of the measure. Internal consistency reliability and construct validity were examined. Results: CFA showed that the original IEQ's 2-factor structure had an adequate fit (RMSEA = 0.07, CFI = 0.96, SRMR = 0.05). The factors included Severity/irreparability and Blame/unfairness. Internal consistency was excellent (α = 0.92, ω = 0.94). The IEQ showed significant positive associations with physical and psychological symptoms (rs = 0.20 - 0.65, Ps < 0.05). The IEQ also showed significant negative associations with quality of life and acceptance of cancer (rs=-0.51 - -0.46, Ps < 0.05). Conclusion: Findings provide preliminary support for using the IEQ in patients with advanced cancer. Future research should assess the sensitivity of the IEQ to change in an interventional context.Item Using Second-Order Factor Analysis in Examining Multiple Problems of Clients(Research on Social Work Practice is available online at [LINK]http://rsw.sagepub.com/[/LINK].[BREAK]Copyright © 1998 Sage Publications, Inc.[BREAK]The original doi for the article is 10.1177/104973159800800204. To access the doi, open the following DOI site in your browser and cut and paste the doi name where indicated: [LINK] http://dx.doi.org [/LINK]. [BREAK] Access to the original article may require subscription and authorized logon ID/password. IUPUI faculty/staff/students please check University Library resources before purchasing an article. Questions on finding the original article via our databases? Ask a librarian: [LINK] http://www.ulib.iupui.edu/research/askalibrarian[/LINK]., 1998-03) Pike, Cathy King; Hudson, Walter W.; Murphy, Douglas L.; Rathbone-McCuan, EloiseData from veterans of the Persian Gulf engagement were studied to assess the potential of second-order factor analysis in examining, interpreting, and directing person-environment interventions with an array of different but related individual and environmental problems. Participants of the study were 1,532 veterans of the Persian Gulf engagement who were eligible for social services provided by the Veterans Administration. The results provided support for the use of second-order factors in examining client data and provided information about the relationships among clinically significant problems. Further research on the second-order factors of multidimensional instruments that are used in social work to measure client progress can yield information about how client populations differ and provide direction in selecting interventions that are congruent with social work's person-environment focus.