Tag: factor analysis

Predictors of impaired functioning among long COVID patients

Abstract:

Background: There is limited information on what acute factors predict more long-term symptoms from COVID-19.

Objective: Our objective was to conduct an exploratory factor analysis of self-reported symptoms at two time points of Long COVID-19.

Methods: Data from patients with Long COVID-19 were collected at the initial two weeks of contracting SARS CoV-2 and the most recent two weeks, with a mean duration of 21.7 weeks between the two-time points. At time point 2, participants also complete the Coronavirus Impact Scale (CIS), measuring how the COVID-19 pandemic affected various dimensions of their lives (e.g., routine, access to medical care, social/family support, etc.).

Results: At time 1, a three-factor model emerged consisting of Cognitive Dysfunction, Autonomic Dysfunction and Gastrointestinal Dysfunction. The analysis of time 2 resulted in a three-factor model consisting of cognitive dysfunction, autonomic dysfunction, and post-exertional malaise. Using factor scores from time 1, the Autonomic Dysfunction and the Gastrointestinal Dysfunction factor scores significantly predicted the CIS summary score at time two. In addition, the same two factor scores at time 1 predicted the occurrence of myalgic encephalomyelitis/chronic fatigue syndrome at time 2.

Conclusion: As Cognitive and Autonomic Dysfunction emerged as factors for both time points, suggesting health care workers might want to pay particular attention to these factors that might be related to later symptoms and difficulties with returning to pre-illness family life and work functioning.

Source: Jason LA, Dorri JA. Predictors of impaired functioning among long COVID patients. Work. 2023 Mar 8. doi: 10.3233/WOR-220428. Epub ahead of print. PMID: 36911958. https://content.iospress.com/articles/work/wor220428 (Full text)

Confirmatory factor analysis of a myalgic encephalomyelitis and chronic fatigue syndrome stigma scale

Abstract:

This study adapted a chronic illness stigma scale and explored its psychometric properties. The main purposes were to confirm the factor structure of the instrument with this population and address the previous factor intercorrelation discrepancies. Five hundred and fifty-four individuals with myalgic encephalomyelitis or chronic fatigue syndrome completed the adapted stigma scale.

Results document the stigma experienced by an international sample of individuals with myalgic encephalomyelitis and chronic fatigue syndrome. Factors demonstrated good internal consistency, and a model fit was found in a confirmatory factor analysis. Participants endorsed high levels of stigma, estrangement, and disclosure. Implications of these findings and future directions are discussed.

Source: Terman JM, Awsumb JM, Cotler J, Jason LA. Confirmatory factor analysis of a myalgic encephalomyelitis and chronic fatigue syndrome stigma scale. J Health Psychol. 2018 Sep 5:1359105318796906. doi: 10.1177/1359105318796906. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/30183363

Deconstructing post-exertional malaise: An exploratory factor analysis

Abstract:

Post-exertional malaise is a cardinal symptom of myalgic encephalomyelitis and chronic fatigue syndrome. There are two differing focuses when defining post-exertional malaise: a generalized, full-body fatigue and a muscle-specific fatigue. This study aimed to discern whether post-exertional malaise is a unified construct or whether it is composed of two smaller constructs, muscle fatigue and generalized fatigue. An exploratory factor analysis was conducted on several symptoms that assess post-exertional malaise. The results suggest that post-exertional malaise is composed of two empirically different experiences, one for generalized fatigue and one for muscle-specific fatigue.

© The Author(s) 2016.

 

Source: McManimen SL, Sunnquist ML, Jason LA. Deconstructing post-exertional malaise: An exploratory factor analysis. J Health Psychol. 2016 Aug 24. pii: 1359105316664139. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/27557649

 

Factor Analysis of the DePaul Symptom Questionnaire: Identifying Core Domains

Abstract:

The present study attempted to identify critical symptom domains of individuals with Myalgic Encephalomyelitis (ME) and chronic fatigue syndrome (CFS). Using patient and control samples collected in the United States, Great Britain, and Norway, exploratory factor analysis (EFA) was used to establish the underlying factor structure of ME and CFS symptoms.

The EFA suggested a four-factor solution: post-exertional malaise, cognitive dysfunction, sleep difficulties, and a combined factor consisting of neuroendocrine, autonomic, and immune dysfunction symptoms. The use of empirical methods could help better understand the fundamental symptom domains of this illness.

 

Source: Jason LA, Sunnquist M, Brown A, Furst J, Cid M, Farietta J, Kot B, Bloomer C, Nicholson L, Williams Y, Jantke R, Newton JL, Strand EB. Factor Analysis of the DePaul Symptom Questionnaire: Identifying Core Domains. J Neurol Neurobiol. 2015 Sep;1(4). doi: 10.16966/2379-7150.114. Epub 2015 Sep 17. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4830389/ (Full article)

 

Factor analysis of the Beck Depression Inventory-II with patients with chronic fatigue syndrome

Abstract:

This study examined the properties of the Beck Depression Inventory-II (BDI-II) in a sample of 111 patients with chronic fatigue syndrome (CFS). Exploratory factor analysis identified two factors. The mean score for the Somatic-Affective factor was significantly higher than the Cognitive factor. Convergent and discriminant validity were assessed for BDI-II total score, the two factor scores, and the BDI for Primary Care (BDI-PC). The BDI-PC and Cognitive factor demonstrated superior validity. Results suggest patients endorse BDI-II somatic items that overlap with CFS symptoms at a high rate. Factor scores should be evaluated separately, or the BDI-PC should be utilized with this population.

 

Source: Brown M, Kaplan C, Jason L. Factor analysis of the Beck Depression Inventory-II with patients with chronic fatigue syndrome. J Health Psychol. 2012 Sep;17(6):799-808. doi: 10.1177/1359105311424470. Epub 2011 Nov 21. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3655435/ (Full article)

 

Classifying medication use in clinical research

Abstract:

BACKGROUND: Medication use data are usually collected in clinical research. Yet no standardized method for categorizing these exists, either for sample description or for the study of medication use as a variable.

OBJECTIVE: The present investigation was designed to develop a simple, empirically based classification scheme for medication use categorization.

METHOD: The authors used factor analysis to reduce the number of possible medication groupings. This permitted a pattern of medication usage to emerge that appeared to characterize specific clinical constellations. To illustrate the technique’s potential, the authors applied this classification system to samples where sleep disorders are prominent: chronic fatigue syndrome and sleep apnea.

RESULTS: The authors’ classification approach resulted in 5 factors that appear to cohere in a logical fashion. These were labeled Cardiovascular or Metabolic Syndrome Medication, Symptom Relief Medication, Psychotropic Medication, Preventative Medication, and Hormonal Medication.

CONCLUSIONS: The findings show that medication profile varies according to clinical sample. The medication profile for participants with sleep apnea reflects known comorbid conditions; the medication profile associated with chronic fatigue syndrome appears to reflect the common perception of this condition as a psychogenic disorder.

 

Source: Rizzo D, Creti L, Bailes S, Baltzan M, Grad R, Amsel R, Fichten CS, Libman E. Classifying medication use in clinical research. J Prim Care Community Health. 2011 Jan 1;2(1):26-32. doi: 10.1177/2150131910385843. Epub 2010 Oct 27. https://www.ncbi.nlm.nih.gov/pubmed/23804659

 

Factor analysis of symptoms among subjects with unexplained chronic fatigue: what can we learn about chronic fatigue syndrome?

Abstract:

OBJECTIVE: Chronic fatigue syndrome (CFS) case definitions agree that fatigue must be unexplained, debilitating and present for at least 6 months, but they differ over accompanying symptoms. Our objective was to compare the 1994 CFS case-defining symptoms with those identified by factor analysis.

METHODS: We surveyed the Wichita population and measured the occurrence of 21 symptoms in 1391 chronically fatigued subjects who did not report fatigue-associated medical or psychiatric conditions. We used factor analyses to identify symptom dimensions of fatigue and cluster analysis to assign subjects to subgroups.

RESULTS: Forty-three subjects had CFS. We confirmed three factors: musculoskeletal, infection and cognition-mood-sleep, essentially defined by CFS symptoms. Although factor scores were higher among CFS subjects, CFS and non-CFS distributions overlapped substantially. Three clusters also showed overlap between CFS and non-CFS subjects.

CONCLUSION: CFS symptomatology is a multidimensional phenomenon overlapping with other unexplained fatiguing syndromes and this must be considered in CFS research.

 

Source: Nisenbaum R, Reyes M, Unger ER, Reeves WC. Factor analysis of symptoms among subjects with unexplained chronic fatigue: what can we learn about chronic fatigue syndrome? J Psychosom Res. 2004 Feb;56(2):171-8. http://www.ncbi.nlm.nih.gov/pubmed/15016574

 

A factor analysis of chronic fatigue symptoms in a community-based sample

Abstract:

BACKGROUND: This study examined characteristics of fatigue in individuals with chronic fatigue from a community-based study. Most studies of chronic fatigue have been based on patients recruited from primary or tertiary care settings. Samples such as these might not be representative of patients within the general population. The purpose of this study was to determine the factor structure of participants’ symptoms in a random community sample of individuals with chronic fatigue.

METHOD: A random sample of 18,675 respondents in Chicago received a brief telephone questionnaire designed to identify individuals with chronic fatigue. A group of 780 (4.2%) with chronic fatigue received further interview via telephone questionnaire involving characteristics of their fatigue. The analyses for this study were based on those people identified with having chronic fatigue. A factor analysis was conducted on responses to questionnaire items, and a four-factor solution emerged. Mean factor scores were derived and analyzed in relation to sociodemographic characteristics and sample subgroups.

RESULTS: The four factors were labeled: Lack of Energy, Physical Exertion, Cognitive Functioning, and Fatigue and Rest.

CONCLUSIONS: Results indicated that individuals with chronic fatigue have symptoms that can be differentiated into theoretically distinct factors.

 

Source: Jason LA, Taylor RR, Kennedy CL, Jordan K, Huang CF, Torres-Harding S, Song S, Johnson D. A factor analysis of chronic fatigue symptoms in a community-based sample.  Soc Psychiatry Psychiatr Epidemiol. 2002 Apr;37(4):183-9. http://www.ncbi.nlm.nih.gov/pubmed/12027245

 

Factor analysis of unexplained severe fatigue and interrelated symptoms: overlap with criteria for chronic fatigue syndrome

Abstract:

The objective of this study was to identify factors explaining the correlations among unexplained severe fatigue of different durations (1-5 months or > or =6 months) and symptoms reported as being significant health problems during a preceding 4-week period.

Between June and December of 1994, a cross-sectional, random digit dialing telephone survey was conducted among residents of San Francisco, California. All subjects who reported having severe fatigue lasting for > or =1 month and a random sample of nonfatigued subjects were asked to participate in a detailed telephone interview. Data from 1,510 individuals aged 18-60 years who did not have medical or psychiatric conditions that could explain their severe fatigue were analyzed.

Common factor analyses identified three correlated factors (defined as “fatigue-mood-cognition” symptoms, “flu-type” symptoms, and “visual impairment”) that explained the correlations among fatigue lasting for > or =6 months and 14 interrelated symptoms. No factor explained the correlations among fatigue lasting for 1-5 months and other symptoms.

The combination of fatigue of > or =6 months’ duration and selected symptoms overlaps with published criteria used to define cases of chronic fatigue syndrome (CFS). Although symptoms described in this study were reported as appearing within the preceding month, and CFS symptoms must have been present for the previous 6 months, these results provide empirical support for the interrelations among unexplained fatigue of > or =6 months’ duration and symptoms included in the CFS case definition.

 

Source: Nisenbaum R, Reyes M, Mawle AC, Reeves WC. Factor analysis of unexplained severe fatigue and interrelated symptoms: overlap with criteria for chronic fatigue syndrome. Am J Epidemiol. 1998 Jul 1;148(1):72-7. http://aje.oxfordjournals.org/content/148/1/72.long (Full article)