Validation of the three-factor model of the PSQI in a large sample of chronic fatigue syndrome (CFS) patients

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Abstract

Objective

To evaluate whether a 3-factor model of the Pittsburgh Sleep Quality Index (PSQI) scale would fit the constellation of sleep disturbances in patients with a diagnosis of chronic fatigue syndrome (CFS).

Methods

Consecutive CFS patients filled out the PSQI. Scores from this self-report questionnaire were examined with exploratory and confirmatory factor analysis (CFA).

Results

413 CFS patients were included for analysis in this study. CFA showed that the 7 PSQI component scores clustered into the 3 factors reported by Cole et al. (2006), i.e. Sleep Efficiency, Perceived Sleep Quality and Daily Disturbances. In contrast with the single-factor and all 2-factor models, all factor loadings were significant, and all goodness-of-fit values were acceptable.

Conclusion

In CFS, the PSQI operates as a 3-factor scoring model as initially seen in healthy and depressed older adults. The separation into 3 discrete factors suggests the limited usefulness of the global PSQI as a single factor for the assessment of subjective sleep quality, as also evidenced by a low Cronbach's alpha (0.64) in this patient sample.

Introduction

Chronic fatigue syndrome (CFS) is a disabling condition characterized by chronic fatigue of a new or definite onset that lasts for at least 6 months and that is not explained by medical or psychiatric causes [1]. Next to this major criterion, the 1994 case definition requires the co-occurrence of at least four out of eight minor criteria: unusual postexertional malaise, impaired memory or concentration, unrefreshing sleep, headaches, muscle pain, joint pain, sore throat and tender cervical nodes [1]. These 1994 CDC diagnostic criteria prevail as a standard in current clinical practice and scientific research.

Complaints of unrefreshing sleep and poor sleep quality are common in CFS patients. The Pittsburgh Sleep Quality Index (PSQI) is one of the most used and validated questionnaires to measure sleep quality and disturbances during the past month [2]. The self-report questions are divided into 7 clinically derived components of sleep difficulties: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications and daytime dysfunction. Individual component scores are summed to yield one global score or a single factor, with higher scores indicating poorer sleep quality. Psychometric properties of the PSQI have been examined and found to be appropriate in relation to internal consistency [2], [3], concurrent validity [3], [4] and discriminative validity [3], [4] in a range of clinical and healthy populations.

Using a cross-validation approach in healthy and depressed elderly US adults, Cole et al.[5] found that a single summed global score did not best capture the multidimensional nature of sleep disturbances. An exploratory factor analysis (EFA) followed by a confirmatory factor analysis (CFA) on the 7 quality components revealed that a 3-factor scoring model significantly better fitted than either the original single-factor or a 2-factor model. This model documents sleep disturbances in the separated factors Sleep Efficiency, Perceived Sleep Quality and Daily Disturbances.

Three other studies provided evidence that a multiple factor scoring method of the PSQI could be more appropriate to assess sleep problems compared to the originally proposed single- factor method. In a sample of Nigerian university students, a 3-factor model of the PSQI was identified performing EFA, however, the factors differed from Cole's findings [6]. EFA and subsequent CFA on the PSQI results deriving from a sample of Australian adults determined a 2- and 3-factor scoring model with slight differences in the optimal factor structures compared to the model of Cole et al. [7]. Conducting CFA, the original 3-factor model [5] was also found to better fit than a single-factor model in renal transplant recipients [8]. Although the fit indices noticed were not as good as those found by Cole et al. [5], an additional pathway significantly improved its fit [8].

Differences in sample characteristics may account for the different factor structures identified in various studies since sleep patterns, sleep quality and perception of sleep are influenced by a range of factors related to age, health and culture [9], [10], [11]. As a consequence, there is a need for further studies examining the factor structure of the PSQI.

The aim of this study was to evaluate whether the 3-factor model of the PSQI reported by Cole et al. [5] would fit the constellation of sleep disturbances in a large sample of patients with CFS.

Section snippets

Patient recruitment

Consecutive patients with a final diagnosis of CFS according to the Fukuda criteria in a multidisciplinary tertiary care referral center were included in this study [12]. The sample was approved by the Ethical Review Board of the Ghent University Hospital.

Questionnaire

All patients filled out the PSQI and scores were calculated according to the scoring guidelines provided by Buysse et al. [2].

Statistical analysis

To investigate the validity of the 3-factor model of the PSQI proposed by Cole et al. [5], CFA was performed using

Results

The study sample included 415 CFS patients (mean age 40.53 years, SD 7.91; 86% female) [12] from which 413 completely filled out all PSQI items, allowing analysis with the AMOS module.

Table 1 provides the descriptive statistics for the global PSQI, the 7 PSQI components and the Spearman's intercorrelations. Generally, high PSQI scores were found with a mean global score of 10.17 (SD 4.02, Cronbach's alpha 0.64). Poor sleep quality was observed in 86% of the patients using the recommended cut-off

Discussion

This is the first time that the PSQI factor structure was examined in a large sample of CFS patients. CFA demonstrated that the PSQI operated as a multiple factor scoring model in CFS, which is consistent with previous findings in different subject groups [5], [6], [7], [8]. Moreover, the 3-factor model proposed by Cole et al. [5] showed good fit criteria and the 7 PSQI component scores clustered into the factors Sleep Efficiency, Sleep Quality and Daily Disturbances. Therefore, the 3-factor

Conflict of interest

The authors state no conflict of interest and have received no payment in preparation of this manuscript.

Acknowledgments

We wish to acknowledge the role of Walter Michielsen, MD PhD, who has pioneered the rehabilitation program for CFS patients at the Department of General Internal Medicine, Infectious Diseases and Psychosomatic Medicine of the University Hospital Ghent, Belgium.

References (18)

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