Confirmatory factor analysis of the Pittsburgh Sleep Quality Index in women with hot flashes

Abstract

Objective Women report poor sleep quality during various stages of the menopause transition and post-menopause, especially those with hot flashes. Sleep measurements vary widely due to the copious instruments available. The Pittsburgh Sleep Quality Index (PSQI) is a frequently used questionnaire that produces a single score for sleep quality. This one-factor structure has not received consistent support in the literature. The goal of this analysis was to determine the best factor structure of the PSQI in women with hot flashes. Methods A confirmatory factor analysis was conducted on the PSQI baseline data from three randomized controlled clinical trials enrolling peri- and postmenopausal women with hot flashes (N=849) from the Menopause Strategies: Finding Lasting Answers for Symptoms and Health (MsFLASH) network. Several a priori factor models were compared. Results One- and two-factor models did not fit the data. A three-factor model comprising Sleep Efficiency, Perceived Sleep Quality, and Daily Disturbance showed good fit; however, the sleep medication item was dropped due to poor fit and low rates of sleep medication use. The three-factor model was examined in African American (AA) and Caucasian subsamples and found to be similar in both groups; however, two items showed small group differences in strength as indicators. Conclusions Sleep quality in midlife women with hot flashes, as measured by the PSQI, appears to comprise three correlated factors. Minor measurement differences detected between groups are of research interest, but do not necessitate different scoring practices. Additional research is needed to further define sleep quality and its associations with health-related outcomes.

Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review

“…The factor analysis of the PSQI has been reported on diverse samples including university/college students in Nigeria, India, Chili, Chinese, Ethiopia, Peru and Thailand, pregnant women, community dwelling adults and older adults in America, Australia, China, Ethiopia, Spain, Portugal, Iranian health professionals, adolescents and young adults [ 15 – 17 , 23 , 24 , 26 – 28 , 31 , 34 , 36 , 39 , 41 , 44 , 45 , 52 , 53 , 57 – 60 ]. Moreover, it has been reported for patient population with breast cancer, Crohn’s disease, depression, diabetes, women with hot flashes, Taiwanese insomniacs, post-traumatic stress disorder, Trauma exposed veterans, temporo-mandibular disorder, traumatic brain injury, fibromyalgia, arthritis, chronic fatigue syndrome, psychiatric disorders and renal transplant patients [ 25 , 27 , 29 , 30 , 32 , 33 , 35 , 37 , 38 , 40 , 42 , 43 , 46 , 49 , 51 , 61 – 65 ].…”

“…We counted the number of studies reporting any of the following 5 indices: Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy, Bartlett’s sphericity test, determinant score, anti-image, and component correlations (Table 1 ). Eighteen studies reported both the KMO and Bartlett’s sphericity test [ 15 – 17 , 25 , 39 , 43 – 45 , 51 – 53 , 57 – 59 , 61 , 64 , 65 , 67 ], reported inter-item correlations [ 16 , 22 , 24 , 25 , 27 , 29 , 30 , 32 – 34 , 36 , 37 , 41 , 42 , 45 , 46 , 50 , 53 , 57 , 64 – 67 ], and 11 studies did not report any index [ 23 , 26 , 28 , 31 , 35 , 38 , 40 , 49 , 60 , 62 , 63 ].…”

“…Eleven studies did not use CFA [ 25 , 27 , 28 , 30 , 31 , 39 , 43 , 57 , 61 , 65 , 67 ] (Table 3 ). Several different software programs were used for CFA: 6 studies used Mplus [ 26 , 29 , 34 – 36 , 42 ], 12 used SPSS with Amos [ 15 – 17 , 24 , 33 , 40 , 48 , 52 , 53 , 57 , 60 , 65 ], 4 used STATA [ 44 , 46 , 49 , 64 ] and 2 each used LISREL [ 32 , 37 ], and SAS [45 [ 58 ]], 1 each used FactoMineR [ 41 ], EQS [ 38 ], and SEM [ 23 ]. Five studies did not report which software program was used [ 22 , 50 , 51 , 59 , 66 ].…”

“…Thirteen studies did not report the method of extraction [ 23 , 24 , 29 , 34 , 40 , 41 , 49 – 53 , 60 , 63 ]. Nine studies used weighted least squares methods [ 26 , 32 , 35 , 37 , 45 , 46 , 48 , 58 , 66 ], 8 employed MLE [ 15 , 16 , 33 , 36 , 38 , 44 , 59 , 62 ], 2 used MLE with bootstrapping for smoothing multivariate non-normality [ 17 , 22 ], and 1 used robust MLE [ 42 ] (Table 3 ). Most of the studies did not use a modification index [ 17 , 24 , 26 , 33 – 35 , 37 , 38 , 40 , 41 , 44 – 46 ].…”

Validity, cut-points, and minimally important differences for two hot flash-related daily interference scales

“…23 Studies have documented one, two, and three factor structures for the PSQI, with a three factor model best representing sleep in midlife women with hot flashes. 24 The scale has demonstrated sensitivity to detect changes in sleep during treatment for primary insomnia 25 and sleep problems concurrent with vasomotor symptoms. 5 …”