Adaptation of the Pittsburgh Sleep Quality Index in Chinese adults with type 2 diabetes

Zhu, Bingqian; Xie, Meng; Park, Chang Gyu; Kapella, Mary C.

doi:10.1016/j.jcma.2017.06.021

Cited by 41 publications

(38 citation statements)

References 30 publications

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“…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 ].…”

Section: Resultsmentioning

confidence: 99%

“…Twenty articles did not report having carried out EFA [ 15 , 23 , 26 , 29 , 32 – 38 , 42 , 48 , 50 , 59 , 60 , 62 – 64 , 66 ]. The types of EFA tests used were principal component analysis (PCA) in 18 studies [ 17 , 22 , 24 , 25 , 27 , 28 , 31 , 39 , 41 , 43 – 45 , 49 , 51 , 57 , 58 , 65 , 67 , 68 ], maximum likelihood estimation (MLE) in 6 [ 16 , 17 , 22 , 24 , 40 , 41 , 53 ] and unreported in 2 [ 30 , 52 ] (Table 2 ).…”

Section: Resultsmentioning

confidence: 99%

“…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 ].…”

Section: Resultsmentioning

confidence: 99%

“…Eight studies found that a 3-factor model best explained the data [ 29 , 35 – 37 , 41 , 45 , 52 , 53 ], Thirteen reported a 2-factor model [ 22 , 24 , 26 , 32 , 34 , 38 , 40 , 50 – 52 , 58 , 60 ], and 9 reported a 1-factor model [ 15 – 17 , 42 , 46 , 48 , 49 , 59 , 64 ]. One study reported both 2-factor and 3-factor models, but in separate sample populations [ 44 ] (Table 3 ).…”

Section: Resultsmentioning

confidence: 99%

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Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review

Manzar

BaHammam

Hameed³

et al. 2018

Health Qual Life Outcomes

148

145

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BackgroundThe Pittsburgh Sleep Quality Index (PSQI) dimensionality is much debated, with the greatest number of reported factor structures. Therefore, this review appraised the methodologies of studies investigating the factor structure of the PSQI.Material and methodsMEDLINE, PsycInfo, AJOL, BASE, Cochrane Library, Directory of Open Access Journals (Lund University), CINAHL, and Embase were searched systematically to include articles published till 23rd March, 2018. The articles with the objective of factor analysis of the PSQI (20 articles) or with a major section on the same subject (25 articles) were included. There was no limitation about participant characteristics. Descriptive analysis of articles for measures of the suitability of the data for factor analysis, details of the exploratory factor analysis (EFA) and details of the confirmatory factor analysis (CFA) was performed.ResultsThe analysis used by the majority did not employ the simplest scheme for interpreting the observed data: the parsimony principle. Other shortcomings included under- or non-reporting of sample adequacy measures (11 out of 45 articles), non-use of EFA (20 out of 45 articles), use of EFA without relevant details, non-use of CFA (11 out of 45 articles), and use of CFA without relevant details. Overall, 31 out of 45 articles did not use either EFA or CFA.ConclusionWe conclude that the various PSQI factor structures for standard sleep assessment in research and clinical settings may need further validation.Trial registrationNot applicable because this was a review of existing literature.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review

Manzar

BaHammam

Hameed³

et al. 2018

Health Qual Life Outcomes

148

145

View full text Add to dashboard Cite

show abstract

“…The internal consistency Cronbach's α was 0.87. Comparably, in the study of Zhu, Xie, Park, and Kapella () who adapted the Chinese Version of PSQI in patients with type 2 diabetes, Cronbach's α was 0.78. Guo et al () evaluated the structural validity of the PSQI in Chinese undergraduate students and reported Cronbach's α of 0.91.…”

Section: Discussionmentioning

confidence: 88%

Evaluation of sleep quality in adolescent patients with osteosarcoma using Pittsburgh Sleep Quality Index

Tao

et al. 2019

Eur J Cancer Care

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The sleep quality of patients with osteosarcoma (OS) was poorly understood. We aimed to evaluate the prevalence of sleep dysfunction in adolescent patients with OS using the Pittsburgh Sleep Quality Index (PSQI) and to further investigate the psychometric properties of the PSQI in this cohort of patients. Fifty four adolescent patients with OS who underwent chemotherapy treatment in our clinic centre were included. Sleep quality was assessed with the Chinese PSQI. Cronbach's alpha was calculated to evaluate the internal consistency. The confirmatory factor analysis (CFA) was used to determine the fitness of a two‐factor structure. Sleep disturbance was observed in 57.4% (31/54) of the patients. Patients with the presence of metastasis or more than 2 cycles of chemotherapy were found to have remarkably higher median global score. The overall Cronbach's alpha was 0.87. The CFA showed an overall comparative fit index of 0.97, a root mean square error of approximation of 0.06 and a standardised root mean square residual of 0.07 respectively. PSQI was a reliable instrument to evaluate the sleep quality of adolescent patients with OS. Over half of the patients may experience sleep disturbance during the treatment. Early psychological interventions were recommended to improve the sleep quality of the patients.

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Parallel Mediating Effects of Sleep Quality, Psychological Distress, and Self‐Stigma in the Associations Between Long COVID Symptoms and Quality of Life Among Taiwanese Individuals With Mental Health Illness

Chang,

Ahorsu,

Tsai

et al. 2024

Brain and Behavior

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BackgroundLong COVID symptoms (i.e., experiencing symptoms of COVID‐19 for 3 months post‐COVID‐19) affect individuals’ health and their quality of life (QoL). However, the pathways through which it does so are not fully known.AimThe present study examined the mediating roles of sleep quality, psychological distress, and self‐stigma in the associations between long COVID symptoms and QoL among individuals with mental illness.MethodIndividuals with mental illness (n = 333) were recruited from a psychiatric center in southern Taiwan to participate in the study. Data were collected regarding sleep quality, psychological distress, self‐stigma, and QoL. Independent t‐tests, Pearson correlations, and regression with Hayes’ Process Macro were used to compare groups, examine relationships, and parallel mediation models, respectively.ResultsParticipants with long COVID symptoms had significantly worse sleep quality, psychological distress, physical QoL, and psychological QoL compared to those without symptoms. There were significant relationships between sleep quality, psychological distress, self‐stigma, and QoL. Sleep quality significantly mediated the associations between long COVID symptoms and physical and social QoL. Psychological distress significantly mediated the associations between long COVID symptoms and all domains of QoL, but not self‐stigma.ConclusionThere are alternative pathways (e.g., sleep quality and psychological distress) through which long COVID symptoms may affect the QoL of individuals with mental illness. The findings suggest that individuals with long COVID symptoms have a higher chance of having poor QoL. Therefore, there may be the need for counseling and possible therapy for those who contract COVID‐19, especially among individuals who already have mental illness.

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Adaptation of the Pittsburgh Sleep Quality Index in Chinese adults with type 2 diabetes

Abstract: The adapted PSQI was similar to the original PSQI in that only the component "use of sleep medication" was removed from the original scale and the one-factor scoring worked better. In contrast, the three-factor model has limited usefulness in this population.

Cited by 41 publications

References 30 publications

Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review

Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review

Evaluation of sleep quality in adolescent patients with osteosarcoma using Pittsburgh Sleep Quality Index

Parallel Mediating Effects of Sleep Quality, Psychological Distress, and Self‐Stigma in the Associations Between Long COVID Symptoms and Quality of Life Among Taiwanese Individuals With Mental Health Illness

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