interventions or work with the health care team to assess the sleep issue in greater depth. BEST TOOL: The Pittsburgh Sleep Quality Index (PSQI) is an effective. Psychiatry Res. May;28(2) The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Buysse DJ(1), Reynolds. Pittsburgh Sleep Quality Index (PSQI). Instructions: The following questions relate to your usual sleep habits during the past month only. Your answers.
Sleep Index Pittsburgh Quality
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Below is the PSQI instrument, the correct scoring algorithm, the original article, and the scoring database. The total score ranges from 9 to Consistent with prior studies, we used the median score 12 to define high and low FIRST score groups. The PHQ-9 total score is the sum of scores for the 9 items for each participant and ranges from 0 to The GAD-7 asks participants to rate how often they have been bothered by each of these 7 core symptoms over the past 2 weeks.
The GAD-7 total score is the sum of scores for the 7 items for each participant and ranges from 0 to We first examined the frequency distributions of maternal sociodemographics, behavioral characteristics, and reproductive history. We used the Student's t -test and the Chi-square test to determine bivariate differences according to sleep quality for continuous and categorical variables, respectively.
We assessed the reliability of the PSQI using several agreement and consistency indices. Further, to investigate the factor structure, we completed an exploratory factor analysis EFA using the principal component analysis with promax rotation.
Before conducting factor analysis, we assessed the suitability for performing the factor analysis. We used the scree plot and eigenvalues associated with each factor to identify the number of meaningful factors. Due to violation of the multivariate normality assumption, we used the weighted least squares WLS estimation for the CFA. We calculated the following parameters to evaluate model fit: The present study used the following criteria for consideration of a reasonable fit: As a post hoc analysis, based on the best fit model of the CFA, we created 3 subscale scores for the PSQI by summing scores of the components that loaded on factors 1, 2, and 3, respectively.
We included potential confounders of a priori interest i. Statistical analyses were performed using SAS 9. Table 1 presents sociodemographics and reproductive characteristics of the study population.
The mean age of the participants was The majority of the participants were married or living with a partner The average gestational age of participants at interview was 9. On the structured questionnaire, Based on the PSQI global score, Compared with good sleepers, poor sleepers were less likely to be married or living with a partner and report current pregnancy as planned.
Poor sleepers were more likely to have difficulty paying for very basic foods and experience childhood abuse and intimate partner violence. Compared with good sleepers, poor sleepers had significantly higher mean total scores on all other measures i. Figure 1 shows the distribution of the global PSQI score.
Among this population, the global PSQI score ranged from 0 to 15, with a mode of 3. The mean score was 4. In particular, among the participants, only 37 women 5. The results of the exploratory factor analysis indicated a 3-factor solution with eigenvalues of 1. These 3 factors together explained A series of confirmatory factor analyses was conducted Table 4.
Among models including all 7 components model 1, 2, and 3 , model 3, for which 7 components were assigned to 3 factors and allowed correlations between factor 1 and 2, and between factor 1 and 3, indicated an adequate fit: Standardized regression weights for paths associated with model 3 is shown in Figure 2.
Further adjustments for maternal age resulted in negligible changes in the magnitude of partial correlation coefficients. The magnitudes of correlation coefficients were stronger for factors 1 and 3 than those estimated for factor 2. After adjusting for possible confounding by maternal age, parity, early pregnancy body mass index, difficulty paying for the basic foods, history of childhood physical or sexual abuse, and history of intimate partner violence, we found that poor sleep quality was associated with a 3.
Furthermore, as compared with good sleepers, we noted that poor sleepers had a 5. The Spanish-language version of the PSQI demonstrated good construct validity when used among a cohort of low-income pregnant Peruvian women.
Women classified as having poor sleep quality in early pregnancy i. Exploratory factor analysis yielded a three-factor structure, including a sleep quality factor, a sleep efficiency factor, and a sleep medication factor.
Based on the results of confirmatory factor analysis, the one-factor structure of Buysse 17 did not fully capture the multidimensional nature of sleep disturbance with a poor fit. A three-factor model demonstrated a better fit than the one-factor model, which was consistent with reports from several previous studies. For example, using the principal component analysis, in a sample of Nigerian university students, Aloba et al.
Although several three-factor models have been reported, the specific contents of the three factors varied across previous studies. Differences in culture, demographics, and linguistics may contribute to observed variations. Investigators have argued that the three-factor structure of the PSQI has the clinical advantage of obtaining multiple dimensions of sleep problems from a single questionnaire.
Cole and colleagues have argued that relying solely on the PSQI global score may not identify disturbances that only reside on one of the three PSQI factors. The PSQI demonstrated good construct validity in our study population.
We found that that the PSQI global score and two of the subscale scores were moderately correlated with stress-induced sleep disturbance assessed using the FIRST , depressive symptoms assessed using the PHQ-9 , and symptoms of generalized anxiety disorder assessed using the GAD In Hunsley, John; Mash, Eric.
A Guide to Assessments that Work. Journal of Clinical Sleep Medicine. Prevalence, self-help treatments, consultations, and determinants of help-seeking behaviors". Psychometrics and outcomes following cognitive behavioral therapy". Retrieved from " https: Sleep medicine Psychological testing Clinical psychology tests Psychological tools.
The PSQI is a relatively new assessment. Not enough research has been conducted on inter-rater reliability to give a comprehensive rating.
The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research.
The Pittsburgh Sleep Quality Index (PSQI) is a self-report questionnaire that assesses sleep quality over a 1-month time interval. The measure consists of 19 . The Pittsburgh Sleep Quality Index (PSQI) was developed by Dr. Daniel J. Buysse and coworkers at the University of Pittsburgh's Western. The Pittsburgh Sleep Quality Index (PSQI): A new instrument for psychiatric research and practice. Psychiatry Research, 28(2), The detailed scoring .