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Purpose <p>We examined the psychometric properties of the Pittsburgh Sleep Quality Index (PSQI) in a large sample of young women in Soweto, South Africa, to assess its reliability and structural validity in this context.</p> Methods <p>Data were collected from 7182 women enrolled in the Bukhali randomized controlled trial, part of the Healthy Life Trajectories Initiative (HeLTI). Sociodemographic information and PSQI data were collected through interviewer-administered surveys. Internal consistency was assessed using Cronbach’s alpha, McDonald’s omega and item-level correlations. Confirmatory factor analysis (CFA) evaluated the original one-factor and established two- and three-factor multidimensional models. Model fit was examined using Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Tucker–Lewis Index (TLI).</p> Results <p>Most women (57.4%) reported good sleep quality (PSQI ≤ 5). Poor sleep quality was associated with higher household socioeconomic status (assets score), higher education, and single relationship status. Average sleep was 7.8&#xa0;hours, characterized by prolonged onset latency and high fragmentation, suggesting that continuity disruptions rather than opportunity shortage drove poor sleep. The PSQI had modest internal consistency (α = .57; ω = .57; item–total <i>r</i> = .33&#xa0;–&#xa0;.65). The one-factor model demonstrated poor fit (χ<sup>2</sup>(14) = 1677.70; CFI = .65; TLI = .48; RMSEA = .13) whereas fit was good for the two-factor (χ<sup>2</sup>(13) = 291.46; CFI = .94; TLI = .91; RMSEA = .05) and three-factor models (χ<sup>2</sup>(11) = 285.21; CFI = .94; TLI = .89; RMSEA = .06).</p> Conclusion <p>The PSQI showed a multidimensional structure in this population. While both multidimensional models performed well, the two-factor model showed slightly better fit and is recommended for use in this population. Interpreting PSQI components rather than the global score offers more meaningful insight into sleep quality and highlights the need for context-specific psychometric validation in diverse settings.</p> Brief Summary Current Knowledge/Study Rationale <p>The Pittsburgh Sleep Quality Index is widely used, but prior evidence shows its reliability and factor structure vary across populations, settings, and sex. Young women in under-resourced urban South African settings may experience sleep disruption shaped by psychosocial stress, safety concerns, caregiving demands, and environmental factors, yet the PSQI had not been evaluated in this population.</p> Study Impact <p>In this large Soweto cohort, sleep problems appeared driven more by fragmented sleep and continuity disruptions than by insufficient sleep opportunity. The PSQI performed better as a multidimensional measure, particularly a parsimonious two-factor structure, than as a single global score. The findings support using component- or factor-informed PSQI interpretation and highlight the need for context-specific validation of sleep measures in diverse populations.</p>

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Psychometric evaluation of the Pittsburgh Sleep Quality Index among South African women participating in the Bukhali trial: Healthy Life Trajectories Initiative

  • 期刊论文

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  • 发表日期：

    2026年8月3日

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  • Stephanie Alcock,
  • Johanna Beukes,
  • Claire Hart,
  • Karine Scheuermaier,
  • Stephen J. Lye,
  • Shane A. Norris

摘要

Purpose

We examined the psychometric properties of the Pittsburgh Sleep Quality Index (PSQI) in a large sample of young women in Soweto, South Africa, to assess its reliability and structural validity in this context.

Methods

Data were collected from 7182 women enrolled in the Bukhali randomized controlled trial, part of the Healthy Life Trajectories Initiative (HeLTI). Sociodemographic information and PSQI data were collected through interviewer-administered surveys. Internal consistency was assessed using Cronbach’s alpha, McDonald’s omega and item-level correlations. Confirmatory factor analysis (CFA) evaluated the original one-factor and established two- and three-factor multidimensional models. Model fit was examined using Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Tucker–Lewis Index (TLI).

Results

Most women (57.4%) reported good sleep quality (PSQI ≤ 5). Poor sleep quality was associated with higher household socioeconomic status (assets score), higher education, and single relationship status. Average sleep was 7.8 hours, characterized by prolonged onset latency and high fragmentation, suggesting that continuity disruptions rather than opportunity shortage drove poor sleep. The PSQI had modest internal consistency (α = .57; ω = .57; item–total r = .33 – .65). The one-factor model demonstrated poor fit (χ2(14) = 1677.70; CFI = .65; TLI = .48; RMSEA = .13) whereas fit was good for the two-factor (χ2(13) = 291.46; CFI = .94; TLI = .91; RMSEA = .05) and three-factor models (χ2(11) = 285.21; CFI = .94; TLI = .89; RMSEA = .06).

Conclusion

The PSQI showed a multidimensional structure in this population. While both multidimensional models performed well, the two-factor model showed slightly better fit and is recommended for use in this population. Interpreting PSQI components rather than the global score offers more meaningful insight into sleep quality and highlights the need for context-specific psychometric validation in diverse settings.

Brief Summary Current Knowledge/Study Rationale

The Pittsburgh Sleep Quality Index is widely used, but prior evidence shows its reliability and factor structure vary across populations, settings, and sex. Young women in under-resourced urban South African settings may experience sleep disruption shaped by psychosocial stress, safety concerns, caregiving demands, and environmental factors, yet the PSQI had not been evaluated in this population.

Study Impact

In this large Soweto cohort, sleep problems appeared driven more by fragmented sleep and continuity disruptions than by insufficient sleep opportunity. The PSQI performed better as a multidimensional measure, particularly a parsimonious two-factor structure, than as a single global score. The findings support using component- or factor-informed PSQI interpretation and highlight the need for context-specific validation of sleep measures in diverse populations.