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  1. Afolalu EF, Ramlee F, Tang NKY
    Sleep Med Rev, 2018 06;39:82-97.
    PMID: 29056414 DOI: 10.1016/j.smrv.2017.08.001
    Emerging longitudinal research has highlighted poor sleep as a risk factor of a range of adverse health outcomes, including disabling pain conditions. In establishing the causal role of sleep in pain, it remains to be clarified whether sleep deterioration over time is a driver of pain and whether sleep improvement can mitigate pain-related outcomes. A systematic literature search was performed using PubMed MEDLINE, Ovid EMBASE, and Proquest PsycINFO, to identify 16 longitudinal studies involving 61,000 participants. The studies evaluated the effect of sleep changes (simulating sleep deterioration, sleep stability, and sleep improvement) on subsequent pain-related outcomes in the general population. A decline in sleep quality and sleep quantity was associated with a two- to three-fold increase in risk of developing a pain condition, small elevations in levels of inflammatory markers, and a decline in self-reported physical health status. An exploratory meta-analysis further revealed that deterioration in sleep was associated with worse self-reported physical functioning (medium effect size), whilst improvement in sleep was associated with better physical functioning (small effect size). The review consolidates evidence that changes in sleep are prospectively associated with pain-related outcomes and highlights the need for further longitudinal investigations on the long-term impact of sleep improvements.
  2. Ramlee F, Sanborn AN, Tang NKY
    Sleep, 2017 07 01;40(7).
    PMID: 28525617 DOI: 10.1093/sleep/zsx091
    Study objectives: We conceptualized sleep quality judgment as a decision-making process and examined the relative importance of 17 parameters of sleep quality using a choice-based conjoint analysis.

    Methods: One hundred participants (50 good sleepers; 50 poor sleepers) were asked to choose between 2 written scenarios to answer 1 of 2 questions: "Which describes a better (or worse) night of sleep?". Each scenario described a self-reported experience of sleep, stringing together 17 possible determinants of sleep quality that occur at different times of the day (day before, pre-sleep, during sleep, upon waking, day after). Each participant answered 48 questions. Logistic regression models were fit to their choice data.

    Results: Eleven of the 17 sleep quality parameters had a significant impact on the participants' choices. The top 3 determinants of sleep quality were: Total sleep time, feeling refreshed (upon waking), and mood (day after). Sleep quality judgments were most influenced by factors that occur during sleep, followed by feelings and activities upon waking and the day after. There was a significant interaction between wake after sleep onset and feeling refreshed (upon waking) and between feeling refreshed (upon waking) and question type (better or worse night of sleep). Type of sleeper (good vs poor sleepers) did not significantly influence the judgments.

    Conclusions: Sleep quality judgments appear to be determined by not only what happened during sleep, but also what happened after the sleep period. Interventions that improve mood and functioning during the day may inadvertently also improve people's self-reported evaluation of sleep quality.

  3. Hamzah H, Tan CS, Ramlee F, Zulkifli SS
    BMC Psychol, 2023 Nov 13;11(1):392.
    PMID: 37957763 DOI: 10.1186/s40359-023-01435-5
    BACKGROUND: The original Family Resilience Scale (FRS) is a reliable tool to assess family resilience. However, the FRS is based on the United States and parental context. Thus, the usefulness of the FRS for the adolescent and young adult population in Asian countries, particularly Malaysia remains unknown. This study translated the FRS into the Malay language and validated it on Malaysian adolescents and young adults to identify its potential as a self-report tool to assess the resilience level of their family.

    METHODS: A total of 351 participants (Mage = 19.75, SDage = 3.29) were recruited in the study using purposive sampling. Confirmatory factor analysis was conducted to examine the factorial structure of the Family Resilience Scale-Malay (FRS-Malay) and measurement invariance between adolescents and young adults. Then, the scale's reliability was investigated using Cronbach's alpha, McDonald's omega coefficients, and composite reliability index. Finally, we examined the discriminant validity of the FRS-Malay by correlating its score with individual resilience score and examined the incremental validity of the scale using hierarchical multiple regression analysis to test if family resilience can explain individual well-being levels beyond and above individual resilience.

    RESULTS: The findings of the confirmatory factor analysis suggest that a single-factor model is supported for both age groups. Furthermore, the scale exhibited scalar invariance between adolescents and young adults. The scale also exhibited good reliability, as the value of Cronbach's alpha, McDonald omega coefficients, and composite reliability index were above 0.80. Additionally, the Pearson correlation analysis showed a positive correlation between the FRS-Malay and individual resilience scores, which supports the discriminant validity of the scale. Similarly, the incremental validity of the scale is also supported. Specifically, family resilience had a positive correlation with well-being, even after controlling for individual resilience in the regression analysis.

    CONCLUSIONS: The FRS-Malay has demonstrated good reliability and validity. The scale measures the same construct of family resilience across adolescents and young adults, making it suitable for comparisons. Therefore, this unidimensional tool is appropriate for self-reporting their perceived level of family resilience. It is also useful for studying the development and fluctuation of family resilience in the Malaysian context.

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