Being kind to self is being kind to sleep? A structural equation modelling approach evaluating the direct and indirect associations of self-compassion with sleep quality, emotional distress and mental well-being

Abstract

The study examined the relationship between self-compassion and sleep quality. We also investigated whether the relationship was mediated by brooding, perceived stress, sleep hygiene, and anxiety about sleep and whether self-compassion was associated with anxiety, depression, and mental well-being indirectly through sleep quality. A sample of 468 adults completed measures of demographics, health, sleep quality, self-compassion, predisposing (arousability, brooding, perfectionism, interpersonal problems), precipitating (perceived stress, presence of life-changing events) and perpetuating (sleep hygiene, anxiety about sleep) factors of insomnia, depression, anxiety and mental well-being. The results of the hierarchical multiple regression analysis revealed that low self-compassion was significantly associated with poorer sleep quality when controlling for socio-demographic variables, health-related factors and predisposing factors of insomnia. The association, however, became non-significant when precipitating and perpetuating factors of insomnia were added to the model. Structural equation modelling showed that the relationship between self-compassion and sleep quality was mediated by anxiety about sleep and through sequential mediations involving anxiety about sleep and then sleep hygiene; or anxiety about sleep, perceived stress and then sleep hygiene; or perceived stress and then sleep hygiene. Poor sleep in turn was associated with anxiety and depression, which had a negative effect on mental well-being. This study provided cross-sectional evidence that low self-compassion is a potential risk factor for poor sleep quality, and consequently, poor mental well-being. These findings provide insights into possible mechanisms underlying the relationship between self-compassion and sleep quality that could inform etiological models of insomnia.