Abstract
Introduction and Project Objectives: Cognitive theories of depression hypothesized that affective-cognitive processing bias of emotional information, such as human faces, is related to the maintenance of depression. Sleep disturbances were found to maintain depression, and t he possible role of sleep in the maintenance of depression through emotional processing bias still requires exploration. To further examine the specific sleep mechanism of the maintenance of depression, we focused on one of the affective-cognitive features in depression: attentional bias towards emotional faces. This study adopted a napping design to examine how sleep is associated with attentional bias towards emotional faces among patients with major depressive disorder (MDD).
Methods: Participants (n = 106, 18-60 years) were assessed by the research version of Structured Clinical Interview for DSM-IV-TR Disorders (SCID), clinician-rated Hamilton Depression Scale (HAM-D), self-reported Beck Depression Inventory-II (801-1 I) and Insomnia Severity Index (ISi). SCIO identified 45 MOD patients (mean HAM-0 score = 14.53, mean BDl-11 score = 23.58, 87% female) and 61 non-depressed control (mean HAM-D score = 1 .48, mean 801-11 score = 3.81, 69% female). All participants were randomly assigned to wake, 30-min nap and 90-min nap conditions. They completed the dot-probe task measuring attentional bias towards sad and happy faces before and after wake or nap.
Results: Repeated-measures MANCOVA controlling for sleep quality, diagnosis of insomnia, insomnia symptoms, positive and negative mood changes showed that participants with MOD showed higher attentional bias towards sad faces and lower attentional bias towards happy faces after wakefulness, but not after napping. On the other hand, the non-depressed controls had no significant changes in attentional bias after wakefulness and napping.
Conclusion: Our data provided the first evidence that napping is beneficial in ameliorating the escalating attention towards sad faces and declining attention towards happy faces among MOD patients throughout the day. Clinicians may consider the potential role of sleep on attentional bias in pharmacological and psychological interventions of depression. Copyright © 2019 Health Research Symposium.
Methods: Participants (n = 106, 18-60 years) were assessed by the research version of Structured Clinical Interview for DSM-IV-TR Disorders (SCID), clinician-rated Hamilton Depression Scale (HAM-D), self-reported Beck Depression Inventory-II (801-1 I) and Insomnia Severity Index (ISi). SCIO identified 45 MOD patients (mean HAM-0 score = 14.53, mean BDl-11 score = 23.58, 87% female) and 61 non-depressed control (mean HAM-D score = 1 .48, mean 801-11 score = 3.81, 69% female). All participants were randomly assigned to wake, 30-min nap and 90-min nap conditions. They completed the dot-probe task measuring attentional bias towards sad and happy faces before and after wake or nap.
Results: Repeated-measures MANCOVA controlling for sleep quality, diagnosis of insomnia, insomnia symptoms, positive and negative mood changes showed that participants with MOD showed higher attentional bias towards sad faces and lower attentional bias towards happy faces after wakefulness, but not after napping. On the other hand, the non-depressed controls had no significant changes in attentional bias after wakefulness and napping.
Conclusion: Our data provided the first evidence that napping is beneficial in ameliorating the escalating attention towards sad faces and declining attention towards happy faces among MOD patients throughout the day. Clinicians may consider the potential role of sleep on attentional bias in pharmacological and psychological interventions of depression. Copyright © 2019 Health Research Symposium.
Original language | English |
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Publication status | Published - Jun 2019 |
Event | Health Research Symposium 2019: "Genomics and Big Data in Health and Disease" - , Hong Kong Duration: 12 Jun 2019 → 12 Jun 2019 https://rfs1.healthbureau.gov.hk/english/events/health_research_symposium_2019.html |
Conference
Conference | Health Research Symposium 2019: "Genomics and Big Data in Health and Disease" |
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Country/Territory | Hong Kong |
Period | 12/06/19 → 12/06/19 |
Internet address |