Sleep-related attentional bias in insomnia: A state-of-the-science review

Harris, Kamelia; Spiegelhalder, Kai; Espie, Colin A.; Macmahon, Kenneth; Woods, Heather; Kyle, Simon D.

doi:10.1016/j.cpr.2015.08.001

Cited by 88 publications

(80 citation statements)

References 42 publications

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“…Consistent with such theoretical accounts, studies have confirmed that insomnia is associated with patterns of biased attention favouring sleep-related threatening information [2]. …”

Section: Tablementioning

confidence: 62%

Assessing the Therapeutic Potential of Targeted Attentional Bias Modification for Insomnia Using Smartphone Delivery

Clarke

Bedford

Notebaert

et al. 2016

Psychother Psychosom

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“…Consistent with such theoretical accounts, studies have confirmed that insomnia is associated with patterns of biased attention favouring sleep-related threatening information [2]. …”

Section: Tablementioning

confidence: 62%

Assessing the Therapeutic Potential of Targeted Attentional Bias Modification for Insomnia Using Smartphone Delivery

Clarke

Bedford

Notebaert

et al. 2016

Psychother Psychosom

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“…We suggest that future studies should consider employing more nuanced and direct measures of attention allocation (e.g. eye‐tracking; Beattie, Bindemann, Kyle, & Biello, ; Harris et al, ).…”

Section: Discussionmentioning

confidence: 99%

Sham sleep feedback delivered via actigraphy biases daytime symptom reports in people with insomnia: Implications for insomnia disorder and wearable devices

Gavriloff

Sheaves

Juss

et al. 2018

Journal of Sleep Research

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This study investigated whether providing sham feedback about sleep to individuals with insomnia influenced daytime symptom reports, sleep-related attentional bias and psychomotor vigilance. Sixty-three participants meeting DSM-5 criteria for insomnia disorder were recruited from the community. Following baseline assessments and actigraphy briefing, participants were randomised to receive next-day sham feedback on sleep quality ("positive" vs. "negative" sleep efficiency condition). Feedback was delivered at habitual rise-time using an integrated actigraphy-diary watch to simulate wearable device behaviour. Participants completed symptom reports immediately before receiving feedback, and at 12:00 and 15:00 hr, using the experience sampling method. Following this they returned to the laboratory in the evening to complete symptom reports and computerised tests of sleep-related attentional bias and basic psychomotor vigilance. Participants randomised to negative feedback (n = 32) evidenced impaired daytime function (decreased alert cognition [d = 0.79], increased sleepiness/fatigue [d = 0.55]) in the evening compared with those given positive feedback (n = 31). Within-day trajectories revealed that the positive-feedback group, relative to the negative-feedback group, displayed a significantly greater increase in positive mood and alert cognition (from rise-time to 12:00 hr), and significantly greater decrease in sleepiness/fatigue. There were no significant between-group differences on measures of sleep-related attentional bias [d = 0.20] or psychomotor vigilance [d = 0.12]. This controlled experiment shows that sham feedback about sleep biases appraisal of daytime symptoms, highlighting a pathway connecting sleep misperception with daytime features of insomnia. Findings have important implications for wearable devices that claim to measure "objective" sleep yet may provide inaccurate data relative to gold-standard measurement.

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“…Attention bias in insomnia refers to the tendency to selectively pay attention to perceived internal or external threats to sleep or the consequences of poor sleep (37). Mindfulness begins by training oneself to pay attention to present moment experience and to redirect attention back to the focal point (e.g., breathing) should it become distracted by some thought.…”

Section: How Mindfulness Meditation May Impact Sleepmentioning

confidence: 99%

The Quest for Mindful Sleep: a Critical Synthesis of the Impact of Mindfulness-Based Interventions for Insomnia

Garland

Zhou

Gonzalez

et al. 2016

Curr Sleep Medicine Rep

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Mindfulness-Based Interventions (MBIs) for insomnia and sleep disturbances are receiving increasing clinical and research attention. This paper provides a critical appraisal of this growing area investigating the application of MBIs for people with insomnia and sleep disturbance. First, we discuss the theoretical justification for how mindfulness meditation practice may affect sleep processes. Second, we provide a focused review of literature published between January 1, 2012 and April 1, 2016 examining the impact of MBIs on sleep, broken down by whether insomnia or sleep disturbance was a primary or secondary outcome. Recommendations for future research are discussed.

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Sleep-related attentional bias in insomnia: A state-of-the-science review

Cited by 88 publications

References 42 publications

Assessing the Therapeutic Potential of Targeted Attentional Bias Modification for Insomnia Using Smartphone Delivery

Assessing the Therapeutic Potential of Targeted Attentional Bias Modification for Insomnia Using Smartphone Delivery

Sham sleep feedback delivered via actigraphy biases daytime symptom reports in people with insomnia: Implications for insomnia disorder and wearable devices

The Quest for Mindful Sleep: a Critical Synthesis of the Impact of Mindfulness-Based Interventions for Insomnia

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