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Data · dataset · 2026

Sleep, Digital Health Technologies and Psychotic Symptoms

Listed in UCL Research Data Repository

(1) A systematic review and meta-analysis of digital health technologies effects on psychotic symptoms in adults with psychosis<br>Abstract:<br>Objective: To conduct a systematic review and meta-analysis of controlled studies to determine the effect of digital health technologies on psychotic symptoms.<br>

Description

Method

Electronic databases were searched up to March 2019. A narrative synthesis and meta-analyses of subcategories were completed.Results: Twenty-one articles met inclusion criteria, covering three DHT types: avatar therapy, phone apps and computer-assisted cognitive remediation (CACR). In the latter, psychotic symptoms were secondary outcomes and only one of nine CACR studies demonstrated an effect on these symptoms.

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All four of the avatar trials and one of three phone app studies provided preliminary evidence of effectiveness in reducing psychotic symptoms.<br>Conclusion: Although effectiveness of DHTs for reducing psychotic symptoms cannot yet be conclusively established, the emerging literature suggests that DHTs using immersive avatar therapy holds most promise.<br>(2) The Association Between Sleep Quality and Attenuated Psychotic Symptoms in a Community Sample<br>Abstract:<br>Aim: To determine if poor sleep quality makes a unique contribution to predicting the number ofattenuated psychotic symptoms endorsed in a prodromal questionnaire and the level of distressassociated with the symptoms, when controlling for demographics, depression and drug/alcohol use.<br>

Method

An online survey was conducted using Amazon’s online crowdsourcing service MechanicalTurk (MTurk). The sample was 1,013 adults (18 to 36 years) from the general population in the USA.The survey consisted of the Prodromal Questionnaire 16 (PQ-16), the Pittsburgh Sleep Quality Index,the Patient Health Questionnaire 9 (PHQ-9), the DAST-10 and the AUDIT. Regression analyses wereperformed with the PQ-16 as the dependent variable, and sleep quality as the predictor variable,holding constant sociodemographic variables, depression, and alcohol/drug abuse.Results: 37% of the sample endorsed six or more PQ-16 items, which may be suggestive of an at-riskmental state, with sleep disturbance significantly increasing the likelihood (Odds ratio 2.09 <.001) ofendorsing six or more PQ-16 items.

After controlling for socio-demographic variables, depression anddrug/alcohol abuse, poor sleep quality made a unique contribution of 5.8% of the variance accountedfor in level of distress experienced by attenuated psychotic symptoms.<br>Conclusion: The results add to the evidence that sleep disturbance is a contributory factor inattenuated psychotic symptoms. Effective treatment of sleep disturbance may reduce the likelihood ofdeveloping an at-risk mental state.

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Where it is published

Catalogue records · 1

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Provenance · 1 source records, 5 field assertions
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FieldAssertionExtractorEvidence
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