Literature DB >> 33618070

Enhancing attention and memory of individuals at clinical high risk for psychosis with mHealth technology.

Huijun Li1, Shuwen Yang2, Hongmei Chi3, Lihua Xu4, Tianghong Zhang5, Gwendolyn Singleton6, Yingying Tang7, William S Stone8, Jijun Wang9.   

Abstract

BACKGROUND: Cognitive impairment has adverse impact on the social and role functions of those at clinical high risk for psychosis and it has become an important target for intervention. Mobile health applications are user-friendly, real-time, personalized and portable in administering cognitive training and have promising application prospects in the field of mental health.
METHODS: Eighty CHR subjects were randomized into an intervention group and a control group. CHR subjects of the intervention group performed attention and memory training via a Specific Memory Attention Resource and Training (SMART) application in their smart phones for 10 min per day, five days per week for three months. Both groups were followed up for three months. At baseline and follow-up phases, cognitive function was measured using the MATRICS Consensus Cognitive Battery (MCCB). In the follow-up, the intervention group completed the Mobile Application Rating Scale (MARS) to provide feedback to improve SMART.
RESULTS: There is a significant group by time interaction effect in the Attention/Vigilance domain, which is significantly better in the intervention group than in the control group at 3- month follow-up. The improvement in Attention/Vigilance in the intervention group is significantly related to the amount of cognitive training time. Global Assessment of Function (GAF) reduction rate at baseline could predict the improvement of Attention/Vigilance. MARS results indicate that CHR subjects were receptive of SMART.
CONCLUSION: Mobile technology can be applied to improve cognitive function of CHR individuals, especially in the Attention/Vigilance domain.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Attention; Clinical high risk; Memory cognitive function; Mobile health application

Mesh:

Year:  2021        PMID: 33618070     DOI: 10.1016/j.ajp.2021.102587

Source DB:  PubMed          Journal:  Asian J Psychiatr        ISSN: 1876-2018


  2 in total

1.  Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study.

Authors:  Aditya Vaidyam; John Halamka; John Torous
Journal:  JMIR Mhealth Uhealth       Date:  2022-01-07       Impact factor: 4.773

2.  Digital technology for addressing cognitive impairment in recent-onset psychosis: A perspective.

Authors:  Imogen Bell; Roos M C A Pot-Kolder; Stephen J Wood; Barnaby Nelson; Nicola Acevedo; Alexandra Stainton; Katie Nicol; James Kean; Shayden Bryce; Cali F Bartholomeusz; Amity Watson; Orli Schwartz; Rothanthi Daglas-Georgiou; Courtney C Walton; Donel Martin; Magenta Simmons; Isabel Zbukvic; Andrew Thompson; Jennifer Nicholas; Mario Alvarez-Jimenez; Kelly Allott
Journal:  Schizophr Res Cogn       Date:  2022-03-10
  2 in total

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