Development and Testing of a Smartphone-Based Cognitive/Neuropsychological Evaluation System for Substance Abusers. Issue 4 (7th August 2016)

• Record Type: Journal Article
• Authors: Pal, Reshmi; Mendelson, John; Clavier, Odile; Baggott, Mathew J.; Coyle, Jeremy; Galloway, Gantt P.
• Is Part Of: Journal of psychoactive drugs. Volume 48:Issue 4(2016)
• Page Start: 288
• Page End: 294
• Publication Date: 2016-08-07
• Subjects: Methamphetamine -- N-Back task -- neurocognitive -- Neurophone -- Stop Signal task -- Stroop task; Hallucinogenic drugs -- Periodicals; Drug abuse -- Periodicals; Hallucinogens -- Periodicals; Psychotropic Drugs -- Periodicals; Drogues -- Périodiques; Hallucinogènes -- Périodiques; Electronic journals; 616.86
• DOI: 10.1080/02791072.2016.1191093
• Languages: English
• ISSNs: 0279-1072

Abstract

ABSTRACT: Introduction : In methamphetamine (MA) users, drug-induced neurocognitive deficits may help to determine treatment, monitor adherence, and predict relapse. To measure these relationships, we developed an iPhone app (Neurophone) to compare lab and field performance of N-Back, Stop Signal, and Stroop tasks that are sensitive to MA-induced deficits. Methods : Twenty healthy controls and 16 MA-dependent participants performed the tasks in-lab using a validated computerized platform and the Neurophone before taking the latter home and performing the tasks twice daily for two weeks. Results : N-Back task: there were no clear differences in performance between computer-based vs. phone-based in-lab tests and phone-based in-lab vs. phone-based in-field tests. Stop-Signal task: difference in parameters prevented comparison of computer-based and phone-based versions. There was significant difference in phone performance between field and lab. Stroop task: response time measured by the speech recognition engine lacked precision to yield quantifiable results. There was no learning effect over time. On an average, each participant completed 84.3% of the in-field NBack tasks and 90.4% of the in-field Stop Signal tasks (MA-dependent participants: 74.8% and 84.3%; healthy controls: 91.4% and 95.0%, respectively). Participants rated Neurophone easy to use. Conclusion : Cognitive tasks performed in-field using Neurophone have the potential to yield results comparable to those obtained in a laboratory setting. Tasks need to be modified for use as the app's voice recognition system is not yet adequate for timed tests.