Pending challenges to e-mental health in the COVID-19 era: Acceptability of a smartphone-based ecological momentary assessment application among patients with schizophrenia spectrum disorders. (13th April 2021)

• Record Type: Journal Article
• Authors: Lopez-Morinigo, J.-D.; Luisa, B.-E. Maria; Porras-Segovia, A.; Martínez, A. Sánchez-Escribano; Escobedo-Aedo, P.-J.; Ruiz-Ruano, V. González; Mata-Iturralde, L.; Muñoz-Lorenzo, L.; Sánchez-Alonso, S.; Artés-Rodríguez, A.; Baca-Garcia, E.
• Is Part Of: European psychiatry. Volume 64:Supplement 1(2021)
• Page Start: S343
• Page End: S343
• Publication Date: 2021-04-13
• Subjects: Schizophrenia spectrum disorders -- acceptability -- ecological momentary assessment; Psychiatry -- Periodicals; Mental illness -- Periodicals; Electronic journals; 616.89
• DOI: 10.1192/j.eurpsy.2021.920
• Languages: English
• ISSNs: 0924-9338

Abstract

Abstract : Introduction: Concerns have been raised about ecological momentary assessment (EMA) acceptability among patients with schizophrenia spectrum disorders (SSD), which is of major relevance during the e-Mental health-focused COVID-19 pandemic. Objectives: To investigate i) the levels of adherence to a passive smartphone-based EMA tool, the Evidence-Based Behavior (eB2), among SSD patients; and ii) putative predictors of this. Methods: Sample: SSD (F20-29-ICD10) outpatients, age 18-64, without financial incentives, recruited over 17/06/2019-11/03/2020 at the Hospital Universitario Fundación Jiménez Díaz (Madrid, Spain). Those who accepted the eB2 installation -users- and those who did not -non-users- were compared in sociodemographic, clinical, premorbid adjustment, neurocognitive, psychopathological, insight and metacognitive variables by a multivariable binary logistic regression model. Results: Sample (N=77): n=41 males; age: 47.69±9.76 years, n=24 users (31.2%). n=14 users (70%) had the eB2 installed at follow-up (median=14.50 weeks). Multivariable binary logistic regression model on 'user' as outcome β SE Wald p OR 95% CI Age -0.075 0.038 3.910 0.048 0.928 0.861-0.999 Education level -0.967 1.289 0.563 0.453 0.380 0.030-4.755 Early adolescence premorbid adjustment -0.285 0.110 6.695 0.010 0.752 0.606-0.933 Trail Making Test A -0.030 0.025 1.488 0.222 0.970 0.924-1.018 Trail Making Test B -0.005 0.010 0.278 0.598 0.995 0.976-1.014 Cognitive Insight 0.062 0.061 1.043 0.307 1.064 0.944-1.200 X 2 =25.296, df=6, p<0.001. Nagelkerke-R 2 =44.7%. Correctly classified: 76.9%, users:54.5%, non-users:88.4%. Conclusions: Acceptability of a smartphone-based EMA application among SSD patients was low. Age (young) and good premorbid adjustment predicted acceptability. e-Mental Health methods need to be tailored for patients with SSD. Otherwise, these highly vulnerable individuals may be neglected by e-health-based services in the post-COVID-19 years ahead.