1
|
Eisner E, Richardson C, Thomas N, Rus-Calafell M, Syrett S, Firth J, Gumley A, Hardy A, Allan S, Kabir T, Ward T, Priyam A, Bucci S. Measurement of Adverse Events in Studies of Digital Health Interventions for Psychosis: Guidance and Recommendations Based on a Literature Search and Framework Analysis of Standard Operating Procedures. Schizophr Bull 2024:sbae048. [PMID: 38683836 DOI: 10.1093/schbul/sbae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
BACKGROUND Given the rapid expansion of research into digital health interventions (DHIs) for severe mental illness (SMI; eg, schizophrenia and other psychosis diagnoses), there is an emergent need for clear safety measures. Currently, measurement and reporting of adverse events (AEs) are inconsistent across studies. Therefore, an international network, iCharts, was assembled to systematically identify and refine a set of standard operating procedures (SOPs) for AE reporting in DHI studies for SMI. DESIGN The iCharts network comprised experts on DHIs for SMI from seven countries (United Kingdom, Belgium, Germany, Pakistan, Australia, United States, and China) and various professional backgrounds. Following a literature search, SOPs of AEs were obtained from authors of relevant studies, and from grey literature. RESULTS A thorough framework analysis of SOPs (n = 32) identified commonalities for best practice for certain domains, along with significant gaps in others; particularly around the classification of AEs during trials, and the provision of training/supervision for research staff in measuring and reporting AEs. Several areas which could lead to the observed inconsistencies in AE reporting and handling were also identified. CONCLUSIONS The iCharts network developed best-practice guidelines and a practical resource for AE monitoring in DHI studies for psychosis, based on a systematic process which identified common features and evidence gaps. This work contributes to international efforts to standardize AE measurement and reporting in this emerging field, ensuring that safety aspects of DHIs for SMI are well-studied across the translational pathway, with monitoring systems set-up from the outset to support safe implementation in healthcare systems.
Collapse
Affiliation(s)
- Emily Eisner
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
- Research and Innovation, Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK
| | - Cara Richardson
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Neil Thomas
- Centre for Mental Health and Brain Sciences, Swinburne University of Technology, Melbourne, Australia
- Monash Alfred Psychiatry Research Centre, Alfred Hospital, Melbourne, Australia
| | - Mar Rus-Calafell
- Mental Health Research and Treatment Centre, Ruhr-Universität Bochum, Bochum, Germany
| | - Suzy Syrett
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
- NHS Research Scotland Mental Health Network, Edinburgh, UK
| | - Joseph Firth
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
- Research and Innovation, Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK
| | - Andrew Gumley
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Amy Hardy
- Institute of Psychiatry, Psychology, and Neuroscience; King's College London, London, UK
- South London & Maudsley NHS Foundation Trust, London, UK
| | - Stephanie Allan
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Thomas Kabir
- McPin Foundation, London, UK
- Departments of Experimental Psychology & Psychiatry, Oxford University, Oxford, UK
| | - Thomas Ward
- Institute of Psychiatry, Psychology, and Neuroscience; King's College London, London, UK
- South London & Maudsley NHS Foundation Trust, London, UK
| | - Aansha Priyam
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
- Research and Innovation, Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK
| | - Sandra Bucci
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
- Research and Innovation, Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK
| |
Collapse
|
2
|
Zaher F, Diallo M, Achim AM, Joober R, Roy MA, Demers MF, Subramanian P, Lavigne KM, Lepage M, Gonzalez D, Zeljkovic I, Davis K, Mackinley M, Sabesan P, Lal S, Voppel A, Palaniyappan L. Speech markers to predict and prevent recurrent episodes of psychosis: A narrative overview and emerging opportunities. Schizophr Res 2024; 266:205-215. [PMID: 38428118 DOI: 10.1016/j.schres.2024.02.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 02/18/2024] [Accepted: 02/25/2024] [Indexed: 03/03/2024]
Abstract
Preventing relapse in schizophrenia improves long-term health outcomes. Repeated episodes of psychotic symptoms shape the trajectory of this illness and can be a detriment to functional recovery. Despite early intervention programs, high relapse rates persist, calling for alternative approaches in relapse prevention. Predicting imminent relapse at an individual level is critical for effective intervention. While clinical profiles are often used to foresee relapse, they lack the specificity and sensitivity needed for timely prediction. Here, we review the use of speech through Natural Language Processing (NLP) to predict a recurrent psychotic episode. Recent advancements in NLP of speech have shown the ability to detect linguistic markers related to thought disorder and other language disruptions within 2-4 weeks preceding a relapse. This approach has shown to be able to capture individual speech patterns, showing promise in its use as a prediction tool. We outline current developments in remote monitoring for psychotic relapses, discuss the challenges and limitations and present the speech-NLP based approach as an alternative to detect relapses with sufficient accuracy, construct validity and lead time to generate clinical actions towards prevention.
Collapse
Affiliation(s)
- Farida Zaher
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Mariama Diallo
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Amélie M Achim
- Département de Psychiatrie et Neurosciences, Université Laval, Québec City, QC, Canada; Vitam - Centre de Recherche en Santé Durable, Québec City, QC, Canada; Centre de Recherche CERVO, Québec City, QC, Canada
| | - Ridha Joober
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Marc-André Roy
- Département de Psychiatrie et Neurosciences, Université Laval, Québec City, QC, Canada; Centre de Recherche CERVO, Québec City, QC, Canada
| | - Marie-France Demers
- Centre de Recherche CERVO, Québec City, QC, Canada; Faculté de Pharmacie, Université Laval, Québec City, QC, Canada
| | - Priya Subramanian
- Department of Psychiatry, Schulich School of Medicine, Western University, London, ON, Canada
| | - Katie M Lavigne
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Martin Lepage
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Daniela Gonzalez
- Prevention and Early Intervention Program for Psychosis, London Health Sciences Center, Lawson Health Research Institute, London, ON, Canada
| | - Irnes Zeljkovic
- Department of Psychiatry, Schulich School of Medicine, Western University, London, ON, Canada
| | - Kristin Davis
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Michael Mackinley
- Department of Psychiatry, Schulich School of Medicine, Western University, London, ON, Canada; Prevention and Early Intervention Program for Psychosis, London Health Sciences Center, Lawson Health Research Institute, London, ON, Canada
| | - Priyadharshini Sabesan
- Lakeshore General Hospital and Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Shalini Lal
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada; Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada; School of Rehabilitation, Faculty of Medicine, University of Montréal, Montréal, QC, Canada
| | - Alban Voppel
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada; Department of Psychiatry, Schulich School of Medicine, Western University, London, ON, Canada; Robarts Research Institute, Western University, London, ON, Canada.
| |
Collapse
|
3
|
Gleeson JF, McGuckian TB, Fernandez DK, Fraser MI, Pepe A, Taskis R, Alvarez-Jimenez M, Farhall JF, Gumley A. Systematic review of early warning signs of relapse and behavioural antecedents of symptom worsening in people living with schizophrenia spectrum disorders. Clin Psychol Rev 2024; 107:102357. [PMID: 38065010 DOI: 10.1016/j.cpr.2023.102357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 11/03/2023] [Accepted: 11/14/2023] [Indexed: 01/17/2024]
Abstract
BACKGROUND Identification of the early warning signs (EWS) of relapse is key to relapse prevention in schizophrenia spectrum disorders, however, limitations to their precision have been reported. Substantial methodological innovations have recently been applied to the prediction of psychotic relapse and to individual psychotic symptoms. However, there has been no systematic review that has integrated findings across these two related outcomes and no systematic review of EWS of relapse for a decade. METHOD We conducted a systematic review of EWS of psychotic relapse and the behavioural antecedents of worsening psychotic symptoms. Traditional EWS and ecological momentary assessment/intervention studies were included. We completed meta-analyses of the pooled sensitivity and specificity of EWS in predicting relapse, and for the prediction of relapse from individual symptoms. RESULTS Seventy two studies were identified including 6903 participants. Sleep, mood, and suspiciousness, emerged as predictors of worsening symptoms. Pooled sensitivity and specificity of EWS in predicting psychotic relapse was 71% and 64% (AUC value = 0.72). There was a large pooled-effect size for the model predicting relapse from individual symptom which did not reach statistical significance (d = 0.81, 95%CIs = -0.01, 1.63). CONCLUSIONS Important methodological advancements in the prediction of psychotic relapse in schizophrenia spectrum disorders are evident with improvements in the precision of prediction. Further efforts are required to translate these advances into effective clinical innovations.
Collapse
Affiliation(s)
- J F Gleeson
- Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Fitzroy, VIC, Australia.
| | - T B McGuckian
- Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Fitzroy, VIC, Australia
| | - D K Fernandez
- Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Fitzroy, VIC, Australia
| | - M I Fraser
- Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Fitzroy, VIC, Australia
| | - A Pepe
- Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Fitzroy, VIC, Australia
| | - R Taskis
- Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Fitzroy, VIC, Australia
| | - M Alvarez-Jimenez
- Orygen, Parkville, VIC, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - J F Farhall
- Department of Psychology and Counselling, La Trobe University, Melbourne, VIC, Australia
| | - A Gumley
- Glasgow Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| |
Collapse
|
4
|
Allan S, Beedie S, McLeod HJ, Farhall J, Gleeson J, Bradstreet S, Morton E, Bell I, Wilson-Kay A, Whitehill H, Matrunola C, Thomson D, Clark A, Gumley A. Using EMPOWER in daily life: a qualitative investigation of implementation experiences. BMC Psychiatry 2023; 23:597. [PMID: 37592231 PMCID: PMC10433590 DOI: 10.1186/s12888-023-05096-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 08/08/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Digital self-management tools blended with clinical triage and peer support have the potential to improve access to early warning signs (EWS) based relapse prevention in schizophrenia care. However, the implementation of digital interventions in psychosis can be poor. Traditionally, research focused on understanding how people implement interventions has focused on the perspectives of mental health staff. Digital interventions are becoming more commonly used by patients within the context of daily life, which means there is a need to understand implementation from the perspectives of patients and carers. METHODS Semi-structured one-on-one interviews with 16 patients who had access to the EMPOWER digital self-management intervention during their participation in a feasibility trial, six mental health staff members who supported the patients and were enrolled in the trial, and one carer participant. Interviews focused on understanding implementation, including barriers and facilitators. Data were coded using thematic analysis. RESULTS The intervention was well implemented, and EMPOWER was typically perceived positively by patients, mental health staff and the carer we spoke to. However, some patients reported negative views and reported ideas for intervention improvement. Patients reported valuing that the app afforded them access to things like information or increased social contact from peer support workers that went above and beyond that offered in routine care. Patients seemed motivated to continue implementing EMPOWER in daily life when they perceived it was creating positive change to their wellbeing, but seemed less motivated if this did not occur. Mental health staff and carer views suggest they developed increased confidence patients could self-manage and valued using the fact that people they support were using the EMPOWER intervention to open up conversations about self-management and wellbeing. CONCLUSIONS The findings from this study suggest peer worker supported digital self-management like EMPOWER has the potential to be implemented. Further evaluations of these interventions are warranted, and conducting qualitative research on the feasibility gives insight into implementation barriers and facilitators, improving the likelihood of interventions being usable. In particular, the views of patients who demonstrated low usage levels would be valuable.
Collapse
Affiliation(s)
| | | | | | | | - John Gleeson
- Australian Catholic University, Melbourne, Australia
| | | | - Emma Morton
- University of British Columbia, Vancouver, Canada
| | - Imogen Bell
- Orygen Centre of Youth Mental Health, Melbourne, Australia
| | | | | | | | | | | | | |
Collapse
|
5
|
Yu H, Sun YJ, Qin MN, Ren JX, Yu K, Song J, Zhou YQ, Liu L. Perception of risk of relapse among patients with first episode and recurrent schizophrenia: a descriptive phenomenological study. BMC Psychiatry 2023; 23:582. [PMID: 37563579 PMCID: PMC10413637 DOI: 10.1186/s12888-023-05023-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 07/12/2023] [Indexed: 08/12/2023] Open
Abstract
BACKGROUND Patients suffering from schizophrenia are at a higher risk of relapse. The perception of the risk of relapse in patients is critical for relapse prevention. In the field of psychiatry, the study of risk perception of relapse has been neglected. METHODS We carried out a qualitative study using a descriptive phenomenological approach. Data were collected at two psychiatric hospitals in China. In total, 22 patients with schizophrenia were recruited through purposive sampling. Face to face semi-structured in-depth interviews were conducted. Interview recordings were transcribed by the research team, and transcripts were analysed by two independent coders with Colaizzi's descriptive analysis framework. The consolidated criteria for reporting qualitative research checklist were used for reporting. RESULTS The data of first-episode patients yielded three themes: (i) lack of knowledge about disease recognition and medical treatment; (ii) overoptimistic estimation of the risk of relapse; (iii) perceived importance of treatment. For first-relapse patients : (i) initial awareness of relapse warning signs; (ii) lack of systematic and accurate assessment of disease information; (iii) the perception that drug withdrawal is related to relapse. Patients with multiple relapses: (i) susceptibility to relapse: confusion and powerlessness; (ii) the severity of relapse: suicidal thoughts and behavior; (iii) effects of perceived benefits and barriers of medication behaviour. CONCLUSIONS In schizophrenic patients with first-episode, first-relapse, and multiple relapses, there were dynamic changes in the perception of disease relapse risk and medication behaviour. Medical workers must improve risk awareness education. They should provide patients with scientific, accurate, and timely communication channels, and dynamically assess and manage the risk of relapse in various patients.
Collapse
Affiliation(s)
- Hong Yu
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China
| | - Yu-Jing Sun
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China
| | - Meng-Nan Qin
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China
| | - Jia-Xin Ren
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China
| | - Kai Yu
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China
| | - Jin Song
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China
| | - Yu-Qiu Zhou
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China.
| | - Li Liu
- Department of Nursing, Harbin Medical University Daqing Campus, Heilongjiang, 163319, Daqing, China
| |
Collapse
|