The implementation of Digital Mobile Mental Health in clinical care pathways: Towards person-centered care in psychiatry

Leistungen

Set of basic statistics for direct implementation and visualization

To obtain the basic statistics for visualization in WP2 and implemented in WP7 as well as to provide a solid baseline to which to compare the more advanced methods below WP4 will first focus on simple quick to compute statistically robust low standard error and easy to interpret statistics that describe distributional properties of the data and covariation between different feature dimensions These involve mean levels and variability of symptomscontextual factors over time as indicators of symptomcontext level and volatility and their mutual comparison to detect key personalized strengths and weaknesses Next they involve simple statistical time series tools for tracking symptoms and contextual factors and their correlations over time such as autoregressive movingaverage ARMA models or measures of mutual predictability Granger causality allowing to obtain basic insight into how symptomscontext variables cooccur or predict one another over time Finally to capture clinically significant moments of change or tipping points within the behavioural trajectories as they are unfolding across larger periods of time WP4 will use statistical change point detection techniques as developed in Leuven eg 138 and Mannheim eg 139 to detect reliable phase changes in mean levels as a function of for instance instalment of treatment or a particular change in treatment over time Methods for the correction of familywise error rate such as the HolmBonferroni procedure regularization techniques in model estimation and measures of outofsample prediction error will be adopted to minimize the risk of false positives to inform clinical decision making Outcomes from lowerlevel statistics and machine learning predictors will be summarized and delivered to the visualization platform in a clinically meaningful and accessible way

Report on Technology Context and Self-tracking Practices

This report will consist of two papers one paper that reports the full results of the survey conducted in Task 51 and one paper that reports qualitative and quantitative findings from Task 52

Consolidated descriptions of interventions and implementation strategies for each of the participating sites

Jointly with WP5 stakeholder engagement and other work packages ie WP24 WP6 we will first specify and optimize our strategies for implementation of the DMMH into practice The chosen implementation strategies will includea the DMMH information technology system which adheres to prevailing standards and regulations particularly regarding data protectionb an intervention manual consistent with the Template for Intervention Description and Replication Checklist training and support package for clinicians and services to facilitate the use of the DMMH with service usersc a wellbalanced package of tailored information counselling and reminders for service users to motivate and enable them to use the DMMHThese strategies will purposefully vary somewhat between the different clinical sites to address local requirements A detailed factual description of the DMMH intervention and implementation strategies as planned will be tailored to and optimized based on the requirements of each site Building on the work carried out in WP5 stakeholder engagement we will generate an a priori assessment of anticipated barriers and facilitators that influence implementation using the nonadoption abandonment scaleup spread and sustainability NASSS implementation science framework84 This has been specifically proposed for the implementation of novel technologies and will be used to optimize in close collaboration with WP5 the DMMH implementation strategies with regard to the 7 domains of this framework the condition or illness ie a mental disorder the technology the value proposition the adopter system comprising professional staff service users and informal caregivers the organizations the wider institutional and societal context and the interaction and mutual adaptation between all these domains over time Findings from the qualitative framework analysis method which has been designed to inform policy will directly inform tailoring of our implementation strategies to local requirements These will be further adopted and finalized based on findings from other work packages ie WP24 WP6 prior to the start of the cRCT

H - Requirement No. 12

For each clinical study the following documentsinformation must be submitted as a deliverable in one package prior to enrolment of first study subject i Final version of study protocol as submitted to regulatorsethics committees ii Registration number of clinical study in a WHO or ICMJEapproved registry with the possibility to post results iii Approvals ethics committees and national competent authority if applicable required for invitationenrolment of first subject in at least one clinical centre

Data Management Plan

WP3 will provide a comprehensive data management plan based on the Horizon 2020 template DMP The DMP will cover aspects of data acquisition processing quality control data privacy aspects metadata annotation data deposition licensing and usage policy according to the FAIR guiding principles The DMP will provide as appendices an inventory of data elements processed during the project and a threat analysis regarding data privacy

Veröffentlichungen

The European Health Data Space: Too Big To Succeed?

Autoren: Marelli, L., Stevens, M., Sharon, T., Van Hoyweghen, I., Boeckhout, M., Colussi, I., ... & Southerington, T.
Veröffentlicht in: Health Policy, Ausgabe 104861, 2023, ISSN 0922-3444
Herausgeber: Elsevier
DOI: 10.1016/j.healthpol.2023.104861

Využitie mobilných technológií v liečbe psychických porúch: Projekt IMMERSE

Autoren: Kurilla, A., Dančík, D., Čavojská, N., Izáková, Ľ., Pečeňák, J., Hajdúk, M., Heretik, A.
Veröffentlicht in: Psychiatria pre prax, Ausgabe 23(4), 2022, Seite(n) 163-166, ISSN 1335-9584
Herausgeber: SOLEN Medical Education

Using Experience Sampling Methods to support clinical management of psychosis: The perspective of people with lived experience.

Autoren: de Thurah L, Kiekens G, Sips R, Teixeira A, Kasanova Z, Myin-Germeys I
Veröffentlicht in: Psychiatry Research, Ausgabe 324, 2023, Seite(n) 115207, ISSN 0165-1781
Herausgeber: Elsevier BV
DOI: 10.1016/j.psychres.2023.115207

Can digital tools improve clinical care in psychiatry?

Autoren: Myin-Germeys, I.
Veröffentlicht in: DUSUNEN ADAM-JOURNAL OF PSYCHIATRY AND NEUROLOGICAL SCIENCES, Ausgabe 36, 2023, Seite(n) 1-3, ISSN 1018-8681
Herausgeber: Bakirkoy Research and Training Hospital for Psychiatry, Neurology and Neurosurgery
DOI: 10.14744/dajpns.2022.00200

mHealth in psychiatry: A pathway to person-centered care

Autoren: Myin-Germeys, I.
Veröffentlicht in: Psychiatry Research, Ausgabe 319, 2023, Seite(n) 114978, ISSN 0165-1781
Herausgeber: Elsevier BV
DOI: 10.1016/j.psychres.2022.114978

Weaving EU digital health policy into national healthcare practices. The making of a reimbursement standard for digital health technologies in Belgium

Autoren: Lievevrouw, E., Marelli, L. & Van Hoyweghen, I.
Veröffentlicht in: Social Science & Medicine, Ausgabe 346, 2024, Seite(n) 116620, ISSN 0277-9536
Herausgeber: Pergamon Press Ltd.
DOI: 10.1016/j.socscimed.2024.116620

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