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Experience sampling methods for the personalised prediction of mental health problems in Spanish university students: protocol for a survey-based observational study within the PROMES-U project

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dc.contributor.author Portillo-Van Diest, Ana
dc.contributor.author Ballester Coma, Laura
dc.contributor.author Mortier, Philippe
dc.contributor.author Vilagut Saiz, Gemma, 1975-
dc.contributor.author Amigo, Franco
dc.contributor.author Puértolas Gracia, Beatriz
dc.contributor.author García-Mieres, Helena
dc.contributor.author Alayo, Itxaso
dc.contributor.author Alonso Caballero, Jordi
dc.date.accessioned 2023-09-29T07:33:35Z
dc.date.available 2023-09-29T07:33:35Z
dc.date.issued 2023
dc.identifier.citation Portillo-Van Diest A, Ballester Coma L, Mortier P, Vilagut G, Amigo F, Puértolas Gracia B, et al. Experience sampling methods for the personalised prediction of mental health problems in Spanish university students: protocol for a survey-based observational study within the PROMES-U project. BMJ Open. 2023 Jul 14;13(7):e072641. DOI: 10.1136/bmjopen-2023-072641
dc.identifier.issn 2044-6055
dc.identifier.uri http://hdl.handle.net/10230/57994
dc.description.abstract Introduction: There is a high prevalence of mental health problems among university students. Better prediction and treatment access for this population is needed. In recent years, short-term dynamic factors, which can be assessed using experience sampling methods (ESM), have presented promising results for predicting mental health problems. Methods and analysis: Undergraduate students from five public universities in Spain are recruited to participate in two web-based surveys (at baseline and at 12-month follow-up). A subgroup of baseline participants is recruited through quota sampling to participate in a 15-day ESM study. The baseline survey collects information regarding distal risk factors, while the ESM study collects short-term dynamic factors such as affect, company or environment. Risk factors will be identified at an individual and population level using logistic regressions and population attributable risk proportions, respectively. Machine learning techniques will be used to develop predictive models for mental health problems. Dynamic structural equation modelling and multilevel mixed-effects models will be considered to develop a series of explanatory models for the occurrence of mental health problems. Ethics and dissemination: The project complies with national and international regulations, including the Declaration of Helsinki and the Code of Ethics, and has been approved by the IRB Parc de Salut Mar (2020/9198/I) and corresponding IRBs of all participating universities. All respondents are given information regarding access mental health services within their university and region. Individuals with positive responses on suicide items receive a specific alert with indications for consulting with a health professional. Participants are asked to provide informed consent separately for the web-based surveys and for the ESM study. Dissemination of results will include peer-reviewed scientific articles and participation in scientific congresses, reports with recommendations for universities' mental health policy makers, as well as a well-balanced communication strategy to the general public. Study registration: osf.io/p7csq.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher BMJ Publishing Group
dc.relation.ispartof BMJ Open. 2023 Jul 14;13(7):e072641
dc.rights © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
dc.title Experience sampling methods for the personalised prediction of mental health problems in Spanish university students: protocol for a survey-based observational study within the PROMES-U project
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1136/bmjopen-2023-072641
dc.subject.keyword Epidemiologic studies
dc.subject.keyword Mental health
dc.subject.keyword Public health
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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