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
Gemma Vilagut,
Jordi Alonso,
Miquel Roca,
Philippe Mortier,
Beatriz Puértolas Gracia,
Laura Ballester Coma,
Margalida Gili,
Marisa Rebagliato,
Jose A Piqueras,
Franco Amigo,
Ana Portillo-Van Diest,
Helena García-Mieres,
Itxaso Alayo,
Maria Jesus Blasco,
Paula Carrasco Espi,
Raquel Falcó,
Ines Forteza-Rey,
Patricia Garcia-Pazo,
Cristina Giménez-García,
Francisco H Machancoses,
Juan Carlos Marzo Campos,
Guillem Navarra-Ventura,
Tiscar Rodriguez Jiménez,
Lorenzo Roldan,
Estefanía Ruiz-Palomino,
Victoria Soto-Sanz
Affiliations
Gemma Vilagut
CIBERESP, Madrid, Comunidad de Madrid, Spain
Jordi Alonso
Health Services Research Group, Institut Hospital del Mar d`Investigacions Mediques, Barcelona, Spain
Miquel Roca
IdISBa, Palma de Mallorca, Illes Balears, Spain
Philippe Mortier
Health Services Research Group, Institut Hospital del Mar d`Investigacions Mediques, Barcelona, Spain
Beatriz Puértolas Gracia
CIBERESP, Madrid, Comunidad de Madrid, Spain
Laura Ballester Coma
Health Services Research Group, Institut Hospital del Mar d`Investigacions Mediques, Barcelona, Spain
Margalida Gili
IdISBa, Palma de Mallorca, Illes Balears, Spain
Marisa Rebagliato
CIBERESP, Madrid, Comunidad de Madrid, Spain
Jose A Piqueras
Department of Health Psychology, Miguel Hernandez University of Elche, Elche, Spain
Franco Amigo
CIBERESP, Madrid, Comunidad de Madrid, Spain
Ana Portillo-Van Diest
Health Services Research Group, Institut Hospital del Mar d`Investigacions Mediques, Barcelona, Spain
Helena García-Mieres
Health Services Research Group, Institut Hospital del Mar d`Investigacions Mediques, Barcelona, Spain
Itxaso Alayo
Health Services Research Group, Institut Hospital del Mar d`Investigacions Mediques, Barcelona, Spain
Maria Jesus Blasco
Hospital Provincial Castellon, Castellon de la Plana, Valenciana, Spain
Paula Carrasco Espi
Department of Medicine, Universitat Jaume I, Castello de la Plana, Spain
Raquel Falcó
Department of Health Psychology, Miguel Hernandez University of Elche, Elche, Spain
Ines Forteza-Rey
IdISBa, Palma de Mallorca, Illes Balears, Spain
Patricia Garcia-Pazo
Department of Nursing and Physiotherapy, Universitat de les Illes Balears, Palma de Mallorca, Illes Balears, Spain
Cristina Giménez-García
Department of Basic and Clinical Psychology, Science Health Faculty, Universitat Jaume I, Castello de la Plana, Castelló, Spain
Francisco H Machancoses
Predepartamental Unit of Medicine, Science Health Faculty, Universitat Jaume I, Castello de la Plana, Comunitat Valenciana, Spain
Juan Carlos Marzo Campos
Department of Health Psychology, Miguel Hernandez University of Elche, Elche, Spain
Guillem Navarra-Ventura
IdISBa, Palma de Mallorca, Illes Balears, Spain
Tiscar Rodriguez Jiménez
Department of Psychology and Sociology, University of Zaragoza, Zaragoza, Spain
Lorenzo Roldan
IdISBa, Palma de Mallorca, Illes Balears, Spain
Estefanía Ruiz-Palomino
Department of Basic and Clinical Psychology, Science Health Faculty, Universitat Jaume I, Castello de la Plana, Castelló, Spain
Victoria Soto-Sanz
Department of Health Psychology, Miguel Hernandez University of Elche, Elche, Spain
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.