SOLITAIRE – Digital Interventions for Social Isolation in Youths and Their Families

SOLITAIRE – Digital Interventions for Social Isolation in Youths and Their Families Overview This repository is part of the project "SOLITAIRE - Digital Interventions for Social Isolation in Youths and Their Families", funded by the European Union – Next Generation EU – NRRP M6C2 – Investment 2.1 Enhancement and Strengthening of Biomedical Research within the Italian National Health Service (SSN). Project code: PNRR-MAD-2022-12376834CUP: E33C22001020006Principal Investigator: Marcella Bellani SOLITAIRE is a multicenter research project aimed at developing, implementing, and evaluating innovative digital interventions for adolescents and young adults experiencing moderate-to-severe social isolation, as well as for their family members. The project integrates clinical psychiatry, developmental neuropsychiatry, cognitive neuroscience, machine learning, and translational neuroscience approaches. UO1 – Coordinating CenterPsychiatry Unit, Azienda Ospedaliera Universitaria Integrata Verona (Italy)Principal Investigator: Marcella Bellani UO2Unit for Severe Disabilities in Developmental Age and Young Adulthood, IRCCS Eugenio Medea, Apulia Scientific Center, Brindisi (Italy)Responsible Investigator: Isabella Fanizza UO3Department of Computer Science and Department of Pathophysiology and Transplantation, University of Milan (Italy)Responsible Investigator: Antonella delle Fave UO4Institute of Neuroscience, National Research Council (CNR), Milan (Italy)Responsible Investigator: Fabrizia GuarnieriThe SOLITAIRE Group: Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy & Azienda Ospedaliera Universitaria Integrata Verona, Verona, Italy: Marcella Bellani, Maria Gloria Rossetti, Cinzia Perlini, Francesca Girelli, Niccolò Zovetti, Maria Diletta Buio; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy: Paolo Brambilla, Cinzia Bressi, Antonella delle Fave, Virginia Pupi; CNR Institute of Neuroscience, Vedano al Lambro, Italy: Fabrizia Guarnieri, Edoardo Moretto; Department of Computer Science, University of Milan, Milan, Italy: Roberto Sassi, Maria Renata Guarneri, Stavros Ntalampiras, Samara Soares Leal; Unit for Severe Disabilities in Developmental Age and Young Adults, Associazione La Nostra Famiglia - IRCCS E. Medea, Scientific Hospital for Neurorehabilitation, Brindisi, Italy: Isabella Fanizza, Lara Scialpi, Giorgia Carlucci, Mariangela Leucci; Scientific Institute IRCCS Eugenio Medea, Scientific Direction, Bosisio Parini, Lecco, Italy: Antonio Trabacca. Repository contents This repository contains the anonymized dataset, metadata, and Stata code associated with the publication by Rossetti et al. (2025). How to cite If you use this resource, please cite both the associated publication and this Zenodo record. Associated publication Rossetti, M. G., Girelli, F., Zovetti, N., Fanizza, I., delle Fave, A., Guarnieri, F. C., Brambilla, P., Trabacca, A., & Bellani, M. (2025). Social Isolation in Youth: A Public Health Challenge and the Emerging Role of Telepsychotherapy. In Loneliness – The Ultimate Suffering in Modern Society. IntechOpen. https://doi.org/10.5772/intechopen.1013387 Zenodo record Rossetti, M. G., Girelli, F., Zovetti, N., Fanizza, I., delle Fave, A., Guarnieri, F. C., Brambilla, P., Trabacca, A., & Bellani, M. (2026). SOLITAIRE – Adults CBT Telepsychotherapy Dataset and Analysis Code. Zenodo. DOI: https://doi.org/10.5281/zenodo.20526320. Repository relationship This repository is associated with two SOLITAIRE project sub-repositories: 1) Speech Features and Machine Learning Pipeline for Depression Recognition Associated publication: Leal, S. S., Ntalampiras, S., Rossetti, M. G., Trabacca, A., Bellani, M., & Sassi, R. (2025). Speech-Based Depression Recognition in Hikikomori Patients Undergoing Cognitive Behavioral Therapy. Applied Sciences, 15(21), 11750. https://doi.org/10.3390/app152111750 Zenodo DOI: https://doi.org/10.5281/zenodo.20099145 2) SOLITAIRE Adults T0 Dataset on Hikikomori, Basic Psychological Needs, and Parental Bonding Associated publication: Pupi, V., Bressi, C., Brambilla, P., Rossetti, M. G., Perlini, C., Girelli, F., Buio, M. D., Zovetti, N., Fanizza, I., Trabacca, A., Guarnieri, F. C., Sassi, R., Bellani, M., & Delle Fave, A. (2026). Basic Psychological Needs and Parental Bonding in Italian Adults at High Risk of Hikikomori (Extreme Social Withdrawal): The Distinctive Association of Competence Frustration with Symptom Severity. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1738750 Zenodo DOI: https://doi.org/10.5281/zenodo.20418021 Data contents data/ Rossetti_2025_dataset.xlsx syntax/ Rossetti_2025_analysis.do documentation/ README.md LICENSE_NOTE.txt CITATION.cffCITATION.cff Expected data format The dataset is organized in wide format, with one row per anonymized participant. Variable labels, descriptions, and formats are reported in the data dictionary worksheet included in the dataset file. The dataset includes: - anonymized participant identifiers;- randomization group;- participant status;- sociodemographic variables;- baseline and post-intervention clinical measures;- baseline and post-intervention psychological measures. Syntax summary The `syntax/`folder contains Stata code used to reproduce the statistical analyses reported in the associated publication. The code supports the following steps: 1. participant selection procedures;2. descriptive statistics of baseline sample characteristics;3. linear regression analyses testing baseline predictors of social isolation;4. paired-sample t-tests evaluating pre-post treatment changes;5. generation of figures reported in the publication. Ethical and access notes This repository contains only anonymized data. No directly identifiable participant information is included. The dataset was derived from participants enrolled in the SOLITAIRE project and shared in accordance with applicable ethical approvals and data protection regulations. License - Dataset: CC BY 4.0;- Documentation: CC BY 4.0;- Stata code: MIT License Versioning If dataset files, metadata, code, or documentation are updated in the future, a new Zenodo version may be released while preserving the same concept DOI.