@article{rigasOptimizingFutureTelehealth2026,

title = {Optimizing future Telehealth mental health programs: a secondary analysis of a prospective cohort study to identify key predictors of intervention response in the Telehealth intervention program for older adults (TIP-OA)},

author = {C. Rigas and P. Lavin and C. -L. Su and M. Hassan and K. Cinalioglu and B. Vacaflor and E. Dikaios and A. Goodman and M. Ibrahim and J. Gruber and J. Se and N. Sasi and R. Nazar and K. Bodenstein and S. Elbaz and H. Fajzel and S. Berkani and C. Hanganu and H. Noble and K. Looper and S. Bouchard and D. Seitz and S. Kumar and O. Beauchet and C. Launay and E. McDonald and B. Khoury and A. Ryder and B. Battistini and P. Fallavollita and I. Vahia and H. Sekhon and S. Bukhari and S. Rej},

url = {https://www.scopus.com/pages/publications/105038539121?origin=resultslist},

doi = {10.1186/s12888-025-07688-1},

issn = {1471244X (ISSN)},

year  = {2026},

date = {2026-01-01},

journal = {BMC Psychiatry},

volume = {26},

number = {1},

publisher = {BioMed Central Ltd},

abstract = {Background: The Telehealth Intervention Program for Older Adults (TIP-OA) was a volunteer-based phone support program for to older adults during the COVID-19 pandemic. While volunteer-based phone programs can be effective in providing mental health support, there is limited data on the predictors of response to such interventions. This study aimed to examine clinical and demographic predictors of response to the TIP-OA intervention among older adults. Methods: This secondary analysis of a prospective cohort study included 82 TIP-OA users who expressed interest in the program’s research component, met inclusion criteria, and provided informed consent. Participants completed both baseline and 8-week assessments or had 4-week data carried forward using the last observation carried forward (LOCF) method. The intervention consisted of weekly supportive phone calls over eight weeks. Baseline mental health risk level was assessed by clinicians during intake and categorized as low, medium, or high based on symptom severity within specific symptom categories. Associations between baseline risk level and changes in stress (primary outcome), depression, and anxiety (secondary outcomes) were examined. The primary outcome was measured by the Perceived Stress Scale (PSS; scores ranging from 0 (never) to 4 (very often)). Secondary outcomes were measured by the Patient Health Questionnaire-9 (PHQ-9; scores ranging from 0 (not at all) to 3 (nearly every day)), and the Generalized Anxiety Disorder-7 scale (GAD-7; scores can range from 0 (not at all sure) to 3 (nearly every day)). Results: At 8 -week follow-up assessment, participants with higher baseline risk levels showed greater reductions in stress (mean difference in Perceived Stress Scale reduction by 2.13, (F(1,77) = 2.82},

keywords = {80 and over, adult, aged, Anxiety, article, clinical outcome, clinician, cohort analysis, coronavirus disease 2019, COVID-19, demographics, Depression, female, Generalized Anxiety Disorder-7, Geriatric mental health, health hazard, health program, human, human experiment, Humans, informed consent, male, Mental health, Mental Health Teletherapy, mental stress, older adults, Patient Health Questionnaire 9, Perceived Stress Scale, physiological stress, prediction, Predictors of treatment response, Prospective Studies, prospective study, Psychological, psychology, SARS-CoV-2, secondary analysis, Severe acute respiratory syndrome coronavirus 2, Social isolation, social worker, Stress, telehealth, Telemedicine, teletherapy, Therapy, treatment response, very elderly, Volunteer-based intervention},

pubstate = {published},

tppubtype = {article}

}

@article{ansado_how_2021,

title = {How brain imaging provides predictive biomarkers for therapeutic success in the context of virtual reality cognitive training},

author = {J. Ansado and C. Chasen and S. Bouchard and G. Northoff},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089070480&doi=10.1016%2fj.neubiorev.2020.05.018&partnerID=40&md5=8e5ea676958e050b32a893830dbc2a93},

doi = {10.1016/j.neubiorev.2020.05.018},

issn = {01497634},

year  = {2021},

date = {2021-01-01},

journal = {Neuroscience and Biobehavioral Reviews},

volume = {120},

pages = {583–594},

publisher = {Elsevier Ltd},

abstract = {As Virtual reality (VR) is increasingly used in neurological disorders such as stroke, traumatic brain injury, or attention deficit disorder, the question of how it impacts the brain's neuronal activity and function becomes essential. VR can be combined with neuroimaging to offer invaluable insight into how the targeted brain areas respond to stimulation during neurorehabilitation training. That, in turn, could eventually serve as a predictive marker for therapeutic success. Functional magnetic resonance imaging (fMRI) identified neuronal activity related to blood flow to reveal with a high spatial resolution how activation patterns change, and restructuring occurs after VR training. Portable and quiet, electroencephalography (EEG) conveniently allows the clinician to track spontaneous electrical brain activity in high temporal resolution. Then, functional near-infrared spectroscopy (fNIRS) combines the spatial precision level of fMRIs with the portability and high temporal resolution of EEG to constitute an ideal measuring tool in virtual environments (VEs). This narrative review explores the role of VR and concurrent neuroimaging in cognitive rehabilitation. © 2020 Elsevier Ltd},

note = {Publisher: Elsevier Ltd},

keywords = {accuracy, attention deficit disorder, biological monitoring, brain depth stimulation, brain electrophysiology, brain radiography, brain region, cell function, cerebrovascular accident, clinician, cognition, Cognitive rehabilitation, disease marker, electroencephalogram, Electroencephalography, functional magnetic resonance imaging, functional near-infrared spectroscopy, human, image quality, in vivo study, nerve cell, neuroimaging, neurologic disease, neuropsychological test, neuropsychology, neurorehabilitation, nonhuman, prediction, priority journal, review, therapy effect, training, traumatic brain injury, virtual reality, virtual reality cognitive training},

pubstate = {published},

tppubtype = {article}

}