BSSM Data Core Member Martina Luchetti
- Email:m artina.luchetti@med.fsu.edu
- Software: SPSS, Mplus, Excel, GPower, Redcap, Qualtrics, Other (R: only for adjusting existing syntaxes)
- Study Type: Cross-sectional studies, Case-control studies, Cohort studies / longitudinal studies
- Unfavorite Study Type: Cross-sectional studies
- Study Component: Research idea initiating and/or research question/hypothesis generating, Questionnaire or other measurement designing, Data collecting, Data analyses
- Unfavorite Study Component: Data cleaning, Data integrating (combining & merging)
- Analysis Method: Basic descriptive statistical analyses, t-test, Chi-squared test, Correlation, ANOVA, ANCOVA, Multiple linear regression, Logistic regression, Multilevel models/Mixed models, Structural equation modeling, Meta-analysis, Other (Analytic approaches to address intensive longitudinal assessment (ecological momentary assessments))
- Interested Population:Aging adults 40+, caregivers, patients from memory clinics (reporting subjective complaints or cognitive impairment)
- Interested Topic:Personality, loneliness, cognitive/memory function, classification of cognitive status, dementia, some biomarkers (e.g., CRP), health behaviors, smartphone-based assessments of cognition, feelings and behaviors
- Collaboration Availability: Research topic
- Time Availability: Other (For collaboration and actual work depending on the research topic)
- Self-Description: In my past work, I have applied longitudinal methodologies to identify psychological factors (e.g., personality) that contribute to memory and cognitive health across the adult lifespan. In recent years, I specifically directed attention to socio-relational factors, particularly loneliness, that affect risk of late-life cognitive impairment and dementia (Luchetti et al., 2020, Int J Geriatr Psychiatry; Sutin et al., 2023, Int Psychogeriatr) and focused on relational dynamics, within spouses (Luchetti et al. 2022, J Gerontol B Psychol Sci) and caregivers (Luchetti et al., 2021, Aging Mental Health). My expertise pertains aging and cognition, and use of ambulatory assessments is fundamental to the project. II have experience in the use of large and complex datasets (e.g., Health and Retirement Study and other public aging cohorts), and application of advanced statistical models in Mplus(e.g., latent change models).
Since 2015, I work as a Faculty at the Florida State University in close collaboration with co-investigators, Drs. Sutin and Terracciano.