Santiago Papini, PhD

People

Kaiser Permanente Division of Research
2000 Broadway
Oakland, CA 94612

510-891-3216 (phone)
santiago.x.papini@kp.org

Santiago Papini, PhD, received his doctorate in clinical psychology from The University of Texas at Austin and completed his internship at the VA San Diego Healthcare System. He joined DOR as a Delivery Science and Clinical Informatics Fellow and is also a recipient of the National Institute of Mental Health T32 grant, Embedded Mental Health Services Postdoctoral Research Training in Health Systems.

His research spans cross clinical trials for PTSD, substance use, and anxiety disorders, and translational research applying neuroimaging, psychophysiology, and experimental models of psychopathology. His NIH-funded dissertation research developed machine learning models of PTSD emergence and treatment response. As a Delivery Science and Clinical Informatics Fellow he aims to apply predictive modeling to facilitate targeted treatment approaches for psychiatric disorders.

Current Position(s):

Postdoctoral Research Fellow

Section Affiliations:

Primary Research Interests:

Machine learning and predictive modeling
Anxiety, stress, and substance use disorders
Targeted treatment dissemination

Studies

Development and validation of a prediction model of time to suicide attempt

Prediction models have the potential to transform targeted prevention strategies for suicide, a leading cause of death in the U.S. The work of our partners in the Mental Health Research Network demonstrated that predictive machine learning algorithms for suicide risk based on electronic health record data can accurately identify individuals with elevated suicide risk. However, a key limitation of current suicide prediction models is that the outcome window of prediction is 90 days post-visit. This means that current models do not necessarily distinguish between someone who is at imminent risk for suicide, and someone whose suicide attempt may occur months after the point of prediction. To address this limitation, we will develop models that predict time to suicide attempt and evaluate their overall performance, as well as performance across racial-ethnic categories where differences in suicide rates have been observed.
Investigator: Papini, Santiago
Funder: Northern California Community Benefit Programs

Predictive modeling of adverse mental health outcomes following acute hospitalizations for serious illness: A machine learning approach with natural language processing

This study addresses predicting risk of post-traumatic stress disorder and other mental health conditions following hospitalization for life-threatening conditions. We will use an existing, retrospective cohort of 408,377 patients hospitalized with severe illness, including sepsis, to develop and validate predictive models of mental health diagnoses using only electronic health record data, including features extracted with natural language processing from symptoms recorded in clinician notes.
Investigator: Papini, Santiago
Funder: Section Pilot Grants

Detection and Mitigation of Algorithmic Bias in Predictive Models of Suicide Risk

This project will assess the potential impact of algorithmic bias on the allocation of preventive care for suicide and compare the performance of methods designed to mitigate algorithmic bias.
Investigator: Papini, Santiago
Funder: Section Pilot Grants

Highlighted Publications

No results found matching criteria

Publications

Performance of a Prediction Model of Suicide Attempts Across Race and Ethnicity

Author(s): Papini, Santiago; Hsin, Honor; Kipnis, Patricia; Liu, Vincent X; Lu, Yun; Sterling, Stacy A; Iturralde, Esti

JAMA Psychiatry. 2023 Apr 01;80(4):399-400.

Current Position(s):

Section Affiliations:

Primary Research Interests:

Studies

Development and validation of a prediction model of time to suicide attempt

Predictive modeling of adverse mental health outcomes following acute hospitalizations for serious illness: A machine learning approach with natural language processing

Detection and Mitigation of Algorithmic Bias in Predictive Models of Suicide Risk

Highlighted Publications

Publications

Performance of a Prediction Model of Suicide Attempts Across Race and Ethnicity

Associations of polygenic risk scores with posttraumatic stress symptom trajectories following combat deployment

Posttraumatic stress disorder symptom trajectories in a 16-month COVID-19 pandemic period

Use of Cannabidiol (CBD) oil in the treatment of PTSD: Study design and rationale for a placebo-controlled randomized clinical trial

Comparing the effectiveness of a brief intervention to reduce unhealthy alcohol use among adult primary care patients with and without depression: A machine learning approach with augmented inverse probability weighting

Impact of cannabidiol-rich hemp extract oil on reconsolidation disruption of naturalistic interoceptive aversive memory in humans: Protocol for a randomized clinical trial

Exploratory and Confirmatory Bayesian Networks Identify the Central Role of Non-judging in Symptoms of Depression.

Distinct trajectories of depression symptoms in early and middle adolescence: Preliminary evidence from longitudinal network analysis.

Singular and combined effects of transcranial infrared laser stimulation and exposure therapy on pathological fear: a randomized clinical trial.

Community-based smoking cessation treatment for adults with high anxiety sensitivity: a randomized clinical trial.

Frustrative nonreward and cannabinoid receptors: Chronic (but not acute) WIN 55,212-2 treatment increased resistance to change in two reward downshift tasks.

Network analysis reveals the associations of past quit experiences on current smoking behavior and motivation to quit.

The impact of prior and ongoing threat on the false alarm threshold for facial discrimination.

Dose Timing of D-Cycloserine to Augment Exposure Therapy for Social Anxiety Disorder: A Randomized Clinical Trial.

Response-to-Treatment for Comorbid Post-Traumatic Stress and Substance Use Disorders: The Value of Combining Person- and Variable-Centered Approaches.

Isradipine enhancement of virtual reality cue exposure for smoking cessation: Rationale and study protocol for a double-blind randomized controlled trial.

Pretreatment Posttraumatic Stress Disorder Symptom Network Metrics Predict the Strength of the Association Between Node Change and Network Change During Treatment.

Enhancing panic and smoking reduction treatment with D-Cycloserine: A pilot randomized clinical trial.

Effect of d-cycloserine on fear extinction training in adults with social anxiety disorder.

Immersive 3D exposure-based treatment for spider fear: A randomized controlled trial.

Bias-contingent attention bias modification and attention control training in treatment of PTSD: a randomized control trial.

Ensemble machine learning prediction of posttraumatic stress disorder screening status after emergency room hospitalization.

Lagged effects of substance use on PTSD severity in a randomized controlled trial with modified prolonged exposure and relapse prevention.

Exposure-based therapy changes amygdala and hippocampus resting-state functional connectivity in patients with posttraumatic stress disorder.

Immersive 3D exposure-based treatment for spider fear: A randomized controlled trial.

Effect of cognitive bias modification-memory on depressive symptoms and autobiographical memory bias: two independent studies in high-ruminating and dysphoric samples.

Emotion dysregulation moderates the effect of cognitive behavior therapy with prolonged exposure for co-occurring PTSD and substance use disorders.

A randomized controlled study of power posing before public speaking exposure for social anxiety disorder: No evidence for augmentative effects.

Effects of acute exercise on fear extinction in rats and exposure therapy in humans: Null findings from five experiments.

Concurrent Treatment with Prolonged Exposure for Co-Occurring Full or Subthreshold Posttraumatic Stress Disorder and Substance Use Disorders: A Randomized Clinical Trial.

Identifying attendance patterns in a smoking cessation treatment and their relationships with quit success.

Impact of Cannabis Use on Treatment Outcomes among Adults Receiving Cognitive-Behavioral Treatment for PTSD and Substance Use Disorders.

Altered resting state functional connectivity of fear and reward circuitry in comorbid PTSD and major depression.

A cross species study of heterogeneity in fear extinction learning in relation to FKBP5 variation and expression: Implications for the acute treatment of posttraumatic stress disorder.

Chronic cannabis use is associated with impaired fear extinction in humans.

Neural changes in extinction recall following prolonged exposure treatment for PTSD: A longitudinal fMRI study.

Greater hippocampal volume is associated with PTSD treatment response.

PTSD REMISSION AFTER PROLONGED EXPOSURE TREATMENT IS ASSOCIATED WITH ANTERIOR CINGULATE CORTEX THINNING AND VOLUME REDUCTION.

Pathways to change: Use trajectories following trauma-informed treatment of women with co-occurring post-traumatic stress disorder and substance use disorders.

Combining seeking safety with sertraline for PTSD and alcohol use disorders: A randomized controlled trial.

Linguistic characteristics in a non-trauma-related narrative task are associated with PTSD diagnosis and symptom severity.

Toward a translational approach to targeting the endocannabinoid system in posttraumatic stress disorder: a critical review of preclinical research.

At the crossroads: the intersection of substance use disorders, anxiety disorders, and posttraumatic stress disorder.

Psychometric Properties of the Modified Posttraumatic Stress Disorder Symptom Scale among Women with Posttraumatic Stress Disorder and Substance Use Disorders Receiving Outpatient Group Treatments.

Identifying profiles of recovery from reward devaluation in rats.