Samsuk Kim, PhD.
Postdoctoral Scholar, Anesthesiology, Perioperative and Pain Medicine
Bio
Dr. Samsuk Kim is a dual research and clinical T32 fellow at Stanford University. She earned her PhD in Clinical Psychology from the University of Detroit Mercy and completed external research training at the University of Michigan (Kratz Lab), where she studied psychosocial factors—such as mindfulness and pain acceptance—in chronic pain. She also completed an APA-accredited internship at the VA Boston Healthcare System. Clinically, Dr. Kim specializes in pain management, health promotion, adjustment-related challenges, and emotional regulation. She draws from a range of evidence-based treatments, including Cognitive Behavioral Therapy (CBT), Acceptance and Commitment Therapy (ACT), mindfulness-based interventions, Dialectical Behavior Therapy (DBT), and interpersonal psychotherapy. Her current research focuses on understanding the bidirectional relationship between sleep and pain and developing personalized, digital interventions to improve outcomes in both domains.
Professional Education
-
Doctor of Philosophy, University of Detroit Mercy (2023)
-
Internship, VA Boston Healthcare System, Clinical Psychology (2023)
-
Master of Arts, University of Detroit Mercy (2020)
-
Master of Science, University of Michigan Dearborn (2017)
Research Interests
-
Psychology
Lab Affiliations
Graduate and Fellowship Programs
-
Pain Management (Fellowship Program)
All Publications
-
Optimism and Cognitive Functioning Trajectories in a Cohort of Aging Men.
The journals of gerontology. Series B, Psychological sciences and social sciences
2025
Abstract
Robust evidence supports optimism as an asset for good physical and emotional health in aging populations, but its role in cognitive aging remains understudied. This study evaluated whether higher optimism levels would be prospectively associated with higher initial levels and slower decline in cognitive functioning over 26 years in a community-dwelling cohort of aging men.Participants included 847 men from the Veterans Affairs Normative Aging Study who completed the Revised Optimism-Pessimism scale of the Minnesota Multiphasic Personality Inventory-2 in 1986 and ≥1 cognitive assessment repeated triennially in 1993-2019. At each assessment, scores from 7 cognitive tests were combined into a global composite and 3 domain-specific composites: verbal memory, executive functioning, and visuospatial ability. Mixed-effects regression models evaluated the associations between optimism and cognitive trajectories.Higher optimism levels were associated with higher initial levels but not less decline in global cognitive functioning over time (B = 0.04, 95%CI: 0.001, 0.07), adjusted for demographics, practice effects, and lag between optimism assessment and the first cognitive assessment. In domain-specific analyses, optimism was associated with higher initial levels but not magnitude of decline in verbal memory (B = 0.06, 95%CI: 0.01, 0.12), and unrelated to executive functioning or visuospatial ability trajectories.This study adds specificity to a nascent literature linking optimism to cognitive aging, indicating an association with initial levels, but not decline-particularly in verbal memory-in older men. Examining these relationships earlier in life may further clarify the etiologic role of optimism in cognitive health across the developmental span.
View details for DOI 10.1093/geronb/gbaf139
View details for PubMedID 40711855
-
Revealing sleep and pain reciprocity with wearables and machine learning.
Communications medicine
2025; 5 (1): 160
Abstract
Sleep disturbance and chronic pain share a bidirectional relationship with poor sleep exacerbating pain and pain disrupting sleep. Despite the substantial burden of sleep disturbance and pain, current treatments fail to address their interplay effectively, largely due to the lack of longitudinal data capturing their complex dynamics. Traditional sleep measurement methods that could be used to quantitate daily changes in sleep, such as polysomnography, are costly and unsuitable for large-scale studies in chronic pain populations. New wearable polysomnography devices combined with machine learning algorithms offer a scalable solution, enabling comprehensive, longitudinal analyses of sleep-pain dynamics. In this Perspective, we highlight how these technologies can overcome current limitations in sleep assessment to uncover mechanisms linking sleep and pain. These tools could transform our understanding of the sleep and pain relationship and guide the development of personalized, data-driven treatments.
View details for DOI 10.1038/s43856-025-00886-8
View details for PubMedID 40335627
View details for PubMedCentralID 7527024
-
Impact of Pain Self-Efficacy on Health Outcomes in High-Impact Chronic Pain: A Longitudinal Study.
The Clinical journal of pain
2025
Abstract
High-impact chronic pain (HICP), affecting 36.4% of individuals with chronic pain, significantly limits work, social, and self-care activities. Effective treatments for HICP remain elusive. In addition to pain catastrophizing, growing evidence suggests that pain self-efficacy may be a treatment target for HICP. Our study examines the relative contributions of pain self-efficacy and catastrophizing to health outcomes in patients with HICP.A total of 259 patients with chronic pain (154 with HICP; 105 without HICP) completed validated measures at baseline and three months later. These included the Chronic Pain Self-Efficacy Scale (CPSS), the Pain Catastrophizing Scale (PCS), and Patient-Reported Outcomes Measurement Information System (PROMIS) domains for physical health (i.e., pain interference, physical function, fatigue, and sleep disturbance) and psychosocial health (i.e., depression, anxiety, anger, and social isolation).Repeated measures MANOVA showed a significant group effect (HICP vs. No-HICP), but no significant time or group by time interaction effect. The HICP group reported significantly lower CPSS scores and higher PCS scores than the No-HICP group, alongside worse physical and psychosocial health outcomes (η²=0.076~0.445). Pain self-efficacy explained a greater proportion of group differences in health outcomes (52.9-71.7%) compared to pain catastrophizing (10.1-43.3%). Especially, self-efficacy in activity engagement accounted for the largest health disparities between the groups.Findings highlight pain self-efficacy as a critical treatment target for HICP, with greater predictive utility than pain catastrophizing. Enhancing self-efficacy through tailored interventions may reduce the burden of HICP. Future studies should prioritize self-efficacy-based interventions and explore their scalability and long-term impact.
View details for DOI 10.1097/AJP.0000000000001295
View details for PubMedID 40325564
-
Pain Self-Efficacy and Pain Catastrophizing as Predictors of Health Outcomes in Patients with Chronic Pain
CHURCHILL LIVINGSTONE. 2025
View details for DOI 10.1016/j.jpain.2025.105210
View details for Web of Science ID 001502651300002
-
Treatment Mediators of Sleep Improvement after Skills-based Behavioral Interventions for Chronic Low Back Pain: A Secondary Analysis of a Randomized Clinical Trial
CHURCHILL LIVINGSTONE. 2025
View details for DOI 10.1016/j.jpain.2025.105222
View details for Web of Science ID 001502651300046
-
Impact of Childhood Trauma History on Treatment Responses to Psychosocial Interventions for Chronic Low Back Pain: A Randomized Controlled Trial
CHURCHILL LIVINGSTONE. 2024: 33
View details for Web of Science ID 001282167300150
-
Emotional Dynamics in Fibromyalgia: Pain, Fatigue, and Stress Moderate Momentary Associations Between Positive and Negative Emotions
JOURNAL OF PAIN
2023; 24 (9): 1594-1603
Abstract
Affective disruptions, particularly deficits in positive affect, are characteristic of fibromyalgia (FM). The Dynamic Model of Affect provides some explanations of affective disruptions in FM, suggesting that the inverse association between positive and negative emotions is stronger when individuals with FM are under greater stress than usual. However, our understanding of the types of stressors and negative emotions that contribute to these affective dynamics is limited. Using ecological momentary assessment (EMA) methods, 50 adults who met the FM survey diagnostic criteria rated their momentary pain, stress, fatigue, negative emotions (depression, anger, and anxiety), and positive emotions 5X/day for eight days using a smartphone application. Results of multilevel modeling indicate that, consistent with the Dynamic Model of Affect, there was a stronger inverse association between positive emotion and negative emotions during times of greater pain, stress, and fatigue. Importantly, this pattern was specific to depression and anger, and was not present for anxiety. These findings suggest that fluctuations in fatigue and stress may be just as important or more important than fluctuations in pain when understanding the emotional dynamics in FM. In addition, having a more nuanced understanding of the role that different negative emotions play may be similarly important to understanding emotional dynamics in FM. PERSPECTIVE: This article presents new findings on the emotional dynamics in FM during times of increased pain, fatigue, and stress. Findings highlight the need for clinicians to conduct a comprehensive evaluation of fatigue, stress, and anger in addition to more routinely assessed depression and pain when working with individuals with FM.
View details for DOI 10.1016/j.jpain.2023.04.007
View details for Web of Science ID 001076674600001
View details for PubMedID 37094743
View details for PubMedCentralID PMC10527274
https://orcid.org/0000-0001-8893-2248