Jiyeong Kim

All Publications

• Patient-Centered Research Through Artificial Intelligence to Identify Priorities in Cancer Care. JAMA oncology Kim, J., Chen, M. L., Rezaei, S. J., Ramirez-Posada, M., Caswell-Jin, J. L., Kurian, A. W., Riaz, F., Sarin, K. Y., Tang, J. Y., Asch, S. M., Linos, E. 2025

  Abstract

  Patient-centered research is essential for bridging the gap between research and patient care, yet patient perspectives are often inadequately represented in health research.To leverage artificial intelligence (AI) and natural language processing (NLP) to analyze a large dataset of patient messages, defining patient concerns and generating relevant research topics, and to quantify the quality of these AI-generated topics.This case series was conducted using an automated framework involving a 2-staged unsupervised NLP topic model and AI-generated research topic suggestions. The study was based on deidentified patient portal message data from individuals with breast or skin cancer at Stanford Health Care and 22 affiliated centers over July 2013 to April 2024.A widely used large language model (ChatGPT-4o [OpenAI]; April 2024) was used and guided through multiple prompt-engineering strategies to perform multilevel tasks, including knowledge interpretation and summarization (eg, interpreting and summarizing the NLP-defined topics), knowledge generation (eg, generating research ideas corresponding to patients' issues), self-reflection and correction (eg, ensuring and revising the research ideas after searching for scientific articles), and self-reassurance (eg, confirming and finalizing the research ideas).Three breast oncologists (J.L.C., A.W.K., F.R) and 3 dermatologists (K.Y.S, J.Y.T., E.L.) evaluated the meaningfulness and novelty of the AI-generated research topics using a 5-point Likert scale (1 representing exceptional to 5 representing poor). Mean (SD) scores for meaningfulness and novelty were computed for each topic.A total of 614 464 patient messages were analyzed from 25 549 individuals, 10 665 with breast cancer (98.6% female) and 14 884 had skin cancer (49.0% female). The overall mean (SD) scores for meaningfulness and novelty were 3.00 (0.50) and 3.29 (0.74), respectively, for breast cancer topics and 2.67 (0.45) and 3.09 (0.68), respectively, for skin cancer topics. One-third of the AI-suggested research topics were highly meaningful and novel when both scores were lower than the average (5 of 15 for breast cancer and 6 of 15 for skin cancer). Notably, two-thirds of the AI-suggested topics were novel (10 of 15 for breast cancer and 11 of 15 for skin cancer).This case series demonstrates that AI/NLP-driven analysis of large volumes of patient messages can generate quality research topics in cancer care that reflect patient perspectives, providing valuable guidance for future patient-centered health research endeavors.

  View details for DOI 10.1001/jamaoncol.2025.0694

  View details for PubMedID 40272833

• Artificial intelligence tools in supporting healthcare professionals for tailored patient care. NPJ digital medicine Kim, J., Chen, M. L., Rezaei, S. J., Hernandez-Boussard, T., Chen, J. H., Rodriguez, F., Han, S. S., Lal, R. A., Kim, S. H., Dosiou, C., Seav, S. M., Akcan, T., Rodriguez, C. I., Asch, S. M., Linos, E. 2025; 8 (1): 210

  Abstract

  Artificial intelligence (AI) tools to support clinicians in providing patient-centered care can contribute to patient empowerment and care efficiency. We aimed to draft potential AI tools for tailored patient support corresponding to patients' needs and assess clinicians' perceptions about the usefulness of those AI tools. To define patients' issues, we analyzed 528,199 patient messages of 11,123 patients with diabetes by harnessing natural language processing and AI. Applying multiple prompt-engineering techniques, we drafted a series of AI tools, and five endocrinologists evaluated them for perceived usefulness and risk. Patient education and administrative support for timely and streamlined interaction were perceived as highly useful, yet deeper integration of AI tools into patient data was perceived as risky. This study proposes assorted AI applications as clinical assistance tailored to patients' needs substantiated by clinicians' evaluations. Findings could offer essential ramifications for developing potential AI tools for precision patient care for diabetes and beyond.

  View details for DOI 10.1038/s41746-025-01604-3

  View details for PubMedID 40240489

  View details for PubMedCentralID 5069713

• Perspectives on Artificial Intelligence-Generated Responses to Patient Messages. JAMA network open Kim, J., Chen, M. L., Rezaei, S. J., Liang, A. S., Seav, S. M., Onyeka, S., Lee, J. J., Vedak, S. C., Mui, D., Lal, R. A., Pfeffer, M. A., Sharp, C., Pageler, N. M., Asch, S. M., Linos, E. 2024; 7 (10): e2438535

  View details for DOI 10.1001/jamanetworkopen.2024.38535

  View details for PubMedID 39412810

• Large language models outperform mental and medical health care professionals in identifying obsessive-compulsive disorder. NPJ digital medicine Kim, J., Leonte, K. G., Chen, M. L., Torous, J. B., Linos, E., Pinto, A., Rodriguez, C. I. 2024; 7 (1): 193

  Abstract

  Despite the promising capacity of large language model (LLM)-powered chatbots to diagnose diseases, they have not been tested for obsessive-compulsive disorder (OCD). We assessed the diagnostic accuracy of LLMs in OCD using vignettes and found that LLMs outperformed medical and mental health professionals. This highlights the potential benefit of LLMs in assisting in the timely and accurate diagnosis of OCD, which usually entails a long delay in diagnosis and treatment.

  View details for DOI 10.1038/s41746-024-01181-x

  View details for PubMedID 39030292

  View details for PubMedCentralID 10352922

• Analysing common topics of secure patient messages in hidradenitis suppurativa: a text-embedding and natural language-processing approach. The British journal of dermatology Chen, M. L., Kim, J., Naik, H. B., Aleshin, M. A., Sarin, K. Y., Barnes, L. A., Linos, E. 2024

  View details for DOI 10.1093/bjd/ljae222

  View details for PubMedID 38975641

• Telehealth Utilization and Associations in the United States During the Third Year of the COVID-19 Pandemic: Population-Based Survey Study in 2022. JMIR public health and surveillance Kim, J., Cai, Z. R., Chen, M. L., Onyeka, S., Ko, J. M., Linos, E. 2024; 10: e51279

  Abstract

  BACKGROUND: The COVID-19 pandemic rapidly changed the landscape of clinical practice in the United States; telehealth became an essential mode of health care delivery, yet many components of telehealth use remain unknown years after the disease's emergence.OBJECTIVE: We aim to comprehensively assess telehealth use and its associated factors in the United States.METHODS: This cross-sectional study used a nationally representative survey (Health Information National Trends Survey) administered to US adults (≥18 years) from March 2022 through November 2022. To assess telehealth adoption, perceptions of telehealth, satisfaction with telehealth, and the telehealth care purpose, we conducted weighted descriptive analyses. To identify the subpopulations with low adoption of telehealth, we developed a weighted multivariable logistic regression model.RESULTS: Among a total of 6252 survey participants, 39.3% (2517/6252) reported telehealth use in the past 12 months (video: 1110/6252, 17.8%; audio: 876/6252, 11.6%). The most prominent reason for not using telehealth was due to telehealth providers failing to offer this option (2200/3529, 63%). The most common reason for respondents not using offered telehealth services was a preference for in-person care (527/578, 84.4%). Primary motivations to use telehealth were providers' recommendations (1716/2517, 72.7%) and convenience (1516/2517, 65.6%), mainly for acute minor illness (600/2397, 29.7%) and chronic condition management (583/2397, 21.4%), yet care purposes differed by age, race/ethnicity, and income. The satisfaction rate was predominately high, with no technical problems (1829/2517, 80.5%), comparable care quality to that of in-person care (1779/2517, 75%), and no privacy concerns (1958/2517, 83.7%). Younger individuals (odd ratios [ORs] 1.48-2.23; 18-64 years vs ≥75 years), women (OR 1.33, 95% CI 1.09-1.61), Hispanic individuals (OR 1.37, 95% CI 1.05-1.80; vs non-Hispanic White), those with more education (OR 1.72, 95% CI 1.03-2.87; at least a college graduate vs less than high school), unemployed individuals (OR 1.25, 95% CI 1.02-1.54), insured individuals (OR 1.83, 95% CI 1.25-2.69), or those with poor general health status (OR 1.66, 95% CI 1.30-2.13) had higher odds of using telehealth.CONCLUSIONS: To our best knowledge, this is among the first studies to examine patient factors around telehealth use, including motivations to use, perceptions of, satisfaction with, and care purpose of telehealth, as well as sociodemographic factors associated with telehealth adoption using a nationally representative survey. The wide array of descriptive findings and identified associations will help providers and health systems understand the factors that drive patients toward or away from telehealth visits as the technology becomes more routinely available across the United States, providing future directions for telehealth use and telehealth research.

  View details for DOI 10.2196/51279

  View details for PubMedID 38669075

• Human-AI interaction in skin cancer diagnosis: a systematic review and meta-analysis. NPJ digital medicine Krakowski, I., Kim, J., Cai, Z. R., Daneshjou, R., Lapins, J., Eriksson, H., Lykou, A., Linos, E. 2024; 7 (1): 78

  Abstract

  The development of diagnostic tools for skin cancer based on artificial intelligence (AI) is increasing rapidly and will likely soon be widely implemented in clinical use. Even though the performance of these algorithms is promising in theory, there is limited evidence on the impact of AI assistance on human diagnostic decisions. Therefore, the aim of this systematic review and meta-analysis was to study the effect of AI assistance on the accuracy of skin cancer diagnosis. We searched PubMed, Embase, IEE Xplore, Scopus and conference proceedings for articles from 1/1/2017 to 11/8/2022. We included studies comparing the performance of clinicians diagnosing at least one skin cancer with and without deep learning-based AI assistance. Summary estimates of sensitivity and specificity of diagnostic accuracy with versus without AI assistance were computed using a bivariate random effects model. We identified 2983 studies, of which ten were eligible for meta-analysis. For clinicians without AI assistance, pooled sensitivity was 74.8% (95% CI 68.6-80.1) and specificity was 81.5% (95% CI 73.9-87.3). For AI-assisted clinicians, the overall sensitivity was 81.1% (95% CI 74.4-86.5) and specificity was 86.1% (95% CI 79.2-90.9). AI benefitted medical professionals of all experience levels in subgroup analyses, with the largest improvement among non-dermatologists. No publication bias was detected, and sensitivity analysis revealed that the findings were robust. AI in the hands of clinicians has the potential to improve diagnostic accuracy in skin cancer diagnosis. Given that most studies were conducted in experimental settings, we encourage future studies to further investigate these potential benefits in real-life settings.

  View details for DOI 10.1038/s41746-024-01031-w

  View details for PubMedID 38594408

  View details for PubMedCentralID 8237239

• Assessment of correctness, content omission, and risk of harm in large language model responses to dermatology continuing medical education questions. The Journal of investigative dermatology Cai, Z. R., Chen, M. L., Kim, J., Novoa, R. A., Barnes, L. A., Beam, A., Linos, E. 2024

  View details for DOI 10.1016/j.jid.2024.01.015

  View details for PubMedID 38310972

• Prevalence and associations of poor mental health in the third year of COVID-19: U.S. population-based analysis from 2020 to 2022. Psychiatry research Kim, J., Linos, E., Rodriguez, C. I., Chen, M. L., Dove, M. S., Keegan, T. H. 2023; 330: 115622

  Abstract

  BACKGROUND: Poorer mental health was found early in the COVID-19 pandemic, yet mental health in the third year of COVID-19 has not been assessed on a general adult population level in the United States.METHODS: We used a nationally representative cross-sectional survey (Health Information National Trends Survey, HINTS 5 2020 n=3,865 and HINTS 6 2022 n=6,252). The prevalence of poor mental health was examined using a Patient Health Questionnaire-4 scale in 2020 and 2022. We also investigated the factors associated with poor mental health in 2022 using a weighted multivariable logistic regression adjusting for sociodemographic and health status characteristics to obtain the odds ratio (OR).OUTCOMES: The prevalence of poor mental health in adults increased from 2020 to 2022 (31.5% vs 36.3%, p=0.0005). U.S. adults in 2022 were 1.28 times as likely to have poor mental health than early in the pandemic. Moreover, individuals with food insecurity, housing instability, and low income had greater odds of poor mental health (ORs=1.78-2.55). Adults who were females, non-Hispanic Whites, or age 18-64 years were more likely to have poor mental health (ORs=1.46-4.15).INTERPRETATION: Mental health of U.S. adults worsened in the third year of COVID-19 compared to the beginning of the pandemic.

  View details for DOI 10.1016/j.psychres.2023.115622

  View details for PubMedID 38006717

• Assessing Biases in Medical Decisions via Clinician and AI Chatbot Responses to Patient Vignettes. JAMA network open Kim, J., Cai, Z. R., Chen, M. L., Simard, J. F., Linos, E. 2023; 6 (10): e2338050

  View details for DOI 10.1001/jamanetworkopen.2023.38050

  View details for PubMedID 37847506

• Effectiveness of Digital Mental Health Tools to Reduce Depressive and Anxiety Symptoms in Low- and Middle-Income Countries: Systematic Review and Meta-analysis. JMIR mental health Kim, J., Aryee, L. M., Bang, H., Prajogo, S., Choi, Y. K., Hoch, J. S., Prado, E. L. 2023; 10: e43066

  Abstract

  Depression and anxiety contribute to an estimated 74.6 million years of life with disability, and 80% of this burden occurs in low- and middle-income countries (LMICs), where there is a large gap in care.We aimed to systematically synthesize available evidence and quantify the effectiveness of digital mental health interventions in reducing depression and anxiety in LMICs.In this systematic review and meta-analysis, we searched PubMed, Embase, and Cochrane databases from the inception date to February 2022. We included randomized controlled trials conducted in LMICs that compared groups that received digital health interventions with controls (active control, treatment as usual, or no intervention) on depression or anxiety symptoms. Two reviewers independently extracted summary data reported in the papers and performed study quality assessments. The outcomes were postintervention measures of depression or anxiety symptoms (Hedges g). We calculated the pooled effect size weighted by inverse variance.Among 11,196 retrieved records, we included 80 studies in the meta-analysis (12,070 participants n=6052, 50.14% in the intervention group and n=6018, 49.85% in the control group) and 96 studies in the systematic review. The pooled effect sizes were -0.61 (95% CI -0.78 to -0.44; n=67 comparisons) for depression and -0.73 (95% CI -0.93 to -0.53; n=65 comparisons) for anxiety, indicating that digital health intervention groups had lower postintervention depression and anxiety symptoms compared with controls. Although heterogeneity was considerable (I2=0.94 for depression and 0.95 for anxiety), we found notable sources of variability between the studies, including intervention content, depression or anxiety symptom severity, control type, and age. Grading of Recommendations, Assessments, Development, and Evaluation showed that the evidence quality was overall high.Digital mental health tools are moderately to highly effective in reducing depression and anxiety symptoms in LMICs. Thus, they could be effective options to close the gap in depression and anxiety care in LMICs, where the usual mental health care is minimal.PROSPERO CRD42021289709; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=289709.

  View details for DOI 10.2196/43066

  View details for PubMedID 36939820

  View details for PubMedCentralID PMC10131603

• Mental health care needs of caregivers of people with Alzheimer's disease from online forum analysis. Npj mental health research Kim, J., Cai, Z. R., Chen, M. L., Rezaei, S. J., Onyeka, S., Rodriguez, C. I., Hernandez-Boussard, T., Filkov, V., Whitmer, R. A., Linos, E., Choi, Y. K. 2024; 3 (1): 54

  Abstract

  Informal caregivers of people with Alzheimer's disease and related dementias (ADRD) are at risk of poor mental health. This study aimed to investigate the feasibility and validity of studying caregivers' mental stressors using online caregiving forum data (March 2018-February 2022) and natural language processing and machine learning (NLP/ML). NLP/ML topic modeling generated eight prominent topics, which we compared with qualitatively defined themes and the existing caregiving framework to assess validity. Among a total of 60,182 posts, 5848 were mental distress-related; for the ADRD patients (symptoms, medication, relocation, care duty share, diagnosis, conversation strategy) and the caregivers (caregiving burden and support). While we observed novel topics from NLP/ML-defined topics, mostly those were aligned with the existing framework. For feasibility assessment, qualitative title screening was done. The findings shed new light on the potential of NLP/ML text analysis of the online forum for informal caregivers to prepare tailored support for this vulnerable population.

  View details for DOI 10.1038/s44184-024-00100-y

  View details for PubMedID 39537826

  View details for PubMedCentralID 9047171

• Mental Health, Sleep and General Health Among Individuals With Dermatologic Conditions: A US Population-Based Study Using the National Health and Nutrition Examination Survey (NHANES). Experimental dermatology Rezaei, S. J., Chen, M. L., Kim, J., Linos, E. 2024; 33 (10): e15195

  View details for DOI 10.1111/exd.15195

  View details for PubMedID 39400435

• Skin Cancer and Other Dermatologic Conditions Among US Veterans. JAMA dermatology Rezaei, S. J., Kim, J., Onyeka, S., Swetter, S. M., Weinstock, M. A., Asch, S. M., Linos, E. 2024

  Abstract

  US veterans may be at an increased risk of developing various dermatologic conditions compared with nonveterans.To compare the prevalence and the odds of dermatologic conditions (eg, skin cancers, dermatitis/eczema/rash, psoriasis) between veterans and nonveterans.This population-based cross-sectional study leveraged nationally representative data from the National Health and Nutrition Examination Survey (NHANES). Three questionnaires (demographics, medical conditions, and dermatology) were merged from 1999-2018 for analysis. Participants were nonveterans and veterans from NHANES data. Data were analyzed from August 2023 to April 2024.The prevalence and odds ratios (ORs) comparing veterans and nonveterans were examined for various dermatologic conditions, including self-reported skin cancer history (any skin cancer, melanoma, nonmelanoma and unknown subtypes), dermatitis/eczema/inflamed rash, and psoriasis.In a total of 61 307 participants (54 554 nonveterans and 6753 veterans), there was a higher prevalence of any skin cancer history among US veterans compared with nonveterans (9.0% vs 2.9%; P < .001) as well as a higher prevalence of melanoma history (2.2% vs 0.6%; P < .001). Adjusted for demographic factors, veterans had higher odds of any skin cancer history (OR, 1.72; 95% CI, 1.23-2.40) and higher odds of a melanoma history (OR, 2.27; 95% CI, 1.17-4.39) compared with nonveterans. Veterans had a higher prevalence of a psoriasis diagnosis compared with nonveterans (4.5% vs 2.9%; P = .002) and a 61% higher odds of a psoriasis diagnosis (OR, 1.61; 95% CI, 1.05-2.46) compared with nonveterans.This cross-sectional study found that veterans have higher prevalence and odds of various dermatologic conditions compared with nonveterans. Efforts aimed at improving health care quality among veterans must investigate the underlying causes of worsened skin health in this population.

  View details for DOI 10.1001/jamadermatol.2024.3043

  View details for PubMedID 39230881

• Development of Melanoma and Other Nonkeratinocyte Skin Cancers After Thyroid Cancer Radiation. JAMA network open Rezaei, S. J., Chen, M. L., Kim, J., John, E. M., Sunwoo, J. B., Linos, E. 2024; 7 (9): e2434841

  View details for DOI 10.1001/jamanetworkopen.2024.34841

  View details for PubMedID 39298173

• Incidence of Suicide Among Melanoma and Non-Keratinocyte Skin Cancer Patients in the US, 2000-2020. Journal of the American Academy of Dermatology Chen, M. L., Rezaei, S. J., Kim, J., Rodriguez, C., Swetter, S. M., O'Hara, R., Linos, E. 2024

  View details for DOI 10.1016/j.jaad.2024.05.028

  View details for PubMedID 38768863

• Impact of COVID-19, cancer survivorship and patient-provider communication on mental health in the US Difference-In-Difference. Npj mental health research Kim, J., Linos, E., Dove, M. S., Hoch, J. S., Keegan, T. H. 2023; 2 (1): 14

  Abstract

  Poor mental health has been found to be more prevalent among those with cancer and is considered a public health crisis since COVID-19. This study assessed the impact of COVID-19 and cancer survivorship on mental health and investigated factors, including online patient-provider communications (OPPC; email/internet/tablet/smartphone), associated with poor mental health prior to and during the early COVID-19. Nationally representative Health Information National Trends Survey data during 2017-2020 (n = 15,871) was used. While the prevalence of poor mental health was high (40-42%), Difference-In-Difference analyses revealed that cancer survivorship and COVID-19 were not associated with poor mental health. However, individuals that used OPPC had 40% higher odds of poor mental health. Low socioeconomic status (low education/income), younger age (18-64 years), and female birth gender were also associated with poor mental health. Findings highlight the persistence of long-standing mental health inequities and identify that OPPC users might be those who need mental health support.

  View details for DOI 10.1038/s44184-023-00034-x

  View details for PubMedID 38609572

  View details for PubMedCentralID 2880195

• Cancer survivors with sub-optimal patient-centered communication before and during the early COVID-19 pandemic. Patient education and counseling Kim, J., Fairman, N. P., Dove, M. S., Hoch, J. S., Keegan, T. H. 2023; 115: 107876

  Abstract

  OBJECTIVES: Patient-Centered Communication (PCC) is an essential element of patient-centered cancer care. Thus, this study aimed to examine the prevalence of and factors associated with optimal PCC among cancer survivors during COVID-19, which has been less studied.METHODS: We used national survey (Health Information National Trends Survey) among cancer survivors (n=2579) to calculate the prevalence (%) of optimal PCC in all 6 PCC domains and overall (mean) by time (before COVID-19, 2017-19 vs. COVID-19, 2020). Multivariable logistic regressions were performed to explore the associations of sociodemographic (age, birth gender, race/ethnicity, income, education, usual source of care), and health status (general health, depression/anxiety symptoms, time since diagnosis, cancer type) factors with optimal PCC.RESULTS: The prevalence of optimal PCC decreased during COVID-19 overall, with the greatest decrease in managing uncertainty (7.3%). Those with no usual source of care (odd ratios, ORs =1.53-2.29), poor general health (ORs=1.40-1.66), depression/anxiety symptoms (ORs=1.73-2.17) were less likely to have optimal PCC in most domains and overall PCC.CONCLUSIONS: We observed that the decreased prevalence of optimal PCC, and identified those with suboptimal PCC during COVID-19.PRACTICE IMPLICATIONS: More efforts to raise awareness and improve PCC are suggested, including education and guidelines, given the decreased prevalence during this public health emergency.

  View details for DOI 10.1016/j.pec.2023.107876

  View details for PubMedID 37406471

• Factors Associated with Online Patient-Provider Communications Among Cancer Survivors in the United States during COVID: A Cross-Sectional Study. JMIR cancer Kim, J., Linos, E., Fishman, D. A., Dove, M. S., Hoch, J. S., Keegan, T. H. 2023

  Abstract

  BACKGROUND: Online Patient-Provider Communication (OPPC) is crucial in enhancing access to health information, self-care, and related health outcomes among cancer survivors. The necessity of OPPC increased during SARS/COVID-19 (COVID), yet investigations in vulnerable subgroups have been limited.OBJECTIVE: Thus, this study aimed to assess the prevalence of OPPC and sociodemographic and clinical characteristics associated with OPPC among cancer survivors and adults without a history of cancer during COVID vs. pre-COVID.METHODS: Nationally representative cross-sectional survey data (Health Information National Trends Survey, HINTS 5 2017-2020) was used among cancer survivors (n= 1,900) and adults without a history of cancer (n= 13, 292). COVID included data from February to June 2020. We calculated the prevalence of three types of OPPC, defined as using email/internet, tablet/smartphone, or Electronic Health Records (EHR) for patient-provider communication, in the past 12 months. To investigate the associations of sociodemographic and clinical factors with OPPC, multivariable-adjusted weighted logistic regression was performed to obtain odds ratios (OR) and 95% confidence intervals (95% CI).RESULTS: The average prevalence of OPPC increased from pre-COVID to COVID among cancer survivors (39.7% vs. 49.7%, email/internet; 32.2% vs. 37.9%, tablet/smartphone; 19.0% vs. 30.0%, EHR). Cancer survivors (OR=1.32, 95% CI 1.06-1.63) were slightly more likely to use email/internet communications than adults without a history of cancer prior to COVID. Among cancer survivors, email/internet (OR=1.61, 1.08-2.40) and EHR (OR=1.92, 1.22-3.02) were more likely to be used during COVID than pre-COVID. During COVID, subgroups of cancer survivors, including Hispanics (OR=0.26, 0.09-0.71 vs. non-Hispanic Whites), or those with the lowest income (OR=6.14, 1.99-18.92 $50,000 to <$75,000; OR=0.42, 1.56-11.28 ≥ $75,000 vs. <$20,000), with no usual source of care (OR=6.17, 2.12-17.99), or reporting depression (OR=0.33, 0.14-0.78) were less likely to use email/internet and those who were the oldest (OR=9.33, 2.18-40.01 age 35-49; OR=3.58, 1.20-10.70 age 50-64; OR=3.09, 1.09-8.76 age 65-74 vs. ≥75), unmarried (OR=2.26, 1.06-4.86) or had public/no health insurance (ORs=0.19-0.21 Medicare, Medicaid, or Other, vs. private) were less likely to use tablet/smartphone to communicate with providers. Cancer survivors with a usual source of care (OR=6.23, 1.66-23.39) or healthcare office visits within a year (ORs=7.55-8.25) were significantly more likely to use EHR to communicate. While not observed in cancer survivors, lower education level was associated with lower OPPC among adults without a history of cancer during COVID.CONCLUSIONS: Our findings identified vulnerable subgroups of cancer survivors who were left behind in online patient-provider communications which are becoming an increasing part of healthcare. Those vulnerable subgroups of cancer survivors with lower OPPC should be helped through multidimensional interventions to prevent further inequities.CLINICALTRIAL: Not applicable.

  View details for DOI 10.2196/44339

  View details for PubMedID 37074951

• Characterizing risky alcohol use, cigarette smoking, e-cigarette use, and physical inactivity among cancer survivors in the USA-a cross-sectional study JOURNAL OF CANCER SURVIVORSHIP Kim, J., Keegan, T. H. 2022

  Abstract

  Unhealthy lifestyle behaviors are associated with inferior health outcomes among cancer survivors, including increased mortality. It is crucial to identify vulnerable subgroups, yet investigations have been limited. Thus, this study aimed to examine sociodemographic and clinical characteristics associated with risky health behaviors among cancer survivors.We used national, cross-sectional survey data (Health Information National Trends Survey, HINTS 2017-2020) for 2579 cancer survivors. We calculated the prevalence of risky alcohol use, current cigarette smoking, e-cigarette use, and not meeting physical activity guidelines. We performed weighted logistic regression to obtain multivariable-adjusted odds ratios (OR) for the association between each unhealthy behavior with sociodemographic and clinical characteristics.Overall, 25% showed risky alcohol use, 12% were current cigarette smokers, 3% were current e-cigarette users, and 68% did not meet physical activity guidelines. Cancer survivors who were males, non-Hispanic Whites or African Americans, without a college education, not married and with comorbidities or psychological distress were more likely to have unhealthy behaviors. Those with lung disease or depression were 2 times as likely to smoke cigarette or e-cigarettes and those with psychological distress were 1.6 times as likely to be physically inactive. Moreover, risky drinkers (OR = 1.75, 95% CI = 1.22-2.52) and e-cigarette smokers (OR = 16.40, 95% CI 3.29-81.89) were more likely to be current cigarette smokers.We identified vulnerable subpopulations of cancer survivors with multiple unhealthy lifestyle behaviors.Our findings inform clinicians and program and policy makers of the subgroups of cancer survivors to target for multiple health behavior interventions.

  View details for DOI 10.1007/s11764-022-01245-5

  View details for Web of Science ID 000840291700001

  View details for PubMedID 35963976

  View details for PubMedCentralID 2988633

• Sociodemographic factors associated with HPV awareness/knowledge and cervical cancer screening behaviors among caregivers in the U.S BMC WOMENS HEALTH Kim, J., Dove, M. S., Dang, J. T. 2022; 22 (1): 335

  Abstract

  Family caregivers may be at a higher risk for several chronic diseases, including cancer. Cervical cancer is one of the most common causes of cancer death among women. Despite family caregivers' vulnerability, the status of their HPV awareness, knowledge, and preventive health behaviors, including cervical cancer screening, has been understudied. Thus, this study aimed to examine the sociodemographic factors associated with HPV awareness and knowledge and adherence to the cervical cancer screening guidelines among caregivers in the U.S.Nationally representative cross-sectional survey data were obtained from the Health Information National Trends Survey (HINTS 5, 2017-2020). Female caregivers aged 21-65 were included (N = 1190). Weighted multivariable logistic regression was performed to identify factors associated with HPV awareness (heard of HPV), knowledge (HPV can cause cervical cancer), and adherence to the United States Preventive Service Task Force 2018 cervical cancer screening guidelines by sociodemographic factors (age, race/ethnicity, education, household income, marital status,) and the intensity of caregiving.An estimated 79% of female caregivers were aware of HPV and 84% adhered to the cervical cancer screening guidelines. Caregivers who were older than 50 (OR = 3.62, 1.91-6.85, adherence of aged 21-50 vs. 51-65), Hispanics of race/ethnicity compared with Black/African Americans (OR = 3.14, 1.31-7.52, adherence of Black/African Americans vs. Hispanics), with a high school education or less (OR = 2.34, 1.14-4.82, adherence of Some college or more vs. High school education or less), and with intense caregiving duty (spending 35 h/week or more on caregiving) compared with light-duty (OR = 2.34, 1.10-5.00, adherence of 5-14 h vs. 35 h or more, weekly) had poor adherence to the cervical cancer screening guidelines. Caregivers who were older, racial minorities (Asian, Native Hawaiian/Pacific Islander, American Indian/Alaska Native, Multiple races), and less educated showed lower HPV awareness (Heard of HPV) than their counterparts.There are caregiving populations whose HPV awareness and cervical cancer screening adherence are low. To improve their awareness and knowledge of HPV and support their cervical cancer screening behaviors, we need to consider interventions that target those specific populations.

  View details for DOI 10.1186/s12905-022-01918-4

  View details for Web of Science ID 000837679800002

  View details for PubMedID 35941594

  View details for PubMedCentralID PMC9358833

• The Rationale for Economic Evaluation in Speech and Language: Cost, Effectiveness, and Cost-effectiveness SEMINARS IN SPEECH AND LANGUAGE Hoch, J. S., Smith, B. P., Kim, J., Dewa, C. S. 2022; 43 (03): 208-217

  Abstract

  Economic evaluation studies the costs and outcomes of two or more alternative activities to estimate the relative efficiency of each course of action. Economic evaluation is both important and necessary in the management of speech and language issues. Economic evaluation can help focus attention on interventions that provide value for improving population health. The purpose of this article is to introduce readers to fundamental economic concepts. Readers are also introduced to common issues when conducting economic evaluations and how to address them in practice.

  View details for DOI 10.1055/s-0042-1750345

  View details for Web of Science ID 000827789000004

  View details for PubMedID 35858606