Establishing the clinical relevance of grade A post-hepatectomy liver failure.

INTRODUCTION: The International Study Group of Liver Surgery's criteria stratifies post-hepatectomy liver failure (PHLF) into grades A, B, and C. The clinical significance of these grades has not been fully established. METHODS: The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) hepatectomy-targeted database was analyzed. Outcomes between patients without PHLF, with grade A PHLF, and grade B or C PHLF were compared. Univariate and multivariable logistic regression were performed. RESULTS: Six thousand two hundred seventy-four adults undergoing elective major hepatectomy were included in the analysis. The incidence of grade A PHLF was 4.3% and grade B or C was 5.3%. Mortality was similar between patients without PHLF (1.2%) and with grade A PHLF (1.1%), but higher in those with grades B or C PHLF (25.4%). Overall morbidities rates were 19.3%, 41.7%, and 72.8% in patients without PHLF, with grade A PHLF, and with grade B or C PHLF, respectively (p < 0.001). Grade A PHLF was associated with increased morbidity (grade A: odds ratios [OR] 2.7 [95% CI: 2.0-3.5]), unplanned reoperation (grade A: OR 3.4 [95% CI: 2.2-5.1]), nonoperative intervention (grade A: OR 2.6 [95% CI: 1.9-3.6]), length of stay (grade A: OR 3.1 [95% CI: 2.3-4.1]), and readmission (grade A: OR 1.8 [95% CI: 1.3-2.5]) compared to patients without PHLF. CONCLUSIONS: Although mortality was similar between patients without PHLF and with grade A PHLF, other postoperative outcomes were notably inferior. Grade A PHLF is a clinically distinct entity with relevant associated postoperative morbidity.

Prospective Evaluation of Circulating Tumor DNA using Next Generation Sequencing as a Biomarker during Neoadjuvant Chemotherapy in Localized Pancreatic Cancer.

OBJECTIVE: In this prospective study, we aim to characterize the prognostic value of circulating tumor DNA (ctDNA) by next-generation-sequencing (NGS) in patients undergoing neoadjuvant chemotherapy (NAC) for pancreatic ductal adenocarcinoma (PDAC). SUMMARY BACKGROUND DATA: Circulating tumor DNA is a promising blood-based biomarker that is prognostic in several malignancies. Detection of ctDNA by NGS may provide insights regarding the mutational profiles in PDAC to help guide clinical decisions for patients in a potentially curative setting. However, the utility of ctDNA as a biomarker in localized PDAC remains unclear. METHODS: Patients with localized PDAC were enrolled in a prospective study at Northwestern Medicine between October 2020 and October 2022. Blood samples were collected to perform targeted tumor agnostic NGS utilizing the Tempus x|F 105 gene panel at three timepoints: pre-therapy (at diagnosis), post-NAC, and after local therapy, including surgery. The relationship between ctDNA detection and CA19-9, and the prognostic significance of ctDNA detection were analyzed. RESULTS: 56 patients were included in the analysis. ctDNA was detectable in 48% at diagnosis, 33% post-NAC, and 41% after local therapy. After completion of NAC, patients with detectable ctDNA had higher CA19-9 levels versus those without (78.4 vs. 30.0, P=0.02). The presence of baseline ctDNA was associated with a CA19-9 response; those without ctDNA had a significant CA19-9 response following NAC (109.0 U/mL vs. 31.5 U/mL; P=0.01), while those with ctDNA present at diagnosis did not (198.1 U/mL vs. 113.8 U/mL; P=0.77). In patients treated with NAC, the presence of KRAS ctDNA at diagnosis was associated with and independently predicted worse progression-free-survival. CONCLUSION: This report demonstrates the prognostic value of ctDNA analysis with NGS in localized PDAC. NGS ctDNA is a biomarker of treatment response to NAC. KRAS ctDNA at diagnosis independently predicts worse survival in patients treated with NAC.

Red Media vs. Blue Media: Social Distancing and Partisan News Media Use during the COVID-19 Pandemic.

Political polarization surrounding the COVID-19 health crisis has been on the rise since the beginning of the pandemic. We combine prior research on motivated reasoning, selective exposure, and news framing to understand the association between partisan media use and social distancing behavior related to COVID-19. To do so, we collected media content data and national survey data during the onset of the pandemic. We employed structural topic modeling (STM), dependency parsing, word co-occurrence, and manual coding to examine the media coverage. Next, we analyzed survey data collected with a Qualtrics panel from a sample of U.S. residents for factors explaining social distancing behaviors. Results reveal coverage from the right leaning outlets downplayed the virus and highlighted the consequences of lockdowns on the economy. Our survey findings show that even after accounting for a range of demographic, political orientation, and COVID-19 awareness variables, conservative media use was linked, although modestly, with a lower likelihood of social distancing behavior. Our findings echo past research on media framing of pandemics and their association with public attitudes and behavior.

Effects of Bundling Medication for Opioid Use Disorder With an mHealth Intervention Targeting Addiction: A Randomized Clinical Trial.

OBJECTIVE: Medication for opioid use disorder (MOUD) improves treatment retention and reduces illicit opioid use. A-CHESS is an evidence-based smartphone intervention shown to improve addiction-related behaviors. The authors tested the efficacy of MOUD alone versus MOUD plus A-CHESS to determine whether the combination further improved outcomes. METHODS: In an unblinded parallel-group randomized controlled trial, 414 participants recruited from outpatient programs were assigned in a 1:1 ratio to receive either MOUD alone or MOUD+A-CHESS for 16 months and were followed for an additional 8 months. All participants were on methadone, buprenorphine, or injectable naltrexone. The primary outcome was abstinence from illicit opioid use; secondary outcomes were treatment retention, health services use, other substance use, and quality of life; moderators were MOUD type, gender, withdrawal symptom severity, pain severity, and loneliness. Data sources were surveys comprising multiple validated scales, as well as urine screens, every 4 months. RESULTS: There was no difference in abstinence between participants in the MOUD+A-CHESS and MOUD-alone arms across time (odds ratio=1.10, 95% CI=0.90-1.33). However, abstinence was moderated by withdrawal symptom severity (odds ratio=0.95, 95% CI=0.91-1.00) and MOUD type (odds ratio=0.57, 95% CI=0.34-0.97). Among participants without withdrawal symptoms, abstinence rates were higher over time for those in the MOUD+A-CHESS arm than for those in the MOUD-alone arm (odds ratio=1.30, 95% CI=1.01-1.67). Among participants taking methadone, those in the MOUD+A-CHESS arm were more likely to be abstinent over time (b=0.28, SE=0.09) than those in the MOUD-alone arm (b=0.06, SE=0.08), although the two groups did not differ significantly from each other (∆b=0.22, SE=0.11). MOUD+A-CHESS was also associated with greater meeting attendance (odds ratio=1.25, 95% CI=1.05-1.49) and decreased emergency department and urgent care use (odds ratio=0.88, 95% CI=0.78-0.99). CONCLUSIONS: Overall, MOUD+A-CHESS did not improve abstinence relative to MOUD alone. However, MOUD+A-CHESS may provide benefits for subsets of patients and may impact treatment utilization.

Using Machine Learning of Online Expression to Explain Recovery Trajectories: Content Analytic Approach to Studying a Substance Use Disorder Forum.

BACKGROUND: Smartphone-based apps are increasingly used to prevent relapse among those with substance use disorders (SUDs). These systems collect a wealth of data from participants, including the content of messages exchanged in peer-to-peer support forums. How individuals self-disclose and exchange social support in these forums may provide insight into their recovery course, but a manual review of a large corpus of text by human coders is inefficient. OBJECTIVE: The study sought to evaluate the feasibility of applying supervised machine learning (ML) to perform large-scale content analysis of an online peer-to-peer discussion forum. Machine-coded data were also used to understand how communication styles relate to writers' substance use and well-being outcomes. METHODS: Data were collected from a smartphone app that connects patients with SUDs to online peer support via a discussion forum. Overall, 268 adult patients with SUD diagnoses were recruited from 3 federally qualified health centers in the United States beginning in 2014. Two waves of survey data were collected to measure demographic characteristics and study outcomes: at baseline (before accessing the app) and after 6 months of using the app. Messages were downloaded from the peer-to-peer forum and subjected to manual content analysis. These data were used to train supervised ML algorithms using features extracted from the Linguistic Inquiry and Word Count (LIWC) system to automatically identify the types of expression relevant to peer-to-peer support. Regression analyses examined how each expression type was associated with recovery outcomes. RESULTS: Our manual content analysis identified 7 expression types relevant to the recovery process (emotional support, informational support, negative affect, change talk, insightful disclosure, gratitude, and universality disclosure). Over 6 months of app use, 86.2% (231/268) of participants posted on the app's support forum. Of these participants, 93.5% (216/231) posted at least 1 message in the content categories of interest, generating 10,503 messages. Supervised ML algorithms were trained on the hand-coded data, achieving F1-scores ranging from 0.57 to 0.85. Regression analyses revealed that a greater proportion of the messages giving emotional support to peers was related to reduced substance use. For self-disclosure, a greater proportion of the messages expressing universality was related to improved quality of life, whereas a greater proportion of the negative affect expressions was negatively related to quality of life and mood. CONCLUSIONS: This study highlights a method of natural language processing with potential to provide real-time insights into peer-to-peer communication dynamics. First, we found that our ML approach allowed for large-scale content coding while retaining moderate-to-high levels of accuracy. Second, individuals' expression styles were associated with recovery outcomes. The expression types of emotional support, universality disclosure, and negative affect were significantly related to recovery outcomes, and attending to these dynamics may be important for appropriate intervention.

The Effects of Vaccine Efficacy Information on Vaccination Intentions Through Perceived Response Efficacy and Hope.

Response efficacy information indicating the effectiveness of a recommended behavior in risk reduction is an important component of health communication. For example, many messages regarding COVID-19 vaccines featured numerical vaccine efficacy rates in preventing infections, hospitalizations, and deaths. While the relationship between disease risk perceptions and fear has been well established, we know less about the psychological factors involved in communicating vaccine efficacy information, such as response efficacy perceptions and hope. This study examines the effects of numerical vaccine efficacy information and message framing on vaccination intentions and their relationship to perceived response efficacy and hope, using a fictitious infectious disease similar to COVID-19. Findings suggest that communicating a high efficacy rate of the vaccine in preventing severe illness increased perceived response efficacy, which in turn boosted vaccination intention directly and indirectly through increasing hope. Also, fear about the virus was positively associated with hope about the vaccine. Implications of using response efficacy information and hope appeals in health communication and vaccination promotion are discussed.

The inaccuracies of gastric adenocarcinoma clinical staging and its predictive factors.

INTRODUCTION: Accurate clinical staging (CS) of gastric adenocarcinoma is important to guide treatment planning. Our objectives were to (1) assess clinical to pathologic stage migration patterns for patients with gastric adenocarcinoma, (2) identify factors associated with inaccurate CS, and (3) evaluate the association of understaging with survival. METHODS: The National Cancer Database was queried for patients who underwent upfront resection for stage I-III gastric adenocarcinoma. Multivariable logistic regression was used to detect factors associated with inaccurate understaging. Kaplan-Meier analyses and cox proportional hazards regression were performed to assess overall survival (OS) for patients with inaccurate CS. RESULTS: Of 14 425 analyzed patients, 5781 (40.1%) patients were inaccurately staged. Factors associated with understaging included treatment at a Comprehensive Community Cancer Program, presence of lymphovascular invasion, moderate to poor differentiation, large tumor size, and T2 disease. Based on overall CS, median OS was 51.0 months for accurately staged patients and 29.5 months for understaged patients (<0.001). CONCLUSION: Clinical T-category, large tumor size, and worse histologic features lead to inaccurate CS for gastric adenocarcinoma, impacting OS. Improvements to staging parameters and diagnostic modalities focusing on these factors may improve prognostication.

Team Science Principles Enhance Cancer Care Delivery Quality Improvement: Interdisciplinary Implementation of Breast Cancer Screening Shared Decision Making.

PURPOSE: Implementing shared decision making (SDM), recommended in screening mammography by national guidelines for women age 40-49 years, faces challenges that innovations in quality improvement and team science (TS) are poised to address. We aimed to improve the effectiveness, patient-centeredness, and efficiency of SDM in primary care for breast cancer screening. METHODS: Our interdisciplinary team included primary and specialty care, psychology, epidemiology, communication science, engineering, and stakeholders (patients and clinicians). Over a 6-year period, we executed two iterative cycles of plan-do-study-act (PDSA) to develop, revise, and implement a SDM tool using TS principles. Patient and physician surveys and retrospective analysis of tool performance informed our first PDSA cycle. Patient and physician surveys, toolkit use, and clinical outcomes in the second PDSA cycle supported SDM implementation. We gathered team member assessments on the importance of individual TS activities. RESULTS: Our first PDSA cycle successfully generated a SDM tool called Breast Cancer Risk Estimator, deemed valuable by 87% of patients surveyed. Our second PDSA cycle increased Breast Cancer Risk Estimator utilization, from 2,000 sessions in 2017 to 4,097 sessions in 2019 while maintaining early-stage breast cancer diagnoses. Although TS activities such as culture, trust, and communication needed to be sustained throughout the project, shared goals, research/data infrastructure support, and leadership were more important earlier in the project and persisted in the later stages of the project. CONCLUSION: Combining rigorous quality improvement and TS principles can support the complex, interdependent, and interdisciplinary activities necessary to improve cancer care delivery exemplified by our implementation of a breast cancer screening SDM tool.

Patient-provider communication while using a clinical decision support tool: explaining satisfaction with shared decision making for mammography screening.

BACKGROUND: Clinical decision aids may support shared decision-making for screening mammography. To inform shared decision-making between patients and their providers, this study examines how patterns of using an EHR-integrated decision aid and accompanying verbal patient-provider communication predict decision-making satisfaction. METHODS: For 51 patient visits during which a mammography decision aid was used, linguistic characteristics of patient-provider verbal communication were extracted from transcribed audio recordings and system logs automatically captured uses of the decision aid. Surveys assessed patients' post-visit decisional satisfaction and its subcomponents. Linear mixed effects models assessed how patients' satisfaction with decision making was related to patterns of verbal communication and navigation of the decision aid. RESULTS: The results indicate that providers' use of quantitative language during the encounter was positively associated with patients' overall satisfaction, feeling informed, and values clarity. Patients' question-asking was negatively associated with overall satisfaction, values clarity, and certainty perception. Where system use data indicated the dyad had cycled through the decision-making process more than once ("looping" back through pages of the decision aid), patients reported improved satisfaction with shared decision making and all subcomponents. Overall satisfaction, perceived support, certainty, and perceived effectiveness of decision-making were lowest when a high number of navigating clicks occurred absent "looping." CONCLUSIONS: Linguistic features of patient-provider communication and system use data of a decision aid predict patients' satisfaction with shared decision making. Our findings have implications for the design of decision aid tools and clinician training to support more effective shared decision-making for screening mammography.

Coaching older adults discharged home from the emergency department: The role of competence and emotion in following up with outpatient clinicians.

OBJECTIVE: Motivating older adults to follow up with an outpatient clinician after discharge from emergency departments (ED) is beneficial yet challenging. We aimed to answer whether psychological needs for motivation and discrete emotions observed by care transition coaches would predict this behavioral outcome. METHODS: Community-dwelling older adults following ED discharge were recruited from three EDs in two U.S. states. We examined home visit notes documented by coaches (N = 725). Retrospective chart reviews of medical records tracked participants' health care utilization for 30 days. RESULTS: Observed knowledge-based competence predicted higher likelihood of outpatient follow-up within 30 days, while observed sadness predicted a lower likelihood of follow-up within seven days following discharge. Moreover, participants who demonstrated happiness were marginally more likely to have an in-person follow-up within seven days, and those who demonstrated knowledge-based competence were more likely to have an electronic follow-up within 30 days. CONCLUSIONS: Knowledge-based competence and emotions, as observed and documented in coach notes, can predict older adults' subsequent outpatient follow-up following their ED-discharge. PRACTICE IMPLICATIONS: Intervention programs might encourage coaches to check knowledge-based competence and to observe emotions in addition to delivering the content. Coaches could also customize strategies for patients with different recommended timeframes of follow-up.

Ideology and COVID-19 Vaccination Intention: Perceptual Mediators and Communication Moderators.

Widespread COVID-19 vaccination is critical to slow the spread of the illness. This study investigates how political ideology is associated with COVID-19 vaccine intention via perceived effectiveness of the vaccine, perceived side effects, and perceived severity of the illness, three key aspects of the Health Belief Model (HBM). This study also examines how partisan information flow moderates the effects of ideology on these three HBM components. Using survey data collected from two battleground states in the 2020 election (N = 1849), regression, mediation and moderation analyses revealed that conservatives were less likely to intend to get vaccinated against COVID-19, and this association was significantly mediated by perceived effectiveness and perceived side effects of vaccination, as well as perceived severity of COVID-19. In addition, partisanship of news sources and discussion partners were significant moderators of ideology's association with perceived vaccine effectiveness, with conservatives viewing COVID-19 vaccination as less effective if they were frequently exposed to liberal news, and if they had frequent conversations with fellow conservatives. This suggests boomerang effects for cross-cutting mass media exposure, and reinforcement effect for interpersonal communication. Implications for efforts to promote COVID-19 vaccine uptake are discussed, including tailored and targeted campaign strategies.

Vaccine discourse during the onset of the COVID-19 pandemic: Topical structure and source patterns informing efforts to combat vaccine hesitancy.

BACKGROUND: Understanding public discourse about a COVID-19 vaccine in the early phase of the COVID-19 pandemic may provide key insights concerning vaccine hesitancy. However, few studies have investigated the communicative patterns in which Twitter users participate discursively in vaccine discussions. OBJECTIVES: This study aims to investigate 1) the major topics that emerged from public conversation on Twitter concerning vaccines for COVID-19, 2) the topics that were emphasized in tweets with either positive or negative sentiment toward a COVID-19 vaccine, and 3) the type of online accounts in which tweets with either positive or negative sentiment were more likely to circulate. METHODS: We randomly extracted a total of 349,979 COVID-19 vaccine-related tweets from the initial period of the pandemic. Out of 64,216 unique tweets, a total of 23,133 (36.03%) tweets were classified as positive and 14,051 (21.88%) as negative toward a COVID-19 vaccine. We conducted Structural Topic Modeling and Network Analysis to reveal the distinct topical structure and connection patterns that characterize positive and negative discourse toward a COVID-19 vaccine. RESULTS: Our STM analysis revealed the most prominent topic emerged on Twitter of a COVID-19 vaccine was "other infectious diseases", followed by "vaccine safety concerns", and "conspiracy theory." While the positive discourse demonstrated a broad range of topics such as "vaccine development", "vaccine effectiveness", and "safety test", negative discourse was more narrowly focused on topics such as "conspiracy theory" and "safety concerns." Beyond topical differences, positive discourse was more likely to interact with verified sources such as scientists/medical sources and the media/journalists, whereas negative discourse tended to interact with politicians and online influencers. CONCLUSIONS: Positive and negative discourse was not only structured around distinct topics but also circulated within different networks. Public health communicators need to address specific topics of public concern in varying information hubs based on audience segmentation, potentially increasing COVID-19 vaccine uptake.

Environmental and genetic risk factors for gastric cancer.

Gastric cancer is a heterogeneous and prevalent disease. The traditional environmental exposures associated with an elevated risk of gastric cancer are less prevalent in the United States today. Genetic risks and risks associated with inflammation remain. Most cases are sporadic and familial clustering is observed in about 10% of the cases. Hereditary gastric cancer accounts for a very low percentage of cases. Here we review the genetic and environmental risk factors associated with the disease.

Inhibition of MNKs promotes macrophage immunosuppressive phenotype to limit CD8+ T cell antitumor immunity.

To elicit effective antitumor responses, CD8+ T cells need to infiltrate tumors and sustain their effector function within the immunosuppressive tumor microenvironment (TME). Here, we evaluate the role of MNK activity in regulating CD8+ T cell infiltration and antitumor activity in pancreatic and thyroid tumors. We first show that human pancreatic and thyroid tumors with increased MNK activity are associated with decreased infiltration by CD8+ T cells. We then show that, while MNK inhibitors increase CD8+ T cells in these tumors, they induce a T cell exhaustion phenotype in the tumor microenvironment. Mechanistically, we show that the exhaustion phenotype is not caused by upregulation of programmed cell death ligand 1 (PD-L1) but is caused by tumor-associated macrophages (TAMs) becoming more immunosuppressive following MNK inhibitor treatment. Reversal of CD8+ T cell exhaustion by an anti-PD-1 antibody or TAM depletion synergizes with MNK inhibitors to control tumor growth and prolong animal survival. Importantly, we show in ex vivo human pancreatic tumor slice cultures that MNK inhibitors increase the expression of markers associated with immunosuppressive TAMs. Together, these findings demonstrate a role of MNKs modulating a protumoral phenotype in macrophages and identify combination regimens involving MNK inhibitors to enhance antitumor immune responses.

Intraindividual, Dyadic, and Network Communication in a Digital Health Intervention: Distinguishing Message Exposure from Message Production.

Communicating within digital health interventions involves a range of behaviors that may contribute to the management of chronic illnesses in different ways. This study examines whether communication within a smartphone-based application for addiction recovery produces distinct effects depending on 1) the "level" of communication, defined as intraindividual communication (e.g., journal entries to oneself); dyadic communication (e.g., private messaging to other individuals); or network communication (e.g., discussion forum posts to all group members), and 2) whether individuals produce or are exposed to messages. We operationalize these communication levels and behaviors based on system use logs as the number of clicks dedicated to each activity and assess how each category of system use relates to changes in group bonding and substance use after 6 months with the mobile intervention. Our findings show that (1) intraindividual exposure to one's own past posts marginally predicts decreased drug use; (2) dyadic production predicts greater perceived bonding; while dyadic exposure marginally predicts reduced drug use; (3) network production predicts decreased risky drinking. Implications for digital health interventions are discussed.

News Attention and Social-Distancing Behavior Amid COVID-19: How Media Trust and Social Norms Moderate a Mediated Relationship.

Despite the fact that social distancing is an effective mean to slow the spread of COVID-19, individuals often fail to practice this behavior. Major US news media provided information to the public about social distancing after COVID-19 was declared a pandemic, potentially spurring this preventative health practice. Using data from a representative sample of US residents, this study aims to understand the relationship between news media attention and social-distancing behavior via three potential mediators: perceived effectiveness of social distancing, perceived susceptibility to COVID-19 infection, and perceived negative consequences of infection. Media trust and social norms concerning social distancing were included as potential moderators of these relationships, along with political ideology. With multiple regression and mediation analyses, we found that news media attention was positively associated with social-distancing behavior during this period. Perceived effectiveness of social distancing mediated this relationship, while perceived susceptibility and negative consequences of COVID-19 did not. Notably, media trust negatively moderated news attention's impact on the perceived effectiveness of social distancing, with the relationship being more pronounced among those who have lower trust in media. Political ideology did not moderate the relationship between news attention and perceived effectiveness. Further, social norms negatively moderated the relationship between perceived effectiveness and social-distancing behavior, with this relationship growing stronger among those uncertain about the adoption of social-distancing norms in their circle. Overall, the study found news media to have an important role in promoting social-distancing behavior when they emphasized safety measures across the ideological spectrum.

Effect of an eHealth intervention on older adults' quality of life and health-related outcomes: a randomized clinical trial.

BACKGROUND: By 2030, the number of US adults age ≥65 will exceed 70 million. Their quality of life has been declared a national priority by the US government. OBJECTIVE: Assess effects of an eHealth intervention for older adults on quality of life, independence, and related outcomes. DESIGN: Multi-site, 2-arm (1:1), non-blinded randomized clinical trial. Recruitment November 2013 to May 2015; data collection through November 2016. SETTING: Three Wisconsin communities (urban, suburban, and rural). PARTICIPANTS: Purposive community-based sample, 390 adults age ≥65 with health challenges. EXCLUSIONS: long-term care, inability to get out of bed/chair unassisted. INTERVENTION: Access (vs. no access) to interactive website (ElderTree) designed to improve quality of life, social connection, and independence. MEASURES: Primary outcome: quality of life (PROMIS Global Health). Secondary: independence (Instrumental Activities of Daily Living); social support (MOS Social Support); depression (Patient Health Questionnaire-8); falls prevention (Falls Behavioral Scale). Moderation: healthcare use (Medical Services Utilization). Both groups completed all measures at baseline, 6, and 12 months. RESULTS: Three hundred ten participants (79%) completed the 12-month survey. There were no main effects of ElderTree over time. Moderation analyses indicated that among participants with high primary care use, ElderTree (vs. control) led to better trajectories for mental quality of life (OR=0.32, 95% CI 0.10-0.54, P=0.005), social support received (OR=0.17, 95% CI 0.05-0.29, P=0.007), social support provided (OR=0.29, 95% CI 0.13-0.45, P<0.001), and depression (OR= -0.20, 95% CI -0.39 to -0.01, P=0.034). Supplemental analyses suggested ElderTree may be more effective among people with multiple (vs. 0 or 1) chronic conditions. LIMITATIONS: Once randomized, participants were not blind to the condition; self-reports may be subject to memory bias. CONCLUSION: Interventions like ET may help improve quality of life and socio-emotional outcomes among older adults with more illness burden. Our next study focuses on this population. TRIAL REGISTRATION: ClinicalTrials.gov ; registration ID number: NCT02128789.

The Relationship among COVID-19 Information Seeking, News Media Use, and Emotional Distress at the Onset of the Pandemic.

Although several theories posit that information seeking is related to better psychological health, this logic may not apply to a pandemic like COVID-19. Given uncertainty inherent to the novel virus, we expect that information seeking about COVID-19 will be positively associated with emotional distress. Additionally, we consider the type of news media from which individuals receive information-television, newspapers, and social media-when examining relationships with emotional distress. Using a U.S. national survey, we examine: (1) the link between information seeking about COVID-19 and emotional distress, (2) the relationship between reliance on television, newspapers, and social media as sources for news and emotional distress, and (3) the interaction between information seeking and use of these news media sources on emotional distress. Our findings show that seeking information about COVID-19 was significantly related to emotional distress. Moreover, even after accounting for COVID-19 information seeking, consuming news via television and social media was tied to increased distress, whereas consuming newspapers was not significantly related to greater distress. Emotional distress was most pronounced among individuals high in information seeking and television news use, whereas the association between information seeking and emotional distress was not moderated by newspapers or social media news use.

Prospective Prediction of Lapses in Opioid Use Disorder: Protocol for a Personal Sensing Study.

BACKGROUND: Successful long-term recovery from opioid use disorder (OUD) requires continuous lapse risk monitoring and appropriate use and adaptation of recovery-supportive behaviors as lapse risk changes. Available treatments often fail to support long-term recovery by failing to account for the dynamic nature of long-term recovery. OBJECTIVE: The aim of this protocol paper is to describe research that aims to develop a highly contextualized lapse risk prediction model that forecasts the ongoing probability of lapse. METHODS: The participants will include 480 US adults in their first year of recovery from OUD. Participants will report lapses and provide data relevant to lapse risk for a year with a digital therapeutic smartphone app through both self-report and passive personal sensing methods (eg, cellular communications and geolocation). The lapse risk prediction model will be developed using contemporary rigorous machine learning methods that optimize prediction in new data. RESULTS: The National Institute of Drug Abuse funded this project (R01DA047315) on July 18, 2019 with a funding period from August 1, 2019 to June 30, 2024. The University of Wisconsin-Madison Health Sciences Institutional Review Board approved this project on July 9, 2019. Pilot enrollment began on April 16, 2021. Full enrollment began in September 2021. CONCLUSIONS: The model that will be developed in this project could support long-term recovery from OUD-for example, by enabling just-in-time interventions within digital therapeutics. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29563.