Influencing public acceptance of artificial intelligence (AI) in healthcare delivery

Frontiers in Digital Health · 2026-01-13 · 3 citations

Introduction Despite the potential of artificial intelligence (AI) to transform healthcare delivery and reduce costs, adoption remains uneven across populations. Understanding the demographic, behavioral, and cognitive factors influencing public willingness to use AI-powered health tools is critical for equitable implementation. This study examined determinants of AI adoption in healthcare among adults in the United States (U.S.). Methods A cross-sectional survey was conducted between March and June 2024 using convenience sampling across the U.S. The study included 568 adult respondents recruited via Qualtrics. The survey assessed demographic characteristics, digital health behaviors, self-reported health status, cognitive and attitudinal factors, and behavioral intentions related to AI use in healthcare. Logistic regression models were used to examine associations between predictors and willingness to adopt AI, with z-tests for subgroup comparisons and Bonferroni correction applied for multiple hypothesis testing. Results The sample was predominantly female (66.7%) and Hispanic/Latino (50.7%), with moderate income and education levels. Older age was negatively associated with AI adoption ( β = −0.029), males were less likely to use AI than females ( β = −0.388), and income was positively correlated with AI adoption ( β = 0.096). Trust in AI was substantially lower than trust in physicians: 14.6% trusted ChatGPT's diagnosis for serious illness compared with 92.3% trusting physicians, and 17.1% versus 96.4% for specialist referrals. Telehealth use strongly predicted AI adoption ( β = 1.012), while lower self-rated mental health was associated with higher AI use ( β = −0.254). Uninsured participants reported higher trust in AI diagnostic capabilities than insured participants (57% vs. 43%, p < 0.05). Ethnic differences were observed, with Asian participants reporting higher AI usage rates than Hispanic participants (16.49% vs. 5.56%, p < 0.05). Discussion AI adoption in healthcare is shaped by the interaction of demographic, socioeconomic, and cultural factors. While AI has the potential to expand healthcare access, adoption patterns reflect existing disparities in healthcare access and trust. Trust emerged as a central determinant, with AI functioning as a compensatory tool when traditional healthcare access is limited. Given the U.S.-specific context, findings should be interpreted as exploratory and may not generalize to other healthcare systems. These results highlight the need for future research on transparency, digital literacy, and structural barriers to support equitable implementation of healthcare AI.

Impact of Sex on Viral Shedding and Symptom Severity During Acute COVID-19

Pathogens and Immunity · 2026-05-06

Background: To evaluate the impact of sex on acute SARS-CoV-2 infection, 668 participants from the ACTIV-2/A5401 study were followed over a 28-day period. Methods: A primary analysis was performed on 469 participants with quantifiable viral loads at baseline. Results: Male and female participants had comparable nasal SARS-CoV-2 RNA levels at study entry and throughout follow-up. However, sex-specific differences in viral shedding emerged when stratified by symptom duration. In the first 3 days after symptom onset, female participants exhibited higher nasal SARS-CoV-2 RNA levels than males, but lower viral RNA levels thereafter. The higher viral RNA levels in females during the earliest phase of acute COVID-19 were observed even after adjusting for age, race, and region of enrollment. Female participants also tended to have higher symptom scores across days since symptom onset, but no significant correlation was observed between nasal SARS-CoV-2 RNA levels and symptom score regardless of sex. Conclusion: These findings highlight the impact of sex on both viral shedding and symptom dynamics and underscore the importance of considering time since symptom onset when evaluating antiviral therapies for respiratory viruses in clinical trials.

Association of long COVID with health-related quality-of-life outcomes

Scientific Reports · 2026-03-19

The association of long COVID with health-related quality-of-life (HrQOL) has not been well-characterized. Participants who received blinded placebo in the ACTIV-2/A5401 outpatient COVID-19 treatment trial were included in an analysis of the association of long COVID with HrQOL (both pre-specified exploratory trial endpoints) 9 months after acute COVID-19. Long COVID was defined as presence of self-assessed COVID-19 symptoms and HrQOL was assessed with EQ-5D-5L and SF-36v2 questionnaires. Associations were evaluated by Fisher's exact tests and Wilcoxon rank-sum tests. Of 546 participants, 13% had long COVID. Long COVID was associated with greater risk of reported problems in the EQ-5D-5L dimensions of mobility, usual activities, pain/discomfort, and anxiety/depression (risk ratios 3.45-6.00, all p < 0.001) and worse self-reported health scores (median 80 vs. 95, p < 0.001). Participants with long COVID also had worse SF-36v2 composite physical and mental component scores (both p < 0.001) and individual SF-36 domain scores (physical functioning, physical role, bodily pain, general health, vitality, social functioning, emotional role, and mental health; all p < 0.001). Associations were similar regardless of baseline (pre-COVID-19) medical history. Long COVID is associated with impaired HrQOL across multiple domains, highlighting the need to develop preventative and therapeutic interventions for this protean condition.

Implementation of a seamless phase 2/3 study design in the setting of an emergent infectious disease pandemic: Lessons learned from the ACTIV-2 platform COVID-19 treatment trial

UNC Libraries · 2026-03-26

Will animal reservoirs give us the next SARS-CoV-2 variant?

PLoS Pathogens · 2026-03-03

Effect of inhaled interferon-β1a on SARS-CoV-2 diversity and evolution

Microbiology Spectrum · 2026-05-18

ABSTRACT Interferon resistance has been implicated in SARS-CoV-2 escape from innate immunity, but exogenous interferon’s impact on viral evolution and diversity is unknown. SNG001, an inhaled interferon-β1a treatment, was evaluated in the ACTIV-2/A5401 randomized controlled trial of therapeutics for COVID-19. We measured viral kinetics and performed whole-genome sequencing on longitudinal nasal swabs collected from ACTIV-2 participants who received either SNG001 or placebo to assess viral sequence diversity. No difference in nasal viral load decay was detected between study arms when stratifying by SARS-CoV-2 variant or by viral culture conversion. Compared to placebo participants, the SNG001-treated participants displayed significantly lower nonsynonymous amino acid average pairwise distance, indicating lower sequence diversity. Similarly, SNG001-treated individuals also developed numerically fewer nonsynonymous mutations during their infection in ORF1a, ORF1b, Spike, and Nucleocapsid. No specific emerging SARS-CoV-2 nonsynonymous amino acid changes indicating signatures of viral escape were enriched in those receiving SNG001. These in vivo data provide an intriguing signal that exogenous interferon-β1a may restrict SARS-CoV-2 viral diversity and add to growing evidence that interferon levels play a critical role in antiviral responses during COVID-19. IMPORTANCE SARS-CoV-2 encodes several genes which can antagonize the interferon signaling cascade, preventing it from activating antiviral responses and thereby facilitating viral establishment and dissemination. It is unknown how the administration of exogenous interferon might affect viral evolution and immune escape. ACTIV-2/A5401 represents a unique opportunity to study the virologic effects of interferon treatment in a rigorous randomized, placebo-controlled clinical trial setting. Our characterization of longitudinal nasal samples shows that interferon-treated individuals had lower viral diversity and no evidence of viral escape mutations. CLINICAL TRIALS This study is registered with ClinicalTrials.gov as NCT04518410 .

Characterization of HIV humoral immunity during analytical treatment interruption

Journal of Clinical Virology · 2026-03-03

INTRODUCTION: This study investigated whether HIV binding antibody (Ab) and p24 antigen (Ag) quantitation could detect humoral immune responses or p24 Ag before or following detectable plasma viral load (VL) rebound during antiretroviral therapy interruption (ATI) and provide insights into post-rebound viral replication. METHODS: Longitudinal plasma samples collected before and following ATI from 40 participants (485 samples; mean of 12/participant) in the ACTG A5345 study who began antiretroviral therapy during either acute or chronic stages of infection were analyzed using commercial immunoassays to assess HIV Ab and Ag dynamics, including following dissociation of immune complexes for improved Ag detection. RESULTS: Neither Ab nor Ag levels increased in plasma before VL rebound. However, 75% of participants exhibited increased Ab reactivity concurrent with or shortly after VL rebound, which declined upon ART reinitiation. Participants who were ART-treated early had lower Ab levels at ATI initiation but demonstrated greater fold increases in Ab during ATI than late-treated participants. Two participants who demonstrated post-treatment control of VL showed gradual Ab increases that paralleled intermittent VL elevations. p24 Ag was only detectable after dissociating immune complexes in samples with VL > 10⁴ RNA copies/mL, correlating strongly with VL levels. CONCLUSIONS: Although antibody levels did not predict viral rebound, tracking their longitudinal changes provided meaningful information about viral replication patterns and immune reactivation during and after rebound, offering a practical tool for monitoring ATI outcomes.

Minimal Disruption of the Rectal Microbiome in Acute and Early Untreated HIV Infection

JAIDS Journal of Acquired Immune Deficiency Syndromes · 2026-04-09

BACKGROUND: Alterations in the gut microbiome have been linked to chronic HIV infection, yet less is known about microbiome dynamics during the earliest phases of HIV acquisition. It remains unclear whether microbial changes precede or follow HIV infection, and whether specific taxa could serve as early biomarkers or modulators of disease progression. SETTING: The San Diego Primary Infection Resource Consortium (PIRC), a large HIV resource infrastructure program that enrolled predominantly men who have sex with men in Southern California, USA. METHODS: We analyzed rectal swabs from 316 participants, 86 without HIV, 100 with acute (≤30 days post-infection) and 130 with early (31-180 days) untreated HIV infection. 16S rRNA sequencing was used to characterize bacterial communities. Alpha and beta diversity metrics, and taxon-level relative abundance were compared across groups using generalized linear models and MaAsLin3, adjusting for confounders and correcting for false discovery rate (FDR). RESULTS: No significant differences in Shannon and Pielou index or beta diversity were observed by HIV status or stage. However, HIV infection was independently associated with a modest reduction in microbial richness (observed species; p=0.039). Enterocloster clostridioformis was significantly depleted among people with HIV (aβ -1.31, FDR p<0.001). Among participants with HIV, relative abundance of Akkermansia muciniphila was positively correlated with plasma HIV RNA levels (aβ 0.48, FDR p=0.016). CONCLUSION: The rectal bacteriome remains largely preserved during the first six months of untreated HIV infection. Subtle taxon-specific changes may reflect early viro-immunological perturbations but suggest limited diagnostic and prognostic utility of microbiome profiling.

Cell-type specific impact of opioid use disorder and HIV on the human forebrain and cerebellum

bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-03

Abstract Opioid use disorder (OUD), which frequently co-occurs with HIV infection, causes long-term neurological disease, yet the epigenetic and transcriptomic effects of OUD and HIV on specific cell types and regions of the brain are poorly understood. To assess the cell-type specific impacts of OUD and HIV across the human brain, we measured single cell transcriptomes and epigenomes of 580,353 cells in the prefrontal cortex, amygdala and cerebellum of 44 donors. We cataloged over 750k candidate cis -regulatory elements (cCREs) and identified gene regulatory networks (GRNs) of transcription factor activity across 35 neuronal and non-neuronal cell types. We identified specific neuronal and glial populations whose cCREs were significantly enriched for genetic risk of addiction-related traits. In OUD donors, we found evidence for reduced metabolic function in neurons in the PFC and cerebellum as well as increased gene expression related to voltage-gated calcium channel activity in the cerebellum. Using a cerebellar organoid model, fentanyl treatment reduced metabolic activity while increasing neuronal activity. Across brain regions, HIV activated immune-related pathways in glial populations, while comorbid OUD and HIV exacerbated metabolic changes in cortical glial cells. Cerebellum-specific Bergmann glia, in addition to forebrain microglia and astrocytes, showed expansion of reactive state identity in HIV. These results highlight shared and specific changes to immune, synaptic, and metabolic processes in OUD and HIV across brain regions and reveal that cerebellar cell types are distinctly affected by opioid abuse.

Mapping opioid exposure through prescription data and postmortem analysis of opioid drugs in multiple tissues

British Journal of Clinical Pharmacology · 2026-03-30

BACKGROUND AND PURPOSE: Although opioids are central to end of life (EoL) care, tissue-level opioid exposure remains poorly understood. The objective of this study was to characterize the relationship between prescription-derived morphine equivalent daily dose (MEDD) and measured morphine concentrations across multiple organs. EXPERIMENTAL APPROACH: We analysed data from the Last Gift cohort, a community-centred HIV research rapid autopsy programme. Cumulative MEDD for the final 7 and 30 days before death (MEDD-7, MEDD-30) was calculated using prescription data. Postmortem samples from multiple organs were analysed using ultra-high-performance liquid chromatography with tandem mass spectrometry to quantify opioids. Mixed-effects regression models and Pearson correlations evaluated relationships between MEDD and tissue morphine concentrations. KEY RESULTS: Among 261 samples from 27 participants (median age 65 years), 96% had ≥1 detectable opioid. Morphine was most frequently prescribed (78%), followed by fentanyl (41%), hydromorphone (37%), and oxycodone (33%). Median MEDD-7 and MEDD-30 were 940 (IQR 158-3481) and 3430 (IQR 563-9972), respectively. Morphine concentrations were highest in the ascending colon, kidney, duodenum, and liver, and lowest in adipose tissue and cerebrospinal fluid. Tissue morphine concentrations correlated with both MEDD-7 and MEDD-30 (e.g., medulla r = .80; spinal cord r = .77; parietal cortex r = .72; all p < .01). In adjusted mixed-effects models, each 10-fold increase in MEDD-7/-30 predicted a 3.7- to 3.8-fold increase in tissue morphine concentration. CONCLUSION AND IMPLICATIONS: Prescription-based morphine exposure was strongly associated with morphine tissue concentrations across multiple organs, providing a quantitative framework for integrating pharmacologic data into EoL research.