Tag: pubmed

J Radiol Prot. 2024 Dec 16. doi: 10.1088/1361-6498/ad9f73. Online ahead of print.

ABSTRACT

In short terms, a society’s available resources are finite and must be prioritised. The more resources that are spent on radiological protection, the lesser resources are available for other needs. The ALARA principle states that exposure of ionizing radiation should be kept as low as reasonably achievable, taking into account economic and societal factors. In practice, one of several approaches to determine what is considered as reasonably achievable is cost-benefit analysis. A demanding part of cost-benefit analysis is to decide on an α value, which stipulates the value of radiological protection. There are different conversion methods on how to convert societal costs into an α value. However, with the assistance of recent developments within both health economics and radiological protection room for improvements was found. Therefore, the aims of the present study were to develop a new conversion method (on how to convert societal costs into an α value) and to provide recommendations of α values for each member country of The Organisation for Economic Co-operation and Development (OECD). With the help of systematic reviews of societal costs (the value of a statistical life, productivity losses and healthcare costs) and discount rates, as well as Monte Carlo simulations of the number of years between exposure and cancer diagnosis, a new conversion method and recommendations of α values could be presented. The new conversion method was expressed as a discounted nominal risk of exposure with a median (interquartile range) of 175 (136-222) per 10 000 persons per Sv for the public and 169 (134-207) per 10 000 persons per Sv for workers. For OECD in general, recommendations of α values were determined to be $56-170 per man.mSv for the public and $61-162 per man.mSv for workers (2023-USD).

PMID:39681002 | DOI:10.1088/1361-6498/ad9f73

J Med Internet Res. 2024 Dec 16;26:e63476. doi: 10.2196/63476.

ABSTRACT

BACKGROUND: The number of confirmed COVID-19 cases is a crucial indicator of policies and lifestyles. Previous studies have attempted to forecast cases using machine learning techniques that use a previous number of case counts and search engine queries predetermined by experts. However, they have limitations in reflecting temporal variations in queries associated with pandemic dynamics.

OBJECTIVE: This study aims to propose a novel framework to extract keywords highly associated with COVID-19, considering their temporal occurrence. We aim to extract relevant keywords based on pandemic variations using query expansion. Additionally, we examine time-delayed web-based search behavior related to public interest in COVID-19 and adjust for better prediction performance.

METHODS: To capture temporal semantics regarding COVID-19, word embedding models were trained on a news corpus, and the top 100 words related to “Corona” were extracted over 4-month windows. Time-lagged cross-correlation was applied to select optimal time lags correlated to confirmed cases from the expanded queries. Subsequently, ElasticNet regression models were trained after reducing the feature dimensions using principal component analysis of the time-lagged features to predict future daily case counts.

RESULTS: Our approach successfully extracted relevant keywords depending on the pandemic phase, encompassing keywords directly related to COVID-19, such as its symptoms, and its societal impact. Specifically, during the first outbreak, keywords directly linked to COVID-19 and past infectious disease outbreaks similar to those of COVID-19 exhibited a high positive correlation. In the second phase of the pandemic, as community infections emerged, keywords related to the government’s pandemic control policies were frequently observed with a high positive correlation. In the third phase of the pandemic, during the delta variant outbreak, keywords such as “economic crisis” and “anxiety” appeared, reflecting public fatigue. Consequently, prediction models trained by the extracted queries over 4-month windows outperformed previous methods for most predictions 1-14 days ahead. Notably, our approach showed significantly higher Pearson correlation coefficients than models based solely on the number of past cases for predictions 9-11 days ahead (P=.02, P<.01, and P<.01), in contrast to heuristic- and symptom-based query sets.

CONCLUSIONS: This study proposes a novel COVID-19 case-prediction model that automatically extracts relevant queries over time using word embedding. The model outperformed previous methods that relied on static symptom-based or heuristic queries, even without prior expert knowledge. The results demonstrate the capability of our approach to track temporal shifts in public interest regarding changes in the pandemic.

PMID:39680913 | DOI:10.2196/63476

Ecol Evol Physiol. 2024 Sep-Oct;97(5):274-291. doi: 10.1086/732781. Epub 2024 Sep 27.

ABSTRACT

AbstractMammalian herbivory represents a complex adaptation requiring evolutionary changes across all levels of biological organization, from molecules to morphology to behavior. Explaining the evolution of such complex traits represents a major challenge in biology, as it is simultaneously muddled and enlightened by a growing awareness of the crucial role of symbiotic associations in shaping organismal adaptations. The concept of hologenomic evolution includes the partnered unit of the holobiont, the host with its microbiome, as a selection unit that may undergo adaptation. Here, we test some of the assumptions underlying the concept of hologenomic evolution using a unique experimental evolution model: lines of the bank vole (Myodes [=Clethrionomys] glareolus) selected for increased ability to cope with a low-quality herbivorous diet and unselected control lines. Results from a complex nature-nurture design, in which we combined cross-fostering between the selected and control lines with dietary treatment, showed that the herbivorous voles harbored a cecal microbiome with altered membership and structure and changed abundances of several phyla and genera regardless of the origin of their foster mothers. Although the differences were small, they were statistically significant and partially robust to changes in diet and housing conditions. Microbial characteristics also correlated with selection-related traits at the level of individual variation. Thus, the results support the hypothesis that selection on a host performance trait leads to genetic changes in the host that promote the maintenance of a beneficial microbiome. Such a result is consistent with some of the assumptions underlying the concept of hologenomic evolution.

PMID:39680902 | DOI:10.1086/732781

Asian Pac Isl Nurs J. 2024 Dec 16;8:e67928. doi: 10.2196/67928.

ABSTRACT

BACKGROUND: The Fourth Industrial Revolution is transforming the health care sector through advanced technologies such as artificial intelligence, the Internet of Things, and big data, leading to new expectations for rapid and accurate treatment. While the integration of technology in nursing tasks is on the rise, there remains a critical need to balance technological efficiency with empathy and emotional connection. This study aims to develop and validate a competency model for emotional touch nursing that responds to the evolving demands of the changing health care environment.

OBJECTIVE: The aims of our study are to develop an emotional touch nursing competencies model and to verify its reliability and validity.

METHODS: A conceptual framework and construct factors were developed based on an extensive literature review and in-depth interviews with nurses. The potential competencies were confirmed by 20 experts, and preliminary questions were prepared. The final version of the scale was verified through exploratory factor analysis (n=255) and confirmatory factor analysis (n=256) to assess its validity and reliability.

RESULTS: From the exploratory analysis, 8 factors and 38 items (client-centered collaborative practice, learning agility for nursing, nursing professional commitment, positive self-worth, compliance with ethics and roles, nursing practice competence, nurse-client relationship, and nursing sensitivity) were extracted. These items were verified through convergent and discriminant validity testing. The internal consistency reliability was acceptable (Cronbach α=0.95).

CONCLUSIONS: The findings from this study confirmed that this scale has sufficient validity and reliability to measure emotional touch nursing competencies. It is expected to be used to build a knowledge and educational system for emotional touch nursing.

PMID:39680900 | DOI:10.2196/67928

J Med Internet Res. 2024 Dec 16;26:e60794. doi: 10.2196/60794.

ABSTRACT

BACKGROUND: Given the public release of large language models, research is needed to explore whether older adults would be receptive to personalized medication advice given by artificial intelligence (AI) tools.

OBJECTIVE: This study aims to identify predictors of the likelihood of older adults stopping a medication and the influence of the source of the information.

METHODS: We conducted a web-based experimental survey in which US participants aged ≥65 years were asked to report their likelihood of stopping a medication based on the source of information using a 6-point Likert scale (scale anchors: 1=not at all likely; 6=extremely likely). In total, 3 medications were presented in a randomized order: aspirin (risk of bleeding), ranitidine (cancer-causing chemical), or simvastatin (lack of benefit with age). In total, 5 sources of information were presented: primary care provider (PCP), pharmacist, AI that connects with the electronic health record (EHR) and provides advice to the PCP (“EHR-PCP”), AI with EHR access that directly provides advice (“EHR-Direct”), and AI that asks questions to provide advice (“Questions-Direct”) directly. We calculated descriptive statistics to identify participants who were extremely likely (score 6) to stop the medication and used logistic regression to identify demographic predictors of being likely (scores 4-6) as opposed to unlikely (scores 1-3) to stop a medication.

RESULTS: Older adults (n=1245) reported being extremely likely to stop a medication based on a PCP’s recommendation (n=748, 60.1% [aspirin] to n=858, 68.9% [ranitidine]) compared to a pharmacist (n=227, 18.2% [simvastatin] to n=361, 29% [ranitidine]). They were infrequently extremely likely to stop a medication when recommended by AI (EHR-PCP: n=182, 14.6% [aspirin] to n=289, 23.2% [ranitidine]; EHR-Direct: n=118, 9.5% [simvastatin] to n=212, 17% [ranitidine]; Questions-Direct: n=121, 9.7% [aspirin] to n=204, 16.4% [ranitidine]). In adjusted analyses, characteristics that increased the likelihood of following an AI recommendation included being Black or African American as compared to White (Questions-Direct: odds ratio [OR] 1.28, 95% CI 1.06-1.54 to EHR-PCP: OR 1.42, 95% CI 1.17-1.73), having higher self-reported health (EHR-PCP: OR 1.09, 95% CI 1.01-1.18 to EHR-Direct: OR 1.13 95%, CI 1.05-1.23), having higher confidence in using an EHR (Questions-Direct: OR 1.36, 95% CI 1.16-1.58 to EHR-PCP: OR 1.55, 95% CI 1.33-1.80), and having higher confidence using apps (EHR-Direct: OR 1.38, 95% CI 1.18-1.62 to EHR-PCP: OR 1.49, 95% CI 1.27-1.74). Older adults with higher health literacy were less likely to stop a medication when recommended by AI (EHR-PCP: OR 0.81, 95% CI 0.75-0.88 to EHR-Direct: OR 0.85, 95% CI 0.78-0.92).

CONCLUSIONS: Older adults have reservations about following an AI recommendation to stop a medication. However, individuals who are Black or African American, have higher self-reported health, or have higher confidence in using an EHR or apps may be receptive to AI-based medication recommendations.

PMID:39680885 | DOI:10.2196/60794

JMIR Mhealth Uhealth. 2024 Dec 16;12:e63316. doi: 10.2196/63316.

ABSTRACT

BACKGROUND: Obsessive-compulsive disorder (OCD) is the third most prevalent mental health disorder in Singapore, with a high degree of burden and large treatment gaps. Self-guided programs on mobile apps are accessible and affordable interventions, with the potential to address subclinical OCD before symptoms escalate.

OBJECTIVE: This randomized controlled trial aimed to examine the efficacy of a self-guided OCD program on the mobile health (mHealth) app Intellect in improving subclinical OCD and maladaptive perfectionism (MP) as a potential moderator of this predicted relationship.

METHODS: University students (N=225) were randomly assigned to an 8-day, self-guided app program on OCD (intervention group) or cooperation (active control). Self-reported measures were obtained at baseline, after the program, and at a 4-week follow-up. The primary outcome measure was OCD symptom severity (Obsessive Compulsive Inventory-Revised [OCI-R]). Baseline MP was assessed as a potential moderator. Depression, anxiety, and stress (Depression Anxiety and Stress Scales-21) were controlled for during statistical analyses.

RESULTS: The final sample included 192 participants. The intervention group reported significantly lower OCI-R scores compared with the active control group after the intervention (partial eta-squared [η_p²]=0.031; P=.02) and at 4-week follow-up (η_p²=0.021; P=.044). A significant, weak positive correlation was found between MP and OCI-R levels at baseline (r=0.28; P<.001). MP was not found to moderate the relationship between condition and OCI-R scores at postintervention (P=.70) and at 4-week follow-up (P=.88).

CONCLUSIONS: This study provides evidence that the self-guided OCD program on the Intellect app is effective in reducing subclinical OCD among university students in Singapore. Future studies should include longer follow-up durations and study MP as a moderator in a broader spectrum of OCD symptom severity.

TRIAL REGISTRATION: ClinicalTrials.gov NCT06202677; https://clinicaltrials.gov/study/NCT06202677.

PMID:39680884 | DOI:10.2196/63316

J Chem Theory Comput. 2024 Dec 16. doi: 10.1021/acs.jctc.4c01389. Online ahead of print.

ABSTRACT

Free energy calculations for protein-ligand complexes have become widespread in recent years owing to several conceptual, methodological and technological advances. Central among these is the use of ensemble methods which permits accurate, precise and reproducible predictions and is necessary for uncertainty quantification. Absolute binding free energies (ABFEs) are challenging to predict using alchemical methods and their routine application in drug discovery has remained out of reach until now. Here, we apply ensemble alchemical ABFE methods to a large data set comprising 219 ligand-protein complexes and obtain statistically robust results with high accuracy (<1 kcal/mol). We compare equilibrium and nonequilibrium methods for ABFE predictions at large scale and provide a systematic critical assessment of each method. The equilibrium method is more accurate, precise, faster, computationally more cost-effective and requires a much simpler protocol, making it preferable for large scale and blind applications. We find that the calculated free energy distributions are non-normal and discuss the consequences. We recommend a definitive protocol to perform ABFE calculations optimally. Using this protocol, it is possible to perform thousands of ABFE calculations within a few hours on modern exascale machines.

PMID:39680850 | DOI:10.1021/acs.jctc.4c01389

Scand J Work Environ Health. 2024 Dec 16:4203. doi: 10.5271/sjweh.4203. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim was to develop a gender-specific European job exposure matrix (EuroJEM) for occupational physical workload and study its predictive validity for musculoskeletal pain in four European cohorts.

METHODS: National, gender-specific JEM from Finland, France, Norway and Sweden, based on self-reported exposure information, were evaluated for similarities in exposures, exposure definitions, and occupational coding. The EuroJEM harmonized five exposures: heavy lifting, faster breathing due to heavy workload, kneeling/squatting, forward bent posture, and working with hands above shoulder level. Our expert panel addressed disagreements and missing information to reach consensus on exposure levels across occupations. To assess predictive validity of the EuroJEM, we examined associations between the harmonized exposure measures and self-reported musculoskeletal pain across the four cohorts.

RESULTS: The EuroJEM provides semi-quantitative exposure estimates for 374 ISCO-88 (COM) occupational codes. Five categories of exposure were defined by the proportion of workers exposed within each occupation. Comparable and statistically significant associations were found between EuroJEM exposures and low back, shoulder, and knee pain across all cohorts and genders, except for knee pain among women in the Finnish cohort. For instance, in both genders heavy lifting, faster breathing due to heavy workload, and forward bent posture were statistically significantly associated with low-back pain in all four cohorts, with OR ranging from 1.25-2.18 (men) and 1.23-2.04 (women).

CONCLUSIONS: Despite differences in study populations and outcome definitions, good predictive validity was observed in each national cohort, suggesting that EuroJEM can be an effective tool for exposure assessment in large-scale European epidemiological studies.

PMID:39680844 | DOI:10.5271/sjweh.4203

J Can Dent Assoc. 2024 Sep;90:o7.

ABSTRACT

OBJECTIVES: A growing body of literature highlights the negative impact of the COVID-19 pandemic on the mental health of health care professionals. This paper explores the effects of gender and work/life factors on dentists’ mental health before and during the pandemic.

METHODS: Data were obtained from a cross-sectional, online survey of Canadian dentists, which was part of a broader study of Canadian professionals’ mental health challenges conducted in 2020-2021. Using logistic regression, we compared the influence of life stress, work stress, gender and role in practice on dentists’ self-rated mental health before and during the pandemic.

RESULTS: Respondents reported that their mental health had worsened during the pandemic. Among survey respondents (n = 397), women dentists (50%) reported worse mental health than men (39%). Those who had higher levels of work and life stress reported more mental health challenges both before and during the pandemic.

CONCLUSIONS: Our findings point to the need for more attention to dentists’ mental health and highlight the need for gender-sensitive mental health resources and supports for Canadian dentists.

PMID:39680811

J Can Dent Assoc. 2024 Oct;90:o5.

ABSTRACT

OBJECTIVES: To compare trends in teaching and placement of composite resin versus amalgam in posterior restorations in Canadian dental schools with those in the United States.

METHODS: Secondary descriptive and statistical analyses were performed on data from 2 previous studies. The data consisted of responses to questionnaires on teaching policies and the proportion of posterior restorations (amalgam and composite resin) performed in Canadian and US dental schools. Fisher’s exact test and 2-sample z-test were used to compare the proportions.

RESULTS: Canadian dental schools allocated less time than US schools to teaching composite resin restorations (p = 0.006): 22.2% of Canadian schools versus 76.4% of US schools devoted more than 50% of preclinical teaching time to such restorations. Canadian dental schools also dedicated more time to teaching amalgam restorations (p = 0.041): 33.3% of Canadian schools versus 8.8% of US schools devoted 50-75% of preclinical teaching time to amalgam restorations. Between 2008 and 2018, a significantly higher proportion of composite resin restorations were performed in US dental schools than in Canadian schools (p < 0.001).

CONCLUSIONS: In Canadian dental schools, teaching of posterior composite resin restorations was more conservative than in US schools. There was no consensus among Canadian and US dental schools on composite resin preparation techniques or contraindications. Clear, standardized guidelines pertaining to composite resin teaching policies are suggested.

PMID:39680810