One of the most common statistical analyses in experimental psychology concerns the comparison of two means using the frequentist t test. However, frequentist t tests do not quantify evidence and require various assumption tests. Recently, popularized Bayesian t tests do quantify evidence, but these were developed for scenarios where the two populations are assumed to have the same variance. As an alternative to both methods, we outline a comprehensive t test framework based on Bayesian model averaging. This new t test framework simultaneously takes into account models that assume equal and unequal variances, and models that use t-likelihoods to improve robustness to outliers. The resulting inference is based on a weighted average across the entire model ensemble, with higher weights assigned to models that predicted the observed data well. This new t test framework provides an integrated approach to assumption checks and inference by applying a series of pertinent models to the data simultaneously rather than sequentially. The integrated Bayesian model-averaged t tests achieve robustness without having to commit to a single model following a series of assumption checks. To facilitate practical applications, we provide user-friendly implementations in JASP and via the RoBTT package in R . A tutorial video is available at https://www.youtube.com/watch?v=EcuzGTIcorQ.
- MeSH
- Bayes Theorem MeSH
- Psychology, Experimental * methods MeSH
- Data Interpretation, Statistical MeSH
- Humans MeSH
- Models, Statistical * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Human migration is an increasingly common phenomenon and migrants are at risk of disadvantageous treatment. We reasoned that migrants may receive differential treatment by locals based on the closeness of their facial features to the host average. Residents of Türkiye, the country with the largest number of refugees currently, served as participants. Because many of these refugees are of Arabic origin, we created target facial stimuli varying along the axis connecting Turkish and Arabic morphological prototypes (excluding skin colour) computed using geometric morphometrics and available databases. Participants made judgements of two universal dimensions of social perception-warmth and competence-on these faces. We predicted that participants judging faces manipulated towards the Turkish average would provide higher warmth and competence ratings compared to judging the same faces manipulated towards the Arabic average. Bayesian statistical tools were employed to estimate parameter values in multilevel models with intercorrelated varying effects. The findings did not support the prediction and revealed raters (as well as target faces) to be an important source of variation in social judgements. In the absence of simple cues (e.g. skin colour, group labels), the effect of facial morphology on social judgements may be much more complex than previously assumed.
- MeSH
- Bayes Theorem MeSH
- Adult MeSH
- Humans MeSH
- Judgment * MeSH
- Adolescent MeSH
- Young Adult MeSH
- Face anatomy & histology MeSH
- Facial Recognition physiology MeSH
- Social Perception * MeSH
- Stereotyping * MeSH
- Refugees psychology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Turkey MeSH
The soil microbiota exhibits an important function in the ecosystem, and its response to climate change is of paramount importance for sustainable agroecosystems. The macronutrients, micronutrients, and additional constituents vital for the growth of plants are cycled biogeochemically under the regulation of the soil microbiome. Identifying and forecasting the effect of climate change on soil microbiomes and ecosystem services is the need of the hour to address one of the biggest global challenges of the present time. The impact of climate change on the structure and function of the soil microbiota is a major concern, explained by one or more sustainability factors around resilience, reluctance, and rework. However, the past research has revealed that microbial interventions have the potential to regenerate soils and improve crop resilience to climate change factors. The methods used therein include using soil microbes' innate capacity for carbon sequestration, rhizomediation, bio-fertilization, enzyme-mediated breakdown, phyto-stimulation, biocontrol of plant pathogens, antibiosis, inducing the antioxidative defense pathways, induced systemic resistance response (ISR), and releasing volatile organic compounds (VOCs) in the host plant. Microbial phytohormones have a major role in altering root shape in response to exposure to drought, salt, severe temperatures, and heavy metal toxicity and also have an impact on the metabolism of endogenous growth regulators in plant tissue. However, shelf life due to the short lifespan and storage time of microbial formulations is still a major challenge, and efforts should be made to evaluate their effectiveness in crop growth based on climate change. This review focuses on the influence of climate change on soil physico-chemical status, climate change adaptation by the soil microbiome, and its future implications.
BACKGROUND: Understanding population health trends and their key determinants is essential for planning health services and implementing effective interventions. One of these determinants may be national cultural characteristics that are related to various health outcomes and health-related behaviours. However, little is known about their potential association to overall burden of disease. Thus, this study examined whether cultural characteristics expressed by Hofstede indexes are associated with the burden of disease. METHODS: We used data from open-source databases - Hofstede's Cultural Index, the Global Burden of Diseases (GBD) and the Human Development Index (HDI). The final sample comprised 69 countries covering all the continents. The burden of disease was measured using disability-adjusted life years (DALYs), years lived with disabilities (YLD), and years of life lost (YLL). National cultural characteristics were measured using Hofstede's dimensions. Bayesian correlation analyses were conducted to assess the relationships between cultural dimensions and health outcomes, stratified by countries' HDI levels. RESULTS: In countries with a very high HDI, there was strong evidence (Bayes Factor > 10) of a positive correlation of Power distance with the total disability-adjusted life years (r = 0.448) and years of life lost (r = 0.528), and Individualism (r = 0.667) and Indulgence (r = 0.494) with years lived with disabilities. In contrast, Long-term orientation negatively correlated of with years lived with disabilities (r = -0.527) and Indulgence with disability-adjusted life years (r = -0.437) and years of life lost (r = -0.537). Further, Power distance and Indulgence were correlated with the majority of the GBD indicators and Individualism with a few GBD indicators. In countries with a high and medium HDI, strong evidence of the associations was found in only a few cases. CONCLUSION: We found a correlation between national cultural characteristics and burden of disease. Policy-makers should consider integrating cultural factors into public health strategies to better align healthcare interventions with the local population's values and behaviours. Moreover, cross-cultural research and collaboration should increase to understand how cultural influences can be used to mitigate disease burdens and improve health outcomes globally. This study also opens a potentially new research area within population health research.
Anticipating clinical transitions in bipolar disorder (BD) is essential for the development of clinically actionable predictions. Our aim was to determine what is the earliest indicator of the onset of depressive symptoms in BD. We hypothesized that changes in activity would be the earliest indicator of future depressive symptoms. The study was a prospective, observational, contactless study. Participants were 127 outpatients with a primary diagnosis of BD, followed up for 12.6 (5.7) [(mean (SD)] months. They wore a smart ring continuously, which monitored their daily activity and sleep parameters. Participants were also asked to complete weekly self-ratings using the Patient Health Questionnaire (PHQ-9) and Altman Self-Rating Mania Scale (ASRS) scales. Primary outcome measures were depressive symptom onset detection metrics (i.e., accuracy, sensitivity, and specificity); and detection delay (in days), compared between self-rating scales and wearable data. Depressive symptoms were labeled as two or more consecutive weeks of total PHQ-9 > 10, and data-driven symptom onsets were detected using time-frequency spectral derivative spike detection (TF-SD2). Our results showed that day-to-day variability in the number of steps anticipated the onset of depressive symptoms 7.0 (9.0) (median (IQR)) days before they occurred, significantly earlier than the early prediction window provided by deep sleep duration (median (IQR), 4.0 (5.0) days; p <.05). Taken together, our results demonstrate that changes in activity were the earliest indicator of depressive symptoms in participants with BD. Transition to dynamic representations of behavioral phenomena in psychiatry may facilitate episode forecasting and individualized preventive interventions.
- Publication type
- Journal Article MeSH
- MeSH
- Humans MeSH
- Population Dynamics MeSH
- Population Forecast * MeSH
- Delivery of Health Care MeSH
- Primary Prevention MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Aging MeSH
- Health Services for the Aged * MeSH
- Check Tag
- Humans MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Publication type
- Newspaper Article MeSH
- Geographicals
- Czech Republic MeSH
The Arteriovenous Access Stage (AVAS) classification simplifies information about suitability of vessels for vascular access (VA). It's been previously validated in a clinical study. Here, AVAS performance was tested against multiple ultrasound mapping measurements using machine learning. A prospective multicentre international study (NCT04796558) with patient recruitment from March 2021-July 2024. Demographics, risk factors, vessels parameters, types of predicted and created VA (pVA, cVA) were collected. We modelled pVA and cVA using the Random Forest algorithm. Model performance was estimated and compared using Bayesian generalized linear models. ROC AUC with 95% credible intervals was the performance metric. 1151 patients were included. ROC AUC for pVA prediction by AVAS was 0.79 (0.77;0.82) and by mapping was 0.85 (0.83;0.88). ROC AUC for cVA prediction by AVAS was 0.71 (0.69;0.74) and by mapping was 0.8 (0.78;0.83). Using AVAS with other parameters increased the ROC AUC to 0.87 for pVA (0.84;0.89) and 0.82 (0.79;0.84) for cVA. Using mapping with other parameters increased the ROC AUC to 0.88 for pVA (0.86;0.91) and 0.85 (0.83;0.88) for cVA. Multiple mapping measurements showed higher performance at VA prediction than AVAS. However, AVAS is simpler and quicker, so may be preferable for routine clinical practice.
- MeSH
- Arteriovenous Shunt, Surgical MeSH
- Bayes Theorem MeSH
- Middle Aged MeSH
- Humans MeSH
- Prospective Studies MeSH
- ROC Curve MeSH
- Aged MeSH
- Machine Learning * MeSH
- Ultrasonography * methods MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Research Support, Non-U.S. Gov't MeSH
- Comparative Study MeSH
The ReAct (Recovery, Activity) project is an ENFSI (European Network of Forensic Science Institutes) supported initiative comprising a large consortium of laboratories. Here, the results from more than 23 laboratories are presented. The primary purpose was to design experiments simulating typical casework circumstances; collect data and to implement Bayesian networks to assess the value (i.e., likelihood ratio) of DNA results given activity level propositions. Two different experimental designs were used to simulate a robbery, where a screwdriver was used to force a door or window. Propositions and case information were chosen following laboratory feedback listing typical casework circumstances (included in the paper). In a direct transfer experiment, the defendant owned and used the screwdriver, but he did not force the door/window in question. An unknown person used the defendant's stolen screwdriver. In an indirect transfer experiment, the defendant neither owned, saw, nor used the screwdriver, nor did they force the door or window. For the second experiment, given the defence view, the defendant never held the screwdriver. We envisaged the situation where an object manipulated by the defendant (or the defendant himself/herself) would be touched by the unknown offender who would then force the window. It was found for the direct transfer experiment that unless a single contributor profile aligning with the known person's of interest profile was retrieved, the results did not allow to discriminate between propositions. On the other hand, for the indirect transfer experiment, both single and major contributor profiles that aligned with the person of interest (POI) supported the proposition that the person used the tool rather than an unknown person who had touched an object, when indeed the former was true. There was considerable variation in median recoveries of DNA between laboratories (between 200pg-5ng) for a given experiment if quantities are taken into account. These differences affect the likelihood ratios given activity level propositions. More than 2700 samples were analysed in the course of this study. Two different Bayesian Networks are made available via an open source application written in Shiny R: Shiny_React(). For comparison, all datasets were analysed using a qualitative method categorised into absent, single, major or other given contributors. The importance of standardising methods is emphasised, alongside the necessity of developing new approaches to assign the probability of laboratory-dependent DNA recovery. Freely accessible open databases play a crucial role in supporting these efforts.
- MeSH
- Bayes Theorem * MeSH
- DNA Fingerprinting * MeSH
- DNA * genetics MeSH
- Laboratories * MeSH
- Humans MeSH
- Microsatellite Repeats MeSH
- Likelihood Functions MeSH
- Forensic Genetics methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Chemosensory learning is a lifelong process of acquiring perceptual expertise and semantic knowledge about chemical stimuli within the everyday environment. In the research context, it is usually simulated using olfactory training, which typically involves repeated exposure to a set of odors over a period of time. Following olfactory training, enhanced olfactory performance has been observed in adults, and similar evidence is beginning to emerge in children. However, the literature is scant concerning the effects of interventions that more closely resemble how chemosensory experience is acquired in daily life. Since children's chemosensory ecology appears to play a crucial role in olfactory development, we investigated whether engaging in activities that stimulate the chemical senses enhances olfactory performance and metacognition. To this end, we invited 20 children aged 9-11 years to participate in teacher-assisted after-school activities for 30-60 minutes a day for six weeks. During the odd weeks, the children appraised herbal and spice blends and used them to prepare dishes and make beauty products. During the even ones, they explored the city by smellwalking and created smellscape maps. The educational outcomes were evaluated using the Sniffin' Sticks test for odor identification and discrimination and the Children's Personal Significance of Olfaction. Bayesian analyses did not reveal any compelling evidence in support of the alternative hypothesis that children in the chemosensory education group outperform those in the comparison group at the post-test. Rates of reliable increase but also decrease in performance on the Sniffin' Sticks identification and discrimination tests were similar in both groups. We corroborated the previous findings regarding girls' and older children's greater proficiency at identifying odors and the female keener interest in the sense of smell. We offer several practical suggestions researchers may want to consider to tailor their research protocols to reflect more closely the broader context in which chemosensory learning takes place and better capture the nuanced outcomes of such interventions.
- MeSH
- Bayes Theorem MeSH
- Smell * physiology MeSH
- Olfactory Perception * physiology MeSH
- Child MeSH
- Humans MeSH
- Odorants * MeSH
- Schools MeSH
- Learning physiology MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Dalbavancin is increasingly being used for long-term treatment of subacute and chronic staphylococcal infections. In this study, a new Bayesian model was implemented and validated using MwPharm software for accurately forecasting the duration of pharmacodynamic target attainment above the efficacy thresholds of 4.02 mg/L or 8.04 mg/L against staphylococci. Forecasting accuracy improved substantially with the a posteriori approach compared with the a priori approach, particularly when two measured concentrations were used. This strategy may help clinicians to estimate the duration of optimal exposure with dalbavancin in the context of long-term treatment.
