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Oriental beech (Fagus orientalis) is distributed from Turkey to northern Iran. It is one of the most economically important tree species in this natural distribution range and has been exploited for a long time in the Hyrcanian forest. This study compared genetic variation between adult individuals and recent cohorts of 1–3-year-old seedlings using 14 SSR primers in four pure stands of F. orientalis with over 90% canopy cover. The results showed that the expected heterozygosity (He) varied from 0.83 to 0.92 (mean value 0.88), and a significant difference was detected between the expected and observed heterozygosity. In total, 75 private alleles were detected; of these, 56 were rare and had a frequency below 0.05. Pairwise Fst values indicated that seedlings were more similar to each other than to mature trees in the same population. It was found that the populations in each pair (mature trees-seedlings) differed (global average D = 0.35). The average percentage of migrants in the population was 8.83% and varied from 6.64% to 13.41%. The genetic differentiation within the same stands, the genetic differences between adults and seedlings were also significant in some populations, and contemporary gene flow drastically decreased in the next generation. Therefore, the transfer of genetic variation between tree generations is currently strongly affected by anthropogenic influence, at least in the studied beech populations, leading to the high vulnerability of Oriental beech populations to future climate changes.

There is an ongoing debate about the potential of localized conservation efforts to address the ecological challenges brought about by global climate shifts. Among these challenges, biological invasion negatively affects ecosystem health and biodiversity. In this study, we assessed the potential impact of global climate changes and human activities on the spread of the invasive species Broussonetia papyrifera in Pakistan's subtropical region. Jackknife analysis indicated that, among the climatic variables studied, the maximum temperature of the warmest month (bio05) made the most significant contribution, accounting for 25.6 % of the model's predictive capacity. Potential highly invaded regions are located in the territory of Islamabad, Rawalpindi, Attock, Nowshera, Swabi, Haripur, and Mardan. Some patches were also found to be invaded in Khyber Pakhtunkhwa (Abbottabad, Buner, Tor Ghar, and Peshawar) and Punjab (Narowal, Sialkot, Gujrat, Jhelum, and Chakwal). Specifically, based on all four Shared Socioeconomic Pathways (SSPs) scenarios for the 2050 s and 2070 s, the highly invaded regions of B. papyrifera are predicted to shift Northern Punjab, Eastern Khyber Pakhtunkhwa, and Northern Kashmir. Based on the SSPs 245 and 585 scenarios, the majority of highly invaded regions are projected to expand by 2050. Similarly, within these regions, the potentially invaded land area is estimated to increase to 2.74 % under SSPs 585 in the 2050 s, 5.29 % under SSPs 245 in the 2070 s, and 6.27 % under SSPs 585 in the 2070 s. Applying circuit theory and ecological resistance, a surface connectivity map of the species revealed that Rawalpindi and Sargodha in Punjab had the most prominent corridors, with rates being highest where ecological patches continually merged. This study is the first to predict B. papyrifera distribution in Pakistan under current and future climate change scenarios. Implementing nationwide guidelines comprehensively may curb the spread of invasive species and protect native plant diversity from extinction. The findings of this study will aid in timely monitoring and surveillance of B. papyrifera and in formulating integrated management plans at the national level to prevent its invasion, spread, and potential harm to newly projected regions.

Abstract The wild relatives of cultivated apples would be an ideal source of diversity for breeding new varieties, which could potentially grow in diverse habitats shaped by climate change. However, there is still a lack of knowledge about the potential distribution of these species. The aim of the presented work was the understand the impacts of climate change on the potential distribution and habitat fragmentation of Caucasian crab apple (Malus orientalis Uglitzk.) and the designation of areas of high interest according to climatic conditions. We used the MaxEnt models and Morphological-Spatial Analysis (MSPA) to evaluate the potential distribution, suitability changes, habitat fragmentation, and connectivity throughout the species range in Turkey, Armenia, Georgia, Russia, and Iran. The results revealed that the potentially suitable range of M. orientalis encompasses 858,877 km², 635,279 km² and 456,795 km² under the present, RCP4.5 and RCP8.5 scenario, respectively. The range fragmentation analysis demonstrated a notable shift in the edge/core ratio, which increased from 50.95% in the current scenario to even 67.70% in the future. The northern part of the range (Armenia, northern Georgia, southern Russia), as well as the central and western parts of Hyrcania will be a core of the species range with suitable habitats and a high connectivity between M. orientalis populations and could work as major refugia for the studied species. However, in the Zagros and central Turkey, the potential range will shrink due to the lack of suitable climatic conditions, and the edge/core ratio will grow. In the southern part of the range, a decline of M. orientalis habitats is expected due to changing climatic conditions. The future outlook suggests that the Hyrcanian forest and the Caucasus region could serve as important refuges for M. orientalis. This study helps to understand spatial changes in species’ range in response to climate change and can help develop conservation strategies. This is all the more important given the species’ potential use in future breeding programs aimed at enriching the gene pool of cultivated apple varieties.

Background: Overweight and obesity in older adults increase the risk of a range of comorbidities by sustaining chronic inflammation and thus enhancing immunosenescence. This study aimed to assess whether excess body mass affected disproportion in T lymphocytes. Therefore, the study was designed to explain whether excess body mass in older individuals affected the disproportion in numbers of T lymphocytes and whether anthropometric indices and immune risk profile expressed as CD4/CD8 ratio are diagnostically useful in the analysis of immunosenescence. Materials & methods: One hundred three individuals aged 73.6 ± 3.1 years were allocated to the normal body mass (body mass index (BMI) 18.5–24.9 kg/m2, n = 39), the pre-obesity (BMI 25.0–29.9 kg/m2, n = 44) or the obesity (BMI ≥30.0 kg/m2, n = 20) group, based on WHO recommendations. Details on the subjects' medical history and lifestyle were obtained by health questionnaire. Anthropometric analysis was performed by bioelectrical impedance method, biochemical analysis was made by the automatic analyzer and ELISA immunoassays, and T and B lymphocyte counts were determined by eight-parameter flow cytometry. Additionally, visceral adiposity index, body adiposity index (BAI), and body shape index (ABSI) were evaluated based on body circumference, BMI and lipid-lipoprotein profile measurements. Results: The highest percentage of CD3+CD4+ T lymphocytes (59.4 ± 12.6 %) and the lowest CD3+CD8+ T lymphocytes (31.6 ± 10.0 %) were noted in patients the obesity group. The highest cut-off value of 1.9 for CD4/CD8 ratio was recorded in the normal body mass vs pre-obesity model. CD4/CD8 ratio > 2.5 was recorded in >20 % of our pre-obesity and obesity groups while 64.5 % of the normal body mass group had CD4/CD8 ratio

IntroductionChronic low-grade inflammation is an important aspect of morbidity and mortality in older adults. The level of circulating pro-inflammatory cytokines (interleukin (IL)-6, tumor necrosis factor (TNF) or IL-1β) is a risk factor in cardiovascular and neurodegenerative diseases and is also associated with sarcopenia and frailties. The objective of this study was to assess each cytokine: IL-6, TNF, and IL-1β separately in the elderly with comorbidities against controls without diseases according to the data published in the available literature.MethodsThe electronic bibliographic PubMed database was systematically searched to select all the relevant studies published up to July 2023. The total number of the subjects involved in the meta-analysis included patients with diseases (n=8154) and controls (n=33967).ResultsThe overall concentration of IL-6 was found to be higher in patients with diseases compared to controls and the difference was statistically significant, with a p-value of

Abstract The diagnosis of metabolic syndrome (MetS) focuses on the assessment of risk factors such as insulin resistance, dyslipidemia, central adiposity and elevated blood pressure. Evidence suggests that markers of systemic inflammation may also be included in the definition of MetS and play some role in its pathogenesis. The study was designed to evaluate low-grade inflammation status in older adults with MetS in relation to increased body fat tissue and an attempt was made to evaluate new predictors for MetS through the analysis of the ROC Curve. Ninety-six middle-aged (69.2 ± 4.9) individuals from University of Third Age (women n = 75 and men n = 21) were allocated to two groups: without metabolic syndrome (n = 37) and with metabolic syndrome (n = 59) according to International Diabetes Federation criteria in agreement with American Heart Association/National Heart, Lung and Blood Institute 2009. Participants’ current health status was assessed using medical records from a routine follow-up visit to a primary care physician. Statistical analysis was performed using R studio software. Depending on the normal distribution, ANOVA or the Kruskal–Wallis test was used. The optimal threshold value for clinical stratification (cut-off value) was obtained by calculating the Youden index. The AUC was observed to be the highest for a new anthropometric index i.e. lipid accumulation product (0.820). Low-grade inflammation dominated in MetS group (BMI 28.0 ± 4.4 kg/m2, WHR 0.9 ± 0.1, FM 24.7 ± 7.9 kg) where significantly higher values of TNF-α (p = 0.027) and HGMB-1 protein (p = 0.011) were recorded.The optimal threshold values for immunological indices assessed as new predictors of the metabolic syndrome were: 93.4 for TNF-α, 88.2 for HGMB-1 protein and 1992.75 for ghrelin. High AUC values for these indices additionally confirmed their high diagnostic usefulness in MetS.

Abstract Viscum album L. is a plant of great importance due to its influence on the host trees and, by extension, entire ecosystems. The species is also significant to humans—on the one hand, because of its use in medicine, and on the other, because of the growing threat it poses to the stability of conifer stands. Therefore, it is important to recognize the future range of three mistletoe subspecies (Viscum album subsp. album, V. album subsp. austriacum, and V. album subsp. abietis). Modelling of the potential range of these subspecies was performed using MAXENT software. Locations were collected from literature and databases. A total number of 3335 stands were used. Bioclimatic data for the current conditions and three future scenarios (SSP 1.26, SSP 3.70, SSP 5.85) were downloaded from the CHELSA database. The results confirmed that the temperature is the key variable on the potential range of the analysed subspecies. V. album subsp. abietis is withdrawing from its range according to all scenarios. In the case of V. album subsp. austriacum, a slight range shift is visible. Only the V. album subsp. album will expand non-directionally. The reason is most likely a very large number of host species and greater genetic variability compared to the subspecies found on conifers.

Abstract The climate drives species distribution and genetic diversity; the latter defines the adaptability of populations and species. The ongoing climate crisis induces tree decline in many regions, compromising the mitigation potential of forests. Scientific‐based strategies for prioritizing forest tree populations are critical to managing the impact of climate change. Identifying future climate refugia, which are locations naturally buffering the negative impact of climate change, may facilitate local conservation. In this work, we conducted the populations' prioritization for Castanea sativa (sweet chestnut), a Neogene relict growing in the Caucasus global biodiversity hotspot. We generated genetic and ecological metrics for 21 sites in Georgia and Azerbaijan, which cover the natural range of sweet chestnut across the region. We demonstrated that climate primarily drives the pattern of genetic diversity in C. sativa, proved with a significant isolation‐by‐environment model. In future, climate change may significantly reorganize the species' genetic diversity, inducing even some genetic loss, especially in the very distinct eastern fringe of the species range in Azerbaijan. Based on our combined approach, we mapped populations suitable for ex situ and in situ conservation, accounting for genetic variability and the location of future climate refugia.

The Mediterranean Basin is one of the 36 global hotspots of biodiversity and it is rich in endemic tree species. The complex geological history of the region throughout the Neogene and Quaternary periods that were marked with several palaeoclimatic transformations was a major factor triggering the genetic divergence of lineages in tree species in the region. The ongoing global climate change is the main factor threatening Mediterranean biodiversity. The risk of population decline related to aridization is the highest in the case of endemics, especially for cold-adapted conifers, such as Abies cilicica . The Cilician fir grows in the East Mediterranean mountains that constitute a local centre of endemism within the region. The species range is fragmented and small-size populations prevail. Previous studies have suggested that the last glacial cycle led to a significant reduction in the species range and might have initiated genetic divergence. As a result, two lineages are currently recognized at the subspecies level, A. cilicica subsp. isaurica (Turkey) and A. cilicica subsp. cilicica (Turkey, Syria, and Lebanon). The predictions about the impact of future climate changes in the East Mediterranean suggest a profound reduction of precipitation and overall warming that may put the remnant populations of A. cilicica at a risk of decline. Here, we used the Bayesian approach to investigate the demographic history of endemic A. cilicica . Specifically, we estimated the probable time of the intraspecies divergence to verify previous assumptions about the species’ evolutionary history. Additionally, niche modelling was used to outline the potential range of changes in the past and to indicate glacial refugia in where the species persisted climate crisis. This approach was also used to explore the possible influence of the future climate changes on the distribution of A. cilicica in the region. Our results demonstrate that the divergence between the Lebanese and the Turkish populations that occurred ~220 ka years BP coincided with the Riss glaciation. According to palaeoecological data, in the East Mediterranean, that glacial period caused a severe reduction in the populations of woody species due to the aridity of the climate. At that time, the Lebanese-Syrian part of the range was likely disconnected from the main range. The second split was induced by the last glacial cycle ~60 ka years BP and led to the separation of the Central Taurus and East Taurus population and, consequently, to the formation of the two subspecies. Niche modelling for the last glacial maximum has allowed us to locate the probable refugia for A. cilicica in the western Anatolia and Syria-Lebanon area. A projection of the future possible distribution of the species indicates a serious reduction of the range during this century.

High-mountain and arctic plants are considered especially sensitive to climate change because of their close adaptation to the cold environment. Kalmia procumbens, a typical arctic–alpine species, reaches southernmost European localities in the Pyrenees and Carpathians. The aim of this study was the assessment and comparison of the current potential niche areas of K. procumbens in the Pyrenees and Carpathians and their possible reduction due to climate change, depending on the scenario. The realized niches of K. procumbens in the Pyrenees are compact, while those in the Carpathians are dispersed. In both mountain chains, the species occurs in the alpine and subalpine vegetation belts, going down to elevations of about 1500–1600 m, while the most elevated localities in the Pyrenees are at ca. 3000 m, about 500 m higher than those in the Carpathians. The localities of K. procumbens in the Carpathians have a more continental climate than those in the Pyrenees, with lower precipitation and temperatures but higher seasonality of temperature and precipitation. The species covered a larger area of geographic range during the Last Glacial Maximum, but its geographic range was reduced during the mid-Holocene. Due to climate warming, a reduction in the potential area of occurrence could be expected in 2100; this reduction is expected to be strong in the Carpathians and moderate in the Pyrenees.

Sorbus aucuparia (Rosaceae) is a small tree species widely distributed in Eurasia. The Hyrcanian forest is the southernmost distribution limit of this species. Severe habitat degradation and inadequate human interventions have endangered the long-term survival of this species in this region, and it is necessary to develop and apply appropriate management methods to prevent the loss of its genetic diversity. In this study, we used 10 SSR markers in order to evaluate the genetic diversity of this taxon. Leaf samples were collected from five known populations of S. aucuparia throughout its distribution area in the Hyrcanian forest. Expected heterozygosity ranged from 0.61 (ASH) to 0.73, and according to the M-ratio, all populations showed a significant reduction in effective population size, indicating a genetic bottleneck. Global FST was not statistically significant and attained the same values with and without excluding null alleles (ENA) correction (FST = 0.12). Bayesian analysis performed with STRUCTURE defined two genetic clusters among the five known populations, while the results of discriminant analysis of principal components (DAPC) identified three distinct groups. The average proportion of migrants was 22. In general, the gene flow was asymmetrical, with the biggest differences between immigration and emigration in Barzekoh and Asbehriseh. The Mantel test showed that there was no significant correlation between genetic distance (FST) and geographic distance in S. aucuparia. The best pathway for theoretical gene flow is located across the coast of the Caspian Sea and significant spatial autocorrelation was observed in only one population. In order to reduce the extinction risk of very small and scattered populations of S. aucuparia in the Hyrcanian forest, it is very important to establish and/or enhance the connectivity through habitat restoration or genetic exchange.

Horse-chestnut (Aesculus hippocastanum L.) is an endemic and relict species from the Mediterranean biodiversity hotspot and a popular ornamental tree. Knowledge about the evolutionary history of this species remains scarce. Here, we ask what historical and ecological factors shaped the pattern of genetic diversity and differentiation of this species. We genotyped 717 individuals from nine natural populations using microsatellite markers. The influence of distance, topography and habitat variables on spatial genetic structure was tested within the approaches of isolation-by-distance and isolation-by-ecology. Species niche modeling was used to project the species theoretical range through time and space. The species showed high genetic diversity and moderate differentiation for which topography, progressive range contraction through the species' history and long-term persistence in stable climatic refugia are likely responsible. A strong geographic component was revealed among five genetic clusters that are connected with very limited gene flow. The environmental variables were a significant factor in the spatial genetic structure. Modeling results indicated that future reduction of the species range may affect its survival. The possible impact of climate changes and high need of in situ conservation are discussed.

Riparian trees, especially relict trees, are attractive and important for research to understand both past and recent biogeographical and evolutionary processes. Our work is the first study to elucidate the genetic diversity and spatial genetic structure of the canopy-dominating riparian (Juglandaceae) along two altitudinal gradients in different river systems of the Hyrcanian forest, which is one of the most important refugium of relict trees in Western Eurasia. Altitudinal gradients were chosen along two river systems at 100, 400 and 900 m a.s.l. Leaf samples were collected from 116 trees, and the genetic diversity was evaluated with eight SSR markers. Overall, 39 alleles were identified for all of the populations studied. The observed heterozygosity (Ho) varied from 0.79 to 0.87 (with a mean of 0.83). The results of the AMOVA analysis indicated that the variation within populations was 88%, whereas the variation among populations was 12% for all of the gradients. A structure analysis indicated that 93% of the trees were grouped in the same gradient. The genetic distance based on Fst confirmed the structure result and indicated a high rate of gene flow among the investigated populations. Based on high gene flow (low differentiation of the population along the same river) and the clearly distinct genetic structure of the investigated gradients, it can be concluded that rivers are the main seed dispersal vector among populations. The genetic diversity of did not show any trend from upstream to downstream. The high level of gene flow and uniform genetic diversity along each river suggest the âclassicalâ metapopulation structure of the species. Pterocarya fraxinifoliaP. fraxinifoliaP. fraxinifolia

Abstract Background Recent advances in machine learning combined with the growing availability of digitized health records offer new opportunities for improving early diagnosis of depression. An emerging body of research shows that Electronic Health Records can be used to accurately predict cases of depression on the basis of individual’s primary care records. The successes of these studies are undeniable, but there is a growing concern that their results may not be replicable, which could cast doubt on their clinical usefulness. Methods To address this issue in the present paper, we set out to reproduce and replicate the work by Nichols et al. (2018), who trained predictive models of depression among young adults using Electronic Healthcare Records. Our contribution consists of three parts. First, we attempt to replicate the methodology used by the original authors, acquiring a more up-to-date set of primary health care records to the same specification and reproducing their data processing and analysis. Second, we test models presented in the original paper on our own data, thus providing out-of-sample prediction of the predictive models. Third, we extend past work by considering several novel machine-learning approaches in an attempt to improve the predictive accuracy achieved in the original work. Results In summary, our results demonstrate that the work of Nichols et al. is largely reproducible and replicable. This was the case both for the replication of the original model and the out-of-sample replication applying NRCBM coefficients to our new EHRs data. Although alternative predictive models did not improve model performance over standard logistic regression, our results indicate that stepwise variable selection is not stable even in the case of large data sets. Conclusion We discuss the challenges associated with the research on mental health and Electronic Health Records, including the need to produce interpretable and robust models. We demonstrated some potential issues associated with the reliance on EHRs, including changes in the regulations and guidelines (such as the QOF guidelines in the UK) and reliance on visits to GP as a predictor of specific disorders.

Abstract Background Depression is one of the most significant health conditions in personal, social, and economic impact. The aim of this review is to summarize existing literature in which machine learning methods have been used in combination with Electronic Health Records for prediction of depression. Methods Systematic literature searches were conducted within arXiv, PubMed, PsycINFO, Science Direct, SCOPUS and Web of Science electronic databases. Searches were restricted to information published after 2010 (from 1st January 2011 onwards) and were updated prior to the final synthesis of data (27th January 2022). Results Following the PRISMA process, the initial 744 studies were reduced to 19 eligible for detailed evaluation. Data extraction identified machine learning methods used, types of predictors used, the definition of depression, classification performance achieved, sample size, and benchmarks used. Area Under the Curve (AUC) values more than 0.9 were claimed, though the average was around 0.8. Regression methods proved as effective as more developed machine learning techniques. Limitations The categorization, definition, and identification of the numbers of predictors used within models was sometimes difficult to establish, Studies were largely Western Educated Industrialised, Rich, Democratic (WEIRD) in demography. Conclusion This review supports the potential use of machine learning techniques with Electronic Health Records for the prediction of depression. All the selected studies used clinically based, though sometimes broad, definitions of depression as their classification criteria. The reported performance of the studies was comparable to or even better than that found in primary care. There are concerns with generalizability and interpretability.

Abstract During a pandemic, isolating oneself from the community limits viral transmission and helps avoid repeated societal lockdowns. This entails a social dilemma—either distance oneself from others for the benefit of the public good or free-ride and enjoy the benefits of freedom. It is not yet understood how the unfamiliar incentive structure and interpersonal context presented by a pandemic together modulate individuals’ approach to this social dilemma. In this preregistered study, we take a game-theoretical approach and investigate people’s decisions to self-isolate, using a novel iterated multiplayer game designed to capture the decision-making environment in the pandemic. To elucidate players’ thinking, we use a variation of the strategy method and elicit beliefs about how much others will self-isolate. Players tend to respond to social norms with abidance, rather than transgression; they resist the temptation to freeride when others are self-isolating. However, they deal with exponential growth poorly, as they only self-isolate sufficiently when lockdowns are imminent. Further, increased collective risk can motivate more self-isolation, even though the link between self-isolation and lockdowns is stochastic. Players underreport the influence of others’ choices on their own, and underestimate others’ self-isolation. We discuss implications for public health, and communication to the public.

Abstract Background Existing research suggests that physical access to food can affect diet quality and thus obesity rates. When defining retail food environment (RFE) quantitatively, there is a little agreement on how to measure “lack of healthy food” and what parameters to use, resulting in a heterogeneity of study designs and outcome measures. In turn, this leads to a conflicting evidence base being one of the many barriers to using evidence in policy‐making. Aims This systematic review aimed to identify and describe methods used to assess food accessibility in the United Kingdom (UK) to overcome heterogeneity by providing a classification of measures. Materials & Methods The literature search included electronic and manual searches of peer‐reviewed literature and was restricted to studies published in English between January 2010 and March 2021. A total of 9365 articles were assessed for eligibility, of which 44 articles were included in the review. All included studies were analysed with regards to their main characteristics (e.g., associations between variables of interest, setting, sample, design, etc.) and definition of RFE and its metrics. When defining these metrics, the present review distinguishes between a point of origin (centroid, address) from which distance was calculated, summary statistic of accessibility (proximity, buffer, Kernel), and definition of distance (Euclidean, network distance). Trends, gaps and limitations are identified and recommendations made for food accessibility research in UK. Results Multiple theoretical and methodological constructs are currently used, mostly quantifying distance by means of Euclidean and ring‐buffer distance, using both proximity‐ and density‐based approaches, and ranging from absolute to relative measures. The association between RFE and diet and health in rural areas, as well as a spatiotemporal domain of food access, remains largely unaccounted. Discussion Evidence suggests that the duration of exposure may bear a greater importance than the level of exposure and that density‐based measures may better capture RFE when compared with proximity‐based measures, however, using more complex measures not necessarily produce better results. To move the field forward, studies have called for a greater focus on causality, individual access and the use of various measures, neighbourhood definitions and potential confounders to capture different aspects and dimensions of the RFE, which requires using univariate measures of accessibility and considering the overall context in terms of varying types of neighbourhoods. Conclusion In order to render ongoing heterogeneity in measuring RFE, researchers should prioritise measures that may provide a more accurate and realistic account of people’s lives and follow an intuitive approach based on convergence of results until consensus could be reached on using some useful standards.

Political polarization on social media has been extensively studied. However, most research has examined polarization about topics that have preexisting associations with ideology, while few studies have tracked the onset of polarization about novel topics or the evolution of polarization over a prolonged period. The occurrence of COVID-19 provides a unique opportunity to study whether social media discourse about a novel event becomes increasingly polarized along ideological lines over time. This paper analyzes trends in Twitter polarization in relation to COVID-19 and other geopolitical events of 2020. The first two studies use topic analysis to examine the evolving difference over time in discussions of COVID-19 and other topics by liberals and conservatives on social media. COVID-19-related polarization is initially absent but gradually increases over time, in contrast to polarization related to other events. A third study examines structural polarization in retweet networks and finds that the frequency of counterpartisan retweets reduces over time. Across all three studies, we find evidence that Twitter discussion of COVID-19 has become more polarized over time.

Abstract Background This study examined the impact of a ‘rewards-for-exercise’ mobile application on physical activity, subjective well-being and sleep quality among 148 employees in a UK university with low to moderate physical activity levels. Methods A three-month open-label single-arm trial with a one-year follow-up after the end of the trial. Participants used the Sweatcoin application which converted their outdoor steps into a virtual currency used for the purchase of products available at the university campus’ outlets, using an in-app marketplace. The primary outcome measure was self-reported physical activity. Secondary measures included device-measured physical activity, subjective well-being (i.e., life satisfaction, positive affect, negative affect), and self-reported sleep quality. Results The findings show an increase in self-reported physical activity (d = 0.34), life satisfaction (d = 0.31), positive affect (d = 0.29), and sleep quality (d = 0.22) during the three-month trial period. Conclusion The study suggests that mobile incentives-for-exercise applications might increase physical activity levels, positive affect, and sleep quality, at least in the short term. The observed changes were not sustained 12 months after the end of the trial.

Introduction This trial tests the efficacy of implementing a hybrid digital cognitive–behavioural therapy for insomnia (dCBT-I) and emotion regulation (ER) in the workplace. The study protocol follows the SPIRIT (Standard Protocol Items: Recommendations for Intervention Trials) 2013 recommendations.Methods and analysis This is a mixed methods evaluation with a two-arm randomised waitlist control design of a 6-week dCBT-I+ER intervention through self-guided online platform and four videoconferencing therapy sessions. A process evaluation will examine the fidelity of delivery and experiences of the intervention. The primary outcomes are the Insomnia Severity Index, the Patient Health Questionnaire-9 and the Generalised Anxiety Disorder-7. The secondary outcomes are job productivity, job satisfaction, well-being, quality of life, self-reported (sleep diary data) and objective (actigraphy) sleep parameters, and usage of online intervention platform. Assessments take place at baseline (T0), week 8 post-treatment (T1) and week 12 postrandomisation (T2). We will recruit 156 workers with sleep and ER problems ranging from subclinical to clinical levels not engaged in treatment at the time of the trial.Ethics and dissemination Full approval was given by the University of Warwick Biomedical and Research Ethics Committee (BSREC 45/20-21). The current protocol version is 2.9_Dec21. Publication of results will inform the scientific, clinical and business communities through peer-reviewed articles, webinars, conferences and newsletters.Trial registration number ISRCTN13596153.

“Return-to-player” information is used in several jurisdictions to display the long-run cost of gambling, but previous evidence suggests that these messages are frequently misunderstood by gamblers. Two ways of improving the communication of return-to-player information have been suggested: switching to an equivalent “house-edge” format, or via the use of a “volatility warning,” clarifying that the information applies only in the statistical long run. In this study, Australian participants (N = 603) were presented with either a standard return-to-player message, the same message supplemented with a volatility warning, or a house-edge message. The return-to-player plus volatility warning message was understood correctly more frequently than the return-to-player message, but the house-edge message was understood best of all. Participants perceived the lowest chance of winning in the return-to-player plus volatility warning condition. These findings contribute data on the relative merits of two proposed approaches in the design of improved gambling information.

Loot boxes are digital containers of randomised rewards present in some video games which are often purchasable for real world money. Recently, concerns have been raised that loot boxes might approximate traditional gambling activities, and that people with gambling problems have been shown to spend more on loot boxes than peers without gambling problems. Some argue that the regulation of loot boxes as gambling-like mechanics is inappropriate because similar activities which also bear striking similarities to traditional forms of gambling, such as collectable card games, are not subject to such regulations. Players of collectible card games often buy sealed physical packs of cards, and these 'booster packs' share many formal similarities with loot boxes. However, not everything which appears similar to gambling requires regulation. Here, in a large sample of collectible card game players (n = 726), we show no statistically significant link between in real-world store spending on physical booster and problem gambling (p = 0.110, η2 = 0.004), and a trivial in magnitude relationship between spending on booster packs in online stores and problem gambling (p = 0.035, η2 = 0.008). Follow-up equivalence tests using the TOST procedure rejected the hypothesis that either of these effects was of practical importance (η2 > 0.04). Thus, although collectable card game booster packs, like loot boxes, share structural similarities with gambling, it appears that they may not be linked to problem gambling in the same way as loot boxes. We discuss potential reasons for these differences. Decisions regarding regulation of activities which share structural features with traditional forms of gambling should be made on the basis of definitional criteria as well as whether people with gambling problems purchase such items at a higher rate than peers with no gambling problems. Our research suggests that there is currently little evidence to support the regulation of collectable card games.

In-play gambling is a recent innovation allowing gambling to occur during the course of a sporting event, rather than merely before play commences. For years, in-play gambling has been marketed in the UK via adverts displaying current betting odds during breaks in televised soccer, e.g., "England to score in the first 20 minutes, 4-to-1." Previous research shows that this so-called "live-odds" advertising is skewed toward complex events with high profit margins which consumers do not evaluate rationally. Recent UK regulatory guidance on "impulsiveness and urgency," aiming to enhance consumer protection around gambling advertising, states that gambling advertising should not "unduly pressure the audience to gamble." We explored the frequency and content of live-odds advertising over the 2018 soccer World Cup, as a case study of the first major televised sporting event after the publication of this UK regulatory guidance. In total, 69 live-odds adverts were shown over 32 matches (M = 2.16 per-match), by five bookmakers. We identified two key features that made advertised bets appear more urgent than necessary. First, 39.1% of bets could be determined before the match ended. Second, 24.6% of bets showed a recent improvement in odds, including a 15.9% subset of "flash odds," which were limited in both time and quantity. Advertised odds were again skewed toward complex events, with a qualitative trend toward greater complexity than at the previous World Cup. We believe that consumers should be protected against the targeted content of gambling advertising.

We use data from Twitter.com to study the interplay between affect and expectations about uncertain outcomes. In two studies, we obtained tweets about candidates in the 2014 US Senate elections and tweets about National Football League (NFL) teams in the 2014/2015 NFL season. We chose these events because a) their outcomes are highly uncertain and b) they attract a lot of attention and feature heavily in the communication on social media. We also obtained a priori expectations for the events from political forecasting and sport betting websites. Using this quasi-experimental design, we found that unexpected events are associated with more intense affect than expected events. Moreover, the effect of expectations is larger for outcomes that fall below expectations than outcomes that exceed expectations. Our results are consistent with fundamental principles in psychological science, such as reference-dependence in experienced affect. We discuss how naturally occurring online data can be used to test psychological predictions and develop novel psychological insights.

Online marketplaces allow consumers to leave reviews about the products they purchase, which are visible to potential customers and competitors. While the impact of reviews on valuations of worth and purchasing decisions has been intensively studied, little is known about how the reviews themselves are attended to, and the relation between attention and valuations. In three studies we use eye-tracking methodologies to investigate attention in subjective monetary valuations of consumer goods. We find that, when evaluating consumer goods, individuals' attention to ratings are related to their frequencies, attention to positive or negative information is related to subjective valuations, and that perspective (owner vs. non-owner) influences the type of information attended to. These findings extend previous research regarding the valuations of risky prospects as implemented in abstract monetary gambles and suggest that similar cognitive processes might underlie both types of tasks.

Background ‘Lockdowns’ to control the spread of COVID-19 in the UK affected many aspects of life and may have adversely affected diets. We aimed to examine (1) the effect of lockdowns on fruit and vegetable consumption, as a proxy for healthy diets more generally, and on weight and well-being, (2) whether any subgroup was particularly affected and (3) the barriers and facilitators to a healthy diet in lockdown.Methods We conducted a mixed-method longitudinal study, involving an online survey of 1003 adults in the West Midlands, UK, 494 of whom were surveyed at two different points in time. Our first time point was during stringent COVID-19 lockdown and the second during a period of more relaxed restrictions. We asked quantitative questions about fruit and vegetable consumption; physical activity, sociodemographic characteristics, body mass index and well-being and qualitative questions about the reasons behind reported changes.Results We find no evidence for decreased fruit and vegetable consumption during lockdown compared with afterwards. If anything, consumption increased by half a portion daily among women, particularly among those who normally have a long commute. This finding, combined with a significant increase in physical activity, suggests that behaviours were healthier during lockdown, consistent with higher self-reported health. However, well-being deteriorated markedly, and participants reported being heavier during the lockdown as well. Our qualitative data suggest that an abundance of resources (more time) supported higher fruit and vegetable consumption during lockdown, despite increased access issues.Conclusions Our results may assuage concerns that lockdowns adversely affected diets. They may point to the impact of commuting on diet, particularly for women. We add longitudinal evidence to a growing body of literature on the adverse effect of lockdown on mental health.