Monitoring of the periglacial environment is relevant for many disciplines including glaciology, natural hazard management, geomorphology, and geodesy. Since October 2022, Rock Glacier Velocity (RGV) is a new Essential Climate Variable (ECV) product within the Global Climate Observing System (GCOS). However, geodetic surveys at high elevation remain very challenging due to environmental and logistical reasons. During the past decades, the introduction of low-cost global navigation satellite system (GNSS) technologies has allowed us to increase the accuracy and frequency of the observations. Today, permanent GNSS instruments enable continuous surface displacement observations at millimetre accuracy with a sub-daily resolution. In this paper, we describe decennial time series of GNSS observables as well as accompanying meteorological data. The observations comprise 54 positions located on different periglacial landforms (rock glaciers, landslides, and steep rock walls) at altitudes ranging from 2304 to 4003 ma.s.l. and spread across the Swiss Alps. The primary data products consist of raw GNSS observables in RINEX format, inclinometers, and weather station data. Additionally, cleaned and aggregated time series of the primary data products are provided, including daily GNSS positions derived through two independent processing tool chains. The observations documented here extend beyond the dataset presented in the paper and are currently continued with the intention of long-term monitoring. An annual update of the dataset, available at https://doi.org/10.1594/PANGAEA.948334 (Beutel et al., 2022), is planned. With its future continuation, the dataset holds potential for advancing fundamental process understanding and for the development of applied methods in support of e.g. natural hazard management.
Background Monitoring salt consumption in children is essential for informing and implementing public health interventions to reduce children’s salt intake. However, collection of 24-hour urines, considered as the most reliable approach, can be especially challenging to school children. This study aimed to assess the agreement between 24-hour urine (24hrU) and 24-hour food recall (24hrFR) in: (1) estimating salt intake in children; (2) classifying salt intakes above the recommended upper level set for children, and; (3) estimating change in mean salt intake over time. Methods This study utilised data from two cross-sectional surveys of school children aged 8 to 12 years living in the state of Victoria, Australia. A single 24hrU and 24hrFR were collected from each participant. Suspected inaccurate urine collections and implausible energy intakes were excluded based on pre-defined criteria. The agreement between the two methods was assessed using Bland-Altman methodology, the intraclass correlation coefficient (ICC), and the kappa statistic. The difference between the measured change in salt intake over time using 24hrU and 24hrFR was derived using mixed effects linear regression analysis. Results A total of 588 participants provided a 24hrU and 24hrFR. Overall, there was no meaningful difference in mean estimated salt intake between the two methods (− 0.2 g/day, 95% CI − 0.5 to 0.1). The Bland-Altman plot showed wide 95% limits of agreement (− 7.2 to 6.8). The ICC between the two methods was 0.13 (95% CI 0.05 to 0.21). There was poor interrater reliability in terms of classifying salt intake above the recommended upper level for children, with an observed agreement of 63% and kappa statistic of 0.11. The change in mean salt intake over time was 0.2 g/day (− 0.4 to 0.7) based on 24hrU, and 0.5 g/day (− 0.0 to 1.1) based on 24hrFR, with a difference-in-differences of 0.4 g/day (− 0.3 to 1.1). Conclusions 24hrFR appears to provide a reasonable estimate of mean salt intake as measured by 24hrU in Australian school children. However, similar to previous observations in adults, and of studies exploring other alternative methods for estimating salt intake, 24hrFR is a poor predictor of individual-level salt intake in children.
Automated synthesis planning is key for efficient generative chemistry. Since reactions of given reactants may yield different products depending on conditions such as the chemical context imposed by specific reagents, computer-aided synthesis planning should benefit from recommendations of reaction conditions. Traditional synthesis planning software, however, typically proposes reactions without specifying such conditions, relying on human organic chemists who know the conditions to carry out suggested reactions. In particular, reagent prediction for arbitrary reactions, a crucial aspect of condition recommendation, has been largely overlooked in cheminformatics until lately. Here we employ the Molecular Transformer, a state-of-the-art model for reaction prediction and single-step retrosynthesis, to tackle this problem. We train the model on the US patents dataset (USPTO) and test it on Reaxys to demonstrate its out-of-distribution generalization capabilities. Our reagent prediction model also improves the quality of product prediction: the Molecular Transformer is able to substitute the reagents in the noisy USPTO data with reagents that enable product prediction models to outperform those trained on plain USPTO. This allows to improve upon the state-of-the-art in reaction product prediction on the USPTO MIT benchmark.
This partially randomised controlled, crossover study sought to investigate the effects of normobaric hypoxia (NH) and hypobaric hypoxia (HH) on cognitive performance, the physiological response at rest and after a 3-min step-test. Twenty healthy participants (10 females and 10 males, 27.6±6.2yrs, 73.6±13.7kg, 175.3±8.9cm) completed a cognitive performance test, followed by the modified Harvard-step protocol, in four environments: normobaric normoxia (NN; P i O 2 : 146.0±1.5mmHg), NH (P i O 2 : 100.9±1.3mmHg), HH at the first day of ascent (HH1: P i O 2 = 105.6±0.4mmHg) and HH after an overnight stay (HH2: P i O 2 = 106.0±0.5mmHg). At rest and/or exercise, SpO 2 , NIRS, and cardiovascular and perceptual data were collected. The cerebral tissue oxygenation index and the cognitive performance (throughput, accuracy, and reaction time) were not different between the hypoxic conditions (all p>0.05). In NH, SpO 2 was higher compared to HH1 (ΔSpO 2 NH vs HH1: 1.7±0.5%, p = 0.003) whilst heart rate (ΔHR NH vs HH2: 5.8±2.6 bpm, p = 0.03) and sympathetic activation (ΔSNSi NH vs HH2: 0.8±0.4, p = 0.03) were lower in NH compared to HH2. Heart rate (ΔHR HH1 vs HH2: 6.9±2.6 bpm, p = 0.01) and sympathetic action (ΔSNSi HH1 vs HH2: 0.9±0.4, p = 0.02) were both lower in HH1 compared to HH2. In conclusion, cognitive performance and cerebral oxygenation didn’t differ between the hypoxic conditions. SpO 2 was only higher in NH compared to HH1. In HH2, heart rate and sympathetic activation were higher compared to both NH and HH1. These conclusions account for a P i O 2 between 100–106 mmHg.
Background: The fungal biodiversity on cheese rinds has been extensively studied for some soft cheeses such as Brie, Camembert, and Roquefort, but scant information is available on the microbiota colonizing the rinds of cheese produced in the Southern Switzerland Alps. This study aimed at exploring the fungal communities present on rinds of cheese produced and matured in Southern Switzerland. We used classical techniques such as dilution series, culturing and macro- and microscopical morphology, matrix-assisted laser desorption/ionization–time of flight (MALDI-TOF) mass spectrometry, and sequencing, as well as metabarcoding targeting the ITS and β-tubulin gene regions, to characterize the fungal communities present of cheese rinds collected in five ripening cellars. Results: Isolation by serial dilution yielded 201 isolates, of which 39 were yeasts and 162 filamentous fungi. Mucor and Penicillium were the dominant genera. Mucor racemosus, M. lanceolatus, P. camemberti, and P. chrysogenum/rubens were the most frequent species. All but two yeast isolates were identified as Debaryomyces hansenii. Overall, metabarcoding detected 80 fungal species, with Mucor spp. and Penicilliumspp. being the dominant taxa, as opposed to only 9 species recovered by serial dilutions. Culture-dependent and independent methods produced similar results in terms of dominant taxa and similarity of the fungal communities in the five cellars, metabarcoding, however, providing more detailed information. Conclusions: Our study has shown that the mycobiota on the rinds of alpine cheese is a complex community defined by different parameters, including temperature, relative humidity, and type of cheese, as well as microenvironmental and possibly geographic factors.
We assessed the distribution of alien fishes in one of the most ecologically and economically important aquatic ecosystems in Iran, the Karun River Basin. Fish samples were collected from 35 sites in the Karun River Basin during the low-flow period from November to December 2018. We documented the occurrence of 37 species of fishes from nine orders and 14 families. Amongst these, 10 species were alien (986 individuals; 15.7%). The relative abundance of native, endemic, and alien species estimated as 54.8%, 29.5% and 15.7%, respectively. Total length of alien species ranged from 0.4 to 25.5 cm and their total weight from 0.17 to 350 g. The ten alien species belonged to seven families including, Cyprinidae, Cichlidae, Xenocyprididae, Gobiidae, Poeciliidae, Gobionidae, and Salmonidae. Carassius gibelio , Oreochromis aureus , and Coptodon zillii were found to be the most abundant alien species in the downstream region. We applied redundancy analysis (RDA) as a direct stressor method to identify the extent of changes in alien fish assemblages with environmental parameters. The first two axes (RDA1 and RDA2) accounted for 36.24% and 25.33% of the variation of five alien species, respectively. Altitude, depth, electrical conductivity, water temperature, turbidity, dissolved oxygen, and river width were the most significant parameters affecting the distribution of alien species. Our results propose that management practices are needed in the downstream sections of the Basin to recover native and endemic species. Monitoring of presence and extent of alien species is a key to measuring the success of these efforts.
In (pre)school, children acquire and deepen their basic motor competencies (BMCs) and interact with peers and friends. BMCs are a central developmental goal in childhood and the prerequisite for participation in sportive aspects of social life. Both motor competencies and social integration are linked to children’s health-related quality of life (HRQoL). The aim of the present study was to describe the connection between BMCs, social relationships, and aspects of HRQoL in (pre)school children. In this study, the BMCs of N = 1163 preschool children (M = 5.7 years, SD = 0.57, 52% boys) and N = 880 first and second graders (M = 7.5 years, SD = 0.58, 51% boys) were tested. The children’s social integration was assessed by the teachers; the HRQoL was recorded from the parents’ perspective. In both preschool and primary school, children with better BMCs also showed higher values in their social integration. Moreover, the results indicated a connection between BMCs and general HRQoL in primary school and BMCs and physical well-being in preschool. As BMCs, social integration, and HRQoL seem to be connected in (pre)school, this should be considered both from developmental and health-oriented perspectives, as well as for physical education (PE) lessons. Keywords: kindergarten; sport; health; motor skills; physical education; well-being
Background Healthcare is facing a shortage of qualified healthcare professionals. The pandemic has brought to light the fragile balance that affects all healthcare systems. Governments have realized that these systems and the professionals working in them need support at different levels to strengthen the retention of the workforce. Health professionals’ education can play an important role in ensuring that new generations of workers have sound personal and professional competencies to successfully face the challenges of professional practice. These challenges are described in the literature, but the extent to which they are considered in health professionals’ education is less clear. Methods This qualitative study compares the professional challenges and educational needs described in the literature with the current curricula for health professionals offered in Switzerland. Data were collected nationally through focus group interviews with 65% of Switzerland’s directors of bachelor’s and master’s programs of health professions (nursing, physiotherapy, occupational therapy, midwifery, nutrition and dietetics, osteopathy, radiologic medical imaging technology, health promotion and prevention, and health sciences). The data attained were analyzed using knowledge mapping. Results The results reveal a gap among education programs with regard to occupational health promotion and cultural diversity. Both topics are taught with a sole focus on patients, and students are expected to adopt similar strategies for their health promotion and stress management. Physicians are insufficiently involved in interprofessional education. The programs fail to enhance health professionals’ political, economic and digital competencies. Conclusion The results of this study offer clear guidance about what topics need to be integrated into curricula to improve health professionals’ well-being at work and their preparedness to face daily professional challenges.
The adoption of blockchain technology is emerging as a promising approach in managing decentralized local energy markets (LEM). In this study we analyze the issues related to the deployment of a blockchain-based LEM on devices as much as possible similar to modern smart meters. The presented LEM is based on an automated market-making mechanism. Buying and selling prices are dynamically determined by the amount of energy consumed and produced within a local energy community. We implemented the market in a blockchain application based on the Cosmos framework, which was deployed on embedded devices in a test pilot consisting of 18 residential buildings in Southern Switzerland. The sustainability of the application was investigated by analyzing the resources required by the blockchain to operate. The obtained results show how the developed application uses a small part of the resources of the embedded devices, approximately 100 MB for the memory usage and about 4% as regards the CPU. Thus, while the application deployment on smart meters is still troublesome, especially for memory requirements, the deployment at the data concentrator level is reasonable and feasible. Finally, we propose possible improvements and extensions that can be implemented in future versions of the presented solution.
Artificial Intelligence (AI) has demonstrated superhuman capabilities in solving a significant number of tasks, leading to widespread industrial adoption. For in-field network-management application, AI-based solutions, however, have often risen skepticism among practitioners as their internal reasoning is not exposed and their decisions cannot be easily explained, preventing humans from trusting and even understanding them. To address this shortcoming, a new area in AI, called Explainable AI (XAI), is attracting the attention of both academic and industrial researchers. XAI is concerned with explaining and interpreting the internal reasoning and the outcome of AI-based models to achieve more trustable and practical deployment. In this work, we investigate the application of XAI for network management, focusing on the problem of automated failure-cause identification in microwave networks. We first introduce the concept of XAI, highlighting its advantages in the context of network management, and we discuss in detail the concept behind Shapley Additive Explanations (SHAP), the XAI framework considered in our analysis. Then, we propose a framework for a XAI-assisted ML-based automated failure-cause identification in microwave networks, spanning model’s development and deployment phases. For the development phase, we show how to exploit SHAP for feature selection and how to leverage SHAP to inspect misclassified instances during model’s development process, and how to describe model’s global behavior based on SHAP’s global explanations. For the deployment phase, we propose a framework based on predictions uncertainty to detect possibly wrong predictions that will be inspected through XAI.
The mayfly Prosopistoma pennigerum (Müller, 1785) (Insecta: Ephemeroptera) once occurred in many European river networks. However, observations decreased in the last decades and the species can be considered largely extinct throughout Europe due to river alterations. Only three extant populations are known from Cabriel (southern Spain), Volga (Russia) and Vjosa (Albania) rivers. We recorded the species along a 150 km stretch in the Vjosa River in three sampling seasons (spring 2018, fall 2018 and fall 2019), counting up to 302 P. pennigerum per m2, the highest recorded abundance for the species to date. Moreover, we detected traces of environmental DNA in a newly designed targeted eDNA assay. In our modelling approach we define the species' niche in a theoretically available niche space given by the Vjosa River network and predict a high probability of presence (θ$$ \theta $$) in downstream located sections of this river. Expected abundances (λ) could be related to a set of environmental variables, importantly to higher discharge and increased sediment dynamics. Simultaneous occurrence of larvae of different sizes at individual sites suggests an asynchronous life cycle, which may be advantageous to cope with the highly dynamic river hydrology. The P. pennigerum population in the Vjosa is of key importance for the species' global survival. A robust population of the almost extinct mayfly, Prosopistoma pennigerum, occurs in the last free‐flowing river network, the Vjosa. We observed the species with a targeted environmental DNA approach and standard kicknet sampling along a > 150 km stretch of the Vjosa main stem and in its major tributaries. Prosopistoma pennigerum's asynchronous life cycle strategy and morphology grant resilience and resistance, at population and individual level, and are linked to the Vjosa's free‐flowing hydrologic dynamics.
Industrial control systems play a central role in today’s manufacturing systems. Ongoing trends towards more flexibility and sustainability, while maintaining and improving production capacities and productivity, increase the complexity of production systems drastically. To cope with these challenges, advanced control algorithms and further developments are required. In recent years, developments in Artificial Intelligence (AI)-based methods have gained significantly attention and relevance in research and the industry for future industrial control systems. AI-based approaches are increasingly explored at various industrial control systems levels ranging from single automation devices to the real-time control of complex machines, production processes and overall factories supervision and optimization. Thereby, AI solutions are exploited with reference to different industrial control applications from sensor fusion methods to novel model predictive control techniques, from self-optimizing machines to collaborative robots, from factory adaptive automation systems to production supervisory control systems. The aim of the present perspective paper is to provide an overview of novel applications of AI methods to industrial control systems on different levels, so as to improve the production systems’ self-learning capacities, their overall performance, the related process and product quality, the optimal use of resources and the industrial systems safety, and resilience to varying boundary conditions and production requests. Finally, major open challenges and future perspectives are addressed.
Zusammenfassung. Hintergrund: Die einschneidenden Veränderungen, welche moderne Gesellschaften durch die Digitalisierung erfahren haben, haben es unerlässlich gemacht, heutigen und künftigen Generationen höhere Kompetenzen als Rüstzeug für die neue Lern- und Arbeitswelt mitzugeben. Die Verwendung von digitalen Lernumgebungen zusammen mit maschinellem Lernen kann in diesem Kontext ein leistungsstarkes Werkzeug darstellen. Methoden: In der vorliegenden Übersichtsarbeit werden die Chancen und Herausforderungen von maschinellem Lernen im Bildungswesen anhand ausgewählter Anwendungsbereiche aufgezeigt. Zu jedem Anwendungsbereich wird eine Zusammenfassung der bestehenden Forschung präsentiert und die Anwendung anhand eines konkreten Beispiels aus der jüngsten Forschung veranschaulicht. Ergebnisse: Die Ergebnisse aus der jüngsten Forschung bestätigen, dass maschinelles Lernen ein enormes Potenzial hat, um das Bildungswesen durch personalisierte Lernmöglichkeiten für höhere Kompetenzen zu bereichern. Jedoch ist noch weitere Forschung nötig, um die wirkliche Lernwirksamkeit solcher Ansätze zu validieren.
Importance The effectiveness of selective decontamination of the digestive tract (SDD) in critically ill adults receiving mechanical ventilation is uncertain. Objective To determine whether SDD is associated with reduced risk of death in adults receiving mechanical ventilation in intensive care units (ICUs) compared with standard care. Data Sources The primary search was conducted using MEDLINE, EMBASE, and CENTRAL databases until September 2022. Study Selection Randomized clinical trials including adults receiving mechanical ventilation in the ICU comparing SDD vs standard care or placebo. Data Extraction and Synthesis Data extraction and risk of bias assessments were performed in duplicate. The primary analysis was conducted using a bayesian framework. Main Outcomes and Measures The primary outcome was hospital mortality. Subgroups included SDD with an intravenous agent compared with SDD without an intravenous agent. There were 8 secondary outcomes including the incidence of ventilator-associated pneumonia, ICU-acquired bacteremia, and the incidence of positive cultures of antimicrobial-resistant organisms. Results There were 32 randomized clinical trials including 24 389 participants in the analysis. The median age of participants in the included studies was 54 years (IQR, 44-60), and the median proportion of female trial participants was 33% (IQR, 25%-38%). Data from 30 trials including 24 034 participants contributed to the primary outcome. The pooled estimated risk ratio (RR) for mortality for SDD compared with standard care was 0.91 (95% credible interval [CrI], 0.82-0.99; I ² = 33.9%; moderate certainty) with a 99.3% posterior probability that SDD reduced hospital mortality. The beneficial association of SDD was evident in trials with an intravenous agent (RR, 0.84 [95% CrI, 0.74-0.94]), but not in trials without an intravenous agent (RR, 1.01 [95% CrI, 0.91-1.11]) ( P value for the interaction between subgroups = .02). SDD was associated with reduced risk of ventilator-associated pneumonia (RR, 0.44 [95% CrI, 0.36-0.54]) and ICU-acquired bacteremia (RR, 0.68 [95% CrI, 0.57-0.81]). Available data regarding the incidence of positive cultures of antimicrobial-resistant organisms were not amenable to pooling and were of very low certainty. Conclusions and Relevance Among adults in the ICU treated with mechanical ventilation, the use of SDD compared with standard care or placebo was associated with lower hospital mortality. Evidence regarding the effect of SDD on antimicrobial resistance was of very low certainty.
Vincent van Gogh’s painting Congregation Leaving the Reformed Church in Nuenen from the collection of the Van Gogh Museum in Amsterdam was executed in 1884 and partially repainted by the artist in 1885. The painting was restored in 1961, however, the details of this treatment were not documented. After being stolen from the museum in 2002 and finally recovered in 2016, the Church was subjected to an extensive technical examination campaign which started in 2017. The aims were to: characterise the stratigraphy of both initial and later paint layers (including identification of the painting materials used by Van Gogh), evaluate the condition of the painting and assess the feasibility of the desired restoration treatment. Portable X-ray fluorescence spectrometry (XRF) was performed to non-invasively identify elements related to pigments in the paint layers of the two painting campaigns. To further identify constituent materials and comprehend the painting’s complex stratigraphy, a single paint sample was collected and embedded in resin for analysis by means of Optical Microscopy, Scanning Electron Microscopy with Energy Dispersive X-ray spectrometry (SEM-EDS) and Fourier Transform Infrared spectrometry - Attenuated Total Reflectance (FTIR-ATR). Additional non-invasive measurements were performed in a MOLAB campaign in 2018 by two complementary and portable analytical techniques: Optical Coherence Tomography (OCT) and reflection FTIR spectroscopy were used to gain further insight into the painting’s stratigraphy and identify surface layers across various regions of the painting. The presence of an original varnish under the paint from 1885 (and therefore likely applied by Van Gogh himself) was revealed by OCT. It was characterised as being protein based by FTIR-ATR and reflection FTIR spectroscopy. Based on the knowledge on the artist’s varnishing practice, it could be concluded that this most likely concerns an egg white varnish for the first time found in an early work by Van Gogh. The upper varnish layer, however, was identified as an alkyd resin applied during the aforementioned 1961 treatment. The combined use of FTIR and OCT enabled non-invasive in situ assessment of solvent cleaning procedures aimed at the selective removal of the 1961 restoration varnish with the preservation of Van Gogh’s original varnish. Specifically, OCT and FTIR analyses were carried out before, during and after each cleaning test to carefully assess the condition of the painted surface and that of the original varnish. The results of the cleaning tests aided in fine-tuning the procedure of varnish removal during the restoration process.
Spinocerebellar Ataxia Type 1 is a degenerative disorder caused by polyglutamine expansions and aggregation of Ataxin-1. The interaction between Capicua (CIC) and the AXH domain of Ataxin-1 protein has been suggested as a possible driver of aggregation for the expanded Ataxin-1 protein and the subsequent onset of Spinocerebellar ataxia 1. Experimental studies have demonstrated that short constructs of CIC may prevent such aggregation and suggested this as a possible candidate to inspire the rational design of peptidomimetics. In this work, molecular modelling techniques, namely the Alchemical mutation and forcefield-based molecular dynamics, have been employed to propose a pipeline for the rational design of a CIC-inspired inhibitor of the ataxin-1 aggregation pathway. In particular, this study has shown that the Alchemical mutation can estimate the affinity between AXH and CIC with good correlation with experimental data, while molecular dynamics shed light on molecular mechanisms that occur for stabilization of the interaction between the CIC-inspired construct and the AXH domain of Ataxin-1. This work lays the foundation for a rational methodology for the in-silico screening and design of peptidomimetics, which can expedite and streamline experimental studies to identify strategies for inhibiting the ataxin-1 aggregation pathway.
Headwater streams harbor diverse macroinvertebrate communities and are hotspots for leaf litter breakdown. The process of leaf litter breakdown mediated by macroinvertebrates forms an important link between terrestrial and aquatic ecosystems. Yet, how the vegetation type in the local riparian zone influences leaf-associated macroinvertebrate assemblages and leaf litter breakdown rates is still not resolved. We investigated how leaf-associated macroinvertebrate assemblages and leaf litter fragmentation rates differ between forested and non-forested sites using experimental leaf litter bags in sixteen sites paired across eight headwater streams in Switzerland. Our results show that sensitive taxa of the invertebrate orders Ephemeroptera, Plecoptera and Trichoptera (EPT) and the functional group of shredders were strongly associated with forested sites with overall higher values of abundance, diversity, and biomass of EPTs in forested compared to non-forested sites. However, the importance of riparian vegetation differed between study regions, especially for shredders. Fragmentation rates, which are primarily the result of macroinvertebrate shredding, were on average three times higher in forested compared to non-forested sites. Our results demonstrate that not only the composition of the aquatic fauna but also the functioning of an essential ecosystem process depend on the vegetation type in the local riparian zone.
Background Community Occupational Therapy in Dementia in Italy (COTID−IT) is a feasible and effective treatment that aims improving the quality of life and well−being of people with dementia and caregivers. The implementation of the program in the national context has not been studied yet. Aim The objective of this study is to identify barriers and facilitators in the Italian implementation of the program. Methods We designed a quantitative cross-sectional survey. A questionnaire was developed to collect descriptive data regarding the respondents, the perceived barriers and facilitators regarding the application of COTiD and possible actions to promote the implementation process. Results The questionnaire was sent to all 90 Italian OTs trained in the use of COTiD−IT from 2013 to 2020. 50 people responded (61%). Barriers to the implementation of the COTID−IT included lack of knowledge about Occupational Therapy and the COTID−IT program by other health professionals. In addition, the scarcity of economic funds invested in home rehabilitation is experienced as another significant barrier. Facilitators were found to be the presence of an interprofessional team interested in the COTID−IT program and occupational therapy and the fact that COTID−IT is supported by scientific evidence. The creation of national and regional inter professional education and support groups, the availability of online resources are seen as opportunities to better implement the COTID−IT program. Conclusions Implementation of psychosocial interventions is complex. OTs in Italy should be increasingly included within health policies and care programs of people with dementia to promote the use of COTID−IT. Further studies are needed to detail the policy and methodological actions that OTs should take in the future to disseminate and consolidate this intervention.
Inspired by Psychology of Working Theory (PWT), our aim in this study was to investigate vocational guidance and career counselling specialists’ perceptions of decent work and of the resources that promote access to decent work by using qualitative methods analyses. With this objective, 17 Swiss professionals were interviewed. First, content analysis showed that, in addition to dimensions considered by PWT, positive relations at work should be considered as part of decent work. Moreover, in addition to the resources considered by PWT, soft skills development emerged as important to access decent work. Second, textual analysis highlighted that specialists’ representations of decent work and the resources that facilitate access to it differ according to their professional category.
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