Université du Québec en Outaouais

Understanding and predicting how densities of interacting species change over time has been one of the main goals of community ecology, which has become a pressing challenge in the context of global change. We present the R package ATNr , which provides an implementation of different versions of Allometric Trophic Network models that simulate the biomass dynamics of trophically interacting species. Relying on C++ routines, the ATNr proposes an efficient and standardised implementation of the different ATNs models. By proposing a set of built in functions ready to use in a language widely used in the community of ecologists, the ATNr package offers an easy access to ATN models focusing on trophic interactions.

The aim of this study was to provide a better understanding of the mechanisms underlying the relationships between family connectedness, coping strategies, and stress-triggering problems in adolescents. To this end, it longitudinally examined the relationships between these three phenomena in a sample of New Zealand adolescents. Data were the three waves of the Youth Connectedness Project, in which 1,774 adolescents aged 10–17 completed a self-report survey three times at one-year intervals. Using random intercept longitudinal mediation path models, we tested whether and to what extent different coping strategies at T2 functioned as mediators between family connectedness at T1 and stress-triggering problems at T3. As predicted, statistical analyses indicated that family connectedness negatively predicted stress-triggering problems over time, and we found that maladaptive coping, but not adaptive coping, significantly mediated this relationship. This result suggests that family connectedness predicted a reduction in maladaptive coping one year later, and this lower level of maladaptation predicted a reduction in stress-triggering problems a subsequent year later. These and other related findings are important as they highlight several mechanisms shaping unfolding problematic situations experienced by adolescents. Contributions of the results to the existing body of knowledge about adolescents’ stress and coping strategies are discussed, as well as their clinical implications for the prevention or reduction of stress experienced by adolescents.

In urban Vehicular Ad Hoc Network (VANET) environments, buildings play a crucial role as they can act as obstacles that attenuate the transmission signal between vehicles. Such obstacles lead to multipath effects, which could substantially impact data transmission due to fading. Therefore, quantifying the impact of buildings on transmission quality is a key parameter of the propagation model, especially in critical scenarios involving emergency vehicles where reliable communication is of utmost importance. In this research, we propose a supervised learning approach based on Artificial Neural Networks (ANNs) to develop a predictive model capable of estimating the level of signal degradation, represented by the Bit Error Rate (BER), based on the obstacles perceived by moving emergency vehicles. By establishing a relationship between the level of signal degradation and the encountered obstacles, our proposed mechanism enables efficient routing decisions being made prior to the transmission process. Consequently, data packets are routed through paths that exhibit the lowest BER. To collect the training data, we employed Network Simulator 3 (NS-3) in conjunction with the Simulation of Urban MObility (SUMO) simulator, leveraging real-world data sourced from the OpenStreetMap (OSM) geographic database. OSM enabled us to gather geospatial data related to the Two-Dimensional (2D) geometric structure of buildings, which served as input for our Artificial Neural Network (ANN). To determine the most suitable algorithm for our ANN, we assessed the accuracy of ten learning algorithms in MATLAB, utilizing five key metrics: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Correlation Coefficient (R), and Maximum Prediction Error (MaxPE). For each algorithm, we conducted fifteen iterations based on ten hidden neurons and gauged its accuracy against the aforementioned metrics. Our analysis highlighted that the ANN underpinned by the Conjugate Gradient With Powell/Beale Restarts (CGB) learning algorithm exhibited superior performance in terms of MSE, RMSE, MAE, R, and MaxPE compared to other algorithms such as Levenberg-Marquardt (LM), Bayesian Regularization (BR), BFGS Quasi-Newton (BFG), Resilient Backpropagation (RP), Scaled Conjugate Gradient (SCG), Fletcher-Powell Conjugate Gradient (CGF), Polak-Ribiére Conjugate Gradient (CGP), One-Step Secant (OSS), and Variable Learning Rate Backpropagation (GDX). The BER prediction by our ANN incorporates the TWO-RAY Ground (TRG) propagation model, an adjustable parameter within NS-3. When subjected to 300 new samples, the trained ANN's simulation outcomes illustrated its capability to learn, generalize, and successfully predict the BER for a new data instance. Overall, our research contributes to enhancing the performance and reliability of communication in urban VANET environments, especially in critical scenarios involving emergency vehicles, by leveraging supervised learning and artificial neural networks to predict signal degradation levels and optimize routing decisions accordingly.

Introduction Migrant, internally displaced, asylum seeking and refugee women experience ongoing risks of having their reproductive healthcare rights violated. This ever-increasing population also has limited access to sexual and reproductive health services. We conducted a scoping review to identify the barriers and facilitating factors when accessing sexual and reproductive health services for this specific population. Methods We searched the grey literature and queried eight bibliographic databases (Embase, Medline, Cinahl, Scopus, Science Direct, Web of Science, Hinari, and Cochrane Library) to extract articles published between January, 2000, and October, 2021. The extracted data were organized in a framework adapted from Peters et al. and then categorized as facilitators or barriers. We followed the Arksey and O’Malley framework and wrote the report according to the PRISMA-Scr recommendations. Results The search identified 4,722 records of which forty-two (42) met eligibility criteria and were retained for analysis. Ten (10) groups of factors facilitating and/or limiting access to sexual and reproductive health care emerged from the synthesis of the retained articles. The main barriers were lack of knowledge about services, cultural unacceptability of services, financial inaccessibility, and language barriers between patients and healthcare providers. Facilitators included mobile applications for translation and telehealth consultations, patients having a wide availability of information sources, the availability health promotion representatives, and healthcare providers being trained in cultural sensitivity, communication and person-centered care. Conclusion Ensuring the sexual and reproductive rights of migrant, internally displaced, asylum-seeking and refugee women requires that policymakers and health authorities develop intervention strategies based on barriers and facilitators identified in this scoping review. Therefore, considering their mental health in future studies would enable a better understanding of the barriers and facilitators of access to sexual and reproductive health services.

This study evaluated the effectiveness of the Triple P (Primary Care and/or Group) parenting support program on various aspects of the parenting experience through a quasi-experimental pretest – post-test protocol with an active comparison group (Care as usual). A sample of 384 parents assigned to two groups (n Triple P = 291; n Care as usual = 93) completed three subscales of the Parenting Stress Index – 4 – Short Form (Parental Distress, Parent-Child Dysfunctional Interaction, and Difficult Child) and the Parental Self-Agency Measure. The amount of intervention received by each parent was considered in the analyses. Path analysis showed that the type (Triple P vs Care as usual) and the amount of intervention (number of sessions attended) contributed independently to predicting changes in parenting experience between pretest and post-test. Receiving Triple P was systematically associated with more positive outcomes than receiving care as usual, whereas more intervention was positively associated with improved self-efficacy and parent-child relationship quality. Overall, the model explained between 4.0% and 12.6% of the variance in individual change, depending on the outcome, suggesting that unmeasured drivers of change came into play. A follow-up of parents in the Triple P group two to four years after the end of the program (n follow-up = 164) showed that the observed changes were maintained over time, with moderate to large effect sizes. These results help to broaden the evidence base on the effectiveness of this program in a sociocultural and linguistic context different from that in which it was developed.

Mangroves are a challenging ecosystem for the microorganisms that inhabit them, considering they are subjected to stressful conditions such as high and fluctuating salinity. Metagenomic analysis of mangrove soils under contrasting salinity conditions was performed at the mouth of the Ranchera River to the Caribbean Sea in La Guajira, Colombia, using shotgun sequencing and the Illumina Hiseq 2500 platform. Functional gene analysis demonstrated that salinity could influence the abundance of microbial genes involved in osmoprotectant transport, DNA repair, heat shock proteins (HSP), and Quorum Sensing, among others. In total, 135 genes were discovered to be linked to 12 pathways. Thirty-four genes out of 10 pathways had statistical differences for a p-value and FDR < 0.05. UvrA and uvrB (nucleotide excision repair), groEL (HSP), and secA (bacterial secretion system) genes were the most abundant and were enriched by high salinity. The results of this study showed the prevalence of diverse genetic mechanisms that bacteria use as a response to survive in the challenging mangrove, as well as the presence of various genes that are recruited in order to maintain bacterial homeostasis under conditions of high salinity.

Aim To identify indicators sensitive to the practice of primary healthcare nurse practitioners (PHCNPs). Materials and methods A review of systematic reviews was undertaken to identify indicators sensitive to PHCNP practice. Published and grey literature was searched from January 1, 2010 to December 2, 2022. Titles/abstracts (n = 4251) and full texts (n = 365) were screened independently by two reviewers, with a third acting as a tie-breaker. Reference lists of relevant publications were reviewed. Risk of bias was examined independently by two reviewers using AMSTAR-2. Data were extracted by one reviewer and verified by a second reviewer to describe study characteristics, indicators, and results. Indicators were recoded into categories. Findings were summarized using narrative synthesis. Results Forty-four systematic reviews were retained including 271 indicators that were recoded into 26 indicator categories at the patient, provider and health system levels. Nineteen reviews were assessed to be at low risk of bias. Patient indicator categories included activities of daily living, adaptation to health conditions, clinical conditions, diagnosis, education-patient, mortality, patient adherence, quality of life, satisfaction, and signs and symptoms. Provider indicator categories included adherence to best practice-providers, education-providers, illness prevention, interprofessional team functioning, and prescribing. Health system indicator categories included access to care, consultations, costs, emergency room visits, healthcare service delivery, hospitalizations, length of stay, patient safety, quality of care, scope of practice, and wait times. Discussion Equal to improved care for almost all indicators was found consistently for the PHCNP group. Very few indicators favoured the control group. No indicator was identified for high/low fidelity simulation, cultural safety and cultural sensitivity with people in vulnerable situations or Indigenous Peoples. Conclusion This review of systematic reviews identified patient, provider and health system indicators sensitive to PHCNP practice. The findings help clarify how PHCNPs contribute to care outcomes. PROSPERO registration number CRD42020198182 .

Objectives This article aims to analyze the vulnerabilities experienced by Haitian adolescent girls before their pregnancy. Methods A qualitative research design was developed from Dewey’s social survey. From October 2020 to January 2021, semi-structured interviews were conducted with 33 pregnant adolescents living in Haiti’s North and North-East departments. Thematic data analysis was performed using the qualitative data analysis software QDA miner, 6.0.5. Results The adolescent girls interviewed were between 14 and 19. The study showed that adolescent girls experienced economic and social hardship, gender issues, and barriers to contraceptive use before pregnancy. These girls have experienced restrictive conditions that make them vulnerable to risky sexual practices and unwanted pregnancy. Conclusions The results have indicated that Haitian adolescent girls’ vulnerabilities before their pregnancy result from economic, social, and cultural injustices to which they are exposed from early childhood. These adolescent girls are also highly vulnerable to sexual exploitation and rape, as well as pregnancy. It is essential to address these issues when implementing programs aimed at improving the living conditions of adolescents in Haiti, including the prevention of early and unwanted pregnancy.

Background: Effective healthcare innovations are often not scaled up beyond their initial local context. Lack of practical knowledge on how to move from local innovations to large-system improvement hinders innovation and learning capacity in health systems. Studying scale-up processes can lead to a better understanding of how to facilitate the scale-up of interventions. eConsult is a digital health innovation that aims to connect primary care professionals with specialists through an asynchronous electronic consultation. The recent implementation of eConsult in the public health systems of four Canadian jurisdictions provides a unique opportunity to identify different enabling strategies and related factors that promote the scaling up of eConsult across jurisdictions. Methods: We conducted a narrative case study in four Canadian provinces, Quebec, Ontario, Manitoba, and Newfoundland & Labrador, over a 3-year period (2018–2021). We observed provincial eConsult committee meetings (n=65) and national eConsult forums (n=3), and we reviewed internal documents (n=93). We conducted semi-structured interviews with key actors in each jurisdiction (eg, researchers, primary care professionals, specialists, policy-makers, and patient partners) (n=40). We conducted thematic analysis guided by the literature on factors and strategies used to scale up innovations. Results: We identified a total of 31 strategies related to six key enabling factors to scaling up eConsult, including: (1) multi-actor engagement; (2) relative advantage; (3) knowledge transfer; (4) strong evidence base; (5) physician leadership; and (6) resource acquisition (eg, human, material, and financial resources). More commonly used strategies, such as leveraging research infrastructure and bringing together various actors, were used to address multiple enabling factors. Conclusion: Actors used various strategies to scale up eConsult within their respective contexts, and these helped address six key factors that seemed to be essential to the scale-up of eConsult.

Along with forest managers, builders are key change agents of forest ecosystems’ structure and composition through the specification and use of wood products. New forest management approaches are being advocated to increase the resilience and adaptability of forests to climate change and other natural disturbances. Such approaches call for a diversification of our forests based on species’ functional traits that will dramatically change the harvested species composition, volume, and output of our forested landscapes. This calls for the wood-building industry to adapt its ways of operating. Accordingly, we expand the evaluation of the ecological resilience of forest ecosystems based on functional diversification to include a trait-based approach to building with wood. This trait-based plant-building framework can illustrate how forecasted forest changes in the coming decades may impact and guide decisions about wood-building practices, policies, and specifications. We apply this approach using a fragmented rural landscape in temperate southeastern Canada. We link seven functional groups based on the ecological traits of tree species in the region to a similar functional grouping of building traits to characterize the push and pull of managing forests and wood buildings together. We relied on a process-based forest landscape model to simulate long-term forest dynamics and timber harvesting to evaluate how various novel management approaches will interact with the changing global environment to affect the forest-building relationships. Our results suggest that adopting a whole system, plant-building approach to forests and wood buildings, is key to enhancing forest ecological and timber construction industry resilience.

Social policies determine the distribution of factors (e.g. education , cardiovascular health) protecting against the development of dementia in Alzheimer's disease (AD). However, the association between social policies and the likelihood of AD without demen-tia (ADw/oD) has yet to be evaluated. We estimated this association in an ecological study using systematic review and meta-analysis. Four reference databases were consulted; 18 studies were included in the final analysis. ADw/oD was defined as death without dementia in people with clinically significant AD brain pathology. The indicators of social policy were extracted from the Organisation for Economic Cooperation and Development database (OECD). The probability of ADw/oD with moderate AD brain pathology was inversely associated with the Gini index for disposable income, poverty rate, and certain public expenditures on healthcare. ADw/oD with advanced AD brain pathology was only associated with public expenditures for long-term care. Social policies may play a role in maintaining and sustaining cognitive health among older people with AD. ARTICLE HISTORY

Time-driven activity-based costing (TDABC) and activity-based costing (ABC) are methods used in the healthcare sector to assess the costs of patient care pathways. These methods help identify opportunities for optimizing and reducing activity times without compromising the quality of care. TDABC is recommended in the value-based healthcare (VBHC) model to assess the outcomes of care pathways in relation to their associated costs. By focusing on the creation of value for patients, TDABC helps identify the interventions and processes that provide the most value in terms of clinical outcomes and patient satisfaction. This enables healthcare organizations to make informed decisions on improvements that will maximize value for patients. We have chosen to use the TDABC and ABC methods to calculate the costs of care pathways for thoracic surgery patients in two healthcare establishments prior to and following the implementation of a digital health solution. By using these methods, we were able to calculate the costs associated with each stage of the patients’ care pathway. This has given us a clearer picture of the costs associated with each activity and a better understanding of the sources of expenditure. The results show that implementing the digital health solution and applying the principles of the VBHC model have provided tangible benefits in terms of reviewing processes and the roles of the various players involved, eliminating unnecessary or non-value-added activities, automating administrative or repetitive tasks, and improving coordination between the two healthcare establishments and between healthcare professionals. These improvements have contributed to better patient care.

Recent long‐term tree biodiversity experiments have shown that diversity effects on productivity tend to strengthen over time, as complementarity among constituent species increases over the course of forest development. However, these community‐level metrics only account for the net outcome of multiple interactions among species and, thus, do not inform about the individual species' responses to diversity. In this study, using 11 years of growth records from a large diversity experiment, we explored how species respond to diversity based on their functional traits and those of their heterospecific neighbours over time and analysed their contribution to the community‐level overyielding. We show species‐specific responses to diversity, with fast‐growing deciduous species rapidly performing better in mixtures relative to monocultures, than slow‐growing evergreen species. Moreover, we find that species productivity in mixtures enhances over time as the proportion of slow‐growing evergreen species in the heterospecific neighbourhood increases. These patterns of response of species scale up and explain community overyielding, which occurs primarily in deciduous‐evergreen mixtures and is explained by the overyielding of deciduous species overcompensating the poor performance of evergreen species. This study sheds light on the temporal dynamics of species responses to diversity, which together help improve our understanding of community‐level overyielding over the course of stand development. Read the free Plain Language Summary for this article on the Journal blog.

Following the surge for empathy training in service literature and its increasing demand in service industries, this study systematically reviews empirical papers implementing and testing empathy training programs in various service domains. A mixed-methods systematic review was performed to identify and describe empathy training programs and discuss their effectiveness in service quality, service employees' well-being, and service users' satisfaction. Included papers met those eligibility criteria: qualitative, quantitative, or mixed-methods study; one training in empathy is identifiable; described training(s) developed for or tested with service employees dealing with service users. We searched health, business, education, and psychology databases, such as CINAHL, Medline ABI/Inform Global, Business Source Premier, PsycINFO, and ERIC. We used the Mixed-Method Assessment Tool to appraise the quality of included papers. A data-based convergent synthesis design allowed for the analysis of the data. A total of 44 studies published between 2009 to 2022 were included. The narrative presentation of findings was regrouped into these six dimensions of empathy training programs: 1) why, 2) who, 3) what, 4) how, 5) where, and 6) when and how much. Close to 50% of studies did not include a definition of empathy. Four main empathic competencies developed through the training programs were identified: communication, relationship building, emotional resilience, and counseling skills. Face-to-face and group-setting interventions are widespread. Our systematic review shows that the 44 papers identified come only from health services with a predominant population of physicians and nurses. However, we show that the four empathic skills identified could be trained and developed in other sectors, such as business. This is the first mixed-methods, multi-disciplinary systematic review of empathy training programs in service research. The review integrates insights from health services, identifies research limitations and gaps in existing empirical research, and outlines a research agenda for future research and implications for service research.

Background: The COVID-19 pandemic has disproportionately and severely affected older adults, namely those living in long-term care facilities (LTCFs). Aside from experiencing high mortality rates, survivors were critically concerned by social isolation and loneliness (SIL). To address this serious public health concern and stay connected with LTCF residents, information and communication technology (ICT) platforms (eg, video calls) were used as an alternative to maintaining social interactions amid the visiting restriction policy. Objective: This paper aimed to synthesize the effects of ICT-related communication interventions using SMS text messaging or chat, video, voice mail, or photo to address SIL in LTCF residents during the COVID-19 pandemic. Methods: In total, 2793 references published in English and French in 2019 and onward were obtained from 10 relevant databases: PsycINFO-Ovid, Ovid-MEDLINE, CINAHL-EBSCO, Cochrane Library, Web of Science, Scopus, DirectScience, Communication & Mass Media Complete, IEEE Xplore, and ACM Digital Library. A 2-person screening approach was used, and the studies were screened independently and blindly. A narrative synthesis was performed to interpret the results of the included studies, and their quality was appraised. Results: In total, 4 studies were included in the review. ICT-related applications were used to ensure connectedness to address SIL. ICT interventions consisted mainly of videoconferencing, intergroup video call sessions between residents, and chatting (SMS text messages and phone calls). Roughly 3 classes of mediating ICT tools were used: video calls using software applications (eg, Skype); robot systems embedding video telephones; and ordinary telecommunication such as telephone, internet, social media platforms, and videoconferencing. This review has included the role of humanoid robots in LTCFs as an innovation avenue because of their multipurpose use (eg, communication tools and remotely operable). Conclusions: Remote social capitalization through ICT applications has become an avenue to reduce SIL among LTCF residents. This review examined a social connection approach that will remain relevant and even be fostered after the COVID-19 pandemic. As families remain the main stakeholders of LTCFs, this study's findings could inform policy makers and frontline managers to better shape programs and initiatives to prevent or reduce SIL in LTCFs. International registered report identifier (irrid): RR2-10.2196/36269.

Context Uneven-aged forest management is sometimes seen as offering interesting compromises between timber production and other important ecosystem services, compared to even-aged approaches. However, uncertainties remain concerning its impacts over longer time periods and broader spatial scales, as larger areas and further roads are required to harvest the same amount of wood. Objectives We compared the large-scale and long-term impacts of uneven-aged and even-aged managements on the composition, road density and fragmentation of a landscape composed of northern temperate and boreal forests, and presenting frequent forest fires. Methods We simulated an 800,000 ha forested landscape in the Mauricie region (Quebec, Canada) over a 150-year planning horizon with the LANDIS-II model and an extension that simulates forest road construction. We compared 30 different management scenarios that varied the proportion of even- and uneven-aged managements, the level of aggregation of the harvested areas, and the presence of pre-existing forest roads. Results Compared with even-aged management, uneven-aged management increased (i) the density of forest roads and their operational costs, (ii) the amount of old forests, and (iii) their fragmentation. Aggregating harvested areas did not noticeably reduce road density, and the presence of an initial road network had no long-term effects. Differences in landscape fragmentation between scenarios were reduced in the northern region of the landscape due to the fire regime. Conclusions Choosing uneven-aged over even-aged management represents a trade-off between the amount of old forests in the landscape and three variables related to roads: their density, their related cost, and the fragmentation per se that they generate, This trade-off seems to disappear in the presence of stand-replacing disturbances in the landscape and is unlikely to be improved by aggregating the harvested areas.

Background: The aim of the present study was to identify eaters profiles using the latest advantages of Machine Learning approach to cluster analysis. Methods: A total of 317 participants completed an online-based survey including self-reported measures of body image dissatisfaction, bulimia, restraint, and intuitive eating. Analyses were conducted in two steps: (a) identifying an optimal number of clusters, and (b) validating the clustering model of eaters profile using a procedure inspired by the Causal Reasoning approach. Results: This study reveals a 7-cluster model of eaters profiles. The characteristics, needs, and strengths of each eater profile are discussed along with the presentation of a continuum of eaters profiles. Conclusions: This conceptualization of eaters profiles could guide the direction of health education and treatment interventions targeting perceptual and eating dimensions.