Development and validation of the Trust in Multidimensional Healthcare Systems Scale (TIMHSS).

CONTEXT: The COVID-19 pandemic has reignited a commitment from the health policy and health services research communities to rebuilding trust in healthcare and created a renewed appetite for measures of trust for system monitoring and evaluation. The aim of the present paper was to develop a multidimensional measure of trust in healthcare that: (1) Is responsive to the conceptual and methodological limitations of existing measures; (2) Can be used to identify systemic explanations for lower levels of trust in equity-deserving populations; (3) Can be used to design and evaluate interventions aiming to (re)build trust. METHODS: We conducted a 2021 review of existing measures of trust in healthcare, 72 qualitative interviews (Aug-Dec 2021; oversampling for equity-deserving populations), an expert review consensus process (Oct 2021), and factor analyses and validation testing based on two waves of survey data (Nov 2021, n = 694; Jan-Feb 2022, n = 740 respectively). FINDINGS: We present the Trust in Multidimensional Healthcare Systems Scale (TIMHSS); a 38-item correlated three-factor measure of trust in doctors, policies, and the system. Measurement of invariance tests suggest that the TIMHSS can also be reliably administered to diverse populations. CONCLUSIONS: This global measure of trust in healthcare can be used to measure trust over time at a population level, or used within specific subpopulations, to inform interventions to (re)build trust. It can also be used within a clinical setting to provide a stronger evidence base for associations between trust and therapeutic outcomes.

Development and validation of the Trust in Government measure (TGM).

BACKGROUND: Trust in government is associated with health behaviours and is an important consideration in population health interventions. While there is a reported decline in public trust in government across OECD countries, the tools used to measure trust are limited in their use for informing action to (re)build trust, and have limitations related to reliability and validity. To address the limitations of existing measures available to track public trust, the aim of the present work was to develop a new measure of trust in government. METHODS: Fifty-six qualitative interviews (Aug-Oct 2021; oversampling for equity-deserving populations) were conducted to design a national survey, including factor analyses and validation testing (N = 878; June 1-14th 2022) in Canada. RESULTS: The measure demonstrated strong internal consistency (α = 0.96) and test validity (CFI = 0.96, RMSEA = 0.09, SRMR = 0.03), suggesting that trust in government can be measured as a single underlying construct. It also demonstrated strong criterion validity, as measured by significant (p < 0.0001) associations of scores with vaccine hesitancy, vaccine conspiracy beliefs, COVID-19 conspiracy beliefs, trust in public health messaging about COVID-19, and trust in public health advice about COVID-19. We present the Trust in Government Measure (TGM); a 13-item unidimensional measure of trust in Federal government. CONCLUSIONS: This measure can be used within high-income countries, particularly member countries within the OECD already in support of using tools to collect, publish and compare statistics. Our measure should be used by researchers and policy makers to measure trust in government as a key indicator of societal and public health.

Examining factors impacting acceptance of COVID-19 countermeasures among structurally marginalised Canadians.

The COVID-19 pandemic highlighted and exacerbated inequities in health for structurally marginalised Canadians. Their location on society's hierarchies constrained their ability to access healthcare and follow recommended health behaviours. The aim of this article is to identify, from the perspective of marginalised populations, factors influencing the acceptance or rejection of COVID-19 countermeasures by structurally marginalised Canadians. Interviews were conducted with Canadians 18 + who identified as Black (n = 8), First Nations, Métis, or Inuit (n = 7) and low-income (<40,000 annual household income) (n = 8) between August and December 2021. Measures were said to impact well-being and interfere with revenue generating activities. Longstanding unfavourable living and environmental conditions as they relate to structural marginalisation was said to fuel anger toward the government and lead to a greater reluctance to accept countermeasures. Participants described concerns about government decisions being made without considering their unique contexts, or knowledge of the experiences of the population for whom these decisions were being made. Effective proactive action from government is important to foster trust with marginalised populations to support acceptance of health information and address growing inequities. Action that demonstrates government competence and commitment to the interests of marginalised populations is critical.

Newcomer perceptions of COVID-19 countermeasures in Canada.

Newcomers to Canada have been disproportionally affected by COVID-19, with higher rates of infection and severity of illness. Determinants of higher rates may relate to social and structural inequities that impact newcomers' capacity to follow countermeasures. Our aim was to describe and document factors shaping newcomers' acceptance of COVID-19 countermeasures. Semi-structured qualitative interviews were conducted with individuals living in Canada for <5 years. Participants were asked to discuss their pandemic experiences, and perceptions and acceptance of measures. Five themes were identified: (i) belief in the necessity and efficacy of countermeasures; (ii) negative impact of measures on health/wellbeing; (iii) existing barriers to newcomer settlement exacerbated by pandemic measures; (iv) countermeasure adherence related to immigration status and (v) past experiences shaping countermeasure acceptance. Government should continue to provide messaging regarding the importance of measures for individual and population heath and continue to demonstrate a commitment to the interests of citizens. Importantly, newcomer trust in government should not be taken for granted, as this trust is critical for the acceptance of government interventions now and moving forward. It will be important to ensure that newcomers are given support to overcome challenges to settlement that were intensified during the pandemic.

Spatial variation in the association between agricultural activities and bird communities in Canada.

Agriculture is one the main drivers of bird decline in both Europe and North America. While it is clear that agricultural practices and changes in the rural landscape directly and indirectly affect bird communities, we still do not know the extent to which these impacts might change across broad spatial and temporal scales. To address this question, we combined information on agricultural activities with occurrence and abundance of 358 bird species across five time periods spanning 20 years in Canada. As a proxy for agricultural impact, we used a combined index that included different agricultural metrics, such as cropland and tillage area and area treated with pesticides. We found that agriculture impact was negatively associated with bird diversity and evenness across all 20 years studied, but these associations seemed to vary by region. We found good support for an overall negative association between agriculture impact and bird diversity and evenness in the Eastern and Atlantic regions but weaker associations in the Prairies and Pacific. These findings suggest that agricultural activities result in bird communities that are less diverse and disproportionately benefit certain species. The spatial variation in the impact of agriculture on bird diversity and evenness we observed is likely a result of regional differences in the native vegetation, the type of crops and commodities produced, the historical context of agriculture, as well as the native bird community and the extent of their association with open habitat. Thus, our work provides support for the idea that the on-going agricultural impact on bird communities, while largely negative, is not uniform, and can vary across broad geographic regions.

Mood Disturbances Across the Continuum of Care Based on Self-Report and Clinician Rated Measures in the interRAI Suite of Assessment Instruments.

Background: Mood disturbance is a pervasive problem affecting persons of all ages in the general population and the subset of those receiving services from different health care providers. interRAI assessment instruments comprise an integrated health information system providing a common approach to comprehensive assessment of the strengths, preferences and needs of persons with complex needs across the continuum of care. Objective: Our objective was to create new mood scales for use with the full suite of interRAI assessments including a composite version with both clinician-rated and self-reported items as well as a self-report only version. Methods: We completed a cross-sectional analysis of 511,641 interRAI assessments of Canadian adults aged 18+ in community mental health, home care, community support services, nursing homes, palliative care, acute hospital, and general population surveys to develop, test, and refine new measures of mood disturbance that combined clinician and self-rated items. We examined validity and internal consistency across diverse care settings and populations. Results: The composite scale combining both clinician and self-report ratings and the self-report only variant showed different distributions across populations and settings with most severe signs of disturbed mood in community mental health settings and lowest severity in the general population prior to the COVID-19 pandemic. The self-report and composite measures were strongly correlated with each other but differed most in populations with high rates of missing values for self-report due to cognitive impairment (e.g., nursing homes). Evidence of reliability was strong across care settings, as was convergent validity with respect to depression/mood disorder diagnoses, sleep disturbance, and self-harm indicators. In a general population survey, the correlation of the self-reported mood scale with Kessler-10 was 0.73. Conclusions: The new interRAI mood scales provide reliable and valid mental health measures that can be applied across diverse populations and care settings. Incorporating a person-centered approach to assessment, the composite scale considers the person's perspective and clinician views to provide a sensitive and robust measure that considers mood disturbances related to dysphoria, anxiety, and anhedonia.

Longitudinal Trends and Risk Factors for Depressed Mood Among Canadian Adults During the First Wave of COVID-19.

Background: The COVID-19 pandemic has raised serious concerns about the mental health impact of people directed and indirectly affected by the virus. Because this is a rapidly evolving situation, our goal was to explore potential risk factors and trends in feelings of anxiety and depression among the general population in Canada over the first 5 months of the pandemic. Methods: We completed on-line surveys of 3,127 unique individuals representative of the Canadian general population at 4 discreet periods every 6 weeks from April 15th to July 28th 2020. We assessed feelings of anxiety, depression and loss of interest with the interRAI self-reported mood scale using a multivariable generalized estimating equation model to examine factors associated with having a 5+ score on the scale (indicating potentially depressed mood). We also investigated potential longitudinal trends to examine temporal variation in mood scores. Results: More than 30% of participants felt highly anxious, depressed, and disinterested in everyday activities in the first survey (April), but this number decreased to about 20% over 4 months. Feeling lonely, younger age, feeling overwhelmed by one's health needs, having financial concerns, and living outside of Québec were significantly associated with depressed mood. Interpretation: The prevalence of depressed mood during the pandemic was between 2 and 3 times the pre-pandemic rate (especially among young people), but it can change rapidly in response to social changes. Thus, monitoring of psychological distress among vulnerable groups that may benefit from additional supports should be a priority.

Early warning indicators of population collapse in a seasonal environment.

Recent studies have demonstrated that generic statistical signals derived from time series of population abundance and fitness-related traits of individuals can provide reliable indicators of impending shifts in population dynamics. However, how the seasonal timing of environmental stressors influences these early warning indicators is not well understood. The goal of this study was to experimentally assess whether the timing of stressors influences the production, detection and sensitivity of abundance- and trait-based early warning indicators derived from declining populations. In a multi-generation, season-specific habitat loss experiment, we exposed replicate populations of Drosophila melanogaster to one of two rates of chronic habitat loss (10% or 20% per generation) in either the breeding or the non-breeding period. We counted population abundance at the beginning of each season, and measured body mass and activity levels in a sample of individuals at the end of each generation. When habitat was lost during the breeding period, declining populations produced signals consistent with those documented in previous studies. Inclusion of trait-based indicators generally improved the detection of impending population collapse. However, when habitat was lost during the non-breeding period, the predictive capacity of these indicators was comparatively diminished. Our results have important implications for interpreting signals in the wild because they suggest that the production and detection of early warning indicators depends on the season in which stressors occur, and that this is likely related to the capacity of populations to respond numerically the following season.

Habitat selection patterns are density dependent under the ideal free distribution.

Despite being widely used, habitat selection models are rarely reliable and informative when applied across different ecosystems or over time. One possible explanation is that habitat selection is context-dependent due to variation in consumer density and/or resource availability. The goal of this paper is to provide a general theoretical perspective on the contributory mechanisms of consumer and resource density-dependent habitat selection, as well as on our capacity to account for their effects. Towards this goal we revisit the ideal free distribution (IFD), where consumers are assumed to be omniscient, equally competitive and freely moving, and are hence expected to instantaneously distribute themselves across a heterogeneous landscape such that fitness is equalised across the population. Although these assumptions are clearly unrealistic to some degree, the simplicity of the structure in IFD provides a useful theoretical vantage point to help clarify our understanding of more complex spatial processes. Of equal importance, IFD assumptions are compatible with the assumptions underlying common habitat selection models. Here we show how a fitness-maximising space use model, based on IFD, gives rise to resource and consumer density-dependent shifts in consumer distribution, providing a mechanistic explanation for the context-dependent outcomes often reported in habitat selection analysis. Our model suggests that adaptive shifts in consumer distribution patterns would be expected to lead to nonlinear and often non-monotonic patterns of habitat selection. These results indicate that even under the simplest of assumptions about adaptive organismal behaviour, habitat selection strength should critically depend on system-wide characteristics. Clarifying the impact of adaptive behavioural responses may be pivotal in making meaningful ecological inferences about observed patterns of habitat selection and allow reliable transferability of habitat selection predictions across time and space.

Food availability modulates temperature-dependent effects on growth, reproduction, and survival in Daphnia magna.

Reduced body size and accelerated life cycle due to warming are considered major ecological responses to climate change with fitness costs at the individual level. Surprisingly, we know little about how relevant ecological factors can alter these life history trade-offs and their consequences for individual fitness. Here, we show that food modulates temperature-dependent effects on body size in the water flea Daphnia magna and interacts with temperature to affect life history parameters. We exposed 412 individuals to a factorial manipulation of food abundance and temperature, tracked each reproductive event, and took daily measurements of body size from each individual. High temperature caused a reduction in maximum body size in both food treatments, but this effect was mediated by food abundance, such that low food conditions resulted in a reduction of 20% in maximum body size, compared with a reduction of 4% under high food conditions. High temperature resulted in an accelerated life cycle, with pronounced fitness cost at low levels of food where only a few individuals produced a clutch. These results suggest that the mechanisms affecting the trade-off between fast growth and final body size are food-dependent, and that the combination of low levels of food and high temperature could potentially threaten viability of ectotherms.

Simple signals indicate which period of the annual cycle drives declines in seasonal populations.

For declining wild populations, a critical aspect of effective conservation is understanding when and where the causes of decline occur. The primary drivers of decline in migratory and seasonal populations can often be attributed to a specific period of the year. However, generic, broadly applicable indicators of these season-specific drivers of population decline remain elusive. We used a multi-generation experiment to investigate whether habitat loss in either the breeding or non-breeding period generated distinct signatures of population decline. When breeding habitat was reduced, population size remained relatively stable for several generations, before declining precipitously. When non-breeding habitat was reduced, between-season variation in population counts increased relative to control populations, and non-breeding population size declined steadily. Changes in seasonal vital rates and other indicators were predicted by the season in which habitat loss treatment occurred. Per capita reproductive output increased when non-breeding habitat was reduced and decreased with breeding habitat reduction, whereas per capita non-breeding survival showed the opposite trends. Our results reveal how simple signals inherent in counts and demographics of declining populations can indicate which period of the annual cycle is driving declines.

Experimental evidence that density mediates negative frequency-dependent selection on aggression.

Aggression can be beneficial in competitive environments if aggressive individuals are more likely to access resources than non-aggressive individuals. However, variation in aggressive behaviour persists within populations, suggesting that high levels of aggression might not always be favoured. The goal of this study was to experimentally assess the effects of population density and phenotypic frequency on selection on aggression in a competitive environment. We compared survival of two strains of Drosophila melanogaster that differ in aggression across three density treatments and five frequency treatments (single strain groups, equal numbers of each strain and strains mixed at 3:1 and 1:3 ratios) during a period of limited resources. While there was no difference in survival across single-strain treatments, survival was strongly density dependent, with declining survival as density increased. Furthermore, at medium and high densities, there was evidence of negative frequency-dependent selection, where rare strains experienced greater survival than common strains. However, there was no evidence of negative frequency-dependent selection at low density. Our results indicate that the benefits of aggression during periods of limited resources can depend on the interaction between the phenotypic composition of populations and population density, both of which are mechanisms that could maintain variation in aggressive behaviours within natural populations.

Fear creates an Allee effect: experimental evidence from seasonal populations.

Allee effects driven by predation can play a strong role in the decline of small populations but are conventionally thought to occur when generalist predators target specific prey (i.e. type II functional response). However, aside from direct consumption, fear of predators could also increase vigilance and reduce time spent foraging as population size decreases, as has been observed in wild mammals living in social groups. To investigate the role of fear on fitness in relation to population density in a species with limited sociality, we exposed varying densities of Drosophila melanogaster to mantid predators either during an experimental breeding season or non-breeding season. The presence of mantids in either season decreased the reproductive performance of individuals but only at low breeding densities, providing evidence for an Allee effect. We then used our experimental results to parametrize a mathematical model to examine the population consequences of fear at low densities. Fear tended to destabilize population dynamics and increase the risk of extinction up to sevenfold. Our study provides unique experimental evidence that the indirect effects of the presence of predators can cause an Allee effect and has important consequences for our understanding of the dynamics of small populations.

Why are we not evaluating multiple competing hypotheses in ecology and evolution?

The use of multiple working hypotheses to gain strong inference is widely promoted as a means to enhance the effectiveness of scientific investigation. Only 21 of 100 randomly selected studies from the ecological and evolutionary literature tested more than one hypothesis and only eight tested more than two hypotheses. The surprising rarity of application of multiple working hypotheses suggests that this gap between theory and practice might reflect some fundamental issues. Here, we identify several intellectual and practical barriers that discourage us from using multiple hypotheses in our scientific investigation. While scientists have developed a number of ways to avoid biases, such as the use of double-blind controls, we suspect that few scientists are fully aware of the potential influence of cognitive bias on their decisions and they have not yet adopted many techniques available to overcome intellectual and practical barriers in order to improve scientific investigation.

A fitness trade-off between seasons causes multigenerational cycles in phenotype and population size.

Although seasonality is widespread and can cause fluctuations in the intensity and direction of natural selection, we have little information about the consequences of seasonal fitness trade-offs for population dynamics. Here we exposed populations of Drosophila melanogaster to repeated seasonal changes in resources across 58 generations and used experimental and mathematical approaches to investigate how viability selection on body size in the non-breeding season could affect demography. We show that opposing seasonal episodes of natural selection on body size interacted with both direct and delayed density dependence to cause populations to undergo predictable multigenerational density cycles. Our results provide evidence that seasonality can set the conditions for life-history trade-offs and density dependence, which can, in turn, interact to cause multigenerational population cycles.

Daphnia inhibits the emergence of spatial pattern in a simple consumer-resource system.

Spatial self-organization can occur in many ecosystems with important effects on food web dynamics and the maintenance of biodiversity. The consumer-resource interaction is known to generate spatial patterning, but only a few empirical studies have investigated the effect of the consumer on resource distribution. Here we report results from a large aquatic mesocosm experiment used to investigate the effect of the consumer Daphnia magna on the distribution of its resource, the green algae Chlorella vulgaris. We maintained large tanks with capacity for 26 ,000 L with either algae or both algae and Daphnia in different temperature conditions. We found that the presence of D. magna inhibited spatial structure in algal distribution that arose as a consequence of increasing temperature. We conjecture that this homogenization effect might be caused by a combination of high mobility combined with high rates of algal consumption by Daphnia. Our study emphasizes the importance of both local constraints on growth and behavioral responses in either promoting or suppressing spatial self-organization in natural populations.

Calcium interacts with temperature to influence Daphnia movement rates.

Predicting the ecological responses to climate change is particularly challenging, because organisms might be affected simultaneously by the synergistic effects of multiple environmental stressors. Global warming is often accompanied by declining calcium concentration in many freshwater ecosystems. Although there is growing evidence that these changes in water chemistry and thermal conditions can influence ecosystem dynamics, little information is currently available about how these synergistic environmental stressors could influence the behaviour of aquatic organisms. Here, we tested whether the combined effects of calcium and temperature affect movement parameters (average speed, mean turning frequency and mean-squared displacement) of the planktonic Daphnia magna, using a full factorial design and exposing Daphnia individuals to a range of realistic levels of temperature and calcium concentration. We found that movement increased with both temperature and calcium concentration, but temperature effects became considerably weaker when individuals were exposed to calcium levels close to survival limits documented for several Daphnia species, signalling a strong interaction effect. These results support the notion that changes in water chemistry might have as strong an effect as projected changes in temperature on movement rates of Daphnia, suggesting that even sublethal levels of calcium decline could have a considerable impact on the dynamics of freshwater ecosystems.

Experimental evidence for within- and cross-seasonal effects of fear on survival and reproduction.

Fear of predation can have non-lethal effects on individuals within a season but whether, and to what extent, these effects carry over into subsequent seasons is not known. Using a replicated seasonal population of the common fruit fly, Drosophila melanogaster, we examined both within- and cross-seasonal effects of fear on survival and reproductive output. Compared to controls, flies exposed to the scent of mantid (Tenodera sinensis) predators in the non-breeding season had 64% higher mortality, and lost 60% more mass by the end of the non-breeding season and, in the subsequent breeding season, produced 20% fewer offspring that weighed 9% less at maturity. Flies exposed to the scent of mantids in the breeding season did not produce fewer offspring, but their offspring developed faster and weighed less as adults compared to the controls. Our results demonstrate how effects of fear can be manifested both within and across seasons and emphasize the importance of understanding how events throughout the annual cycle influence individual success of animals living in seasonal environments.

Experimental evidence for the effect of habitat loss on the dynamics of migratory networks.

Migratory animals present a unique challenge for understanding the consequences of habitat loss on population dynamics because individuals are typically distributed over a series of interconnected breeding and non-breeding sites (termed migratory network). Using replicated breeding and non-breeding populations of Drosophila melanogaster and a mathematical model, we investigated three hypotheses to explain how habitat loss influenced the dynamics of populations in networks with different degrees of connectivity between breeding and non-breeding seasons. We found that habitat loss increased the degree of connectivity in the network and influenced population size at sites that were not directly connected to the site where habitat loss occurred. However, connected networks only buffered global population declines at high levels of habitat loss. Our results demonstrate why knowledge of the patterns of connectivity across a species range is critical for predicting the effects of environmental change and provide empirical evidence for why connected migratory networks are commonly found in nature.

Body size, carry-over effects and survival in a seasonal environment: consequences for population dynamics.

In seasonal populations, vital rates are not only determined by the direct effects of density at the beginning of each season, but also by density at the beginning of past seasons. Such delayed density dependence can arise via non-lethal effects on individuals that carry over to influence per capita rates. In this study, we examine (i) whether parental breeding density influences offspring size, (ii) how this could carry over to affect offspring survival during the subsequent non-breeding period and (iii) the population consequences of this relationship. Using Drosophila melanogaster, the common fruit fly, submitted to distinct breeding and non-breeding seasons, we first used a controlled laboratory experiment to show that high parental breeding density leads to small offspring size, which then affects offspring survival during the non-breeding period but only at high non-breeding densities. We then show that a model with the interaction between parental breeding density and offspring density at the beginning of the non-breeding season best explained offspring survival over 36 replicated generations. Finally, we developed a biseasonal model to show that the positive relationship between parental density and offspring survival can dampen fluctuations in population size between breeding and non-breeding seasons. These results highlight how variation in parental density can lead to differences in offspring quality which result in important non-lethal effects that carry over to influence per capita rates the following season, and demonstrate how this phenomenon can have important implications for the long-term dynamics of seasonal populations.