Pathogens have evolved a variety of life-history strategies. An important strategy consists of successful transmission by an infected host before the appearance of symptoms, that is, while the host is still partially or fully asymptomatic. During this initial stage of infection, it is possible for another pathogen to superinfect an already infected host and replace the previously infecting pathogen. Here, we study the effect of superinfection during the first stage of an infection on the evolutionary dynamics of the degree to which the host is asymptomatic (host latency) in that same stage. We find that superinfection can lead to major differences in evolutionary behaviour. Most strikingly, the duration of immunity following infection can significantly influence pathogen evolutionary dynamics, whereas without superinfection the outcomes are independent of host immunity. For example, changes in host immunity can drive evolutionary transitions from a fully symptomatic to a fully asymptomatic first infection stage. Additionally, if superinfection relative to susceptible infection is strong enough, evolution can lead to a unique strategy of latency that corresponds to a local fitness minimum, and is therefore invasible by nearby mutants. Thus, this strategy is a branching point, and can lead to coexistence of pathogens with different latencies. Furthermore, in this new framework with superinfection, we also find that there can exist two interior singular strategies. Overall, new evolutionary outcomes can cascade from superinfection. To limit this burden and successfully decrease disease transmission, it is important to quantify epidemiological dynamics e.g. –3). Nume. Nume3])The evolutionary dynamics of a pathogen play a central role in host epidemiology. Evolving pathogens are under a series of constraints, including those imposed by within-host replication and host immunity. These constraints can modulate the degree of latency, i.e. the spectrum from fully symptomatic to fully asymptomatic, in the initial infectious stage. Here, we consider the initial infectious stage to be one where transmission may occur; this stage is distinct from and may follow a stage after infection where hosts are infected but not infectious. In other words, we consider a two-stage infection process where the first stage is said to have ‘zero latency’ if this stage is fully symptomatic, whereas we say the first stage has ‘maximal latency’ if it is fully asymptomatic. Thus, latency is a measure of the degree to which a host in the initial infectious stage fails to exhibit symptoms. If a host is more latent in the first stage (i.e. more asymptomatic), then the pathogen can potentially remain in this stage longer due to lowered host immune responses that would lead to pathogen clearance. However, in order for the pathogen to successfully ‘hide’ from the host immune system, decreased within-host replication and thus decreased pathogen shedding is required, which in turn decreases transmission  on the initial infection stage. These authors examined simple forms of progression and transmission trade-offs, and found four possible evolutionary behaviours: a unique evolutionarily stable strategy (ESS) at zero latency, positive latency, maximal latency or bistability with zero and maximal latency. With more complicated trade-off forms that changed concavity of progression and transmission as functions of latency, these authors also observed the appearance of multiple interior evolutionarily singular strategies. Throughout their analyses, Saad-Roy et al. [Pathogen evolutionary dynamics can be examined through a variety of approaches. Historically, there has been strong interest in understanding pathogen virulence from an evolutionary perspective e.g. ,13–20). –20. 13–2et al.  coupled y et al.  assumed The infection of an already-infected host by a different strain has been suggested as an important mechanism in infectious disease dynamics ,22, in psuperinfection as the within-host competitive clearance of the resident infecting pathogen by another pathogen. Therefore, superinfection is distinct from co-infection, where a host can be simultaneously infected by multiple strains [Here, we follow ,26–29 an strains ,30.et al. [et al. [The ties between superinfection and the evolution of virulence have been explored through various modelling frameworks , but equivalent results hold for the more general forms . Indeed, Saad-Roy et al. [λ but rather on the relationship between α1 and ν1 in addition to their values at maximal latency. Furthermore, to simplify our analyses, we take the biologically reasonable assumption that the basic reproduction number k of the second infection stage is greater than 1, i.e. k = α2/(ν2 + δ) > 1, where k is the expected number of new infections that arise in a naive population from a single host in the second stage.With no superinfection, Saad-Roy et al.  found thy et al.  highlighc2, and the transmission decay exponent, b2.The ability of a pathogen to superinfect gives rise to some notable evolutionary differences with respect to the previous model with no superinfection . The evob2 > c2. Thus, solving for α1 in terms of ν1 [b2 > c2 means that the dependence of α1 on ν1 is concave up. If there exists an interior evolutionarily singular strategy, then it is a fitness minimum and this is therefore not an ESS .We first assume that transmission in the first stage decays faster than progression, i.e. ms of ν1 , b2 > c2σ, on the sign of λ = λ* = 0, and on the value of the fully latent transmission rate times the average host lifespan, α1,∞/δ. Here, we succinctly summarize the qualitative behaviours and focus on the transitions in evolutionary dynamics mediated by the superinfection parameter in our model. We describe the various conditions and thresholds for each evolutionary outcome in electronic supplementary material, Expanded Results.The exact evolutionary dynamics depend upon the value of the superinfection parameter, σ, our results are illustratively summarized in σ > 0) only in the first infection stage, we let τ denote the average time a host infected by or with immunity to one pathogen cannot get superinfected, i.e. the average time that a host is not in I1 after infection before return to susceptibility. Since 1/(ν2 + δ) is the average time in I2, ν2/(ν2 + δ) is the probability of surviving I2, and 1/(μ + δ) is the average time in R, it follows that τ = 1/(ν2 + δ) + (ν2/(ν2 + δ))(1/(μ + δ)). Thus, τδ is biologically intuitive and corresponds to the fraction of individuals that die while in I2 or R. If the superinfection parameter is such that σ < (1 − τδ)/k (which forces σ < 1), then the possible evolutionary outcomes mirror almost exactly those without superinfection [a). Furthermore, for certain values of α1,∞/δ, there is either a unique or no interior evolutionarily singular strategy, whereas for other values the existence of additional singular strategies is possible.For different regimes of the superinfection parameter, nfection . Indeed,ν1,∞τ)/k > σ > (1 − τδ)/k, then a new evolutionary phenomenon emerges. For these values of superinfection, there can exist a unique branching point for intermediate values of the fully latent transmission rate times the average host lifespan, α1,∞/δ. This branching point is an evolutionarily singular strategy that is convergence stable [figure 2b and electronic supplementary material, Expanded Results). If the superinfection parameter increases further, so that σ > /k, the possibility of alternative stable states at zero and maximal latency disappears: instead, there is either a branching point, or an ESS at zero latency .If the likelihood of superinfection increases, so that . In this setting, there exists either at least one interior attractor which is an interior ESS and is thus a continuously stable strategy (CSS), or there exists at least one local attractor at zero latency . The CSS is shown to be unique in certain special cases . These results qualitatively mirror those without superinfection, where c2 > b2 guarantees either a unique interior ESS or a global ESS at zero latency.If progression decays faster than transmission, i.e. b2 > c2 (and α1 as a function of ν1 is concave up), it is also useful to consider the evolutionary outcomes for a fixed value of α1,∞/δ as the superinfection parameter σ varies. First, consider α1,∞/δ close to zero (i.e. where there is a unique ESS at zero latency in figure 2a). Then, irrespective of the values of σ, there is a unique ESS at zero latency (σ). Second, consider a value of α1,∞/δ where there is a local ESS at maximal latency (figure 2a) for small σ. As σ increases, this local ESS at maximal latency disappears, and there is either an ESS at zero latency  or a unique branching point . The existence of a branching point significantly complicates the evolutionary dynamics of latency.When transmission decays faster than progression, i.e. 3.2.a, we illustrate the existence of a unique evolutionarily singular strategy that is a branching point. From the pairwise invasibility plot (PIP), it is clear that this singular strategy is an attractor, but allows nearby mutants to invade. Thus, if initial latency is above or below the branching point, mutations intermediate to the initial strategy lead to invasion. As evolution progresses, the resident pathogen continues to approach the singular strategy. However, as the singular strategy is reached, mutants with smaller or larger latencies can invade, giving rise to branching and mutual invasibility. As an example, we schematically illustrate the region of mutual invasibility in figure 3b for two competing types when there exists a branching point.In the previous section, we have found regions of parameter space where a convergence-stable singular strategy is not an ESS, which gives rise to the very interesting behaviour of branching. Furthermore, for those parameter regimes where we have proved that a branching point can exist, it is also unique. In figure 3Since our model assumes immediate replacement of the infecting strain by the superinfectant, the existence of a branching point in our model could be considered counterintuitive. This, despite the fact that a superinfectant can immediately take over a single host, does not prevent mutual invasibility of strains at the population level. In certain ecological models, mutual invasibility implies coexistence (see Chesson  and GeriEvolutionary dynamics in the presence of coexistence). In particular, we have shown that, if there exists any isocline for either coexisting type, then it is a fitness minimum. Thus, any interior evolutionarily singular coalition, if it exists, would be evolutionarily unstable . Furthermore, for the example in After branching, it is complicated to determine the evolutionary dynamics of latency. However, if an endemic equilibrium with two coexisting types exist, then a generalized adaptive dynamics approach applies in this case also (see ), and weThe mutual invasibility of two different types of latencies has interesting analogies with the competitive-exclusion principle ,50, and 3.3.μ, following infection has no effect on the evolutionary dynamics of latency. Here, even with the simplest model of superinfection where the superinfecting pathogen immediately clears the ‘resident’ pathogen, the duration of immunity can have a dramatic effect on the possible evolutionary outcomes of latency.In the model with no superinfection , the durμ can affect the dynamics in our model, consider both extremal values, i.e. lifelong immunity (μ = 0) and no immunity (μ = ∞). If μ = 0, then τ = 1/δ is the average lifespan, so that (1 − τδ)/k = 0. Thus, for any superinfection σ > 0, the resulting evolutionary dynamics are as in figure 2b or c. On the other hand, if μ = ∞, then τ = 1/(ν2 + δ) is the death-adjusted duration of the second stage, so that (1 − τδ)/k = (1/k)(ν2/(ν2 + δ)). Thus, for 0 < σ < (1/k)(ν2/(ν2 + δ)), the evolutionary dynamics will be different if μ = 0 or if μ = ∞. If there is no immunity, then the evolutionary dynamics are almost as in the case with no superinfection, whereas if there is lifelong immunity following infection, then the qualitative evolutionary dynamics have important differences. Notably, a branching point can emerge (figure 2b), or the possibility of alternative stable states can disappear (figure 2c).To understand intuitively why the rate of waning immunity b2 > c2, shown in figure 4a,b. With lifelong immunity, i.e μ = 0, for this example it appears that there is a unique ESS is at μ → ∞, then there is a unique ESS at Next, we numerically examine some possible evolutionary transitions due to host immunity. c2 > b2, then the change in evolutionary outcome due to immunity is more moderate (c). Indeed, suppose that with no loss of immunity there is a unique interior ESS. As the duration of immunity decreases, then the interior ESS shifts to a smaller value of latency, until eventually it reaches zero latency. Thus, for these values of the progression and transmission decay exponents, changes in immunity modulate the evolutionary dynamics of latency through incremental changes in the value of the ESS, which may eventually lead to the replacement of an interior ESS at positive latency by one at zero latency.If the progression decay exponent is greater than the transmission decay exponent, i.e. moderate c. Indeed3.4.λ and those at infinity cannot be distinguished.)In the model without superinfection and under the specific formulations of equations  and 3.23.2 for ta has a unique attractor at infinite latency. With a large enough mutational change of latency to λ*, however, it can be seen from the PIP that a non-monotonic approach to the ESS at infinite latency is possible, i.e. mutants with a smaller latency than the endemic strain—and far enough away from the resident phenotype—can invade. For this setting, the regions of mutual invasibility are illustrated in figure 5d. Indeed, a strategy with large latency can invade a resident with zero latency, and a resident at high latency can be invaded by a mutant with zero latency, even if the unique attractor is at maximal latency. Without superinfection, the PIP is symmetric, and so such mutual invasibility is not possible.Figure 5μ increases, it crosses a unique value for which there is a transition in evolutionary behaviour, and the critical value is presented in figure 5b. Here, there is an evolutionarily singular strategy for which the isocline does not cross the diagonal. This strategy is convergence semi-stable: for initial latency above this singular strategy, mutants with values of latency progressively further away from the singular strategy can invade, whereas for initial latencies below the singular strategy, mutants with values intermediate to the singular strategy can invade. Thus, this singular strategy is approached in evolutionary time only from below. When it is reached, then it is susceptible to invasion by mutants with larger latency. Therefore, a small mutation can lead away from this singular strategy. In this case, transmission decays faster than progression, and therefore this singular strategy is a fitness minimum and is not evolutionarily stable. Indeed, even as the resident approaches the singular strategy from below, it can be seen that types with slightly smaller latencies can successfully invade. This is partially reminiscent of a branching point, but this mutual invasibility is only true for latency values that are near and smaller than the singular strategy. Furthermore, the region of mutual invasibility is greater when compared with the previous case without the interior singular strategy (figure 5e).On the other hand, as c. Again, since b2 > c2, these singular strategies are not ESSs and are fitness minima . Visual examination reveals that one strategy  is convergence stable, whereas the other (with larger latency) is not. Therefore, the convergence-stable strategy that is not an ESS is a branching point, and the other singular strategy is a repeller. For initial values of latency above the repeller, the evolutionary endpoint is at infinite latency. With such initial latencies and small mutations, the branching point is not approached in evolutionary time. This contrasts with the evolutionary dynamics with a unique branching point and highlights the important evolutionary implications of the existence of this repeller. For other initial values, the branching point is approached, but eventually nearby mutants can invade, which leads to mutual invasibility. The region of mutual invasibility takes a different shape with these two interior singular strategies (figure 5f), which illustrates the complex behaviour that results from these two fixed points. The differences in figure 5a–c are due to the small changes in the duration of immunity following infection. Thus, host immune responses can finely modulate more complex evolutionary phenomena that only appear in the presence of superinfection.This unique singular strategy then branches into two interior strategies, depicted in figure 54.et al. [We have extended the framework developed by Saad-Roy et al.  to incluσ, the transmission decay exponent, b2, and the fully latent transmission rate times the average lifespan, α1,∞/δ. This is particularly the case when transmission decays faster than progression in the first stage. Indeed, we proved that in this regime, then any evolutionarily singular strategy is not an ESS, and we further showed that there can exist an ESS at zero latency, a singular strategy (possibly unique) that is a repeller and so leads to bistability at zero and maximal latency. We also showed that there can exist a unique convergence-stable singular strategy that is not an ESS, and is therefore a branching point. If progression decays faster than transmission, then any singular strategy is an ESS, and we showed that there can either be an ESS at zero latency, or an interior CSS, leading to a sub-symptomatic first infectious stage. Through numerical simulations, we have also illustrated that two interior evolutionarily singular strategies can exist with superinfection, posing a stark contrast to the case without superinfection. It is also worth noting that our ‘latent’ stage is distinct from a short stage after infection before a host is infectious and without symptoms, though we explore a generalization of this scenario in electronic supplementary material, The addition of infection stages. Furthermore, in a situation where hosts with no symptoms cannot transmit, i.e. α1,∞ = 0, then λ = ∞ is never an ESS. Intuitively, a completely presymptomatic stage during which pathogens are not transmissive does not evolutionarily emerge, nor does the branching point (irrespective of the strength of superinfection). A symptomless host lacking the ability to transmit could be due to a variety of host or pathogen constraints, and our model illustrates the evolutionary implications of such constraints.Using adaptive dynamics, we have shown that the evolutionary outcomes of latency depend upon the values of the superinfection parameter, More specifically, our underlying epidemiological model captures a continuum of immune durations. Most interestingly, we have shown that superinfection can enable the duration of host immunity to influence critically the evolutionary outcomes of latency. For example, superinfection can lead to different evolutionary possibilities if immunity is lifelong or if hosts have no immunity following recovery. By contrast, without superinfection, the SIIRS, SIIR and SIIS frameworks all give rise to identical evolutionary dynamics. This notable distinction is powerful: under superinfection, for the same shapes of trade-offs, the possible outcomes for latency evolution can be set by the duration of host immunity. Furthermore, significant qualitative and quantitative changes of evolutionary dynamics can cascade from a small change in the duration of immunity. For certain viral diseases in humans, such as influenza or coronaviruses, it is thus imperative to determine the propensity for superinfection by closely related strains, in addition to the shape of the underlying trade-off between transmission and progression. Once these are quantified, our model could be appropriately parametrized while also taking into account the duration of immunity following infection, and the predictions from our model tested. If a branching point is found to exist, our model would provide a potential mechanism to explain the coexistence of viral lineages.et al. [Other studies on superinfection have focused on a different life-history trait (virulence) rather than latency, with different underlying epidemiological assumptions. For example, Boldin & Diekmann , Alizon et al.  assumed et al.  assumed The superinfection parameter as a function of latency, we show that relaxing the assumption of a constant superinfection parameter can lead to alternative evolutionary behaviour. In particular, when progression decays faster than transmission (i.e. c2 > b2), it is now possible that an interior evolutionarily singular strategy may not be an ESS.With regard to superinfection, we have so far assumed that the superinfection parameter is constant across the latency spectrum, which is the most ‘minimal’ model of strain replacement. In an SI model with disease-induced death, in order for branching to emerge, the superinfection parameter as a function of both resident and mutant strategies must satisfy certain properties (given in Alizon ). FurtheOverall, we find that including this simplified approach to superinfection for hosts early in the course of infection , can lead to numerous qualitative differences in evolutionary dynamics. In particular, a larger superinfection parameter decreases the parameter space for which there is an ESS at maximal latency . However, a larger superinfection parameter also implies that a unique branching point can exist. Furthermore, it appears  that a coalition of zero and maximal latency can be evolutionarily stable. While this coalition outcome does not represent a local ESS at maximal latency, it nevertheless suggests that it may be possible for a fully latent pathogen to emerge evolutionarily even when there is high superinfection. In addition, the inclusion of superinfection in our modelling framework can also lead to multiple interior evolutionarily singular strategies.Thus, from a public-health perspective, superinfection can have dramatic and counterintuitive evolutionary effects on latency. In order to gain pathogen-specific insight into the evolution of latency, it is therefore necessary to characterize the relative propensity of superinfection relative to susceptible infection. Then, initiatives such as the isolation of infectious individuals can be regarded with an evolutionary lens. Indeed, knowledge of the evolutionary outcomes could clarify if it is sufficient to isolate all infectious individuals together (and hence possibly enable superinfection), or if care should be taken to properly isolate individual cases (to reduce the probability of superinfection). The economic costs of these alternative measures can differ substantially, and more costly initiatives would probably only be enacted if there existed clear benefits. Thus, these questions are of significant public health interest, and they have implications for the current COVID-19 pandemic.μ = 0 or μ → ∞ (which guarantee a stable endemic equilibrium if The addition of infection stages). For example, numerous diseases exhibit a short period after infection before transmission starts.Under the assumption of lifelong immunity, the qualitative evolutionary dynamics of latency in the first infection stage without superinfection does not change if an additional infection stage is included in the multi-stage compartmental model . Assuminher case ,52), anaν2 denotes disease-induced death instead of recovery, the evolutionary dynamics of latency were found to be equivalent [Based on our findings on branching in our simple two-stage model with superinfection, we conjecture that even more complex evolutionary behaviour could arise if we consider more stages with different superinfection parameters. Under this framework, there may be a scenario that leads to serial branching. Such a result would be particularly appealing given that certain pathogens exhibit a range of latency in the first stage, and would indicate that a general theory could explain the emergence of all these divergent life-history strategies. Lastly, in the case without superinfection and with a similar model where uivalent , and simIn a different context, our result on branching could also be applied to pathogen speciation. Our work illustrates that superinfection mediates scenarios where, for identical parameters, pathogens with two different strategies can successfully invade each other. Furthermore, we presented a numerical example with a coexistence equilibrium and a coalition of two strategies that is evolutionarily stable with respect to mutations. If additional branching was observed in a more complicated model as we conjecture above, then this could further our understanding of the coexistence of pathogens with different strategies but similar underlying biology.While our model assumes the simplification that there is no within-host coexistence of pathogen strains (as occurs for HIV ), our re4.1.To model superinfection, we have made two key assumptions. First, we have assumed that the superinfecting pathogen immediately replaces the one being superinfected. It would be valuable to investigate the evolutionary dynamics of latency if longer co-infection can occur. Second, motivated by underlying biological processes, we have assumed that superinfection only occurs in the initial stage of infection. However, it is possible that superinfection in the symptomatic stage could occur with a different propensity compared to that in the first infection stage, and this would also be a logical direction to explore. Investigating the addition of further infection stages with different propensities of superinfection would also be an immediate extension. Additionally, while we have explored a situation in which the superinfection parameter decays as a function of latency, it would be worthwhile to more generally characterize the evolutionary behaviour in these cases.et al. [In our model, we have focused on pathogen properties and evolutionary dynamics, and ignored host characteristics, such as heterogeneity and their (longer) evolutionary timescales. However, the inclusion of superinfection leads to the modulation of latency evolutionary outcomes by host immunity, which suggests that specific host characteristics could affect latency evolution. One potential approach would be to perform similar latency evolutionary analyses with superinfection within the epidemiological model framework presented by Morris et al.   with a et al. .Furthermore, while we have proved that a unique branching point can exist in our model, we have not analytically proved the long-term epidemiological and evolutionary behaviour after the system approaches a branching point. Most importantly, it would be valuable to show that mutual invasibility implies coexistence for our model. Furthermore, in these regions with mutual invasibility, it would be useful to show that there exists a unique coexistence equilibrium that is stable, which would then facilitate analytical characterizations of evolutionary dynamics after branching.et al. [Our work could also be taken in a myriad of other more general directions. For example, Saad-Roy et al.  numericaIt would also be useful to explicitly incorporate vaccination in this epidemiological-evolutionary latency modelling framework. Indeed, ’leaky vaccines’ (those that do not fully block transmission) or population vaccination strategies can have unexpected evolutionary and epidemiological outcomes ,59, and Lastly, while all of these prospective directions are at the population level, it would also be interesting to characterize the within-host dynamics of pathogen replication and competition. In the framework with superinfection, this would be particularly informative, and could inform the shapes of the trade-offs in addition to possibly determining the value of the superinfection parameter.


We aimed to evaluate the evidence reported to underpin exercise dose in randomised controlled trials (RCTs) using strengthening exercise in RA. We searched six different databases between 1 January 2000 and 3 April 2019. We included RCTs, where a main component of the intervention and/or control used strengthening exercise. Evidence sources cited to underpin dose were judged for their quality, consistency and applicability. Thirty-two RCTs were reviewed. Four (12.5%) piloted the intervention without using dose-escalation designs to determine optimal dose-response. Twenty (62.5%) reported no evidence underpinning dose. Where reported, quality, consistency and applicability of the underpinning evidence was a cause for methodological concern. The majority of RCTs did not report the evidence underpinning dose. When reported, the evidence was often not applicable to the clinical population. Frequently, the dose used differed to the dose reported/recommended by the underpinning evidence. Our findings illustrate exercise dose may not be optimised for use with clinical populations prior to evaluation by RCT. The majority of exercise trials in RA don’t report evidence underpinning dose of strengthening exercise.Exercise trials in RA seldom pilot their interventions to determine dose-response.Evidence used by exercise trials in RA to underpin dose is often low in quality.In the United Kingdom (UK), exercise is recommended by clinical guidelines alongside pharmaceutical interventions for the management of RA . One typThe randomised controlled trial (RCT) is a robust approach for evaluating the effectiveness of clinical interventions . A critiIn the absence of early phase clinical trials, researchers may rely on expert opinion, consensus or draw from the available evidence base  to determine what dose to prescribe. Examples may include the 2018 EULAR recommendations for physical activity in people with inflammatory arthritis and osteoarthritis or the ACSM’s exercise management for persons with chronic diseases , 23. HowDetermine what proportion of published RCTs evaluating strength-based exercise interventions in RA report using phase-I/II trials for setting dose parameters.Determine what type and level of evidence is used to underpin dose parameters.Explore the quality, consistency and applicability of the evidence used to underpin dose parameters.Narratively explore if a relationship exists between risk of bias for RCTs evaluating strength-based interventions in RA and the level of evidence for underpinning prescription parameters.The review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. We developed the protocol and pre-registered it with the International Prospective Register of Systematic Reviews (PROSPERO): PROSPERO 2018 CRD42018090963. The full protocol has been published .Rheumatology online).We systematically searched the following databases: (1) Allied and Complimentary Medicine Database (AMED) via OVID; (2) Cochrane Central Register of Controlled Trials (CENTRAL); (3) Cumulative Index to Nursing and Allied Health Literature (CINAHL) via EBSCOhost; (4) Excerpta Medica Database (EMBASE) via OVID; (5) MEDLINE via OVID; and (6) Physiotherapy Evidence Database (PEDro). Search strategies for each of the databases were developed iteratively and included relevant controlled vocabulary terms (e.g. MeSH and EMTREE headings) and free-text terms searched in the title, abstract or keyword fields for variants of ‘rheumatoid arthritis’, ‘exercise’ and ‘stength’ or ‘resistence training’. Where available, validated RCT search filters were used including the Cochrane Highly Sensitive Search Strategy for identifying randomized trials in MEDLINE (sensitivity-maximizing version (2008 revision) Ovid format), the McMaster EMBASE RCT search filter  and the SIGN Search Filter for identifying randomized trials in CINAHL (for EBSCO). We aimed to examine the state of contemporary practice in prescribing the dose of strengthening exercise in clinical trials. Therefore, we limited our search to identify RCTs published after 1 January 2000 to coincide with the year the MRC published their original framework for developing and evaluating randomized controlled trials for complex interventions used to improve health . The iniWe included all RCTs that evaluated exercise interventions where a main component (i.e. key feature) of the intervention and/or control included land-based strengthening exercise.We included published RCTs involving adults  with a diagnosis of RA. We purposefully chose not to limit the eligibility criteria for diagnosis using one of the common classification criterias (e.g. ARA 1987 revised criteria for the classification of RA or 2010 ACR-EULAR Classification Criteria for RA) in order to include as many RCTs as possible , 27. We Strengthening exercise could involve the participant using equipment (e.g. free weights/machines), or their own bodyweight to provide resistance against gravity (e.g. sit-to-stand exercise). The intervention could be unsupervised (e.g. home-based), supervised (e.g. by a therapist) or both and carried out individually or in a group. The strength-based intervention could be multifactorial (e.g. used in conjunction with cointerventions like education), or multicomponent (e.g. used with other forms of exercise like aerobic or flexibility exercise).Two authors  independently screened the titles and abstracts of records obtained through our database search. The title and abstract were examined and those meeting the above eligibility criteria were retrieved for further evaluation. Where ambiguity existed, resolution was achieved through consensus. If this was not possible, resolution was achieved using a third reviewer (N.E.O.).Two authors  extracted data from every included RCT. To do this, we developed and piloted an Excel data extraction form using two RCTs investigating knee osteoarthritis interventions , 29. Then-of-1 trials, (2) = Randomized trial or observational study with dramatic effect, (3) = Non-randomized controlled cohort/follow-up study, (4) = Case-series, case-control studies, or historically controlled studies and (5) = Mechanism-based reasoning.For every underpinning evidence source identified, we used the Oxford Centre for Evidence Based Medicine (OCEBM) – levels of evidence to grade its quality, using the framework’s question ‘Does this treatment help?’ . We chosGrading using the above framework was relatively straightforward. However, when the evidence source cited to underpin dose was a pilot study, literature review, clinical guideline or book, to be more accurate with our grading, we had to explore the evidence used by these specific sources. Pilot studies act as the pre-cursor for the RCT, therefore to grade quality, we identified the evidence (if any) reported by the pilot study to underpin dose. For literature reviews, clinical guidelines and books, we identified (where possible) the references used by these evidence sources that were most relevant to the dose parameters reported in the RCT. These types of evidence source commonly draw on large bodies of published information to make recommendations. An example of this type of evidence source used in the exercise are the American College of Sports Medicine (ACSM) position stands . TherefoWe judged consistency by comparing the dose parameters  reported by the RCT to the dose parameters reported in underpinning evidence. When the dose was identical, or kept within the range reported by the underpinning evidence, we judged the RCT had been ‘consistent’ in using the same dose. When the RCT used a different dose to that reported, we judged the RCT had been ‘inconsistent’. Where the RCT and/or underpinning evidence insufficiently described the dose used, we could not make a comparison and judged it to be ‘unclear’. We approached pilot studies differently, assuming the characteristics of dose would be broadly similar. Therefore, any differences in dose were judged to be ‘inconsistent’.We judged applicability by looking for areas of homogeneity/heterogeneity across three areas: (1) Whether the underpinning evidence source was applicable to RA clinical population; (2) Whether a similar gender mix was used; and (3) Whether the mean age was similar (±10 years). We judged these areas as ‘applicable’ or ‘not applicable’. In cases where the underpinning evidence source was not a clinical trial  and there was no definitive population to assess, we judged gender and age to be ‘not applicable’.Two reviewers  assessed risk of bias for each of the RCT sources using the six key domains of the Cochrane risk of bias tool : (1) Adeet al. 2018 [We summarize the search and screening process in the PRISMA study flow diagram . A totalal. 2018 . We inclRheumatology online).We assessed eight RCTs (25%) to be at overall low RoB , 61, 68,Rheumatology online). These included clinical trials, literature reviews, clinical guidelines, clinical opinion, books and a mobile phone application.Twenty RCTs (62.5%) did not cite evidence to underpin prescribed dose of strengthening exercise , 66–70. Rheumatology online). Key dose parameters were also incomplete (Thirty-one RCTs (97%) provided incomplete descriptions of their interventions  reported using the same dose in both the pilot and main trial. We noted inconsistencies in the dose used for Neuberger et al. (2007) and Lemmey et al. (2009). Neuberger and its pilot study reported insufficient information to compare the majority of dose parameters. We were only able to judge three parameters . The method used for progression was inconsistent and we were unable to locate justification for it being modified. Lemmey reported progressing dose more gradually to reduce muscle soreness when compared with its pilot study. However, we found no evidence (e.g. adverse events) that participants experienced problems with muscle soreness during the pilot study. Therefore, we are unclear why dose was modified if no problems were experienced. We could not compare dose in the fourth RCT  owing to the pilot study being unpublished.Four RCTs (12.5%) , 54, 59 et al. (1997) reported their intervention was developed by two physical therapists, an aerobics instructor hired to teach the class and the principal investigator, but did not cite any evidence to underpin dose. Marcora et al. (2005) cited the 2002 ACSM position stand: progression models in resistance training for healthy adults [et al. (2015) cited Hurley et al. (2007) [et al. (2015) was only described briefly [et al. (2006) which also involved the rheumatoid hand and was therefore relevant. The content of the exercise programme used by O’Brien was defined by expert opinion (an unpublished survey of 60 senior hand therapists), one of the lowest levels of evidence [We also explored what evidence the pilot studies cited to underpin dose. Neuberger y adults  to under. (2007) , an RCT- briefly , 74 and evidence .Across the thirty-two trials  we foundet al. (2009) cited the ACSM position stand [We rated the quality of the twenty-seven underpinning evidence sources using the OCEBM level of evidence framework . We judgon stand  to underon stand  and 3–5 on stand . Sometimon stand . Two  of the underpinning evidence . RelatinThis is the first systematic review that we are aware of to explore in detail the underpinning evidence used by healthcare researchers to justify the prescribed dose of strengthening exercise used in clinical trials of RA. We identified that the majority of clinical trials involving exercise in RA do not report the use of evidence to underpin exercise dose. Only four trials formally piloted the intervention and its dose prior to evaluation. None of the pilot studies used dose-escalation designs to optimise dose-response, something which is more commonly seen in the evaluation of new drugs. In the absence of formal piloting, the underpinning evidence cited to justify dose parameters (when used) varied in quality and applicability and sometimes did not support the reported dose parameters.The lack of formal piloting highlighted by this review suggests that current practice in the field of RCTs using exercise-based interventions in RA does not align with the MRC framework for the development and evaluation of complex interventions. Potential reasons for not piloting may include lack of time, research culture, funding, conflicting priorities, policy focus etc, though in some cases may simply reflect a lack of reporting . For theIn the absence of piloting, the judicious use of evidence to underpin all aspects of dose development should be expected , yet onlThis review offers new insight into clinical trials using exercise interventions. Our comprehensive search strategy without language limitations and methodological approach allowed us to explore in detail the evidence used to underpin dose of strengthening exercise. We acknowledge our review does have some limitations. Firstly, without a complete published description of the intervention, incomplete reporting by both RCTs and the underpinning evidence limited the amount of information available to conduct the review, though this in itself highlights a challenge for this field. Secondly, owing to the number of clinical trials involving strengthening exercise in musculoskeletal conditions, we chose only to include people living with RA. It is possible that the underpinning evidence for exercise dose in other conditions may be more robust. However, given the broad issues identified in the current review, we suggest this is unlikely and may not be limited to strengthening exercise in RA . ThirdlyIn the context of patient-centred care, the prescription of an effective exercise intervention should be tailored to meet the needs of the individual ; for strOur systematic review identified that the majority of included RCTs did not report pilot studies or evidence to underpin exercise dose. When evidence is cited, the different types used vary in quality, consistency and applicability. Our findings question whether dose is optimised for use with the clinical populations, which is a cause for methodological concern. There are clear scientific imperatives to improve practice in this area of clinical research, including to maximise the potential for exercise interventions to deliver benefit. Addressing these weaknesses may contribute to better quality research being conducted and reducing research waste in exercise interventions.keaa150_supplementary_dataClick here for additional data file.


In the hyperbolic community, discontinuous Galerkin (DG) approaches are mainly applied when finite element methods are considered. As the name suggested, the DG framework allows a discontinuity at the element interfaces, which seems for many researchers a favorable property in case of hyperbolic balance laws. On the contrary, continuous Galerkin methods appear to be unsuitable for hyperbolic problems and there exists still the perception that continuous Galerkin methods are notoriously unstable. To remedy this issue, stabilization terms are usually added and various formulations can be found in the literature. However, this perception is not true and the stabilization terms are unnecessary, in general. In this paper, we deal with this problem, but present a different approach. We use the boundary conditions to stabilize the scheme following a procedure that are frequently used in the finite difference community. Here, the main idea is to impose the boundary conditions weakly and specific boundary operators are constructed such that they guarantee stability. This approach has already been used in the discontinuous Galerkin framework, but here we apply it with a continuous Galerkin scheme. No internal dissipation is needed even if unstructured grids are used. Further, we point out that we do not need exact integration, it suffices if the quadrature rule and the norm in the differential operator are the same, such that the summation-by-parts property is fulfilled meaning that a discrete Gauss Theorem is valid. This contradicts the perception in the hyperbolic community that stability issues for pure Galerkin scheme exist. In numerical simulations, we verify our theoretical analysis. In recent years, significant efforts have been made to construct and develop high-order methods for hyperbolic balance laws, and most of the methods are either based on finite difference (FD) or finite element (FE) approaches. In the FE framework, one favorable, if not the most favorable scheme, seems to be the discontinuous Galerkin (DG) method introduced by Reed and Hill  because One may only speculate where this erroneous perception come from? In our opinion, one major reason could be that if one considers a pure Galerkin method using a linear Lagrange polynomial basis of order one, it can be shown that the method is equivalent to the 3-point central difference scheme. This scheme is not von Neumann stable  when perIn this paper, we focus on the stability property of a pure Galerkin scheme, but follow a different approach. Our preliminary idea/thought is: If one considers the DG method with one element, the method is stable. There is nothing that says that the approximation space must be a broken polynomial space, the only thing that is needed is that the trial and test function must have some kind of regularity within the elements, so that the divergence theorem (or SBP techniques) can be applied. Continuity at the boundaries and regularity inside the elements due to the polynomial space are enough. No internal artificial dissipation is required and no special conditions on the grid structure, for instance cartesian grids, have to be assumed. Thus, for example unstructured triangular meshes can be applied. Hence, one can see a CG method as a DG one, with only one element (the union of the simplices) with an approximation space made of polynomials with continuity requirement between the simplices. Hence, what is the difference between these two approaches? The answer to this question points to the procedure at the boundary. In the stability proofs, the use of SATs is essential. In  diagonalK the generic element of the mesh and by h the characteristic mesh size. Then, the degrees of freedom (DoFs) K: we have a set of linear forms acting on the set k such that the linear mapping K. The set U will be approximated by some element from the space K or Bézier polynomials.In this section, we shortly introduce the pure continuous Galerkin scheme (CG) as it is also known in the literature , 16, 26.To start the discretisation, we apply a Galerkin approach and multiply with a test function ain with  a systemU, but may depend on the spatial coordinate. In all the numerical experiences, we will make the spatial dependency simple enough , so that it will always be possible to find a standard quadrature formula and obtain accurate approximations for the integrals. Note, if the quadrature rule is accurate enough,  is nowadays standard in the FD community and has been developed there. Together with summation-by-parts (SBP) operators it provides a powerful tool for proofs of semidiscrete  An operator u and similarly for uNow, a semi-discretisation of  is givensolution . Transla like in , the bouK(t) is bounded for any finite t and independent from b and the mesh.The scheme  is calleb, for details see [The Definition ails see .As established in , we can Let Multiplying  with \doain from \documentThis shows that the boundary operator ation of . Next, wdiscontinuous Galerkin spectral element method (DGSEM). Here, we consider nodal continuous Galerkin methods and focus on stability conditions in this context. As we described already in Sect. Instead of working with SBP-FD framework we consider now a Galerkin approach for the approximation of . In 5, , 5, 6, iequation  with tesribed in . Let us uch that  is satisIf the Galerkin method  is appligiven by  and \docThe weak formulation of the problem reads:ximation  on the rtization :\documenIn the derivation above, we restricted ourselves to one-dimensional problems using Lagrange interpolations. Nevertheless, this shows that a continuous Galerkin method is stable if the boundary condition is enforced by a proper penalty term. For the general FE semi-discretization of , the proApply the general FE semidiscretisation  togethert}M__ of  be symmeWe use the energy approach and multiply our discretization with However, no internal stabilization terms are necessary when  The weak formulation of the boundary condition is not done for the first time to analyze stability properties in continuous Galerkin methods. As already mentioned in the introduction, in –23 the aFurther, in  the auths method  for ellientclass1pt{minimas method  can be fs method  which isFinally, we want to point out again that the purpose of this paper is to demonstrate that no further internal dissipation is needed if the boundary conditions are implemented correctly. In addition, our analysis holds also if we apply unstructured grids as demonstrated in the numerics section below.As described before, a proper implementation of the boundary condition is essential for stability. Here, we give a recipe for how these SAT boundary operators can be chosen to get a stable CG scheme for different types of problems. First, we consider a scalar equation in 2D and transfer the eigenvalue analysis for the spatial operator from the continuous to the discrete setting. Then, we extend our investigation to two dimensional systems. Using again the continuous setting, we develop estimates for We derive conditions on the boundary operators and perform an eigenvalue analysis to get an energy estimate in the continuous setting. Next, the results are transformed to the discrete framework to guarantee stability of the discrete scheme.f describes the initial condition, B represents the boundary operator and the function g the boundary data. Without loss of generality, it is enough to consider homogeneous boundary conditions and we consider the spatial operatorConsider the initial boundary value problemecommend , 36 for D and the boundary condition (B.C), i.e. Du and Bu weakly. Here, the projection operator We have to approximate the spatial operator ondition  are the (Periodic Boundary Conditions) As already described in the Introduction q is the number of boundary conditions to satisfy. We assume that A, B are constant and that the system . However, the results are similar after applying the SAT procedure, we obtain only negative or zero eigenvalues.We see from Tables We also mention that for higher degrees and more DoFs, we may strengthen the SAT terms to guarantee that the eigenvalues are negative and /or forced to zero. All of our investigations are in accordance with the analysis done in Sect. Finally, we did a couple of additional simulations changing both, the domain This is in contradiction of a common belief in the hyperbolic research community about continuous Galerkin schemes.But what are the reasons for this belief? In our opinion, one of the major issues is that the chosen quadrature rule in the numerical integration differs from the the one used in the differential operators and without artificial stabilization terms the continuous Galerkin scheme collapses, and the corresponding To support our statement, we provide the following example. We consider the same problem as before, but in the Galerkin scheme we lower the accuracy of our quadrature rule to calculate the mass matrix and the conditions at the boundary procedure. Before, we used always a quadrature rule which is accurate up to sixth order. Then, we lower the quadrature rule for the surface integral to five, the rest remain the same. Please be aware that in the Galerkin approach, we apply integration by parts before formulating the variation formulation. We decrease the CFL number to 0.01 for stability reasons. However, as it is shown in Fig. entclass1pt{minimaAdditional time steps will lead to a complete crash of the test. At 400 steps the maximum value is 74.45 and the minimum is at r series  to demonr series  and applr series , 44 can In the next test we consider an advection problem with variable coefficients. The speed vector has componentsWe apply an unstructured triangular mesh with 932 triangles. In the second calculation 5382 triangles are used. The time integration is again done via a SSPRK54 scheme with CFL=0.2. A pure continuous Galerkin scheme with Bernstein polynomials is used for the space discretization. Due to the variable coefficient problem, we apply the splitting technique as described in , 31 and We compute this problem up to ten rotations for different orders. We observe that all of our calculation remain stable both using Lagrange or Bernstein polynomials as can be seen for example in Fig. Finally, we analyze the error behavior and calculate the order. We use again the SSPRK schemes of the same order Fig. .Fig. 6\dWe recognize a slight decrease of the order similar to the observation made in  which waA following the ideas of Sect. As a first example for systems with non-homogeneous boundary condition, we consider the linear wave equationribed in , the progiven in  and the ory Fig. .Fig. 7ReUnder the same terms and conditions, we ran the test again now with a random mesh. Figure In our last simulation, we consider the steady R13 sub-model for heat conduction investigated in , 47. It P, we can calculate We sete system  can be rrsion of \documente system  is symmeP, i.e. for eigenvectors Since the system is symmetrizable, the eigenvectors are orthogonal for the quadratic form associated to x-axis and the outward unit normal on G asU instead of V in the implementation, we have to multiply The physical boundary condition follows from Maxwell’s kinetic accommodation model. We haveAnother way to determine We have explained how we estimate the boundary operator in the above Eq. . In the In the second test, we increase the number of elements in the mesh. Now, we are using 5824 elements and also Bernstein polynomials of second order. The mesh and the result are presented in Fig. In this paper, we have demonstrated that a pure continuous Galerkin scheme is stable only through the applied boundary conditions. No further stabilizations terms are needed. This contradicts the erroneous perception in the hyperbolic community about pure continuous Galerkin schemes to be unstable without additional stabilizations terms. In our approach, the application of the SAT technique is essential where we impose the boundary conditions weakly. Using this approach, we derive a suitable boundary operator from the continuous setting to guarantee that the discrete energy inequality is always fulfilled. We present a recipe on how these operators can be constructed, in detail, for scalar two-dimensional problems and two-dimensional systems. In numerical experiments, we verify our theoretical analysis. Furthermore, in one test, we demonstrate the importance of the used quadrature rule. The chosen quadrature rule in the numerical integration has to be the same as in the differential operators such that the SBP property of our Galerkin scheme is valued. If not, the Galerkin scheme suffers from stability issues. If stability can be reached only by enforcing the proper dissipative boundary conditions, there is no free meal: this procedure is very sensitive to any numerical error, like roundoff error or quadrature error. We think and hope that through our results the common opinion about continuous Galerkin and its application in CFD problems changes, modulo the restriction we have already described. This result is also interesting from a theoretical point of view, and emphasizes the positive role that the boundary conditions may have. In the companion paper , we cons


Intergenerational programs facilitate mutually beneficial interactions between youth and older adults, achieving an array of outcomes. With few exceptions, implementation factors rarely figure into outcome analyses, though researchers frequently gather data on factors influencing outcomes. The resulting practice-evidence gap may deter wide-spread adoption of intergenerational programming. We conducted a scoping review of 35 peer-reviewed articles (2000-2019) to map key concepts and evidence sources of empirically-supported practices impacting intergenerational program outcomes. A scoping review is appropriate when an area is complex, like intergenerational programs that incorporate diverse participants, content, and goals. Primarily qualitative studies involved programs equally likely to involve young, school-age, or post-secondary age youth and independent or frail older adults. Half had sample sizes under 50, frequently measuring both age groups. Implementation practices included co-learning and sharing personal stories. Program content  and greater exposure amplified outcomes. Rigorous implementation research is needed to advance evidence-based intergenerational practice.


N = 48), divided into an experimental group with virtual bystanders and a control group without them. Subjects were instructed to perform a rescue procedure in a virtual reality headset. The performance of participants was logged and they completed questionnaires regarding sense of presence in the virtual environment, perceived realism of the environment and perceived co-presence of virtual agents. The obtained results confirmed the role of social realism as a moderator of the occurrence of social facilitation in the presence of computer-generated agents. At the same time, the main effect of facilitation was not confirmed. These results support predictions that the subjective feeling of being in a realistic company of others may be more important in evoking social facilitation than objective facts. Furthermore, the results contribute to the debate regarding the mechanism of social facilitation, suggesting that simple augmentation of the environment with social distractors is not always enough, thus questioning the attentional explanation of the effect. Taken together, our results extend previous findings on social facilitation and open up new possibilities for designing effective virtual environments.Social facilitation has been researched for decades, but in the face of the development of virtual reality technology, new questions arise regarding the possibility of its occurrence in this environment —in the presence of computer-generated agents. Past research provided inconclusive answers: several experiments confirmed this possibility, but several others disagreed. On the other hand, previous studies have shown the important role of VR characteristics, such as realism or co-presence, in evoking other psychological phenomena. However, no study has investigated the interplay between the presence of computer-generated agents and perceived social realism in evoking social facilitation in virtual reality. To this end, the present randomized control study was conducted. The sample consisted of professional firefighters ( The influence of other people on individuals performing a task is a common problem in real life. For example, bystanders are often present at various accident sites, possibly influencing performance of the rescuers. It is important to try to understand this influence and studying it in terms of the social facilitation effect appears to be a promising direction. Moreover, if such influence can be replicated in a virtual environment, rescuers (or other people exposed to the influence of bystanders during their work) could be trained in conditions similar to those which are present in real life. In the present paper, results of a study on social facilitation in virtual reality, specifically—in a rescue context, will be described.mere presence vs. audience to trigger the social facilitation effect. According to early definition, the sufficient condition of social facilitation occurrence is the presence of others, even if the actor is not an object of their interest  technologies, researchers have begun to explore the impact of computer-generated agents in virtual environments (VEs) on users in terms of the social facilitation effect. Several studies examining this phenomenon in VR have been published, but according to the recent review their results are not consistent  and social facilitation, we conducted a study in which for the first time to our knowledge the level of these characteristics was controlled. It was done in order to determine if they moderate the occurrence of the social facilitation effect evoked by computer-generated agents in VR. The presented study was preceded by an exploratory one, in which we found an interactive influence of spectators' presence and realism on subjectively assessed performance. To capture the social facilitation effect in terms of objective performance, we conducted the study described herein. Since the task we used was well-known by the participants , we expected the social facilitation (not inhibition) effect. We hypothesized that co-presence (Hypothesis 1), sense of presence (Hypothesis 2), and realism (Hypothesis 3) would moderate the relationship between audience presence and performance: high level of co-presence, sense of presence, and realism separately would be a condition of occurrence of social facilitation, while low level would not.Participants were recruited at the College of the State Fire Service and firefighting units in Cracow (Poland); all of them had undergone at least one year of training and had participated in real-life rescue operations. This research was accepted by the Ethical Committee at Jagiellonian University Institute of Applied Psychology. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The participants received a T-shirt after participating in the study. There were no defined exclusion criteria.Mage = 22.52, SDage = 4.55) participated in the described part of the studyIn total, 48 men (t(46) = 1.08, p = 0.284] between conditions. None of participants reported problems with perception of VR, and all of them had previously learned to control the simulator .The participants were randomly assigned to one of the conditions . There was no age difference [Firstly, participants were briefly interviewed and equipped with apparatus for measuring physiological variables https://www.youtube.com/watch?v=Bn_E4wX1RPE&feature=emb_logo.Then, the VR simulation took place. Participants wore a HTC Vive head-mounted display (HMD) with hand-held controllers and headphones. The HMD was connected to a PC with a 3.40 GHz Intel Core i7 processor, 16 GB of RAM and a NVIDIA GeForce GTX 1080 graphics card. The simulation was developed with use of the Unity engine and depicted a collision between a car and a group of six pedestrians on an intersection in a small town see . The posThe experimental condition contained an additional group of three bystanders located next to each victim . Some of them were stimuli in other experimental conditions and some of them were masking items.The Polish version of The Co-Presence and Social Presence in Virtual Environments Scale , the single action was considered an “error.” We counted all actions taken in the wrong order (“errors”). No feedback on the performance was given during the session. An erroneous action could not be corrected, but further actions were calculated according to the rule presented above—it was feasible to avoid further mistakes simply by performing subsequent actions in the correct order resulting from previous decisions.Moreover, it was possible to count the total sum of taken actions, regardless of their correctness. Therefore, such index was calculated in order to test the possible impact of audience presence on activity.Participants completed the Polish versions of several other questionnaires at the end of the study: Self-Assessment Manikin  is used  on the relationship between independent and dependent variables. Moderation analysis is used to answer the question which conditions have to be met for an effect to occur , three main effects are calculated: the separate influences of the predictor and moderator and the interaction of these variables  = 1.78, p = 0.08, d = 0.53).To check the possibility that audience presence affected participants' activity (the number of actions), we compared both conditions in such terms. We found that the difference in number of actions in both conditions was not statistically significant and slightly above the “medium” threshold in terms of effect size.  = 0.320, p = 0.625, given equivalence bounds of −0.44 and 0.44 and an alpha of 0.05. Based on both the equivalence test and the null-hypothesis test, we may conclude that the observed effect is statistically not different from zero and statistically not equivalent to zero.Because the Mcontrol = 9.73, SDcontrol = 3.71, Maudience = 8.27, SDaudience = 3.27, t(42) = 1.38, p = 0.175, d = 0.42). Thus, we did not observe the main effect of social facilitation, it is possible the effect was to small to met conventional criterion of alpha 0.05 with the sample size we used.In order to test the main effect of audience presence on performance, we separately compared both conditions in terms of errors made. We found main effect of bystanders presence on performance to be statistically not significant and small in terms of effect size . Calculated simple main effects indicated that only in the case of high assessment of co-presence did the audience cause social facilitation and the effect was of moderate strength . For co-presence assessed as low, the relationship was insignificant and the effect size was very small . This dependency is shown in According to our first hypothesis, we analyzed the interactional influence between audience presence and subjectively assessed co-presence on performance. We found a statistically significant interaction  to be statistically significant moderators .According to our second hypothesis, we analyzed the interactional influence between audience existence in the scene and subjectively assessed sense of presence on performance. The analysis ruled out the role of this variable as a moderator, due to the statistical insignificance of the results . Calculated simple main effects indicated that high level of realism resulted in statistically significant, positive relationship between virtual agents' presence and subjects' performance—social facilitation, with a moderately strong effect size . For low perceived realism, the relationship was insignificant and the effect size was very small . This dependency is shown in According to our third hypothesis, we analyzed the interactional influence between audience existence in the scene and subjectively assessed sense of presence on performance. We found a statistically significant interaction  and realism (Hypothesis 3) on social facilitation in VR. On the other hand, sense of presence did not play the same role (Hypothesis 2). In order to successfully evoke the social facilitation effect in the presence of computer-generated bystanders, a certain level of (subjective) co-presence in the VE must be achieved. Realism plays an analogous role. In this study, mere presence of virtual agents on the simulated accident site was enough to improve the trainees' performance (reduce the number of erroneous actions), but only for those who evaluated co-presence and realism as relatively high.We found no main effect of bystanders' presence on performance, which is in line with some previous studies , which did not turn out to moderate social facilitation, does not include any subscale related to social interactions. Keeping in mind the exploratory nature of these results, further detailed research is needed, but these results clearly suggest the crucial role of social realism in evoking phenomena based in social interactions in VR.Our results should be also analyzed from the perspective of the new terminology of phenomena regarding illusion of VR realism proposed by Slater . The ideexist, but they have to be perceived as realistic and (co-)present as well for the social facilitation effect to occur.Our results may contribute to the theoretical dispute about the mechanism of the social facilitation effect. According to one of the most popular explanations, attentional conflict caused by the physical presence of other people is the basis of the social facilitation phenomenon Baron, . If thisAll of the aforementioned observations lead to a conclusion that it is useful to implement social stimuli in VR training simulators, especially in the case when real people are present during actual implementation of the task being trained. It would be beneficial to implement virtual agents in the simulation, as it was confirmed that such agents can, to some extent, evoke effects similar to those observed in the real world. Bystanders are very often present at accident sites. They influence the rescuers' emotions and may sometimes actively hinder the operation . Since we conducted our study on specific participants, we could not find the inhibition effect during a task which was easy for them. However, using an existing procedure instead of an abstract task may increase the ecological validity of the study. Subsequent research should address this issue either by recruiting participants from a general population (not familiar with rescue procedures) or by manipulating the task in order to transform a well-practiced procedure into a counter-intuitive one. In both cases we would expect the social inhibition effect. Moreover, the characteristics of the population from which the participants were recruited led to the lack of representation of women in the study, which also may be viewed as a limitation of the study. Therefore, further studies with a more diverse group of participants should be conducted in order to improve generalizability of the results.The hypotheses we formulated regarded all of three potential moderators separately. However, it is plausible that the moderators are interrelated—we did not take it into consideration during experiment preparation. A model that includes three moderators at the same time would require a much larger sample to draw conclusions from it. We see our results as a first step in analysing the phenomenon of social facilitation in VR in context of subjective perception of the virtual environment . Testing whether these variables are related to each other should be considered in further studies on this issue.Besides, we operationalized VR characteristics as self-reported. Further studies should use experimental manipulation of these variables. Moreover, we used a simple method of assessing the participants' performance —namely, the number of committed errors. In further studies it could be useful to develop a more sophisticated performance measure . Moreover, we used a well-documented, but still highly specific activity. In future studies more general tasks should be used to strengthen the external validity of the results.the mere presence of other people, as it was firstly defined by Zajonc . Therefore, it may not be the fact that social facilitation is evoked by other people being there, but by the roles they have, the affective states they evoke in participants . This interpretation matches our results—the virtual bystanders were in fact similar to Cottrell et al's (Lastly, it could be viewed as a big limitation of the study that virtual agents—the victims—were present on the scene in both conditions. The understanding of social facilitation effect as the influence of y Zajonc  and showy Zajonc  may leadl et al. . In his  et al's  audienceIn sum, co-presence and realism seem to play an important moderating role in the relationship between the presence of computer-generated agents and social facilitation in VR. This finding is crucial considering the increasing use of similar tools to teach complex skills in a social context.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by Ethical Committee at Jagiellonian University Institute of Applied Psychology. The patients/participants provided their written informed consent to participate in this study.PS created the main conception and study design, analyzed majority of the data, interpreted the results, drafted and prepared the final version of the paper. NL and ND-M performed the experiment, gathered, and partially analyzed data. AS provided substantial contribution to the conception of the experiment and took part in data interpretation. ND-M wrote a minor part of the paper. NL visualized data. All authors contributed to manuscript revisions, read and approved the submitted version.The authors were employed by company Nano Games sp. z o.o.


Problem-Oriented Primary Care System Development Record, or PCSDR) that enables a data-driven and contextualized approach to primary care system development.There is significant global policy interest related to enabling a data-driven approach for evidence-based primary care system development. This paper describes the development and initial testing of a prototype tool (the The PCSDR is an electronic record that enables the systematic input, classification, structuring, storage, processing and analysis of different types of data related to the structure, function and performance of primary care systems over time. Data inputted into the PCSDR was coded using the WHO’s PHC-IMPACT framework and classification system. The PCSDR’s functionalities were tested by using a case study of primary care system development in Tajikistan.Tajikistan’s case study demonstrated that the PCSDR is a potentially effective and conceptually-sound tool for the input, classification, structuring and storage of different data types from myriad sources. The PCSDR is therefore a basic data entry and data management system that enables query and analytics functions for health services research and evidence-based primary care system development functions.The PCSDR is a data system that enables a contextualized approach to evidence-based primary care system development. It represents a coherent and effective synthesis of the fields of primary care system development and performance assessment. The PCSDR enables analysts to leverage primary care performance assessment frameworks for a broad range of functions related to health systems analysis, improvement and the development of learning health systems. The development and realization of effective, efficient and equitable health care systems is contingent on policy-makers applying evidence-based interventions . The WHOThe successful operationalization of such a mandate requires the development of robust and conceptually sound data systems , 4. At tCrossing the Global Quality Chasm: Improving Health Care Worldwide , namely:[F(x)] are concrete actions and activities that can influence the sub-systems of primary care .These primary care system development functions In turn, these primary sub-systems ) are conceptualized and classified using the PHC-IMPACT primary care system framework, and comprise the vertical axis of the PCSDR .Both development functions [F(x)] and primary care sub-systems (α) upon which they act are respectively structured and coded using the PCSDR’s seven fields  Fig. .Fig. 2Cproblem-oriented, and (ii) the classification system of the domain’s subject matter must be systems-oriented.The PCSDR is therefore a biaxial electronic record comprised of key development functions [F(x)] (PCSDR x-axis), and the subject matter these functions pertain to (i.e. primary care sub-systems) (PCSDR y-axis). Each PCSDR axis has distinct conceptual requirements: (i) development functions [F(x)] must be [F(x)]  must be problem-oriented.This study is based on the assumption that primary care system development functions Problem-orientation enables the PCSDR to structure and contextualize interactions in a way that renders performance states and commensurate development functions meaningful. Problem-orientation is premised on a pragmatist philosophical conception of knowledge as problem-solving, and is one of the principal attributes for the domain of systems-oriented policy science –19.Problem-oriented development functions, in turn, must be premised on influencing the sub-systems of primary care (α), as conceptualized by rigorous systems-oriented frameworks such as the WHO PHC-IMPACT , 14.The PCSDR enables the scientific coding of problem and intervention systems (α), which are essential for data management, analysis, research and evaluation. The design of the PCSDR is modular and agnostic; therefore, it uses different primary care classification systems, at least for exploratory purposes. The PCSDR’s structure thereby enables flexibility and adaptability, while maintaining rigour. In this study, the PCSDR was coded using the WHO’s PHC-IMPACT framework classification system Fig.  10, 12––12–14.FIt is important to note that the PHC-IMPACT framework, classification system and indicators are still undergoing development, and its indicator database has not yet been populated , 14. OncThe PCSDR is premised on the assumption that primary care system performance is the result of complex interactions of combinations of different systems , 20. TheThe structure of the PCSDR enables multi-system variables to be systematically entered, structured and stored into a relational database. Operationalizing the electronic record using a relational database enables data to be structured as knowledge in the form of a semantic network. This approach operationalizes a systems paradigm, whereby knowledge is conceived as a network of interconnections of constituent entities , 17. KnoOperationally, the relational database provides a framework that captures statements regarding the content and dynamics of relationships between the PCSDR’s fields (i.e. its classified core content). Furthermore, through data linkage, the database can capture statements regarding relationships between the content of the record’s database and the entities of external databases. The relational database therefore facilitates powerful functions related to structuring, storing, querying and analyzing the content and relationships of data. These functionalities can support scientific research, evaluation and ongoing iterative knowledge generation.the PCSDR table;the PCSDR data entry form;the WHO PHC-IMPACT classification system; andCitations (unlinked table includes MS Word document attachment).The PCSDR was created using a relational database (MS Access). Two experts in health care informatics provided advice and guidance regarding the design and development of the relational database. The database  and Deutsches Institut für Entwicklungspolitik (DIE) Constellations of State Fragility , 25.To illustrate how the integration of external databases can provide additional contextual information, the following tables were included in the relational database:Tajikistan was chosen as a case study to test the PCSDR, due to alignment with recent and ongoing WHO primary care system strengthening work, with ample and accessible data availability. Tajikistan’s PCSDR’s content was derived from a scoping literature review, performed by adapting the York approach outlined by Arksey and O’Malley .The search strategy involved several literature sources, including peer-reviewed scientific journals, official reports and secondary documents. Search terms were purposefully kept broad as the goal was to conduct a sensitive rather than specific search.The first author performed the initial selection and review of relevant literature. Inclusion and exclusion criteria related to whether literature contained meaningful content in relation to primary care system development in Tajikistan, guided by the theoretical primary care system domains outlined by the WHO’s PHC-IMPACT framework.PubMed was searched using combinations of the terms “Tajikistan”, “primary care”, “primary health care”, “health care” and “healthcare”, for articles published between 1990 and May 2019. The search date was selected as 1991 marking Tajikistan’s independence from the Soviet Union and the beginning of substantive primary care system reforms. A “grey” news and document search  was performed in English using Google. Where possible, website searches were performed in a systematic manner, and site maps, publication links and internal website search engines were leveraged, when available. Snowball searches to identify additional data sources were performed by searching the reference lists of key scientific articles, reports and documents found.Themes and data from the literature were abstracted, synthesized and organized using thematic content analysis. Findings were compiled and triangulated against the various data sources. Data were cited and hyperlinked to their original online source, when available.Synthesized findings were shared with the co-authors , who are experienced health system researchers. The co-authors contributed to the analysis, and provided guidance regarding the initiation of additional searches to enable the completeness and validation of findings.To further complete and validate the data, the PCSDR’s content was exported to MS Word and reviewed by an expert from the WHO, for completeness and accuracy. The expert was requested to pay particular attention to the “Problem Statement” and “Findings” fields, and to provide a brief summary and indicators describing the original problems, going back to year 2000, since they were often poorly articulated or described in the literature. Furthermore, the expert was asked to include any active (i.e. ongoing) problems that have been overlooked, along with related content and/or references. The expert was asked to include any important references that may have been missed or are available in the Tajik language, along with a brief synthesis of their content. The expert’s proposed revisions and comments were reviewed by the first author, who made changes using MS Word’s “Track Changes” feature.Tajikistan’s PCSDR was coded using WHO’s PHC-IMPACT and PCET classification system. Codes (Probα and Txα) were assigned according to technical criteria of relevance and accuracy. The coding process entailed significant technical judgment and subjectivity, particularly in cases where problem statements, interventions and codes were poorly defined. PCET codes were only assigned to problem systems, since that specific coding exercise was related to demonstrating the potential of cross-mapping classification systems.The MS Access relational database functionality enables various useful data management tasks that support evidence-informed decision-making for the field of primary care system development, such as search and retrieval, structured queries, question answering and definition acquisition .Simple queries of fields, as well as queries of relationships within and between problem and intervention system codes, which enable health services research, performance assessment and development activities.The following queries were performed to demonstrate and analyze the PCSDR’s core functionalities:The results section reports and describes the content of the PCSDR and its key functionalities, using Tajikistan as a case study.the WHO PHC-IMPACT classification system table;the PCSDR data entry form;the PCSDR table (i.e. the record table); andcontextual tables for Tajikistan.The PCSDR relational database  . The data entry form’s multi-value fields enable multiple codes to be recorded for respective problem and intervention systems.The data entry form allows entry of hyperlinked free text in the “Findings”, “Intervention” and “Progress notes” fields. Such content enables the contextualization of information within the PCSDR and informs the further development of classification content. A bibliography of sources cited is available for download from the ‘Citations’ table.The totality of entered data is structured and stored in the PCSDR table referred to as the “Record” table Fig. . The conTajikistan’s completed PCSDR is comprised of 36 problem statements. It conveys the narrative of a middle-income country in transition, attempting to orient its health care system towards the principles of universal health coverage and a primary health care approach. The content of the problem statement list is mainly comprised of foundational and structural domains, such as governance, policy, financing, funding, infrastructure, human resources and education, depicting Tajikistan’s efforts related to redressing the structural legacy of its inherited Soviet system Table .Table 1Similar to other post-Soviet countries undergoing structural adjustment-type reforms, primary care system development in Tajikistan was not generally done using a problem-oriented approach , 29. TheMulti-value fields for intervention systems may also indicate that problems were appropriately addressed by targeting multiple underlying causal system areas. Elucidating the complex network relationships between Problem (Probα) and Intervention Systems (Txα) enables analysts and researchers to understand the interactions and dynamics within the health care system, which in turn enables more effective and efficient development activities. The MS Access relational database query functionality enables interrogation of these relationships. For example, an analyst can easily query what Intervention Systems (Txα) relate to specific Problem Systems (Probα), and vice versa.For example, Fig. Contextual tables providing indicators on Tajikistan’s state fragility, public health, and socioeconomic contextual indicators are organized by database type and year, to facilitate ease of use. Figure By including these contextual tables in the relational database, their respective content could hypothetically be linked with the PCSDR if fields for time intervals are included. This could allow for useful research that integrates the work of different fields (e.g. primary care system development and state fragility). Snapshots of the fragility and socioeconomic contextual tables can be viewed in Additional file Systems-oriented evidence-based decision making is contingent on the application of scientific knowledge to problems and issues of concern within particular contexts . For thiThe PCSDR presents an example of a basic data source system via a structured record for input and classification of different data types from myriad sources, as well as a data management system that enables the structuring, storing and processing of data. The structured data entry presents an opportunity for primary care system analytics, modeling and reporting functions, which in turn can directly support research, evaluation and evidence-informed decision-making.To enable its practical and effective use in the context of real-world complex and dynamic primary care systems, the PCSDR was designed be conceptually sound (i.e. problem and systems-oriented), content valid , and fit-for-purpose (i.e. enable evidence-based primary care system development functions).Lasswell’s concept of problem-orientation has recently been recognized as being fundamental in relation to building state capacity and international development functions , 19, 28.The PCSDR is a tool that can systematically enable a problem-oriented approach for primary care system development. Its ability to both create a system of recording and meaningfully associate data is particularly relevant for countries undergoing long-term and large-scale transitions.data collection and entry for different types of data from myriad sources;coding of PCSDR data using scientific classification systems (e.g. PHC-IMPACT framework classification);measurement of primary care system performance;assessment of determinants of performance;measurement and assessment of changes in performance states over time ;assessment of system interactions and interventions associated with changes in performance; andaccess to external databases via data linkage .The PCSDR enables the use of systems-oriented primary care frameworks and classification systems for primary care system development activities  , 14, 32.The PCSDR’s simple structure enables these functions to be conducted in a logical, scientific and systematic manner. Its systems-oriented classification systems and taxonomies of problem-oriented development functions (i.e. F(x) fields] promote scientific progress by enabling research, analysis and evaluation.The scientific development of primary care system classifications and the practical use of the PCSDR are complementary and codependent. Conceptually-sound and granular classification systems enable effective operationalization of the PCSDR, which in turn, generates, structures and stores content knowledge, enabling further refinement and development of classification systems.A relational database enables data to be structured and stored in the form of a semantic network . This apBy structuring data, the relational database enables analysts and researchers to conduct queries for descriptive and analytical functions , 5. QuerQueries of relationships between the PCSDR’s fields (e.g. between Problem [Probα] and Intervention System [Txα] codes) are critical from a scientific research and knowledge perspective, since they enable key health services research and health system performance assessment functions. For example, an understanding of the complex influence of interventions on system interactions would provide useful insights related to their respective effectiveness and efficiency. Tajikistan’s PCSDR provided a clear example of how problems are often addressed by targeting multiple underlying causal system areas, which in turn often influence other problem areas. The PCSDR enables this systems complexity to be systematically structured and interrogated.This study also demonstrated how the relational database enables strategic linkage with external datasets containing relevant and useful contextual data, such as demographic, epidemiological and socioeconomic, political indicators. Such simple functionalities are not only efficient and practical for analysts; they can enable effective cross-disciplinary research through data linkage between the respective databases –35.The PCSDR provides a potentially conceptually sound, effective and practical approach that can contribute towards enabling a data-driven approach for primary care system development. For example, the PCSDR can potentially be adapted and leveraged to enable operationalization of the mandate of the newly established WHO ‘Division of Data, Analytics and Delivery’ relating to “enhancing the collection, storage, analysis and usage of data to drive policy change in countries” . The tooThe PCSDR can enable and systematize important policy and planning governance functions by supporting Ministries of health through a consolidated and structured database. Updates and changes to the underpinning evidence base are recorded, thereby enabling transparency. As earlier noted, the record facilitates institutional memory that is often lost between policy cycles. The availability of a structured and consolidated database is especially relevant in contexts where there are many international stakeholders and financiers, such as in the case of Tajikistan where organizations operate in siloes and have their own data structures and reporting mechanisms.At an international level, PCSDR datasets comprised of longitudinal data across countries has the potential to support health services research to leverage statistical and machine learning tools in order to identify complex patterns, and to accurately understand the structure and function of primary care systems. This would enable cross-learning and the development of decision support tools that yield contextualized knowledge on the influences of interventions to primary care system performance. Such assessments of the effectiveness and efficiency of interventions foster quality improvement cycles and innovative system design work. Together, the PCSDR, classification systems and structured relational databases may form the fundamental building blocks of future learning primary care systems.Embarking upon this ambitious future vision requires an awareness of the current realities of the field of international primary care system development. The PCSDR prototype presented in this paper was purposefully designed to align with and reflect the current state of the field, which remains in its infancy in relation to defining, standardizing and classifying its core content (i.e. functions and subject matter) , 12.What fields should comprise the core content of the PCSDR?How should the status and content of the problem list be designated (e.g. active and inactive problems) and updated (e.g. redefining and reclassifying problems)?What are the rules for data entry?What classification system(s) should be used?How should date and time stamps be incorporated?How should the ‘Progress Notes’ field be updated? How should citations be integrated and linked?What contextual databases are relevant and useful for inclusion, what are the optimal mechanisms for their linkage?What types of decision support tools should be developed and integrated  Evidence Tool Database).What type of database management system should be used?What standard operating procedures and protocols need to be developed to enable proper operationalization and testing?The PCSDR presented in this paper has many technical and operational limitations, as it is a preliminary prototype that aims to demonstrate basic proof-of-concept. Ultimately, health services researchers and development experts must decide on collaborative processes to properly develop its content and design. For example, some key areas for further reflection and consideration may include:Furthermore, the development of practical evaluation frameworks that enable the testing of the type of outputs produced by the PCSDR under different scenarios is required. Such studies would provide insights into the utility and effectiveness of the PCSDR, particularly in relation to alternative approaches and the status quo, and to investigate what inputs, resources and training are required to enable the efficient and effective use of the tool. It is also essential to explore whether and how the PCSDR could potentially be integrated with other planning tools currently in use.In addition to the PCSDR’s conceptual and technical development, scientific and organizational consensus is required in relation to systematically adopting problem-orientation for primary care system development , 28, 31.Certain attributes of systems development functions are essential and universal, namely: problem-orientation, systems-orientation and contextuality . These aThe PCSDR structures data in a way that enables the development of measurable scientific knowledge related to the basic anatomy (structure) and physiology (function) of primary care systems. Such knowledge enables research pertaining to the aetiology of system dysfunction which, in turn, enables analysts and researchers to devise and test mechanisms and interventions related to influencing and rectifying dysfunction.The PCSDR enables the structuring of all such functions, which enables analysts to meaningfully assess the value (i.e. effectiveness and efficiency) of respective interventions. The PCSDR thereby enables the field of primary care system development to transform into a professional and scientific domain, amenable to assessment and improvement.Additional file 1. PCSDR Database for Tajikistan. The database is comprised of the PCSDR table, the PCSDR data entry form, the WHO PHC-IMPACT classification system, citations and contextual tables.Additional file 2. Tajikistan PCSDR table.Additional file 3. Query of relationships between Txα and Probα codes for Tajikistan’s PCSDR.Additional file 4. Query of relationships between Probα and Txα codes for Tajikistan’s PCSDR.Additional file 5. Supplementary file containing the following: the full Table