Patient portals have emerged as a recognized digital health strategy. To date, research on patient portals has grown rapidly. However, there has been limited evaluation of the growing body of evidence on portal availability, use, clinical or health behavior and outcomes, and portal adoption over time.This paper aims to comprehensively consolidate the current state of evidence on patient portals using the umbrella review methodology, introduce our approach for evaluating evidence for quantitative and qualitative findings presented in included systematic reviews, and present a knowledge translation tool that can be used to inform all stages of patient portal adoption.For this study, a modified version of the Joanna Briggs Institute umbrella review method was used. Multiple databases were searched for systematic reviews focused on patient portals, and the final sample included 14 reviews. We conducted a meta-level synthesis of findings from quantitative, qualitative, and mixed methods primary studies reported in systematic reviews. We organized the umbrella review findings according to the Clinical Adoption Meta-Model (CAMM). Vote-counting, GRADE , and CERQual  were used to assess the umbrella review evidence.Our knowledge translation tool summarizes the findings in the form of an evidence map. Organized by the CAMM categories, the map describes the following factors that influence portal adoption and effects over time: patient contexts, patient's interest and satisfaction, portal design, facilitators and barriers, providers' attitudes, service utilization, behavioral effects, clinical outcomes, and patient-reported outcomes. The map lists the theories and mechanisms recognized in the included portal research while identifying the need for business models and organizational theories that can inform all stages of portal adoption. Our GRADE and CERQual umbrella review evaluation resulted in the majority of evidence being rated as moderate to low, which reflects methodological issues in portal research, insufficient number of studies, or mixed results in specific focus areas. The 2 findings with a high rating of evidence were patients' interest in using portals for communication and the importance of a simple display of information in the portals. Over 40 portal features were identified in the umbrella review, with communication through secure messaging and appointment booking mentioned in all systematic reviews.Our umbrella review provides a meta-level synthesis to make sense of the evidence on patient portals from published systematic reviews. Unsystematic and variable reporting of portal features undermines the ability to evaluate and compare portal effects and overlooks the specific context of portal use. Research designs sensitive to the social, organizational, policy, and temporal dimensions are needed to better understand the underlying mechanisms and context that leverage the identified factors to improve portal use and effects. Internationally, there has been an increasing effort to engage patients and consumers in their own health care using information and communication technology. The COVID-19 pandemic significantly stimulated the adoption and use of information and communication technology in primary care and outpatient clinics to facilitate remote visits, distant monitoring, and communication during the period of social distancing, particularly for patients living with chronic conditions . These cCountries such as Canada, the United Kingdom, and the United States have created national consumer digital health strategies and programs to encourage greater patient and consumer interactions with their health care providers through a variety of digital health solutions such as the patient portal -9. For ePatient portal is a digital health tool managed by a health organization to provide patients with secure online access to their own health information such as laboratory results, doctor’s notes, and medication lists; care services such as appointment booking and reminders; and communication with their health care providers via secure messaging from anywhere via the internet . It is aDespite widely acknowledged portal benefits, the empirical evidence on patient portals reflects important challenges and context-dependent outcomes of portal use. For example, a recent review examining the behavioral and clinical outcomes associated with portal use reported improved patient understanding of their health conditions and medication adherence while noticing modest or no effects on diabetes and hypertension biophysiological indicators . Our prespecific health conditions [select study design, for example, randomized controlled trials (RCTs) using a portal as an intervention [determinant and outcome category” from 19 SRs retrieved up to early 2018. Among the limitations of their review, van Mens et al [Research on patient portals, including primary studies (PSs), systematic reviews (SRs), and meta-level reviews, has been rapidly growing. Most SRs focus on nditions , patientnditions , aspectsnditions -18, or orvention . To datervention ,20. van rvention  used theIn addition to focusing on portal technology, both meta-level reviews ,20 and sOur contributions are threefold. The first is substantive: this umbrella review comprehensively consolidates the current state of evidence about patient portals. The second is methodological: we included a wide range of high-quality SRs that were specifically focused on portal technology, eliminated duplicate PSs, and appraised the quality of umbrella review quantitative and qualitative evidence using modified GRADE  and CERQual  criteria, thus presenting the relative strength of each umbrella review finding. The third contribution is knowledge translation, where our findings in the form of an evidence map can provide guidance for organizations in their patient portal adoption efforts. This is especially important in the Canadian context as many jurisdictions are actively pursuing patient portals at this time.The objectives of this umbrella review are to summarize the current state of evidence in patient portals based on published SRs and to create an evidence-based knowledge translation tool for the adoption of this technology. The questions addressed in this umbrella review are as follows:What are the characteristics of the patient portals being introduced and used in different settings?What are the system-related, health care provider–related, and patient-related factors that influence the introduction, use, and impact of patient portals?What is the impact of patient portals on clinical outcomes of care?modifications [Our methodology is detailed in a published protocol  registerications . Overallications  and Smitications .In April 2018, the original search was conducted in 9 databases: MEDLINE, EMBASE, CINAHL Plus with Full Text, Web of Science Core Collection, Scopus, the Cochrane Database of Systematic Reviews, the PROSPERO registry, the JBI Database of Systematic Reviews and Implementation Reports, and Proquest Dissertations and Theses. An updated search in MEDLINE was conducted in November 2019 to identify the SRs published since the initial search. The complete search strategy is provided in Citations were imported to Covidence. Two researchers independently screened titles and abstracts and then full-text articles against the inclusion and exclusion criteria. Discrepancies were resolved by consensus between 2 researchers and/or by a third researcher. The methodological quality of each SR was independently assessed by at least two researchers using the JBI critical appraisal checklist for SRs consisting of 11 questions . Upon reOur initial database search for SRs yielded 158 citations. After eliminating duplicates and screening for relevant titles and abstracts, we retained 40 SRs for full-text assessment. By applying the inclusion or exclusion criteria, we identified 16 SRs for critical appraisal. An updated search in November 2019 identified 108 citations, yielding 6 SRs for full-text assessment, 3 of which underwent critical appraisal  group A: purely quantitative reviews (n=3) where the SR authors only reported on findings from quantitative PSs, and (2) group B: reviews with a mix of quantitative, qualitative, or mixed methods PSs (n=10). There were no purely qualitative reviews .Initially, we categorized the included SRs according to the logic underpinning their approach to synthesis ,37: reviOne researcher extracted all the data, and 100% of the outputs were validated by at least one other researcher, with discrepancies resolved by discussions among the 3 researchers. All relevant PSs, their design, sample size, and all findings, as reported by the SR authors were extracted into Excel tables. Duplicate findings from duplicate PSs were removed to manage an overlap among the reviews. Data were synthesized into themes and then a smaller number of domains and statements. No statistical meta-analyses or subgroup analyses were performed due to heterogeneity of the study design.As a precursor for rating the strength of umbrella review quantitative evidence and the confidence in umbrella review qualitative evidence, our 2 main data extraction documents were quantitative and qualitative Excel tables, respectively. The headings and/or introductory sentences in the paragraphs describing findings or results in each SR were used for initial domain categorization. Domains were further developed through an iterative process of cross-checking with the Clinical Adoption Meta-Model (CAMM) framework, sorting within Excel documents, and weekly analysis meetings among the researchers.P values, significance, and confidence intervals) of PS findings. Our qualitative data extraction table included those PSs from SRs in group B, where the SR authors provided sufficient information about the study design for the reader to classify those PSs as qualitative. After removing duplicates, the quantitative table included 360 unique individual findings from 10 SRs [Our quantitative data extraction table included those PSs from SRs (both group A and group B), where the SR authors referenced statistical significance  and CERQual-UR , by applying a voting-counting method  and adapThe GRADE-UR tool rates the strength of evidence as high, moderate, low, or insufficient -41. BrieTo the best of our knowledge, no tools are currently available for rating the evidence in reviews that synthesize mixed methods and findings from quantitative studies reported in SRs without any reference to statistical analysis; thus, we were unable to assess umbrella review evidence synthesized from our respective Excel tables. However, we compared umbrella review findings from mixed methods or quantitative descriptive PSs with the umbrella review findings from quantitative and qualitative PSs. We looked for differences and correspondences with the goal of formulating any additional umbrella review finding statements arising from mixed methods or quantitative descriptive findings and not subject to GRADE-UR or CERQual-UR evaluation. This information can be found in adoption model with 5 dimensions: availability, system use, clinical/health behavior, outcomes, and time. In this review, adoption refers to the planning, implementation, utilization, and support of a patient portal. Availability refers to making the patient portal accessible to users. Use refers to patterns of user interaction and experience with the portal. Clinical/health behavior refers to changes in user behaviors from interacting with the portal. Outcomes refers to the health impact from portal use. Time refers to the transition periods across the 4 dimensions [The output of our umbrella review consists of 2 summary of findings and evidence profile tables, a narrative synthesis, and a knowledge translation tool in the form of an evidence map on patient portal use and impact. CAMM  underpinmensions .aggregation reviews, resulting in 1075 unique findings. We handled the findings of the only configuration review [The population, objectives, design, and context of the 14 reviews are described below and further summarized in n review  holisticn review  proposedA total of 6 reviews focused on specific populations: people with diabetes ,35 or otIncluded SRs examined patient engagement , facilitaggregation reviews, the number of PSs ranged from 5 [Across the 13 d from 5  to 143 [d from 5 , yieldind from 5 ,32,34,35d from 5 ,24,32,34d from 5 , and pord from 5 , low quad from 5 ,33, and aggregation reviews, we found limited application of models, theories, and frameworks as the conceptual foundation for evaluating patient portal use and outcomes. None of the included SRs applied models, theories, or frameworks as a guide for their review. Some authors briefly referenced models, theories, and frameworks as justification for the review or in their discussion, whereas others summarized the use of models and theories in the included PSs [Across the 13 uded PSs ,31,36. Guded PSs  found thuded PSs , and 2 Suded PSs ,24. The uded PSs , activatuded PSs  and deveA total of 10 reviews named the countries where the PSs were conducted; most were in the United States, with Europe, Australia, and Asia referenced ,31,34-36Portal features were reported inconsistently and unsystematically across reviews  ,31,32,34Patients are interested and satisfied in using patient portals if they are designed to be easy to use and useful ,24,33. TThere are many barriers that impede the adoption of patient portals. Patients may forget their password, not have internet access, or lack the necessary interface or literacy and computer skills ,33,35,36A limited number of reviews addressed these factors. The lack of incentive or reimbursement may dissuade providers from promoting portal use to their patients ,31. Two Multiple qualitative studies reported on providers’ attitudes toward portals ,29,33. TCommunication and influence on patient-provider relationships became a common thread throughout our evidence map. Some SRs found that patients were interested in the potential of using portals for communication with providers ,30,33 anThree SRs reported on providers’ interest in portals for encouraging patient engagement and communication of complex information with recognition of the potential impact on patient-provider relationships ,29,33. I1c [Although patient portals may improve patient safety by having patients note and correct errors ,24,33,351c -17,31, p1c ,35, and 1c .Limited number of studies have examined changes in the utilization of preventive or testing services ,33, rateThe review by Otte-Trojel et al  includedThe study by Grossman et al  was the Data included in our mixed methods and quantitative descriptive extraction tables and not subject to the evidence rating provided additional support for the quantitative and qualitative umbrella review findings discussed earlier . In addiTo the best of our knowledge, our umbrella review demonstrates the first attempt to adapt GRADE and CERQual processes and to develop GRADE-UR and CERQual-UR tools for evaluating evidence generated in an umbrella review. Moreover, our combined approach of evaluating the evidence and application of CAMM at the umbrella review level provides a novel approach for analyzing outcomes. In particular, we demonstrate how this approach can provide a more nuanced understanding of the evidence for common findings generated in portal research.Our umbrella review provides an evidence map based on CAMM and the consolidated summary on the current state of evidence on patient portals and can be used to inform all stages of portal adoption. The map should be used in conjunction with the evidence tables to understand the strength of the available empirical support for different factors influencing patient portal adoption, use, and outcomes. In the next four paragraphs, we present key umbrella review findings and elaborate on how the map can be applied to address current knowledge gaps and across research, industry, policy, and practice.interest to registration or enrollment, activation, and then to use or utilization ending with empowerment in the best-case scenario. In our umbrella review, we found enrollment and use often being conflated, thus blurring the line between these 2 separate, yet very significant, dimensions of portal adoption.The temporal aspect of CAMM suggests that portal adoption per se is not a guarantee of its effectiveness and that it should not be evaluated at a single point in time; rather, there are transitions from portals change provider workload was rated as very low, indicating that further research on this topic is likely to produce useful findings. However, the tables summarizing our findings also show that this topic has been extensively researched, but the studies exhibited great variability in the direction of the findings. This incongruence in the findings about changes to provider workload reveals a complex interplay of factors mobilized when technology is introduced into clinical practice and patients’ homes. Neither the types of studies that control for these factors  nor the study designs that simply explore participants’ satisfaction and perception are capable of shedding light on local organizational contexts that are often responsible for divergent portal outcomes.We color coded different factors included in the evidence map to visually represent the strength of the current evidence. The colors can reveal not only existing knowledge gaps but also methodological assumptions made in some research on portals. For example, the evidence for the statement easy-to-use portal design is required that does not introduce usability barriers at a later stage. In the policy realm, there is a need for governance guidelines that address both patients’ and providers’ privacy and security concerns to encourage trusting patient-provider relationships.The ideal use of the evidence map would be that each stakeholder looks across adoption stages and recognizes the interdependency among different factors, as the following examples suggest . For example, for industry to support the promised long-term vision of improving clinical and patient-oriented outcomes, an interested in the communication afforded by patient portals, whereas providers are concerned about the increased workload introduced by the new channels for communication. Further, portals are promoted as a tool for patient empowerment, whereas providers are concerned about the loss of control over information. With portals designed to serve more than one user group and to support their sometimes-divergent agendas, the success of portal technology hinges on acknowledging these different values and addressing these differences through the engagement of all relevant user groups.In addition, the evidence map reveals the areas of differing values that need to be considered within practice to achieve successful portal adoption. For example, patients are There are a number of strengths to this umbrella review. First, the elimination of duplicate PSs from the included SRs provides a more accurate account of the reported findings. Second, the application of vote-counting, GRADE-UR, and CERQual-UR allows the direction, strength, and confidence of the evidence to be quantified and compared. Third, the evidence-based knowledge translation tool offers practical guidance to those involved in the planning, implementation, and support of patient portals. The evidence map seems promising as it helps to cast the use and impact of patient portals over time across preadoption, early adoption, and mature adoption stages while summarizing both key known success factors strongly supported by research and areas with low evidence base where more research is needed.There are possible limitations to our search strategy. First, the literature on patient portals is varied in its coverage of eHealth modalities, inconsistent in defining portals, and evolving. Our search and selection strategy could have missed reviews that should be included. Second, we only focused on reviews published in English; those in other languages could have been missed. We also relied on the SR authors' identification of patient portals. However, in reviewing the SRs' reference list, we discovered that some SRs had included PSs that were broader in scope than the SR definition of patient portals. We accounted for these occasional discrepancies between the intended and actual SR focus during our GRADE-UR and CERQual-UR evaluation.P values to evaluate the strength of evidence. Many of the PSs included in the GRADE-UR evaluation had a limited sample size, and reporting on the power calculation of these studies was lacking; therefore, we were unable to evaluate these claims of statistical significance.Our application of GRADE and CERQual at the meta-synthesis level could have been flawed, as there is little or no guidance available on how to appraise evidence synthesized across several SRs. In particular, we used SR authors’ reporting of statistical significance and Similarly, we relied on SR authors’ reporting of the PS findings. When we suspected possible errors in SR authors’ reporting of findings, we consulted the original PS; in these cases, consensus among all umbrella review researchers was sought to determine how to address these individual discrepancies. However, this process was not exhaustive, and we did not cross-check all the findings between SRs and PSs.evidence in the context of portal research should not be limited to a narrowly conceived evidence stemming from controlled studies. The role of RCTs is well recognized, and the strength of this design is acknowledged [At the time of analyzing the included SRs, we noticed a certain tendency for not recognizing the findings from qualitative research as evidence worthy of being evaluated for its strength, which may reinforce the hierarchy of what is considered evidence. This observation might be explained by the lack of appropriate tools such as CERQual, which was developed recently and presents a counterpart to GRADE. The notion of owledged ; howeverowledged  call forowledged ,48.When examining portal-related outcomes, comparative studies to date have focused on biomedical measures for people with diabetes or hypertension and patient empowerment scores for general patient populations. We recommend further research with people living with other chronic conditions and comparative measures that communicate patients' values and perspectives . This wiUnsystematic reporting of portal features in the included SRs may reveal a mistaken assumption in some patient portal research that portal features are inconsequential for the outcomes. In comparative research, this can lead to a faulty comparison of portals that may be quite different from each other. We recommend that researchers report actual portal functionalities and technology characteristics. Ammenwerth et al  offer a Consistent with the findings of other SRs not included in our umbrella review, we found that the most extensive areas of research and evidence were on patient-related factors, namely, common barriers and facilitators ,51, clinOur umbrella review offers an organized knowledge translation tool on what is known about patient portals, the quality of the available evidence, and areas that require further work. The evidence map can be used to inform planning, implementing, and supporting the adoption of patient portals across research, industry, policy, and practice. Through our GRADE-UR and CERQual-UR approach, we demonstrated not only how to consolidate findings from SRs, including PSs of various designs, but also how to evaluate the strength and confidence in the evidence of findings from quantitative and qualitative studies. For many of the umbrella review findings, the quality of the evidence was rated as low. This suggests at least two interrelated conclusions. For many identified factors playing a role in portal success, their interactions and underlying mechanisms, especially over time, are still mostly unknown and invite new research. Along with this, we need a broader conceptualization as to what constitutes evidence. This calls for study designs and theoretical perspectives attentive to the contextual complexity of portal adoption.


Food and nutrition literacy promotion needs multi-dimensional interventions. In the process of developing an intervention to promote food and nutrition literacy, the present review protocol aims to critically examine the evidence in the area of school-based interventions for promoting food and nutrition literacy (FNLIT) in elementary school children.Food and nutrition literacy is a newly emerged concept to connect food-related knowledge and skills to healthy diets. Its promotion is important to protect children as they eat too many low-nutrient, high-energy foodsWe will search PubMed/MEDLINE, EMBASE, Web of Science, CENTRAL, and ProQuest (from inception onwards). Additional studies will be identified through manual searching of reference lists. Quantitative studies  evaluating the effect of interventions to promote food and nutrition literacy in elementary school children (5–12 years old) will be included. Main outcomes will be food and nutrition literacy at functional, interactive, and critical levels. Secondary outcomes will be dietary intake indicators  and health outcome measures . Two reviewers will independently screen all citations, full-text articles, and abstract data. Potential conflicts will be resolved through discussion. The study methodological quality (or bias) will be appraised using appropriate tools. If feasible, we will conduct random effects meta-analysis. The quality of the included studies will separately evaluate using the validated Quality Assessment Tool for Quantitative Studies, developed by the Effective Public Health Practice Project (EPHPP). Data will be extracted by two reviewers from the identified relevant literature. Standard data synthesis and analysis will be used for the review.This systematic review will summarize the evidence regarding the components, implementation methods, and effectiveness of the interventions of food and nutrition literacy promotion in elementary school children. The results of this review will provide a useful reference for policymakers and curriculum developers to assess education curricula and develop practical learning and teaching strategies to improve students’ food and nutrition literacy.PROSPERO (CRD42019135118) Non-communicable diseases (NCDs) are the major cause of mortality and morbidity globally . The WorHealth literacy is considered as one of the most important personal skills to enable individuals to control health determinants. Nutbeam described health literacy as “the cognitive and social skills which determine the motivation and ability of individuals to gain access to, understand and use information in ways which promote and maintain good health” . He highEvidence shows that promoting FNLIT is a key factor in healthy food choice and following healthy eating patterns in children and adolescents –17. IncrGuided by Nutbeam’s hierarchical model of health literacy , food liFunctional literacy is considered as the lowest level and critical literacy as the highest , 20. In Educating individuals about portion sizes and daily food group, describing and learning how to read nutritional labels and apply them to one’s dietary change by training and video programsTraining in gardening and plantingCookbooks that feature healthy recipesFunctional guideline for food purchasing using an empty grocery list in accordance with the traffic light-coded food labelsMedia literacy/critiquing a food commercialDue to the novelty of the concept of FNLIT, a comprehensive intervention to promote FNLIT, especially at the interactive and critical levels, has not been yet developed. Some of the interventions related to the promotion of food literacy/nutrition literacy mentioned in some studies are as follows , 24–26:The promotion of FNLIT in children seems to be one of the most important elements in improvement of healthy dietary pattern and prevention of diet-related non-communicable diseases for several reasons. First, FNLIT is related to everyday living activities, i.e., food related activities, including eating . Second,Third, based on the evidence, interventions in the early years of life are recommended to take advantage of the child learning ability and more possibility of successful stabilization of healthy behavior into adulthood . The fouAccording to the studies, FNLIT has multi-dimensional political, cultural, and social characteristics. This multi-dimensional nature of this concept confirms the need for multi-dimensional interventions to improve FNLIT , 28. TheThe objectives of this study will be to systematically determine components within interventions that have an impact on children’s food and nutrition literacy  among elementary school children (5–12 years old).Determine components within interventions that have an impact on food and nutrition literacy  among elementary school children (5–12 years old).Determine the implementation methods of food and nutrition literacy interventions  among elementary school children (5–12 years old).Determine the effectiveness of interventions in promotion of FNLIT  among elementary school children (5–12 years old).The objectives of this study are to:The present protocol has been registered within the PROSPERO database (registration number CRD42019135118) and is being reported in accordance with the reporting guidance provided in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement   evaluating the effect of interventions to promote food and nutrition literacy in elementary school children (5–12 years old) will be included.We will assess all studies whose target group are elementary school students (5–12 years old).Any type of studies available in English featuring interventions that contain one or more components of food literacy/nutrition literacy , includiReferring to Nutbeam’s tripartite model , 21, whinutrition facts labels, cooking skill confidence, and desire to fewer fast food meals. Increase in fruit and vegetable and whole grain consumption [Functional food and nutrition literacy: improve meal planning, prioritizing healthy meal choices, reading sumption  and prepsumption .Interactive food and nutrition literacy: family-child feeding interactions , skill oCritical food and nutrition literacy: trying ethnic and unfamiliar food , food laSuccessful interventions and those that include theories and hands-on activities to enhance literacy will be taken into account.Secondary outcomes include improvement in diet quality  , dietaryThe study outcomes will not be a criterion to enter the study, and all the positive and negative outcomes will be checked.The primary source of literature will be a structured search of major electronic databases (from inception onwards): PubMed/MEDLINE, EMBASE, Scopus, Web of Science, and CENTRAL. The secondary source of potentially relevant material will be a search of the grey or difficult to locate literature, including ProQuest and Google Scholar. We will perform hand-searching of the reference lists of included studies, relevant reviews, or other relevant documents. The literature searches will be designed and conducted by the review team which includes two experienced health information specialists. The search will include a broad range of terms and keywords related to “food literacy,” “nutrition literacy,” “children,” “adolescents,” and “interventions”. A draft search strategy for multiple databases is provided in Additional file All the identified studies of different sources will be transferred to Endnote and systematically de-duplicated, and a merged library will be created. Two reviewers will independently screen the titles and abstracts according to a pre-defined inclusion criteria checklist and will exclude unrelated ones. In case of disagreement between the reviewers, the judgment of article inclusion in the study will be made by a third person. The full texts will be read by the two individuals separately, and the final decisions will be made based on the checklist of inclusion criteria. The PRISMA  flowchart  will be Study characteristics: study design, year of publication, journal, year (or period) of study conduct, and geographical location of study conductParticipant characteristics: sample size, age , and genderIntervention characteristics: intervention (name and type), intervention description , and timing of post-intervention evaluationOutcome results: data collection method , main outcomes including improvement in FNLIT at functional, interactive, and critical literacy and secondary outcomes including improvement in diet quality  , dietaryA data extraction form will be designed and used to extract information from each study report. Information of interest will include the following:The content of each included studies will be extracted by two team members, independently, and potential conflicts will be resolved through discussion. Authors of primary publications will be contacted for data clarifications or missing outcome data, as necessary.Two reviewers will separately evaluate the quality of the included studies using the validated Quality Assessment Tool for Quantitative Studies, developed by the Effective Public Health Practice Project (EPHPP) . This toI2 statistic. The I2 is the proportion of variation in prevalence estimates that is due to genuine variation in prevalence rather than sampling (random) error. I2 ranges between 0 and 100% . We will also report Tau2 and Cochran Q test with a P value of < 0.05 being considered as statistically significant (heterogeneity). If quantitative synthesis is not appropriate, the findings will be summarized and discussed. Conclusions will be also formed on the basis of the power of each of the studies. After summarizing the results and providing conclusions that lead to improving interventional decision-making, the most successful and effective interventions will be identified.The data from each paper  will be used to build evidence tables of an overall description of included studies. If feasible and appropriate, data points from primary observational studies will be used to perform random effects meta-analyses. Since heterogeneity is expected a priori, we will estimate summary estimates  and its 95% confidence interval using the random effects model. The random effects model assumes the study prevalence estimates follow a normal distribution, considering both within- and between-study variations. Forest plots will be used to visualize the extent of heterogeneity among studies. We will quantify statistical heterogeneity by estimating the variance between studies using P values are < 0.10.If sufficient studies are identified and data points are available, potential sources of heterogeneity will be investigated further by subgroup or meta-regression analysis according to baseline characteristics and methodological covariates. We plan to conduct analyses by sex (girls vs boys) , age  of the intervention.The potential limitations at evidence source (study level) include the following:Since many studies do not directly use the term food literacy or nutritional literacy, we may miss some interventions related to the improvement of some components of food and nutrition literacy. However, the search strategy in our study is highly sensitive to overcome this limitation.The results of the review will be utilized to assess education curricula and develop practical learning and teaching strategies to improve students’ food and nutrition literacy in Iran which can be utilized by other countries as well.This review is intended for publication in a peer-reviewed journal. Analyses and scripts will be made publicly available. Any changes to the protocol will be documented as well.Additional file 1. PRISMA-P 2015 Checklist.Additional file 2: Table S1. Electronic search strategies.


The ability to cancel an already initiated response is central to flexible behavior. While several different behavioral and neural markers have been suggested to quantify the latency of the stopping process, it remains unclear if they quantify the stopping process itself, or other supporting mechanisms such as visual and/or attentional processing. The present study sought to investigate the contributions of inhibitory and sensory processes to stopping latency markers by combining transcranial direct current stimulation (tDCS), electroencephalography (EEG) and electromyography (EMG) recordings in a within-participant design. Active and sham tDCS were applied over the inferior frontal gyri (IFG) and visual cortices (VC), combined with both online and offline EEG and EMG recordings. We found evidence that neither of the active tDCS condition affected stopping latencies relative to sham stimulation. Our results challenge previous findings suggesting that anodal tDCS over the IFG can reduce stopping latency and demonstrates the necessity of adequate control conditions in tDCS research. Additionally, while the different putative markers of stopping latency showed generally positive correlations with each other, they also showed substantial variation in the estimated latency of inhibition, making it unlikely that they all capture the same construct exclusively. Here, participants are instructed to quickly respond to the appearance of a go-stimulus. In a minority of trials, the go-stimulus is followed by a stop-signal with a variable delay , prompting the participant to cancel their initiated response. Consequently, successful response inhibition is characterized by the lack of observable behavior, making the inhibitory process difficult to investigate.Response inhibition, i.e. the ability to cancel a prepotent or ongoing response, is considered essential for adaptive behavior. It is thought to rely on the right inferior frontal gyrus3, and is commonly calculated as a difference measure between some summary statistic of the reaction times in go trials and the stop-signal delay. At the neural level, the P3 event-related potential (ERP) was early on suggested as a marker of successful inhibition4. While the P3 amplitude scales with factors like inhibitory load and incentives for stopping6, the evidence for an association between P3 amplitudes and SSRTs is mixed9. Furthermore, P3 amplitude differences, both between groups and between experimental conditions, have repeatedly been reported without concurrent differences in SSRTs12. Recently, it has been proposed to shift the focus towards temporal aspects of the P3. In fact, studies have shown that both the peak and onset latency of the P3 might correlate with the SSRT16, suggesting that P3 latency measures could be potential neural markers of inhibitory capability. In addition to this, studies have found that the effects of inhibitory control can be measured by electromyographic (EMG) activity at response effector muscles in successful stop trials19. While the onset of this so-called partial response EMG (prEMG) reflects the response to the preceding go stimuli, the point for the prEMG decline (i.e. peak latency) may indicate the timing of inhibition reaching the periphery and could thus be another potential marker for the stopping latency.Several indirect measures have been suggested to quantify the timing of the inhibitory process. The most common measure derived from the SST is the stop-signal reaction time (SSRT). The SSRT is defined as the covert latency of the stopping process22. In fact, the computational model underlying SSRT estimation makes no assumptions about the processes leading up to the estimated stopping latency. This suggests that potential stopping markers could be sensitive to variations in processing stages preceding inhibition, a notion which has been supported by recent computational work24. In fact, several studies show that sensory, attentional and perceptual processes all play into inhibitory performance in the SST28.While a great deal of research has focused on quantifying the stopping latency, it has been argued that the use of inhibition as a general construct is not enough to properly explain SST performance29. Therefore, tDCS can be a powerful tool to make causal inferences about the role of the regions and processes involved in SST performance. Several studies have found decreased SSRTs following anodal stimulation of the IFG35, suggesting that this method can indeed alter inhibition latencies. However, both increased and decreased reaction times in go trials have also been reported36, indicating that anodal IFG stimulation could potentially influence strategic adjustments of task performance rather than an inhibitory process per se. Furthermore, investigations of concurrent electrophysiological modulations are sparse, and no one has investigated the effects of anodal IFG stimulation on inhibition at the effector level.Transcranial direct current stimulation (tDCS) is a promising avenue for delineating the relative impact of sensory processing and inhibitory control to the latency of the different potential inhibitory markers. TDCS has the potential to modulate neural activity, with anodal and cathodal stimulation being associated with increased and decreased excitability in cortical areas, respectively37. We used a multimodal approach and combined the tDCS with electroencephalography (EEG) and electromyography (EMG) recordings prior to, during, and after stimulation. Based on previous literature, we expected to find decreased SSRTs following anodal IFG stimulation. Additionally, if the SSRT, the P3 onset latency and the prEMG all index the same inhibitory process, we would expect to see decreased SSRTs accompanied by earlier P3 onset latencies as well as earlier prEMG latencies. Furthermore, if anodal tDCS over the visual cortices can facilitate sensory processing, which presumably contributes to the stopping latency, we would expect to see similar decreases in SSRTs, P3 latencies and prEMG latencies following VC stimulation, accompanied by more global decreases in reaction times in go trials.In this study, we explored the relationship between the different potential stopping latency measures, i.e. the SSRT, the prEMG, and the peak and onset latency of the P3 potential. We also investigated how these different markers were modulated by tDCS. We used a repeated measures design with three separate tDCS sessions for each participant and compared anodal stimulation of the inferior frontal gyri (IFG) and visual cortices (VC) to sham stimulation. Electrode positions were chosen in accordance with current flow simulations for the specified target areastime  and condition . The analyses were performed within a Bayesian framework using the JASP software38, and Bayes factors (BF10) are reported. BFs are a measure of strength of evidence in favor of one hypothesis relative to another, and thus quantifies how plausible each of the competing hypotheses are given the data collected39. In the case of BF10, values below 1 support the null hypothesis, and values larger than 1 support the alternative hypothesis. It has further been suggested that the strength of evidence can be assessed as follows: values between 0.33–1 or 1–3 are considered inconclusive, only providing anecdotal evidence. Values between 0.10–0.33 or 3–10 are considered moderate, and values smaller than 0.10 or larger than 10 are considered as strong evidence for H0 or H1, respectively41. It should be noted that since correction procedures for violations of sphericity are not well-developed in this framework, instances that fail to meet this assumption will additionally be presented with Greenhouse-Geisser epsilon (ε), the F-value for the corrected degrees of freedom, and the corresponding p-value.All behavioral, EEG, and EMG measures were analyzed used 3 × 3 repeated measures ANOVA (rmANOVA) with the factors 10 > 394 000), thus meeting the assumptions of the horse-race model. A full overview of all behavioral measures can be seen in Table Across all measurements, i.e. across pre-, peri- and post-stimulation measurements for all tDCS conditions, average go reaction times (goRT), SSRTs and stop accuracies were 500 ms, 210 ms and 49.5%, respectively, and thus in line with previous studies using a visual SST in a sample of healthy young adults. Furthermore, goRTs were longer than unsuccessful stop RTs (USRTs) for all participants in all measurements . Additionally, SSRTs did not change over the course of a session (BF10 = 0.201 for the main effect of time), nor did it differ across conditions (BF10 = 0.105 for the main effect of condition).Neither of the tDCS conditions were associated with changes in SSRTs, as indicated by moderate evidence against a time × condition interaction (BF10 = 0.087). We found anecdotal evidence for a main effect of time (BF10 = 1.296) and moderate evidence for a main effect of condition (BF10 = 8.923). Post hoc tests for the condition factor suggested that reaction times were longer in the VC session, with strong evidence for a difference between VC and IFG , anecdotal evidence for a difference between VC and SHAM , and moderate evidence against a difference between IFG and SHAM .TDCS did not affect goRTs, as shown by strong evidence against the time × condition interaction (BF10 = 0.094). We found anecdotal evidence against a main effect of time (BF10 = 0.802) and strong evidence for a main effect of condition (BF10 = 14.390). Post hoc tests for the condition factor suggested that SSDs were longer in the VC session, with strong evidence for a difference between VC and IFG , anecdotal evidence for a difference between VC and SHAM  and anecdotal evidence against a difference between IFG and SHAM .In addition, there was no stimulation-specific effects on SSDs, as indicated by strong evidence against the Across all measurements, the stop-P3 peaked at 374 ms, with an average onset latency of 302 ms. ERPs can be seen in Fig. time (BF10 = 0.228), anecdotal evidence against a main effect of condition (BF10 = 0.811), and moderate evidence against a time × condition interaction  = 0.987, p = 0.395). For the P3 onset latency, there was anecdotal evidence against a main effect of time (BF10 = 0.514) and moderate evidence for a main effect of condition (BF10 = 3.353). Post hoc comparisons for the condition factor showed moderate evidence against a difference between VC and SHAM , and anecdotal evidence for a difference between the IFG- and VC-condition  as well as between the IFG-and SHAM-condition , both in the direction of slightly later onset latencies in the IFG condition. The time × condition term showed anecdotal evidence against the interaction  = 3.043, p = 0.054).TDCS did not modulate P3 peak latencies, as shown by moderate evidence against a main effect of PrEMG activity could be detected in roughly 30% of successful stop trials, with an average peak latency of 160 ms across all measurements. PrEMG time courses can be seen in Fig. time (BF10 = 0.090), moderate evidence against a main effect of condition (BF10 = 0.208), and moderate evidence against the time × condition interaction (BF10 = 0.219). As for the latency of the prEMG, we found strong evidence against a main effect of time (BF10 = 0.100), moderate evidence against a main effect of condition (BF10 = 0.220) and anecdotal evidence against a time × condition interaction (BF10 = 0.370).The number of detected responses did not differ between measurements, as shown by strong evidence against a main effect of r values averaged across all conditions and time points (Mr) and BF10 for one-sample t-tests are reported in text. An overview of all correlation coefficients, their averages as well as their 95% credible intervals can be seen in Table To probe the relationship between the different markers of stopping latency  as well as their relationship with goRTs, we calculated correlations separately for each condition and time point and tested these conjointly against the null hypothesis that there are no stable associations between any two measures (see Methods for details). For simplicity, 10 = 15.126, Mr = 0.44), suggesting that faster inhibition as measured by the SSRT was accompanied by earlier onsets of the P3 potential. The relationship between the SSRT and P3 peak latency was also positive . Furthermore, earlier prEMG latencies were related to shorter SSRTs  as well as earlier onsets of the P3 . The correlations between prEMG latencies and P3 peak latencies were more variable both in size and direction .The SSRT and P3 onset latency showed medium to large positive correlations at almost all measurement points , shorter prEMG peak latency , as well as shorter SSRTs , while the relationship between goRTs and P3 peak latencies showed more variability across measurements .Longer reaction times were generally associated with shorter latencies for the P3 onset . Participants were also asked to rate whether they thought the experienced side effects were related to tDCS. The data was inconclusive regarding whether participants were more likely to attribute side effects to active stimulation compared to SHAM (BF10 = 1.126), potentially due to the low amount of side effects reported in general.We also investigated the presence and severity of potential side effects of tDCS using a questionnaire suggested by Brunoni To assess the contribution of sensory and inhibitory processing to the latency of stopping, we investigated the effects of tDCS over the IFG and VC on different putative measures of inhibitory timing, namely the SSRT, P3 onset and peak latencies, and the latency of the prEMG. Since several different markers have been associated with the timing of inhibition, we also assessed the relationship between these markers, as well as their relationship with goRTs.36, they are in line with other studies failing to find any SSRT modulations43. This discrepancy could be driven by several methodological differences between this and earlier reports, such as experimental design, electrode locations, or stimulation lateralization.Contrary to our expectations, we found evidence against any stimulation-specific effects on any of the investigated behavioral measures for both stimulation conditions, thus showing that tDCS did not affect reaction times in go trials, SSDs or SSRTs. The evidence also suggested that tDCS did not affect P3 latency measures or prEMG latencies. While our behavioral results contrast with some previous reports of SSRT reductions following anodal IFG stimulation44. Further, the inclusion of pre-, peri- and post-measurements has several benefits: It acts as a control for baseline differences, but it can also control for potential expectancy effects between conditions . The higher relative support for the null hypothesis thus suggests that additional control conditions should be incorporated when researching the effects of tDCS on stopping.First, we utilized a within-participant design with several active and sham stimulation conditions in combination with a multimodal approach and pre-, peri- and post-stimulation measurements. Therefore, our design allowed for a more thorough examination of potential tDCS effects on response inhibition than what has been possible in previous studies. Several active conditions could provide more control than just comparing active tDCS to sham stimulation46. In fact, a recent study showed that anodal IFG stimulation not only altered the functional connectivity and neural activity in the fronto-basal-ganglia network presumed to implement response inhibition, but that it also induced activity changes in both the dorsolateral prefrontal and the inferior parietal cortices47. Such widespread modulations raise the possibility that other regions might drive the previously reported effects. This notion could also be supported by the fact that SSRT modulations do not appear to be specific to anodal IFG stimulation. In fact, they have also been reported following e.g. stimulation of the dorsolateral prefrontal cortex49 or the pre-supplementary motor area52.Second, whereas previous studies have largely relied on approximate and thus unprecise electrode positions to stimulate the IFG, we chose electrode positions after modelling the current distribution for a given target region. Consequently, the discrepant results might be caused by differences in electrode positioning, both with respect to the exact position of the anode as well as the resulting current distributions. The previously mentioned SSRT decreases were reported after anodal stimulation of the right IFG, usually with a contralateral and often more anterior cathode. However, these types of distant bipolar montages can result in widespread and diffuse neuromodulation33, several studies point to the involvement of bilateral IFG in SST performance54. For these reasons, we used an electrode montage that provided simultaneous anodal stimulation of the bilateral IFG. Importantly, we combined this with ipsilateral cathodes placed posterior to the anodes. This setup provided more control over effects that might stem from the accidental stimulation of larger prefrontal and/or premotor areas. We also chose the same cathodal placement for both active stimulation conditions for better control over potential cathodal effects. While the decreased distance between anode and cathode has been found to provide more focal stimulation, it comes at the cost of higher amounts of current being shunted across the scalp46. Therefore, we stimulated at a higher intensity compared to previous studies investigating tDCS effects on stopping. Lastly, it should be noted that recent debate about the validity of different SSRT estimation techniques opens for the possibility that discrepant results are driven by differences in SSRT estimation methods. As SSRT decreases have been reported using different estimation methods, this is at least unlikely to be the sole reason underlying the different results. In sum, our results show that further investigations are needed to ascertain the exact effects of tDCS on response inhibition, as well as whether SSRT reductions following anodal IFG stimulation are actually driven by the concurrent modulation of neural activity outside of the IFG.Furthermore, while high-definition tDCS to the right IFG has been associated with an SSRT decrease 15, as well as between prEMG latencies and SSRTs17. In addition, we also found positive correlations between prEMG and P3 onset latencies. In sum, this suggests that earlier EMG activity is followed by earlier SSRTs, and an earlier onset of the P3. Furthermore, the correlations between these measures and reaction times in go trials were negative, in line with the notion that proactive slowing of behavioral responses can facilitate inhibitory control55. However, the markers differ noticeably in their estimated stopping latency  for further analysis. All participants were naïve to tDCS and reported no contraindications for electrical stimulation. In accordance with the Helsinki declaration, all participants provided written informed consent prior to participation, and everyone received monetary compensation. The study was approved by the institutional review board of the Department of Psychology, University of Oslo.The sample size was determined based on previous studies that found SSRT decreases related to anodal IFG stimulation in within-participant designs42. The tasks were a visual SST and a two-choice reaction time (CRT) task presented in alternating blocks. For this report, we focused exclusively on the SST  with concurrent EEG- and EMG-recordings Fig. , and a tSST Fig. . Each taBoth EEG- and EMG-activity were recorded using a BrainAmp system  Fig. . We used59. Then, EMG time courses were extracted for all trial types (−200 ms to +1600 ms relative to go-stimulus onset) and baseline corrected. The EMG activity was transformed and smoothed in the time-domain  and z-scored across all trials. The resulting EMG time courses reflect the ratio of a root mean square-transformed signal relative to baseline, z-scored relative to the total amount of EMG activity in all trials. Following this, trials where the average untransformed baseline activity exceeded 100 µV were defined as artifacts and excluded from further analyses. Due to electrical noise of the DC stimulator and for baseline estimation purposes only, the data was notch-filtered at 100 Hz and 200 Hz using a basic FIR filter with a −6 dB roll-off rate and passband edges of 95/105 Hz and 195/205 Hz, respectively. Following artifact rejection, an automated algorithm was used to detect the presence of EMG activity in successful stop trials. Specifically, an EMG response was detected if any time point between go-stimulus onset and the response window offset exceeded 1.2, i.e. activity that deviated from baseline with at least 1.2 SDs. The SD threshold was based on visual examination of the data, and detection algorithm performance was visually validated in a random subsample of trials. After this, the time courses were re-epoched (−200 ms to +800 ms relative to stop-stimulus onset), baseline corrected, and averaged across trials.EEG preprocessing consisted of visual identification and exclusion of time frames containing tDCS-related artifacts, re-referencing to averaged earlobes, low-pass-filtering (40 Hz), down-sampling (500 Hz), high-pass-filtering (0.1 Hz), ocular artifact correction based on independent component analysis, epoching (−200 ms to +800 ms relative to stop-stimulus onset), baseline correction and threshold based artifact rejection (absolute threshold = 120 µV). EMG preprocessing consisted of low-pass-filtering (250 Hz), down-sampling (500 Hz) and high-pass-filtering (20 Hz). All filtering was performed using the basic FIR filter implemented in EEGLAB60. From the EMG, we extracted the percentage of detected prEMG responses from successful stop trials, as well as the peak latency of these responses. Peak latency was extracted from the averaged prEMG time courses and defined as the maximum between stop-signal onset and the participant’s SSRT for that session and measurement. From the behavioral data, we extracted reaction times in go trials (goRTs), reaction times in unsuccessful stop trials (USRTs), SSRTs and average stop-signal delays (SSDs). To assess whether the SSRT estimation method influenced the results, we did the main analysis on SSRTs estimated using both the mean and the integration method with replacement of go omissions61. While the two methods provided slightly different estimates for the SSRT, the estimation method did not alter the conclusion, and therefore only the results of the integration SSRTs are reported.From the EEG, we extracted peak and onset latencies of the stop-P3 potential at electrode Cz. Peak latency was defined as the latency of the local maximum within 250–500 ms post-stop, while P3 onset latency was defined as the half-amplitude latency, i.e. the earliest latency at which the P3 exceeded 50% of its peak amplitude when tracking amplitudes backwards in time from the peak. This approach has been found to be a reliable onset estimation procedure for late potentials like the P3, with acceptable power for detecting relatively small differences in onset latency38, and Bayes factors (BF10) are reported. BFs express the relative likelihood of the data under two competing hypotheses, essentially providing an estimate of how likely the alternative hypothesis is compared to the null hypothesis39.All statistical analyses were performed within a Bayesian framework using the JASP softwareFirst, the data was assessed for outliers, defined as values with a z-score of +/−3.5. None of the participants qualified as outliers on any of the analyzed measures. Then, to ensure the validity of the horse-race model, individual paired-samples t-tests were performed comparing goRTs to USRTs for each condition and time point using a default Cauchy  prior.62 (rmANOVA), with the factors time  and condition . We used default priors, i.e. a multivariate Cauchy  distribution63, and set number of samples to 100 000 for precise BF estimation. BFs for main effects indicating at least moderate evidence in favor of the alternative hypothesis were followed up with post hoc tests, which are based on t-tests with a default Cauchy  prior. Sphericity was assessed using Mauchly’s W, and Greenhouse-Geisser estimated epsilon (ε) will be provided. However, as correction procedures for sphericity violations are not yet well developed within this Bayesian framework, no correction could be implemented. In these instances, BFs are presented alongside the corresponding corrected F- and p-values.Behavioral, EEG and EMG data were analyzed using two-way Bayesian repeated measures ANOVAsd exceeding 164, were removed prior to analysis. No statistics were calculated for the individual correlation coefficients. Rather, to get an indication of the stability of the direction and size of the association between different measures, the correlation coefficients were Fisher-z-transformed65. Then, the nine correlation coefficients obtained between each two measures  were tested together against the null hypothesis with a one-sample t-test using a default Cauchy  prior. Average r values were calculated after Fisher-z transform with correction for unequal sample sizes, and their 95% credible intervals was provided by Jasp. Both the average z and its credible intervals were back-transformed to r by calculating the hyperbolic tangent.To investigate the relationship between the different inhibition indices, we calculated pairwise correlations between SSRTs, prEMG peak latency, P3 peak latency and P3 onset latency separately for each condition and time point, which resulted in 9 correlation coefficients between any two measures. To explore the relationship between inhibition measures and go trial performance, we also calculated the correlations between goRT and P3 peak and onset latencies, as well as between goRT and the prEMG latency. Bivariate outliers, defined as highly influential values quantified by a Cook’s 42. Participants indicated the presence of a range of potential side effects using a scale from 1–4 (PRESENCE), as well as if they thought any experienced effects were caused by the stimulation using a scale from 1–5 (PROBABILITY). Estimates were obtained for each participant by averaging across their presence and probability scores separately. Presence and probability scores were analyzed using separate rmANOVAs with condition  as a factor and the default Cauchy priors.Lastly, as an evaluation of tDCS safety and condition blinding, we analyzed responses to a tDCS questionnaire


Physical literacy is a multidimensional concept that describes a holistic foundation for physical activity engagement. Understanding the utilization and effectiveness of physical literacy in the context of health and the health care setting will support clinical and population health programming. The purpose of this rapid scoping review was to: 1) map the conceptualization of physical literacy as it relates to health; 2) identify and describe the utilization of physical literacy in the context of health and engagement of health care providers; and 3) better understand the relationship between physical literacy, physical activity, and health.Following established scoping review methods adapted for a rapid review approach, we searched electronic databases Medline OVID, CINAHL Ebsco, PsycInfo Ebsco, Web of Science ISI, and ERIC Ebsco from conception until September 2019. Tabulation coding was used to identify the key themes across included articles and synthesize findings. The review follows an integrated knowledge translation approach based on a partnership between the health system, community organizations, and researchers.Following removal of duplicates, our search identified 475 articles for title and abstract screening. After full text review, 17 articles were included . There was near consensus among included papers with 16 of 17 using the Whiteheadian definition of physical literacy. There was limited involvement of health care providers in the concept of physical literacy. Physical literacy was connected to the following health indicators: BMI and body weight, waist circumference, cardiorespiratory fitness, physical activity, and sedentary behaviour. The primary demographic focus of included studies was children and there was a conceptual focus on the physical domain of physical literacy.Despite growing popularity, the empirical evidence base linking physical literacy and health outcomes is limited and the relationship remains theoretical. Physical literacy may present a novel and holistic framework for health-enhancing physical activity interventions that consider factors vital to sustained participation in physical activity across the life course. Future work should continue to explore the nature and direction of the relationship between physical activity and physical literacy to identify appropriate focused approaches for health promotion. Physical literacy is a multifaceted concept comprised of affective (motivation and confidence), physical , cognitive (knowledge and understanding), and behavioural  domains . These fAs a relatively new concept conceived by Whitehead in 1993, measuring and understanding physical literacy is of increasing interest in the fields of education, sport, recreation, and population health . Along wPhysical literacy is increasingly used as a tool to support population health in Canada with inclusion in ParticipACTION report cards  and as oHealth care providers are key messengers, advocates, and promoters of health. Integrating preventive medicine strategies, such as physical activity promotion, with primary care is challenging –22. SpecLinking multiple settings for promotion of physical activity increases the feasibility and likelihood of changing behaviour  and findHow does current literature define and/or conceptualize physical literacy as it relates to health?In what areas of the health sector is the term ‘physical literacy’ utilized and how are health care providers engaged with this construct?Does existing literature describe a relationship between physical literacy, physical activity levels, and improved health outcomes, and if so, what are the key findings?This rapid scoping review aims to develop an understanding of physical literacy within the context of health by answering the following research questions:https://physicalliteracy.ca/physical-literacy-for-communities-british-columbia-initiative/) and to inform implementation approaches for a regional physical activity strategy, aligned with provincial and federal objectives. Our scoping review follows the rigorous methodology established by Arksey and O’Malley [A rapid scoping review approach was used to collect and synthesize information describing how physical literacy is defined and utilized in the context of health literature, and to identify physical literacy interventions within the health sector. A rapid review technique was chosen because it allows for rapid collection of evidence to map the field of study to inform the health system and other stakeholders to support decision making –29. ThisO’Malley  with modO’Malley . The proO’Malley . AccordiO’Malley .The search strategy was developed by a health sciences librarian (TF) using key words and subject headings for physical literacy  and health  for screening based on inclusion and exclusion criteria. In line with a rapid review approach, items were screened by one reviewer (KC) in two stages: title and abstract, and full text –35. The Data extraction was performed using a standardized data extraction form in DistillerSR, iteratively revised after piloting and discussion with the research team. Data extraction for conceptual articles included study and author information, design of review or model development, definition or conceptualization of physical literacy used, and the nature of the relationship between physical literacy, physical activity levels, and improved health outcomes. The data extraction form for original research articles included additional extraction points including: the study setting and context, population and sample size, purpose and aim of study, definition or conceptualization of physical literacy, engagement of health care providers, the nature or characteristics of the intervention (where applicable), and key findings or study outcomes.Excel tables were used to organize the data and descriptive statistics were used to summarize the number of publications per year, country of origin, and study design . Tables n = 7). In 2019, there were five articles published. The majority of the research was published and conducted in Canada . Two articles were published in the United Kingdom, and one article each was published from Australia, China, Germany, and Austria [The electronic database search yielded 617 items total and 475 remained following removal of 142 duplicates. After title and abstract screening, the full texts of 64 articles were reviewed. Seventeen articles were included in the final sample. Twelve included articles were original primary research articles  used quantitative methodologies and two used qualitative approaches. Study designs were cross-sectional , 51n = 1 [n = 1; ), a mult [n = 1; ), a non- [n = 1; ), and a  [n = 1; ). The fi [n = 1; , 19, and [n = 1; , 54, 55. [n = 1; , 50, 51, [n = 1; , 46. One [n = 1; , and one [n = 1; .Sixteen of 17 included articles (94%) used the Whiteheadian definition of physical literacy: “physical literacy is defined as the motivation, confidence, physical competence, knowledge and understanding to value and take responsibility for engagement in physical activities for life” (p.11) . This isSeven included articles focused on the physical domain of physical literacy , 50, 51.n = 6) or PLAYbasic/PLAYfun (n = 2). Table Physical literacy was most commonly measured with a standardized questionnaire such as the Canadian Assessment of Physical Literacy  determine the definition and conceptualization of physical literacy as it relates to health in the current literature; 2) identify if health care providers are engaged with the construct of physical literacy and in what types of health care settings physical literacy is used; 3) describe the relationship between physical literacy, physical activity, and health. Synthesis of 17 included articles suggest consensus for the definition of physical literacy, a predominant focus on the physical domain of physical literacy, and little meaningful engagement of health care providers in the construct of physical literacy to promote health.With only one exception, there was consistent use of the Whiteheadian or International Physical Literacy Association definition of physical literacy among included articles. The remaining article used the term ‘fundamental movement skills’ and provided no definition of physical literacy . The finPhysical literacy is a cluster of domains  conceptually linked together. As individual constructs, they are commonly separated or prioritized depending on context or target population. Although this separation may help with measurement from a research and evaluation perspective, it may diminish the holistic intent and philosophical underpinnings of the concept as originally envisioned . The domOriginal research studies and systematic reviews within the sample identified positive changes to physical literacy can be made using interventions that target all four domains of physical literacy in children, youth, and adults , 46, 52.The development of physical literacy is based on engagement in activities in a variety of environments and the fundamental need to participate in movement experiences that are safe, nurturing, rewarding, and enjoyable to promote confidence and motivation . Among tFindings from this review suggest health care providers are not engaged with the construct of physical literacy. The absence of literature examining how health care providers are engaging with physical literacy in practice may indicate the area is understudied, or articles are not being formally published in the academic literature. Nonetheless, this work indicates a gap in the literature examining the application and utilization of the concept of physical literacy in health care practice. If we are to collectively advance the construct and usefulness of physical literacy in health care settings, then we need to understand how health care providers engage with the concept. The healthcare setting is an important environment for the promotion of physical activity, with strategies that include referrals, exercise prescriptions, and brief counselling interventions . Most prFindings from this rapid scoping review yielded valuable information about the scope of literature in the physical literacy landscape. Physical literacy as a body of research is expanding, with research actively being pursued and published. Current and recently published works from 2019 were included in the sample; however, given the literature search for this work was conducted in September of 2019, items published within the last quarter of 2019 were not included. Recent literature searches in December of 2019 have concluded articles of value to this rapid review are actively being published. Such is the case with a recently published article by Jefferies, Ungar, Aubertin, and Kriellaars  who demoThis rapid review has identified key knowledge gaps. First, we recommend research dedicated to exploring the understudied domains of physical literacy - affective, cognitive, and behavioural - not only in children, but across the lifespan. While seven studies focused on physical literacy in children, only two articles in the original research sample studied physical literacy in adults , 46 and In order to meet timelines and following other established rapid review approaches , 71, we Health care practitioners are not engaged with the construct of physical literacy in practice;Greater emphasis is placed on the physical domain of physical literacy, leaving the remaining domains  underrepresented and understudied;There is evidence to support a relationship between the physical domain of physical literacy and improved health outcomes, although the directionality of this relationship is unknown.Based on tabulation coding and synthesis, the key themes and findings identified from the included literature are:This review advances understanding of the concept of physical literacy as it relates to health and the health care setting. Although there are emerging efforts to understand measurement of each individual domain of physical literacy, the utilization of this concept in the context of health is not well established or understood in the academic literature. The nature and direction of the relationship between physical literacy, physical activity, and health requires further exploration with consideration of the theoretical underpinnings of physical literacy as a holistic concept. This work is needed to clarify the role of physical literacy as a catalyst for promoting physical activity, decreasing the burden of disease, and increasing health and well-being.Additional file 1. ProtocolAdditional file 2. PRISMA-ScR checklistAdditional file 3. Search strategy


The features of a logically sound approach to a theory of statistical reasoning are discussed. A particular approach that satisfies these criteria is reviewed. This is seen to involve selection of a model, model checking, elicitation of a prior, checking the prior for bias, checking for prior-data conflict and estimation and hypothesis assessment inferences based on a measure of evidence. A long-standing anomalous example is resolved by this approach to inference and an application is made to a practical problem of considerable importance, which, among other novel aspects of the analysis, involves the development of a relevant elicitation algorithm. Thus, it is argued in It is relevant to ask what characteristics should be required of a theory of statistical reasoning. The phrase In k quantitative predictors G is a known cdf and In The main theme of the approach discussed here for (ii) centers around being clear about how statistical evidence is to be measured and, as will be seen, this has implications for (i) as well. Certainly, the concept of statistical evidence plays a key role in the development of the subject, but, as discussed in Chapter 3 of , it can There are many others who have also focused on treating statistical evidence and its measurement as a central concept in the subject. Jeffreys’ earliest papers focus on this , and thevidence concerning answers to (E) and (H). The purpose of statistical theory is to provide a reasoning process that can be applied to d to determine what the evidence has to say about (E) or (H), namely, produce an estimate of the quantity based on the evidence or assess whether there is evidence either in favor of or against the hypothesized value. In addition, as is widely recognized, estimation and hypothesis assessment should also produce a measure of the accuracy of the estimate and a measure of the strength of the evidence for or against the hypothesis. Answering (E) and/or (H) is called statistical inference and a sound, logical theory of statistical inference, which contained the minimal ingredients possible, can be viewed as a major goal of the subject.When concerned with the foundations of statistics, it is reasonable to ask: what is the purpose of statistics as a subject or what is its role in science? To answer this, consider a context where an investigator has interest in some quantity and either wants to know (E) the value of this quantity or has a theory that leads to a specific value for the quantity and so wants to know (H) if this value is indeed correct and so test the theory. In addition, the investigator has available data Any theory that does not lead to specific answers to (E) and (H) or is dependent on ingredients or rules of reasoning that are not well-justified is unsatisfactory. In the end, the believability of the inferences drawn is entirely dependent on the soundness of the theory that produced them. Thus, statistics is not an empirical subject like physics, where conclusions can also be assessed against the empirical world, but is more like an extension of purely logical reasoning to contexts where the data does not lead to categorical answers to (E) and (H) and so produces uncertainty. The view is taken here that we want to maintain a close relationship between a theory of statistical reasoning and the theory of logical reasoning. This has a number of consequences with perhaps the most important being that it implies a separation of the assessment of the appropriateness of the ingredients specified to a statistical analysis beyond the data, and the theory producing the inferences. The ingredients play the role of the premises and the theory of statistical inference takes the role of the rules of inference used in a logical argument. The separation of these aspects of a logical argument has been understood since Aristotle (see ).There are two main theses of the argument developed here: (I) all ingredients to a statistical analysis must be checkable against the data and (II) the theory of inference must be based on a measure of statistical evidence. The rationale for (I) and (II) are now considered with (II) discussed first, as it plays a key role.The concept of the evidence in the data is clearly of utmost importance to statistical reasoning. There is no need, however, to provide a measure of the total evidence contained in the data, for the measure of evidence only has to deal with (E) and (H) for the quantity of interest. The measure of evidence must clearly indicate whether there is evidence for or against any specific value of the quantity of interest being the true value. This follows from the desired relationship with logic, as the rules of logical inference assume the truth of the premises, so the theory of statistical inference has to be based on the truth of the ingredients and this implies that one of the possible values for the quantity of interest is true. A theory of logical reasoning that could only determine falsity and never truth is not useful and similarly any valid measure of evidence must be able to indicate evidence in favor as well as evidence against.Once a measure of statistical evidence is determined, an estimate of the quantity of interest is necessarily the value that maximizes the measure of evidence and the accuracy of the estimate can be assessed by looking at the size of the set of values that has evidence in their favor. The measure of evidence similarly necessarily determines whether there is evidence for or against a hypothesized value and the strength of this evidence can be assessed by comparison with the evidence associated with the other possible values for the quantity of interest.assumed hereafter that the data f is unknown and it is assumed that, once f is known, then this completely determines the answers to (E) and (H). The ingredients are then as follows: it is assumed that assumed that there is a probability measure Consider now requirement (I). If a satisfactory measure of evidence could be determined from the data alone, then this would be ideal, but currently this is not available and it is questionable whether it is even possible. It is It can be questioned as to whether both the model and prior are necessary for the development of a satisfactory theory and certainly minimizing the ingredients is desirable. However, as discussed in It is not clear how the ingredients are to be chosen and guidance needs to be provided for this. Not much has been written about how the model is to be chosen, but certainly something needs to be said to justify a specific choice as part of the statistical reasoning argument. Much more has been written about the selection of the prior and the position is adopted here that it is necessary to base this on a clearly stated elicitation algorithm, namely, a prescription for how an expert can translate knowledge into beliefs as expressed via the prior.In summary, the desiderata for a theory of statistical reasoning include the following: a methodology for choosing a model, an elicitation algorithm for selecting a prior, methodology for assessing the bias in the ingredients chosen, model checking and checking for prior-data conflict procedures and a theory of inference based upon a measure of statistical evidence.Choosing and checking the ingredients logically comes before inference, but it is convenient to discuss these in reverse order.Consider now a statistical problem with ingredients the data p-values, namely, there is no obvious dividing line between evidence for and evidence against. Moreover, it is to be noted that probabilities measure belief and not evidence. If we start with a large prior belief in principle of conditional probability to update beliefs after receiving information or data and this is to be regarded as the first principle of the theory of relative belief.As discussed in principle of evidence: if change in belief rather than belief. A number of measures of this change have been proposed  and, in the discrete case . In  establisRelative belief prediction inferences for future data are naturally produced by using the ratio of the posterior to prior predictive densities for the quantity in question. The following example illustrates this and demonstrates significant advantages for relative belief.Example 1.Prediction for Bernoulli sampling.f future observations n independent tosses Consider an example discussed in Chapter 6 of  who furt…,yf) ismn,f isRB≤oshonov [MT(mT(t)≤oshonov [MT(mT(t)≤The following example, based on real data, is used to illustrate each aspect of the approach to statistical reasoning recommended here.Example 2.Bioassay experiment.T given age (see ). The doIn , a goodnG is the standard logistic cdf and the prior is given by the Elicitation of a prior can be difficult when the interpretation of the parameters is unclear. For example, with model , it is nk of the The strange behavior of diffuse normal priors has been noted by others. Bedrick, Christensen and Johnson ,25, baseFollowing ,25, prioloyed in  to deterj simply because Another reason for allowing the elicitation procedure to be independent of the observed The second way in which our approach differs from previous developments is that ctly how  translatote that  is equivk-cell k-dimensional vector of ones, which implies The task then is to determine  so that  is satisi achieves this, but clearly this choice does not reflect what is actually known about the probabilities. As might be expected, the choice of the Given that the tisfying . For exaG by a normal cdf (see Examples 3–5). Suppose then that at least one of Since res that  is satisatisfiesΦG−1.In this example, Let us suppose that an expert believes with virtual certainty that the true probabilities lie in the intervals o, using , the larConsider applying the approach discussed in Example 7.Bioassay experiment (Example 2 continued).T and Consider whether or not there is bias induced by the prior in Example 6 with respect to the hypothesis Now, The relative belief ratio for 2, which  implies For given Algorithm 1: Algorithm(i)simultaneously estimate the values ple from  and stor(ii)simultaneously estimate the values (iii)T and then estimate using the values in these two tables estimate The bias in favor can be estimated at In general problems, the approach to the computations used here will not be feasible and so alternative methods are required. In certain examples, some aspects of the computations can be done exactly, but, in general, approximations such as those discussed in  will be Consider now checking the prior derived in Example 8.Bioassay experiment (Example 2 continued).The tail probability for checking the prior is given byMT.Consider first the assessment of the hypothesis i-th coordinate of this joint estimate is not necessarily the value that has the greatest evidence in its favor, rather this is obtained by maximizing To obtain the joint relative belief estimate of The value of Implementing this for An interesting phenomenon occurs when considering the estimation of shown in  for RB2(As long as it is possible to sample from the posterior for a 1-dimensional parameter, then the computations necessary for the inferences for such a parameter are feasible. As such, the Gibbs sampling algorithm of  is partiCriteria for a satisfactory theory of statistical reasoning have been developed. Perhaps more should be required, but it seems that those stated are necessary. In particular, the separation of the choosing and checking of the ingredients from the inference step has been emphasized as a key aspect based upon maintaining a desirable relationship with logical reasoning. An approach to statistical reasoning that satisfies these criteria has been presented. Application to a well-known example has shown that this approach can resolve anomalies/paradoxes that arise via commonly used methodology. Many other such instances of resolving inferential difficulties as well as results establishing optimal performance have been documented in . An appl