Despite the relatively high prevalence of low health literacy among individuals living with chronic obstructive pulmonary disease (COPD), limited empirical attention has been paid to the cognitive and health literacy–related skills that can uniquely influence patients’ health-related quality of life (HRQoL) outcomes.The aim of this study was to examine how health literacy, electronic health  literacy, and COPD knowledge are associated with both generic and lung-specific HRQoL in people living with COPD.Adults from the COPD Foundation’s National Research Registry (n=174) completed a cross-sectional Web-based survey that assessed sociodemographic characteristics, comorbidity status, COPD knowledge, health literacy, eHealth literacy, and generic/lung-specific HRQoL. Hierarchical linear regression models were tested to examine the roles of health literacy and eHealth literacy on generic (model 1) and lung-specific (model 2) HRQoL, after accounting for socioeconomic and comorbidity covariates. Spearman rank correlations examined associations between ordinal HRQoL items and statistically significant hierarchical predictor variables.R2=21%; F9,164=6.09, P<.001). Health literacy  was the only predictor positively associated with generic HRQoL (P<.001). Adding health literacy, eHealth literacy, and COPD knowledge as predictors explained an additional 7.40% of variance in lung-specific HRQoL . Following adjustment for covariates, both health literacy  and eHealth literacy  were positively associated with lung-specific HRQoL. Health literacy was positively associated with most lung-specific HRQoL indicators , whereas eHealth literacy was positively associated with 5 of 8 (60%) lung-specific HRQoL indicators. Upon controlling for confounders, COPD knowledge  was inversely associated with lung-specific HRQoL.After adjusting for confounding factors, health literacy, eHealth literacy, and COPD knowledge accounted for an additional 9% of variance in generic HRQoL (total adjusted Health literacy, but not eHealth literacy, was positively associated with generic HRQoL. However, both health literacy and eHealth literacy were positively associated with lung-specific HRQoL, with higher COPD knowledge indicative of lower lung-specific HRQoL. These results confirm the importance of considering health and eHealth literacy levels when designing patient education programs for people living with COPD. Future research should explore the impact of delivering interventions aimed at improving eHealth and health literacy among patients with COPD, particularly when disease self-management goals are to enhance HRQoL. Chronic obstructive pulmonary disease (COPD) is a leading cause of death in the United States, affecting up to 15 million US adults . An estiLiving with COPD can significantly affect physical, mental, and emotional domains of health-related quality of life (HRQoL) ; howeverPatients living with COPD generally receive little guidance in terms of how to recognize and avoid breathing exacerbations. Most patients can only answer about two-thirds of questions about their condition correctly , and 16%Low health literacy, or reduced capacity to understand, evaluate, and act on health information, is associated with worse self-management, more severe COPD, learned helplessness, and lower respiratory-specific HRQoL ,23. PuenAlthough there are multiple communication modes and channels for COPD patient education, many patients are left to primarily locate answers to their disease-related questions outside of primary practice settings through self-directed sources such as the internet and Web-based support groups ,29. A grAlthough lower health literacy is associated with poorer HRQoL in patients with COPD, we do not yet know which aspects of HRQoL may be most impacted by inadequate health literacy skills. Despite the relatively high prevalence of low health literacy among individuals with COPD, limited empirical attention has been paid to the cognitive and health literacy skills that can uniquely influence patients’ general health status (generic HRQoL) and health outcomes faced primarily by people living with COPD (lung-specific HRQoL). Therefore, it remains unclear whether distinct types of health literacy are associated with both generic and lung-specific HRQoL among adults living with COPD. In addition, very few studies have examined the role that eHealth literacy may play in affecting HRQoL in people living with COPD . The potHypothesis 1: Health literacy, eHealth literacy, and COPD knowledge will be positively associated with generic HRQoL among patients living with COPD, even after controlling for potentially confounding factors affecting HRQoL.Hypothesis 2: Health literacy, eHealth literacy, and COPD knowledge will be positively associated with lung-specific HRQoL among patients living with COPD, even after controlling for potentially confounding factors affecting HRQoL.Hypothesis 3: COPD knowledge will moderate the effect of health literacy on lung-specific HRQoL, such that higher COPD knowledge will significantly increase (or enhance) the effect of health literacy on lung-specific HRQoL.Hypothesis 4: COPD knowledge will moderate the effect of eHealth literacy on lung-specific HRQoL, such that higher COPD knowledge will significantly increase (or enhance) the effect of health literacy on lung-specific HRQoL.Adults from the COPD Foundation’s National Research Registry were recruited to participate. This confidential database includes individuals from all 50 states of the United States who self-report physician or specialist-diagnosed COPD. Enrolled individuals can opt-in to being contacted about potential research opportunities that are promoted for patients enrolled in the Registry. Patients who choose to opt-in complete informed consent documentation indicating that they agree to be contacted about potential patient-oriented research opportunities. Enrolled adults older than 40 years with a valid email address were eligible to participate in this study (N=1270). COPD develops most often in adults older than 40 years . Over thEligible participants received an email invitation to participate in a Web-based survey powered by Qualtrics. All eligible participants were required to provide electronic informed consent before completing the survey. Institutional Review Board (IRB) approval for the study was obtained from both a hospital-based regulatory body overseeing studies of Registry members, as well as a university-sponsored IRB. Participants were notified that their email address would be entered a random drawing to receive a small electronic gift card for their participation. Due to restrictions stipulating that registrants only be contacted once about opportunities to participate in research, the investigators were unable to recontact nonresponders (n=1071).living with comorbidities, whereas respondents indicating none of these other conditions were marked as not living with comorbidities.Demographic questions assessed several sociodemographic characteristics, including age (years), sex, race , marital status , and education level . Participants were also asked to affirm (yes/no) if they were currently living with 1 or more comorbidities . Respondents reporting any of these diseases/disorders were coded as COPD knowledge was measured using the Chronic Obstructive Pulmonary Disease Knowledge Questionnaire (COPD-Q) . The COPThe 3-item Health Literacy Screening Questionnaire (HLSQ)  was usedeHealth literacy was assessed using an 8-item rating scale called the eHealth Literacy Scale (eHEALS) . This brno problems (level 1) to some problems (level 2) to inability or extreme difficulty (level 3). Responses are used to quantify an individual’s unique health state by using a 5-digit descriptor ranging from 11111 for perfect health to 33333 for worst possible health. Weights are applied to score responses on each of the 5 domains and then converted to a single index value ranging from 0 to 1, where a score of 1 represents a perfect health state. This index value is based on a value set derived from a Time Trade Off valuation study reflecting data collected in the US population [no problems originally marked as level 1 were recoded to 3 to reflect higher self-report on HRQoL dimension). The EQ-5D is self-administered, written at a 7th-grade level and can be completed in 5 to 10 min [Generic HRQoL was measured using the EuroQol (EQ)-5D , an instpulation . For poso 10 min . Data co1 indicated significant difficulties on dimension of lung-specific HRQoL). Total possible CAT scores can range from 0 (mild) to 40 (very severe) [Lung-specific HRQoL was assessed using the COPD Assessment Test (CAT) . CAT is  severe) ,46. Amon severe) , which ir correlation coefficients.Frequency statistics were used to summarize categorical data, whereas means (SDs) were computed to describe interval data. Missing items from multi-item scales were mean-imputed if at least half of the scale items were completed. Correlations between main study variables were analyzed using Pearson F-test statistics were evaluated to determine statistically significant R2 changes in explained variance (%) at each step of the analysis. Unstandardized beta coefficients were examined for each control/predictor variable, and interaction effects were assessed by interpreting multiple R2 and adjusted R2. Tolerance and variance inflation factor (VIF) estimates for each hierarchical model were computed to ensure that tolerance estimates were below 0.10 and VIF were less than 10 [f2 is a useful measure of local effect size appropriate for hierarchical regression models [f2≥0.02, f2≥0.15, and f2≥0.35 represent small, medium, and large effect sizes, respectively.Hierarchical linear regressions were computed to examine the roles of health literacy and eHealth literacy on generic (model 1) and lung-specific (model 2) HRQoL by sequentially adding predictors into 2 blocks within each model. To control for the effects of demographic covariates and comorbidity status on the dependent variables of generic and lung-specific HRQoL, sociodemographic factors  and comorbidity (present/not present) were entered in block 1 as potential confounding factors affecting each type of HRQoL. Because we were primarily interested in the additional effects of COPD-related knowledge, health literacy, and eHealth literacy above and beyond these covariates, predictor variables were subsequently entered in block 2 of each model. To determine whether health literacy, eHealth literacy, and COPD knowledge provided any significant increment in the amount of variance explained in generic (model 1) and lung-specific HRQoL (model 2),  than 10 . In addin models , and thin models , f2≥0.02P<.05 considered statistically significant.Associations between ordinally scaled HRQoL items and statistically significant predictor variables from hierarchical analyses were assessed using Spearman rank correlation procedures. In the third  step of the hierarchical regression analyses, interaction terms of eHealth literacy×COPD knowledge and health literacy*COPD knowledge were entered in both models, one predicting generic HRQoL and another predicting lung-specific HRQoL. All statistical analyses were conducted using IBM SPSS Statistics version 24 , with values of Overall, 199 adults with COPD submitted responses to the Web-based survey. List-wise deletion was used to remove cases that contained missing data (n=25); therefore, responses from 174 of 1270 patients (response rate=13.70%) were analyzed. The mean score on HLSQ items measuring health literacy was 4.52 (SD 0.62), which was higher than self-reported scores on the 8-item eHEALS measure of eHealth literacy . On average, respondents answered almost 10  out of 13 questions correctly on the COPD-Q measuring knowledge related to COPD.r=.61, P<.001). More than 80% of the sample  reported living with at least one comorbidity.The mean EQ-5D score was 0.723 (SD 0.18) on the EQ-5D index scale measuring generic HRQoL from 0 to 1, whereas the mean score on the CAT measuring lung-specific HRQoL on a scale of 0 to 40 was 24.02 (SD 6.65), indicating moderate lung-specific HRQoL. EQ-5D index scores were positively associated with CAT scores (R2=13%) of the variance in generic HRQoL, F6,167=5.30, P<.001. b=.01, SE 0.001, P<.01) and higher education level  were associated with better generic HRQoL. Introducing health literacy, eHealth literacy, and COPD knowledge as predictor variables (step 2) explained an additional 9% of variance in generic HRQoL (adjusted R2=21%), F9,164=6.09, P<.001. After adjusting for confounding factors, health literacy  was the only predictor variable positively associated with generic HRQoL (P<.001). Cohen f 2 for the effects of health literacy, eHealth literacy, and COPD knowledge on generic HRQOL was 0.12, which is a medium effect size.In the hierarchical regression model examining effects of health literacy, eHealth literacy, and COPD knowledge on generic HRQoL, demographic characteristics and comorbidity (step 1) accounted for 16.0% (adjusted P<.05) associated with at least one EQ-5D dimension score. Older participants reported less difficulty managing pain/discomfort  and anxiety/depression . However, age was not significantly associated with mobility , self-care ability , or engagement in usual daily activities . Higher educational attainment was associated with better ability to wash or dress oneself , greater engagement in usual activities such as housework and family or leisure time , and less difficulty with pain and discomfort . Education level was not significantly associated with mobility or anxiety/depression, although the association between education and mobility approached statistical significance . Participants living without comorbidities reported significantly less pain and discomfort  but no significant associations with any other dimension of generic HRQoL. Higher health literacy scores were associated with significantly (P<.05) better scores on all 5 EQ-5D dimensions: mobility ; self-care ; usual activities ; pain/discomfort ; and anxiety/discomfort . eHealth literacy was positively associated with 3 generic HRQoL dimensions: mobility , self-care , and usual activities .R2=19.7%) of the variance in lung-specific HRQoL, F6,163=7.90, P<.001. P<.001), higher education level , and living with no comorbidities  were associated with better lung-specific HRQoL scores. Adding health literacy, eHealth literacy, and COPD knowledge as predictor variables (step 2) explained an additional 7.4% of variance in lung-specific HRQoL (adjusted R2=26.4%), F8,161=8.59, P<.001. After adjusting for potentially confounding factors, health literacy  and eHealth literacy  were positively associated with lung-specific HRQoL. Interestingly, after adjusting for confounding variables, COPD knowledge  was inversely associated with lung-specific HRQoL. In other words, higher COPD knowledge was related to lower lung-specific HRQoL among people living with COPD. Cohen f2 for the effects of health literacy, eHealth literacy and COPD knowledge on lung specific HRQoL was 0.13, which is a medium effect size.In the hierarchical regression model examining effects of health literacy, eHealth literacy, and COPD knowledge on lung-specific HRQoL, demographic characteristics and comorbidity status (step 1) accounted for 22.5% (adjusted P<.05) associated with at least three CAT item scores, except for COPD knowledge, which was not significantly associated with any CAT item. Increased age was associated with better symptom scores related to cough frequency , chest congestion , chest tightness , sleep quality , and energy level . Older participants also demonstrated greater confidence leaving home . Education level was positively associated (P<.05) with better scores on every CAT item, except for chest congestion . Participants without comorbidities reported less challenges with chest tightness , more confidence leaving home , and better energy levels . Health literacy was positively associated with scores on most lung-specific symptoms, including cough frequency , chest tightness , activity limitation at home , confidence leaving home , sleep quality , and energy level . eHealth literacy scores were also positively associated with over 60% (5/8) of the CAT items: chest congestion , chest tightness , activity limitations at home , sleep quality , and energy level .R2 change=.01, P=.10  only approached statistical significance (P=.055). Greater knowledge of COPD did not significantly increase (or enhance) the effect of health literacy on lung-specific HRQoL in this sample of patients living with COPD. Cohen f2 for the moderating effects of COPD knowledge on health literacy and lung-specific HRQoL was 0.12, which is a medium effect size.The interaction between COPD knowledge and health literacy (step 3) did not account for significantly more variance in lung-specific HRQoL than COPD knowledge and health literacy alone, 1, P=.10 . MoreoveR2 change=.01, P=.28  also did not account for significantly more variance in lung-specific HRQoL than COPD knowledge and health literacy did alone, 1, P=.28 . Greaterf2≥0.15) effect sizes according to Cohen’s guidelines [This study aimed to assess how health literacy, COPD-related knowledge, and eHealth literacy are associated with both generic HRQoL and lung-specific HRQoL for people diagnosed with COPD while controlling for the effect of comorbid conditions, socioeconomic status, education level, and other factors known to be associated with HRQoL. Overall, results provide support for the importance of considering both health and eHealth literacy levels when developing patient education and self-management support programs for people living with COPD. More specifically, results revealed that health literacy was significantly associated with all 5 EQ-5D dimensions measuring generic HRQoL, whereas eHealth literacy was associated with significantly better scores on 3 generic HRQoL dimensions . Both health and eHealth literacies were positively associated with lung-specific HRQoL; however, higher levels of COPD knowledge did not significantly enhance the impact of health literacy or eHealth literacy on lung-specific HRQoL. These results also signified approximately moderate  to previous studies. HRQoL is generally lower for individuals living with COPD compared with the general population . This stHowever, as this study showed, education and age were not significantly associated with all dimensions of HRQoL, as measured by the EQ-5D; therefore, more research should be conducted to better explain which dimensions are influenced by these variables and in what ways. Furthermore, after adjusting for confounding variables, including age and education level, only health literacy was found to be significantly associated with generic HRQoL. These findings are consistent with 2 previous research studies ,24 that Although the current investigation demonstrates a strong association between health literacy and general HRQoL, even when controlling for sociodemographic variables such as education and age, eHealth literacy and COPD knowledge were not statistically associated with all 5 EQ-5D dimensions. However, eHealth literacy was significantly associated with scores on 3 generic HRQoL dimensions, including mobility, usual activities, and self-care. Collectively, these dimensions reflect the ability of a patient to manage their illness, and prior research supports that higher levels of eHealth literacy can improve patient self-management of COPD . NeverthThe results regarding COPD knowledge support previous research findings that the transfer of disease-specific knowledge does not necessarily have a long-term impact on behavior change that could lead to improved quality of life for patients living with COPD . In factThe results, overall, showed that after adjusting for potentially confounding variables, health literacy and eHealth literacy levels were significantly associated with lung-specific HRQoL. The impact of distressing COPD symptoms, such as dyspnea, fatigue, coughing, anxiety, wheezing, pain interference, and breathlessness, can help explain much of the variance in lung-specific HRQoL among patients living with the disease -62. ThiseHealth literacy is also positively associated with patients’ lung-specific HRQoL in this sample. The eHealth literacy scores are comparable with those in other studies assessing eHealth literacy in the general older adult population , as a maAlthough eHealth literacy was positively associated with lung-specific HRQoL, it was not associated with generic HRQoL. Patients with COPD who use Web-based media for health-related purposes readily disclose unmet needs related to respiratory symptoms, including cough, mucus production, and dyspnea . Rather Greater COPD knowledge did not enhance the effect of health literacy or eHealth literacy on general or lung-specific HRQoL. COPD knowledge, however, was inversely related to lung-specific HRQoL; therefore, the higher the knowledge level, the lower was the self-reported lung-specific HRQoL of study participants. This finding was not anticipated, but one explanation for this result is that even with increased knowledge of the disease, patients might lack the skills or self-efficacy to change their behaviors that are linked to one’s disease state, impacting their lung-specific HRQoL. In addition, it is possible that more knowledge related to the serious diagnosis may result in higher levels of anxiety, fear, and even depression, which could, in turn, negatively affect their general and/or lung-specific HRQoL .This study has several limitations related to recruitment techniques employed, a low sample size, and lack of a representative sample. Despite collaborating with the COPD Foundation’s National Research Registry, this Web-based survey had a low response rate of patients with COPD (13.7%) as compared with other internet surveys conducted with the general population . Our recThe statistically significant associations found in this cross-sectional study cannot be used to establish cause-and-effect relationships; however, use of hierarchical predictor variable entry provided some advantages when attempting to identify relationships between health/eHealth literacy, COPD knowledge, and relevant health-related outcomes. The construct of eHealth literacy was measured with eHEALS, a widely used scale that has been questioned in the age of new media where communication technologies such as social media are pervasive ,69. StudIn addition, low socioeconomic status minorities living with COPD were underrepresented. Most participants in this study identified as being white and highly educated, which is not reflective of the sociodemographics of COPD . As mentAlthough previous research has shown a relatively high prevalence of low health literacy among individuals living with COPD, little empirical attention has been directed at exploring the cognitive and health literacy–related skills that can influence patients’ HRQoL. Findings from this study indicated that health literacy, but not eHealth literacy, was positively associated with generic HRQoL. In addition, health literacy and eHealth literacy were found to be positively associated with lung-specific HRQoL, with higher COPD knowledge associated with lower lung-specific HRQoL. These results confirm the importance of considering patient health and eHealth literacy levels when designing self-management support programs for people living with COPD. Future research should explore the impact of delivering COPD interventions aimed at improving eHealth and health literacy, particularly when self-management program goals include improving HRQoL outcomes.


In the past decades, the scientific quality of biomedical studies has been hierarchically depicted in the well-known pyramid of evidence-based medicine (EBM), with higher and higher levels of evidence moving from the base to the top. Such an approach is missing in the modern crop protection and, therefore, we introduce, for the first time, this novel concept of evidence-based phytoiatry in this field. This editorial is not a guideline on plant protection products (PPP) registration, but rather a scientific and technical support for researchers involved in the general area of plant pathology, providing them with evidence-based information useful to design critically new studies. Journal of American Medical Association (JAMA), referring to the use and the critical appraisal of the best scientific evidence to support clinical decision-making. This idea purported that all medical activities intended for diagnosis, prognosis and therapy should be based, not primarily on clinical experiences, but on solid scientific evidences coming from clinical research. Since then, EBM approach has continued to grow and spread, taking a pivotal place beside the competence of the clinician and the care preferences of the single patient.The term “evidence-based medicine” (EBM) was first introduced in 1992 in the This new way of thinking and acting now accounts the most updated evidence resulting from methodologically rigorous studies, mainly randomized controlled clinical trials (RCTs) and systematic reviews, which correspond to the highest level of scientific quality and represent the top of the EBM pyramid . The basIn the EBM, the clinician is trained to identify the best scientific evidence currently available on a medical issue, after constructing an appropriate research question and using the reference database for medical literature (PubMed) for reviewing studies. To construct the clinical question, EBM proposes the PICO strategy, where P stands for Patients (with a particular condition or disease), I for the Intervention of interest , C for Control or Comparison  and O for Outcome (the expected results coming from the intervention).In the phytoiatric/phytopathological area, an evidence-based approach is still missing. Similar to the medical sciences, the efficacy of plant protection products can be assessed with diverse experimental designs each with different levels of scientific evidence. In general, active substances are initially assayed with in vitro tests evaluating their biostatic/biocidal activity on cultivable plant pathogens. To the next level, in planta experiments in controlled environments, i.e., phytotron cabinets, growth chambers, greenhouses and screenhouses, can be carried out to test the efficacy of both active substances and agrochemicals on model pathosystems as well as obligate pathogens. In these experimental conditions, phytotoxicity and adverse effects on non-target plant species can also be evaluated. Overall, in vitro and in planta experiments (pre-open field studies) can be compared to in vitro/in vivo preclinical research of biomedical area, at the base of the evidence-based phytoiatry pyramid . FollowiOf course, to design and perform an open-field trial is complex, and a number of general principles should be followed. First, the concept of Good Plant Protection Practice (GPP) was defined by the European and Mediterranean Plant Protection Organization (EPPO), a specific set of recommendations including guidelines on decision-making for choice of active substances and formulations, dosage (and appropriate volume), number of applications, timing or frequency of applications, equipment and method of application . In addiNot last, systematic reviews  are not used in phytoiatry/plant pathology research as a powerful tool to reach the highest level of evidence in a specific phytosanitary issue. Therefore, we believe that the plant protection sector can neither be apart from considering that different levels of scientific evidence actually exist nor disregard a modern evidence-based approach.


Age-related frailty is a multidimensional dynamic condition associated with adverse patient outcomes and high costs for health systems. Several interventions have been proposed to tackle frailty. This correspondence article describes the journey through the development of evidence- and consensus-based guidelines on interventions aimed at preventing, delaying or reversing frailty in the context of the FOCUS (Frailty Management Optimisation through EIP-AHA Commitments and Utilisation of Stakeholders Input) project (664367-FOCUS-HP-PJ-2014). The rationale, framework, processes and content of the guidelines are described.The guidelines were framed into four questions – one general and three on specific groups of interventions – all including frailty as the primary outcome of interest. Quantitative and qualitative studies and reviews conducted in the context of the FOCUS project represented the evidence base. We followed the GRADE Evidence-to-Decision frameworks based on assessment of whether the problem is a priority, the magnitude of the desirable and undesirable effects, the certainty of the evidence, stakeholders’ values, the balance between desirable and undesirable effects, the resource use, and other factors like acceptability and feasibility. Experts in the FOCUS consortium acted as panellists in the consensus process. Overall, we eventually recommended interventions intended to affect frailty as well as its course and related outcomes. Specifically, we recommended (1) physical activity programmes or nutritional interventions or a combination of both; (2) interventions based on tailored care and/or geriatric evaluation and management; and (3) interventions based on cognitive training . The panel did not support interventions based on hormone treatments or problem-solving therapy. However, all our recommendations were weak  due to the limited available evidence and based on heterogeneous studies of limited quality. Furthermore, they are conditional to the consideration of participant-, organisational- and contextual/cultural-related facilitators or barriers. There is insufficient evidence in favour of or against other types of interventions.We provided guidelines based on quantitative and qualitative evidence, adopting methodological standards, and integrating relevant stakeholders’ inputs and perspectives. We identified the need for further studies of a higher methodological quality to explore interventions with the potential to affect frailty. The term ‘frailty’ has been used to describe an age-related state of decline and vulnerability characterised by weakness and decreased physiological reserve . Frail oAlthough the use of different definitions leads to the identification of different target populations and leads to a variation in the estimate of the actual prevalence of frailty , 6, the To add to the international efforts to reduce the impact of frailty, we conducted the FOCUS (Frailty Management Optimisation through EIP-AHA Commitments and Utilisation of Stakeholders Input) project, funded by the European Union’s Third Health Programme 2014–2020) , 9. The 4–2020 , At the time of designing our project, we recognised the need to offer patients, their formal and informal carers, healthcare practitioners, and decision-makers a scientific support to their actions, by bringing together scientific evidence and stakeholder perspectives into recommendations that responded to the definition of clinical guidelines , 18. In This correspondence article presents the development process of our FOCUS guidelines, providing their justification, with emphasis on their novelty, limitations and implications.We started by formulating the questions to be answered by the guidelines, based on the PICO format  Table 22. While We adopted the GRADE  Working Group system to assess the certainty of evidence and define the strength of related recommendations , 26. In The development of our guidelines was preceded by a series of quantitative and qualitative studies performed within the FOCUS project, reported in separate publications –16, whicThe guideline panel included the FOCUS project investigators with a background in health and social sciences as well as expertise in frailty, aging and health research methods. Most of them are members of the European Innovation Partnership on Active and Healthy Ageing (EIP-AHA) . Table SOf the 13 FOCUS project investigators who were given the role of voting panellists, 11 participated in the voting process. All criteria for all questions were covered by the voting, but with a few missing votes, which were evenly distributed across criteria and questions. We provide an example of the voting outcome, based on the iEtD output and with the addition of the panel’s comments and technical team’s annotations .The recommendation stems from the belief, common among different stakeholders and endorsed by the guideline panel, that frailty as an outcome is important and that interventions explicitly conceived to address it are needed. We found some quantitative evidence for different interventions being associated with delaying the progression of frailty or reverting frailty, although the effects were moderate in their size at maximum. These interventions, based on either a mainly physical concept of frailty or on a more comprehensive view, could be potentially fair, acceptable and feasible from a population perspective. However, the strength of this recommendation is weak/conditional because of the low certainty/quality of the quantitative evidence, due to substantial study limitations, inconsistency and heterogeneity across studies  as well as imprecision of the estimates.The level or extent of frailty was expected to act as an effect modifier of interventions on frailty, i.e. affecting their relative effect, because of several reasons. For instance, some interventions are expected to work only or more in the presence of a certain deficit status. On the other hand, being frailer might affect the opportunity to benefit from interventions that either require an active participation or work only in less severe illness states. In fact, among the studies examined in our systematic review , those tThe panel judged the implementation of strategies to monitor (and then improve) the adherence to the intervention as important, in particular in the case of interventions that require an active participation of the older person. The need to implement an effective evaluation plan of the interventions was also emphasised. In the FOCUS project, we aimed to analyse the initiatives (i.e. commitments or Good Practices) within the EIP-AHA  in orderR1 – We suggest implementing physical interventions, including physical activity/exercise, nutritional interventions, and a combination of exercise and nutritional interventions, to prevent or delay the progression of frailty or to reverse frailty . The recommendation is stronger for group-based supervised exercise programmes, either alone or in association with nutritional supplementation.We found quantitative evidence supporting the success of physical interventions in delaying the progression of or revert frailty, especially when frailty was defined according to a physical paradigm or measures of its physical component. This component, according to older people’s opinions collected through our qualitative studies Table , althougAmong the studies on physical interventions included in our systematic review , those tR2 – We suggest implementing interventions based on tailored care and/or Geriatric Evaluation and Management (GEM), to prevent or delay the progression of frailty or to reverse frailty . The recommendation is stronger for GEM-based interventions involving a multidisciplinary team, especially in inpatient clinical settings, but still conditional to the confirmation from further studies of good quality.We found some quantitative evidence for interventions based on a tailored care concept and/or on GEM being able to delay the progression of or revert frailty, as defined according to either a mainly physical paradigm or a multidomain paradigm. Some studies also reported on the impact of these interventions on frailty-related outcomes like functional ability, quality of life and hospitalisation , and on exercise combined with diet consultation, at least in prefrail populations. At present, the panel does not suggest adopting interventions based on hormone therapy or on problem-solving therapy with the aim of preventing or delaying the progression of frailty or of reverting frailty . Currently, there is no evidence in favour or against other interventions that could potentially be effective on frailty .Interventions included in this last question were assessed separately because of their heterogeneity. Only one study per intervention was available. The panel judgment was mainly based on the quantitative results of these single studies and their quality, along with considerations regarding values, equity, acceptability and feasibility that could apply to each intervention separately. Thus, the evidence was judged as uncertain and the recommendations were made with weak strength, conditional to the confirmation from further studies.All the studies relevant to this question were performed on a population definable as prefrail; therefore, no subgroup considerations could be made.This paper presents evidence- and consensus-based clinical guidelines on interventions to prevent or treat frailty, developed in the context of the FOCUS project. This was a core objective of the project, i.e. an ultimate deliverable in which the quantitative and qualitative research studies conducted in context of the project converged, and also represented the content of the service we intended to deliver in our proposal. To achieve such a pivotal objective, we required a solid methodological structure and the involvement of the entire FOCUS consortium to act as the guideline panel. We developed four guidelines based on one overarching question concerning interventions for frailty in general and three sub-questions on specific groups of interventions. Each guideline includes a recommendation on whether and how interventions should be implemented.the main areas of interest that policy makers at Member State level would need to support in order to tackle frailty” [Our work has distinctive characteristics among other initiatives that have been undertaken to help clinicians and patients make informed decisions in the context of frailty. For instance, in 2015, the EIP-AHA – Action Group A3 produced a Decalogue on Frailty Prevention as a result of the work conducted by the group in the period 2012–2015, which includes ten key messages focusing on “frailty” . Before frailty” . Both offrailty” . Startinfrailty” , 37. At Our work has recognised limitations. The main limitation to the production of definitive guidelines was related to the quantitative evidence base. The evidence available was of low quality due to methodological bias, inconsistencies and imprecision in the existing studies. In addition to the low quality of the collected evidence, there was a high level of methodological heterogeneity, which had already prevented any quantitative synthesis in our systematic review . The divThe ultimate lesson we learned with our 3-year work is that, while stakeholders showed awareness of and place relevance to the challenge represented by age-related frailty, the current scientific quantitative evidence still has important limitations. This was reflected in our guidelines, which could include only weak or conditional recommendations. Even if such types of recommendations might seem less appealing or helpful, they do yield an important message to the clinician and decision-maker, i.e. to be considered when these interventions are adopted, or indeed, to give consideration to when and whether to adopt them. This message reflects the limitations of the scientific literature and important implementation considerations. Our work also conveys an important lesson to the researcher – while the evidence heterogeneity could never be eliminated since it reflects the heterogeneity in the definition of frailty itself, we need more studies which specifically recognise and measure frailty as an outcome as well as greater adherence to high methodological standards. This is true in general, but in particular for studies on comprehensive frailty interventions, which have the potential to be effective, especially when defined holistically, and have so far not been adequately evaluated. We also need more studies to compare different interventions. The fact that most of the studies included in our evidence base compared the experimental intervention with ‘usual practice’, which can differ dramatically from reality to reality, made the findings extremely context bound. This generated the need to include, in our guidelines, not only an answer to the question ‘does it work?’ but also a consideration of the circumstances of success.Herein, we delivered evidence- and consensus-based guidelines on interventions that can affect frailty as an outcome. We recognised that these are not conclusive; rather, they should foster further studies, both on those interventions already investigated in the literature but requiring higher research standards as well as on potentially effective interventions that have not been appropriately studied thus far. On the other hand, our recommendations should start informing practices. In the context of the FOCUS project, we ended our project by testing the feasibility and impact of our guidelines when used to inform clinical decisions and help implement or refine interventions addressing frailty as a patient-important outcome; the results of these proof-of-concept pilots are currently in preparation for publication .Additional file 1. Synthesis of quantitative evidence from the FOCUS systematic review [c review , showingAdditional file 2. Narrative synthesis of the effect of interventions on secondary outcomes, as offered to the guideline panellists.Additional file 3: Table S1. Table that describes the members of the FOCUS Guideline Panel and their role in the development of the guidelines.Additional file 4. Example of the output of the voting process using the Evidence to Decision template, as received and processed by the guidelines technical team.Additional file 5. Detailed justification for the judgement upon each Evidence to Decision criterion, for each guideline.


E-Synthesis, a Bayesian framework for causal assessment. Computational results regarding dose-response evidence are shown at the end of this article.Today’s surge of big data coming from multiple sources is raising the stakes that pharmacovigilance has to win, making evidence synthesis a more and more robust approach in the field. In this scenario, many scholars believe that new computational methods derived from data mining will effectively enhance the detection of early warning signals for adverse drug reactions, solving the gauntlets that post-marketing surveillance requires. This article highlights the need for a philosophical approach in order to fully realize a pharmacovigilance 2.0 revolution. A state of the art on evidence synthesis is presented, followed by the illustration of  The problem of collecting, analyzing and evaluating evidence on pharmaceutical safety is a central problem of health-care practice. Statistics on drug-induced hospitalizations range between 5% and 10% of total hospitalizations in Europe as well as in all Western countries ,3,4,5,6.In this landscape, evidence synthesis is now rising as a robust approach, especially in the field of post-marketing drug safety. This trend stems mainly from a public interest towards the integration of information coming from different sources when evaluating safety signals  No 1235/2010; see also the 21st Century Cures Act, recently enacted in the US). An analogous wish has also been expressed by researchers in the field ,17, and,E-Synthesis”, a tool encoded through a Bayesian network able to robustly screen and amalgamate evidence of different types  that are combined together in order to form the “critical mass” needed to make decisions about the approval/withdrawal of a particular drug for/from the market DifferencPD)Probabilistic dependence . Probabe, e.g., ): The coe, e.g., ) discussDR)Dose-response relationship  monotonic growth for a significant portion of the range Rate of growth  systematic relationship between D and E. RoG, DR, PD are semantically and epistemically related and we refer to them as “statistical black-box indicators”, denoted by Σ.The indicators of causality M)Mechanistic Knowledge Time course , which can refer to temporal order, distance, or duration. If D causes E, T must hold (as a necessary condition): © ⇒ T. T remains an imperfect indicator, nevertheless, because temporal precedence is also compatible with ¬(D causing E) while D and E are connected by a common cause or through reversed causation. Hence T ⇒ © does not necessarily hold.According to our view, study design determines the kind of information that the evidence is able to provide us, hence in the following we define the evidence as a function of the kind of information it delivers: That is, the causal indicator it “speaks” to.We associate study designs with causal indicators as follows: RCTs provide information about difference making, time course, possibly also dose-response relationship and rate of growth. Cohort studies provide evidence of time course and statistical association (Σ). Case-control studies provide information about Σ only. Individual case reports cannot provide information about statistical association, but they provide very detailed information about time course and possibly difference-making whenever this can be established with confidence . E-Synthesis many indicators of causality contribute to the assessment of pharmacological risk. Among them, we decide in this part to focus on Σ, and, in particular, on the DR arm. This choice is motivated by the fact that dose-responsiveness has been investigated for a long time as a manifest signal of pharmaceutical harm in pharmacosurveillance [As outlined above, in eillance  (non-doseillance ).E-Synthesis by applying it to a case study: The debated causal association between paracetamol and asthma. We focus here on the DR arm. [DR and T. The study reports a prospective cohort study for women in which, between 1990 and 1996, 73,321 subjects were included in the analysis. Proportional hazard models included age, race, socioeconomic status, body mass index, smoking, other analgesic use, and postmenopausal hormone use. During 297,282 person-years of follow-up, 299 participants reported a new physician diagnosis of asthma meeting diagnostic criteria  and E-Synthesis is able to process the given evidence, but this process occurs through the mediating “lenses” of an evaluation of research studies, meaning that all the available evidence has always been analyzed ab initio by other researchers.In  we prese DR arm.  is a stueria see . For thiDR arm, what we would like to compute is thus:Nevertheless, from a more general point of view, a preferred approach would be to compute the above probabilities directly, by treating the evidence at glance. If we focus on the DR evidence with the final goal of making a sound estimate of such probability. Regarding this problem, in recent years an extensive literature has been developed not directly in the realm of pharmacosurveillance but more specifically for dose-finding assessment, a task that is usually targeted in Phase II of clinical research. In [Hence, a key question here is which may be the most suitable computational methods to be implemented to process arch. In , an algop-values in such test is analyzed in [Given our interest in pharmacovigilance, we will focus only on the “MCP” step. The mentioned test for trend is a data analysis procedure able to demonstrate a dose-response association between the risk factor (drug prescription) and the outcome (adverse event), even if the association is not statistically significant for any particular level of exposure. A clear description of this test  is presented in , whereaslyzed in .DR pattern. As shown in P(data|θ) where θ represents a set of parameters embodied in a statistical model f(id|θ) that defines the possible functional patterns of dose-responsiveness exhibited in Since its introduction in , the MCPid represents the dose-level, in the number of subjects in each dose-group, iy the number of subjects with effect in the corresponding dose-group and ir is the dose-response computed as the ratio iy/in. The index i is a natural number less or equal to G, the number of dose-groups.In this formula, f(id|θ) = k where k is a real number subjected to the following bound: 0 ≤ k ≤ 1. Among all the possible values of k, it is possible to calculate the optimal one (r) data. That can be achieved by solving this problem:We exploit Equation  to compur) data. , i.e., which functional pattern of dose-responsiveness has to be used in Equation (P(DR), that is the a priori probability of dose-responsiveness. This probability can be estimated through clinical considerations regarding the expectation of dose-responsiveness for a certain drug, or, more generally, in a specific field of scientific inquiry. The degree of specificity of such a prior depends on the available knowledge.In order to compute such expression, it appears crucial to determine which statistical model Equation . Here, wEquation . MoreoveEquation  requiresR2 and its adjusted version. Such analysis is outlined in R2 and adjusted R2), whereas the linear and the cubic models perform worst.We now present a numerical example of this new methodology to assess he study . By analDR according to an exponential model: From the data, it is possible to estimate the likelihood for non dose-responsiveness:If we again consider Equation , we concP(DR|data) for the best and worst tested statistical models at varying levels of P(DR).This results are consistent with what was previously done in  and showAdverse drug reactions present a significant problem to drug manufacturers, are a serious risk to patients, and constitute a major ethical problem in licensing decisions of pharmaceutical products. Current standards for drug evaluation are based on a methodology developed for the assessment of benefits that focuses on internal validity and privileges randomized controlled trials. However, evidence for harm often emerges unsystematically and unpredictably in form of anecdotal reports, case series and survey data. Hence, this methodology faces overwhelming challenges in integrating such diverse evidence.Whereas a sophisticated set of tools for meta-analysis and systematic reviews has been developed for the purpose of evaluating intended effects of interventions, the adaptation of these instruments with the aim of evaluating safety of health technologies encounters various problems, mainly due to the (i) relative scarcity, (ii) heterogeneity, and (iii) “fragility” of data concerning unintended effects of medical treatments: (i) Evidence about unknown risks emerges gradually from spontaneous reports or other kinds of sporadic data: Especially in the earlier phases of risk detection, these data can be at the same time very noisy and rare; (ii) furthermore, they may come from heterogeneous sources ; (iii) and it can be unreliable, because of noise and bias. Risk minimization requires however, that timely decisions are made on the basis of the available, albeit inconclusive and possibly “low-quality” evidence.One major obstacle for the optimization of the kind of diverse evidence that we encounter in pharmacosurveillance is inherited from the epistemology underpinning the standard methodological paradigm entrenched in the medical community, i.e., frequentist hypothesis testing. This only works with predefined research protocols and can pool only homogeneous data. Thus, current approaches lack the justificatory underpinning for anecdotal reports, case series, or survey data, which are the main source of evidence for drug safety assessment. Such a perspective, together with the implementation of new computational methods , challenStarting from these premises, in E-Synthesis, a Bayesian framework for causal assessment that represents a new approach to evidence synthesis grounded on theoretical bases [E-Synthesis can be pictured as a Bayesian network able to synthesize evidence of different types  that are combined together in order to form the “critical mass” needed to make decisions about the approval/withdrawal of a particular drug on the market. Through several indicators of causality , E-Synthesis acts as a theoretical ordering scaffold on the available evidence and arrange it in order to assess the causal relationship between a certain drug and harm in a given population.Following this path, in al bases ,21. E-SyE-Synthesis. By combining different approaches and frameworks , we hav, in Bayesian networks one may conditionalise on any proposition (or event), since probabilities are interpreted more widely as one’s uncertainties about general propositions. While a certain degree of subjectivity is undeniable, there is a good argument to be made that some subjectivity is unavoidable in any approach to statistical/uncertain inference . FurtherADRs are responsible for a heavy economic and social burden ; additioE-Synthesis aims to respond to the challenge of merging information from diverse sources by providing a structured way to exploit their joint (dis)confirmatory strength.Within such perspective, methods for synthesizing heterogeneous evidence are rising as a more and more robust approach to drug safety. While developing its framework on a sound foundational basis, E-Synthesis to better predict ADRs and improve the risk management process  will benefit the pharmaceutical industry, patients and drug agencies.The theoretical system developed in  is being


Visual landmarks are important navigational aids for research into and design of applications for last mile pedestrian navigation, e.g., business card route of pedestrian navigation. The business card route is a route between a fixed origin  to a fixed destination . The changing characteristics and combinations of various sensors’ data in smartphones or navigation devices can be viewed as invisible salient landmarks for business card route of pedestrian navigation. However, the advantages of these invisible landmarks have not been fully utilized, despite the prevalence of GPS and digital maps. This paper presents an improvement to the Dempster–Shafer theory of evidence to find invisible landmarks along predesigned pedestrian routes, which can guide pedestrians by locating them without using digital maps. This approach is suitable for use as a “business card” route for newcomers to find their last mile destinations smoothly by following precollected sensor data along a target route. Experiments in real pedestrian navigation environments show that our proposed approach can sense the location of pedestrians automatically, both indoors and outdoors, and has smaller positioning errors than purely GPS and Wi-Fi positioning approaches in the study area. Consequently, the proposed methodology is appropriate to guide pedestrians to unfamiliar destinations, such as a room in a building or an exit from a park, with little dependency on geographical information. Computer-assisted pedestrian navigation is an area that requires ongoing research because of people’s varying abilities , the com(1)An improved D-S theory of evidence is introduced by integrating the co-existing phenomena of sensors’ signal change characteristics. This approach is distinguished from navigation methods that use fingerprint-based localization and navigation applications by its focus on the nature of the combined rather than individual signal changes.(2)The similarity of real-time data of co-existing sensors to the predefined evidence framework is defined to refine the basic belief assignment in the theory of evidence.(3)A match error-based sensor weight assignment approach is proposed to handle conflicts of evidence processing.This paper introduces an invisible landmark-based approach to locate pedestrians in indoor and outdoor environments, that is, an improved Dempster-Shafer (D-S) theory of evidence, which is proposed to locate pedestrian by considering co-existing phenomena in the form of sensors’ signal change characteristics. All signals from the sensors are sequenced in a linear reference manner along a target “business card” route. The target route is requested by the proposer from a specific location  to a particular destination of him, such as the office. Then, the changing characteristics of various sensors and their combinations are analyzed to build up the frame of discernment in the theory of evidence. In this paper, we propose:Thus, the invisible landmark-based pedestrian locating approach based on the D-S theory of evidence is a useful guide to allow newcomers to follow predesigned business card routes.The remainder of this paper is structured as follows: Landmark-based navigation tasks are broadly discussed in the disciplines of cognition, neuroscience, geographical information science (GIS), computing, and communication.There is rich literature in the disciplines of cognition and neuroscience on the spatial cognitive aspects of landmark-based instruction. Researchers have studied the perceptual, cognitive, and contextual aspects of landmarks in wayfinding; for example, landmark-based instructions enable pedestrians to comprehend efficiently the visual prominence, semantic salience, and structural significance of landmarks ,22,23,24In the discipline of GIS, many studies focus on the collection of landmark information, the use of landmarks in route instructions, and the modeling of landmarks in GIS: for example, discovering landmark preferences from photo postings , extractIn the disciplines of computing and communication, many studies have been conducted on scene landmark recognition, understanding, and classifications for applications, including robot navigation. For example, identifying landmarks in urban scenes , vision-Much research work has focused on the usage of inertial sensors in smartphones or navigation devices for pedestrian localization, for example: GPS, infrared , Ultra WNowadays, the functionality of smartphones far exceeds simple communication. Current expectations are such that phones have applications for entertainment, practice, and learning. Thus, smartphones integrate more and more sensors  to meet people’s expectation for technological assistance in day-to-day existence.The sensors in smart phones can be classified as three categories: motion, environmental, and position sensors. A gyroscope, as a motion sensor, can effectively detect data changes caused by pedestrian movement. The light sensor is an environmental sensor, which can measure light intensity in the pedestrian’s environment. GPS, Wi-Fi and magnetometer sensors are position sensors although it is influenced by the Sun. GPS sensors can determine a person’s position both indoors and outdoors. Wi-Fi can be used to triangulate a pedestrian’s location and provide internet services for them. This paper will use the gyroscope, light sensor, GPS, Wi-Fi, and magnetometer sensors to match the locations of pedestrians with predetermined routes that connect origins and destinations, and recode all the signals of these sensors while traveling along the route.This paper proposes an invisible landmark-based navigation guidance approach, based on the D-S theory of evidence, which aims to guide pedestrians to their destination smoothly by following business card route. The business card route is represented by a sequence of signals detected by the smartphone’s sensors between the origin and the destination of this route. The proposed approach compares the real-time signals in smartphones with the precollected signals of the business card route so as to sense the current location of pedestrian.This section introduces the basic concept and approach of the D-S theory of evidence, and then proposes improvements for determining the location of pedestrians.The D-S theory of evidence, also known as the theory of belief functions, is an efficient Bayesian framework for approximate reasoning and decision-making in uncertain environments, which was originally proposed by Dempster  and imprm is a BPA on A belongs to the set Let cernment . Each elion (Pl) , where BTherefore, the interval represents the level of uncertainty based on the evidence in the framework. For example, the interval In the case of multiple sources of evidence, the BPAs could be combined to yield a new BPA function Two main factors can lead to conflicts of evidence in the theory of evidence, namely: sensor unreliability, caused by equipment failure or limitations, and incomplete knowledge of the world . As longThis paper improves the D-S theory by combining the accompanying rules of evidence and their processing of conflicts of evidence. In the implementation of D-S, this paper generates evidence frameworks for individual route segments. Each segment has some associated evidence from sensors. The following subsection will firstly introduce the path division, and then introduce the consequential improvement in D-S theory.Before establishing the frame of discernment, the user conducts several complete walks along the target business card route, and collects the sensor data of the smartphone on this route using any sensor data acquisition application. For each sensor, this study divides the route into segments according to the changes in its data. Consequently, this study could obtain the route segment set for each kind of sensor, namely, The first kind of sensor is a magnetometer, which is an instrument that measures the direction and strength of a magnetic field at a particular location. For a fixed point, the geomagnetic field can be decomposed into two horizontal components and a component that is perpendicular to the ground The second kind of sensor is the gyroscope. This sensor is able to detect the angular velocity of a moving object, which allows the recognition of turning. In the process of turning, the absolute value of angular velocity obtained by the gyroscope will increase significantly. However, in the situation of smooth walking, the z-axis value of the gyroscope is nearly zero. The positions of left and right turns correspond to the peaks and troughs of the gyroscope data, respectively, as shown in The third kind of sensor is the light meter. The other sensors are for Wi-Fi and GPS and the processes associated with them are very similar. The Wi-Fi signal distribution has a certain range, and the mobile phone can accept that signal anywhere within that range. Therefore, Wi-Fi Media Access Control (MAC) address along the target route could be used to divide it into segments. Each segment has a limited Wi-Fi MAC address set and the neighbor segments will have a different Wi-Fi MAC address. For example, the route segment set i is the serial number of a route segments in the target route, and i. The status of magnetometer data along the x- and y-axis This study divides the target route into many tiny segments by intersecting the route segment set of all sensors, which is viewed as the frame of discernment, The determination of the above mentioned evidence framework is based on single data source. To a certain extent, the framework would bring about incorrect segment results due to external interference. For example, when encountering a temporarily parked vehicle in the process of targeting road, the record of magnetometer would fluctuate and generate redundant segment points. In addition, when data collector changes direction in order to avoid pedestrian, the record of gyroscope reaches peak or valley, which also affects the correctness of the framework. In order to eliminate above mentioned interferences, this paper optimizes the framework by using multiple repeated data sources. In this paper, each sensor data were collected Co-existing relationships of evidence are common phenomena for smartphone sensors used to locate pedestrians as a result of similarities in activity behaviors and constraints in a navigation environment. Usually, the best evidence is when they have co-existing relationships that can reflect the uniqueness of the actual scene in space and time sequences. Therefore, the basic selection rule of co-existing relationships between sensors is that the sensor data feature can be readily detected by simple filtering algorithms, such as moving windows, and the combination of sensors in each route segment or the sensor features presents an obvious difference between the neighboring route segments. For smartphones’ sensors in pedestrian navigation environments, the data from the magnetometer, Wi-Fi, and GPS are independent environmental information, and these data obtained at each route segment could become evidence of a unique environment. The gyroscope mainly detects the changes (or turns) in the journey through the environment so that the gyroscope can be added to the evidence framework when the real-time gyroscope data exhibits changing features. For example, After selecting sensors as a co-existing sensor combination for each route segment, our proposed approach calculates the similarity of the real-time data of co-existing sensors with a predefined evidence framework, according to the following Equations (6)–(15):i in evidence framework and it in the real-time data set.Here, The light sensor is more complex than other sensors in that the intensity of light varies greatly across time and climate. The most accurate match result can be obtained when the light condition of In order to improve the error tolerance performance of the matching process, this study finds the five most similar discernments in the frame of evidence using Equations (6)–(15), and ranks them with levels of 1–5. The Equation (17) gives an example of similarity matrix with 6 discernments (left part of This study uses Equation (18) to calculate the probabilities of the five most similar discernments. The probability is used to build up a basic belief assignment of each sensor for real-time sensor data.By combining the co-existing rules of evidence, this study proposes an improved theory of evidence combination formula as follows.In the process of evidence combination, two factors affect the accuracy of sensor data, one is data latency, the other is external interference. Conflicts of evidence may exist in the matching process of sensor data and evidence. Therefore, it is necessary to deal with this issue during evidence combination. Several approaches have been proposed to manage conflicts in D-S evidence theory, such as, averaging , and comWeighting evidence is crucial to improving the accuracy of the evidence combination results in the case of different evidence association rules. The weights are usually subjectively assigned, or can be objectively calculated in the presence of historical data sets . In thisi. Let u is the number of labelled points. The matching error can be estimated by comparing the location of the labelled points with the corresponding matched route segments. i at times i according to a basic rule that if the matching error of a sensor is smaller, the weight of this sensor is higher. Therefore, the weight of sensor i is defined as follows:D11, D11, Dq-11, Dq1. Here, D11 + D11 + …… + Dq-11 + Dq1) + (D21 + D21 + …… + Dq-12 + Dq2) + (D31 + D31 + …… + Dq-13 + Dq3)]/3q in the case of sensor i.Then, this study improves the theoretical formula for evidence by employing two strategies. The first is to assign a small probability to the whole frame gligible . The othThis section introduces the experimental environment and collected data for a target route. Then, it gives the calculated frame of evidence of the improved approach, which is similar as a system training. Finally, this section demonstrates the advantages of the proposed approach by comparing the matched results with those obtained by the traditional D-S theory, GPS locations outdoors, and Wi-Fi locations indoors.The experiment was conducted on the campus of Wuhan University and a business card route for pedestrians from the entrance of Wuhan University to the No. 2 School Building was selected see . This stThe data format collected in this study is listed in Here, RSSI is received signal strength indicator, which is a measurement of how well your device can hear a signal from an access point or router. Due to the situation that RSSI have large fluctuation over the same distance and are attenuated, this study used the radio propagation model  to estimIn addition, five pieces of data in daytime and the same numbers in nighttime are selected to examine the accuracy of the proposed light condition selection method based on the continuity of light. In Based on the determined framework, this study calculated the basic belief assignment of each sensor in the frame of discernment shown in f Murphy  for comblogy see .After using the repeated data from collections 2 to 9, this methodology can be used to calculate the distribution of weights of co-existing evidence by the rule that a sensor with a smaller average error has a greater weight in the methodology. Because of the repeatable characteristics of sensors, such as the magnetometer, Wi-Fi, light and GPS along the target route, and two clear conditions of changing and unchanging characteristics of the gyroscope, this study classifies the co-existing situations of sensors into two class, namely, the co-existing situations with and without gyroscope. To estimate the performance of the proposed approach in terms of match success rate and positioning error of results, this study selected nine (black) labelled points along the target route shown in i.The match success rate is the ratio of the success match cases among all experimental cases. Here, the match success rate is calculated as:From To compare the location error of results, this study uses multiple sensors and GPS when outdoors and multiple sensors and Wi-Fi when indoors. The positioning errors of these approaches, which are the difference between the matched route segments and the actual locations, were evaluated using the nine labelled points. 4.4% see . The equIn this study, the changing characteristics and combinations of various sensors’ data in smartphones or navigation devices are viewed as invisible salient landmarks for predefined business card route of pedestrian navigation. This study introduces an improved Dempster-Shafer theory of evidence to find invisible landmarks along predesigned pedestrian routes without using digital maps by integrating the co-existing phenomenon of sensors’ signal change characteristics. This approach distinguishes navigation methods from fingerprint-based localization and navigation applications by focusing on combinational features of signal changes, rather than on individual signal changes. Moreover, it integrates a proposed similarity measure of real-time data of co-existing sensors with a predefined evidence framework for refining the basic belief assignment in the theory of evidence, and a match error-based sensor weight assignment approach for handling the conflict of evidence processing. Furthermore, this paper optimizes the framework for possible pedestrian navigation situations by using multiple repeated data sources to eliminate temporally incorrect segment results, e.g., the external interference when encountering a parked vehicle or avoiding pedestrians. In this approach, the frame of discernment is utilized according to the path division by sensors’ characteristics. The real-time pedestrian’s sensor data features are extracted to contrast and match with the framework. As result, this study improves the evidence theory to fuse the matching results of each sensor and infer a pedestrian’s location. The proposed approach is tested in the real experiment environment of pedestrian navigation. The experimental results shows the proposed approach could achieve the 100% match success rate for all labelled points, while the average match success rate of the traditional D-S theory is about 40%. This approach also improved the positioning accuracy of 15.9% and 54.4% for labelled points outdoors and 10.1% to 62.6% for labelled points indoors when it is compared with GPS or Wi-Fi alone in the study area. These experiments demonstrate that the proposed approach outperforms those based on GPS or Wi-Fi alone in the study area. Also, this approach can be applied seamlessly both indoors and outdoors for newcomers to follow predesigned business card routes.There is scope for further research following this proposed approach. The first avenue it to combine the mapless pedestrian navigation with digital maps, which aims to make full use of visual and invisible landmarks within pedestrian navigation environments. The second avenue is to improve positioning sensors or create an adaptive smartphone-dependent sensor weight assignment method. The third avenue is to produce invisible landmark-based navigation maps and integrate these invisible landmarks into current landmarks or point-of-interest-based pedestrian navigation data models. The fourth avenue is to create comparative navigation in future work.


Humanitarian action in crisis zones is fraught with many challenges, including lack of timely and accessible research evidence to inform decision-making about humanitarian interventions. Evidence websites have the potential to address this challenge. Evidence Aid is the only evidence website designed for crisis zones that focuses on providing research evidence in the form of systematic reviews. The objective of this study is to explore stakeholders’ views of Evidence Aid, contributing further to our understanding of the use of research evidence in decision-making in crisis zones.We designed a qualitative user-testing study to collect interview data from stakeholders about their impressions of Evidence Aid. Eligible stakeholders included those with and without previous experience of Evidence Aid. All participants were either currently working or have worked within the last year in a crisis zone. Participants were asked to perform the same user experience-related tasks and answer questions about this experience and their knowledge needs. Data were analysed using a deductive framework analysis approach drawing on Morville’s seven facets of the user experience — findability, usability, usefulness, desirability, accessibility, credibility and value.n = 8), advisors (n = 7), field managers (n = 7), analysts/researchers (n = 5) and healthcare providers (n = 4). Participant self-reported knowledge needs varied depending on their role. Overall, participants did not identify any ‘major’ problems (highest order) and identified only two ‘big’ problems (second highest order) with using the Evidence Aid website, namely the lack of a search engine on the home page and that some full-text articles linked to/from the site require a payment. Participants identified seven specific suggestions about how to improve Evidence Aid, many of which can also be applied to other evidence websites.A total of 31 interviews were completed with senior decision-makers (Stakeholders in crisis zones found Evidence Aid to be useful, accessible and credible. However, they experienced some problems with the lack of a search engine on the home page and the requirement for payment for some full-text articles linked to/from the site. Humanitarian action in crisis zones is fraught with many challenges, not the least of which is having rapid access to research evidence that has the potential to inform decisions. Acting on available research evidence can help to improve the effectiveness and efficiency of humanitarian interventions . Access This gap persists in the existing literature for five main reasons. First, while literature exists that examines evidence websites in other settings, these studies do not focus on evidence use in crisis zones –12. SecoIn light of the lack of third-party research in this area, this study presents a non-affiliated examination of the use of Evidence Aid by a diverse array of stakeholders working in crisis zones. Evidence Aid is the only evidence website designed for crisis zones that focuses on providing research evidence in the form of systematic reviews. Systematic reviews critically appraise and summarize all relevant individual studies, which reduces the amount of time and search skills other stakeholders need to access and appraise large bodies of research . EvidencEmploying a user-testing study design, our objective herein was to explore the information needs of stakeholders working in crisis zones and their views of and experiences with the Evidence Aid website. This paper also aims to put forward specific suggestions about how to improve evidence websites designed to support the use of research evidence in decision-making in crisis zones. Many of these suggestions can also be applied to other evidence websites that support the use of evidence in decision-making more broadly.A user-testing study design was used to address our research objective. This type of design is widely employed in the field of product design and evaluation, and involves having users complete task-specific problems –19. UserWe started our interview with a set of preliminary general questions about the participant’s profession and knowledge needs followed by a set of think-aloud user experiences and views while performing task-specific questions. Our lack of involvement with Evidence Aid makes us particularly well positioned to elicit frank feedback. Participants were informed of our lack of involvement with Evidence Aid at the outset of the interview.https://www.evidenceaid.org) is an English-language interface with some articles and user-friendly summaries available in Spanish and French. To be included in Evidence Aid, the systematic review must focus on the effectiveness of humanitarian action and include health-related outcomes. Evidence Aid provides appraisal for each of the systematic reviews. Research evidence is available on Evidence Aid in three ways — first, through a simple search bar located under a resources tab with the option of selecting month (e.g. March 2019) and category (e.g. emergency type); second, research evidence is organized into four main categories, namely health issues , emergency type , humanitarian cluster  and person groups ; finally, Evidence Aid produces curated collections of evidence specific to crisis zones .Evidence Aid . However, some of the full-text articles available through the site do require a payment to access the content, although this is arguably outside of Evidence Aid’s scope given the nearly limitless liability they would face if they offered free access to all articles.anyone that has an interest in, is likely to be affected by, or has the ability to influence” a decision .We aimed at completing at least five user test interviews for each type of participant category  for both types of participants (i.e. those that have used Evidence Aid and those that have not), recognizing that this estimate was dependent on the availability of appropriate participants. We recruited 9 participants from our first stage of sampling, and 22 additional participants were identified through snowball sampling. Our sample size amounted to a total of 31 participants (Table Interviews were conducted via Skype by the first author (AFK), who acted as both the interviewer and note taker. The interviews lasted approximately 60 minutes and were audio-recorded after receiving permission from the participant. Audio recordings were transcribed verbatim and the written transcriptions were used for data analysis. Potentially identifying information (e.g. name) was removed at the time of transcription. We conducted the interviews in English, which is the language used in the Evidence Aid interface.The user testing began with preliminary questions about the participant’s profession, what sources of research evidence they use and knowledge of evidence websites including Evidence Aid , advisors (n = 7), field managers (n = 7), analysts/researchers (n = 5) and healthcare providers (n = 4). Good balance was achieved across types of organizations . A high proportion of interviewees had not used Evidence Aid before (n = 22); 65% of the participants were women (n = 20) and 35% were men (n = 11); 17 interviewees have never heard of Evidence Aid before our interview, while 14 participants had heard and used Evidence Aid occasionally.A total of 31 interviews were completed  were most cited by senior decision-makers, healthcare providers and advisors. Global guidelines (e.g. from WHO) were most cited by advisors. Finally, our participants obtained information from a wide variety of sources .Overall, there were two notable differences in responses across our diverse types of stakeholders and between users and non-users of Evidence Aid. First, analysts and researchers we interviewed demonstrated enthusiasm that Evidence Aid is attempting to bring research evidence closer to humanitarian aid workers, while some senior decision-makers were sceptical about using Evidence Aid as opposed to relying on information stemming from their ground operations to answer specific questions. Additionally, participants that have used Evidence Aid before were more familiar with the organization of tabs on the website, which facilitated faster access to desired content than non-users. Finally, there were no notable differences in responses across gender.Participants did not identify any ‘major’ problems (highest order) across the seven domains of the user experience Table . HoweverParticipants cited a minor issue of having difficulty locating the search bar. As for positive feedback, participants indicated that the four cluster areas  under the ‘Resources’ tab were helpful in locating desired information. In addition, participants appreciated that the ‘tags’ in the results page helped to further narrow down their search results. Participants suggested the addition of an advanced search filter for more targeted search results .I appreciate that there is a learning curve until one is familiar with the site and how to use it efficiently.”“To improve the usability of the site, some participants suggested creating a clearer statement of the site’s purpose and the type of evidence it provides.Participants cited as a minor issue having to undertake multiple steps to perform basic tasks to arrive at results on first use. However, some participants did note that, once they had enough time on the site, they were able to perform basic tasks efficiently. A field manager commented:It is good for humanitarian workers to have all the articles on one site so they can go there and look for evidence-based approaches.”“For minor issues, participants sometimes cited a lack of systematic reviews and guidelines related to their own particular areas of professional interests or fields of work. Participants provided positive feedback related to how useful the site is in providing an independent evidence website for curated evidence on crisis zones for decision-makers working in the field. As one senior decision-maker commented:Most people in the humanitarian sector do not understand abstracts and they almost alienate them. A better strategy is friendly-summary reviews that are shorter, to the point, with clear actionable points.”“Most participants suggested that Evidence Aid should focus some of their efforts on turning the evidence available into explicit actionable points for decision-makers to use in crisis zones. A stakeholder highlighted this suggestion by stating:Photos make it seem like a training workshop website with the pictures of classroom settings.”“Photos displayed on Evidence Aid prompted many participants  to suggest that the developers behind the site should consider using compelling photos that are relevant to humanitarian contexts. Participants did appreciate the basic simple design of the site and the lack of numerous pop-up advertisements.Participants cited a minor issue of photos on Evidence Aid being ‘ordinary’ (i.e. academic looking) and repetitive. A healthcare provider explained Evidence Aid choice of pictures on the home page stating:Access to the internet in the field is a big barrier. It is a touch and go situation.” – healthcare provider working in the field at a non-governmental organization (NGO)“Participants cited concerns over whether documents can be read online or have to be downloaded first, the latter of which can be a problem in a low-bandwidth internet setting and would pose a significant limitation to those using the site from the frontlines of a crisis zone, with a healthcare provider stating:There needs to be more open-access resources. Organizations need to share early on data from the field that would allow us to somehow get other actors to build the evidence to better inform our decisions.”“A healthcare provider further emphasized the importance of open-access resources stating: Open source access is still a big problem unless you have university library access.”“Participants did appreciate that Evidence Aid is accessible to a broad spectrum of people working in the humanitarian sector who have access to the internet. A mobile friendly app, which is not currently available, or the use of a responsive web design was suggested as a way to improve the overall user experience. Senior decision-makers highlighted the importance of having open-access resources and timely assessment data on current crises to inform decision-making, with one stakeholder stating:Highlight the main funders of the site on front page to make it more transparent with emphasis on the major contributors to Evidence Aid.”“Participants cited as a minor issue not clearly knowing what inclusion criteria are used to include best available evidence on the site. Participants emphasized that the direct and clear link to the Cochrane Library increased their level of trust of the evidence presented. For specific suggestions, participants wanted to see greater visibility given to major contributors and funders, with an advisor working at an NGO, stating:I heard of it but never used it. It has the potential of being super helpful. But not many people know about it now.” – advisor working at an NGO“This prompted our participants to suggest that Evidence Aid should emphasize more clearly on their site why evidence matters in humanitarian action and to continue collaborating with other organizations to fill gaps with new systematic reviews.The lack of awareness among humanitarian aid workers about the existence of or value added by Evidence Aid was cited by participants as a minor issue. Several participants made comments about hearing of Evidence Aid but never using it because of lack of awareness about its value. An advisor and a field manager highlighted this during the interview, stating:Our study suggests that there are no ‘major’ problems (highest order) and only two ‘big’ problems (second highest order) that stakeholders’ experience with using Evidence Aid website, namely the lack of a search engine on the home page and that some full-text articles linked to or from the site are not accessible without payment to the publisher. Our study participants identified a positive feedback related to credibility (i.e. direct and clear link to the Cochrane Library increasing their level of trust of the evidence presented) that raises an important point that warrants highlighting. We found that users were inclined to make judgements about the trustworthiness of the Cochrane Library as the publishing source rather than critically assessing individual pieces of evidence, a similar finding in other studies . AdditioSeven specific suggestions made by our participants and illustrated in Table A common challenge that stakeholders face when trying to use research evidence to inform their decision-making relates to the lack of knowledge management skills and infrastructure , 39–43; Our findings suggest the following three contributions to understanding evidence use in a crisis zone. First, many of our participants emphasized the need for evidence to be turned into explicit actionable points (e.g. check-lists). However, we recognize that this task is better delegated to a person or group that create connections between researchers and decision-makers (e.g. knowledge brokers). Second, our participants highlighted that evidence summaries must clearly indicate the basic findings from systematic reviews, including key messages that can be acted upon . Third, Our finding that participants did not identify any major problems (and only two big problems) with using Evidence Aid aligns with previous studies identifying that users generally find there are many helpful attributes of using evidence websites (e.g. multiple sources of information in one spot) , 15. ThiThere are a number of strengths to this study. As far as we are aware, this is the first study to examine evidence website use in crisis zones and the first user-testing study to investigate the information needs of stakeholders working in crisis zones, which provides valuable insight on how best to meet their knowledge needs. Second, we interviewed a large number and diverse range of people for a study of this type, with the number higher than that thought to reveal 80% of known usability problems . The divOne potential limitation to this study is that all our interviews, except one, were conducted with stakeholders not physically present in a crisis zone at the time of the interview. Increased time pressure in crisis zones may influence participants’ views and experiences in finding relevant research evidence for decision-making. To mitigate this limitation, we purposively sampled participants who were either currently working or have worked within the last year in a crisis zone and we prompted them to consider real-life situations when responding.There are four main implications, the first of which is that the developers of Evidence Aid should continue their efforts of providing the best available evidence on the effectiveness of humanitarian action while taking into account the specific suggestions, summarized above, to improve the site. These specific suggestions can also be applied to other evidence websites designed to support the use of research evidence in decision-making. Second, the developers of Evidence Aid site should consider whether they or another group are better positioned to fulfil the second part of their mission, namely ‘enabling the use of the best available research evidence’, by expanding their activities to include creating demand for research evidence, providing rapid reviews in response to decision-maker requests and institutionalizing the use of research evidence, among other options –52. ThirThe next steps in research could be for researchers to explore stakeholders’ experiences with an updated version of Evidence Aid to ‘test’  if specific changes have improved the usability and use of the site. Additionally, researchers could evaluate future efforts by Evidence Aid or its partners to address the part of its mission focused on enabling the use of research evidence. Researchers could also explore other evidence websites , which were most cited by our participants as their main source of obtaining information to find ways to adapt these websites’ strengths to improve Evidence Aid. Finally, researchers working in other domains (i.e. outside humanitarian crises) could use our methodology  to explore stakeholders’ views and experiences with other evidence websites designed to support evidence-informed decision-making.Stakeholders in crisis zones found Evidence Aid to be useful, accessible and credible. However, they experienced some problems with the lack of a search engine on the home page and the fact that some full-text articles linked to or from the site require a payment. This is the first study to specifically focus on an evidence website for crisis zones, elaborated on the information needs of stakeholders, and put forward specific suggestions about how to improve evidence websites. By making evidence available, evidence websites provide one of the necessary inputs for evidence-informed decision-making processes. The absence of evidence websites creates a clear gap in supporting evidence-informed decision-making.Additional file 1.. Interview guide used in Test.