Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution. To address such a limitation, we design a novel deep learning dehazing model by combining the transformer and guided filter, which is called as Deep Guided Transformer Dehazing Network. Specially, we address the limitation of convolution via a transformer-based subnetwork, which can capture long dependency. Haze is dependent on the depth, which needs global information to compute the density of haze, and removes haze from the input images correctly. To restore the details of dehazed result, we proposed a CNN sub-network to capture the local information. To overcome the slow speed of the transformer-based subnetwork, we improve the dehazing speed via a guided filter. Extensive experimental results show consistent improvement over the state-of-the-art dehazing on natural haze and simulated haze images. I is the input hazy image, and J is the corresponding clean image, t represents how much the light reflected from objects is received by the camera, A is the air-light.Image dehazing is a hot topic in classic computer vision, whose goal is to restore a clean image from the input. The quality of the captured image is affected by the air particle, which absorbs the ray emitted from objects and reflects other light into the camera. We can describe the hazing process as:6 or additional information9. Requiring additional information restricts the application scope of these methods. The priors used for dehazing maybe fail in some cases, such as images containing white objects or the sky. To boost the robustness of dehazing methods, deep learning-based methods11 are introduced to predict the transmission map. But the dehazing performance of these methods is influenced by the precision of the estimated transmission map. To overcome this problem, some End-to-End deep learning dehazing methods20 are proposed. Li et al. fuse the transmission map and airlight into a new parameter and design a low-time consumption dehazing method. Qu et al. designed a dehazing method, which transfers the dehazing problem into a transferring problem. Liu et al.employ the attention mechanism and multi-scale network to boost dehazing performance. Dong et al. employ boosting strategy and dense features fusion21 to design a dehazing network. Zhang et al. propose a transmission map guided dehazing network22. Song et al. propose a wavelet-based dehazing method23. Although these methods have their great power in dehazing, we note the performance can be further boosted by introducing a model which can capture long dependency.In the traditional image dehazing, computing the transmission map and air-light is a highly ill-posed problem if there is no extra information available. To address dehazing problem, a lot of dehazing methods are designed based on the various types of priors24. The prior work25 introduced a transformer into a computer vision task and achieved an impressive performance, which shows the potential of computer vision tasks. However, the computational burden of the transformer is very high, which limits its application of transformer. To boost the dehazing performance, Dehamer26 propose a transformer-based module to estimate the density of haze, and then combine it with CNN features to obtain the final dehazed results. However, Dehamer ignores the information in hazy images, and cannot achieve a high dehazing for dense hazy images. Furthermore, Dehamer inherits the problem of the transformer, which has a high time complexity. Zhao et al. propose a Pyramid dehazing network27, which can extract large contextual information. However, this work also inherits the limitation of CNN. The proposed model extracts the large contextual information using a transformer and reduces the consumption time using the deep guided filter.CNN has shown its effectiveness in low-level computer vision tasks, while transformers have shown great power ability for high-level computer vision tasks. Recently some works although introduce it into low-level computer vision tasksWe introduce transformer-based sub-network to restore the coarse haze-free image and then the details are refined via a CNN-based sub-network. Restoring the coarse haze-free image depends on global information while refining the details needs more local information, which encourages us to design such a dehazing model using CNN and a transformer.We introduce the guided filter to improve the dehazing speed. Transformer is time-consuming, which may limit the application of transformer-based dehazing methods. We address this issue by introducing the guided filter into the proposed model. We reduce the input size of the transformer, which reduces the execution time of the transformer-based model.We do extensive experiments to show the superiority of the proposed method on natural hazy images and simulated hazy images. We also conduct ablation studies to show the effectiveness of the proposed modules.To address this issue, we propose a novel highly efficient dehazing method based on the transformer and guided filter, which is called Deep Guided Transformer Dehazing Network (DGTDN). Haze is depend on the distance between the camera and the objects, which results in the haze density being different from pixel to pixel. The distribution of haze is global, which is hard for CNN to capture the long distance. To capture the long dependency, we design a transformer-based model to capture the global information of haze. However, the transformer cannot capture the local information well. To deal with this case, we propose a lightweight CNN sub-network to capture the local information. Based on the advance of the transformer and CNN, we propose to restore the global haze-free image with the transformer and then refine the details with the CNN sub-network. To achieve the goal of further improving the dehazing speed, we introduce the guided filter to reduce the dehazing time. The contributions of the DGTDN can be summered as follows: We show some previous works related to dehazing. In this paper, we divide the related dehazing works into two groups, which include learning-based and prior-based methods.30. With the development of CNNs, a lot of works36 attempt to solve dehazing using deep learning models. These dehazing methods often attempt to compute the key factor of the physical model or the corresponding haze-free image directly. The works11 employ CNN model to compute the transmission map. However, these methods may boost the error of the transmission map and result in poor dehazing results. To deal this problem, End-to-End dehazing methods40 are proposed. For example, Zhang et al. design a CNN model that incorporates the physical model. Li et al. propose an all-in-one dehazing model13, which fuses the transmission map and airlight into a new parameter. Liu et al. design a novel dehazing model20 based on attention and multi-scale network. However, all these dehazing methods are based on CNNs, which are limited by the local property of convolution. To capture the long dependency of hazy images, Guo et al. propose a transformer-based dehazing method26, which employs the transformer-based encoder to capture the density of haze. Different from the above-mentioned methods, we overcome the problem of CNN by introducing the transformer block into the dehazing model, which can capture the long-range dependency. Some works note the difference between the simulated hazy and real hazy images, which results in a drop of dehazing performance on real hazy images when the model is trained with simulated hazy images. To address these issues, PSD17 proposes to combine the traditional priors to improve the dehazing quality of real hazy images. Domain adaptation dehazing method (DA)19 improves the dehazing quality on real hazy images by converting simulated hazy images into real hazy images. We note that these methods are hard to train. Furthermore, the proposed method focuses on improving the learning ability on simulated hazy images, which has a different goal from PSD and DA.The CNN-based methods have swept the computer vision tasks6 or additional information9 has been proposed. These methods discover the prior based on the statistical analysis of clean images or hazy ones. The famous work is Dark Channel Prior (DCP), which is derived from the observation that a clean image patch contains at least one pixel that has a channel value close to zero. Zhu et al. discover a color attenuation prior5, which is that the divergence between intensity and saturation positively is correlated to the depth. Fattal et al.2 use a color-line prior to removing haze. Berman et al. find a haze-line prior4 based on the observation that one haze-free image can be presented by a small number of color clusters. However, all these priors are simple, and cannot be held in real word complex scenes.To address the ill-posed of single image dehazing, a lot of prior-based dehazing methods41 to capture long dependency and improved the performance of learned models. Transformer shows its effectiveness in NLP and image classification task25 also employs Transformer to improve the performance. With the success of Vision Transformer (ViT)25 and its follow-ups43, researchers have shown the potential of transformers to image segmentation43 and object detection42. Although visual transformers have shown their success in visual tasks, it is hard to directly apply it in single image dehazing. First, Transformers often depend on large-scale datasets. However, there is no existing large-scale dataset to train a transformer-based for image dehazing. Second, it is hard to capture local representation for transformers, which may result in the loss of image details. To overcome this issue, we proposed combining the advantage of CNN and transformer to capture the local texture and global structure jointly to boost the dehazing quality.Natural language processing (NLP) has applied TransformerIn this section, we explain the motivation behind Deep Guided Transformer Dehazing Network (DGTDN) and then show the details of DGTDN. The structure of the proposed DGTDN is shown in Fig. 44. The transformer has shown its ability to capture long-range dependency, which is critical to improve the dehazing quality. However, the transformer cannot capture the local feature details which leads to coarse details for dehazing. According to the prior works45, CNN can provide local connections and capture local features. It is known to all that transformer-based methods are time-consuming. To reduce the inference time, we propose to introduce the deep guided filter into the dehazing network. Based on the above analysis, we combine the advantages of CNN, transformer, and deep guided filter to boost the dehazing quality and reduce the running time. In this paper, we propose a Deep Guided Transformer Dehazing Network (DGTDN). DGTDN consists of BaseNet, DetailNet, and GuidedFilerNet. BaseNet is designed to capture long-rang dependency and restore the coarse haze-free image. DetailNet is designed to capture the local features and restore the image details. GuidedFilterNet is designed to enlarge the low-resolution dehazed result and reduce the dehazing time.The thickness of the haze is dependent on the depth of the objects, which results in the distribution of haze is global information. Based on the fact that the dehazing task needs to restore the image details, which is dependent on the local features. Single image dehazing is dependent on global and local featuresBased on the motivation in subsection 3.1, we introduce the CNN, transformer, and guided filter into the proposed dehazing network. As shown in Fig. BaseNet is the BaseNet, the The BaseNet consists of an encoder that extracts features and a decoder that restores the haze-free image. The encoder contains four stages, and the decoder also contains four stages. Specifically, each encoder stage contains one transformer block, which followed one down-sampling layer. Similar to the encoder stage, each decoder stage contains one transformer block, which is followed by one up-sampling layer. The down-sampling layer is designed to downscale the size of feature maps, which is implemented by DetailNet is the DetailNet, The DetailNet is designed to restore missed details. The DetailNet contains four Residual Dilation Blocks (RDBs), whose structure is shown in Fig. After obtaining the structure layer of dehazed result and the image detail layer, we can obtain the dehazed result as follow:l is the location in r, p. To solve the problem  is proposed based on the transformer and guided filter, which boosts the speed of transformer-based dehazing methods and the image quality of dehazed result. The proposed model consists of BaseNet, DetailNet, and GuidedFilerNet. BaseNet and DetailNet are proposed to capture the local and global features jointly. To boost the advantages of the transformer module and the CNN module, we employ the transformer module to predict the base layer of a clean image, and the CNN module to predict the detail layer. To address the dehazing speed problem of the transformer module, we employ the guided filter model to perform a joint up-sampling, which can improve the dehazing speed while keeping the quality of dehazed result. We show the effectiveness of the proposed method by comparing it with state-of-the-art dehazing methods on real and simulated haze images. We also show the effectiveness of the novel modules by comparing the performance of the different architectures and loss functions. In the future, we will study strategies of combining CNN and the transformer, which is critical to capture the local and global features. We also will study the domain shift of simulated-haze and real-haze images, which is critical to boost the dehazing performance on real haze images.


Health literacy has been defined and studied as an important component of a patient's ability to understand and obtain appropriate healthcare. However, a laboratory component of health literacy, as it pertains to the understanding of laboratory tests and their results, has not been previously defined. An analysis of readily available health literacy tools was conducted to determine laboratory testing-specific content representation. One hundred and four health literacy tools from a publicly available database were analyzed. Many of the health literacy tools were found to be lacking items related to laboratory testing. Of the health literacy tools that did contain a laboratory component, they were categorized pertaining to the laboratory test/testing content. Emerging from this process, eight competencies were identified that encompassed the entire range of laboratory-related aspects of health literacy. We propose that these eight competencies form the basis of a set of competencies needed for one to access, interpret, and act on laboratory results–a capacity we are referring to as “laboratory literacy.” Health literacy can be broadly defined as the capacity to obtain, comprehend, and apply health-related information. Low health literacy is a determinant of health and is correlated with key outcomes, such as lower utilization of preventive services, diminished adherence to recommended medical regimes, and overall poor health outcomes.When considering the objectives of these tools and how they are being used by researchers and healthcare providers to drive improvements in patient outcomes, the study of a patient's understanding of laboratory testing and subsequent laboratory results would seem to be an important component of health literacy. Laboratory tests were ordered or provided in 29% of all office-based physician visits in 2016,,Patients have self-reported difficulty understanding the laboratory data accessed through their electronic health portal, specifically as it pertains to the significance of their results.It stands to reason that a patient who misinterprets their laboratory results may experience unnecessary anxiety. If they falsely believe their results to be sufficient for good health in their situation, they may choose to make decisions regarding their health maintenance that are counterproductive. For this reason, we believe it is worth exploring the laboratory component of health literacy. Many patient populations have been characterized on the basis of measured health literacy, using tools such as the ones previously described.Health Literacy Tool Shed, an online database of health literacy measures that is maintained in partnership by Boston University, CommunicateHealth Inc., and Research Triangle Institute (RTI) International.We identified our pool of health literacy tools by using Health Literacy Tool Shed, in addition to containing relevant and previously aggregated health literacy tools, provides references to each tool's published validation paper. It also provides details on the specifics of the tools including information regarding validation sample size, validated administration modes, and instrument language. It also allows one to filter the database by one or more identifiers of interest.This route was chosen for the efficiency of using a pre-constructed database. The Find Measures search feature of the Health Literacy Tool Shed database, we applied the filter function to filter all entries of health literacy tools  to include only the ones that are in the English language. This returned 104 entries, from which we accessed the published validation study for each. One tool was removed due to being in Spanish and having been erroneously included in the filtered database results. Also removed were four database entries that were duplications or that were validations and expansions of a previously listed tool in the database results.Using the This left a pool of 99 health literacy tools, many of which were readily available for viewing purposes. There were 14, however, that were inaccessible. In many instances, this was due to the tool or instrument being proprietary and requiring licensing. In all instances, an attempt was made to contact the respective author through email for viewing access, and a period of one month was allowed for a response before removing that health literacy tool from the review. The remaining 85 were accessed, and we applied the following criteria in their analysis see . We asceOnly laboratory testing was considered. Clinical testing such as blood pressure readings, spirometry readings, or body mass index measurements, was not considered to involve a laboratory component. At-home blood glucose testing was considered to be a laboratory component. Assessments that were primarily oral  were not included. We made the decision that recognition and reading of more common terms would not help us know if a person could read and understand laboratory terms they likely are not familiar with. If a health literacy tool contained untested ancillary information pertaining to lab work , it was considered not to contain a laboratory component.. The items flagged as containing laboratory components, along with the overall assignment scheme, were then reviewed by third author NM.After all 85 health literacy tools were analyzed, those flagged as containing a laboratory component were scrutinized and assigned competencies delineating what particular aspects of laboratory testing that item addressed. Competencies were created, and assignments were performed independently by authors JF and MF, and then reviewed together afterward for congruence. Upon independently arriving at competencies and assignments, one competency was eliminated for being redundant, and five competencies were addedOut of the 85 health literacy tools analyzed, 20 were found to have a relevant laboratory component.Programme for the International Assessment of Adult Competencies (PIAAC), which is established from an internationally-recurring, cross-culture survey of adult cognitive skills.In proposing models of health literacy, the literature discusses the following domains: fundamental literacy, scientific literacy, civic literacy, and cultural literacyability to interpret a lab result, was the competency most tested. An example was found in the Cancer Health Literacy Tool (CHLT-30), a computer-based cancer health literacy test validated for use in adults aged 18–64 years old.the ability to supplement lab test knowledge gaps with external resources, in the form of asking the respondent to self-report their ability to find health information regarding high lipid levels.Out of the 20 health literacy tools with a laboratory component, competency 1, the understanding when a lab test is necessary, was only tested in 2 of the 20 health literacy tools found to contain a laboratory component. The Cervical Cancer Literacy Assessment Tool (C-CLAT), a paper and pencil-based cervical cancer health literacy tool validated for use in adults aged 18–64 years old,Laboratory competency 4, In the assessment of 85 health literacy tools, we came across several worth mentioning explicitly, which contained either unique test items or items testing many of the above-mentioned laboratory literacy competencies.Numeracy Understanding in Medicine Instrument Short Version (S-NUMi)interpretation of a lab result and understanding lab test limitations, respectively) simultaneously. This type of test item has the potential to shed light on how a patient perceives the validity of their laboratory test result.The 8-item Cancer Message Literacy Test – Reading (CMLT-R)interpretation of a lab result and understanding why a lab test was ordered, respectively), yet both were worded in such a way as to be multi-step questions, requiring the retention of multiple points of information detailed in the passage and then the use of them to answer a single question. For example, one question required the respondent to have retained from the passage information regarding what a PSA test is and the information needed to understand that a high value is a bad result. Such a question required the retention of information, which was not as explicitly encountered in other health literacy tools.The 23-item Health Literacy Assessment using Talking Touchscreen Technology ,The 82-item Health Literacy Tool Shed database as our only source of health literacy tools. Although updates to this database are ongoing and occur on a regular basis,A limitation of this study is our use of the interpreting a lab result. We would have preferred to have viewed the entire health literacy tool in its finalized form to properly view the test item. It is plausible that the exact wording of the item on the instrument, as presented to the respondent, could change the overall assignment of that item to having one or more additional competencies. Also, it is a possibility that other important lab literacy competencies exist but were not identified in these measures.Some health literacy tools were not able to be accessed in full in the way that they would be presented to a respondent. For example, in one instance, we were only able to access a descriptive table in the Comprehensive Health Activities Scale (CHAS) paper that indicated a laboratory component for an item described as “calculate and interpret numeric information from a chart listing 7 days of recorded blood sugar levels before and after meals for a diabetic patient.”, Ability to supplement lab test knowledge gaps with external resources, has the potential to negate the necessity of the other competencies as a higher-order measure of laboratory literacy that incorporates other competencies of accessing, interpreting, and applying information, or perhaps as a high-level competency that builds upon these other competencies. It is an interesting proposition that having proficiency in acquiring external information to supplement their understanding might offset the health literacy effects of deficits in other competencies.Many health literacy tools lack components that specifically address concepts necessary for laboratory literacy. The development process of future health literacy tools should include careful consideration as to the value of incorporating laboratory literacy into their design as a distinct domain within health literacy. We believe further studies surrounding the topic of laboratory literacy are warranted, and many can be envisioned that address a host of interesting research questions. We would suggest an investigation into how the relevant competencies of laboratory literacy might change in importance and utility in the context of one disease compared to another. We would also suggest exploring if competency 8Additionally, an understanding of laboratory literacy among healthcare providers is also an important area of future investigation. Most, if not all, of the competencies identified for laboratory literacy would appear to be applicable to both patients and providers. Analogous to the challenges facing patients, an expanding array of diagnostic assays may pose challenges to providers in each of the competencies we have identified. Studies of the broader topic of health literacy among providers are relatively new, with only a single recent study suggesting gaps in health literacy awareness and limited use of guidelines to communicate more effectively with patients.When considering the impact that this field of research can have on the patient level, the provider level, the health system level, and the national level, we believe that this is a worthy area of further study. This field of inquiry into the relationship between laboratory testing and health literacy has the potential to produce knowledge that can be used to improve health literacy assessments, healthcare delivery, and ultimately to help reduce healthcare disparities and improve patient outcomes.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.10.13039/100016205Association of Pathology Chairs to produce the next generation of outstanding investigators and educational scholars in the field of pathology. This award helps to promote the publication of high-quality original scholarship in Academic Pathology by authors at an early stage of academic development.The article processing fee for this article was funded by an Open Access Award given by the Society of ‘67, which supports the mission of the 10.13039/100010941University of Vermont Roy and Lorraine Korson Green and Gold Professorship and the 10.13039/100010941University of Vermont Larner College of Medicine Summer Medical Research Fund.This study was supported in part by the


Plasmodium falciparum gametocytes within erythrocytes (P. falciparum antigen in the patient’s blood. Abdominal ultrasonography identified a patchy hypoechoic lesion in the spleen (,On the final day of a 3-day oral artemether-lumefantrine combined malaria treatment, a 30-year-old man in the infectious diseases ward began experiencing pain in the left hypochondriac region. A peripheral smear examination revealed the presence of banana-shaped hrocytes . Additioe spleen , which we spleen . Observa


Here, that will be shown just for the general question of whether rates of left-handedness differ in neurodegenerative disorders.Handedness, behavioural asymmetry, and brain lateralisation are of wide interest in biology and neuroscience,2 compared 12 478 individuals who had neurodegenerative disorders with 17 670 cognitively unimpaired (CU) individuals. The abstract describes ‘small differences’, and as A), differ between the four study groups: controls (CU: 10.10% NRH), and the three neurodegenerative groups . A key question, particularly given the large sample size, is whether such differences are meaningful, particularly in the Bayesian sense of asking whether the evidence may be in favour of the null hypothesis of no differences between the groups, a question that cannot be answered with conventional, frequentist statistics of the sort used by Saari and Vuoksimaa.2Saari and Vuoksimaa2 = 11.368, 3 df, P = 0.0099, which seems to suggest there may be a significant difference, and that the null hypothesis, H0, of no differences between the groups should be rejected in favour of the alternative hypothesis, H1. There are problems though. Large sample sizes with conventional tests over-estimate evidence against the null hypothesis5 and are almost certain to become significant, albeit with very small effect sizes, as sample sizes grow.7 More crucially, conventional tests can provide no evaluation of whether the data provide more support for the null hypothesis or the alternative hypothesis.Comparing RH and NRH rates across the groups, a conventional chi-square test gives χ8 However, as Jamil et al. pithily put it, Bayesian analyses seem as though they can, ‘be understood and used only by those with a high level of statistical sophistication, a fetish for archaic notation, and a desire for programming and debugging’.5 As a result, Bayesian methods are often not used by scientists, with software being hard to find and hard to use. A practical solution is the package JASP (https://jasp-stats.org/), where JASP stands for ‘Jeffreys’s Amazing Statistics Program’, in which a simple spreadsheet interface provides a straightforward way of carrying out Bayesian analyses as well as conventional null-hypothesis significance tests.10 Saari and Vuoksimaa2 carried out their analyses in R, for which the function contingencyTableBF in the package BayesFactor can carry out the same analyses as JASP.5The solution is a Bayesian analysis, with the approach going back to that of Jefferys.10), or the odds ratio for the null hypothesis relative to the alternative hypothesis (BF01), each being the reciprocal of the other. Odds ratios greater than one provide support for the hypothesis being tested, whereas those less than one are opposed to it.Bayesian analysis assesses the Bayes Factor (BF), an odds ratio either for the alternative hypothesis relative to the null hypothesis . The odds in favour of H1, of there being a difference, are very low indeed (i.e. much less than one), whereas the odds in favour of the null hypothesis being the better description are very high, it being 1524 times more likely that H0 better describes the data than does H1. For comparison with conventional significance tests, with a small sample size (perhaps 20–50) a BF of 3 (‘moderate evidence’5) is roughly equivalent to about P < 0.05, and a BF of 100 (‘extreme evidence’5) is broadly equivalent to P < 0.001. However, these relationships depend on sample size, and for the present data with its 30 000 participants, and following the method of table 9 of Raftery,7 more significant conventional P-values are needed; for a BFs of 3 (moderate evidence) needing P ≈ 0.002 (rather than P = 0.05) or for a BF of 100 (extreme evidence) of about P ≈ 0.00006 (rather than P = 0.001). On that basis, the conventional chi-square statistics found in the present study might just about provide moderate evidence for a difference. Of course, null-hypothesis significance testing cannot ask what is the evidence for no difference, which the full Bayes approach can do, and then there is extreme evidence BF >>100) in favour of the null hypothesis. Despite the marginal chi-square tests, there is far more reason to accept that there are no differences in NRH rates between the groups. A fundamental advantage of Bayesian analysis is that it quantifies support for the null hypothesis.Comparing the rate of NRH across the four groups of P < 0.001’, presumably using a χ2 test. For those data, JASP gives χ2 = 27.62, 6 df, for which P = 0.00011. The Bayesian analysis, however, gives BF10 = 0.00000235 and BF01 = 426 277. The data are once again extremely strongly in favour of the null hypothesis of no difference between groups .Although in the bulk of their paper, Saari and Vuoksimaa only compare RH and NRH, handedness for CU, AD, DLB, and bvFTD are compared using a RH/A/LH grouping, shown in compellingly negative, strongly supporting the absence of any difference in rates of handedness between the groups. Interpreting negative evidence is always difficult, particularly for small studies lacking statistical power. Bayesian analysis can however say when absence of evidence (non-significance) is indeed evidence of absence, and here, it is clear that evidence for right and left-handedness being associated with neurodegenerative diagnosis is indeed compellingly negative.Bayesian analysis in this case provides evidence for differences being fcad162_Supplementary_DataClick here for additional data file.


Our aim was to evaluate the association between eHealth literacy and lifestyle behaviors to intervene among Chinese university students.The Chinese eHealth Literacy Scale (C-eHEALS) questionnaire was used to investigate the eHealth literacy level and association with lifestyle behaviors among Chinese university students. Independent sample t-test and Pearson’s correlation coefficient were used by statistical software SPSS v20.In the first round, 5,151 university students participated in the study, including 71.46% female and 28.54% male, aged 18–22 (93.13%).The average eHealth literacy score was 26.81 ± 5.83. Four lifestyle behaviors  were all significantly correlated with eHealth literacy scores and demonstrated significant differences. In the second investigation , the average eHealth literacy score was 31.64 ± 6.44, a notable improvement compared with the first investigation.Those in the group with high eHealth literacy scores have a healthier lifestyle than those in the low-score group. Training in eHealth-related resources is a positive measure to improve university students’ eHealth literacy. The Internet has become the main source of health-related information. More and more teenagers use the Internet to obtain health information,4, including university students. The ability to find, understand and evaluate health-related information from electronic resources and apply it solving health problems is called eHealth literacy. eHealth literacy has been regarded as a public health goal in the 21st century and a major challenge facing global health care. While the current generation of university students can obtain a large amount of health information online, access alone cannot ensure that students skillfully search for such health information; their ability to obtain and evaluate electronic health information still has much room for improvement.With the increasing use of Internet and mobile technology, everyone can access information anywhere and at any time. However, university students are prone to engaging in dangerous health behaviors, such as smoking and drinking. It is crucial for university students to obtain a healthy lifestyle to protect and promote their health, and to maintain these behaviors in adulthood. Lifestyle is defined as voluntary activities of daily life, such activities are a regular part of daily life and can seriously affect one’s health. Therefore, eHealth literacy is an important factor for university students in maintaining a healthy lifestyle and good health.University students comprise a special social group, a balanced diet, reasonable nutrition supply and eating habits are particularly important critical to their physical and mental health development. Healthy lifestyle behaviors, such as regular exercise, good sleep, and breakfast, have an important impact on their lives. Research showed that in the general population, those with higher levels of eHealth knowledge demonstrated a healthier lifestyle than those with lower levels. In the case of college students, few studies have detailed the relationship between eHealth literacy and lifestyle behaviors such as regular exercise, healthy diet and regular sleep, such studies have been conducted in Taiwan, Greece and the United States,15,16. The impact of eHealth literacy on lifestyle behavior varied by country, cultural background and Internet use,17,18. To date, such studies are lacking in China. Accordingly, we set out to evaluate the eHealth literacy level of Chinese university students and the associations with lifestyle behaviors.The eHealth literacy scale, an 8-item questionnaire designed to measure self-perceived eHealth literacy skills, is comprised of six core skills, or literacies: traditional literacy, health literacy, information literacy, scientific literacy, media literacy, and computer literacyThis non-experimental comparative correlation study used quantitative research methods with intervention. The intervention measure carried out more than two eHealth-related trainings for 5,151 participants, and randomly selected 2,939 participants for a second analysis to explore the association between eHealth and lifestyle behaviors among Chinese university students, in order to verify eHealth literacy levels and to measurement the effectiveness of eHealth training intervention.University students were recruited from Xinyang University in China, with the stated goal of examining associations between eHealth literacy and lifestyle behaviors among Chinese university students. Two rounds of investigation were conducted from October to December 2021.All participants were native Mandarin speakers majoring in liberal arts and science, from freshman to senior years. Most were aged 18–22 years old. Participants who did not complete the survey were excluded..The C-eHEALS comprises 8 items to which participants respond on a 5–point Likert scale, ranging from 1 for “strongly disagree” to 5 for “strongly agree”, with a total score varying 8 and 40. Data were collected through the online questionnaire created with Wenjuanxing software. Participants were recruited by WeChat, a social media application widely used in China. WeChat was chosen because users are verified, rendering virtually zero possibilities of fake profiles. The researchers sent the questionnaire link to a group of teachers on WeChat and asked them to share it with their students. The questionnaire was anonymous and participants did not receive any payment.The research was conducted in two-stages at two months apart. After the first part, participants were trained at least twice in eHealth-related resources. The aim of the second interview was to explore whether eHealth-related training improved eHealth literacy of university students. Nine indicators, including sex, age, only child, origin, parental education level, major, grade, and number of Internet devices were collected, via the Chinese version of the eHealth Literacy Scale (C-EHEALS) questionnaireLifestyle behaviors were assessed by the following questions of exercise, breakfast, smoking, drinking and sleeping for statistical analysis. Answers to exercise frequency  were divided into two groups regular (≥ 1 day/week) and none or unregular (< 1 day/week). Answers to breakfast frequency  were divided into two groups: having breakfast (≥ 1 day/week) and none (< 1 day/week). Answers of smoking  were divided into two groups: smoking (≥ 1 time/week) and none (< 1 day/week). Answers of drinking  were divided into two groups: drinking (≥ 1 time/month) and none (< 1 day/month). As for sleeping, answers of  were divided into two groups: good (≥ 7 hours/day) and poor (≤ 6 hours/day).The data are presented through descriptive statistics , according to the nature of the variables (quantitative). Reliability and validity of the questionnaire was verified through Kaiser–Meyer–Olkin (KMO) test and Cronbach’s Alpha. The correlation between variables was determined by independent sample t-test and Pearson’s correlation coefficient. The statistical significance was 0.1% and the analyses were assisted by statistical software SPSS v20.This study was performed in compliance with the Helsinki Declaration guidelines. All procedures relevant to study participants were approved by the ethics committee of Xinyang University. Participation was voluntary; participants were informed of the study objective and context and provided their written informed consent regarding privacy and information management policies.The C-eHEALS scores of 5,151 university students ranged from 8 to 40; the mean and standard deviation were 26.81 and 5.83, respectively. The Kaiser–Meyer–Olkin (KMO) test showed an overall KMO value of 0.914. Individual KMO values varied from 0.880 (Item-7) to 0.946 (Item-8). For the eight C-eHEALS items, Cronbach’s Alpha were all above 0.9, varying from 0.921 (Item-3 and Item-4) to 0.929 (Item-7). Thus, the C-eHEALS showed excellent reliability .p < 0.001, p < 0.001), while the C-eHEALS with high parental education was also significantly higher than that of students with low parental education (p < 0.001). Overall, the characteristics of sex, region, parental education level, and major had a significant impact on the eHealth literacy scores of Chinese university students.The average C-eHEALS score of male was 1.95 higher than that of females , Jordanian nursing students (28.96), or adults in Iran (28.2) and Kuwait (28.6). The score was also lower than that of nursing university students in Sri Lanka (28.02) and Japan medical departments (27.0), and firstyear students in the Faculty of Health Sciences at a university in Turkey (27.5). In certain Asian, American and European countries, the eHealth scores of the general population were also relatively high, ranging from 28.1 to 30.5,25. Although the score in this study is low, it is still higher than that of Japanese adults (23.4) and university students(23.6). The eHealth literacy score increased to 31.64 after participants trained for twice or more, indicating that the training of eHealth-related resources is effective in improving university students’ eHealth literacy.Herein, the first average score of C-eHEALS was 26.81, lower than that of young adults in Pakistan (29). The Chinese government has increasingly aimed to provide health-related information on social media, while numerous American and international websites provides health and medical information with Chinese. Thus, eHealth literacy training has the potential to quickly improve the eHealth literacy of university students. Conversely, the relative lack of an effective online medical system in Japan is considered central to the low level of eHealth literacy in Japan compared with Europe. Accordingly, colleges and universities in China and elsewhere should strengthen health and medical science education, optimize network health information services, fortify the training of eHealth-related resources, and provide a good environment for improving the evaluation and application ability of college students’ eHealth information. These measures will help discourage so as to urge them to change dangerous lifestyle behaviors and improve overall quality of life.During the COVID-19 pandemic, the Internet has been a particularly important mode for the dissemination of information. China offers a higher and more reliable source of health information, providing people with knowledge and suggestions on COVID-19 health protection than beforeAmong limitations of this study only eHealth-related resource training intervention was chosen without other intervention measures for comparison. Health professionals require further eHealth literacy research to explore a variety of interventions, in order to help university students achieve healthier lifestyle behaviors.This study used quantitative research methods with intervention to comprehensively analyze the intervention and association between eHealth literacy and lifestyle behaviors among Chinese university students. We found a positive association between university students’ eHealth literacy and lifestyle behaviors. Those in the high-score eHealth literacy group demonstrate a healthier lifestyle than those in the low-score group. Training in health-related resources was a useful measure in improving university students’ eHealth literacy. Most college students have poor exercise behaviors, a factor that requires special consideration when carrying out eHealth-related resource training, especially for the low eHealth literacy group.


In civil society we expect that policy and management decisions will be made using the best available evidence. Yet, it is widely known that there are many barriers that limit the extent to which that occurs. One way to overcome these barriers is via robust, comprehensive, transparent and repeatable evidence syntheses (such as systematic reviews) that attempt to minimize various forms of bias to present a summary of existing knowledge for decision-making purposes. Relative to other disciplines , such evidence-based decision-making remains relatively nascent for environment management despite major threats to humanity, such as the climate, pollution and biodiversity crises demonstrating that human well-being is inextricably linked to the biophysical environment. Fortunately, there are a growing number of environmental evidence syntheses being produced that can be used by decision makers. It is therefore an opportune time to reflect on the science and practice of evidence-based decision-making in environment management to understand the extent to which evidence syntheses are embraced and applied in practice. Here we outline a number of key questions related to the use of environmental evidence that need to be explored in an effort to enhance evidence-based decision-making. There is an urgent need for research involving methods from social science, behavioural sciences, and public policy to understand the basis for patterns and trends in environmental evidence use (or misuse or ignorance). There is also a need for those who commission and produce evidence syntheses, as well as the end users of these syntheses to reflect on their experiences and share them with the broader evidence-based practice community to identify needs and opportunities for advancing the entire process of evidence-based practice. It is our hope that the ideas shared here will serve as a roadmap for additional scholarship that will collectively enhance evidence-based decision-making and ultimately benefit the environment and humanity. On the surface, the concept of evidence-based decision-making is simple—evidence is used to help make decisions. However, the reality is much more complex. Evidence comes in many forms and it is easy to intentionally make selective use of evidence to support a position. For that reason, evidence-based decision-making should be based on the synthesis of all available evidence. However, not all evidence syntheses are robust and can themselves introduce bias . MoreoveAs the environmental sector begins to embrace the notion of evidence-based decision-making , 7, it iWe present each key question along with a brief overview of the context for the questions and potential approaches for answering them. Who addresses these questions varies with each question. In some cases it is the “researcher” while in others it is the broader evidence synthesis community. This is a compilation of ideas based on the lived experiences, knowledge, and perspectives of the international team of authors. All of the authors work in some aspect of the evidence generation, synthesis and application ecosystem.There are many different forms of evidence, including scientific, expert, experiential, local and Indigenous knowledge , 10. Eacwww.evidence2decisiontool.com) have been developed to guide practitioners through a structured process to transparently document and report the evidence that contributes to decisions (see [https://www.conservationevidence.com/) subject-wide evidence syntheses found that well-summarized evidence can direct management choices away from ineffective interventions when it is timely and packaged in a form that meets the needs of practitioners [Contrary to what many in the scientific research community might assume, evidence, especially peer-reviewed science, is rarely the first or most widely used nor the most valued source of information considered in environmental decisions . Severalons (see ). Futureons  or in living evidence syntheses’ (see below) is unlikely to be attractive to individual organisations and may require consortia to ensure aspects of low cost, timeliness and accessibility are provided. Nonetheless, such efforts should be pursued.There are many aspects of the evidence synthesis process that might make them more or less valued by evidence users. The emphasis of systematic review methodology is on estimating the truth whilst reducing risk of bias through replicability of methods, transparency of reporting and critical appraisal of study validity. The extent to which this approach results in useful information to the users depends primarily on the extent and validity of the existing primary evidence. Other aspects such as relevance to need, cost, timeliness, accessibility, certainty, might be of higher priority to an evidence user. Trade-offs in the reliability of evidence and these other characteristics will differ depending on the pressures of the decision-making process (e.g. the risk of making the wrong decision). There is a gap in dialogue between producers and users on how to prioritise these aspects when planning syntheses. Co-production of evidence syntheses is often promoted as a way of selecting both a relevant and valid question and the appropriate synthesis method (e.g. rapid versus systematic review or Mapping evidence versus estimating effects) is a logical next step. Investment in general services  to a wide range of interested parties, which could include policymakers, local decision makers (e.g. Nature reserve managers), local people and the public at larger. One effective form of communication is through the use of diagrams, as they help the user understand the evidence synthesis question(s) and results . IncreasBoundary spanning is one of many approaches intended to enable evidence-based decision-making. It is a concept that emerged from the business and organizational management fields in the 1970s to facilitate knowledge sharing and exchange between two or more entities . In the It is one thing to provide evidence users with evidence in reliable and usable forms (such as systematic reviews), yet underpinning that is the need to create a culture of evidence use among individuals and organizations such that robust syntheses are embraced and used. The outstanding question—is how to do so? Little is known about this in the context of environmental evidence emphasizing much scope for empirical research with key informants. However, there are learnings and lessons from other knowledge domains. In mental health, clinicians are required by insurers to provide evidence that interventions being used are effective—a “top down” mechanism for creating (or forcing) a culture of evidence use and assessment of effectiveness . The crehttps://www.britishecologicalsociety.org/applied-ecology-resources/about-aer/additional-resources/evidence-in-conservation-teaching/). Training specific to evidence-based medicine has been sufficiently well studied that Illic and Maloney [Decision makers are increasingly aware of the need to make their work evidence informed but, with a suite of different methods and terminologies for synthesis methods, it can be difficult for potential users of evidence to know which methods to select to inform decisions, and how reliable or appropriate each may be. There are tools and resources that can help support decision makers in this. For example, the EU Eklipse Mechanism has created a summary of different knowledge synthesis methods, together with their respective costs, time requirements and robustness , but for Maloney  were ablHow government policymakers use evidence in their decision-making has long been the focus of scholarship . Yet, maSo called “modern scientific knowledge” predominates in evidence syntheses for good reason. Such knowledge is often shared via peer reviewed publications that are archived, searchable, and accessible. Ideally such research is conducted in a manner that minimizes biases. Moreover, there are accepted protocols for evaluating and synthesizing such evidence. Yet, other forms of knowledge such as Indigenous science and wisdom and local knowledge are also valid and valued forms of evidence. So how do we weave or braid different types of knowledge (beyond western science) in evidence syntheses? There are a growing number of paradigms .Evidence in Action articles typically involve a discussion of the impact of evidence-based practice on environmental managers, of evidence synthesis on policy making, or a discussion of developments at the science-policy interface. This could be regional, national or global and may resemble a case study or more of a perspective article. Evidence in Action articles should include logical subheadings that guide the reader through the narrative.” Consistent with the notion that there is need to better understand the evidence synthesis and use community, we encourage papers that include diverse contributors including end users, Indigenous knowledge holders, and others that are often excluded from papers. Beyond empirical research, we also welcome reflective essays that provide candid summaries based on lived experiences in the environmental evidence sphere. Beyond the new article type, more broadly we need this work and expect that this paper could yield research that is published in a variety of outlets. We envision a not-too-distant future where the enhanced understanding of the environmental evidence and evidence-based decision-making ecosystem related to the ideas presented here represents meaningful advances in our ability to realize the promise of evidence-based environmental management.These aforementioned activities are consistent with the spirit of the journal Environmental Evidence and it is for that reason that we have created a new type of article  with the hopes that authors will submit their work in this space. As per the guide to authors “


Despite the importance of evidence syntheses in informing policymaking, their production and use remain limited in the Eastern Mediterranean region (EMR). There is a lack of empirical research on approaches to promote and use policy-relevant evidence syntheses to inform policymaking processes in the EMR.This study sought to describe the development of an impact-oriented approach to link evidence synthesis to policy, and its implementation through selected case studies in Lebanon, a middle-income country in the EMR.This study followed a multifaceted and iterative process that included (i) a review of the literature, (ii) input from international experts in evidence synthesis and evidence-informed health policymaking, and (iii) application in a real-world setting (implementation). We describe four selected case studies of implementation. Surveys were used to assess policy briefs, deliberative dialogues, and post-dialogue activities. Additionally, Kingdon’s stream theory was adopted to further explain how and why the selected policy issues rose to the decision agenda.The approach incorporates three interrelated phases: (1) priority setting, (2) evidence synthesis, and (3) uptake. Policy-relevant priorities are generated through formal priority setting exercises, direct requests by policymakers and stakeholders, or a focusing event. Identified priorities are translated into focused questions that can be addressed via evidence synthesis (phase 1). Next, a scoping of the literature is conducted to identify existing evidence syntheses addressing the question of interest. Unless the team identifies relevant, up-to-date and high-quality evidence syntheses, it proceeds to conducting SRs addressing the priority questions of interest (phase 2). Next, the team prepares knowledge translation products  for undertaking knowledge uptake activities, followed by monitoring and evaluation (phase 3). There are two prerequisites to the application of the approach: enhancing contextual awareness and capacity strengthening. The four case studies illustrate how evidence produced from the suites of activities was used to inform health policies and practices.To our knowledge, this is the first study to describe both the development and implementation of an approach to link evidence synthesis to policy in the EMR. We believe the approach will be useful for researchers, knowledge translation platforms, governments, and funders seeking to promote evidence-informed policymaking and practice. There is growing recognition that the use of evidence in health policymaking can strengthen health systems, accelerate progress on achieving the Sustainable Development Goals (SDGs), and improve population health –5. Most Evidence syntheses use formal explicit rigorous methods to provide an account of the totality of what is known from preexisting research . They caDespite their importance in informing policymaking, the production and use of evidence syntheses remain limited in the Eastern Mediterranean region (EMR) –17. A stThere has been mounting interest over the years in the use of frameworks, approaches, and models to gain insights into mechanisms by which uptake and use of evidence is more likely to succeed –28. NoneIn the EMR, there is a lack of empirical research on approaches to promote and use policy-relevant evidence syntheses to inform policymaking processes. In an effort to address the aforementioned gaps, we developed an “impact-oriented approach to link evidence synthesis to policy,” hereby referred to as “approach.” In this paper, we describe the approach followed by its implementation through selected case studies in Lebanon, a middle-income country in the EMR. It is worth noting that at the time of its development and implementation, Lebanon was classified by the World Bank as an upper middle-income country but since then has suffered a series of crises and is now classified as a low middle-income country .(i)Review of literatureWe followed a multifaceted and iterative process that included (i) a review of the literature, (ii) input from international experts in evidence synthesis and evidence-informed health policymaking, and (iii) application in a real-world setting (implementation) through selected case studies Fig. .(i)Revi(ii)Input from international expertsWe conducted a literature review to identify approaches/frameworks/models/strategies associated with evidence synthesis knowledge translation and evidence-informed health policymaking. We used the following combination of terms to search Medline and PubMed: (research OR evidence OR knowledge) AND (synthesis OR translation OR uptake OR implementation OR use) AND (approach OR framework OR model OR theory). The articles were screened by two members of the team for relevance. We included papers that focused on promoting evidence-informed health policymaking, with priority given to evidence synthesis. We generated a preliminary list of framework attributes from all relevant papers. The attributes were reviewed and discussed with all members of the team, taking into consideration the experience and learning from two collaborating knowledge centers established at the American University of Beirut (AUB) in Lebanon to address high priority policy issues. First, the Center for Systematic Reviews of Health Policy and Systems Research (SPARK) specializes in the production of policy-relevant systematic reviews and other evidence synthesis products in the field of health policy and systems research. Second, the Knowledge to Policy (K2P) center specializes in knowledge translation products (leveraging existing evidence synthesis), knowledge uptake activities, and impact assessment. Both SPARK and K2P form a unique collaboration to promote evidence-informed health policymaking in Lebanon and the EMR. A preliminary version of the approach was subsequently generated.(iii)Application in a real-world settingWe sought input from two groups of experts. The first group included participants in a workshop on an approach and tool for prioritizing questions for evidence synthesis in health policy and systems research at the 22nd Cochrane Colloquium in Hyderabad, India.The approach was implemented by SPARK and K2P centers to address high-priority policy issues. For the purpose of this study, we focused on the following four issues: (1) enhancing access of Syrian refugees to basic healthcare services; (2) promoting quality of pharmaceuticals; (3) addressing medical errors in hospitals; and (4) integrating palliative care into the healthcare system. These have been selected for two main reasons: the first being pragmatic considerations, including the availability of relevant documents on the cases, and the second being that these issues represented a diversity in the source of prioritization, conduct of evidence synthesis, and impact achieved. The uniqueness of each case study as well as intersection points will enable cross-comparisons across the different components of the framework, which in turn will help build a more comprehensive understanding of the activities and key learnings for enhancing these activities under each component of the approach.Policy brief: we adapted the evaluation survey from Lavis et al. and circulated it to participants at the dialogue and followed up with reminder emails a few days later . The surDeliberative dialogue: we also adapted the survey from Lavis et al. and circulated it to participants at the end of the dialogue . The surPost-dialogue survey: 6 months following the dialogue, we circulated a short questionnaire to 4–6 key participants purposively selected from different agencies that championed the issue of interest, each in their own capacity. The questionnaire aimed to follow-up on the deliberations that took place, track progress, and identify implementation issues pertaining to achieving impact.To evaluate “impact” of research on policy, we undertook both formative and summative evaluations. For the formative part, the following activities and outputs were evaluated using standardized tools: policy briefs, deliberative dialogues, and post-dialogue follow-up. Responses were analyzed descriptively.For the summative evaluation, we applied the “theory of change” to examine whether the set of activities and outputs presented within the different phases of the approach collectively led to impact on select policymaking processes. Theory of change allows for multiple pathways, levels of interventions, and feedback loops that better reflect the reality of how complex interventions achieve their impact . It can To further explain how and why policy issues rise to the decision agenda, we adopted Kingdon’s multiple stream model . The modThis section begins with a description of the approach followed by its implementation to selected priority policy issues.The approach incorporates three interrelated phases: (1) priority setting, 2) evidence synthesis, and (3) uptake. The prerequisites to the implementation of the approach include enhancing contextual awareness and capacity strengthening encompassing all three phases  addressing the prioritized question of interest. The identification of relevant, up-to-date, and high-quality evidence syntheses would help avoid duplication of efforts. When relevant, up-to-date, and high-quality evidence syntheses (as assessed using AMSTAR or ROBIS tools) are identified, the K2P Center team proceeds directly to preparing knowledge translation products (phase 3). Otherwise, the SPARK Center team proceeds with conducting evidence syntheses addressing the question of interest .Phase 3, uptake: this phase involves preparing knowledge translation products, undertaking knowledge uptake activities, and monitoring and evaluation to achieve impact. Central to this phase are contextual factors that influence the degree of uptake and use of evidence in policymaking.Knowledge translation products are prepared, drawing on evidence syntheses, particularly systematic reviews. One widely used product is the policy brief, which brings together global research evidence (from SRs), local evidence, and context-specific knowledge to inform deliberations about health policies and programs. An important feature of the policy brief is the involvement of end users in its development and revision to help capture tacit knowledge and contextualized evidence. Additional knowledge translation products include briefing notes and rapid response documents. The knowledge translation products are disseminated to target policymakers and stakeholders using a range of uptake activities. A widely used uptake activity is the deliberative stakeholder dialogue, which brings together research evidence from the knowledge translation product alongside local context, experiences, views, and tacit knowledge of stakeholders who will be involved in or affected by decisions about the issue to increase the prospects of using the evidence in policy . A dialoA description of each of phase of the approach is further provided below:There are two prerequisites to the application of the approach.First, it is important to start with a preparatory phase to understand the political context and the receptiveness of policymakers and stakeholders to evidence-informed health policymaking. The preparatory phase is also critical to enhance contextual and policy awareness . For exaSecond, increasing the use of evidence in policymaking requires strengthening capacity on both the supply side, in terms of capacity for generation and uptake of policy-relevant evidence, and the demand side, in terms of the demand for and use of evidence by policymakers for policy decisions. Efforts should aim to target different levels, including both individual and organizational levels, to ensure sustainability of evidence-informed policymaking and practice. For this purpose, we have adapted the capacity-building framework by Oliver et al. to develop capacity at the individual, team, organizational, and systems levels .We present here four case studies in which we implemented the approach. Table Two of the topics, Syrian refugees and quality of pharmaceuticals, were identified through formal priority setting meetings, while palliative care was generated through direct request from stakeholders, and the topic on medical errors was shaped by a focusing event in the country (phase 1). A quick scoping of the literature did not identify any updated and high-quality SRs for the two priorities identified through the formal priority setting meetings; thus, the SPARK team proceeded with conducting SRs addressing the topics (phase 2), and these were subsequently incorporated into knowledge translation products, specifically policy brief and briefing note. As for the other two topics for which there were preexisting updated and high-quality SRs, the K2P Center team directly proceeded with preparing knowledge translation products (phase 3).A range of uptake activities was undertaken to promote the use of the evidence in health policymaking and practice (phase 3). While some were common across all four case studies, such as convening deliberative dialogues (pre-informed by the knowledge translation products), there were also some notable variations. For instance, follow-up on implementation, including generation of materials to support the implementation process, was conducted for both Syrian refugees (through the development of Terms of Reference (TORs) for the refugee health coordinator to be recruited by the Lebanese Ministry of Public Health) and medical errors . For palliative care, stakeholders created a coalition of non-governmental organizations (NGOs) and engaged in additional advocacy efforts to achieve the desired impact. The issue of quality of pharmaceuticals involved personalized briefings with selected stakeholders  and media engagement  to prompt stakeholders to act on key findings from the deliberations.In all four case studies, researchers, policymakers, and stakeholders interacted at each phase of the approach, from identifying priorities to shaping priority questions  to framing the scope of knowledge translation products, to engaging in deliberative dialogues, and finally to monitoring and evaluation to achieve the desired impact.Different types of evidence were collectively used throughout the approach. While scientific knowledge were derived from research (for the evidence syntheses) and local data (for the knowledge translation product), tacit knowledge was derived from stakeholder interviews as well as elicited through deliberative dialogues and personalized debriefings with policymakers and stakeholders.A total of 26 and 29 participants, respectively, completed the policy brief and deliberative dialogue evaluation surveys for two of the four case studies . Results of the evaluation of the policy brief and deliberative dialogue are presented in Table Post-dialogue follow-up with key selected stakeholders revealed positive attitudes toward research evidence of the type discussed at the dialogues, as well as strong intentions to use research evidence and actual adoption and implementation of some of the evidence-based policy options. For the latter, documentation review and media analysis were also conducted to further capture and document impact.Boxes Box 1: Process adopted and impact achieved for the topic of promoting Access to essential health care services for Syrian refugeesIssue: Syrian refugees in Lebanon face a high burden of communicable and non-communicable diseases. Providing health services to this large number of refugees is a real challenge, given limited capacity of the health system and the preexisting economic crisis in Lebanon.Priority setting: Formal priority-setting exercise brought together 54 policymakers who were representatives from the Ministry of Public Health (MOPH), Lebanese National Council for Research, World Health Organization (WHO) Country Office, United Nations Development Programme, United Nations High Commissioner for Refugees (UNHCR), United Nations Relief and Works Agency for Palestine Refugees in the Near East, International Organization for Migration, and UK Department for International Development, in addition to academics and researchers. Participants shaped and prioritized the question of limited coordination between organizations and agencies providing health services to refugees.Evidence synthesis: Production of two systematic reviews addressing the questions identified in the priority setting step:Addressing Mechanisms and Models of Coordination between Organizations, Agencies and Bodies Providing or Financing Health Services in Humanitarian Crises: A Systematic ReviewCoordinating the Provision of Health Services in Humanitarian Crises: A Systematic Review of Suggested ModelsKnowledge translation product: A briefing note titled “Promoting Access to Essential Health Care Services for Syrian Refugees in Lebanon.” Findings from the two systematic reviews were incorporated into the briefing note. In addition to key findings from the systematic reviews, the briefing note synthesized other relevant global and local research evidence, and contextualized the evidence to the Lebanese health system. Policymakers and stakeholders were involved in shaping and framing the outline for the briefing note.Knowledge uptake activities: A national policy dialogue, titled “Promoting access to essential health care services for Syrian refugees in Lebanon” informed by the briefing note. The dialogue was attended by 28 policymakers and stakeholders involved in providing and/or financing health services for refugees in Lebanon as well as representatives of the refugee population. A post-dialogue summary was prepared and disseminated to all participants. Follow-up on implementation was conducted with key selected policymakers and stakeholders.Impact:Recruitment of a Refugee Health Response Coordinator at the Ministry of Public Health. The coordinator has helped the Ministry of Public Health to establish partnerships with local and international agencies, donors, and academic institutions; develop a refugee health information system; and assist in overseeing the development and implementation of the comprehensive strategic plan for responding to the health needs of Syrian refugees in Lebanon (informed by the briefing note). The coordinator reconvened all of the stakeholders who participated in the policy dialogue to form a Health Steering Committee. The coordinator developed the Health Response Strategy, with guidance from a number of officials and policymakers in the MOPH; this document was released in late 2015 and then updated in 2016. By developing this national strategy, the MOPH assumed a leadership role in coordinating and guiding health response efforts.Reference Document: “This work has made significant progress in addressing the recommendations above and in promoting better access to basic health-care services to Syrian refugees,” says Dr Ammar . https://www.who.int/evidence/resources/publication/en/http://www.moph.gov.lb/userfiles/files/Strategic%20Plans/HRS-DRAFT8.pdf),Health response strategy: a new approach in 2016 & beyond. Beirut: Lebanese Ministry of Public Health; 2015 ; dominance of brand name drugs (> 70%); and reported cases of counterfeit and substandard drugs.Priority setting: Two-step process:Selection of topics: Considered the priorities from two previously conducted priority-setting exercises followed by informal consultations with selected policymakers and stakeholders. One of the topics that emerged was on strengthening pharmaceutical policies in Lebanon.Strategies to reduce counterfeit and substandard drugsStrategies to improve prescribing of drugs.Selection of questions: Formal priority-setting exercise bringing together 15 policymakers and stakeholders including representatives from the Ministry of Public Health; representatives from different orders and syndicates; representatives from academic medical centers, medical schools, and schools of pharmacies; healthcare managers and academic researchers; representatives from international and national agencies; and representatives from insurance companies. Participants shaped and prioritized the following two questions:Evidence synthesis: Production of a series of systematic reviews addressing the questions identified in the priority-setting step. One of the policymakers from the priority-setting phase was involved in co-production of the first systematic review (interventions to combat or prevent drug counterfeiting):Effectiveness of interventions to combat or prevent drug counterfeitingLegislative, educational, policy & other interventions targeting physician-pharmaceutical industry interactionsAssociation between physician-pharmaceutical industry interactions and clinical practicesExtent and type of interactions of physicians with pharmaceutical industry.Knowledge translation product: Policy brief titled “Improving the Quality and Prescribing of Pharmaceuticals in Lebanon.” Findings from the systematic reviews were incorporated into the policy brief. In addition to these key findings, the policy brief gathered and synthesized other relevant global and local research evidence, and contextualized the evidence to the Lebanese health context. Key policymakers and stakeholders were involved in shaping and framing the outline for the policy brief.Knowledge uptake activities: A national policy dialogue titled “Improving the Prescribing Pattern and Quality of Pharmaceutical Drugs in Lebanon,” which was attended by 25 policymakers, practitioners, different orders, and syndicates and researchers involved or affected by pharmaceutical sector in Lebanon. A post-dialogue summary was disseminated to all participants. Personalized briefings were conducted with selected policymakers from the MoPH and Deans of Schools of Medicine. Media engagement was leveraged to maintain momentum and pressure for change.Impact:Revision of Code of Ethics for Pharmaceutical PromotionIntegration of clinical pharmacy services in health care organizations Revision of undergraduate medical curricula at AUB to incorporate education about industry marketing techniquesReference Document: The code is ready to be launched after finalization as a result of a wide participatory process that lasted for 2 years with all relevant stakeholders https://www.moph.gov.lb/en/view/4753/drugs-ethical-standards-https://www.moph.gov.lb/en/Pages/3/20553/accreditation-standards-for-hospitals-in-lebanon-january-2019The revised hospital accreditation standard includes a new chapter on clinical pharmacy services: Box 3: Process adopted and impact achieved for the topic of addressing medical errors in the health systemIssue: There is insufficient attention to quality and patient safety in healthcare; no explicit national policy for quality improvement and patient safety that sets out goals and indicators, clarifies roles and responsibilities, and identifies incentives and non-incentives across the entire healthcare spectrum.Priority setting: Focusing event . Subsequent discussions with policymakers from the Ministry of Public Health led to refinement of topic as follows: Effectiveness of interventions to address medical errors in the healthcare system.Evidence synthesis: Identification and leveraging of preexisting systematic reviews addressing the prioritized topic.Knowledge translation product: Policy brief titled “Addressing medical errors in the Lebanese healthcare system.” Findings from the identified systematic reviews as well as other relevant global and local research evidence were incorporated into the policy brief, and subsequently contextualized to the Lebanese health system. Key policymakers and stakeholders were involved in shaping and framing the outline for the policy brief.Knowledge uptake activities: Policy dialogue; post-dialogue summary report; personalized debriefings; follow-up on implementation through the establishment of national standards for patient safety including training requirements for the hospital accreditation program.Impact:Incorporation of patient safety goals, indicators, and training requirements in the national accreditation standards of the hospital accreditation programs in LebanonRevision of the contractual agreements with healthcare organizations in Lebanon to incorporate selected quality indicators as part of the reimbursement formulaReference Document: The Ministry of Public Health announced the official publication of the new accreditation standards manual for hospitals. https://www.moph.gov.lb/en/Pages/3/20553/accreditation-standards-for-hospitals-in-lebanon-january-2019Box 4: Process adopted and impact achieved for the topic of integrating palliative care into the health systemIssue: The high burden of non-communicable diseases (NCDs) and the rapidly aging population in Lebanon makes palliative care (PC) an essential component of health services needed to relieve the suffering of patients. In Lebanon, the demand for PC is expected to increase with the aging population and the high burden of NCDs. In 2015, Lebanon had the highest percentage of people aged 65 years and older (7.3%) in the Arab region and this number is projected to reach 12% by the year 2030.http://nna-leb.gov.lb/en/show-news/93313/nna-leb.gov.lb/enStatus quo: Palliative care services in Lebanon are not accessible to a wide range of patients due to barriers at the organizational, system, professional, and patient levels. PC services are not financially covered by public and most private insurance parties. In addition, Lebanon does not have a national PC law or a stand-alone national plan to support PC development and integration.Priority setting: Stakeholder-driven (push from NGOs).Evidence synthesis: Identification and leveraging of preexisting systematic reviews addressing the prioritized topic.Knowledge translation product: Policy brief titled “Integrating Palliative care into the Health System.” Findings from the existing systematic reviews in addition to other global and local research evidence were incorporated into the policy brief, and subsequently contextualized to the Lebanese health system. Key policymakers and stakeholders were involved in shaping and framing the outline for the policy brief.Knowledge uptake activities: Policy dialogue; post-dialogue summary report; and advocacy through coalition of NGOs.Impact:Issuance of a Ministerial Decree on reimbursement for palliative care. On 18 March, the Ministry of Public Health took a major step toward integrating palliative care into the Lebanese health system by issuing Decree 1/447 that defines criteria for the reimbursement of palliative care services. The decree defines coverage for both home- and hospital-based programs and provides a blueprint for a reimbursement structure that can be applied by the National Social Security Fund (NSSF) and private insurers.Reference Document: https://www.executive-magazine.com/economics-policy/lebanons-ministry-of-public-health-issues-decree-on-reimbursement-for-palliative-caresystemOur interpretive assessment of changes to public policy process, according to Kingdon’s streams theory, revealed that the convergence of the problem, policy, and politics streams opened a window of opportunity to bring the issue to the decision agenda, propelling government action Table . The proTo our knowledge, this is the first study to describe both the development and implementation of an impact-oriented approach to link evidence synthesis to policy in the EMR. The approach incorporates three phases: (1) priority setting, (2) evidence synthesis, and (3) uptake. It encourages researchers, policymakers, and stakeholders to interact at each phase to achieve the desired impact. The approach can support evidence-informed policymaking and practice by aligning evidence synthesis production to policy priorities, fostering interactions between researchers and policymakers, and utilizing a range of knowledge translation and uptake activities to achieve policy impact and action , 41–43. Moreover, the approach recognizes that evidence-informed health policymaking is a complex phenomenon, and that contextual factors need to be taken into consideration if evidence is to be influential; in doing so, it contests the simple, linear conceptualization of the relationship between research and policy, built upon a singular input of research and independently of policy or politics , 49. As Application of the approach has generated some important lessons to optimize its use and promote evidence-informed policymaking and practice within and beyond Lebanon. Below, we reflect on some of the key lessons learned:Build trust and create demand for evidence Lack of trust can be an initial barrier for policymakers to engage with evidence, thus highlighting the need to challenge existing preconceptions and build confidence in evidence-informed health policymaking and practice [practice . BuildinEngage policymakers and stakeholders early on and ensure their engagement throughout the process (co-production approach) Engaging policymakers and stakeholders at each step of the approach is critical to ensuring relevance, accessibility, and uptake of evidence in policymaking and practice. In all four case studies, deliberate decisions were made to engage key national policymakers, professional associations, nongovernmental organizations, and other stakeholders in each phase from shaping priorities, to framing the evidence synthesis topics, to refining the outline for knowledge translation products, to contextualizing policy options in the policy dialogue, and finally, impact assessment. This level of engagement helps create a sense of ownership and increases commitment of policymakers and stakeholders, which in turn increases the likelihood of the evidence being used in policymaking and practice. The COVID-19 pandemic further re-enforced the importance of co-production for policymaking, where researchers work together with knowledge users  to identify a problem and produce knowledge, sharing power and responsibility from the start to the end of the research [research  AlthoughAlign research production with policy priorities (and identify window of opportunity for action) To generate research that can inform and guide policy, it is critical to link the production of evidence syntheses to the needs and priorities of policymakers. Priority setting is the first, and often missing, step in connecting evidence syntheses with policy needs. Furthermore, recognizing a window of opportunity for action  is another critical factor to increasing policy relevance, and thus the subsequent uptake of evidence in policymaking.Evidence synthesis alone is unlikely to lead to impact; contextualization and dissemination of actionable evidence are critical While systematic reviews or other syntheses of global evidence are increasingly recognized as a fundamental component of the evidence-informed approach to decision-making, there is growing realization that parameters of a single systematic review with one question may not always suffice to inform a national policy or program. Moreover, for systematic reviews and other evidence synthesis products to be policy-relevant and inform decisions, they need to be packaged in user-friendly format, communicated in an easy-to-understand language, and contextualized to local needs and constraints. This highlights the importance of knowledge translation products, which combine insights from multiple sources to provide context-specific and actionable evidence to enable countries to adapt global solutions to local needs and constraints.Deliberative stakeholder dialogues are highly valued knowledge uptake activities, but they may not always be sufficient to achieve impact Our experience reinforces the premise of a deliberative dialogue (informed by knowledge translation products) as a strategy for supporting evidence-informed policies and practice [practice . Respondpractice . EvidencExtend support to policy implementation Successful policy outcomes depend not only upon designing good policies, but also upon managing their implementation [entation . TraditiImpact is the driving force: make sure to measure it Integrating monitoring and evaluation early on enables teams to measure whether and how evidence was used in policy and practice, and whether the policy achieved its intended outcome and impact [d impact . While td impact .Establish linkages to complementary organizations within the evidence ecosystem No one entity may possess all skills and competencies needed for successful implementation of the approach to achieve impact. Building bridges to other complementary organizations within the evidence ecosystem produces teams of people with different backgrounds, perspectives, and complementary skills. The unique collaboration between SPARK and the K2P Center allowed for the adoption of a holistic approach spanning from priority setting to evidence synthesis, uptake, and impact assessment. Leveraging of common resources, capacities, and expertise enhanced the feasibility and effectiveness of the approach and facilitated evidence-informed health policymaking and practice.A strength of this study is that a multidisciplinary team was involved in the development of the approach with input of international experts in evidence synthesis, knowledge translation, and evidence-informed policymaking. As the first of its kind in the EMR, the study demonstrated the utility and applicability of the approach to this context. We used multiple case studies, drawing on different data sources to examine the influence of the approach on policy and capture impact. Having said this, it is important to caution that this study does not claim a cause–effect relationship emerging from the presented approach. As indicated, other factors may have also contributed to the positive changes that followed, such as recognition and interest of policymakers in the issue, alignment with existing health system reforms, and efforts made by different researchers and civil society groups to advance the issues in the country. The application of Kingdon’s model helped explain how key contextual factors facilitated the ascendancy of the issues to the health agenda.There are some limitations worth acknowledging, many of which reflect existing gaps in the science of knowledge translation as opposed to the design and execution of the study.While there is still controversy about what endpoints should be considered when it comes to impact and how they should be measured, the explicit use of evidence in the policymaking process  is a commonly used outcome , 58. As Moreover, while a single case study cannot represent all of the distinctions in approach available, our choice of diverse policy cases improved the generalizability of these results to other policy cases in Lebanon and the region. Convergence of findings from the different case studies further served as a form of validation. Nonetheless, the approach could benefit from further testing and application in other contexts to assess its generalizability as well as generate more empirical data to weigh the various components of the approach, or attribute the presence or absence of any of those components to the degree of impact. Our study and similar types of publications will serve to strengthen the science of knowledge translation, where persistent gaps continue to exist.Finally, for two of the case studies, we could not evaluate the policy briefs and the deliberative dialogues; however, we believe the findings are representative of policymakers’ perceptions in Lebanon, especially since they also align with findings from the literature across settings and topics , 59, 60.Although the path of promoting evidence-informed policies and practice is a long and winding road in the EMR , 61, 62,Future research can seek to test and adapt the approach to different contexts  and situations  to support evidence-informed policymaking and practice. In particular, the COVID-19 pandemic has highlighted the importance of timeliness of evidence, thus it may be worthy, in future initiatives, to experiment with rapid response products and ways to expedite the impact-oriented approach to provide timely responses to emerging policy priorities. In fact, both SPARK and K2P Center are scaling up their activities to provide rapid response services. More research is also needed to explore which combination of strategies and tools are most effective and in what contexts, and the relative attribution of the different components of the approach to impact.There is also a need for more research on rigorous methods and frameworks for evaluating the impact of research (and evidence synthesis) on both policy and populations, with conceptual clarity and metrics for the variety of impacts leading from research . Strengthening the research base on impacts would solidify the argument for promoting evidence-informed policies and practice.More research is also warranted on how to embed and institutionalize the use of knowledge approaches (like the one developed in this study) within policymaking processes to ensure sustainability of evidence-informed policies and practice.The impact-oriented approach linking evidence synthesis to policy will address a gap in the scientific literature. We believe the approach will be useful for researchers, governments, and funders seeking to promote policy-relevant evidence syntheses. It will help support evidence-informed policymaking and practice and reduce research waste by aligning evidence synthesis production to policy priorities, fostering researcher–policymaker interactions, and harnessing knowledge translation products and uptake activities to package, contextualize, and promote the use of evidence to achieve impact. We encourage people involved in evidence-informed policymaking to use the approach and systematic reviewers and knowledge translation platforms to conduct further testing within their own contexts as a contribution to further refining the approach.