For engaging in and taking advantage of eHealth, eHealth literacy is essential. This systematic review aims to summarise and examine the existing evidence on determinants and outcomes of eHealth literacy in healthy adults.We searched the relevant peer-reviewed articles published in English in six databases: MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and ProQuest. The inclusion criteria of the review were: 1) studies examining ‘eHealth literacy’, which refers to the ability to search, select, judge and apply online health information to address or solve health problems and to improve wellbeing; 2) the type of study included observational and experimental studies, mixed method studies or qualitative studies; 3) the participants were healthy adults; 4) the main outcomes were the determinants (i.e. influencing or associated factors) and outcomes (i.e. benefits and disadvantages) of eHealth literacy. Articles were assessed by two reviewers using the Joanna Briggs Institute critical appraisal tool. A conceptual model to map the determinants and outcomes of eHealth literacy in healthy adults into the non-modifiable, individual, social and community networks and structural layers was developed to classify the identified determinants and outcomes.Forty-four studies were included in this review, of which 43 studies were cross-sectional and one was qualitative. eHealth literacy determinants included age, sex, literacy factors, socioeconomic factors and language. eHealth literacy outcomes included better general health promotion behavior, COVID-19 preventive behaviors, psychological wellbeing, social support, self-rated health and health service utilisation.Our results showed that eHealth literacy has multi-layered determinants and positive outcomes. Different strategies at different policy levels are needed to improve the eHealth literacy levels of healthy adults. Advances in information and communication technologies (ICT) have benefitted services in all sectors including health. The use of ICT for supporting health and health-related fields, including health care services, health surveillance, health literature and health education can be referred to as electronic health  . eHealthIn order to engage in, and take the advantage of eHealth, individuals need eHealth literacy . eHealthEvidence indicates that eHealth literacy is associated with health outcomes, such as health promoting behaviors and facilitating psychological well-being across various population groups , 8, 9. OPrevious systematic reviews related to eHealth literacy were carried out across different populations, including college students , older aThe protocol for this review was registered in PROSPERO International Prospective Register of Systematic Reviews (reference number: CRD42021271346).We searched six electronic databases: MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and ProQuest to identify relevant studies. Relevant grey literature including dissertations and theses were identified from ProQuest. These databases were selected since they are among the largest and most widely recognized as authoritative sources in the fields of healthcare, medical, nursing, psychology, and behavioral sciences. They offer a comprehensive coverage of literature relevant to the eHealth literacy topic. Including other databases might introduce redundancy in the review process. These databases were chosen to strike a balance between comprehensive coverage and efficiency.A search strategy was developed to capture the key elements of the topic of interest, i.e.: determinants and outcomes of eHealth literacy. Keywords were combined using AND and OR Boolean operators. The year of publication was not limited. The detailed search strategy is presented in Studies were included if they met these criteria: 1) studies examining ‘eHealth literacy’; 2) the type of study included observational and interventional studies, mixed methods studies, and qualitative studies; 3) population/participants were healthy adults . Duplicates were identified and removed electronically (using ’Find Duplicates’ feature in EndNote) and manually. After removing duplicates, the titles and abstracts of the records were screened against the inclusion and exclusion criteria by two independent reviewers (AM and AAP), using EndNote 20 software. The records which clearly did not meet the inclusion criteria were excluded from the review. Full texts of all retained articles were also screened independently by two reviewers (AM and AAP). Disagreement was resolved by discussion between the two reviewers. The selection process and reasons for exclusion were documented using a PRISMA flow diagram.AM and AAP independently carried out the critical appraisal for each study. The Joanna Briggs Institute (JBI) critical appraisal tools were used, according to each study’s design, to assist in examining the trustworthiness and risk of bias of the included studies . The JBIAM extracted the data using a standardised extraction sheet in Microsoft Word to record the study characteristics of included articles. Afterwards, AAP checked and amended the data extraction results as required.The information included: a) the details of the study’s aim, b) design, c) sample size, d) types of participants, e) participants’ characteristics, f) eHealth literacy instrument and g) mean score of eHealth literacy. In addition, the determinants and outcomes were also extracted from the included studies.A conceptual model illustrating the determinants and outcomes of eHealth literacy was developed, based on Dahlgren and Whitehead’s Determinants of Health Model . AccordiForty-four studies were eligible for inclusion . The stuThis review included 43 cross-sectional studies and one qualitative study . As the Eighteen (41.0%) studies recruited lay people, mostly internet users , 32–48. Thirty four (77.2%) studies , 62–64 uThe quality assessment, using the JBI instrument for each included study, is available in the Supplementary materials. We quantified the number of the critical appraisal components which were fulfilled in each study. The majority of the quantitative studies (n = 24) had 6 out of 8 components fulfilled. Most of the unfulfilled criteria were about identification of confounding factors and strategies to address them. Meanwhile, the qualitative study (n = 1) had 7 out of 10 components fulfilled. This qualitative study did not state the cultural or theoretical location of the researcher, the influence of the researcher on the research, and the ethical considerations of the study. None of the papers was excluded based on the quality evaluation.Summary of findings from studies which address the determinants of eHealth literacy are presented in Age and sex were found to be the non-modifiable determinants of eHealth literacy . StudiesIn the individual layer of eHealth literacy determinant model , there aFor the social and community network layer of determinant model, there was no factor found to be the determinant of eHealth literacy. However, for the next layer (living and working conditions) the factors of: education, employment, living conditions and health care services were identified.Higher education was consistently associated with higher eHealth literacy, as indicated in eight studies , 60, 70.Higher income was consistently related to higher eHealth literacy , 46, 70.Related to the health care service, personal health care financing was found to be linked with eHealth literacy. The ability to pay for medications and doctors were associated with higher eHealth literacy .Other determinants of eHealth literacy are related to ICT infrastructure. In a qualitative study conducted among college students in Pakistan, Adil et al. identified that the access to ICT resources, categorisation of authentic and unauthentic websites and presentation of eHealth information influenced eHealth literacy .Finally, in the outermost layer of the eHealth literacy determinant model, which represents the general socio-economic and cultural environments , there iA summary of findings from the studies which addressed the outcomes of eHealth literacy is presented in Many studies included in this review were conducted during the COVID-19 pandemic and the outcomes were also related to COVID-19. Seven studies found that higher eHealth literacy was associated with higher adherence to COVID-19 preventive behaviors , 64, 67.In terms of psychological outcomes, two studies indicated that higher eHealth literacy was associated with better psychological wellbeing , 35. AnoFive studies showed that eHealth literacy was related to health promoting behavior , 64, 66.Still related to health promoting behaviors, several studies examined the health promoting behaviors more specifically, including exercise, health eating, sleep, a lifestyle free of harmful substances and maintenance of sexual health. Six studies found that eHealth literacy was associated with exercise , 61, 67.Four studies suggested that eHealth literacy was linked with a balanced diet , 58, 61,With regards to colorectal cancer (CRC), a study was conducted among internet users in Japan . This stIn the social and community networks layer, stable friendships or social support were found to be related with eHealth literacy . People In the next layer, regarding living and working conditions, health outcomes and health service/health app utilisation were found to be linked to eHealth literacy. According to four studies, eHealth literacy was associated with self-rated health , 60, 70.The model suggests that eHealth literacy is shaped by a complex interaction of multi-layered determinants . As a result, eHealth literacy is also associated with various outcomes.This review has attempted to consolidate the determinants and outcomes of eHealth literacy in healthy adults. We categorised the determinants and outcomes of the eHealth literacy into layers which could influence health, according to Dahlgren and Whitehead’s model . DahlgreIn the first layer of eHealth literacy determinants, we identified age and sex as the non-modifiable factors. There are conflicting findings regarding these two factors, but, overall, most studies in this review support ‘younger age’ and ‘male sex’ to be linked with higher eHealth literacy level. One study’s result, that older age was associated with better eHealth literacy, is possibly because the participants were heavy internet users regardless of age . HoweverIn the second layer of the eHealth literacy determinants, there are individual factors which comprised literacy issues and online health information seeking behavior issues. According to Norman and Skinner’s Lily Model of eHealth literacy, eHealth literacy is the combination of six core literacies, i.e. traditional literacy, media literacy, information literacy, health literacy, scientific literacy and computer literacy . In thisIn the living and working conditions layer, there is socioeconomic status. This factor includes education, employment, income and ease of paying for health care, all of which play important roles in determining the eHealth literacy levels of healthy adults. This finding is consistent with the result of a previous systematic review of eHealth literacy in an underserved population in the US . In the Referring to Dahlgren and Whitehead’s model , differeWith regard to the outcomes, eHealth literacy was found to have several positive outcomes. Of note, most eHealth literacy studies within this review were conducted during the COVID-19 pandemic. Indeed, in this pandemic, eHealth literacy became more relevant than ever, since most of the COVID-19 information, including misinformation and disinformation, is disseminated through the internet . eHealthA systematic review on the influencing factors of eHealth literacy among Chinese older adults  showed sThe systematic review offers comprehensive summarized evidence of the determinants and outcomes of eHealth literacy in healthy adults. It encompasses a wide range of factors, both non-modifiable and individual, as well as environmental and cultural aspects. In addition, the review acknowledges that different layers of eHealth literacy determinants can have varying policy implications. This recognition is crucial for policymakers and healthcare professionals seeking to enhance eHealth literacy, as it provides insights into targeted interventions and strategies.As with all systematic reviews, we cannot be fully certain that we have identified all relevant literature. This review only covered six databases and studies published in English. We may have missed potentially eligible studies published in other languages or contained within other databases. We only included articles which measured associations of eHealth literacy with the determinant or outcome variables. Articles presenting only differences between those variables were excluded. This constraint might also limit the findings of the review. Furthermore, we limit our population to healthy adults, who may not be the vulnerable population with regards to eHealth literacy. It is important to note that the studies included a relatively diverse group of healthy adults, e.g. students and healthcare professionals. While such inclusion can provide a more comprehensive picture of eHealth literacy in healthy adults, it can also introduce heterogeneity into the study population. Therefore, careful consideration of how the results is interpreted and generalized is needed.This systematic review has contributed to the understanding of the putative determinants and outcomes of eHealth literacy in healthy adults. In summary, the determinants of eHealth literacy include the non-modifiable factors ; individual factors ; living and working conditions  and general cultural conditions (particularly language). Whereas, the outcomes of eHealth literacy include health promotion behaviors, COVID-19 preventive behaviors, psychological wellbeing, better social and community networks, better self-rated health and better health service utilisation. Different layers of eHealth literacy determinants can have different policy implications as they aim to improve eHealth literacy.Future studies should incorporate artificial intelligence (AI) into the eHealth landscape. One possible direction is the expansion of the eHealth Literacy tool to include AI-driven health information. AI can also be used to develop inclusive eHealth solutions that are tailored to different literacy levels. The key to AI’s influence is personalization, which enables the creation of eHealth intervention finely tuned to individual literacy levels. This personalisation encourages more effective health information dissemination while improving accessibility.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file. 14 Feb 2023PONE-D-22-35330Determinants and outcomes of eHealth literacy in healthy adults: A systematic reviewPLOS ONEDear Dr. Milanti,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by Mar 31 2023 11:59PM. 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You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Thank you for the opportunity to read this paper. It address an important topic and contributes to the body of knowledge in this field. I only have few minor comments for authors' consideration.Introduction- Please elaborate why the authors want to understand eHealth literacy in healthy adults?- Why it is important to understand determinants and outcomes?Results- It is worth noting that studies included a wide range of participants , please comment on how it may affect the results of this SR.Discussion- I think readers may be interested to whether the results of this SR in healthy adults differ from those in other populations (e.g. older adults). Please consider adding few sentences to elaborate.Reviewer #2: This is an interesting review which examines the determinants and outcomes of eHealth literacy.Introduction/Background- Rationale: given that there are already three reviews that examine interventions for health literacy, it would be important to be more specific about how this current review adds to the already extensive reviews in the area, in particular as you state that the results are ‘putative’ and other reviews have focused specifically on interventions and the outcomes of interventions.https://pubmed.ncbi.nlm.nih.gov/36716080/- A recently published systematic review: - Why focus on healthy adults only and how are healthy adults defined?- Rationale for how ‘outcomes’ can be described as benefits and disadvantages.Methods:- What software was used to screen the articles?- Where were the data extracted to?- Data Synthesis: the Dahlgren and Whitehead model is explained, but not how the data were synthesised and applied to this model. How was this undertaken from a methods perspective?- I don’t think Table 2 or Table 3 are necessary. These could be put in a supplementary file. Also, no need to list the JBI critical appraisal questions.Results/Discussion- I would question the appropriateness or need to use of the term ‘putative’ throughout the article. If there is a description of what is meant by putative and why these studies are putative determinants and outcomes only in the background (or early results) and perhaps again in the conclusion, there is no need to repeat this throughout the article.- Conceptual model of ehealth literacy: the figure/model as it stands is a bit one dimensional. Suggest distinguishing the different levels as per Dahlgren and Whitehead and be more explicit about the left side that distinguishes determinants and outcomes.Other- Abstract: background should include ‘healthy adults’.- The following sentence appears to be incorrectly in the article: “Please add subheading to guide the classification of determinants according to the model” (p36).- Discussion: need to draw out more the differences between different countries/parts of the world?- Some of the language in the article is awkward. Suggest reviewing for structure of sentences.********** <font color="black"> 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? 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The reviewer comments are listed below in italicised font, while our responses are given in normal font. Changes or additions we made in the manuscripts are marked with red colour. List of responseReviewer #1: Thank you for the opportunity to read this paper. It address an important topic and contributes to the body of knowledge in this field. I only have few minor comments for authors' consideration.Introduction1. Please elaborate why the authors want to understand eHealth literacy in healthy adults?Reply: Thank you for your valuable suggestion. We have taken your feedback into consideration and have elaborated on our rationale for studying eHealth literacy in healthy adults. We have included our response in the introduction section of our manuscript, specifically in the last paragraph.Understanding the determinants and outcomes of eHealth literacy can provide valuable insights into the factors that influence individuals’ ability to use technology to access, understand, and use health information, and the impact that eHealth literacy has on health outcomes. This information can then be used to develop interventions and policies to promote eHealth literacy and improve health outcomes in healthy adults. Focusing on the adult population is important since this population makes up the largest age group in the world [28]. Moreover, by focusing the study population on healthy adults, the researchers can minimise the potential confounding effects of health conditions or other factors that may influence eHealth literacy. (page 2-3)2. Why it is important to understand determinants and outcomes?Reply: Thank you for your comment. We believe that understanding the determinants and outcomes of eHealth literacy is crucial because it can help identify the factors that contribute to individuals' ability to access and use health information through technology, and how this ability impacts their health outcomes. By examining these factors, we can develop interventions and policies that promote eHealth literacy and improve health outcomes in healthy adults. We have added this explanation to the last paragraph of our introduction section. Understanding the determinants and outcomes of eHealth literacy can provide valuable insights into the factors that influence individuals’ ability to use technology to access, understand, and use health information, and the impact that eHealth literacy has on health outcomes. This information can then be used to develop interventions and policies to promote eHealth literacy and improve health outcomes in healthy adults. Focusing on the adult population is important since this population makes up the largest age group in the world [28]. Moreover, by focusing the study population on healthy adults, the researchers can minimise the potential confounding effects of health conditions or other factors that may influence eHealth literacy. (page 2-3)Results3. It is worth noting that studies included a wide range of participants , please comment on how it may affect the results of this SR.Reply: Thank you for raising this issue. We agree that it is important to note about the wide range of participants which may influence the results of our SR. We have acknowledged it in the following comment at the end of the discussion section. It is important to note that the studies included a diverse kind of healthy adults, e.g. students and healthcare professionals. While such inclusion can provide a more comprehensive picture of eHealth literacy in healthy adults, it can also introduce heterogeneity into the study population. Therefore, careful consideration of how the results are interpreted and generalized is needed. (page 44)Discussion4. I think readers may be interested to whether the results of this SR in healthy adults differ from those in other populations (e.g. older adults). Please consider adding few sentences to elaborate.Reply: Thank you for your suggestion. We have written an additional paragraph in the discussion section to elaborate the similarities and differences between our SR and the most relevant previous SR. A systematic review on the influencing factors of eHealth literacy among Chinese older adults [8] showed several similar findings with our study results, i.e. age, gender, education, socioeconomic status, and language influenced the levels of eHealth literacy [8]. These similarities suggest the factors which may be the universal determinants of eHealth literacy across different culture and population. However, our present study found that eHealth literacy was also influenced by literacy factors and ICT infrastructure. Another difference is that physical and psychological conditions, marital status, and being the family carer were found to be associated with the Chinese older adults’ levels of eHealth literacy [8]. These differences may indicate the factors that may be unique to older adult population, especially in China. With regards to outcomes, similar to our study findings, a recent systematic review concluded that eHealth literacy is associated with health-promoting behaviours including regular eating and exercise, and compliance with disease prevention behaviours [27]. These similar and different findings show the importance of conducting systematic review to find the consistent and inconsistent patterns across different studies. (page 43)Reviewer #2: This is an interesting review which examines the determinants and outcomes of eHealth literacy.Introduction/Background1. Rationale: given that there are already three reviews that examine interventions for health literacy, it would be important to be more specific about how this current review adds to the already extensive reviews in the area, in particular as you state that the results are ‘putative’ and other reviews have focused specifically on interventions and the outcomes of interventions.Reply: Thank you for your meaningful feedback on our manuscript. We agree that it is important to clarify how our review adds to the existing literature on eHealth literacy, given the extensive previous reviews particularly on eHealth literacy interventions for older adults. Our review takes a broader approach by examining the determinants and outcomes of eHealth literacy in healthy adults, while previous reviews on eHealth literacy interventions focused on older adults. Focusing on the adult population is important since this population makes up the largest age group in the world. Moreover, by focusing the study population on healthy adults, the researchers can minimise the potential confounding effects of health conditions or other factors that may influence eHealth literacy. In addition, our review offers a model of eHealth literacy determinants and outcomes which can be helpful to outline strategic approaches to promote greater equity in eHealth literacy through different policy levels. Finally, our present review found the factors unique to healthy adults which are not found among older adult population as well as the similar factors across these populations (as illustrated in the second last paragraph in the discussion section).We also added an explanation about this rationale to the last paragraph of our introduction: “However, to the best of our knowledge, there is still no systematic review to summarise the evidence of eHealth literacy’s determinants and outcomes, unrelated to a specific intervention. To address this perceived gap, this systematic review aims to summarise and appraise the existing research which has examined the determinants and outcomes of eHealth literacy in healthy adults. Understanding the determinants and outcomes of eHealth literacy can provide valuable insights into the factors that influence individuals’ ability to use technology to access, understand, and use health information, and the impact that eHealth literacy has on health outcomes. This information can then be used to develop interventions and policies to promote eHealth literacy and improve health outcomes in healthy adults. Focusing on the adult population is important since this population makes up the largest age group in the world [28]. Moreover, by focusing the study population on healthy adults, the researchers can minimise the potential confounding effects of health conditions or other factors that may influence eHealth literacy.” (page 2-3)https://pubmed.ncbi.nlm.nih.gov/36716080/2. A recently published systematic review: Reply: Thank you for suggesting a recently published SR. We have incorporated it in our introduction (page 2) and discussion sections (page 43). 3. Why focus on healthy adults only and how are healthy adults defined?Reply: Thank you for your questions. We added these sentences to the end of our introduction section to answer your question:“Focusing on the adult population is important since this population makes up the largest age group in the world [2]. Moreover, by focusing the study population on healthy adults, the researchers can minimise the potential confounding effects of health conditions or other factors that may influence eHealth literacy.” (page 3) Also, we have inserted the definition of healthy adults in the eligibility criteria, in the Methods section. Healthy adults are defined as individuals aged over 18-64 years  without significant chronic health conditions or disabilities. (page 3)4. Rationale for how ‘outcomes’ can be described as benefits and disadvantages.Reply: Thank you for raising this issue. We replaced the use of terms ‘benefits and disadvantages’ with positive and negative outcomes (page 3). Describing outcomes as both positive and negative allows for a more balanced assessment of the eHealth literacy topic. Methods:5. What software was used to screen the articles?Reply: We used EndNote 20 software to screen the articles . 6. Where were the data extracted to?Reply: The data were extracted to an extraction sheet in Microsoft Word (we have added this information in our Methods section page 4). 7. Data Synthesis: the Dahlgren and Whitehead model is explained, but not how the data were synthesised and applied to this model. How was this undertaken from a methods perspective?Reply: Thank you for raising this issue. From a methods perspective, we synthesised the data from the included studies to this model by extracting the information on the determinants and outcomes of eHealth literacy and mapping the findings onto the model. Finally we identified areas where interventions or policies can be targeted related to each determinants.  Data from the included studies were synthesised and applied to this model by extracting the information on the determinants and outcomes of eHealth literacy and mapping the findings onto the layers of Dahlgren and Whitehead’s model. Finally, areas where interventions or policies can be targeted related to each determinant were identified. (page 4) 8. I don’t think Table 2 or Table 3 are necessary. These could be put in a supplementary file. Also, no need to list the JBI critical appraisal questions.Reply: Thank you for your feedback. We have put table 2 and 3 in the Supplementary material. Results/Discussion9. I would question the appropriateness or need to use of the term ‘putative’ throughout the article. If there is a description of what is meant by putative and why these studies are putative determinants and outcomes only in the background (or early results) and perhaps again in the conclusion, there is no need to repeat this throughout the article.Reply: Thank you for your suggestion. We have removed the term ‘putative’, except in the early part of the Results section  and in the Conclusions. 10. Conceptual model of ehealth literacy: the figure/model as it stands is a bit one dimensional. Suggest distinguishing the different levels as per Dahlgren and Whitehead and be more explicit about the left side that distinguishes determinants and outcomes.Reply: Thank you for your suggestion. We have made some revisions to the figure to improve its clarity. Firstly, we have made a more explicit distinction between the different levels of the determinants and their interactions, as per Dahlgren and Whitehead's model. Secondly, we have separated the groups of determinants and outcomes into upper and lower parts using a bold line to make them more visible. We have also created dashed arrows to indicate non-causal relationships between the determinants and eHealth literacy, as well as between eHealth literacy and the outcomes. Furthermore, we have moved the group of determinants to the upper part of the figure, and the outcomes to the lower part. Lastly, we have included an explanation of the figure in the caption.Figure 2. Conceptual model of eHealth literacy determinants and outcomesThe model suggests that eHealth literacy is shaped by a complex interaction of multi-layered determinants . As a result, eHealth literacy is also associated with various outcomes. Other11. Abstract: background should include ‘healthy adults’.Reply: Thank you for your reminder. We have revised the background section in our abstract accordingly. 12. The following sentence appears to be incorrectly in the article: “Please add subheading to guide the classification of determinants according to the model” (p36).Reply: Thank you for your meticulous review. We have deleted that sentence. 13. Discussion: need to draw out more the differences between different countries/parts of the world?Reply: Thank you for your comment on our article. We appreciate your suggestion to draw out more the differences between different countries in the discussion section. We have compared the results of our SR with those from the previous systematic reviews focused on different countries in these two paragraphs:  …This factor includes education, employment, income and ease of paying for health care, all of which play important roles in determining the eHealth literacy levels of healthy adults. This finding is consistent with the result of a previous systematic review of eHealth literacy in an underserved population in the US [19]. In the countries where there is no universal health coverage, such as the US, those who are poor and uninsured may have lesser access to health care, confirming their status as a vulnerable and underserved population [19]. Economically disadvantaged people may also have decreased opportunity to access technology [19]…. A systematic review on the influencing factors of eHealth literacy among Chinese older adults [8] showed several similar findings with our study results, i.e. age, gender, education, socioeconomic status, and language influenced the levels of eHealth literacy [8]. These similarities suggest the factors which may be the universal determinants of eHealth literacy across different culture and population. However, our present study found that eHealth literacy was also influenced by literacy factors and ICT infrastructure. Another difference is that physical and psychological conditions, marital status, and being the family carer were found to be associated with the Chinese older adults’ levels of eHealth literacy [8]. These differences may indicate the factors that may be unique to older adult population, especially in China. With regards to outcomes, similar to our study findings, a recent systematic review concluded that eHealth literacy is associated with health-promoting behaviours including regular eating and exercise, and compliance with disease prevention behaviours [27]. These similar and different findings show the importance of conducting systematic review to find the consistent and inconsistent patterns across different studies.14. Some of the language in the article is awkward. Suggest reviewing for structure of sentences.Reply: Thank you for your feedback. We have our article professionally proofread and edited by a native English academic and proofreader. We also have reviewed our article to improve its readability and clarity.AttachmentResponse to reviewer_26042023.docxSubmitted filename: Click here for additional data file. 7 Jul 2023 <div> PONE-D-22-35330R1 </div>  <div> Determinants and outcomes of eHealth literacy in healthy adults: A systematic review </div>  <div> PLOS ONEDear Dr. Milanti,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.1-It is necessary to provide a reproducible search strategy. The current given information does not determine the reproducibility. Please provide detail search strategy.https://jbi.global/. Please make sure your methodology is in details and include all aspect of data screening method, data collection methods.2- how did you removing duplicates. The current methodology in incomplete. Please read 3-Please provide us PICO. The PICO framework focuses on the Population, Intervention, Comparison and Outcomes. If you use other framework then give to us. It is mandatory.4-Provide details on grey literature. Mandatory5-Provide justification on why you exclude other database. MandatoryRegarding Study risk of bias assessment. Kindly compare it with other methods such as Cochrane Risk of Bias Tool, Newcastle-Ottawa Scale (NOS), AXIS , AMSTAR 2 (A MeaSurement Tool to Assess systematic Reviews). The current information is not sufficient.6-Kindly organize your table properly. All given tables has several structural flaws. Proof read properly.7-Provide heading and details, Study strength, study limitation, future direction. Mandatory.8-Please revisit PRIMA flow dagram and cross-check the statement and content provided.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by Aug 21 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.An unmarked version of your revised paper without tracked changes. 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For instructions see: We look forward to receiving your revised manuscript.Kind regards,Muhammad Shahzad Aslam, Ph.D.,M.Phil., Pharm-DAcademic EditorPLOS ONEAdditional Editor Comments:1-It is necessary to provide a reproducible search strategy. The current given information does not determine the reproducibility. Please provide detail search strategy.https://jbi.global/. Please make sure your methodology is in details and include all aspect of data screening method, data collection methods.2- how did you removing duplicates. The current methodology in incomplete. Please read 3-Please provide us PICO. The PICO framework focuses on the Population, Intervention, Comparison and Outcomes. If you use other framework then give to us. It is mandatory.4-Provide details on grey literature. Mandatory5-Provide justification on why you exclude other database. MandatoryRegarding Study risk of bias assessment. Kindly compare it with other methods such as Cochrane Risk of Bias Tool, Newcastle-Ottawa Scale (NOS), AXIS , AMSTAR 2 (A MeaSurement Tool to Assess systematic Reviews). The current information is not sufficient.6-Kindly organize your table properly. All given tables has several structural flaws. Proof read properly.7-Provide heading and details, Study strength, study limitation, future direction. Mandatory.8-Please revisit PRIMA flow dagram and cross-check the statement and content provided.[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to Questions <font color="black"> Comments to the Author </font> 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #2: All comments have been addressed********** <font color="black"> 2. Is the manuscript technically sound, and do the data support the conclusions? </font> The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes********** <font color="black"> 3. 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Is the manuscript presented in an intelligible fashion and written in standard English? </font> PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #2: Yes********** <font color="black"> 6. Review Comments to the Author </font> Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #2: (No Response)********** <font color="black"> 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). 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Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  23 Aug 2023PONE-D-22-35330R1 - Determinants and outcomes of eHealth literacy in healthy adults: A systematic reviewPLOS ONE Academic EditorDr. Muhammad Shahzad Aslam, Ph.D.,M.Phil., Pharm-DDear Dr Aslam, On behalf of all authors, I would like to thank the academic editor and reviewers for the valuable feedback to improve the quality of our manuscript. The editor' comments are listed below in italicised font, while our responses are given in normal font. Changes or additions we made in the manuscripts are marked with yellow highlight and red color. The existing contents which address your comments are marked with purple color. List of response1-It is necessary to provide a reproducible search strategy. The current given information does not determine the reproducibility. Please provide detail search strategy.Response: Thank you for your comment. We have added a supporting information file containing our detailed search strategy for each databases that we used. Search strategy  We searched six electronic databases: MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and ProQuest to identify relevant studies. Relevant grey literature including dissertations and theses were identified from ProQuest. These databases were selected since they are among the largest and most widely recognized as authoritative sources in the fields of healthcare, medical, nursing, psychology, and behavioral sciences. They offer a comprehensive coverage of literature relevant to the eHealth literacy topic. Including other databases might introduce redundancy in the review process. These databases were chosen to strike a balance between comprehensive coverage and efficiency.  A search strategy was developed to capture the key elements of the topic of interest, i.e.: determinants and outcomes of eHealth literacy. Keywords were combined using AND and OR Boolean operators. The year of publication was not limited. The detailed search strategy is presented in appendix 1.  (page 4)https://jbi.global/. Please make sure your methodology is in details and include all aspect of data screening method, data collection methods.2- how did you removing duplicates. The current methodology in incomplete. Please read Response: Thank you for your suggestion, We have checked and referred to JBI guidelines to add more details in our methods. All citations were managed using EndNote 20 software . Duplicates were identified and removed electronically (using 'Find Duplicates' feature in EndNote) and manually. (page 4) 3-Please provide us PICO. The PICO framework focuses on the Population, Intervention, Comparison and Outcomes. If you use other framework then give to us. It is mandatory.Response: Thank you for your comments. We have written the population and outcomes in the eligibility criteria of our review. We also added that intervention and comparator were not within the scope of our review.Selection process  Studies were included if they met these criteria: 1) studies examining ‘eHealth literacy’; 2) the type of study included observational and interventional studies, mixed methods studies, and qualitative studies; 3) population/participants were healthy adults ; 4) the main outcomes were the determinants (i.e. influencing or associated factors) and outcomes (i.e. positive and negative outcomes) of eHealth literacy. Intervention and comparator were beyond the scope of this review. (page 4)4-Provide details on grey literature. MandatoryResponse: Thank you for your comment. We have added in our 'Search strategy' section that grey literature were searched from ProQuest. Search strategy  We searched six electronic databases: MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and ProQuest to identify relevant studies. Relevant grey literature including dissertations and theses were identified from ProQuest. These databases were selected since they are among the largest and most widely recognized as authoritative sources in the fields of healthcare, medical, nursing, psychology, and behavioral sciences. They offer a comprehensive coverage of literature relevant to the eHealth literacy topic. Including other databases might introduce redundancy in the review process. These databases were chosen to strike a balance between comprehensive coverage and efficiency.  A search strategy was developed to capture the key elements of the topic of interest, i.e.: determinants and outcomes of eHealth literacy. Keywords were combined using AND and OR Boolean operators. The year of publication was not limited. The detailed search strategy is presented in appendix 1. (page 4)5-Provide justification on why you exclude other database. MandatoryResponse: We have explained our justification to include MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and ProQuest and exclude other databases. Search strategy  We searched six electronic databases: MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and ProQuest to identify relevant studies. Relevant grey literature including dissertations and theses were identified from ProQuest. These databases were selected since they are among the largest and most widely recognized as authoritative sources in the fields of healthcare, medical, nursing, psychology, and behavioral sciences. They offer a comprehensive coverage of literature relevant to the eHealth literacy topic. Including other databases might introduce redundancy in the review process. These databases were chosen to strike a balance between comprehensive coverage and efficiency.  A search strategy was developed to capture the key elements of the topic of interest, i.e.: determinants and outcomes of eHealth literacy. Keywords were combined using AND and OR Boolean operators. The year of publication was not limited. The detailed search strategy is presented in appendix 1. 5. a. Regarding Study risk of bias assessment. Kindly compare it with other methods such as Cochrane Risk of Bias Tool, Newcastle-Ottawa Scale (NOS), AXIS , AMSTAR 2 (A MeaSurement Tool to Assess systematic Reviews). The current information is not sufficient.Response:Thank you for your suggestion. We have incorporated it in our paper. Assessment of methodological quality AM and AAP independently carried out the critical appraisal for each study. The Joanna Briggs Institute (JBI) critical appraisal tools were used, according to each study’s design, to assist in examining the trustworthiness and risk of bias of the included studies [30]. The JBI critical appraisal tools are widely recognized within the field of evidence synthesis for their comprehensive approach to evaluating the risk of bias based on the study’s design, conduct, and analysis. While other tools, such as the Cochrane Risk of Bias Tool, Newcastle-Ottawa Scale (NOS), Appraisal tool for Cross-Sectional Studies (AXIS), and A measurement Tool to Assess Systematic Reviews (AMSTAR 2), mostly focus on specific study types and their respective attributes, JBI tools offer a broader approach in comprehensively assessing various study designs. Therefore, the JBI tools were deemed suitable for systematically reviewing the determinants and outcomes of eHealth literacy across different research methodologies. (page 5)6-Kindly organize your table properly. All given tables has several structural flaws. Proof read properly.Response: Thank you for your comments. We have rechecked the structure, and proofread the tables. Additionally, table of characteristics of included studies has been moved from the main text to the Supporting information part. In that table, we removed the mean eHealth literacy score as it was deemed unnecessary. 7-Provide heading and details, Study strength, study limitation, future direction. Mandatory.Response:Thank you for your suggestion. We have provided headings for the study strengths, limitations and future directions (the future directions was put after the Conclusions). In addition, we also incorporated the study limitations and future directions in the Discussion section to improve clarity and contextualisation (please see below examples).Discussion, Paragraph 1, page 16: (Limitation) However, this review did not include studies among older adults, therefore, comparisons between younger and older age participants cannot be made. In terms of sex, it is quite surprising that men were more likely to have a higher level of eHealth literacy than women. Prior studies showed that women used health apps [76] and searched health information online  more often than men did. Women were also found to be more eHealth literate than men and perceived online information quality better . (Future direction) More studies are needed to clarify how sex differences determine eHealth literacy.Paragraph 3, page 17: (Future direction) Further studies are deemed necessary to update eHEALS to fit its purpose in the Web 2.0 internet era. (Future direction) Subscales to assess communication skills in online social interactions and in synthesising contents are some instances of items that could be developed for updated version of eHEALS. (Future direction) Studies are also needed to assess the traditional literacy, scientific literacy and media literacy. The latter is especially important in combating disinformation and bridging the digital divide [82]. Implications for policymaking (page 17-18)Referring to Dahlgren and Whitehead’s model [31], different policy levels may apply in different layers of the health determinant. Policy level 1 is for the major structural environment, in which the language factor is situated. For addressing this determinant, national-level strategies, such as incorporating language services in the national health care system, are needed [83]. Having national and health industry investments to develop population-based language services by using ICT is also recommended [83]. Furthermore, policy level 2, which aims to improve living and working conditions can achieve that aim by, for example, a) providing the welfare benefits through the social security sector, and improving b) health care services, c) the education system and d) the ICT infrastructure [31]. Policy level 3, aiming at strengthening social and community support is not applicable, as there is no eHealth literacy determinant identified in this layer. Policy level 4 aims at influencing individual lifestyles [31]. The policy can include developing programmes to enhance eHealth literacy skills. Finally, for the innermost layer, i.e. the non-modifiable factor, the intervention can be integrated into the educational improvement of the eHealth literacy for older adults of both sexes and women of all ages. Study strengthsThe systematic review offers comprehensive summarized evidence of the determinants and outcomes of eHealth literacy in healthy adults. It encompasses a wide range of factors, both non-modifiable and individual, as well as environmental and cultural aspects. In addition, the review acknowledges that different layers of eHealth literacy determinants can have varying policy implications. This recognition is crucial for policymakers and healthcare professionals seeking to enhance eHealth literacy, as it provides insights into targeted interventions and strategies.Study limitationsAs with all systematic reviews, we cannot be fully certain that we have identified all relevant literature. This review only covered six databases and studies published in English. We may have missed potentially eligible studies published in other languages or contained within other databases. We only included articles which measured associations of eHealth literacy with the determinant or outcome variables. Articles presenting only differences between those variables were excluded. This constraint might also limit the findings of the review. Furthermore, we limit our population to healthy adults, who may not be the vulnerable population with regards to eHealth literacy. It is important to note that the studies included a relatively diverse group of healthy adults, e.g. students and healthcare professionals. While such inclusion can provide a more comprehensive picture of eHealth literacy in healthy adults, it can also introduce heterogeneity into the study population. Therefore, careful consideration of how the results is interpreted and generalized is needed. Conclusions and future directions (page 19 & 20) This systematic review has contributed to the understanding of the putative determinants and outcomes of eHealth literacy in healthy adults. In summary, the determinants of eHealth literacy include the non-modifiable factors ; individual factors ; living and working conditions  and general cultural conditions (particularly language). Whereas, the outcomes of eHealth literacy include health promotion behaviors, COVID-19 preventive behaviors, psychological wellbeing, better social and community networks, better self-rated health and better health service utilisation. Different layers of eHealth literacy determinants can have different policy implications as they aim to improve eHealth literacy.  Future studies should incorporate artificial intelligence (AI) into the eHealth landscape. One possible direction is the expansion of the eHealth Literacy tool to include AI-driven health information. AI can also be used to develop inclusive eHealth solutions that are tailored to different literacy levels. The key to AI's influence is personalization, which enables the creation of eHealth intervention finely tuned to individual literacy levels. This personalisation encourages more effective health information dissemination while improving accessibility.8-Please revisit PRIMA flow diagram and cross-check the statement and content provided.Response: Thank you for your suggestion. We have revisited our PRISMA flow diagram and checked its content for accuracy.Attachmentresponse to reviewers_23Aug23.docxSubmitted filename: Click here for additional data file. 25 Aug 2023Determinants and outcomes of eHealth literacy in healthy adults: A systematic reviewPONE-D-22-35330R2Dear Dr. Milanti,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Muhammad Shahzad Aslam, Ph.D.,M.Phil., Pharm-DAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments:Reviewer's Responses to Questions <font color="black"> Comments to the Author </font> 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressedReviewer #2: All comments have been addressed********** <font color="black"> 2. Is the manuscript technically sound, and do the data support the conclusions? </font> The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: Yes********** <font color="black"> 3. Has the statistical analysis been performed appropriately and rigorously?  </font> Reviewer #1: YesReviewer #2: N/A********** <font color="black"> 4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. </font> The Reviewer #1: YesReviewer #2: Yes********** <font color="black"> 5. Is the manuscript presented in an intelligible fashion and written in standard English? </font> PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes********** <font color="black"> 6. Review Comments to the Author </font> Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Thanks for the opportunity to review this paper. This systematic review addressed an important topic and filled the gaps in literature.The author has responded to all my suggestions.Reviewer #2: (No Response)********** <font color="black"> 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. </font> Reviewer #1: NoYes: Aisling WalshReviewer #2: ********** 25 Sep 2023PONE-D-22-35330R2  Determinants and outcomes of eHealth literacy in healthy adults: A systematic review Dear Dr. Milanti:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staffon behalf ofDr. Muhammad Shahzad Aslam Academic EditorPLOS ONE


This manuscript presents a concise approach to tackle the widespread misuse of statistical significance in scientific research, focusing on public health. It offers practical guidance for conducting accurate statistical evaluations and promoting easily understandable results based on actual evidence. When conducting a statistical study to inform decision-making, it is recommended to follow a step-by-step sequence while considering various factors. Firstly, multiple target hypotheses should be adopted to assess the compatibility of experimental data with different models. Reporting all P-values in full, rounded in order to have a single non-zero significant digit, enhances transparency and reduces the likelihood of exaggerating the state of the evidence. Detailed documentation of the procedures used to evaluate the compatibility between test assumptions and data should be provided for rigorous assessment. A descriptive evaluation of results can be aided by using statistical compatibility ranges, which help avoid misrepresenting the evidence. Separately evaluating and reporting statistical compatibility and effect size prevents the magnitude fallacy. Additionally, reporting measures of statistical effect size enables evaluation of sectoral relevance, such as clinical significance. Multiple compatibility intervals, such as 99%, 95%, and 90% confidence intervals, should be reported to allow readers to assess the variation of P-values based on the width of the interval. These recommendations aim to enhance the robustness and interpretability of statistical analyses and promote transparent reporting of findings. The author encourages journal adoption of similar frameworks to enhance scientific rigor, particularly in the field of medical science. The abuse and misuse of statistical significance and hypothesis testing in scientific research are well-known and widely debated concepts . In sensFirst premise: methodological validity of the studyConsiderations on statistical evidence are relevant if and only if all initial procedures  have been carried out correctly, that is, ensuring sufficient levels of neutrality, competence, attention, and collaboration . Since iSecond premise: statistical effect sizeThe concept of statistical significance is directly linked to the degree of surprise (how unexpected a result is) compared to the prediction of a statistical model, but it does not provide clear and unambiguous information on the magnitude of the statistical effect because this relationship is confused, at best, by the size of the dataset . TherefoFisher's approach (single-study conclusions)When conducting a single study, the concept of statistical significance can be evaluated using Fisher’s approach ,4. GivenConsidering F1 and assuming F2, the P-value can be defined as a continuous measure of the compatibility between the target hypothesis we have chosen and the experimental data we have observed. The P-value ranges from a minimum value of 0 (very low compatibility) to a maximum value of 1 (very high compatibility) [Neyman-Pearson approach (conclusions from multiple studies)When analyzing the results of multiple valid studies (see previous sections), the Neyman-Pearson approach, also known as hypothesis testing, allows for limiting the proportion of type I errors  and type II errors  . This isConsidering F3, F4, F6, and F7, and assuming F5, it is plausible to think of committing, in total, about α% type I errors and about β% type II errors. This means that we can roughly know how much we are wrong in multiple repetitions but not where we are wrong .Simple operating frameworkWhen conducting a single statistical study with the aim of informing a decision - also based on evidence of other nature  or research in general - it is suggested to adopt the following sequence step by step, keeping in mind all the considerations made above. Adopt multiple target hypotheses  and observe the variation of P-values as a function of the latter. In this way, the reader can get a picture of the compatibility of experimental data with various (even contrasting) models (S1). Always report all P-values in full, keeping a single significant digit different from 0 . This increases transparency and interpretability and reduces the likelihood of reporting exaggerations of the state of evidence  (S2). Report in detail, in the manuscript or in a supplementary file, all the procedures adopted to evaluate the compatibility between the test assumptions and the experimental data. This gives the reader the opportunity to fully evaluate the statistical validity of the investigation (S3). Use statistical compatibility ranges for descriptive evaluation of results . Some possible solutions are proposed in other literature . This reThis paper highlights the importance of adopting a rigorous and transparent approach when conducting statistical analyses in medical and all decision-based research. Especially when dealing with sensitive areas such as public health, even the above-discussed misinterpretations and errors must be weighed on a cost-benefit function specific to the stakeholders.By adopting multiple target hypotheses, reporting all P-values in full according to the above-described modalities, adopting statistical compatibility ranges, and providing detailed information on the procedures used to evaluate test assumptions, researchers can reduce the likelihood of exaggerating the state of evidence and ensure that research findings are accurately communicated and interpreted.Furthermore, the clear distinction between the evaluation of statistical compatibility and statistical and clinical effect sizes can provide valuable information on the sectoral relevance of research findings and help scientists avoid falling into the magnitude fallacy.This framework is designed to provide a brief and clear list of operations to be performed to inform any public health decision regarding the statistical aspect related to testing. For those who wish to delve deeper into these aspects, the following reading is recommended .In conclusion, this manuscript presents a practical approach to addressing the misuse of statistical significance in scientific research, with a focus on public health. By following the recommended step-by-step sequence and adopting multiple target hypotheses, reporting all P-values in full, using statistical compatibility ranges, and adopting separate measures of statistical and clinical effect size, researchers can enhance the accuracy and interpretability of their statistical analyses. These recommendations aim to reduce overstatements, promote transparent reporting of findings, and encourage the adoption of similar frameworks by journals to enhance scientific rigor, particularly in the medical field and all decision-based sciences.