Background: The scientific literature is growing in volume and reducing in readability. Poorly presented numbers decrease readability by either fatiguing the reader with too many decimal places, or confusing the reader by not using enough decimal places, and so making it difficult to comprehend differences between numbers. There are guidelines for the ideal number of decimal places, and in this paper I examine how often percents meet these guidelines.Methods: Percents were extracted from the abstracts of research articles published in 2017 in 23 selected journals. Percents were excluded if they referred to a statistical interval, typically a 95% confidence interval. Counts and percents were calculated for the number of percents using too few or too many decimal places, and these percents were compared between journals.Results: The sample had over 43,000 percents from around 9,500 abstracts. Only 55% of the percents were presented according to the guidelines. The most common issue was using too many decimal places (33%), rather than too few (12%). There was a wide variation in presentation between journals, with the range of ideal presentation from a low of 53% (JAMA) to a high of 80% .Conclusions: Many percents did not adhere to the guidelines on using decimal places. Using the recommended number of decimal places would make papers easier to read and reduce the burden on readers, and potentially improve comprehension. It should be possible to provide automated feedback to authors on which numbers could be better presented. Papers have also become less readable over time, with an increase in the use of scientific jargon3.Scientists read papers in order to keep up with the latest developments in their field and improve their research. However, the ever-increasing number of papers is placing greater demands on scientists’ time. In 2010 there were an estimated 75 trials and 11 systematic reviews published per day in the field of health and medicine4.Poorly presented numbers can decrease readability and can distort or even hide important information. Statistical software packages show results to many decimal places, but this level of precision may be spurious, and authors may overcrowd a paper with numbers if they copy the results from software without considering what level of precision is appropriate. An often cited bad example are journal impact factors, which are reported to three decimal places when one or no decimal places would be enough to show the differences between journals5, so from these results we only know that the number of female applicants was somewhere between 8,137 and 8,554, a range of 417. To use these results in a meta-analysis it would be better to know the actual number of applicants. The large sample size in this example means that potentially useful information is lost by rounding the percent to an integer.Authors may also over-simplify numbers by rounding and losing important information. For example, a review of the gender bias in funding peer review reported in a results table that 20% of applicants were female in a study of 41,727 applicationsAuthors must strike a balance between presenting numbers with too little or too much detail. The abstract and discussion are a summary of the findings, and here numbers can be rounded to make sentences easier to read. Numbers in the results section and tables can be presented with more detail, because they can be an accurate record of the data  and the reader is usually not expected to read every number in a table, especially a large table. Of course, tables can be made clearer by reducing unnecessary numbers, and so allowing the reader to easily comprehend the key information. There is a similar balance to consider when using acronyms in papers, as an overuse of acronyms can make a paper hard to understand because readers need to retrieve additional information, whereas using established acronyms can speed up reading.6 for presenting numerical data, including means, standard deviations, percentages and p-values. These guidelines are part of the wider EQUATOR guidelines for “Enhancing the QUAlity and Transparency Of health Research”http://www.equator-network.org/7. Cole’s guidelines for percentages are:There are guidelines by ColeIntegers or one decimal place for values under 10%, e.g., 1.1%Integers for values above 10%, e.g., 22% not 22.2%One decimal place may be needed for values between 90% to 100% when 100% is a natural upper bound, for example the sensitivity of a test, e.g., 99.9% not 100%Use two or more decimal places only if the range of percents being compared is less than 0.1%, e.g., 50.50% versus 50.55%Australian Zoologist state that, “Numbers should have a reasonable and consistent number of decimal places.” The Australian style guide also recommends a consistent number of decimal places when comparing numbers, so “1.23 vs 4.56” not “1.23 vs 4.5”8. TheEconomist style guide recommends, “resisting the precision of more than one decimal place, and generally favouring rounding off. Beware of phoney over-precision9.”There are also guidelines from journals and style guides. For example, the instructions to authors for the journalBMJ papers between 2011 to 2013 found that one quarter of confidence intervals and an eighth of estimates could have been presented better10. A single reviewer and editor of 53 biosciences articles found 29 (55%) reported too many decimal places for the mean11.It is not clear whether Cole’s guidelines on presenting numerical data are being adhered to, or if there is generally too little or too much rounding in published papers. An audit of 1,250 risk ratios and associated confidence intervals from the abstracts ofThis paper examines a large sample of percents in recent abstracts for multiple journals to examine how they are being presented.PubMed using the “rentrez” R package (version 1.1.0)12. Example abstracts are referred to using theirPubMed ID number rather than citing the paper, and readers can find the paper’s details by putting the number into aPubMed search with the search term “[PMID]”.I extracted percentages from abstracts available inThe BMJ,BMJ Open,Environmental Health Perspectives,F1000Research,JAMA,The Lancet,The Medical Journal of Australia,Nature,NEJM,PLOS ONE andPLOS Medicine. These journals were selected to give a range of journals that publish articles in health and medicine, including some high profile journals and some large open access journals. To look at recent papers, I restricted the search to 2017. To focus on research papers, I restricted the search to article types of: Journal Article, Clinical Trial, Meta-Analysis, Review, Randomized Controlled Trial and Multicenter Study. The search returned 33,147 papers across 23 journals .I searched for papers in the following journals:Despite the initial restriction on article type, the search results included non-research papers that had multiple types, e.g., a retraction of a clinical trial. Hence I excluded any papers that included an article type of: Biography, Conference, Comment, Corrected, Editorial, Erratum, Guideline, Historical, News, Lectures, Letter or Retraction.A flow diagram showing the selection of papers is inI examined only percents because they are a widely used and important statistic, and are relatively easy to extract using text mining compared with other important statistics, such as the mean or rate ratio. I extracted all percentages from the text of the abstract by searching for all numbers suffixed with a “%”, with or without a preceding space. The key steps for extracting the percents from the abstract were:1. ±” symbol and other symbols such as non-separating spacesSimplify the text by removing the “2. Find all the percents3. Exclude percents that refer to statistical intervals or statistical significance, e.g, “95% confidence interval”4. Record the remaining percents as well as the number of decimal places and significant figureshttps://github.com/agbarnett/decimal.places. Based on Cole’s guidelines6, I defined the ideal number of decimal places as:The complete steps are detailed in the R code available here:0 for percents between 10 and 90, and percents over 1001 for percents between 0.1 and 10, and percents between 90 and 100, and percents of exactly 02 for percents under 0.13 for percents under 0.014 for percents under 0.001 but greater than 0PubMed ID 28949973) would both be considered as having one decimal place too many using the above guidelines, but the additional decimal place may be warranted if the small difference of 0.1% is clinically meaningful. However, accurately calculating a small difference of less than 0.1% requires all percents to be displayed using two or more decimal places. Ultimately I ignored this issue because it applied to so few abstracts.Preferably I would have also considered a greater number of ideal decimal places when the aim was to compare a small difference in two percents. For example, 10.5% compared with 10.6% in the same sentence  as these were labels not results. I searched for common interval percents of 80%, 90%, 95% and 99%. I combined these four percents with the words: “confidence interval”, “credible interval”, “Bayesian credible interval”, “uncertainty interval”, “prediction interval”, “posterior interval” and “range”. I included versions using capital and non-capital letters, and the standard acronyms including “CI” and “PI”. I also removed references to statistical significance percents using the common percents of 1%, 5% and 10% combined with the words: “significance”, “statistical significance” and “alpha level”.PubMed ID 29198909), and there was an error with the ideal number of decimal places being 4 for a percent of 0% which led to a change in my ideal number of decimal places. There was also a “95% fixed kernel density estimator” which is a statistical interval and illustrates the difficulty of removing every type of statistical interval. I also checked the percentages for the abstract with the largest number of percents and the abstracts with the largest number of decimal places and significant figures. I also checked some abstracts that included percents of exactly 95% to check for any missing interval definitions. These checks led to additional definitions of intervals including the non-standard arrangements of “95% IC”, "CI 95%" (PubMed ID 28228447) and the typo "uncertainly interval" (PubMed ID 29171811).I verified that the percents were correctly recorded for 50 randomly selected articles which contained 198 percents. There were no errors in the recorded percents, but there were 5 percents that were labels rather than results  abstracts are freely available onPubMed for a wide range of journals, whereas the full text can only be easily text-mined for open access journals such asPLOS ONE, 2) the abstract is a summary of the results and so percentages should be presented according to Cole’s guidelines, whereas percents may be presented with more decimal places in the results in order to give an accurate and reusable record of the data.I only extracted percents that were suffixed with the percent symbol. For example, the only extracted percent for the text “5–10%” or “5 to 10%” would be 10%. Any percents written in words were also not extracted. I also did not extract numbers immediately before the word “percent” or “per cent” as I assumed that these would be rare. I ignored the sign of the percent as I was primarily interested in presentation, so for example “–10%” was extracted as 10%. Similarly “±1, I categorised the data into: too few, just right, and too many. I plotted the three categories by journal. I estimated confidence intervals for the percents in these three categories using a Bayesian Multinomial Dirichlet model13. The large sample size meant all confidence intervals had a width of 2% or less when using the complete sample, hence I did not present these intervals as they were not useful. The intervals are used to summarise the uncertainty for the results from journals. I did not adjust for the clustering of multiple percents within the same abstract.I calculated the difference between the observed number of decimal places and the ideal number as defined above. Because most differences were within14. All the data and code are available here:https://github.com/agbarnett/decimal.places.In a sensitivity analysis I excluded percents that could be due to digit preferences, which were those with no decimal places that were a multiple of 10 as well as 75%. I also excluded percents between 90% and 100% because these may or may not have had a natural upper bound at 100%, and so it is difficult to automatically judge whether they should be presented with one or no decimal places. The data extraction and analyses were made using R (version 3.4.3)PLOS ONE (PubMed ID 28526493) or rounded results .There were 43,119 percents from 9,482 abstracts. Over half the percents were fromLOS ONE . The medThe percent and number of percents meeting the guidelines are inα-tocopherol in cooked foods were as follows: boiling (77.74-242.73%), baking (85.99-212.39%), stir-frying (83.12-957.08%), deep-frying (162.48-4214.53%)” (PubMed ID 28459863).An example where too many decimal places were used is, “True retentions ofPubMed ID 29132879). As the numerators and denominators are given, we can recalculate the two percents using the recommended one decimal place, which are 3.2% and 1.9%, respectively, a difference of 1.3%. Without the reader working out these percents, the implied difference could be smaller than 0.1% because 3% could be as little as 2.5% (rounded up to 3%) and 2% could be as large as 2.4% (rounded down to 2%).An example where too few decimal places were used is, “263 [3%] of 8313 vs 158 [2%] of 8261” (PubMed ID 29138196).There were abstracts where the number of decimal places varied within the same sentence, for example, “pre-2010 vs post-2010 31.69% vs 64%” (PubMed ID 28460828).Some percents which I judged as having too few decimal places, were potentially harshly judged because the sentence aimed to give general percents, for example the following sentence probably did not need the percents to one decimal place, “it is a common, chronic condition, affecting 2–3% of the population in Europe and the USA and requiring 1–3% of health-care expenditure” (PubMed ID 28460828); using the guidelines all the percents under 10% should have had one decimal place.Some percents with too few decimal places according to Cole’s guidelines were presented using a consistent number of decimal places, for example, “we noted reductions in genotypes 6 and 11 . I could not adjust for this correct presentation because I did not extract sample sizes.Some percents with too few decimal places were correctly presented with no decimal places because the sample size was under 100, for example, “with a specimen obtained at 13 to 15 months, in 1 of 25 (4%)” . Hence the “around half” estimate for imperfect presentations found here likely overstates the problem. Additionally, there are far more serious mistakes that can be made with numbers, such as using the wrong dataNature had one of the best results in terms of ideal presentation, and they published relatively few papers, which may mean they have more time to edit papers for clarity and presentation.PLOS ONE had the most amount of papers in the sample and did relatively badly compared with the guidelines, perhaps because there is no time for editors to fix issues with presenting numbers given the large volume of papers and other important tasks, for example, checking for plagiarism and undeclared competing interests.I found large differences between journals in the number of decimal places used. These differences could be due to editorial policy and also differences in the training and experience of the journals’ author cohorts.statcheck program that checks for errors in statistical reporting16. This could be used to flag numbers that may need changing and could be part of an automated submission process for journals through online writing tools such asOverleaf17. Automating the process would reduce the burden on journal staff.The difference in standards between journals likely adds to the confusion for authors about how to present numbers. Greater consistency and better presentation might be improved by having an automated checking procedure similar to theI only examined percents, but it is likely that other statistics, such as means and risk ratios, are also being imperfectly presented. In fact, using percents may underestimate the problem of spurious precision because percents are almost always between –100 and 100, whereas means can take on a far wider range depending on the unit of measurement, and a wider range of numbers creates more opportunity for poor display. I only examined percents because these are the easiest numbers to automatically extract from text, thanks to the “%” suffix.Many percents in abstracts did not adhere to the guidelines on using decimal places. A more considered use of decimal places would increase readability and potentially improve comprehension.The data referenced by this article are under copyright with the following copyright statement: Copyright: © 2018 Barnett AGData associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).https://github.com/agbarnett/decimal.places.All the data and code are available here:doi:10.5281/zenodo.130005618.Archived data and code as at time of publication: The statement in the third paragraph of the introduction starting "Papers have been criticised for using too many decimal places..."  is still not supported by a citation . It should be simple to re-word the sentence or, if papers have been criticized for this practice, cite examples.it would be better to cite the paper describing rentrez, rather than the CRAN repository These issues may seem trivial, and they should not hold up the acceptance of this manuscript, but I think they should be addressed in a final revision.This revision addresses the major issues associated with the code and manuscript, and the paper should thus be accepted. However, two minor issues associated with the manuscript have not been dealt with, and the author's reply to reviews does not explain this decision. To reiterate:I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. In this article, Barnett examines the precision with which percentages are reported in the abstracts of journals indexed in PubMed. The article does a good job of explaining the motivation and design of the research and putting its results into context. The data presented in the manuscript supports the major finding of the work (that percentages are frequently presented with more apparent-precision than is reasonable).  Because my own expertise relates more to the code used for this analysis than the proper presentation of statistics my review focuses on the scripts use to perform the analysis. The linked code repository is currently lacking a number of files required to perform the analysis. I am sure this is simply and oversight, but I cannot recommend this paper for acceptance until these files are included. In addition, the overall design of the analysis code, which contains hundreds of lines of R code without any user-defined functions and no "high-level" documentation of different sections of the scripts, makes it difficult to sport errors or apply this approach to other datasets. I detail these concerns below.Major issues with code The files 'decimalplaces.R' and 'MultinomialCIsBayes.R' are required to perform these analyses but not included in the repository. Many of the datasets produced by this analysis are only saved in binary formats . Key data underlying the results presented in the paper should be made available in a plain-text format (e.g. csv for the tables). The README file for the github repository should contain: (a) brief description of the most important files included in the repository and their purpose   (b) A list of R packages required to run this code  (c) Instructions on how a user can run these analyses  (d) Links to this paper and the Zenodo archive associated with this repository. The file "make.data.R" would benefit from some high-level documentation explaining the motivations for each section of the file, and precisely what is being created by each code block. At present, the comments and the top of each block are very brief and difficult to interpret. For example, the comment # get meta data " (appearing on line 101) has no obvious meaning to me.Minor issues with code I suggest you avoid using the aliases T and F for TRUE and FALSE. These are not  reserved variables, and accidentally setting them to some other value can lead to unexpected results. The code often uses an idiom like  already.saved = T if {     #do something } I am not sure what purpose this serves, as the value is always hard-coded to TRUE. If the intend is to save users from re-running the data-fetching step it may make more sense to save the data to csv, then check for the existence of the data file before fetching fresh data. The variable "journals2" is defined by never used.  Line 146 has "for (a in 1:9000)", hard-coding the number of articles to 9000 (slightly fewer than the number included in the study). A lot of typing could be saved from variables like "ci.phrases" if abstracts where always converted to lower case before matching strings. This would both increase the readability of the code and make it less likely that typographical errors slip into the code.Minor issues with the manuscript. The word "accuracy" is often used to describe the representation of percentages. I think "precision" is a better term for what is being described. In the introduction, the sentence starting "Papers have been criticised for using too many decimal places..." does not cite any criticism. Rentrez now has a paper to cite1. Winter, D. J. (2017) rentrez: an R package for the NCBI eUtils APII have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. The files 'decimalplaces.R' and 'MultinomialCIsBayes.R' have now been added to github.All the key RData files have now also been provided as CSV or tab-delimited files.The README file in github is more detailed.I’ve added sections to the make.data.R code and improved the comments.I've used TRUE/FALSE in place of T/FAs suggested, I’ve now checked for the existence of the RData files.The variable "journals2" was used as a time saver. The many data were created for two sets of journals .The loop up to 9000 was added because there were sometimes breaks in the online connection to pubmed. I’ve used the full loop and added a warning in the code about this issue.I kept the text in upper case because I originally also wanted to find sentences and used the pattern of: full-stop then space then upper-case letter, to define a new sentence. Changing to lower case included some non-sentence breaks for odd character strings such as compounds or labels from genomics. The idea was to compare percentages in the same sentence, but I did not use this in the paper.Thanks for your useful comments on the code and documentation thereof. Barnett's article tests the adherence of papers in 23 journals to Cole's guidelines on the numerical presentation of percentages. As the author of the guidelines I acknowledge a competing interest. The paper is well designed, executed and reported, and it has a clear message - many papers give percentages to excessive precision. I have a few minor suggestions for improving it. 1. The term "accuracy" used several times in the Introduction and elsewhere should more correctly be "precision". 2. Did the algorithm for identifying percents allow for the possibility of the % appearing preceded by a space? 3. Looking at the R code I note the long lists of alternative spellings. First converting all text to lower case would have substantially simplified this process. 4. The spikes in Figure 1 are interesting. The author suggests they represent digit preference, which may be true, but I would have thought it worth formally checking some of them to see.here. It is "Lack of mathematical education does not become more evident than by excessive precision in numerical calculation." Carl Friedrich Gauss (1777-1855). 5. The paper starts with an apt quotation from Einstein. I wanted to draw the author’s attention to another apt quotation, from Gauss, which appears as a response to my original Archives of Disease in Childhood paper Tim ColeI have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Agreed and changed in the Introduction and Discussion.Yes, a preceding space was allowed. I have now added this to the Methods.I kept the text in upper case because I originally also wanted to find sentences and used the pattern of: full-stop then space then upper-case letter, to define a new sentence. Changing to lower case included some non-sentence breaks for odd character strings such as compounds or labels from genomics. The idea was to compare percentages in the same sentence, but I did not use this in the paper.This comment was based on my informal checks made whilst compiling the data. As a more formal check I examined fifty randomly selected percents of exactly 50 and found that only 20 were actual results, with the rest being rounded results or thresholds. I’ve added some additional text to the paper on this.Thank you for this quote. Excessive decimal places have been a problem for some time and this paper will hopefully help to draw attention to it again.Thanks for your useful comments on the paper. My answers to your numbered questions are:


Senior mentoring programs have been established that provide medical students exposure to a community-dwelling older adult mentor with whom they meet multiple times throughout the program. The goal of these programs is to expose students to healthy older adults, increase knowledge of geriatrics, and prepare them to care for an aging population. However, even while participating in a senior mentoring program, health professions students still demonstrate some discriminatory language towards older adults . In fact, research suggests ageist practices occur, intentionally or not, among health professions in disciplines such as medicine, nursing, and social work and even within assisted and long-term care facilities . We evaluated a senior mentoring program to gauge the impact of a new pedagogical approach and to gain a deeper understanding of the learning gained in relation to ageism and elderhood. This qualitative content analysis explored first-year medical students’ opinions of their own aging and attitudes towards caring for older adults. Students (n = 216) participating in a brief curriculum model of a senior mentoring program responded to the following open-ended prompts before and after the program: 1) How do you feel about your own aging?; 2) How do you feel about working with older adult patients after you complete your medical training? Responses suggest that students’ views of their own aging and views towards towards working with older patients are positively impacted by their experiences in the senior mentoring program.


While literature has shown positive patient, health care provider, and system benefits (SDM outputs), further research is required to understand the nuances of this type of decision-making. As such, we set out to address: “In which situations, how, why, and for whom does SDM between patients and health care providers contribute to improved engagement in the Shared Decision-making process?”Shared Decision-making (SDM), a medical decision-making model, was popularized in the late 1980s in reaction to then predominate paternalistic decision-making, aiming to better meet the needs of patients. Extensive research has been conducted internationally examining the benefits of SDM implementation; however, existing theory on To achieve our study goals we conducted a seven-step realist synthesis process, which included: (1) preliminary program theory development, (2) search strategy development, (3) selection and appraisal of literature in accordance with realist methodology, (4) data extraction, (5) identification of relevant formal theories, (6) data analysis and synthesis, and (7) formation of a revised program theory with the input of stakeholders. This process was done in accordance with RAMESES guidelines and publication standards for a realist synthesis. Expert consultations were also held to ensure consistency within the SDM literature.Through our realist synthesis, we developed a program theory of SDM which includes three contexts , eight mechanism sets , and one outcome (engagement in SDM).how SDM works, for whom, in which circumstances, and why. By examining key mechanism sets and exploring how they facilitate or inhibit SDM, we have produced a program theory that may assist health care professionals, policy makers, and patients. While further research is suggested to further unpack the concepts identified within this paper, this provides an initial understanding into the theory behind SDM.As far as the authors of this paper are aware, this paper is the first to begin unpacking PROSPERO: CRD42017062609. Shared Decision-making (SDM) is a style of decision-making involving health care providers (HCPs) and patients, with the aim of making a joint informed and patient-centred decision , 2. SincSDM can be especially useful in complex cases where multiple options exist , such asTwo key elements of SDM are the elicitation of patient preferences and knowledge exchange between parties , 17, 18.how or why this inhibits the process [SDM literature focuses on descriptive frameworks/models and conceptual development , 27, 28, process  , is well-cited (1063 citations) and respected in the field , 42–46. In the absence of an explicit theory to explain how SDM works, for whom and in which circumstances, we used the IP-SDM model as the basis upon which to build such a theory.What mechanisms can facilitate or hinder engagement in the SDM process?What contexts can affect the expression of the identified mechanisms?In which contexts do varying mechanisms apply?The purpose of this research was to develop a realist program theory for SDM. To meet this purpose, we conducted a realist synthesis, selected because it seeks to understand for whom and in what contexts interventions work , the underlying processes that cause outcomes , and the nature and extent of the outcomes . Realist theories are usually framed as CMO hypotheses. Our primary research question was: “In which situations, how, why, and for whom does SDM between patients and health care providers contribute to improved engagement in the Shared Decision-making process?” That is, what are the contexts and mechanisms that lead to better engagement in SDM? To address this question, we explored:By identifying CMOs, we developed a program theory articulating the main mechanisms that result in successful, or unsuccessful, SDM during medical consultations. While previous papers have identified facilitators and barriers to SDM, this manuscript links contextual factors with mechanisms to form hypotheses (in the form of CMOs), depicting how individuals may successfully engage in SDM.In this section we provide a brief review of the methodology used in this realist synthesis. A complete description of the methodology can be found in a previous publication .We chose realist methodology to understand the complexities of shared decision-making, identifying how, in which situations, for whom and why SDM works or fails. Realist methodology is grounded in the philosophy that contends the identification of generative mechanisms within programs. Realist philosophy acknowledges that the world is “real”, but the perception of the world is constructed through social and cultural interpretation , meaningDeveloped by Ray Pawson, realist syntheses examine how and why an intervention is successful or fails , 48, 49.To conduct our realist synthesis, we followed the realist synthesis process developed by Pawson , and vispreliminary program theory with the initial results , and continues on to follow the patient through the SDM process and demonstrated primary and secondary outcomes of SDM implementation. This preliminary program theory is intended to act as an initial sketch of our understandings of SDM to form hypotheses for our formal search strategy. Following this process to explicitly state our rough understanding without a formal synthesis of SDM follows training methods outlined by RAMESES [Our team conducted a scoping review of literature , and dra RAMESES .We began with a purposive (targeting SDM specific literature) search of the SDM literature through PubMed and Google Scholar using the following keywords: “shared”, “collaborative”, “decision-making”, “informed”, “oncology”, “cancer”, “treatment”, “patient(s)”, “physician(s)”, “clinician(s)”, “theory”, “development”, “model(s)”, and “framework(s)” Fig. . OncologScreening was completed by two team members using the following inclusion criteria: (1) an exchange between a patient and/or patient’s family and a health care provider, (2) a clinical situation where the patient is legally competent to make his/her own decision, (3) adult patients (18 years or older) making decisions about their own medical situation, (4) sources from 1980 to present, (5) English-language sources only (due to the language constraints of our team). 1980 was chosen as this is when SDM was first popularized in research. Empirical, theoretical, or grey literature were all included. Studies were excluded if their focus was on surrogate decision-making, when patients are unable to be involved , or if they did not assess factors that attributed to SDM engagement of the health care provider and patient . Pawson’s criteria of relevance and rigor were also used to assess each source for applicability and methodological appropriateness, respectively . SourcesEach source was read in full and explanatory accounts (EA) statements were extracted, in the form of ‘if-then’ statements . An extraction template was used for this process which included: 1) bibliographic information; 2) notes relevant to the developing program theory; 3) country of study/document; 4) focus of document (patient and/or HCP); 5) empirical or theoretical (if relevant). Any middle-range theories that were used were noted by the authors within this template. EA statements were extracted from the results and discussion segments of papers, often connecting multiple findings within a single statement. A list all EA statements has been previously published within a thesis document .Our stakeholder session was comprised of knowledge users who had experience with medical decision-making. Recruited through the local health region and provincial health ministry, this group was composed of two oncology patients, two nurse navigators, one oncology specialist, one family physician, and two policy makers. Patients were recruited through a provincial patient forum with a self-identification process. Stakeholders were identified as those who would be most impacted by the implementation of SDM, as indicated in literature. Two individuals from each stakeholder category were chosen to allow adequate representation. The semi-structured session lasted three hours and participants were asked their perspective on whether the program theory represented their experiences. The session guide has been previously published . Data gaIn-session notes and the session transcript (transcribed from audio-recordings) were analyzed using retroductive techniques, as per realist evaluative processes . Retroduinitial program theory . Typically, EA statements were composed of two-thirds of the CMO configuration . An example of this process  can be n = 180); patients (n = 374); both health care providers and patients (n = 81); and health care system factors (n = 10). Within these four categories, EA statements were placed into a thematic group. Researchers derived themes based on demi-regularities found within the extracted EA statements. This process of consolidation formed a total of 61 thematic groups under the four target categories. If an EA statement could fit into more than one thematic group (e.g. patient anxiety and patient trust), it was placed into both thematic groups. This caused an inflation in the total count of EAs within each category, compared to the total number of extracted EA statements.We created four categories to identify who the EA statements were specifically targeting: health care professionals  but include mechanisms that can inhibit or facilitate SDM dependent on context. Based on our clinical , patient (LB) and research ) expertise, the entire team identified nine mechanisms believed to hold the most causal power, or sets of mechanisms, which we hypothesize are critical for how the process of SDM works or fails. Table focused IP-SDM mechanism map  was then created. The focused IP-SDM mechanism map incorporated mechanisms that can hinder and/or facilitate engagement in SDM . A pathway of SDM is visually depicted based upon the IP-SDM pathway [A  pathway . IP-SDM initial program theory focusing on only the key mechanisms , that context may trigger a higher level of anxiety. Similarly, remaining key mechanisms will be variably expressed; a complex decision is thought to influence the extent to which other key mechanisms are also triggered. Together, the combination of how the context and mechanisms manifest will determine the level of engagement the HCP and patient can achieve, impacting the decision that is made. Therefore, each of the key mechanism sets in the initial program theory have their own gradient, which may shift in expression in each consultation, producing different levels of engagement. Together the interaction within the key mechanisms (how mechanisms impact one another when expressed) and context results in a varying level of engagement in the SDM process from both the patient and HCPs. When engagement in SDM is of a high quality from both the patient and HCP, it then enables a patient-centered and informed decision.To better demonstrate the level of complexity within our program theory, we developed our sms Fig. . Based oThroughout the data extraction phase, TW and TC extracted any formal theories that were used within the SDM literature to underpin the decision-making process. A few theories were identified from our sources; however, only three (Theory of Planned Behaviour (ToPB), Feeling of Rightness (FOR), and Expected Utility Theory) were able to assist in the explanation of the developing middle-range theories. An extension of the Theory of Reasoned Action, the ToPB depicts the volition an individual has, or does not have, to control a decision , determiinitial program theory , the physician may accurately assess the patient’s preferred level of engagement which would promote the process by increasing patient trust. However, if the HCP makes incorrect assumptions, or if a negative history exists, this may increase patient anxiety and decrease patient trust. The second key point was that the stakeholders believed that the key mechanisms could apply to both patients and health care providers, rather than being separated by role within the consultation .Stakeholders were generally supportive of the Stakeholders and researchers continued to explore the role of the key mechanisms, during which we decided to revisit the literature regarding health care system support to better understand how it acts as a mechanism. This iterative fashion of analysis is in-line with the nature of realist research, and the formation of program theories , 53. At revised program theory , and the adaptation of all mechanism sets to be relevant to the patient and the HCP. The white space within the honeycomb pattern represents the existence of other mechanisms, such as the remaining 45 mechanisms identified in our analysis that were not included as key mechanisms. These key mechanisms interact with other elements of the contexts, to determine the level of engagement in SDM during the consultation. Finally, we returned to our focused IP-SDM mechanism map and implemented the changes from the stakeholder session, creating the revised focused IP-SDM mechanism map , for whom, in what circumstances, and why. We overlapped these key mechanisms with the IP-SDM model to understand when these factors may become important during the decision-making process.revised program theory offers a novel understanding of how SDM works, for whom, in which circumstances, and why or why not. Specifically, it demonstrates that SDM works in a complex manner, and for any individual patient and HCP there may be an array of interconnected mechanisms at play. Further, these mechanisms can change in their expression continually depending on contexts. We have built upon previous research by linking facilitators and barriers to contextual factors which alter how mechanisms are expressed. While we aimed to form a program theory that clearly uncovered how SDM works, our analysis uncovered mechanisms that trigger variably based on the simultaneous expression of partnering mechanisms. This has resulted in the formation of testable hypotheses to investigate in future works, and has initiated the first step towards understanding the nuance within SDM.Our Our findings align with previous studies of SDM facilitators and barriers. Through a systematic review Joseph-Williams and colleagues (2014) identified eight factors that patients reported could potentially inhibit their involvement in SDM, giving specific attention to the power imbalance between health care professionals and patients . The autOur results have several potential practical implications. Health care professionals can use this program theory to identify key areas to focus on to provide patient-centered care. Through this, HCPs may be able to identify patients that require increased support based on those who display concerning levels of factors identified in our analysis, such as high anxiety. We anticipate that the program theory will help increase clarity and understanding within the complexity of patient care. Similarly, policy makers may be able to identify where system changes, such as increased consultation times or additional training and education, may be necessary.revised program theory may be used convey the complexity of SDM to current and future HCPs. Guided by this theory, HCPs could better understand how to approach consultations with an array of patients, and gain increased capacities to successfully, and appropriately, attend to the key mechanisms. This program theory makes SDM more explicit by depicting how pre-identified barriers and facilitators influence the SDM process. It will encourage HCPs to provide education to patients in specific areas, and indirectly increase the quality of patient care.Our We identified three formal theories that together describe how the program theory can be used to determine engagement in the SDM process: the Theory of Planned Behaviour (TOPB), Feeling of Rightness (FOR), and Expected Utility Theory. While none of these theories individually explains how engagement in SDM occurs through our revised program theory, the three formal theories support segments of the program theory – such as specific mechanisms, contexts, or predicting the overall engagement outcome. A description of how these formal theories link to the program theory, and a description of their impact, can be found in Table Our research may have been impacted by publication bias (research supportive of SDM is more likely to have been published than that refuting it). To mitigate this, we examined grey literature in medical decision-making. Due to the amount of available literature, and the resources of our team, our search was focused on the medical decision-making rather than decision-making literature more broadly. Future research could be undertaken to broaden the scope. In addition, the time taken from initial searching in 2015 to the refinement of our program theory following stakeholder analysis in mid-2017 may have allowed for newer information to be released. To alleviate the potential impact, we continually investigated new literature, through Ovid literature updates on our secondary search.Realist methodology acknowledges that there will always be other interpretations of data, and final knowledge is never achievable . We are A related, but important limitation to our work is that we identified three contexts that impact the manifestation of all mechanisms, rather than identifying mechanism specific contexts. As this project focused heavily on identifying the key mechanisms, future research is needed to explore what other contexts play a role in this process. This work is required to form a more complete understanding of how the mechanisms operate for different people and in different situations. However, we believe that this synthesis has undertaken the first step in identifying and understanding contexts and mechanisms that impact SDM engagement.Our program theory is novel in revealing the complexities of SDM. We acknowledge this as the first step to a series of applications of our findings. We encourage future research to test the program theory towards determine its applicability within different contexts. This process will confirm, refine, and/or refute the program theory in whichever context it may be applied. Specific examination in additional contexts  may uncover additional key mechanisms. The program theory can be adapted to specific populations for a broader understanding of how engagement within SDM can occur.Our team has begun exploring decision-making in a few areas. One area is with the Saskatchewan Indigenous population, and how culture and beliefs influence their decision-making process, and the resulting implications for the program theory. Using interviews with Indigenous patients living with cancer, and a focused realist synthesis on Indigenous world view and trust, we are refining the program theory to reflect the decision-making experience of the Indigenous populations. We have also conducted focused testing of the program theory in the context of prostate cancer patients. We anticipate testing the program theory in different areas to confirm, refine, and/or refute these findings, creating a more fine-tuned program theory for specific populations.Using a realist synthesis, and following RAMESES guidelines, we have conducted a realist synthesis of SDM. To our knowledge, this is the first examination into the mechanisms of SDM and how they inhibit and facilitate SDM implementation through patient and health care provider engagement. We have produced a program theory depicting key mechanism sets that can inform health care professionals to tailor their consultation process to each individual patient, and can provide a tool for policy makers to identify necessary system level changes. These findings allow us to better understand “In which situations, how, why, and for whom SDM between patients and health care providers contributes to improved decision-making”.Additional file 1. Preliminary Program Theory. This depicts the preliminary program theory that was developed by the authors following an initial scope of the SDM literature, based on the understanding of how SDM worked and the outcomes of implementation.Additional file 2. Refined Medline Search Strategy. Refined Medline Search Strategy Secondary search strategy, conducted October 16th, 2015.Additional file 3. Example of Data Extraction, Synthesis, and Analysis process. An example of how article texts were extracted into EA then synthesized into thematic grouping and eventually analyzed to CMO configurations.Additional file 4. All Identified Mechanisms. All identified mechanisms extracted from EA statements.Additional file 5. Focused IP-SDM Mechanism Map. A mechanism map connecting key mechanisms set IP-SDM.


A revolution in seismic detection technology is underway, capturing unprecedented observations of earthquakes and their impacts. These sensor innovations provide real-time ground shaking observations that could improve emergency response following damaging earthquakes and may advance our understanding of the physics of earthquake ruptures. The impacts of earthquakes are typically greater in developing countries where large populations centres are located in regions of high seismic hazard and the traditional building stock is more vulnerable to earthquake shaking1. Understanding the physics of how, when, and why large, potentially damaging earthquakes occur is critical for mitigating their effects. Yet, there are essentially no direct measurements of fault slip at the depths at which earthquakes start, typically a few to tens of kilometres below the Earth’s surface. Seismometers can accurately detect the displacement, velocity, or acceleration of the ground surface due to permanent shifts resulting from fault movement or the transient oscillations as seismic waves pass under a site. However, these data typically provide only scant observations as instruments are spaced too widely or data are not continuous in time.On average, at least one earthquake of magnitude 7 or greater occurs each month somewhere around the globe. Many of these earthquakes go largely unnoticed as they occur in remote locations, but when a major earthquake happens near an urban centre it can result in substantial loss of life and economic losses. For example, the 2011 M9.0 Tohoku earthquake resulted in more than $300 billion USD in losses due to the earthquake and tsunamiCost also presents a large impediment to long-term, dense (stations spaced at less than 10–20 km) ground motion observations. Research-grade, high-resolution seismic sensors are a fairly niche market with limited customers. These expensive specialty instruments are placed in long-term installations that are hardened to withstand strong shaking from earthquakes. Just one of these stations costs tens of thousands of dollars to build and equip, including sensors, on-site data acquisition systems, telecommunications, and back-up power. Multiple ground shaking measurements are required to locate and characterise an earthquake; and, in the event of a major earthquake the data are critical for determining the severity of shaking across the impacted region in order to guide emergency response to the hardest hit areas. Furthermore, earthquake early warning systems that rapidly detect earthquakes could provide critical warnings to affected populations prior to the arrival of damaging seismic waves, but these systems require dense instrumentation as every additional station improves the speed and accuracy of the alerts. Even the densest seismic networks in the world typically do not have more than one sensor every ~20 km, which can cost hundreds of thousands of dollars or more each year to operate and maintain. Operating a state-of-the-art seismic network can be beyond the reach of many developing countries leaving them especially vulnerable given the lack of data to understand local seismic hazards.However, today earthquake sensing is in the midst of a renaissance as the methods available to more densely observe earthquake ground motions have expanded by leveraging both new types of purpose-built seismic instrumentation and new sensors in the built environment.2. These sensors eliminate the need for transport and installation of the heavy cables that once connected sensors together, and have batteries that last 30 or more days, making these systems attractive for use in earthquake studies. Without cables, the individual sensors are lightweight and easy to transport to remote locations so that station layouts can be better tailored to specific study targets. A 6-month deployment of 5400 sensors over a ~100 km2 area in Long Beach, California was deployed by industry, but data were made available to academic researchers. The data showed unexpected slip occurring in the deep roots of faults3 and provided insights into how shaking may vary across the region during a large earthquake by imaging the shallow subsurface4. A recent experiment on Mount St. Helens deployed a spiderweb of 904 nodes for 2 weeks providing an order of magnitude increase in the number of earthquakes observed beneath the active volcano compared to the existing traditional seismic network5. And, nodal arrays in Oklahoma are being used to track small earthquakes moving along previously undetected fault structures that are induced by injection of wastewater into deep wells in areas of oil and gas production7 . The advent of low-cost, ‘personal’ seismometers provides opportunities for long-term installations at only a few hundred dollars each, a fraction of the cost of a typical seismic station10. Rapid deployment of these sensors following the 2010 M8.8 Maule, Chile and the 2010 M7.2 Darfield, New Zealand earthquakes expanded the number of available observations from a few tens of research-grade sensors to hundreds of (lower-resolution) sensors used for rapid event detection, characterisation of local geology, and details about the earthquake sources13. MyShake also uses smartphones but integrates machine-learning techniques to separate quakes from other movement 14. And, a system deployed in Chile , for earthquake detection ever more attainable. Several groups have been working on collecting and combining data from consumer devices. The Quake Catcher Network pioneered the concept, by exploiting commercial-grade accelerometer inside laptops and smartphones and using distributed computing techniques to record data and detect quakes17 in a recent publication, fibre optic cables used for communication can be transformed into a series of sensors through the use of laser pulses that are backscattered in the fibre and recorded by a receiver. These sensors measure strain, i.e., very small changes in the length of the fibre cable  from extension and compression as seismic waves pass. Effective sensor spacing on the order of 1 to 10 m can be achieved, providing ten to fifty times more sensors over a given distance than even nodal systems. A 15-km-long fibre-optic cable with 4-m sensor spacing is providing new images of extraordinary resolution that show the deformation of faults in Iceland and seismic waves trapped within fault zones . Fibre optic cables have also successfully recorded small earthquakes in Alaska and California at resolutions similar to scientific-grade equipment18. However, although promising, this approach requires significant development in order to translate and calibrate the data for widespread use.As described by Jousset et al.Each of these novel ground motion sensor networks provide incredible opportunities for recording rich datasets with which to study the movement of waves through the Earth and to decipher the inner workings of faults. Low-cost sensors may transform earthquake science in countries at significant risk of damaging earthquakes, but which may not be able to afford the high cost of installing and maintaining traditional seismic networks. There are still limitations to the resolution of the sensors, interpretation of the resulting data, and efficient management of the resulting large data volumes. Despite the limitations, I look forward to a time when smoke detectors and smart gas meters, or even perhaps millions of toasters provide records useful for seismology.


Automated program analysis for inferring program complexity and resource bounds is a very active area of research. Amongst others, approaches have been developed for analyzing functional programs , C# 15]15], C 2, 29, 35,Verification In many applications such as embedded systems there is a hard constraint on the availability of resources such as CPU time, memory, bandwidth, etc. It is an important part of functional correctness that programs stay within their given resource limits. As a concrete example we mention that considerable effort has been invested to analyze the worst case execution time (WCET) of hard real-time systems  In most cases of interest, the initial potential is zero and the potential is always non-negative. In such a situation the total amortized time is an upper bound on the total time [n executions of operation j as a potential function, i.e. we choose tal time . I.e., ientclass1pt{minimaj models the stack size. The j by 1. The inlined. Consider the labeled transition system of Example tarjan shown in Fig. j by 1, a sequence of transitions complete run amortized cost of a sub-run n times and each Example tarjan in Fig. mentclasspt{minimapotential functions. We base our discussion on the concrete semantics of Example tarjan given by the LTS in Fig. length of j’ of local boundj of potential function, as we show next: we get the following amortized costs for executing local boundj of j can be incremented on In the following we argue that our transition bound algorithm mentclasspt{minimamentclasspt{minimaentclass1pt{miniman for the total cost of the Using We presented a new approach to (resource) bound analysis. Our approach complements existing approaches in several aspects, as discussed in Sect. Our algorithm Sect.  obtains difference constraints are a suitable abstract program model for automatic complexity and resource bound analysis. Despite their syntactic simplicity, difference constraints are expressive enough to model the complexity-related aspects of many imperative programs. In particular, difference constraints allow to model amortized complexity problems such as the bound analysis challenge posed by Example xnu  from imperative programs and showed how to use these norms as variables in We have demonstrated that Our approach deals with many challenges bound analysis is known to be confronted: in Sect. scalable than existing approaches. We presented empirical evidence of the good performance characteristics of our analysis by a large experiment and tool comparison on real source code in Sect. We stress that our approach is more We think that the abstract program model of difference constraint programs is worth further investigation: given that difference constraints can model standard counter manipulations , a further research on complexity analysis of difference constraint programs is of high value. We consider In the following we state what we consider to be the main technical reasons that make our analysis scale:local reasoning: note that our abstraction procedure relies on purely local information, i.e., information that is available on single program transitions. In particular, we do not apply global invariant analysis. Further, the sets single (abstract) program transitions based on simple syntactic criteria. Our algorithm for computing the local bound mapping polynomial even in the generalized case . Unlike classical invariant analysis this approach is small, namely simple linear arithmetic formulas, composed of the arithmetic of single transitions. Our approach instruments the SMT solver only for yes/no answers, no optimal solution  is required.Note that the only general purpose reasoner we employ is an SMT solver. Further, the SMT solver is only employed in the program abstraction phase. In terms of size, the problems we feed to the SMT solver are polynomial time. The reasoning based on reset chains . We did not experience this to be an issue in practice because the simplicity of our abstract program model allows to take straightforward engineering measures: program slicing reduces the number of paths in the program significantly, further, merging of similar paths can be applied .Supplementary material 1 (pdf 303 KB)Below is the link to the electronic supplementary material.


A large body of research has established that sport intervention programs can have social, emotional and health benefits for at-risk youth. While research has focused on the positive outcomes associated with these programs, little attention has been given to program inputs. It is recognized that community partnerships can help intervention programs achieve their goals. Yet, how are such partnerships formed and what can help to promote the successful formation of partnerships? This paper provides a detailed account of the partnership implementation process undertaken to develop and deliver a health promotion physical activity program for at-risk youth through the medium of CrossFit in a low socioeconomic area in a rural community in the southeastern United States. Developing successful partnerships serves as a valuable component to help organizations obtain resources and skills needed to initiate and continue programs for underserved populations. The scholars identify and explain how critical success factors such as personal contact, partnership complementarity and fit and the promotion of high levels of commitment and trust, serve as important starting points for developing and maintaining strong community partnerships. Community based programs attempting to address multidimensional social problems within the youth population can benefit from multiple partnerships across a wide range of organizations ,2. IndeeThe promotion of health, both on an individual and community level, is widely recognized as an important component of social progress and societal improvement. However, opportunities and access to programs which support the enhancement of individual and community health vary due to differences in socioeconomic status, race, gender, age and environmental factors . Indeed,To address the gap in literature, this paper presents a detailed account of the partnership implementation process undertaken to develop and deliver a health promotion physical activity program for ‘at-risk’ youth through the medium of CrossFit in a low socioeconomic area in a rural community in the southeastern United States. To gain an understanding of the partnership developed between the youth CrossFit program and the local community, we opted to use Boutin and Le Cren’s  (p. 28) Parent and Harvey  noted thWhile the Parent and Harvey  model haThe current research applying the Parent and Harvey  model inThe youth development program addressed in this manuscript centers on three important areas of sociological critique: (1) the program will be delivered to at-risk youth; (2) the program will be delivered in a geographical area of low socioeconomic status; and (3) the program will be delivered through a non-traditional physical activity medium. It is important to note that none of the aforementioned studies explored partnership model development within these social parameters. Therefore, attempts to replicate and repeat the processes used by our peers would be impractical and ineffectual; the contextual encompassing of the program is critical. However, we acknowledge a need to be conscious of the contributions of previous studies to ensure every attempt is made to glean best practice insights and embed them within our program formation. Collectively, what we have learned from our peers in applying the Parent and Harvey model  to commuThe local CrossFit program discussed in this paper targeted youth who were deemed ‘at-risk,’ a category often described for individuals in circumstances with: limited social support, inconsistencies in life situations and dependence on school and after-school programs for meals. Haudenhuyse, Theeboom and Nols  refer toOver the past two decades there has been a growth in research to understand interventions for at-risk youth that use sport and/or PA as the vehicle for personal betterment ,32,33,34The fitness regime of CrossFit has seen an increased societal interest as a space for physical and personal change. The first CrossFit box (“box” is CrossFit terminology used for gym) opened in 2000 and now there are more than 13,000 affiliates worldwide . CrossFiCrossFit also has a history of being offered to underserved youth populations. Steve’s Club was the first official organization to develop CrossFit programs for inner-city youth at-risk in Camden, NJ in 2008 ,5. As ofCrossFit programs for underserved youth are run at the community level. Often the programs themselves must find ways to generate funding to cover the costs of membership, clothing, equipment and in many cases food and transportation . For exaThere are major challenges in developing, managing and maintaining organizations aiming to provide physical activity for underserved youth. In this paper, the authors focus on the antecedent component of Parent and Harvey’s  model toAdditionally, Schulenkorf, Sugden and Burdsey  assert tIn addition to issues of funding and organizational planning, the community context is also important and needs to be taken into consideration. Organizers of the youth CrossFit program analyzed the local county to gain a clear understanding about the environment. A number of contextual factors arose that could not be addressed without external support, further underscoring the importance of developing partnerships in order to create a successful intervention program. Some of the main obstacles facing the local community centered on high levels of poverty, low education levels, lack of transportation and few available fitness programs for youth. In 2015 where the program was being held, the county-wide per capita annual income was $18,719. Only 29% of adults had a bachelor’s degree or higher. There was no public transportation in the form of buses, trains, or city-wide walkways in the community. This means that if youth want to go somewhere, they have to walk on roads, arrange a personal ride, or simply not go. The organizers realized in order to reach underserved youth, they would have to go to the youth to run a program or find some form of transportation. Finally, there were no fitness programs for underserved youth beyond the county recreation department and school activities. Therefore, bringing in a new fitness routine, like CrossFit, provided a non-traditional, individualized program that represented a significant departure from what was available in the area. Because of limited knowledge about the activity, it was important to hire well qualified, experienced CrossFit staff in order for the intervention to have the best chance at success.Considering Babiak and Thibault’s  concern The committee met to discuss the rural community and identified the major contextual factors that needed to be addressed so the organization could be successful and meet the goals. Realizing that local obstacles included the lack of public transportation, a high percentage of low income population and the need for properly trained staff, the committee recommended partners and sponsors from the local community that could help address these shortcomings. The organizers set-up meetings with community organizations who could assist with specific needs for the program. During the meeting, information was given about the program, how the community organization could be useful and how the program could benefit the organization. Informational sheets were given to the individual who would serve as the point of contact. Follow-up meetings were scheduled with the interested organizations where the point of contact and program leaders discussed the responsibilities of both parties.The youth CrossFit program established four significant partnerships to address the community’s shortcomings. All four partnerships have been maintained for two complete years and each partnership renewed with the program for the third year. A brief description of the organizations and partnership relationships are provided.A national afterschool organization. For the first year of operation, all members of the youth CrossFit program came from the local county location of the national afterschool organization. As the partnership was developed, the local county location of the national afterschool organization described the members as being at-risk. According to the administrators, 94% of their membership come from minority and/or low-income families in the rural community. Many come from single-parent or caregiver homes and the children have limited options for places to go other than their home, school and the afterschool location. Additionally, many of the participants depend on Federal Food Assistance Programs and meals provided from the afterschool organization throughout the academic year. The local county location of the national afterschool organization received a federal grant to fund the organization transporting their members to activities that are not provided on site. The local county location of the national afterschool organization formally agreed to: (1) recruit middle school aged members and transport them to the local CrossFit facility (10-mile round trip); (2) provide an adult supervisor from their organization; (3) provide shoes for each participant which would be stored at their facility; and (4) have food available for each child when they return from CrossFit.Local CrossFit. The local CrossFit facility, established in 2012, started a CrossFit Kids program in 2014. In 2015, the business was doing well and the owner was interested in getting more involved in the community. Coaches who held the CrossFit Level 1 and CrossFit Kids certificates were recruited from the local facility. Additionally, two of the coaches had experience working in the public school system. The local CrossFit box was excited to set-up a partnership where they formally agreed to: (1) assist with the structure and design of the program; (2) provide a qualified coach; (3) provide space and equipment for classes; (4) include the program on the insurance policy held by the facility; and (5) provide discounted memberships to the youth members.Local Pediatric office. There are ten pediatric businesses in the 10-mile radius that spans this community. As the youth CrossFit program was being established, one local pediatric office showed interest in partnering with the youth CrossFit program. This pediatric office was a good fit because their organization already served the local community. The medical organization described working with patients in the same population . The partnership was important because the organization agreed to provide a large financial donation. Additionally, free physicals were provided to each participant between 5–8 p.m., which was valuable because the pediatric office hours of operation are weekdays between 8 a.m. and 5 p.m. Organizers discovered that one reason many at-risk children do not participate in school sports was due to the lack of flexibility in medical office hours, resulting in youth not being able to complete the physical exams that are required in order to participate. These school-based sporting activities often required parents to leave work in order to facilitate their children’s participation in the activities. By providing free physicals later in the evening, parents/caretakers not only did not have to worry about insurance coverage or out-of-pocket charges but the flexible hours allowed parents/caretakers to complete the paperwork and be present for the physical exam after their work day had ended. The pediatric office also agreed to be available for any program participant who needed medical attention as a result of participation in the program .A local, youth-focused private foundation. The youth-focused foundation was created to invest in the lives of young people. The foundation aims to reduce the number of barriers that at-risk youth experience and to expose them to new and different opportunities in the world. The youth-focused foundation formally agreed to provide financial backing that goes towards: (1) paying memberships during the academic year and one scholarship for a participant to attend a summer camp; and (2) provide shoes, shorts and under clothes for any participant so each person can have access, opportunities and new experiences.Throughout this process of partnership development, we sought to rely on findings from previous research to enhance the proposed intervention program and boost its chances of succeeding. The development of the partnership among the four entities described above was guided by our review of the collective critical success factors identified in literature utilizing the Parent and Harvey  model foPersonal contact. One person from each organization was identified as the contact person. This individual was expected to act as the liaison between the partner organization and the program. This person was responsible for funneling information to their stakeholders and making decisions for the partnership. Identifying and cultivating this personal contact within each partner organization during the planning stages, prior to the implementation of the intervention program, was critical for the success of the overall partnership. Having this personal contact in place benefited the partnership in three specific ways: (1) reducing confusion and the potential for mixed messages; (2) enhancing the efficiency of communication and the speed with which decision-making occurred; and (3) assisting in maintaining the partnership’s mission and goals.An outcome from identifying the personal contact was the development of high levels of communication. Since this person was responsible for identifying the best way to work through the partnership, the personal contact was responsible for guiding how decisions would be made for their organization and for recommending how best to address any issues that arose in the partnership. By maintaining open communication with the contact person, we were able to coordinate programmatic needs and plans with all of the community partners in order to streamline program management.Partnership complementarity and fit. Branding and public image were important considerations for our program as well as for each of the partners involved. Therefore, we sought to identify potential partner organizations that had positive public images and had similar missions. For example, each of the organizations we contacted about entering into a partnership worked with youth and all four partners had a vested interest in providing health opportunities for youth. Therefore, the partners were able to work together, each identifying resources that they were able to provide to support the overall partnership and the program.Promoting high levels of commitment and trust. Even before contacting potential partners, the organizers of the program made intentional efforts to develop a strong foundation to show their commitment to the program. For example, the advisory board was in place and the initial grant was secured before any contact was made with potential community partners. The organizers wished to demonstrate their serious intentions with the project, which was also a sign to partners that the program was poised for longer-term success. Early discussions with potential partners emphasized the careful planning that had already taken place to structure the program and new partners were brought into the discussion so that their voices and viewpoints were valued as programmatic planning continued to unfold. By encouraging partner organizations to be involved and have a voice with various decisions from the beginning, the organizers found that both trust and increased commitment were being built. After the program was implemented, community partners continued to be closely involved. They were encouraged to attend CrossFit sessions with the youth throughout the program and representatives of two organizations have come to the gym to join to participate in the activities. The partners were also able to follow the progress of the youth through biannual newsletters.Kidd  highlighThis paper highlights the importance of developing intentional partnerships when creating a sport intervention program for at-risk kids in low-income and underserved communities. Sport intervention programs are widely recognized as an effective vehicle for improving children’s health and well-being. However, scholarly research on intervention programs tend to focus on program outcomes and neglect the value of sharing the processes of establishing a successful, long-term organization. We argue that in order for intervention programs to succeed, careful attention must be paid to the establishment of the organization. Furthermore, we recognize that when serving at-risk kids in underserved communities, successful sport intervention programs often rely on the development of partnerships, which adds a layer of complexity to the planning and development process.Recognizing the need for a tool to manage and evaluate local partnerships for community-based youth sport and physical activity programs, Parent and Harvey  proposedAt the conclusion of our planning process, the youth CrossFit program entered into four significant community partnerships, which ultimately led to the implementation of a successful sport intervention program for at-risk kids in our local community. Organizers of youth development programs in other communities can learn from the example of the youth CrossFit program discussed here. While there is ample evidence that sport intervention programs can have positive outcomes, there is much less attention given to the strategic planning that is required in order to develop partnerships that lead to more effective intervention programs. In sharing the experiences of the local youth CrossFit program, we provide a roadmap for other organizers of youth development programs. Organizers who are cognizant of the antecedents of partnership development will better understand the importance of planning and can take steps that lead to even stronger community partnerships that enhance the overall success of youth development programs.


M = 13.58, SD = 1.26), randomly assigned to the experimental and control groups. Repeated-measures ANOVA of pre-post-test scores were conducted. Results showed a significant decrease in bullying and victimization and cyberbullying and cybervictimization in the experimental group, compared to the control group, indicating that the Prev@cib program is effective in reducing bullying and cyberbullying. Taking into account the harmful effects of these types of violence, the results have important implications in the prevention of these behaviors because they provide scientific evidence of the program’s effectiveness.Due to the negative consequences of being bullied and the increase in cyberbullying among adolescents, there is a need for evidence-based programs to prevent and intervene in these types of peer violence. The aim of this study was to evaluate the effectiveness of the Prev@cib bullying and cyberbullying program, drawing on three theoretical frameworks: the ecological model, empowerment theory, and the model of personal and social responsibility. The Prev@cib program was evaluated using a repeated-measures pre-post-test design with an experimental group and a control group. The sample consisted of 660 adolescents between 12 and 17 years old ( Information and communication technologies have many advantages for adolescents, allowing them to have unlimited access to all types of information and fostering interactions with peers at any place and time ,2. HowevBullying and cyberbullying have some features in common, such as the imbalance of power between the victim and the aggressor and the intentionality and repetition of the violent behavior ,7. TheseThis continued bullying in offline and online settings seems to produce a high level of psychological distress and behavior problems in the victim ,16, as wDue to the social concern about bullying and cyberbullying, numerous programs have been developed to prevent and intervene in these two modalities of peer violence ,27,28. MIn general, previous meta-analyses and systematic reviews have provided little scientific evidence about the effectiveness of bullying and cyberbullying interventions ,36,37. IIn sum, due to the great social relevance that cyberbullying is acquiring worldwide, it is fundamental to develop anti-cyber(bullying) programs that are clearly grounded in theoretical frameworks and experimentally tested.Prev@cib is based on three theoretical frameworks: the ecological model , empowerModule 1. Information about risk and prevention factors in the bullying and cyberbullying problem. This module also includes information about sexting and grooming. In fact, some studies have found evidence of a relationship between cyberbullying and sexting and cybergrooming ,45. The Module 2. Awareness and sensitization about cyberbullying. This consists of two sessions designed to make the participants aware of and sensitive to the harm and negative consequences of peer violence, both in school and through technologies. It is important for adolescents to understand the harmful consequences of school and cybernetic violence, in order to foster changes at cognitive, behavioral, and attitudinal levels and prevent and reduce this peer abuse at school and online.Module 3. Involvement in and commitment to prevention and intervention in cyberbullying. This module is composed of four sessions designed to encourage students’ involvement in and commitment to preventing and acting on this problem. In this regard, an emphasis is placed on the role of all the students in stopping and preventing the appearance and continuance of bullying. Thus, in the classroom, a climate of respect is fostered, so that no type of violence is tolerated among the adolescents in the school or virtual environment. Grounded in this theoretical foundation, the Prev@cib consists of 10 one-hour sessions distributed in three modules: information, awareness, and involvement .Module In addition to these 10 intervention sessions, the program contains two other one-hour sessions to experimentally evaluate the effects of the program (pre-test and post-test).To implement this program, the recommendations of Garaigordobil and Martínez-Valderrey (2014)  were folTaking into account the need for evaluations of programs focused on bullying and cyberbullying prevention, the main aim of the present study is to evaluate and test the effectiveness of the Prev@cib program on (cyber)bullying and (cyber)victimization among adolescent students. Specifically, the hypotheses are: (1) after the program, the intervention group will obtain lower scores on violent school behavior than the control group; (2) the intervention group will obtain lower scores on school victimization than the control group; (3) the intervention group will obtain lower scores on cyberbullying than the control group; and (4) the intervention group will obtain lower scores on cybervictimization than the control group.To evaluate the effects of the Prev@cib program, a repeated-measures (pre-test and post-test) quasi-experimental design was used with an experimental group and a control group. Initially, the sample was composed of 692 adolescents. Thirty-two participants were eliminated (4.63% of the sample) because they did not correctly fill out the questionnaires or because they missed more than one session of the Prev@cib program.M = 13.58, SD = 1.26). The participants belonged to 35 classes from four high schools (compulsory secondary education) in Valencia (Spain). Of them, 28.8 percent were in 7th grade, 32 percent were in 8th grade, 21.5 percent were 9th grade, and 17.5 percent were in 10th grade. The final participants in the Prev@cib program were 660 adolescents (53.2% girls and 46.8% boys) between 12 and 17 years old , gender (χ2(1) = 0.33; p = 0.568), and grade in school (χ2(1) = 0.01; p = 0.919).As Various informative meetings were held with the selected schools to explain the objectives and methodology of the Prev@cib program. The high schools were selected through non-probability convenience sampling based on their accessibility and previous interest in participating in this study. After obtaining parent permission and authorization, the researchers randomly assigned the adolescents to one of two groups: (1) an experimental group, where the Prev@cib program was implemented; (2) a control group, where the program was not implemented.To evaluate the short-term effects of this pilot program, all the adolescents  filled out a structured pen-and-paper questionnaire in their classrooms. Under the supervision of a least one of the researchers, this self-report questionnaire took approximately one hour to complete. When the questionnaires were administered, the adolescents were told that their participation would be voluntary and anonymous. The Prev@cib program, which lasted 9 months, was implemented in the experimental group during their homeroom schedule. A pre-test was carried out in September 2016; a post-test in May 2017. The intervention took place from October through April 2017. The experimental and control groups filled out a battery of instruments in the pre and post-test phases. The Prev@cib program was administered by 13 teachers and four researchers previously trained by one of the investigators in this study. Parental consent for participation was received from all participants. Furthermore, all the adolescents gave their informed consent before they participated in this study. This study followed the ethical values established in the 1964 Declaration of Helsinki and its later amendments, and the UNESCO Universal Declaration of Human Rights. In addition, all the procedures performed in the study were approved by the Ethics Committee of the University of Valencia, Spain (Project identification code: H1456762885511).Scale of Peer Victimization at School ,47. ThisScale of School Aggression ,49. ThisScale of Victimization through the Cell Phone and Internet . The CYBScale of Aggression through the Cell phone and Internet . The CYBPrior to administration, the definitions of bullying and cyberbullying were provided for all scales, and adolescents responded with this type of behavior in mind. In addition, on these scales, the adolescents were asked about the duration of the episodes and the frequency and persistence of bullying and cyberbullying.2) value is used as an indicator of the size of the effect. Cohen (1988) suggested that η2 ≤ 0.06 can be considered a ‘small’ effect size, 0.07 ≤ η2 ≤ 0.14 represents a ‘medium’ effect size, and >0.14 is a ‘large’ effect size [Data analysis was carried out using the SPSS statistical package . To evaluate the effects of the program on each of the study variables, several 2 x 2 mixed factorial ANOVAs were used, with a between-subjects factor  and a within-subjects factor (before and after the program: pre-test and post-test). The use of this analysis is recommended when the groups selected are natural and not equal in the initial situation . The intect size .F = 6.67, p < 0.01, with a medium effect size, η2 = 0.09. As F = 7.80, p < 0.01, with a medium effect size, η2 = 0.10; victimization at post-test was lower than at pre-test, especially in the experimental group.Regarding bullying, a significant group x time interaction effect was found p < 0.01, with a small effect size η2 = 0.05. Findings indicated that cyberbullying remained stable in the control group, whereas it decreased in the experimental group  = 7.03, roup see . A signiThe main objective of this study was to experimentally assess the effects of the Prev@cib Program. Specifically, the short-term impact of the Prev@cib Program was shown on bullying and cyberbullying perpetration and victimization among adolescents.The Prev@cib program is based on three theories that support the contents of the program. This theoretical framework provides a solid and rigorous basis for this novel and necessary proposal in this area of research. Thus, the Prev@cib program is based on the ecological model  because The findings emphasize the effectiveness of the Prev@cib intervention program for both bullying and cyberbullying. Specifically, in the experimental group, a reduction was observed in the involvement in bullying and cyberbullying as aggressors and victims, compared to the control group. This decrease in bullying and cyberbullying in the experimental group could be explained by the variety and suitability of the contents. The positive results of Prev@cib are consistent with other programs that have also shown their experimental effectiveness ,28,37. Consequently, all the hypotheses proposed in our study were confirmed. Regarding the hypotheses related to “face to face” bullying, other programs also obtained positive effects in reducing victimization and perpetration of this type of violence, for example, the Olweus Bullying Prevention Program  or the VIn addition, the Prev@cib Program significantly reduced school victimization. The implications of these positive results are important for the victims of school bullying, who usually experience feelings of anxiety, depression, psycho-somatizations, suicidal ideation, and problems in school as a result of the continued abuse ,56. ThesMoreover, other main objectives of the Prev@cib program related to the last two study hypotheses also showed effective results in reducing cyberbullying. Whereas in the intervention group, cyberbullying decreased in the post-test phase, in the control group, these behaviors did not decline, and instead remained constant over time. These results are congruent with those from other programs that obtained positive effects on reducing cyberaggression, such as The Brief Internet Cyberbullying Prevention Program  or TabbyIn the case of cybervictimization, the results of the Prev@cib program also confirmed the hypothesis of a decline in cybervictimization in the intervention group, compared to their baseline and the control group. Thus, whereas cybervictimization decreased in the intervention group, it increased in the control group. Along these lines, other programs such as the Cyber Friendly Schools Project  or Surf-In sum, the Prev@cib program has been shown to have positive effects on reducing bullying and cyberbullying, and also aggression and victimization. However, the effect size of the program is smaller for cyberbullying than bullying. This result is consistent with those obtained by different authors . It has The results support the idea that adolescents involved in traditional bullying are also usually involved in cyberbullying ,68. BaseThis study has some limitations that should be taken into account when interpreting the conclusions of this study. The first limitation is related to the representativity of the sample. Although the sample of participants is large because it is a classroom intervention, the generalization of the results to the adolescent population must be carried out with caution. Future studies could implement the Prev@cib program in other samples of adolescents from other countries. A longitudinal study should also be carried out to test the stability of the long-term changes observed in the intervention group. It would also be interesting to include other variables, such as school climate, to observe how it changes during the program. In this regard, some authors suggested that cyberbullying victims do not perceive the teacher as a source of authority who helps to solve their bullying problems with peers ,58. ThisIn spite of the limitations, this study provides a novel program to prevent bullying and cyberbullying in adolescence, based on scientific evidence. Prev@cib is a theoretically-based program that has been shown to have positive effects on reducing bullying and cyberbullying perpetration and victimization.This study presents the experimental validation of the effects of the Prev@cib program, which has the objective of preventing and reducing bullying and cyberbullying among adolescents. Specifically, this program is based on three theoretical frameworks: the ecological model, empowerment theory, and the personal and social responsibility model. Regarding the contents, the Prev@cib program consists of ten sessions distributed in three modules: (1) Information; (2) Awareness and sensitization; and (3) Involvement and commitment. To evaluate the effectiveness of the Prev@cib program, a quasi-experimental repeated-measures pre-test and post-test design was used with an experimental group and a control group. The results of the present study showed the efficacy of the Prev@cib program. The program had positive effects on reducing bullying in the participants. Specifically, the findings show that in the experimental group, compared to the control group, school perpetration and victimization behaviors declined significantly. These positive effects were also observed for cyberbullying in the experimental group.In summary, our results present scientific evidence that the Prev@cib program is effective in reducing and preventing bullying and cyberbullying in the adolescent population.