Purpose: To describe the development and implementation of a smartphone application (app) designed to promote physical activity and reduce screen-time in adolescent boys considered “at-risk” of obesity.Methods: An app was developed to support the delivery of a face-to-face school-based obesity prevention program known as the “Active Teen Leaders Avoiding Screen-time” (ATLAS) program. ATLAS was guided by self-determination theory and social cognitive theory and evaluated using a cluster randomized controlled trial with 361 boys (12.7 ± 0.5 years) in 14 secondary schools. Following the completion of the study, participants in the intervention group completed a process evaluation questionnaire and focus groups were conducted with 42 students to explore their general perceptions of the ATLAS program and their experience with the smartphone app. Barriers and challenges encountered in the development, implementation, and evaluation of the app are also described.Results: Participation in the study was not contingent on ownership of a smartphone, but 70% of participants in the intervention group reported having access to a smartphone or tablet device. Focus group participants reported an enjoyment of the program, and felt that it had provided them with new skills, techniques, and routines for the future. However, their engagement with the smartphone app was limited, due to a variety of reasons. Barriers to the implementation and evaluation of the app included limited access to smartphone devices, technical problems with the push notifications, lack of access to usage data, and the challenges of maintaining participants’ interest in using the app.Conclusion: Although participants reported high levels of satisfaction with the ATLAS program in general, the smartphone app was not used extensively. Additional strategies and features may be needed to enhance engagement in adolescent boys. Physical inactivity has been described as a global pandemic . Recent Schools have been identified as ideal settings for physical activity promotion and obesity prevention, as they have access to the majority of youth, appropriate facilities, and qualified personnel to achieve these outcomes . NumerouMobile phone ownership is increasing at a rapid rate and recent data suggest that 77% of US adolescents  and 90% Therefore, the primary objective of this paper is to describe the development and implementation of a smartphone app designed to support the delivery of the Active Teen Leaders Avoiding Screen-time (ATLAS) obesity prevention program . A seconlowest to 10 = highest) was used to identify eligible schools. The SEIFA index is derived from multiple indicators of socioeconomic disadvantage within an area . Public secondary schools located in the Newcastle, Hunter, and Central Coast regions of NSW with a SEIFA index of ≤5 (lowest 50%) and an enrollment of at least 100 students in the targeted year group were considered eligible. Twenty-two eligible secondary schools were identified and 14 agreed to participate.Ethics approval for this study was obtained from the University of Newcastle, Australia and the New South Wales (NSW) Department of Education and Communities. School principals, teachers, parents, and study participants all provided informed written consent. The rationale, study protocol and intervention description have been reported previously . Briefly−2 and 1.5 cm in waist circumference. All male students in the targeted year group at the study schools completed a short screening questionnaire to assess their eligibility for inclusion in the study. The questionnaire aimed to identify those “at-risk” of obesity based on their physical activity and screen-time behaviors. Based on their responses, students failing to meet national physical activity or sedentary behavior guidelines  and waist circumference]. Assuming a drop-out rate of 20% by the primary endpoint, it was calculated that 350 participants  would be required to detect a between-group difference in BMI of 0.4 kg midelines  were conwalk whenever you can; (ii) get some vigorous physical activity on most days; (iii) reduce your recreational screen-time; and (iv) drink more water and less sugary drinks. Briefly, the school-based intervention involved the following components: teacher professional development, researcher-led seminars, enhanced school sport sessions, lunch-time physical activity mentoring sessions, provision of fitness equipment to schools, pedometers for self-monitoring, parental strategies to reduce screen-time, and a smartphone application (app) and website. To assist in facilitating the intervention as intended, participating teachers at the study schools attended two full-day professional development workshops (pre- and mid-program) designed and delivered by the research team. While the other intervention components have been described previously  pilot study, a successful trial conducted in four secondary schools in the Hunter region, NSW, Australia –25. A deeviously , a detaiA smartphone app was developed as a supplement to the intervention and was made available to participants on both iOS  and Android  platforms at no cost to participants Figure . A websiMy steps – participants were able to record their daily step counts measured using their personal pedometer which was provided by the research team. They could then review their “date-stamped” step count entries or select the graph view which allowed a visual representation  of their entries over time. The graph view could be converted to show entries over a daily, weekly, or monthly time scale.My workouts – during the school sport sessions participants were introduced to CrossFit-style fitness challenges (henceforth referred to as workouts), which involved a series of resistance training  and aerobic exercises  with a predetermined number of repetitions  , which are considered to be the foundation for more complex movements used in resistance training programs (y (RTSB) , 32 wereprograms –35. The My goals – the app/website allowed users to set and review goals related to physical activity and screen-time. This function enabled users to select either (a) the number of daily steps they would like to achieve; (b) the number of workouts per week they would like to complete; or (c) the amount of screen-time (in minutes) they would like to limit themselves to each day. The user could then select the date on which they would like the achievement of the goal to be reviewed. On the date selected by the user, a push notification was sent asking the user to verify achievement of the goal. Previously achieved goals were retained and displayed on the screen for user review.My motivation – this function was available on the app only. After the initial download of the app, users were asked to select two of four physical activity outcome expectations that were personally important to them, relating to (i) appearance , (ii) health and well-being , (iii) school performance , and (iv) social interaction . Based on their responses, informational and motivational messages developed in reference to SDT and SCT were sent twice weekly via push notifications through the app  and the motivational messages were based on the user’s initial responses to the motivation question. . As recommended in the literature, messages were simple and written in vernacular “text speak” to engage teenagers (eenagers .Never to 5 = 5 or more times). The post-program questionnaire included more detailed items regarding user enjoyment of the app/website (1 = Strongly disagree to 5 = Strongly agree) and frequency of use for each specific function (1 = Never to 4 = Often).Baseline and post-program assessments were conducted in November–December, 2012 and July–September, 2013, respectively. Trained research assistants completed data collection at the study schools. A process evaluation was conducted to determine participants’ usage of, and satisfaction with, the ATLAS app. Evaluation questionnaires were distributed to study participants at mid- and post-program periods. The mid-program questionnaire included items on the type of app/website usage  and the frequency of use  limit consumption of sugary drinks, (iii) participate in at least 60 min of MVPA each day, and (iv) participate in muscle strengthening physical activities on 2–3 days each week (1 = Strongly disagree to 5 = Strongly agree). To assist researchers interested in the use of smartphone apps for obesity prevention research, barriers and challenges encountered in the development, implementation, and evaluation of the app are described.Participants were also asked their behavioral intentions to (i) A series of focus groups were conducted to gain insights into participants’ experiences in and perceptions of, the ATLAS program. Consenting students took part in separate focus groups, each consisting of six participants. Each focus group included three participants who failed to meet MVPA guidelines and three participants who achieved MVPA guidelines (using baseline accelerometer data). These group meetings lasted between 42 and 58 min and were conducted in a separate classroom during school hours by a research team member who had not been directly involved in the delivery of the ATLAS program. The structured discussion framework was developed by the research team to facilitate discussion and reflection on the program. Specifically, the questions asked of the students were designed to explore their general perceptions of ATLAS and their experience with the ATLAS smartphone app. Views were also sought of the participants as to the perceived impact of the program on a range of attitudes and behaviors relating to physical activity and nutrition. Prompts were used as needed to explore topics in depth.The focus groups were digitally recorded with the participants’ consent and transcribed verbatim. A computer program (NVIVO 10) was used to assist with the organizational aspects of data analysis. Analysis was conducted by an independent qualitative researcher using a standard general inductive approach to qualitative analysis. Initially, inductively derived codes or labels were attached to the meaning units arising from the data. The developing hierarchical coding scheme was continually revised and further expanded after coding of additional transcripts. Following coding of all the transcripts, emerging themes were identified and elaborated. Due to the structured format of the discussion framework, these themes were closely aligned with the research aims. The following reports on these inductive analyses and explores the impact that the program has had on the lived experiences of the students taking part in the ATLAS program.Participants were 361 adolescent males (mean age = 12.7 ± 0.5 years) attending schools in low-income areas of NSW, Australia. The majority of boys  were born in Australia and most  reported speaking English at home. Ninety two percent of boys reported their cultural background as Australian or European. Furthermore, 13.5% of boys indicated they were of Indigenous descent . The sample was predominantly of low socioeconomic position with 91.4% of boys residing within areas with a SEIFA population decile ≤5 . Twenty-nine percent of boys resided in areas with a SEIFA population decile ≤2 .Participation in the study was not contingent on ownership of a smartphone, but 70% of participants in the intervention group reported having access to a smartphone or tablet device (including iPod Touch). At the mid-program evaluation, 49 and 15% of participants had used the iPhone and Android apps, respectively Table . At the After completing the program, almost half of the group agreed or strongly agreed that the push prompt messages reminded them to be more active, reduce their screen-time, and drink less sugary drink Table . Forty-fA total of 42 male students from year 8 participated in 7 focus groups. Each group consisted of students attending the ATLAS program from the same school. The thematic analysis revealed a range of emerging themes surrounding the participants’ general perceptions of the program, key messages, and ATLAS app, as well as clusters relating to the students’ perceptions and evaluations of the physical activity sessions, as well as relationships with teachers and peers. The overarching theme relating to the perceived impact of the ATLAS program contained a number of sub-themes representing the changes to behaviors, knowledge, and attitudes relating to school, diet, and physical activity which were felt to have followed on directly as a result of involvement in the ATLAS program.“I felt the ATLAS program opened a lot of opportunities in the future; taught me a lot of things that I would not really do and helped me find my physical peak”For the majority of the students, one of the most beneficial and important aspects of the program had been the learning of “how to do things right” and adding to their repertoire of techniques and activities which they could do with friends or by themselves. Many students, who reported engaging in various out of school sports, felt that the newly acquired skills, techniques, and fitness benefits arising from the program were highly transferable, such that they had gained an additional competitive edge. The particular techniques and activities most often referred to in this context were squats, lunges, and CrossFit.While a number of students had some suggestions for how the program could have been improved (mainly in terms of less repetitive activities and more variety), all expressed an enjoyment of the program, and felt that it had provided them with new skills, techniques, and routines for the future, while learning about the importance of reducing sedentary behavior, adopting a healthy diet, and limiting sugary drinks also generally having been received well by the students;“At the start of the program in the CrossFit challenges, I was really, really puffed by the end but then at the end of the program I was still getting puffed by them but nowhere near as much and I could run a lot further for a lot longer”while yet others  commented favorably on the social aspects of ATLAS;“… having a training partner, having someone beside you, to slap you across the back of the head and tell you to get up and stop being lazy.”Engaging in activities which were not usually part of the school curriculum was perceived as a special treat for some students who for instance had been doing boxing as part of their program. Not only did this present a welcome change from normal routine, but also appeared to have aided in feelings of empowerment and improved standing compared to students not involved in ATLAS.Another frequently mentioned positive aspect of the ATLAS program had been the sense of achievement gained from the evidential gradual improvement in fitness throughout the duration of the program, with many commenting on the enjoyment they had gained from the regular testing of their performance against oneself and their peers;Students had perceived a range of different key messages being conveyed by the ATLAS program. However, the most frequently mentioned related to the importance of reducing sedentary behavior and in particular screen-time, and reducing the consumption of sugary drinks while increasing water intake. This was closely followed by the importance of staying fit while increasing general physical activity and increasing incidental or opportunistic exercise . While many students had taken away several key messages, these four main areas accounted for over 80% of individual comments made.Other less frequently mentioned key messages were the importance of attending to a healthy diet, with this mostly being associated with reducing overall caloric intake and fat, and the significance of learning and employing the correct technique over sheer strength. Finally, only one student had taken away from the program quite a profound message alluding to the importance of individual capacity and achievement.“It’s all about going at your own pace and achieving your own goals.”The reception of the ATLAS smartphone app was somewhat mixed. While approximately 80% of the students participating in the focus groups reported owning a smartphone or iPad, approximately 60% reported having downloaded the ATLAS app. Of those who had not done so, the reasons given were mostly that they had forgotten, were not aware of it, or had neglected to download it due to issues or problems with their device. Of “non-smartphone owners,” only a few students reported having used the Web app. This was exclusively accessed on home PC, and the use of it was in most instances limited to a single viewing.Of the remaining students, over half reported short-term, once-only or very occasional use of the app, while the remainder (approximately eight students) had used it quite frequently . Three students particularly commented that their little usage of the app was due to being unsure how to use it.In terms of the utility of the specific functions within the app, the My workouts, My steps, and My goals functions were the most frequently used. While the feedback relating to the My workouts function was mostly positive, being described as challenging and enjoyable, a few students had felt it had been boring and repetitive. The My steps function was also a high-use function, but mostly only short-term (limited by accessibility to pedometers), with some reporting simply forgetting about it. However, one student had particularly liked the graphing function to visualize his own performance while, for others, the My steps function had increased their awareness of physical activity or lack thereof. Generally, the use of pedometers was erratic and short-term.The My goals function had received moderate use and reports were generally good . Only one student had used my technique function, and had found it very useful. The function which certainly received the most critical feedback was My motivation, which almost exclusively had been considered a nuisance by students. Mostly, the messages had been considered too frequent, too repetitive, or received at inappropriate times  and therefore not perceived to fit in with the rhythm of their day. However, one student had found self-programed messages very useful as reminders to engage in physical activity.“My goal was just to get fitter be able to get a place in cross country which I had never done. Well, mostly I’d come 10th. But after the ATLAS program, I actually came 3rd or 4th, so I finally got into zone”followed by enhanced self-confidence, including higher expectations of oneself, and feelings of mental stamina;“Before the ATLAS program, I underestimated myself and set my goals pretty low, but during I set them a lot higher and felt I could reach them a lot more easily”Yet others, who reported having reached their goals, had entered the program with the expectation of becoming more physically active, improving their knowledge of health and nutrition, achieving weight loss, achieving a general improvement in their physical or mental strength, or simply, as one student put it, perform to the “best of [his] ability.”The vast majority of students taking part in the focus groups reported having successfully reached the goals which they had set for themselves at the outset of their participation in ATLAS. The most frequently mentioned of these goal accomplishments related to having achieved increased fitness levels including reaching sporting goals;Of the seven students who reported not having reached their goals, four had not set any specific goals at the outset of the program, while two felt they may have reached their goals had the program continued, while one student, very introspectively, noted that while he had failed to reach his goal of a certain number of steps per day, he had learnt the importance of realistic and progressive goal setting.“Yeah it has [changed my attitude to sugary drinks] because after seeing the stuff they showed us about it. It’s just like terrible all the caffeine in like Monsters and all the energy drinks and that, so I’m just sticking with water now.”Of the remainder of the students, who did not perceive any changes to their diets, most reported already adhering to healthy balanced diets, containing little junk foods, which not surprisingly appeared to stem from healthy family dietary routines. A similar pattern was observed in the students’ attitude toward sugary drinks. While five students reported no changes to their consumption of sugary drinks, three of these indicated that such drinks had not been part of their diet in the first place. The remainder of students described changes to their knowledge and behavior relating to the consumption of sugary drinks, with most having cut down their consumption, and some having either switched to sugar-free soft drinks, or cut out sugary drinks from their diet altogether and as a result increased their water consumption, with one student commenting on the positive effects it has had on his energy levels;“I like to drink water and [it has] sort of helped me keep going outside, whereas before I [would] get tired and go inside and sit down but now, because I don’t drink as much soft drink and that, I can sort of stay outside for a bit longer”In terms of dietary changes resulting from participation in the ATLAS program, a little over half of the students reported changes to their dietary habits as a direct result of what they had learnt in the ATLAS program. This had taken the form of attempts to purchase and consume healthier foods (less junk foods), reduce amount of food eaten, eating more of the healthier foods served up at home, healthier snacking options and, most commonly, increased fruit intake. There was clear evidence that students had increased their awareness of healthy nutrition, leading to a “think before you buy” approach and a conscious decision to improve long-term health outcomes;“I used practically every afternoon be on my Xbox just playing video games and when the ATLAS program started like now I like practically out every afternoon shooting hoops with my brother and all of that, doing sport and kicking a ball and everything.”Not surprisingly, there was strong evidence that increased motivation was one of the key factors behind their behavior changes. This motivation appeared to stem from greater enjoyment in physical activity, a more serious approach to fitness, as well as greater knowledge and skill. Indeed, quite a few students talked about the ATLAS program having equipped them with skills and techniques to improve their sporting performance and stamina;“… with surfing it’s helped, like I got heaps more arm strength now or paddling power, like I’d paddle for like 2 h and I’d be tired. Now I can paddle like the entire day and I’m fine.”Another of the more profound impacts of the ATLAS program were changes to students’ routines. While some had made just minor changes to everyday routines, such as running to school bus instead of walking, some had adopted an impressive daily fitness routine;“Well, every time I used to walk home and I used to go for a jog but now I do a little bit more extra; like I’d go for a jog and come home and we’ve got this tree out the back and its kind of like a chin up pole and I’d do chin ups and before I’d go to bed, I do about 50 sit ups.”The discussions around the students’ attitude and behaviors relating to physical activity provided strong evidence of the profound impact that the program had exerted, not only on actual behavior, but also on the cognitions accompanying the choices which the students make. The vast majority reported having replaced sedentary behaviors (mainly some form of screen-time) with physically active behaviors such as outside play or intentional fitness activities such as jogging, bike rides, chin-up’s, push-up’s, etc. In many instances, the students talked about these changes having occurred in personal realms as well as social contexts, such that the increased physical activity had extended to friendship circles and family members as well;As described previously, the ATLAS app was developed to support the delivery of a school-based obesity prevention program for adolescent boys. However, due to the timing of school terms and the conditions of funding, we were unable to conduct a usability study of the ATLAS app prior to the RCT. Consequently, the app was launched and was made available to participants before we were able to rectify minor technical glitches. More specifically, in the original version of the app, the tailored motivational messaging function did not send the push prompts to the participants’ phones. The function was subsequently fixed by the technical team and participants were encouraged to update their app to access this feature, but this did not occur until 5-weeks into the intervention period.Hypertext Preprocessor and hosted in a data center in India. It included a distributed architecture model traditionally used in standard n-tier web applications, in that the client layer, business, and data access layer, and data layer all reside in different locations. Platform decisions were solely based on the two most dominant market shares at the time of development. As shown in Figure My steps, My workouts, My technique, My goals, and My motivation).The diversity of the ATLAS platform and device servicing  was designed to provide greater access for users, but came at the cost of higher maintenance and data dispersion issues Figure . The webThe primary objective was to describe the development and implementation of the ATLAS smartphone app designed to promote physical activity and reduce screen-time in adolescent boys attending schools in low-income communities. Although we were unable to collect objective usage data, the majority of participants reported having access to a smartphone device and utilized the ATLAS app functions to some extent. The focus group findings indicated that the participants benefited from the ATLAS program in general, but did not engage extensively with the smartphone app. Lack of engagement may in part be due to the technical glitches experienced by the research team.To our knowledge, ATLAS is the first smartphone app designed to supplement an obesity prevention program for adolescent boys. The app included five major features, guided by behavioral theory to promote physical activity and reduce sedentary behavior and the consumption of sugary drinks. A unique aspect of the ATLAS smartphone app was that it included push prompt messages , based on information entered by participants. After completing the program, almost half of the participants agreed or strongly agreed that the push prompt messages reminded them to be more active, reduce their screen-time, and drink less sugary drinks. Interestingly, the messaging was considered a nuisance by many students in the focus groups. However, it is possible that messaging still had its desired effect, as participants’ intentions to adhere to the ATLAS behavioral messages were high at the completion of the study. The content of the push prompt messages used in the ATLAS intervention was guided by the Nutrition and Enjoyable Activity for Teen Girls intervention , 12, 37.Due to the structure of the ATLAS architecture, we were not able to determine the degree to which participants engaged with the app or if they continued to use the app after the completion of the study. It is possible that the novelty of the app wore off quickly, as participants may have found more attractive mobile apps to use. In adults, self-monitoring behaviors diminish over the duration of an intervention . While tIn the current study, participants were provided with pedometers to self-monitor their physical activity. A recent systematic review concluded that pedometers could be used to increase physical activity in young people and highlighted the importance of individually tailored goals . AlthougOver two-thirds of participants in the intervention group reported access to a smartphone or tablet. Although access is not equivalent to ownership, there is a growing trend in the ownership of smartphone devices in youth populations . To cateActive Teen Leaders Avoiding Screen-time is the first obesity prevention program targeting adolescent boys to be supplemented with a purpose built smartphone app. Despite these strengths, there are some limitations to the current study. First, it was not possible to determine the unique contribution of the app to behavior change, as it was one component of a multi-component school-based intervention. Second, due to the original software architecture we were not able to access participants’ usage data. Alternatively, participants self-reported their use of the app features, which introduces self-report bias. Third, our study was conducted in a sample of adolescent boys attending schools in low-income communities and therefore our findings cannot be generalized to other populations. Finally, the timing of the school-based intervention prevented us from conducting a usability study before implementation and minor technical problems were experienced.In this study, we have described the development and implementation of a smartphone app designed to supplement a school-based obesity prevention program for adolescent boys. The majority of participants reported having access to a smartphone or tablet and many engaged with the ATLAS app features. Participants reported moderate satisfaction with the app, but were more positive of the intervention in general. Findings from our focus groups suggest that additional training on how to use the app may be necessary to improve usage in future studies. In addition, the technical glitches experienced by the research team highlight the importance of allowing sufficient time to conduct a usability study before conducting a full-scale RCT.Although eHealth interventions hold promise for behavior change in youth, it is unlikely that they will provide the “silver bullet” to the global physical activity pandemic. Physical activity is a complex behavior that can take place in a wide variety of settings and is influenced by various psychological, social, and environmental factors. Future studies are encouraged to explore the utility of technology-based intervention strategies, such as smartphone apps, to determine if they are appropriate stand-alone strategies or adjuncts to face-to-face behavior change interventions.David R. Lubans and Philip J. Morgan obtained funding for the research. All authors contributed to developing the protocols and reviewing, editing, and approving the final version of the paper. David R. Lubans, Philip J. Morgan, and Jordan J. Smith developed the intervention materials. All authors have read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Clinicians need to be supported by universities to use credible and defensible assessment practices during student placements. Web-based delivery of clinical education in student assessment offers professional development regardless of the geographical location of placement sites.This paper explores the potential for a video-based constructivist Web-based program to support site supervisors in their assessments of student dietitians during clinical placements.This project was undertaken as design-based research in two stages. Stage 1 describes the research consultation, development of the prototype, and formative feedback. In Stage 2, the program was pilot-tested and evaluated by a purposeful sample of nine clinical supervisors. Data generated as a result of user participation during the pilot test is reported. Users’ experiences with the program were also explored via interviews . The interviews were transcribed verbatim and thematic analysis conducted from a pedagogical perspective using van Manen’s highlighting approach.This research succeeded in developing a Web-based program, “Feed our Future”, that increased supervisors’ confidence with their competency-based assessments of students on clinical placements. Three pedagogical themes emerged: constructivist design supports transformative Web-based learning; videos make abstract concepts tangible; and accessibility, usability, and pedagogy are interdependent.Web-based programs, such as Feed our Future, offer a viable means for universities to support clinical supervisors in their assessment practices during clinical placements. A design-based research approach offers a practical process for such Web-based tool development, highlighting pedagogical barriers for planning purposes. Within the dietetics profession, students are required to complete 20 weeks of placement, with half of that time spent in developing and demonstrating competence in individual case management . The assWeb-based delivery of education to support clinical supervisors has been successfully used by the professions of medicine, nursing, and physiotherapy -9. The WWhen developing a Web-based learning program, both the discipline-specific content and the learning process need to be considered. Constructivist pedagogy, in which learners construct their own meaning by forming connections through collaboration and reflection between their prior knowledge and new experiences , has been recommended for Web-based delivery ,16. CollPrograms to educate supervisors in the use of more credible and defensible assessment practices are currently non-existent. This paper explores the potential for a Web- and video-based constructivist tool to support clinical supervisors to use credible and defensible assessment practices during clinical placements. The program aims to use authentic video-based learning material and metacognitive activities such as self-monitoring and reflection to support clinical supervisors to transform their assessment practices. The study also considers the interdependence between pedagogy, usability, and accessibility.The Web-based program “Feed our Future” was developed using a design-based research approach adapted from Wang and Hannifin . This apIn October 2012, research consultation and initial development of the program commenced concurrently.Research presented in the publication, “Credible and defensible assessment of entry-level clinical competence: Insights from a modified Delphi study” , informeAn interview with Professor Sue Ash, a member of the original taskforce that developed the dietetic competency standards in 1994 , and parEvidence suggests that resources to support assessments such as visual representation of entry-level performance may increase the consistency of supervisor assessments . As an oInformation technology (IT) expertise from an academic was sought to select an appropriate delivery platform. Consideration was given to budget and timeline, security, usability, incorporation of different file types, with particular considerations of video recordings, and capacity to provide feedback to participants on their learning.The first prototype of Feed our Future was completed within 8 months using the website builder WIX as the delivery platform. The planned learning outcomes for the program were for supervisors (1) to feel more confident in their approach to assessment, and (2) to use credible and defensible competency-based assessment practices. The program comprised four learning modules, each including questions to consider, problem-based learning and self-monitoring activities, key concepts, and suggested readings. A pre-program quiz, a post-program quiz, a discussion forum, and a practice capstone module were included.Feedback obtained during the Feed our Future program development included several sources. An advisory group comprised of industry, academic, student, consumer, and regulatory representation provided direction on the research and the development of the Web-based program. Potential end users trialed the prototype and provided feedback via a market stall/booth established at the Annual National Conference of the Dietitians Association of Australia (DAA) in May 2013. The DAA’s Board of Directors also reviewed the program.A purposeful sample of nine dietitians located in a variety of health care sites and involved in the University of Canberra’s clinical placement program was invited, via email, to participate in this study. These potential end-users were provided with access to the password-protected website and asked to pilot-test the program over a 4-week period. The Human Research Ethics Committee (HREC) of the University of Canberra approved the study protocol (12-209) that conformed to the provisions of the Declaration of Helsinki.Data generated as a result of user participation during the pilot test including participation rates and outcomes from the pre-test, discussion forum, multiple choice quiz, and the post-test, were reviewed. In the pre-test and post-test, participants were asked to (1) rate their level of confidence with assessing a student’s competence during his/her clinical placement using a 10-point scale , (2) rate a student’s performance as observed from a video recording (the method of assessment is described elsewhere ), and  and in the format of individual interviews, via telephone, for the remainder (n=3). Focus groups were chosen to make use of group dynamics to stimulate discussion in a secure environment . The focThe interview questions were developed by the first author in consultation with LW and MJ and covered (1) the overall experience of using the Feed Our Future program, (2) what they learned, (3) whether and in what way their thinking had been challenged, (4) whether it had prompted them to change the way they assessed students on their clinical placement, and (5) suggestions to improve the program. Users were also asked to describe their workplace and experience with supervising and assessing students up to the time of viewing the program.Recordings were audiotaped, transcribed verbatim by two researchers, and crosschecked for accuracy to maintain the integrity of user responses. Transcripts were analyzed independently by the primary researcher and one research assistant with themes highlighted using van Manen’s highlighting approach to thematic analysis . PedagogOf the nine users that pilot-tested Feed our Future, two were from rural and seven from urban locations, four worked in hospitals and five in community settings, five were experienced supervisors, two reported some experience, and two had little or no experience with supervising students.Data generated by participants after pilot-testing the program Feed our Future are presented in Although technical issues prevented some users from participating, the discussion forum was used for introductions and to share learning and reflections. The average score achieved from the multiple choice quiz by users was 86%. Technical issues delayed participants’ completion of the program and hence no results are available from the post-test.The analysis of interview transcripts revealed three pedagogical themes: (1) constructivist design supports transformative online learning, (2) videos make abstract concepts tangible, and (3) accessibility, usability, and pedagogy are interdependent.Although the post-test was not completed by users due to technical issues, qualitative feedback from the focus group and personal interviews showed an increase in user confidence as demonstrated by this exemplar quote:From doing this, I now feel like I would be able to confidently have a final clinical placement student.Focus Group User # 3The constructivist design assisted users to apply their learning as demonstrated by the exemplar quotes in We can use this process for moderation, if we have a number of different supervisors that watch a particular video, we could use it to make sure that our assessments are similar…Personal Interview User #9Through participation in the program, users achieved consensus in their understanding of entry-level performance.Users supported the use of video-based learning material:you can read about it, but actually seeing the videos of an assessment, and knowing where they sit on the scale [from novice to expert]…you know we always want to see stuff in action.Focus Group User #3They commented that prior to completing the program they had found the learning content “difficult to apply” and “frustrating at times”. The users found that the video representations of the authentic student-patient consultations allowed their understanding of “entry-level” competence to become more tangible.I really liked the videos that when, at the end of them would show the scale of where the students were, like from the beginning to the end.Focus Group Participant #2As demonstrated by IT access and capacity at some worksites limited engagement with the program:I’m computer literate but not really up-to-speed with some technological advances I suppose. I was a bit frustrated with some of those things…I suppose once I get annoyed with something I’m not inclined to go back.Personal Interview User #7This paper describes the development of the first research- and Web-based learning program to support clinical supervisors in their assessments of student dietitian competence during clinical placements. This case example demonstrates the value of a design-based research and consultative approach to developing a program. The use of a Web-based mode has the potential to disseminate expertise and research findings nationally, overcoming geographical and time boundaries, in the provision of continuing professional development to health practitioners who assess student performance.. The program encouraged independent self-paced learning and catered to different learning styles as recommended by Ng’ambi and Lombe [The results of the pilot test supported the pedagogical design of Feed our Futurend Lombe . Particind Lombe  achievednd Lombe  with theParticipants in the pilot test found the video recordings of student-client consultations to be helpful in learning about competency-assessment practices. Clinical vignettes in traditional face-to-face learning programs have been used to assist supervisors to gain a shared understanding of entry-level competence in physiotherapy . When usConsistent with the findings of Cook and Steinert , users aTechnical barriers experienced in the pilot-testing of Feed our Future such as IT incompatibilities between organizations’ infrastructure, software and Internet browsers, security restrictions, and bandwidth limitations are not unique . UniversFeed our Future, like many programs ,45, was The research-based design and national consultation used for the development of this program was robust. The sample size and the qualitative design of the pilot test and evaluation, although consistent with similar studies ,47, does, offer a viable solution for universities to provide professional development to geographically dispersed clinical supervisors in preparation for their students’ clinical placements. A design-based research approach offers a practical process for Web-based tool development.Web-based programs, such as Feed our Future


A surface-based approach to grouped icEEG analysis was used to overcome challenges from sparse electrode coverage within subjects and variable cortical anatomy across subjects. The topology of category-selectivity in bilateral VTC and LOC was assessed for five classes of visual stimuli—faces, animate non-face , places, tools, and words—using correlational and linear mixed effects analyses. In the LOC, selectivity for living (faces and animate non-face) and non-living (places and tools) classes was arranged in a ventral-to-dorsal axis along the LOS. In the VTC, selectivity for living and non-living stimuli was arranged in a latero-medial axis along the MFS. Written word-selectivity was reliably localized to the intersection of the left MFS and the occipito-temporal sulcus. These findings provide direct electrophysiological evidence for topological information structuring of functional representations within higher-order visual cortex.Neuroimaging studies suggest that category-selective regions in higher-order visual cortex are topologically organized around specific anatomical landmarks: the mid-fusiform sulcus (MFS) in the ventral temporal cortex (VTC) and lateral occipital sulcus (LOS) in the lateral occipital cortex (LOC). To derive precise structure-function maps from direct neural signals, we collected intracranial EEG (icEEG) recordings in a large human cohort ( Visual object recognition is a ubiquitous feature in our day-to-day lives, enabling us to recognize the faces of our loved ones, find a favorite snack in the grocery aisle, and even read the words on this page. Achieved with rapidity and accuracy, object recognition appears nearly effortless. Yet the apparent automaticity with which we perform this feat belies its underlying neural complexity, and damage to any part of the network of cortical regions involved may produce debilitating deficits—such as visual agnosias (e.g. face-blindness)—that can seriously affect social or vocational life , 2.Extensive human and non-human primate research has identified putative higher-order visual areas in the ventral temporal and lateral occipital cortical complexes , which are believed to mediate object recognition via the activity of distinct neuronal clusters that differentially and selectively activate to specific categories of visual stimuli  –18. HoweRecently, advances in functional, structural, and anatomical neuroimaging have begun to yield new insights into structure-function relationships of the VTC and LOC . SpecifiTaken together, these findings suggest that these anatomical landmarks—the MFS and LOS—may provide a structural framework for the organization of higher-order visual representations, in which opposing sides of these sulci contain neural hardware for processing distinct classes of visual information  . ImportaNotably, given the spatial constraints of the VTC and LOC , different functional maps (e.g. animacy and eccentricity bias) appear to be organized on the same spatial gradients around the MFS and LOS, respectively . HoweverWhile fMRI studies have made great strides towards understanding the organization of these visual areas, the spatio-temporal resolution and indirect nature of hemodynamic measures prevents a definitive assessment of their functional topography , 48. AltDespite recent work, a comprehensive icEEG investigation into the topology of VTC and LOC category-selectivity remains lacking (for review see ). This in = 26); using data collected during the visual naming of living  and non-living (tools and places) stimuli, as well as during a wordstem completion task.Recently, new methodological advances have introduced surface-based normalization strategies for grouping icEEG data , 71, 72,at the group level .If models of visual information structuring are accurate , we expeTo test this hypothesis, we generated topologically precise population-level maps of icEEG data , and dirn = 16) or right hemispheric  subdural electrode (SDE) implantation  undergoing left  were displayed at eye-level on a 15” LCD screen placed at 2 feet from the patient . Subjects were instructed to overtly name the stimuli during the experiment. Face stimuli consisted of gray-scale, real images of famous individuals shown in frontal view . Place stimuli consisted of color, real images of famous landmarks . Animate and tool stimuli were from the Snodgrass and Vanderwart object pictorial set . Word stFor each category, images were randomly selected from our database and never repeated, so each subject saw a unique sequence of images. All subjects in both right and left hemispheric cohorts participated in the visual naming tasks with pictorial stimuli. However, given the strong hemispheric bias associated with word reading , 76–78, Pre-implantation anatomical MRI scans were collected using a 3T whole-body MR scanner  equipped with a 16-channel SENSE head coil. Anatomical images were collected using magnetization-prepared 180-degree radio-frequency pulses and rapid gradient-echo (MP-RAGE) sequence, optimized for gray-white matter contrast, with 1 mm thick sagittal slices and an in-plane resolution of 0.938 x 0.938 mm , and impn = 2101; RH n = 1386) were implanted  using previously published techniques , 7960, 7We also sought to characterize category-selectivity onsets per SDE per individual. We note here that the millisecond temporal resolution afforded by ECoG allows for precise latency estimates . Using td’ (d-prime) sensitivity index was computed for each category per electrode . The d’ index is an established metric in signal detection used to determine how well a target can be discriminated from competing stimuli   –119. To d’ indices (FDR corrected q ≤ 0.01) for each category were visualized on the MNI N27 cortical surface , and color-coded by category-preference.Finally, to visually evaluate the spatial organization of SDE category-selectivity relative to anatomical landmarks (the MFS and LOS), SDEs with significant n = 16; RH n = 10) were analyzed to evaluate the relationship between category-selectivity and cortical topology in higher-level visual cortex. In total, 242 SDEs were evaluated , and 83 SDEs were localized to lateral occipital cortex .ECoG recordings of broadband gamma activity  from 26 subjects , organized with respect to the cortical topology, were consistently seen at the single subject level. However, the sparse sampling in each individual case precluded a comprehensive evaluation of these relationships at the single subject level, and surface-based normalization was performed to transform all SDE coordinates across subjects to a common brain space . In the VTC, a total of 69/94 SDEs (~73%) in the left hemisphere and 34/64 SDEs (~53%) in the right hemisphere had a significant d’ index (FDR corrected q ≤ 0.01) for at least one category  had a significant d’ index for a second category (both faces and places), all of which were localized in the left hemisphere to the respective sulci of interest (MFS or LOS).Of the 242 SDEs used in the analysis , a total of 142 SDEs (~59%) had a significant category , left. Icategory , right. d’ index and SDE coordinates , while controlling for non-independence of data within individuals, linear mixed effects (LME) models were generated for each stimulus category. We note that in the VTC, x and z coordinates were highly correlated . Therefore only the x and y coordinates were evaluated for the VTC (z coordinate was removed). Similarly, in the LOC, the x and y coordinates were highly correlated . Therefore only the y and z coordinates were evaluated in the LOC (x coordinate was removed). The exclusion of the z and x coordinates as predictors for VTC and LOC category selectivity, respectively, remains consistent with the anatomical principles governing structure-function hypotheses currently being tested .To robustly quantify the relationships between d’ indices and the spatially normalized SDE coordinates of interest  are available in the supporting information , were entered as fixed effects into the models. In the LOC, the fixed effects were entered as the y and z coordinates, and the interaction term (z*y). Given that multiple SDEs could be contributed from each individual, all models included random-effect variable intercepts for subjects to control for inter-subject variability. Complete model results for the VTC and LOC are provided in ormation  [ggplot2d’ index in the x-axis , a significant positive relationship with increasing selectivity in the y-axis , and a significant negative relationship between face-selectivity and the x*y interaction term . For place stimuli, we found a significant positive relationship with increasing selectivity in the x-axis , and a significant positive relationship between selectivity and the x*y interaction term . No significant associations were noted for tool- or animate-selectivity.In the right VTC, LME analysis was performed for 4 stimulus categories  using 64 SDEs . For facd’ index in the x-axis . For animate stimuli, a negative relationship was observed for increasing selectivity in the y-axis . For places, we found a negative relationship with increasing place-selectivity in the x-axis , and a positive relationship with increasing selectivity in the y-axis . For tools, we found a negative relationship with increasing selectivity in the x-axis , and a negative relationship with the y-axis . For words, a negative relationship was observed with increasing selectivity in the y-axis .In the left hemisphere VTC, LME analysis was performed for 4 stimulus categories  using 94 SDEs, and for 1 stimulus category (words) using 64 SDEs. For face stimuli, we found a significant positive relationship with an increasing d’ indices in the z-axis . For places, we found a significant positive relationship with increasing selectivity in the z-axis , a significant positive relationship with the y-axis , as well as a significant positive relationship with the y*z interaction term . No significant associations were noted for tool or word-selectivity.In the left LOC, LME analysis was performed for 4 stimulus categories  using 48 SDEs and for 1 stimulus category (words) using 26 SDEs . For botB = -0.0306, S.E. = 0.0134, p = .029; selectivity increases ventrally), and for places we found a significant positive relationship with increasing selectivity in the z-axis . No significant associations were noted for tool- or animate-selectivity.Finally, in the right LOC, LME analysis was performed for 4 stimulus categories  using 35 SDEs. For faces, we found a significant negative relationship with increasing selectivity in the z-axis , and color-coded by category preference (n = 3/3) and nearly all face-selective  SDEs were localized to or lateral to the mid-fusiform sulcus (MFS) in the VTC bilaterally. Similarly, all place-selective  and tool-selective SDEs  were localized to or medial to the MFS bilaterally. Additionally both tool-selective and word-selective (LH n = 6/6) SDEs were clustered along the anterior boundary of the mid-fusiform sulcus in the left VTC. In addition to tools, word-selective SDEs were also interspersed with anteriorly localized face- and animate-selective SDEs.To evaluate the spatial relationship of category-selective SDEs with respect to cortical folding patterns, all SDEs with significant eference . Notablyn = 8/8; RH n = 5/5) and animate-selective  SDEs were uniformly localized at or inferior to the LOS, while all place-selective  and tool-selective  SDEs were localized at or superior to the LOS. However, no discernable spatial arrangement of word-selective (LH n = 3) SDEs could be observed.In the LOC, bilaterally, a similar arrangement of category-selectivity with respect to the lateral occipital sulcus (LOS) was observed. All face-selective  demonstrated little to any change in BGA (i.e. were non-responsive), and all were localized at the boundaries of the VTC/LOC: at-or-anterior to the MFS in the VTC  and at-or-superior to the transverse occipital sulcus in the LOC . The remaining 71 SDEs were largely interspersed amongst category-selective SDEs, with one notable exception: in the VTC bilaterally, no non-selective SDEs were localized postero-lateral to the MFS, in regions of face-selectivity. In the remaining regions, d’ index values of non-selective SDEs were largely congruent with d’ indices of the surrounding category-selective SDEs, consistent with the gradients of category-selectivity observed in the LME analyses and scatterplots  onset latencies were: 158 (42) ms for (n = 5) face-selective SDEs; 191 (84) ms for (n = 2) tool-selective SDEs; 238 (81) ms for (n = 3) place-selective SDEs; and 305 (101) ms for (n = 3) animate-selective SDEs. In the right VTC, median (sd) onset latencies were: 163 (88) ms for (n = 2) tool-selective SDEs; 173 (35) ms for (n = 14) place-selective SDEs; and 203 (74) ms for (n = 17) face-selective SDEs.Systematic comparisons of onset latencies of category-selectivity , within n = 26; LH n = 16, RH n = 10), to provide a population-level electrophysiological evaluation of the topology of category-selectivity in higher-order visual cortex. We demonstrate a consistent spatial organization of category-selective regions with respect to specific anatomical landmarks in the ventral temporal and lateral occipital cortical complexes (VTC and LOC). Importantly, our findings advance prior work by demonstrating that the use of surface-based normalization strategies in grouped icEEG analyses preserves structure-function coupling in a common brain space. In doing so, we provide a method to circumvent the sparse-sampling problem that has constrained the broader application of icEEG to the study of cognitive function at the single subject level [We utilized a surface-based grouped icEEG analyses, combined across a large cohort  provides a consistent boundary for transitions in the selectivity between living (face and animate) and non-living (place and tool) stimuli: face and animate selective regions are constrained at or ventral to the LOS, while place and tool selective regions are constrained dorsally. Notably, face- and animate selective SDEs are interspersed on the ventral aspects of the LOC in a fashion consistent with prior fMRI studies that demonstrate alternating regions of face and limb-selectivity , 124. AdIn the VTC, the mid-fusiform sulcus (MFS) provides a consistent boundary for transitions in the selectivity between living (face and animate) and non-living (place and tool) stimuli: face and animate selective areas are constrained at or lateral to the MFS, while place and tool selective regions are constrained at or medial to the MFS. Furthermore, in the left VTC, the anterior aspect of the MFS predicts the location of word, animate, and tool selective responses, suggesting that the VTC may possess additional functional gradients along the postero-anterior anatomical axis. Notably, regions demonstrating word-selectivity are clustered around the intersection of the occipito-temporal sulcus (OTS) and the anterior MFS , consistcombined across many individuals. Such hypotheses propose that small-scale functional representations are nested together within larger-scale functional maps in higher-level visual cortex, facilitating object categorization by the visual system (and possibly other higher-order cognitive systems) by enabling the extraction of different levels of categorical detail at different spatial scales  [While the locations of VTC and LOC category-selectivity reported here are consistent with an extensive body of invasive and non-invasive neuroimaging studies , 128–138rmation) , 23. Thirmation) , 34, 36.rmation) .Notably, such a parallel network organization is independently supported by the result from our BGA time-series analyses, which revealed no significant regional differences in the emergence of category-selectivity across conditions (between ~150 and ~250 ms). The relative similarities in selectivity onset latencies both across categories within the VTC, as well as between the VTC and LOC, support the hypothesis that visual information is received and processed in these regions in a largely independent fashion , 141. Aln = 6; LH 3, RH 3) and constrained to the individual level. Our work here validates their findings in a larger population, extends the investigation to the LOC, and broadens the stimulus classification to include tools and words. The high spatial resolution of icEEG enabled us to confirm the boundaries of these higher-level visual regions via the consistent localization of non-responsive SDEs anterior to the MFS in the VTC and superior to the transverse occipital sulcus in the LOC. The finding that no non-selective SDEs are localized within postero-lateral VTC, bilaterally, supports prior reports on the highly selective nature of this region  [To date, evidence for hierarchical coding models has come almost exclusively from non-invasive neuroimaging studies. Although a recent electrophysiological study has also reported large-scale animacy distinctions along the MFS , the anao faces) , 144. Noo faces) . While tThe sparse-sampling problem has been a long-standing limitation of icEEG, to which the recent development of surface-based grouped techniques provides a viable and much-needed solution , 98, 122Three main limitations of this work are apparent to us. The first is that we include only subjects implanted with SDEs, which record from the gyral crowns, and may be biased against activity arising from sulcal sources. Notably, prior literature focusing on word-, limb-, and body-selectivity in the VTC has reported regions localized in or near the OTS , 146. ThA second limitation is the inconsistency in the low-level visual features of our stimuli , which provide a potential confound in our analysis. However, higher-level visual regions are known to be invariant to changes in low-level visual features, and to maintain visual selectivity across a large spectrum of visual information, including color , 147–154The third limitation is that our stimulus set does not allow us to unequivocally claim that the abstract semantic concept of “animacy” is the driving force behind the topological organization we observe. Notably, prior studies have argued that animacy distinctions in higher-order visual areas may simply be a by-product of shape similarities between stimuli of related categories (but see ) 156–1661. NeverThus, a final account of the functional topology within higher-order visual regions will likely need to account for both low-level visual features (e.g. shape) as well as influences from semantic or categorical dimensions , 163–165We provide a grouped icEEG investigation of VTC and LOC category-selectivity, and demonstrate unequivocal evidence for structure-function coupling through direct electrophysiological recordings in a large human cohort. Our findings support hypotheses of hierarchical information structuring in higher-level visual cortex, via the generation of large-scale functional maps (e.g. animacy) from nested functional representations consequent to this structure-function coupling.Surface-based strategies to icEEG analyses provide novel opportunities for researchers to pool ECoG datasets across centers. Given the relative rarity of icEEG data in many cortical regions of interest, the adoption of such collaborative strategies could provide an invaluable tool to greatly expand the relevant application of high spatiotemporal resolution icEEG to the study of higher-level cognitive function.S1 Datasetd’ indices for each of the 5 categories tested. The order of the categories in these variables is identical to the order of the listed in the “Categories” cell variable. Additionally, for each SDE, a “Pt_Coords_LH_VTC” matrix contains the SDE coordinates in group space . Finally, there is also a cell labeled “pt_dprime_final_shuf_LH_VTC” which contains all 10,000 shuffled d’ indices for each subject’s SDE. The use of cell format enables the number of SDE’s each subject contributed to be seen. The number of SDEs contained in each cell corresponds to the number of VTC SDEs for the LH cohort listed in S1 Dataset comprises a Matlab file (.mat) containing 6 variables. For the 94 VTC SDEs across the 16 subjects with left hemispheric coverage, there exists a distinct matrix for the BGA mean, BGA standard deviation, and (MAT)Click here for additional data file.S2 DatasetThe S2 dataset contains the identical matrices and cells as described in for the (MAT)Click here for additional data file.S3 DatasetThe S3 dataset contains the identical matrices and cells as described in for the (MAT)Click here for additional data file.S1 Figd’ indices for each category plotted vs. subdural electrode (SDE) coordinates  per hemisphere in each region. In the ventral temporal cortex , comparisons were made against the x and y coordinates. In the lateral occipital cortex , comparisons were made with the z and y coordinates. For each plot, regression lines were fitted (color-coded by category), and the strengths of association were estimated using Spearman correlations . Spearman correlations were selected (over Pearson’s) for their robustness to outlier influence and smaller sample sizes. Furthermore, Spearman’s correlations test for monotonic relationships, and the relationships between d’ indices and SDE coordinates are not known a priori to be linear.Scatterplots depict grouped (TIF)Click here for additional data file.S2 FigBox plots depict median onset latency of category-selectivity in the left (LH) and right (RH) hemisphere lateral occipital cortex (LOC) and ventral temporal cortex (VTC), for the five categories of interest: words (cyan), tools (green), places (blue), faces (red) and non-face animate  stimuli. Timing of the onset of selectivity was evaluated for each category-selectivity SDE per subject, and determined using pairwise comparisons in broadband gamma activity time-series, for each category against all others. No significant differences between categories (following corrections for multiple comparisons) were noted, although low sample sizes likely underpowered these contrasts. Word stimuli were not tested in the right hemisphere, and in the RH VTC, no significant animate SDEs were observed.(TIF)Click here for additional data file.S3 Figd’ index for that electrode (matched to image legends). SDE diameter reflects the magnitude of the d’ value for that category, scaled by the largest d’ value across categories per region . Compass points denote SDE coordinates  and direction. Notably, in the postero-lateral aspects of bilateral ventral temporal cortex, no non-significant SDEs are observed.Non category-selective subdural electrodes (SDEs) are visualized on the MNI N27 template brain  after surface based normalization. SDEs are color-coded by the category with the largest (TIF)Click here for additional data file.


The FIFA 11+ is a simple, and easy to implement, sports injury prevention program comprising a warm up of 10 conditioning exercises. The aim of this systematic review was to evaluate the impact of the FIFA 11+ on injury incidence, compliance and cost effectiveness when implemented among football players. MEDLINE, EMBASE and Scopus databases were searched using the search terms “FIFA 11+”, “football”, “soccer”, “injury prevention”, and “The 11”. The titles and abstracts were screened by two independent reviewers and the data were filtered by one reviewer using a standardized extraction form and thereafter checked by another one. The risk of bias and the methodological quality of the studies were evaluated through the PEDro score and Critical Appraisal Skills Programme (CASP). A total of 911 studies were identified, of which 12 met the inclusion criteria of the review. The FIFA 11+ has demonstrated how a simple exercise program completed as part of warm-up can decrease the incidence of injuries in amateur football players. In general, considerable reductions in the number of injured players, ranging between 30% and 70%, have been observed among the teams that implemented the FIFA 11+. In addition, players with high compliance to the FIFA 11+ program had an estimated risk reduction of all injuries by 35% and show significant improvements in components of neuromuscular and motor performance when participating in structured warm-up sessions at least 1.5 times/week. Most studies had high methodological quality and a low risk of bias. Given the large number of people who play football at amateur level and the detrimental impact of sports injuries on a personal and societal level, the FIFA 11+ can be considered as a fundamental tool to minimize the risks of participation in a sport with substantial health benefits. Football is by far the most popular sport played worldwide. Recent estimates of the International Federation of Football Associations  suggest that the number of people playing football is close to 270 million . Like moThe financial loss due to football injuries in the professional English football leagues was estimated to be approximately 118 million euros during the 1999–2000 season . Junge aet al. [A recent review of the literature revealed that the incidence of injury during football games tended to increase with age across all age groups, with an average incidence of 15 to 20 injuries per 1000 hours of match-play among players older than 15 years . Most inet al.  conducteet al. . Thus, wet al. ,9, it isMultiple modifiable and non-modifiable factors interact to determine injury risk ,11. Yet,One such structured program is the FIFA 11+ injury prevention training program (FIFA 11+), which was developed in cooperation with national and international experts under the leadership of the FIFA Medical and Research Centre (F-MARC), to reduce the incidence of football injuries ,14. The The main aim of this systematic review was to evaluate the impact of the FIFA 11+ on injury risk, and performance in football players. We also evaluated studies examining the economic impact of the program, factors related to the delivery of the program and the influence of compliance.http://www.prisma-statement.org/). Systematic search in electronic databases which were applied by two authors independently. Databases of MEDLINE (via OvidSP) EMBASE (via OvidSP), and Scopus (via ScienceDirect) were searched combining the search terms: “FIFA 11+”, “football”, “soccer”, “injury prevention” and “The 11”. In addition, the reference lists of each publication identified was carefully checked in order to identify additional records. One author (JFME) conducted a search in relevant journals . Furthermore, we only included studies published since 2006 because this is the year in which the program “FIFA 11+” was launched by FIFA with support of the Oslo Sports Trauma and Research Center (OSTRC) and the Santa Monica Orthopaedic and Sports Medicine Research Foundation. No language restrictions were applied. The full search strategies and results for each database can be found in This systematic review incorporates the PRISMA statement  studies involving sports other than football; (ii) studies that implemented the 11+ but measured other outcomes than those considered in this systematic review; (iii) case reports; (iv) reviews and editorials. Data extraction involved geographic location; study participants, study design, outcome measures and results, according to the PICO acronym, as displayed in et al. [The methodological quality of the randomized controlled trials was assessed using the Physiotherapy Evidence Database scale; a score of 5 of 10 was set as the minimum score for inclusion in the review .On the oet al.  the onlyA total of 12 studies implemented in ten different countries were finally included. Approximately half of these studies were conducted in Europe ,27,28,29The outcome measures of the different studies differed substantially. The majority of studies assessed the impact of the FIFA 11+ on injury incidence ,28,30,31The FIFA 11+ leads to significant improvements in thigh muscle strength, jump height, and sprint speed and in a number of measures of balance and proprioception in amateur footballers  22,23,2,31,33,34° and 60° knee flexion and a significant 10.9% improvement in static balance were observed in the intervention group of one FIFA 11+ study [et al. reported a significant 2.8% improvement in time to stabilization—a measure of dynamic balance. Core stability, which may influence lower extremity biomechanics and in turn anterior cruciate ligament risk during rapid changes of direction [A significant decrease in dominant leg proprioceptive error from 2.8% to 1.7% at 451+ study . Impelliirection ,36, was irection .et al. reported statistically significant pre-post warm-up improvements in a number of performance variables, including sprint speed, agility, jump performance and balance.While the evaluation of strength adaptations in specific muscle groups has been confined to isokinetic testing of hamstrings and quadriceps peak torque or peak torque ratios, increases in fluorodeoxyglucose accumulation in the rectus abdominus, erector spinae, gluteus medius and minimus were reported following the FIFA 11+ indicative of significant activation of these trunk and hip muscles by the program. One of the few studies to have examined the acute effects of the program, Bizzini et al., found that delivery of the program by coaches who had been educated during an extensive preseason workshop was associated with greater team adherence to the program compared to its unsupervised delivery [Soligard et al.  reporteddelivery .The efficacy of the majority of the FIFA 11+ studies has demonstrated how a simple to implement, exercise-based warm-up program can decrease the incidence of injuries in both male and female amateur football players. In general, teams that implemented the FIFA 11+ had between 30% and 70% fewer injured players ,27,31. Iet al. reported that a neuromuscular warm-up program comprised of 6 lower body and trunk conditioning exercises and jump-landing exercises significantly reduced the incidence of anterior cruciate ligament (ACL) injury in female adolescent football players, while a number of other randomized controlled intervention studies also demonstrated that prevention programs targeting football players can reduce the incidence of injuries [The efficacy of the FIFA 11+ in decreasing lower extremity injuries concurs with findings in other prevention programs delivered as a warm-up. In a randomized trial among 4.564 Swedish players aged 12 to 17 years, Waldén injuries ,39,40,41et al. may relate to the low compliance in the intervention group [et al. was likely due to the too low overall frequency of training sessions [Of the studies included in the present systematic review, four reported that implementing the FIFA 11+ resulted in a statistically significant reduction in the risk of injury ,19,28,32sessions . Discrepsessions ,44,45,46Nonetheless, while the FIFA 11+ appears to be a useful and effective overall injury risk reduction program at the amateur level, additional loading progressions (volume/intensity) or a greater emphasis on exercises that address specific risk factors may be necessary to produce a significant reduction in injury incidence in higher level players with greater baseline neuromuscular performance. The relative importance of components of the FIFA 11+ are also likely to vary according to player characteristics, in terms of their neuromuscular and biomechanical profile and characteristics such as gender, age and previous injury.The correct implementation of the FIFA11+ and whether there was direct qualified supervision or not may depend on who conducts the program and the initial training they received. More studies are warranted to further evaluate factors associated with compliance and compare injury prevention and performance of the FIFA 11+ when it is led by qualified coaches compared to other professionals such as strength coaches, sport coaches, team captains, physical therapists, and physiotherapists, ,30,47 orMore than 5000 coaches from approximately forty countries have been taught on how to implement the FIFA 11+ until the present moment . During It is a challenge to convince the coaches of all FIFA member associations to implement the FIFA 11+ and to evaluate its results. However, the experiences of the nationwide implementation of the FIFA 11 in Switzerland are very encouraging, showing how an injury prevention program could be successfully implemented by football coaches with beneficial personal and societal outcomes .The current evidence suggests that the FIFA 11+ exercise-based warm-up programs can both decrease the incidence of injuries in male and female amateur football players and also improve motor/neuromuscular performance. Evidence of these improvements in performance are important in “marketing” the program to coaches, players and clubs since injury may be seen as a random event . SimilarGiven the large number of people who play football, the FIFA 11+ and its associated materials could be considered a fundamental public health intervention. The program may have a significant impact in terms of minimizing the potential negative consequences such as direct and indirect healthcare costs and education and productivity time loss ,9. Final


GUS to identify relevant thresholds for known therapeutic decision levels (ISBCR-ABL1/ABL1  = 10% and 0.1%). We then defined the most relevant cut-offs for early molecular response markers  using GUS or ABL1. We demonstrated that, although both control genes could be used  to accurately assess early molecular response, the BCR-ABL1/GUS level at diagnosis is impacted by the higher GUS copy number over-expressed in CML cells, thus negatively impacting its ability to completely replace ABL1 at diagnosis. Furthermore, we pointed out, for the first time, that it would be helpful to monitor BCR-ABL1 levels at an earlier time point than that currently performed, in order to assess response to first-line tyrosine-kinase inhibitors and consider a potential switch of therapy as early as possible. We evaluated this optimal time point as being 19 days after the start of treatment in our cohort.Recent studies demonstrate that early molecular response to tyrosine-kinase inhibitors is strongly predictive of outcome in chronic myeloid leukemia patients and that early response landmarks may identify patients at higher risk for transformation who would benefit from an early switch to second-line therapy. In this study, we evaluated the ability of the control gene  ISBCR-ABL1 levels at 3 and 6 months on Imatinib were significantly correlated with 8-year progression-free survival (PFS) and OS ISBCR-ABL1 levels of 10% at 3 months and 1% at 6 months as clinically important thresholds correlated with 5-year PFS and OS The European Leukemia Network (ELN) recommendations for the management of chronic myeloid leukemia (CML) patients define optimal response, warning or failure according to cytogenetic and/or molecular criteria obtained at 3, 6 and 12 months on tyrosine-kinase inhibitors (TKI) therapy 4.5] and beyond) Is was also demonstrated that EMR at 3 and 6 months correlates with future major molecular response (MMR) and deep molecular response  when quantifying the BCR-ABL1 transcript. This CG was selected by a Europe Against Cancer (EAC) study group BCR-ABL1 transcript levels. Indeed the location of ABL1 primers leads to the simultaneous amplification of the non-translocated allele of ABL1 and the fusion gene BCR-ABL1, then quantifying total-ABL1  to evaluate its ability to accurately define the relevant thresholds for known therapeutic decision levels (10% and major molecular response MMR: 0.1%) and (iii) to compare different markers of EMR  using GUS and ABL1 to predict the achievement of MMR after 12 months of TKI in a series of front line therapy patients. We describe the optimal cut-offs for the different markers to predict the 12-month MMR achievement with confirmation in a validation cohort. We highlight that it could be appropriate to add a new, earlier time point to patient monitoring earlier than those currently recommended in clinical practice in order to identify patients likely to benefit from an early switch of TKI.Our study intended (i) to assess the ability of CML patients included in this retrospective analysis were diagnosed and monitored on TKI in our institutions since August 2000 and the blood samples were collected between August 2000 and January 2013. Patients gave written informed consent for their data to be used in this analysis and the procedures followed were in accordance to the Helsinki declaration as revised in 2008. Samples were stored in the Biological Resource Center Bank according to the French “Comité de Protection des Personnes” specifications. The review board protocol of the Hospices Civils de Lyon approved this study. To address the main questions of the study, samples were collected as follows:GUS as a CG. Therefore, we studied 3 groups of samples according to their transcript values: the first group comprised diagnostic samples (n = 124), the second group comprised follow-up samples with a ISBCR-ABL1/ABL1 ratio between 6 and 14% (n = 18) and the third group consisted of samples at the MMR IS threshold of 0.1% (n = 42). We were particularly interested in these transcript values since (i) diagnosis is highly impacted by the quantification bias but is crucial to assess the EMR (for example between diagnosis and 3–6 months of treatment) and (ii) they represent the relevant thresholds for known therapeutic decision levels (10% and major molecular response MMR: 0.1%).First, we focused on the transcript values obtained by using We then went on to evaluate the prognostic value (probability of obtaining MMR one year after diagnosis) of different parameters described in the literature for assessing the early molecular response (EMR) value. We then selected patients with available samples at diagnosis and after 3 months of TKI therapy. Of the 124 patients obtained at diagnosis, patients with the following criteria were included: (1) TKI therapy started less than 60 days after diagnosis , (2) the patient should have received TKI between 60 and 120 days before the follow-up so-called “3-month” sample  and (3) molecular follow-up assessed for at least 1 year after diagnosis in order to evaluate the achievement of MMR . One patient who simultaneously presented another haematological malignancy and died before 1 year of treatment was excluded. Patient characteristics at diagnosis are listed in We validated our results in a supplemental cohort of patients (n = 58) selected according to the same criteria. Forty patients were on Imatinib as first-line treatment, 9 on Dasatinib and 9 on Nilotinib. Treatment interruption and/or switching was documented for 6 patients on Imatinib .BCR-ABL1 fusion transcript ABL1 and GUS were performed according to standardised EAC protocols previously described BCR-ABL1 transcripts (b2a2 or b3a2) were considered. The final results are expressed as BCR-ABL1/ABL1 ratios in percent according to the international scale IS  as it was previously recommended BCR-ABL1/GUS, without transformation of the original values since no conversion factor was defined for this CG. Samples with copy numbers that were too low  for either ABL1 or GUS were presumably degraded samples  and were excluded.RNA was extracted from peripheral blood sample and reverse transcription (RT) and Quantitative Real-time-PCR (RQ-PCR) to amplify BCR-ABL1/ISABL1) and BCR-ABL1/GUS values was performed by setting a new conversion factor (CF), following the procedure that has been used previously to set the international conversion factor IS ABL1 as CG was compared with that generated with GUS for the same sample. The bias between both measurements reflects the tendency of a method using one given CG to exceed the method using another CG. It was calculated as the difference between both measurements: bias  =  log(ISBCR-ABL1/ABL1) – log(BCR-ABL1/GUS) for each sample. The CF is calculated as the antilog of the mean bias between measurements with both methods.The alignment between both methods using  whereas the BCR-ABL1/GUS median ratio was 15.1% (range: 8.3–51.1%).In the first group of patients, the ISBCR-ABL1 values comprised between 6% and 14%), the median ratios of these transcripts were 11.1% for BCR-ABL1/ABL1 (range: 6.7–13.8%) and 3.1% (range: 2.2–5.8%) for BCR-ABL1/GUS.In the second group (patients chosen for their transcript BCR-ABL1/ABL1 (range: 0.047–0.183%) and 0.035% (range: 0.016–0.072%) for BCR-ABL1/GUS. As samples were chosen according to their transcript value of 0.1% when analysed in laboratory routine practice, and that all measurement were performed again simultaneously for this study, ratios vary slightly in this range of values. Therefore, we will refer to this group of samples as “MMR-related samples” later in this study.In the third group (patients with transcript levels at 0.1%), the median ratios were 0.089% for BCR-ABL1/ISABL1 and BCR-ABL1/GUS values showed a direct correlation .As expected, BCR-ABL1/ABL1 to BCR-ABL1/GUS values would require the introduction of a further conversion factor in order to adapt them to the decision thresholds currently used for MRD monitoring. This conversion is exemplified in ABL1 corresponds to a ratio of 0.036% using GUS.These results indicate that the conversion from ABL1 or GUS was calculated for each sample. In diagnostic samples, the mean bias was 0.65 (standard deviation SD: 0.12) whereas it valued at 0.45 (SD: 0.16) in samples with a 6–14% BCR-ABL1/ABL1 ratio and was somewhat similar, 0.42 (SD: 0.12) in the third group. The CF was then calculated as the antilog of the mean bias and valued at 4.45, 2.84, and 2.65 in the three groups of samples, respectively . Thus the higher copy number of GUS at diagnosis is responsible for the higher CF. Although ABL1 is also overestimated at diagnosis due to the quantification test bias (p<0.001), GUS expression varies at least in the same range of values as ABL1   . The valGUS at diagnosis is not due to the higher number of cells at this point in the disease, since the reverse-transcription protocol is designed to ensure that the same amounts of RNA are used whatever the sample is (MRD or diagnosis) This higher copy number of GUS was overexpressed at CML diagnosis compared to healthy donors GUS may be overexpressed in leukemic cells compared to normal cells and that GUS quantification may be correlated to the BCR-ABL1 transcript level. Indeed, a significant correlation was found between GUS and BCR-ABL1 copy number . The sub-group analysis for patients receiving TKI 1st or 2nd generation did not show any other difference for the BCR-ABL1/GUS or BCR-ABL1/ABL1 ratios. Besides, no prognostic cut-off could be identified for either BCR-ABL1/GUS or BCR-ABL1/ABL1 at diagnosis. Therefore, the transcript level at this time, whatever CG is used, does not predict the achievement of MMR after one year of treatment. Another group reported that elevated BCR-ABL1/GUS at diagnosis correlated with inferior probabilities of optimal response In order to determine whether the transcript level at diagnosis could be used as a prognostic indicator for disease evolution, we compared patients who achieved the MMR threshold 1 year after TKI introduction (n = 70) and those who did not (n = 54). The ISBCR-ABL1 level in this 84-patient cohort was 69.6%  at diagnosis and 0.98%  at 3 months. We used a receiver operating characteristic (ROC) curve to identify the optimal cut-off for the different variables tested that would allow us to classify the patients as presumably achieving or not the MMR at 12 months with maximal sensitivity and specificity . These results were concordant with recent reports regarding the 3-month landmark analysis predictive of 1-year MMR st and 2nd generation BCR-ABL1/GUS levels with a cut-off at 0.36% (corresponding to the 0.99% ISBCR-ABL1 corrected by the conversion factor of 2.65 defined for this MRD level) led to the same conclusions (p<0.001), for both generation of TKI.It was recently demonstrated that the persistence of BCR-ABL1 transcript value shows a 2-fold decrease nd generation TKI (19 days). Using IS(BCR-ABL1/ABL1) , we found that patients with a halving time ≤19 days (n = 46) had a superior rate of MMR achievement at 12 months than patients with halving time >19 days (n = 38) . Similarly to the predictive cut-off for transcript level at 3 months which varies according to the end-point of the study, our halving time cut-off value for 1-year MMR is lower than the 90-day cut-off used by Branford et al. to predict survival BCR-ABL1/GUS, we found that the cut-off of 21 days separated both groups with the maximal accuracy . The same results were obtained by TKI sub-group analysis.The halving time defines the number of days over which the BCR-ABL1/GUS ratio between diagnosis and 3 months of treatment was reported as a predictor of survival IS(BCR-ABL1/ABL1)  ratio, the median log reduction was 1.86 and a cut-off of 1.70 log reduction allowed the best discrimination for MMR achievement . The same results were obtained by TKI sub-group analysis. Of note, all the patients with a ISBCR-ABL1 transcript level ≤0.99% at 3 months also obtained a log reduction >1.70.Similarly, the reduction of the transcript ABL1 as CG is shown ISBCR-ABL1 ratio ≤0.99% at 3 and 6 months, a halving time ≤19 days and a log reduction <1.70) (7 patients out of 43: 16%). No treatment interruption or transformation was reported for these patients and all of them achieved the 0.1% threshold 15 to 22 months after treatment initiation without changing therapy , suggesting that some patients may respond more slowly to TKI therapy. Conversely, 6 patients obtained MMR at 12 months although they were classified as high-risk patients according to each of these early molecular markers  (6 patients out of 35: 17%). Interestingly, of these 6 patients, 5 had a ISBCR-ABL1 ratio ≤1% at 6 months  and 4 obtained a deep molecular response level of at least MR4 at a later stage. It is noteworthy that the cohort of discordant patients is too small to identify the best EMR marker (if one of them would be superior to others). Although all the markers seem to be relevant, the halving time cut-off identified allows the earliest detection of EMR failure.Therefore, the use of halving time, log reduction or transcript level at 3 months seem to have similar capacity to predict the molecular evolution of a patient, whatever CG is used. The comparison of EMR obtained according to the 3 markers using BCR-ABL1/ABL1 ratios were determined in this cohort, since we demonstrated the equivalence of both CG for the determination of EMR markers. The median halving time was 11 days . MMR achievement rate was 70% in patients with a halving time ≤19 days (n = 43) and 7% in patients with a halving time >19 days (n = 15) (p<0.001), thus confirming the reliability of this cut-off. Similarly, cut-offs of 1.70 for log reduction and 0.99% for the 3-month ratio also showed a good distinction between patients achieving MMR and those who did not .The observation that a halving time cut-off of 19 days may distinguish patients more likely to achieve MMR 1 year after diagnosis is a new finding that could change the current practices of molecular follow-up. In other words, a patient whose transcript level has not decreased by half after 19 days of treatment would benefit from an early switch of TKI. In order to confirm this finding, we evaluated this cut-off in a validation cohort of 58 patients. Only the GUS may be used as CG to quantify the BCR-ABL1 transcript, our study highlights that the use of BCR-ABL1/GUS instead of BCR-ABL1/ABL1 would have several consequences.Although GUS and ABL1 are not expressed in the same range of values, which impacts the ratio BCR-ABL1/[CG] and requires a conversion factor to assess the connection between both measurements. This signifies that the use of GUS as CG would (i) imply a new standardization of the international scale and (ii) change in particular the MRD thresholds defined in the international recommendations to assess patient's response to therapy as the MMR threshold Firstly, GUS transcript levels at diagnosis show a direct correlation with BCR-ABL1 levels, thus raising the hypothesis that GUS expression may depend on BCR-ABL1 transcript level. Therefore, although GUS measurement is not affected by a technical quantification bias as observed with ABL1, this overexpression (directly linked to BCR-ABL1 expression or not) does not allow more precise quantification of BCR-ABL1 at diagnosis. Furthermore, GUS expression varies in a greater range of values than ABL1 between the different disease times, which may preclude its use to assess the BCR-ABL1 transcript kinetics of the EMR. Given the limitations described, we therefore do not consider that the replacement of ABL1 by GUS represents an ideal option to assess EMR in CML patients.Secondly, we highlighted that BCR-ABL1/GUS and BCR-ABL1/ABL1 kinetics to predict the achievement of MMR 12 months after the TKI introduction. Using stringent inclusion criteria to ensure the reliability of our findings, we confirmed the strong predictive value of several early molecular markers in CML patients treated with 1st or 2nd generation TKI: the transcript level at 3 months of treatment, the halving time and the log-reduction of transcript levels between diagnosis and 3 months. We described the optimal cut-offs for the different markers for predicting 12-month MMR achievement in our cohort. In accordance with previous studies GUS enables the prediction of patient evolution with more accuracy than ABL1. We identified a time point of 19 days after TKI introduction to assess whether halving time has been reached and these results were confirmed in an additional validation cohort. Patients whose transcript level has not decreased by half after 19 days of treatment are less likely to achieve MMR 1 year after diagnosis. It would therefore be appropriate to add this time point to patient monitoring in order to identify those patients likely to benefit from an early switch of TKI. Although these results remain to be validated on larger cohorts of patients, they suggest that it would be helpful to monitor BCR-ABL1 levels at an earlier time point (close to 19 days) than realized in the current practice, in order to accurately assess response to TKI.In the second part of our study, we investigated different ways recently described to assess the EMR and evaluated the ability of


We determined the optimal cutoff titers in admission and convalescent-phase samples for scrub typhus indirect immunofluorescence assay using Bayesian latent class models. Cutoff titers of ≥1:3,200 in an admission sample or of a ≥4-fold rise to ≥1:3,200 in a convalescent-phase sample provided the highest accuracy . Orientia tsutsugamushi  , 1:100, 1:200, and at a 2-fold dilution series up to a maximum of ≥1:25,600  were used as previously described . In brieA total of 161 patients were included in the study. The median age was 41 years , and 63% (99/158) were male. The median duration of fever before admission to hospital was 5 days , and 138 patients (85.7%) had convalescent-phase samples available. The median duration between the admission sample and convalescent-phase sample was 12 days . Culture, a combination of PCR assays, IgM ICT, and the presence of eschar were positive in 9, 27, 31, and 17 patients, respectively. Overall, 62 patients were considered IFA IgM positive based on the conventional cutoff titers (42 had an admission IFA IgM of ≥1:400), and 46 patients were considered IFA IgM positive based on STIC .First, we used the unbiased ROC curves to evaluate the performance of admission IFA IgM in an admission sample alone  and showAs we found that a criterion of a ≥4-fold rise to ≥1:200 in a convalescent-phase sample led to the low specificities of conventional and STIC cutoff titers of IFA IgM, we validated this finding by evaluating the results of IFA IgM in those who had alternative diagnoses in our data set as previously described . We founIn this study, we used an unbiased Bayesian LCM approach and defined optimal cutoff titers for IFA IgM as either ≥1:3,200 in an admission samples or as a ≥4-fold rise to ≥1:3,200 in a convalescent-phase sample. With these new cutoff titers, the sensitivity and specificity of the IFA IgM is 81.6% and 100%, respectively, indicating that they can be used to diagnose scrub typhus with high confidence in clinical and research settings. The low specificity caused by the low cutoff titers of IFA IgM could be due to cross-reactivity of the IFA IgM with infections caused by other organisms in our setting, and this is also likely to occur in other tropical countries . AlthougThe biased selection of cutoff titers is a common problem affecting many serological tests for tropical infectious diseases because the reference tests are rarely, if ever, perfect . In addi


The Geelong Clinic's 40-day LEAP (Learn to Eat at Peace) Eating Disorders Inpatient Program is unique as consumers have had considerable input in the development and ongoing review of the program. The LEAP philosophy emphasises trust, dignity, individualised treatment, and skill acquisition. The program involves staff-supported meals and groups facilitated by a multidisciplinary team. The aim of this study was to evaluate if there were changes in patients' clinical symptoms following the program.Participants were eating disorder (ED) patients (n = 43), aged 16 to 55 years. Data was collected through self-report measures at admission and discharge from the program. Repeated-measures ANOVAs were used to assess changes in variables including restraint over eating, eating concern, shape concern, weight concern, body mass index, depression, anxiety, and stress.Results indicated statistically significant improvements across all variables. Effect sizes were large , indicating clinical significance. At discharge, 85% of patients agreed that they were satisfied with therapy and with therapists.Findings provide empirical evidence that following the LEAP Program, patients report significant improvements in ED symptoms and general psychopathology, and were satisfied with treatment. Findings support the importance of consumer involvement, using a collaborative approach, and multidisciplinary treatment of EDs.Treatment in Community and Inpatient Settings stream of the 2014 ANZAED Conference.This abstract was presented in the