Physical activity can help mitigate the long-term symptoms and side effects of cancer and its treatment, but most cancer survivors are not active enough to achieve these benefits. An evidence-based strategy to promote physical activity among adults is a community group–based walking program. However, many evidence-based programs do not achieve intended population health outcomes because of the challenges of real-world implementation. We used the Interactive Systems Framework for Dissemination and Implementation to conceptualize implementation of a capacity-building intervention to support delivery of a community group–based walking program. We adapted an evidence-based guide for community group–based walking programs for cancer survivors and their support network. We provided a capacity-building intervention  and evaluated this implementation intervention. We assessed effectiveness of the intervention by measuring adoption, acceptability, appropriateness, feasibility, fidelity, implementation costs, and penetration through monthly progress reports, site visit observations, interviews, and a final report. Eight organizations received a small grant and technical assistance and implemented Step It Up! Survivors (SIUS). SIUS helped cancer survivors increase their physical activity, establish social connections, and be part of a supportive environment. Despite receiving monthly technical assistance, some grantees experienced challenges in recruiting participants, developing community partnerships, and adhering to the prescribed implementation plan. Implementation facilitators included community partners and specific components . Organizations needed different amounts and types of assistance with adaptation and implementation. Overall fidelity to SIUS ranged from 64% to 88%. Some integrated SIUS within existing organizational programming for sustainability. The provision of funding and technical assistance was a successful implementation intervention. Our results suggest a need to better tailor technical assistance while organizations are in the process of adapting, implementing, and sustaining an evidence-based program in their local communities. Providing technical assistance and small-grant funding to community organizations is a promising approach to support implementation of evidence-based programs.Community organizations are challenged by some aspects of implementing an evidence-based program, particularly balancing fidelity and adaptation and conducting a rigorous evaluation.Difficulties experienced by some organizations in balancing fidelity and adaptation of the Step It Up! Survivors program indicate that flexible, individualized guidance and enhanced technical assistance are needed when they are in the process of adapting, implementing, and sustaining an evidence-based program locally.In 2019, approximately 16.9 million cancer survivors were living in the United States, and their number is estimated to increase to 22.1 million by 2030 . AdditioGroup exercise is a promising approach for cancer survivors. Group and/or supervised exercise has resulted in greater improvements in primary outcomes  compared with unsupervised and/or home-based interventions among cancer survivors . Group wPublic health programs, such as group-based walking programs, should reflect the best available evidence. However, many evidence-based programs (EBPs) do not achieve intended health outcomes because of challenges in implementation. Capacity-building interventions enhance community public health practitioners’ adoption and implementation of EBPs . The IntStandard approaches are needed to assess the implementation of evidence-based cancer prevention, control, and treatment interventions. Proctor and colleagues developed a taxonomy of implementation outcomes that includes acceptability, adoption, appropriateness, feasibility, fidelity, cost, penetration and sustainability . Using aThe goals of this study were to 1) adapt an evidence-based guide for community walking programs for cancer survivors and their friends and family, 2) provide capacity-building support  for community organizations to implement this program, and 3) evaluate the success of the implementation of the intervention.We used the ISF to conceptualize implementation of a capacity-building intervention to support delivery of a community group–based walking program. We adapted an evidence-based guide for delivering group-based walking programs for cancer survivors and their friends and family and called the program Step It Up! Survivors (SIUS). We provided capacity-building support, technical assistance, and small-grant funding to community and public health organizations in Oregon.We used a mixed-methods design to assess the implementation outcomes. We collected qualitative and quantitative data from several sources during the study period. The study was approved by the Oregon Health & Science University (OHSU) Institutional Review Board. The study, including planning, took place from July 2017 through February 2019.We completed implementation strategies and activities in each of the 3 interacting systems delineated in the ISF: The Prevention Synthesis and Translation System and the Prevention Support System were represented by OHSU and the Knight Cancer Institute. The Prevention Delivery System was represented by the community-based organizations.Establishing a Group Based Walking Program to Increase Physical Activity Among Youth and Adults , which provides small grants  to community organizations. We issued a request for proposals for implementation of SIUS. Community groups, health and medical clinics, public health departments, and health systems in Oregon that did not have an active walking program were eligible to submit an application for a 1-year $15,000 grant, plus technical assistance. Before the application submission date, we hosted a webinar about the competitive funding process, and funding decisions were based on proposal review by members of our Cancer Prevention and Control Research Network’s Tribal and Rural Advisory Board, a previous Community Partnership Program grantee, and OHSU researchers. Final funding decisions were made by Community Partnership Program leadership. Funding was provided from January 2018 through December 2018.Technical assistance. The team of researchers worked with grantees to implement the SIUS, including assistance with any relevant regulatory approvals. In March 2018, representatives from each organization attended a train-the-trainer webinar on how to train local community members to be walking group leaders. We facilitated 8 monthly, 60-minute webinars on recruitment, retention, and motivation of walking group leaders and participants, adaptation logs, and program sustainability. Each month, a different grantee made a 30-minute presentation on various topics , leaving 30 minutes for discussion facilitated by the research team. The webinars provided an opportunity for organizational leaders to learn from and support each other. Additionally, we responded to questions and provided individual guidance to grantees via telephone calls and email.www.cpcrn.org/training). This 1-day in-person training session provides instruction on implementation of EBPs in public health. This instruction was applied by grantees to the SIUS program, but the skills could also be applied by grantees in future programs.In January 2018, we held a training session developed by the Cancer Prevention and Control Research Network, Putting Public Health Evidence into Action , continuing to publicize and recruit participants, maintaining interest and attendance in the program, and continuing to engage with the community. The third phase was a 2-month maintenance phase, and the final phase was 2 months for follow-up. In addition, each organization had 2 months to complete a final report.We assessed effectiveness of the implementation intervention by measuring acceptability, adoption, appropriateness, feasibility, fidelity, implementation costs, penetration, and sustainability as described by Proctor and colleagues , throughCommunity organization reports. Monthly grantee progress reports described strategies for publicizing SIUS, tactics and incentives used to motivate participants and leaders, walking route, number of groups held, and attendance. A final report gathered data on SIUS objectives and outcomes , project reach , community partnerships , strengths and benefits of the project, barriers, challenges and lessons learned, future plans, and evaluation of the technical assistance . The monthly and final reports were completed in a secure online database. Additionally, the grant applications provided information on the grantee .Fidelity assessment: observation and stakeholder interviews. For each grantee, research staff members observed a walking group and interviewed the program manager to assess fidelity. During the observation, the researchers completed a fidelity checklist of the key components of conducting a walking group outlined in the toolkit. Key components included characteristics of the walking leaders, the routes, use of team building and social support strategies, and accessibility and aesthetics of walking routes.One research staff member conducted 30- to 60-minute semistructured interviews with key leadership at each organization and a second staff member completed the fidelity checklist and took notes during the interview. Key components of implementation described in the toolkit that were not possible to observe during the walking group were asked about during interviews, including types of stakeholders engaged in planning and implementation, identification and training of walking group leaders, alternate routes for inclement weather, minimizing loss of interest, and resources used to plan routes.Adaptation logs. We provided organizations with an adaptation log to record adaptations to the program, the date and description of the adaptation, reason for the adaptation, and its level of importance. These logs allowed for comparison across organizations.Walking group participant survey. Walking group leaders invited cancer-survivor participants to complete an online survey at baseline, 3 months, and 6 months. The survey included 11 statements about their experience and satisfaction with SIUS; respondents rated agreement on a scale from 1 to 6 . At baseline, the survey also collected information on cancer-survivor participants’ demographic characteristics , height and weight, and cancer (type of cancer and number of years since diagnosis).Qualitative data analysis. We exported notes taken during the leadership interviews and coded them line by line. We exported text from the final project reports into Dedoose version 8.1 , a web-based program for analyzing qualitative and mixed-methods data. Two researchers coded the texts independently and met to reach agreement. The coding focused on implementation outcomes, barriers, and facilitators.Quantitative data analysis. We exported quantitative data from the monthly progress reports and site visits into R statistical software version 3.5.1 , data from the online participant surveys into Stata version X (StataCorp LLC), and data from the fidelity checklist and monthly and final reports into Excel (Microsoft). We calculated descriptive statistics for each organization.Walking group attendance was recorded each month by each organization. The average weekly attendance is the mean number of people attending a walking session across all groups hosted by an organization. Some organizations had more than one walking group that met weekly. The average monthly attendance is the average total attendance for all organizations across weeks in a particular month.We measured fidelity to the SIUS implementation toolkit by using a checklist, which we completed during site visits , and an interview guide, which we used during interviews of organizations’ leadership. We calculated a fidelity score for each of the 7 steps of program implementation as a percentage. The checklist included 9 yes/no questions and 12 questions answered on a scale of 1 to 5; the checklist was also used to record the location and date of the site visit. To assign questions equal weight among the fidelity scores, we coded the rating-scale questions from 1 to 5, and we coded dichotomous questions yes = 5 and no = 1. We did not count responses marked as not applicable or missing in the calculation of the fidelity percentage. This method is commonly used in analysis of survey data .Mixed-methods analysis. We placed the coded text and the quantitative results into an implementation outcomes matrix for further analysis. The mixed-methods analysis for organizational-level data spanned 3 areas: measuring program success using attendance data for each organization, assessing fidelity to the SIUS toolkit, and analyzing strategies and tactics to recruit and incentivize walking leaders and participants. Walking group attendance was a quantitative measure of program success, with larger attendance numbers indicating better program engagement. A higher fidelity percentage indicated greater fidelity to the SIUS toolkit. Strategies to recruit and incentivize walking leaders and walking group participants were deduced from the monthly reports, and qualitative themes were deduced from site visit data and monthly reports. We created a case-based matrix with the organizations in rows and the strategies in columns.Sixty cancer-survivor participants completed eligibility screening, 35 met eligibility requirements, 30 consented to participate and completed the baseline survey, and 17 completed the survey at 3 and 6 months. Eligibility requirements included a cancer diagnosis, participation in an SIUS walking group, being aged 18 or older, and ability to speak English. Grantees did not prioritize completion of the online surveys.Of the 30 cancer-survivor participants who completed the baseline survey, the average age was 60.4 . Most were non-Hispanic (n = 28) and White (n = 28), had a bachelor’s degree or higher (n = 20), and were married (n = 26). About half were retired (n = 13), and half were employed full-time or part-time (n = 12). The most common form of cancer was breast cancer (n = 21) with time from diagnosis ranging from 4 months to 30 years.Adoption. Ten organizations responded to the request for proposals for implementing SIUS; 8 organizations received awards. Organizations that received awards were local health departments (n = 3), community cancer centers (n = 3), a nonprofit organization that supports cancer survivors (n = 1), and a physical therapy practice (n = 1); 6 were in rural communities.Acceptability. The average weekly attendance varied within and across organizations , lack of commitment from organizational leadership, challenging retention during the summer because of summer travel and vacations, and weak community partnerships.Feasibility. All organizations reported that they implemented at least 1 walking group during the study period. Some organizations experienced low attendance and challenges with keeping walking leaders engaged over the 3 months , allowing weekly groups to continue.Fidelity. Fidelity was the degree to which the SIUS program was implemented as delineated in the toolkit. The number of adaptations across the 7 steps ranged from 0 to 4 . All organizations reported implementation of SIUS within the budget as planned, including in-kind donations.Penetration. The number of walking groups held in each organization ranged from 1 to 9, with a mean of 5.2 walking groups per organization. One organization stated, “We set a goal of establishing 1 walking group and significantly exceeded our expectations with 5 active walking groups in our community.”Two organizations reported incorporating the walking program into existing organizational structures. One organization reported that SIUS was co-promoted with another well-known wellness program in the organization, which contributed to successful recruitment. As one organization stated, “This walking group has become a part of the survivorship and cancer support/education group program that is led by the Oncology Social Worker, which promotes the likelihood of it continuing on into the next year.”Sustainability. Four organizations reported that their program was highly likely or somewhat likely to be active 1 year after the funding period. These organizations reported that the largest contributing factors to expected sustainability were integration of the walking groups into existing programs (within their own organization or a community partner) and participant enjoyment. Another contributing factor was the use of volunteers to lead the walking groups. One organization noted, “[The city’s] recreation program has taken on the long-term coordination of Step It Up! Survivors in our town. The group is peer led and does not rely on paid staff [to lead the walking groups].”This capacity-building intervention of providing technical assistance and small-grant funding was a successful approach to promoting implementation of an evidence-based community walking program for cancer survivors, their friends, and families. The 8 grantees varied in their capability to achieve success, suggesting the need for tailored technical assistance. Fidelity to the toolkit varied across the 7 steps in the program implementation and across the 8 organizations, suggesting the need for more clarity, more education about the importance of fidelity, and more individualized guidance on balancing fidelity and adaptation. Integration of SIUS into existing programs in the organization and participant enjoyment contributed to the likelihood of sustaining SIUS for at least 1 year beyond the funding period.Six of the 8 organizations that implemented SIUS were in rural  communities . Rural rOrganizations commented that walking groups were an important source of social support for cancer survivors. Extension of the walking groups to cancer survivors’ friends and family and, in some locations, the broader community expanded the network of social support.Capacity-building interventions providing technical assistance and/or small-grant funding have been found to enhance the adoption and implementation of EBPs ,20–24. SAlthough key leadership from each grantee received training on fidelity and adaptation, we found a range of fidelity to and adaptations of the SIUS toolkit. A potentially inappropriate adaptation could compromise an underlying evidence-based component of a group-based walking program, as we found in the broadening of the definition of a walking group attendee. In a mini-grant program in which recipients received training on adaptation and fidelity of evidence-based interventions, the organizations made substantial alterations that might have changed the evidence-based components of the programs . In anotWe found that community organizations with previous program implementation experience were able to build on that experience and move through the steps in the SIUS toolkit better than organizations with less experience. Although we delivered technical assistance through multiple modalities, including telephone calls, emails, training sessions, and monthly webinars, we did not tailor our approach to the experience of each organization. Providing technical assistance in a flexible manner that aligns with and addresses organizational realities  and is both relationship building and content driven has been effective in promoting implementation of EBPs ,27. AsseOur study has several limitations. It was conducted in Oregon only, so results may not be generalizable to other areas of the United States. We did not audio record interviews with key stakeholders and despite careful notes taken during the interviews, some responses from interviewees may not have been fully reflected. Because of a short funding cycle, we could not follow up 1 year after the start of the walking groups to assess sustainability. The community organizations had challenges recruiting and retaining cancer survivors, and most opened the groups to any community member. Strengths of this study include use of theoretical framework, ISF , to concUse of the ISF helped us to conceptualize the elements and relationships of key stakeholders  involved in providing a capacity-building intervention aimed at disseminating and implementing an evidence-based community health walking program for cancer survivors. The capacity-building intervention  was a successful approach for dissemination and implementation of SIUS. Difficulties experienced by some organizations in balancing fidelity and adaptation of the SIUS program indicates that flexible, individualized guidance and enhanced technical assistance are needed while organizations are in the process of adapting, implementing, and sustaining an EBP locally. Use of capacity-building interventions to promote and guide the implementation of EBPs by community organizations is an effective method to achieve a program’s intended population health outcomes. Members of this research team have applied for funding to expand the scope of group walking programs for cancer survivors, their family and friends, as well as community members in rural locations throughout Oregon.


This paper describes the approach used to develop the Adolescent Family Life Program (AFLP) Positive Youth Development (PYD) Model within the structure of an existing state government-run program.The California Department of Public Health, Maternal, Child and Adolescent Health (CDPH/MCAH) Division undertook an innovative approach to develop a program model to help expectant and parenting youth build resilience. CDPH/MCAH started by assessing existing program efforts and theory to develop and test new strategies in the field, structure a program model, and build toward broader expansion and sustainability. CDPH/MCAH engaged local organizations from across the state, their staff and enrolled youth, experts, and evaluators in an iterative program development process to standardize an effective model that could be replicated and evaluated.Key lessons for program developers and administrators are to ensure adequate staffing with diverse expertise related to the topic and content to support the multiple components of program development and implementation, evaluation, and training; identify the guiding theory and framework early and link them with clearly articulated core components to ensure the final model reflects the intended purpose and is structured to support implementation; engage implementation staff on the ground and focus early and often on processes for supporting people through change.The lessons learned can guide others working with existing programs to develop standardized program models or translate new science and theory into practice. Although state agencies often fund and oversee evidence-based public health program models, expanding to program model development presents unique opportunities for broad impact. The California Department of Public Health undertook a process to develop a program model for expectant and parenting youth within an existing program. The process involved extensive engagement of local implementing agencies, youth participants, and experts. The lessons learned can guide others in considering program improvements based on new science and compelling theory. They also reveal the value of a participatory process, which requires intention around managing change and developing systems for supporting implementation and evaluation.Expectant and parenting youth (EPY) often face unique social, economic, and health challenges that can limit their opportunities for success. These challenges may include factors such as inadequate or unsafe living environments, racial and income inequalities, and insufficient access to health care and education  for improving health and well-being. EBPMs are models found to be effective at improving specific outcomes based on rigorous research . In 2008–2009, AFLP suffered major budget cuts triggered by the economic downturn. To sustain funding and build public confidence for the program, CDPH/MCAH needed to show that program activities resulted in positive outcomes. However, it was difficult to identify successful strategies, measure their effectiveness, and ultimately demonstrate program impact because of the substantial variation in how AFLP was implemented in agencies across the state. For example, although all agencies worked with youth to develop individual service plans, some agencies implemented a crisis management model, whereas others focused more broadly on goals and youth development. Additionally, although the program required monthly visits with youth, the number of visits each youth received every month varied by agency. A standardized program model and data collection processes were needed.In 2010, CDPH/MCAH received an Office of Population Affairs  Pregnancy Assistance Fund (PAF) grant to develop and implement a new program model for EPY in California. The PAF project provided CDPH/MCAH with resources to build a team to develop and pilot a model leveraging the existing AFLP and a formative evaluation process. CDPH/MCAH’s goal was to increase and sustain support for California’s youngest families through the development of a standardized model that could reliably produce meaningful results.This section describes the 5-year, nonlinear process of securing resources, building a team, and developing the AFLP PYD Model across three project phases: 1) early program development, (2) iterative pilot implementation and formative evaluation, and (3) formalizing the model structure for expanded implementation and evaluation.  case management, (2) positive youth development approaches, (3) motivational interviewing (MI), and (4) reproductive life planning. Case management is a best practice for supporting EPY in meeting their unique needs and goals . CDPH/MCAH worked with the pilot sites on environmental scans and site profiles to learn about best practices and existing efforts implemented in the field. CDPH/MCAH also trained the pilot sites on the foundational strategies for the model development—PYD, motivational interviewing, and life planning.From 2011 to 2013, during the second project phase—iterative pilot implementation and formative evaluation—CDPH/MCAH and the pilot sites engaged in a cyclical program development process to structure and operationalize strategies and best practices identified as effective with youth. This process included (1) developing or adapting program model elements with local staff, youth, and expert consultants; (2) sending the model elements into the field for local agencies to implement with youth in their existing AFLP; (3) gathering feedback from local agencies (staff and youth) about the implementation experience through formative evaluation; (4) adapting or repackaging the model elements; and then (5) sending the revisions back from the state to local agencies for implementation. This cycle was repeated multiple times. After each major revision, CDPH/MCAH provided case managers and supervisors with training, guidance for implementation, and revised data collection processes that aligned with the changes in implementation.My Life Plan, originally developed by one of the AFLP sites. Case managers quickly focused on implementing and providing feedback on the My Life Plan and expressed challenges with integrating PYD concepts into their daily work. CDPH/MCAH received feedback about the need to clarify concepts of PYD and resiliency, particularly in the context of helping youth to meet their basic needs and work toward personal goals. Integrating PYD in the context of every interaction required a shift in the program paradigm from a traditional framework—where professionals intervene to fix specific issues—to one based on PYD principles, which emphasizes young people’s abilities and supports them in building strengths, skills, and resilience.The first tool pilot tested was a reproductive life planning tool called the Resiliency in Action , to collect information about implementation through semi-structured telephone and in-person interviews and online surveys with local case managers and supervisors, observations of youth-case manager visits, focus groups with youth, and training evaluations. The evaluation resulted in anonymous feedback addressing the utility of the newly developed program materials; factors that impeded or facilitated implementation; and summaries of local staffs’ understanding of the underlying strategies . At the end of each cycle of formative feedback, CDPH/MCAH received an evaluation report with key findings and recommendations for program improvements. The formative evaluation (phase 2) provided CDPH/MCAH with the information needed to make revisions and ultimately to formalize the content, structure, and packaging of the AFLP PYD Model for expanded implementation and evaluation (phase 3). All evaluation work related to the project described in this article was approved by the Institutional Review Board of the State of California and was completed separately and prior to the federal evaluation, the Positive Adolescent Futures study, documented by Asheer and colleagues in this journal supplement , with additional findings anticipated in 2020.In 2013, as the formative evaluation was concluding, CDPH/MCAH secured a second PAF grant. Although key parts of the model were developed—including the foundational resiliency framework, program phases, and key activities/tools—the model was not yet packaged to support standardized implementation, expansion, and evaluation. During an extension year from the first PAF grant (2013–2014), which overlapped with the second grant, CDPH/MCAH was selected for the federal evaluation of the AFLP PYD Model conducted by Mathematica . The federal evaluation provided the impetus to add state staff to the project who had expertise in developing, monitoring, and evaluating evidence-informed program models and expedited the structuring and packaging of the full AFLP PYD Model. As part of the model packaging, CDPH/MCAH articulated core components of the model in terms of logistics ; pedagogy ; and content . The core components resulted from what research indicated should drive change and what the pilot testing and formative evaluation revealed was relevant and feasible in the field. The AFLP PYD Model was structured into 24 face-to-face visits between the case manager and the youth within a 12-month period across four distinct program phases. CDPH/MCAH created a visit-by-visit guide for local agencies that articulated the specific core components and the purpose of the activities related to the resiliency framework and program goals. The visit guide also provided case managers with parameters about where and how to be flexible and responsive to the needs of youth, in relation to model guidelines, while maintaining fidelity to the model. From December 2014 through June 2015, CDPH/MCAH expanded the AFLP PYD Model implementation to an additional 14 local sites, many of which participated in the federal evaluation conducted by Mathematica.CDPH/MCAH offers the following key lessons that emerged through the experience of developing the AFLP PYD Model. The lessons are particularly relevant when developing a program model with extensive engagement from program implementers and participants. In addition, developing and implementing a new model in the context of an existing program presents unique challenges and requires intentional strategies to support success. CDPH/MCAH offers three key lessons that emerged throughout the program development process for consideration by others (see Table The need to ensure adequate staff capacity (number and specific capabilities) to support program development along with routine program monitoring and technical support should not be underestimated. For this type of program development, it is essential to have staff in place that have topical expertise, knowledge of program development and implementation of evidence-informed/based models, monitoring and evaluation expertise, and the ability to train and write clear guidance for implementation. Staff with these areas of expertise should be engaged from the beginning of the project, when possible. From a state perspective, it is also important to have efficient contracting mechanisms and supportive funders that provide the opportunity to engage people with the needed expertise .Early resourcing of the AFLP PYD Model development project focused heavily on conceptual strategies and program material development, including contracted research staff to engage in formative evaluation with local agencies and conduct literature reviews. The state staff translated the research and findings from the field into a packaged model that could be replicated and developed tools to monitor and evaluate implementation. CDPH/MCAH started this work with a small team that gradually grew to include additional expertise. Although the state team was able to respond to formative feedback, revise materials, develop and conduct trainings, update data systems, and provide tailored support to each implementation site, there were substantial challenges and setbacks along the way that may have been alleviated or lessened by having the diverse expertise needed at the project’s outset. Other challenges included staff turnover and extended leaves, which reduced the continuity of the development process and resulted in the loss of particular expertise. These contributing factors are often impossible to control but affect program development. Sustained commitment from CDPH/MCAH leadership and the federal funder, coupled with gradually growing the state team’s expertise and the ongoing dedication from local agencies and UCSF, supported continued success of the development process.Without a clear scientific framework guiding program development, the iterative nature of the process can dilute the final product. Program development research suggests that a set of core components is essential (Blase and Fixsen CDPH/MCAH developed the AFLP PYD Model through extensive engagement with local sites already implementing AFLP case management for EPY. A primary benefit to this approach was the rapid implementation and testing of model strategies and program materials by local staff and youth. Their experience, ideas, and feedback informed changes that ultimately helped ensure program activities were feasible to implement and resonated with youth. Simultaneously continuing services while piloting new and changing strategies gave rise to other challenges. In particular, local agencies expressed considerable anxiety and practical challenges related to the frequency that program tools, processes, and data collection forms changed throughout the cycles of formative feedback and model refinements. CDPH/MCAH engaged in multiple strategies to balance the needs for stability and local planning with the commitment to integrating science and local input for program improvement. Identifying local champions that demonstrated enthusiasm and proficiency helped sustain momentum in the face of challenges. CDPH/MCAH gave local champions opportunities to share experiences and strategies with others slower to adapt to changes. Acknowledging local expertise and providing the opportunity for local staff to express and discuss concerns and to link back to the program development purpose—to create and sustain an effective program for EPY—helped some people adapt. Regular technical assistance, training, site visits, guidance, resources, and ongoing communication also helped alleviate the stress and uncertainty that came with implementing a developing program model.The public expects that public health agencies will not only monitor population health but will also protect and respond, on the public’s behalf, in a responsible and transparent manner. Evidence-informed and evidence-based models are needed to improve the health and well-being of general and targeted populations. Dedicated resources are essential for supporting the related development, evaluation, and program implementation. Through the PAF project, CDPH/MCAH embarked on a process to engage and listen to the voices of local professionals and youth to develop a program that honors and builds the strengths and resiliency within young people.The AFLP PYD Model started as an idea to integrate the latest scientific evidence for supporting EPY with promising practices implemented by local AFLP sites throughout the state. Through diverse expertise from local and state implementers, program developers, evaluators, and trainers, CDPH/MCAH operationalized, tested, and refined the concepts of PYD for EPY. The result was a structured program model with defined core components that could be implemented and evaluated across multiple settings. This project highlights the value of a participatory process as well as the challenges of simultaneously providing services while pilot testing and adapting to programmatic changes. CDPH/MCAH employed multiple strategies for supporting field staff with changing implementation. Key strategies that helped sustain commitment at the state and local levels included identification of local champions to support others in the field, frequent opportunities for support and shared learning between local implementers and state program development staff, and the iterative development of tools and systems to support implementation.Fundamentally, program development requires developers and staff to be responsive, open minded, and adaptive—thus, nimble yet also steadfast around what is core to the work. State public health agencies are in a unique position to leverage the experience and commitment of state and local staff towards innovative solutions that can have widescale impact. The work described in this paper provides an example for other public health and social service entities that are considering taking a leadership role in designing programs or program improvements based on new science and compelling theory.


IntroductionMost medical residency training programs maintain websites to provide content for audiences including current residents, prospective residents, and medical students. This study seeks to characterize when and how a residency program website is being accessed in order to identify the primary audiences to provide appropriate and timely content.MethodsThe authors examined website analytics at a large urban Accreditation Council for Graduate Medical Education (ACGME)-accredited post-graduate year (PGY)1-PGY4 emergency medicine residency training program website. Analytics were performed from July 1, 2016 to June 30, 2018 with daily traffic cataloged along with referral sources, page views, and device type used to access the website. The top five dates by daily traffic were further analyzed with daily traffic trends during the residency interview season.ResultsThere was an average of 45.8 unique visitors daily with 261.5 daily page views. Computer (67.2%), mobile device (29.6%), and tablet (3.1%) were the most common devices used for viewing. The most popular content areas by page-view were “people” , “home” , “clinical curriculum” , and “medical students” . The five most-visited dates were all related to application processes including the opening of the Visiting Student Application Service (VSAS), the Electronic Residency Application Service (ERAS), and Match Day. During the interview season, peak visits occurred the dates immediately preceding interview dates.ConclusionResidency program websites appear to be accessed most commonly by medical students and prospective residency applicants. Website managers should take the needs of these audiences into account and provide appropriate content to maximally inform prospective residency program candidates. To keep pace with the rapid evolution in web-based communication and marketing over the past three decades, most medical residency training programs have created and maintained program-specific websites. There is considerable variability in the presence and quality of information that is available on these websites, especially as they contend with the need to provide content for multiple different audiences such as current residents, prospective residents, and medical students . In induResidency program-specific website managers must understand how, when, and why their website is being accessed to allow for efficient web-based communications. Unfortunately, little is known regarding when and for what purposes residency program-specific websites are being accessed. Such data can be utilized to create an efficient model for editing a program’s website and prioritize the update of commonly accessed content in a timely manner. Thus, the objective of our study was to describe trends in the access patterns of a residency program-specific website.This study was a retrospective analysis using website analytics at one large urban Accreditation Council for Graduate Medical Education (ACGME)-accredited post-graduate year (PGY1)-PGY4 emergency medicine residency training program with 68 residents in training and rotations for both third and fourth-year medical students. Website analytics of the program website were performed using Squarespace™ across two academic years: from July 1, 2016 to June 30, 2018 . Daily tOver the 24-month study period, there was an average of 45.8 unique visitors daily with 261.5 page views per day. Computer access accounted for 67.2% of website visits, mobile device for 29.6% of visits, and tablet for 3.1%. Google searches accounted for 49.3% of visits, direct uniform resource locator entry for 41.8%, and Bing searches for 2.4%. The remaining 6.5% of visits were via other sources. The majority of visits (94.2%) originated from within the United States with less than 1% from each of Canada, India, the Republic of Korea, the United Kingdom, Russia, and other countries.The most popular content by page-view Figure  were “pePeak access to the residency program-specific website was related to medical student and prospective resident application processes along with Match Day. The days immediately preceding interview dates also corresponded to a sharp increase in website traffic. Medical students and potential residency program applicants are likely significant consumers of residency program-specific website content given peak website traffic tended to parallel medical student’s fourth year away rotation and residency application dates. Website managers should consider this primary audience when creating content for their websites and make the content accessible and pertinent to medical students and prospective residency applicants. While computers accounted for the majority of website traffic, about one-third of visits were via a mobile device or tablet. Website managers should thus ensure residency program websites are as mobile device compatible as possible. Additionally, most website traffic was directed via a search engine rather than a direct link from databases such as the Fellowship Residency Electronic Interactive Data Access System (FREIDA) or the ACGME. This finding was not unexpected as these databases have variation in link access to residency program-specific websites . ProgramData on peak traffic dates can help influence decisions about when website edits should take place. According to our study, this is ideally prior to the opening of the application cycles of VSAS and ERAS. As residency program website managers typically work with limited resources and often balance website-related responsibilities with other administrative or clinical duties, it is critical that changes to the website occur efficiently and in a way that will maximize the impact on website viewership.With regard to page-view data, the most popular content accessed was the “people” section of the website. This section includes photographs of current residents and faculty and information regarding their medical school and other training. Efforts to keep these sections up to date and include information pertinent to prospective applicants should be prioritized. Interestingly, information regarding the program’s curriculum was accessed much less often, at about half the frequency as the “people” section, which underscores the value prospective applicants may place on the backgrounds of their potential colleagues.Residency program-specific websites appear to be accessed most commonly by medical students and prospective residency program applicants. Peak access times tended to cluster around medical student dates of importance such as the VSAS and ERAS application opening dates, Match Day, and the days prior to residency program interview dates. Residency program website managers can use these data to better understand the primary audiences of their residency program websites and determine when to update and upload new content to best inform and attract prospective residency program candidates.


During 2017-2019, we conducted a randomized stepped-wedge cluster trial of an online program to increase ease of access to information and support for caregivers of a person living with dementia in rural Australia. The program, called Virtual Dementia Friendly Rural Communities (Verily) Connect, was innovative; it consisted of a custom-designed website and mobile application (app) in Android and iOS, use of videoconferencing for peer support, chat forum and use of volunteers to build technological skills and confidence for online users. The program overcame barriers experienced by rural Australian caregivers, particularly geographical distance from services and other caregivers, stigma, and lack of localized supports. Although participants identified that Verily Connect program afforded several benefits, including increased flexibility in accessing support, easier access to localized dementia-related information, and more opportunities for attaining support, uptake of the program was disappointingly low. A strong theme in the program evaluation, which used the Consolidated Framework of Implementation Research, was that although the program was perceived as advantageous, adaptable, of high quality, and easy to implement, engaging participants failed because the target users, people over 65 years, eschewed involvement with online technology. Our future research plans include finding ways to offer hybrid online/face-to-face support programs specifically designed for older adults, so that older adults have equitable opportunities to access technological innovations. Older adults ought not to be disadvantaged because it is difficult to keep pace in a rapidly changing world.


In Australia, secondary school educators are well positioned to recognize mental illness among students and provide support. However, many report that they lack the knowledge and confidence to do so, and few mental health training programs available for educators are evidence based. To address this gap, the Black Dog Institute (BDI) developed a web-based training program  that aims to improve mental health knowledge, confidence, and helping behaviors among secondary school educators in leadership positions. A pilot study of the training program found it to be positively associated with increased confidence and helping behaviors among educators and reduced personal psychological distress. An adequately powered randomized controlled trial (RCT) is needed.The primary objective of this cluster RCT is to evaluate the effectiveness of the BEAM program for improving educators’ confidence in managing student mental health. The trial will also evaluate the effect of the BEAM program in increasing educators’ frequency of providing help to students and improving their mental health knowledge and reducing educators’ psychological distress and stigma toward students with mental health issues.The target sample size is 234 educators from 47 secondary schools across New South Wales, Australia. Four waves of recruitment and enrollment into the trial are planned. Schools will participate in one wave only and will be randomized to the intervention or waitlist control conditions. Participants from the same school will be assigned to the same condition. Assessments will be conducted at baseline, posttest (10 weeks after baseline), and follow-up (22 weeks after baseline) using the BDI eHealth research platform. Intervention participants will receive access to the BEAM program for 10 weeks upon completion of baseline, and the control condition will receive access for 10 weeks upon completion of the follow-up assessment.Recruitment for this trial began on July 21, 2020, with the first baseline assessments occurring on August 17, 2020. To date, 295 participants from 71 schools have completed baseline. Due to the unexpected success of recruitment in the first 3 waves, the final fourth wave has been abandoned. Intervention participants are currently receiving the program, with follow-up due for completion in March 2021.This is one of the first RCTs to examine the effectiveness of a web-based adolescent mental health training program for Australian secondary school educators in leadership positions. If found to be effective, this training program will offer a sustainable and scalable delivery method for upskilling educators in caring for students’ mental health.Australian New Zealand Clinical Trials Registry ACTRN12620000876998; https://covid-19.cochrane.org/studies/crs-14669208DERR1-10.2196/25870 Over half of all mental illnesses experienced by adults begin before the age of 18 years ,3. UnforDespite the recommendation by government bodies for greater training in adolescent mental health ,15, therAlthough all 6 programs were shown to be effective for improving mental health knowledge, none have yet been shown to be effective in increasing helping behaviors, for example, recommending or referring a student to seek professional help, or in reducing the distress experienced by educators ,25. In a. To accurately identify educators’ training needs, the BEAM program was initially developed in collaboration with an advisory group of teachers in general teaching and leadership roles. The group consisted of 12 school teachers from various secondary schools located in New South Wales (NSW), Australia. BEAM was originally designed for year advisors, given their role in maintaining student engagement and the well-being of an entire cohort of students. They also often act as case managers, linking students with services and resources when needed, and are usually the first point of contact for parents and teachers. However, there is no formal training for this role, and it is performed in addition to their regular teaching duties. Research on workplace mental health has indicated that training programs for managers can improve their mental health knowledge, thereby improving their confidence and increasing their helping behaviors toward their staff’s mental health needs [To fill this gap, the Black Dog Institute (BDI) developed the Building Educators’ Skills in Adolescent Mental Health (BEAM) program. BEAM is a web-based training program on adolescent mental health for secondary school educators in leadership positions, such as year advisors, heads of well-being, and principalsth needs -28. Furtth needs , improvith needs -28 whileth needs . This flmodule suggestion function was embedded that encourages the participant to complete modules based on their interest, and the program was optimized for completion on both mobile and desktop devices to increase accessibility. The eligibility criteria for BEAM have also been extended to encompass other leadership roles within the school, including principals, heads of well-being, and directors of pastoral care, among others. This decision was made because these staff members also have responsibilities regarding student well-being in addition to their regular teaching duties and are well placed to influence schools’ policies and possibly enact change. The program is now ready to be evaluated for its effectiveness using an RCT.A recent pilot study examined the acceptability of the BEAM program among secondary school year advisors (N=71) from NSW, Australia. After using the program for 6 weeks, the year advisors reported significantly higher levels of self-reported confidence in their ability to care for students’ mental health and lower levels of personal psychological distress. Year advisors also reported an increased frequency of helping behaviors at the 19-week follow-up. However, many of the year advisors did not complete the entire program  reporting that the 6-week duration was insufficient, and barriers such as forgetfulness hampered their completion. In preparation for this trial, several modifications were made to the program to increase engagement and completion: program access was extended to 10 weeks, SMS reminders in addition to email reminders were embedded, sequential module completion was removed so that participants can complete the modules in any order, a The primary objective of this trial is to evaluate the effectiveness of the BEAM program in improving secondary school educators’ confidence in recognizing and responding to their students’ mental health needs. The secondary objective is to assess BEAM’s effectiveness in increasing the frequency of help provided to students, improving educators’ mental health knowledge, reducing educators’ stigma toward others with mental illnesses, and reducing their own psychological distress.The primary hypothesis is that educators who are allocated to receive the BEAM program will report significantly higher levels of confidence at posttest (primary endpoint) when compared with the waitlist control condition and that these effects will be sustained at follow-up. It is also hypothesized that educators who receive the BEAM program will report greater improvements in mental health knowledge, stigma, and psychological distress at posttest and a greater frequency of helping behaviors at follow-up, when compared with those in the control condition.This study is a cluster randomized controlled effectiveness trial with 2 parallel conditions (the BEAM program and waitlist control), with measurements taken at baseline, posttest (10 weeks from baseline completion), and follow-up (22 weeks from baseline completion). This study protocol was approved by the primary ethics body of the University of New South Wales (UNSW) Human Research Ethics Committee . Approval was also sought and obtained from the NSW Department of Education State Education Research Applications Process (SERAP2020222) to conduct research within government schools and from the Catholic Schools Office Dioceses of Maitland-Newcastle, Canberra-Goulburn (schools located in the Goulburn area only), and Wollongong to conduct research with schools located within their dioceses.This research project is also guided by a trial management committee consisting of experts in research and trial design and service and program implementation to oversee and provide guidance on the study procedures. This committee meets bimonthly or more frequently on an as-needed basis.To be eligible to participate, secondary school educators must be (1) employed in a school leadership position that includes responsibility for student well-being ; (2) currently working in this role at a government, Catholic, or independent secondary school in NSW, Australia, for the duration of the study; and (3) obtain their principal’s consent for their involvement.Secondary school educators who participated in the pilot study are not eligible to participate in this trial.The target sample size for this trial is 234 participants from at least 47 schools. This calculation is conservatively based on the participation of an average of 5 educators per school and an intraclass correlation of 0.07, which yields a design effect of 1.28. To detect a standardized effect size of 0.50,  with 80% power and α=.05 (2-tailed), an individually randomized trial would require 64 participants per arm. This number is inflated by the design effect to 82 to allow for clustering, with the recruitment increased to conservatively allow for attrition of up to 30%. This yields a minimum of 117 participants per arm.Cluster randomization at the school level is used to avoid potential contamination and bias effects from other participants, reduce administrative tasks for schools, and enable implementation of the peer-to-peer component of the program. As such, all participants from the same school will be allocated to the same condition and complete the trial at the same time using randomly permuted block randomization with block sizes of 2 and 4. Schools will be assigned to either the intervention or control arm using a 1:1 allocation, stratified by school size (<400 or >400 students) and index of community socioeducational advantage (ICSEA) level (<1000 or >1000) as per a computer-generated randomization schedule. Randomization is conducted by a statistician not involved in the day-to-day running of the trial to avoid influence or bias. The research team will be aware of the allocation once registration is scheduled to begin because they are responsible for providing the link to participants for the intervention or control program study website. Participants will be unaware of which group they are allocated to during registration and baseline. Upon completion of baseline, they will be informed, via email, of their allocation. This is because the intervention participants will receive immediate instructions and access to the program, and the waitlist control participants will be asked to wait for their next survey.A passive approach to recruitment is being undertaken using study advertisements. The advertisements are being placed on the BDI’s website and social media channels , within BDI newsletters, and circulated to BDI mailing lists and contacts. The study is also being advertised in the NSW Health School-Link e-newsletters , Teacher Magazine, and Catholic Diocese bulletins. After viewing the study advertisements, interested educators are directed to a web-based expression of interest form on the BDI website, which collects their name, school, suburb, email, and role at their school. Once registered, prospective participants are encouraged to share the study information with their colleagues to increase cluster sizes and encourage peer-to-peer interaction. To promote a representative sample from metropolitan, regional, and rural locations, participation will be open to all government, Catholic, and independent schools within the Australian state of NSW for which we have ethical approval.After expressing interest, the educators are emailed the study information. Interested participants consult their principal to obtain a signed letter of support. The school and its educators are randomized after the letter of support is received by the research team. Only 1 signed letter of support is required per school.Educator consent is obtained online. Prospective participants provide consent by confirming the declaration statements in the web-based participant information sheet and consent form (PISCF). Participants can download the PISCF before providing consent, and they are emailed a copy for their records.withdraw, or completing the withdrawal form located within the PISCF. When a participant withdraws, all study data are retained, but no further data are collected, and all study communication ceases.Participants can withdraw consent at any time without providing a reason by contacting the research team, replying to any email communication with the word This trial will include 4 waves of registration and enrollment. A predetermined cut-off date indicates which wave a school participates in, as determined by the date on which the letter of support is received. Using waves ensures that data collection does not occur during summer school holidays, allows flexibility for when schools enroll in the trial based on their schedule, and ensures that participants from the same school commence the trial concurrently. Once all registered participants from a single school commence the baseline survey, no other prospective colleagues from that school can register. This prevents the influence that knowledge of group allocation might have on future participant enrollment. To avoid disappointment, educators are asked to tell their colleagues about the study at the time of recruitment.Participants are sent an email directing them to the study registration website 1 week before the scheduled baseline start date. Here, they are asked to confirm their eligibility, register their personal details , provide consent, and create a study account. They have the option to enter their mobile phone number to receive SMS notifications and reminders. Once completed, they await further instructions and access to the baseline survey.On the day each wave is due to begin, participants receive an email  inviting them to complete the baseline survey. The survey is accessible for 7 days, and participants who do not complete it are automatically withdrawn. This process is repeated for the 10-week and 22-week assessments. All participants receive 2 email reminders  for the survey completions.module recommendation question in the baseline survey. This question presents participants with a list of 10 topics (such as signs and symptoms and about my role) that are linked to the learning objectives of each module. Participants are then asked to rate the 3 they are most interested in learning about from 1 (most interested) to 3 (least interested). The program then recommends that they begin with the module corresponding to their first choice. Each module includes an optional peer coaching activity that asks participants to meet with a colleague from their school to discuss focus questions, practice, and apply program learnings. Participants then submit their responses to the focus questions through the program. The research team then send standardized feedback via email within 3 business days. Participants who do not have another colleague from their school taking part in the trial can either complete the peer coaching themselves, talk to another colleague who is not taking part, or skip the activity, as it is not mandatory. No other program activities are reviewed by the research team. All participants receive access to the program at no cost for 10 weeks, and it is estimated that the full program takes approximately 6.5 hours to complete. Participants can complete the program at their own pace; however, they are recommended to undertake 1 module per fortnight. Given the current COVID-19–related school closures and physical distancing guidelines, participants are encouraged to complete the peer coaching activities via teleconference or phone. Participants will receive fortnightly email reminders to use BEAM and optional SMS reminders. All program use data are collected by the BDI web-based eHealth research platform hosted on the UNSW servers.The BEAM program is a web-based training program accessible on any internet-enabled device. Each of the 5 modules consists of information, web-based interactive activities, and downloadable resources related to adolescent mental health. In this trial, participants can complete the 5 program modules in any order; however, an initial module is suggested to participants based on their response to the This study uses a waitlist control condition. Participants in the control condition will receive access to the intervention at no cost immediately after they complete the follow-up survey (22 weeks post baseline). If they do not complete the follow-up survey, they will receive access immediately after the survey has closed. They will receive access to the full program whether they have not completed the survey or not.Participants in both conditions will receive an Aus $15 (US $11.59) e-gift voucher to thank them for their time and completion of the posttest survey. They will also receive an Aus $15 (US $11.59) e-gift voucher after completing the follow-up survey. All e-gift cards will be emailed within 5 working days of a participant completing the survey and will be issued through GiftPay.recognizing a student with mental health problems) using a 5-point Likert scale ranging from 1  to 5 (very confident). Mean total scores are calculated to represent participants’ self-reported confidence in managing their students’ mental health needs. Total scores can range from 15 to 75, with higher scores indicating greater levels of confidence. Scores will be compared over time and between the intervention and control arms at each time point.The primary outcome for this trial is educators’ confidence in recognizing and responding to students’ mental health needs. This is measured using an adapted version of the confidence to recognize, refer, and support subscale from the study by Sebbens et al . Particispent time calming a student down) during the past 2 months. This is answered using a 4-point scale . Items are then summed to create a total score (range: 15 to 60), with higher scores indicating a greater frequency of helping behaviors.A modified version of the Help Provided to Students Questionnaire by Jorm et al  is used how would you rate your knowledge of the signs and symptoms of student mental health issues) from 0  to 4 (extremely). Items are then summed to create a total score (range: 0-16), with higher scores indicating greater knowledge of mental health.This is assessed using the Perceived Knowledge and the Perceived Awareness subscales from the Mental Health Literacy and Capacity Survey for Educators . Particihow would you rate your awareness of the risk factors and causes of student mental health issues) from 0  to 4 (extremely). Items are then summed to create a total score (range: 0-20), with higher scores indicating greater awareness of mental health issues.For the awareness subscale, participants are asked to rate their level of perceived awareness on a set of 5 statements  using a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Items are then summed to create a total score (range: 6-30), with higher scores indicating higher mental health literacy. Recognition of common mental illnesses is assessed using the remaining 6 items from the adapted MAKS (items 7-12), where participants are asked to rate whether they believe the conditions of depression, stress, grief, anxiety, self-harm, and substance misuse are mental illnesses using a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Participants are also asked to read 2 vignettes adapted from the study by Jorm and Wright [This consists of 2 constructs: mental health literacy and the recognition of common mental illnesses. These 2 constructs are measured using an adapted version of the 12-item Mental Health Knowledge Schedule  and 2 vd Wright . These vstudents with a mental illness could snap out of it if they wanted) using a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Items are then summed to create a total score (range: 9-45), with higher scores indicating greater levels of stigma.A modified version of the Personal Stigma subscale from the Depression Stigma Scale from Griffiths et al  is used Thinking back over the past 6 weeks, how often have you felt hopeless). Answers are given using a 5-point scale ranging from 1 (never) to 5 . Items are then summed to create a total score (range: 5-25), with higher scores indicating greater levels of psychological distress. The DQ-5 has high internal consistency and convergent validity [The Distress Questionnaire-5 (DQ-5)  is used validity ,37.Participants are asked to provide their name, age, gender identity, whether they identify as Aboriginal or Torres Strait Islander, current role at their school, duration of employment at their current school (years), overall experience as an educator (years), and experience in their current role (years) at baseline.yes or no or prefer not to answer).Participants are asked to indicate whether they have had a personal, family, or close friend experience a mental illness .Participants are also asked to rate how frequently they engage in self-care. This is to be answered on a 6-point scale , how they rate their level of mental health training (answered 0 none to date to 3 extensive training), the mental health training programs they have completed (free response), and how confident they are that an online program can meet their training needs .Participants are asked to rate how important they believe mental health training is for educators , school type , and whether their school is same sex (answered yes or no). Participants are also asked to indicate whether their school has a student well-being policy (answered yes or no) and staffing roles to support students’ mental health (answered yes or no). Participants are also asked to rate the degree to which mental health is their school’s priority (answered 0 not a priority to 4 high priority) and how responsible they feel for their students’ mental health and well-being . Participants are also asked to indicate, on average, the hours per week they spend supporting students’ mental health needs and how supported they feel by their colleagues, supervisor or employer, workplace, friends, and family .Participants are asked to indicate their school location . Participants are also asked how often then have contacted their students about mental health using technology (email or school e-learning platform); this is answered using a 4-point ordinal scale from 1 (never) to 4 (frequently).In response to COVID-19, participants in this trial are asked questions regarding helping behaviors that may have changed due to the pandemic. The first 3 questions, “Have you reached out to students in a way that is different than you have done so in the past because of COVID-19? ?”, “Have you implemented a service, program, or educational information session about mental health?”, and “Are there any other ways you have responded to your students’ mental health that isn’t covered here?” will require a The following measures will be obtained only from participants assigned to BEAM and will be used in subsequent research into factors that may moderate or mediate outcomes.Program use will be measured by the number of completed lessons (maximum of 27), collected automatically by the eHealth research platform.Program barriers will be identified using a 13-item list at posttest.Forgot about it and Didn’t have enough time); this is answered as yes or no. If a participant answers yes to the 13th item Other not listed above (Please specify), a mandatory free response textbox will appear for the participant to provide more detail.Participants will be asked to report if they experienced any of the listed barriers throughout the trial . This is answered using a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).Participants are asked to rate the extent to which they agreed with a set of 14 statements about the BEAM program (such as yes or no), and if yes, how frequently they met  and whether they found these activities to be valuable . Participants are also asked “What could we do to improve the program,” “Is there any content or topics you would have liked to have been covered in the training?”, and “Is there anything else you would like to say about the program and its value for you?” . Finally, participants are asked what device they completed the program on .Participants are asked whether they completed the peer coaching activities with a colleague (answered yes or no). If they answer yes, participants are asked to provide more detail (free response).Participants are asked to indicate whether the program content or resources were shared with other school staff and if any well-being programs had been implemented during the trial period , accounting for repeated assessments within individuals and a random effect to account for clustering within schools. Models will include the factors time, condition (intervention vs control), and their interaction, with the critical test of effectiveness being planned contrasts of this interaction from baseline to postintervention  and follow-up (secondary endpoint). An unconstrained variance-covariance matrix will be used to accommodate within-participant effects. The method of Kenward and Roger  will be Secondary and additional outcome analyses will involve contrasts comparing changes from baseline to follow-up analyses of secondary outcomes  from baseline to other occasions of measurement, using an MMRM approach, as described above. If the intervention is found to be effective, exploratory analyses will examine evidence for moderation effects, that is, whether the intervention was more effective for certain subgroups of the sample. This may include teacher attributes such as gender or age and school characteristics such as ICSEA status.Approval was obtained from the primary ethics body (UNSW HREC) on April 21, 2020, SERAP on July 21, 2020, Maitland-Newcastle Catholic Diocese on May 27, 2020, Canberra-Goulburn Catholic Diocese on June 12, 2020, and Wollongong Catholic Diocese on August 4, 2020. Recruitment of educators started on July 21, 2020, and the baseline for waves 1, 2, and 3 are complete. To date, 465 educators have expressed interest in participating in the trial. In total, 308 educators have registered and 295 have completed baseline, representing 71 schools. Due to the unexpected success of recruitment in the first 3 waves, the decision has been made to not go ahead with the final fourth wave. Intervention participants are currently receiving the program with follow-up due for completion in March 2021. It is planned that the results will be presented at both national and international conferences and submitted to peer-reviewed journals. The results will also be disseminated to stakeholders through reports and presentations and on the BDI website.This protocol describes the RCT of the BEAM program, a study that aims to evaluate the effectiveness of a new web-based mental health training program for secondary school educators in leadership positions. Through the provision of mental health information and interactive activities, the BEAM program aims to improve educators’ knowledge of adolescent mental health. It is anticipated that their confidence in managing their students’ needs and the frequency of help provided will thereby increase, whereas their stigma toward mental ill-health and their own levels of psychological distress will reduce.There remains a significant lack of available evidence-based mental health training programs for educators ,25 and fIf the effectiveness of the BEAM program is demonstrated through this trial, there are significant implications for how mental health training can be delivered to educators. For example, traditional educator training is typically delivered through face-to-face didactic-style workshops that require participants to take leave and have their classroom duties covered by another staff member . By deliThere are limitations to this trial that are acknowledged, including the reliance on self-report questionnaires, which may be susceptible to biases. Self-report outcomes, such as confidence, may not match actual educator behavior; however, we will use validated measures where possible and assess teacher reports of actual helping behavior.Another limitation is that the trial is being conducted among educators who self-selected to participate from within NSW only. The results may not be generalizable to interstate educators or educators who chose not to participate. Although Australia has a national education curriculum, schools are governed by each of the States’ and Territories’ Department of Education, and Catholic schools are governed by the Diocese to which they belong. Each has their own set of frameworks, policies, and rules that guide staffing. For example, there are structural differences between the states of South Australia (SA) and NSW, such that secondary school begins in year 8 in SA and year 7 in NSW. It may also be the case that participating educators are employed at better-resourced schools and have the time to take part. Furthermore, participation is limited to educators from schools for which we have approval from their governing ethical body and could obtain support from their school principal. Not all Catholic Dioceses in NSW granted approval to conduct this research, and gaining principal support might not have been possible for all interested educators.A further limitation is the use of waitlist control and trial length. The total amount of time a control participant is required to wait without any access to the intervention is 22 weeks, which may affect attrition. We have conservatively estimated a 30% attrition in our target sample size, and a monetary reimbursement will be used to motivate completion of the posttest and follow-up surveys. The waitlist control also only enables the assessment of whether the intervention is more effective than the passage of time. Future follow-up studies to compare the intervention with active controls are needed once effectiveness relative to waitlist control is established.Despite these limitations, this trial has several strengths, including the RCT design to examine the effectiveness of BEAM and the clustering and randomization at the school level to reduce the risk of bias and contamination. Once a school begins in the trial, no other educators from that school can enroll, ensuring that participants are not influenced by the participation of other staff members from their school. The standardized delivery of the intervention helps maximize the fidelity of the training being delivered to educators, ensuring that all participants receive the same standardized intervention. Other strengths include the suite of measures included to examine a range of outcomes; the long-term follow-up period; targeted recruiting approach to include educators from metropolitan, regional, and rural areas; exploration of possible moderators; and stratification of school variables to account for factors hypothesized to influence the results. If shown to be effective, the assessment of BEAM through an RCT will provide a novel method for delivering mental health training to secondary school educators.