Female and male participants, and participants from underrepresented and well-represented backgrounds, performed similarly on all bibliometric assessments. Finally, TST/TL1 Program participants outperformed students from other PhD programs at our institution. This analysis suggests that the TST/TL1 Program has been effective for participants, including those who are female and from underrepresented backgrounds.Research education and training in Translational Science develops and sustains a workforce to efficiently advance studies designed to improve human health. We evaluated the effectiveness of a Translational Science Training (TST) TL1 Program. Participants had significantly better publications/year, citations/year,  Research education and training in Translational Science (TS) develops and sustains a workforce to efficiently advance clinical and translational studies designed to improve human health. To meet this strategic goal, we operate a Translational Science Training (TST) TL1 Program (TL1 TR002647), a component within our Institute for the Integration of Medicine and Science (IIMS), which is home to our Clinical and Translational Science Award (CTSA) (UL1 TR002645) and serves the communities of Central and South Texas.The TST/TL1 Program was initiated in 2009, concurrent with our first CTSA. Initial support (2009–2013) was provided by a 5-year grant from the University of Texas System with matching funds from the University of Texas Health Science Center San Antonio (UTHSCSA). Thereafter (2013–2023), support was received from the National Institutes of Health (NIH) through a CTSA-related National Research Service Award (NRSA) provided by the National Center for Advancing Translational Sciences (NCATS).Trainees were selected annually using an NIH style, comprehensive, expert panel review of applications. Successful applicants received 1 year awards that included stipends plus research and travel support. Initially, the Program only supported predoctoral trainees, but in 2018, the Program was expanded to include both predoctoral and postdoctoral Trainees. This analysis is limited to those 66 predoctoral trainees who have completed TST/TL1 training so far.Since inception, the Program has enhanced the quality and scope of predoctoral research training through interdisciplinary Clinical and Translational Science (CTS) training and mentorship. Trainees have used our framework to construct individualized research training and career development programs that facilitated their capacity to move science into human studies and in the community.The primary activity of the TST/TL1 Trainee is to conduct research within the ongoing investigative program of an experienced scientist. The TST/TL1 Program oversees the mentoring process to ensure a supportive and effective mentoring relationship. Trainees must have a committed mentor when they apply to the Program. The Program takes steps to ensure mentor quality. Trainees who have Assistant Professors as mentors must also have more experienced comentors. All mentors are encouraged to complete training that introduces effective strategies for mentoring. Trainees are also offered training to help them better understand their role in effective mentoring. Trainees complete an Individual Development Plan (IDP) within 3 months of their appointment to the TST Program. Alignment of Mentor and Trainee expectations is documented in a required Compact, which is based on the AAMC Compact between Biomedical Graduate Students and Their Research Advisors [Trainees engage in required TS coursework that describes TS investigative efforts and unresolved hypotheses in a format that facilitates case-based discussions and debate. Course directors are successful TS investigators from medicine, nursing, dentistry, and pharmacy. Course content focuses on topics such as Translational Science, Responsible Conduct, Research Design and Analysis, Team Science and Leadership, Cultural Proficiency, Scientific Communication, Business of TS, and Evidence-Based Implementation and Policy.TST/TL1 programmatic activities, including TS coursework, ensure that Trainees recognize the relationship between applied TS and contemporary biomedical research. Monthly TST/TL1 Program Meetings reinforce TS concepts, community engagement, dissemination and implementation (D&I), diversity, equity, inclusion, and accessibility (DEIA), career development, mentoring, and wellness. Together with CTSA KL2 Scholars, TST/TL1 Trainees participate in a TS Roundtable that integrates concepts in process innovation, systems thinking, and boundary crossing, along with team science and cultural diversity. Trainees also participate in research laboratory activities/meetings, seminars/conferences/workshops, scientific meetings, and manuscript and grant preparation workshops.TST/TL1 Trainees are required to participate in a TS practicum course. This experiential learning course immerses Trainees in activities relevant to their primary research and encourages them to move their work along the TS spectrum. Over 6 months, Trainees undergo customized experiential activities like shadowing a clinician, assisting in a clinical trial, and exploring types of research that are new to them. The TS Practicum is highly individualized for each person, and Trainees are encouraged to include a community-engagement activity in their practicum.Thus, the Trainees gained awareness for scientific and cultural challenges in the translation of basic science observations and the interdisciplinary teams needed to support the continuum of TS for benefit in patient care, community, economy, and policy. The ‘phenotype’ of predoctoral Trainees at IIMS are trainees who are prepared for an impactful career as translational scientist or clinician-translational scientist.The primary objective of this analysis was to compare the bibliometrics of TST/TL1 Program participants and nonparticipants. Secondary objectives included comparisons of Program participants by sex and underrepresented status and comparisons of Program participants to students in other UTHSCSA PhD programs at our institution.h-index, and m-quotient. Numerical data were assessed for normality. Since they were not normally distributed, the Wilcoxon Rank Sum test was used to compare numerical data. Nominal data (sex and underrepresented status) were compared using the chi-square test, unless the expected counts were less than 5 in any cell; in which case, the Fisher’s exact test was used instead of the chi-square test. P-values less than a pre-specified alpha level of 0.05 were statistically significant.Bibliometric data were gathered using Scopus and included: publications per year, citations per year, coauthors per year, Among the 66 predoctoral TST/TL1 Trainees, 65% (43/66) were women and 29% (19/66) were underrepresented (UR) in science. Trainees produced an average of eight publications each since starting the Program and one-third subsequently received independent training awards .h-index, and m-quotient (m-quotient = h-index divided by years since first publication)  outperformed those who applied but were not selected for the Program (non-participants). Participants had significantly better publications per year, citations per year, n) Table .h-index than our IBMS students. TST/TL1 participants also had significantly more publications per year, citations per year, coauthors per year (possibly indicating more collaboration and teamwork), and higher h-index and m-quotient than our MD–PhD students. Finally, TST/TL1 participants also had significantly more citations per year than our TS PhD students.TST/TL1 participants also outperformed predoctoral students from our institution’s Integrated Biomedical Sciences (IBMS) PhD Program, MD–PhD Program, and TS PhD Program  Table . TST/TL1TST/TL1 participants outperformed nonparticipants and students from our institution’s IBMS Program, MD–PhD Program, and TS PhD Program on a battery of bibliometric assessments. Moreover, among TST/TL1 participants, males and females, and participants from underrepresented and well-represented backgrounds, performed similarly on all bibliometric assessments. This analysis suggests that the TST/TL1 Program has been beneficial for participants. Furthermore, the Program has been able to achieve similar bibliometric outcomes in men and women and in persons from underrepresented and well-represented backgrounds, which suggests that the Program’s approach to training those from backgrounds underrepresented in science is effective.The study has limitations, including possible selection bias, as participants for the TST/TL1 Program are selected by a rigorous NIH-style review panel and those with the best scores are admitted to the Program. Furthermore, the study did not systematically evaluate contextual factors, like student history, student maturation, scientific discipline, authorship patterns, and type of employment post-Program, which might mediate the findings.Nevertheless, it is encouraging that the TST/TL1 Program fared well when compared to other prominent PhD programs at our institution, and that participants from backgrounds underrepresented in science benefitted to a similar extent as those from well-represented backgrounds.


Pteropus poliocephalus) is an endemic Australian fruit bat, known to carry zoonotic pathogens. We recently showed they harbour bacterial pathogen Klebsiella pneumoniae and closely related species in the K. pneumoniae species complex (KpSC); however, the dynamics of KpSC transmission and gene flow within flying fox colonies are poorly understood. High‐resolution genome comparisons of 39 KpSC isolates from grey‐headed flying foxes identified five putative strain transmission clusters (four intra‐ and one inter‐colony). The instance of inter‐colony strain transmission of K. africana was found between two flying fox populations within flying distance, indicating either direct or indirect transmission through a common food/water source. All 11 plasmids identified within the KpSC isolates showed 73% coverage (mean) and ≥95% identity to human‐associated KpSC plasmids, indicating gene flow between human clinical and grey‐headed flying fox isolates. Along with strain transmission, inter‐species horizontal plasmid transmission between K. pneumoniae and Klebsiella africana was also identified within a flying fox colony. Finally, genome‐scale metabolic models were generated to predict and compare substrate usage to previously published KpSC models, from human and environmental sources. These models indicated no distinction on the basis of metabolic capabilities. Instead, metabolic capabilities were consistent with population structure and ST/lineage.The grey‐headed flying fox ( Klebsiella pneumoniae species complex (KpSC) , along with detection of mobile antimicrobial resistance and virulence determinants, is essential for elucidating the potential routes and/or modes of transmission into the human population.The KpSC have also been isolated from a wide variety of environments including soil , 18/50 from Camellia Gardens (population of 500–2249), 1/52 from Adelaide (population of ~10 000) and 0/52 from Centennial Park wild colonies (population of ~10 000–15 999) . In 2021, grey‐headed flying fox populations of Adelaide Botanic Park colony were 30 000–36 000 . Population estimates for the remaining colonies do not yet have data available. Notably, this was the first non‐human sighting of K. africana, a species which has been reported in just two previous studies globally  and virulence factors, suggesting that these grey‐headed flying fox colonies are not a high‐risk environmental reservoir for problematic KpSC isolates. However, this analysis did not explore detailed strain relationships, or the broader genetic content of these KpSC.Our previous surveillance study sampled KpSC from flying foxes and leverage these data alongside the previously reported draft genomes to perform the first high‐resolution analysis of KpSC strain and plasmid transmission dynamics within/between grey‐headed flying fox colonies. To better understand the potential for strain and plasmid transfer into the human population, we compare completed plasmid sequences from flying fox isolates to those identified among human‐associated KpSC, and utilize the latest genome‐scale metabolic modelling approaches to compare the metabolic capabilities of flying fox‐derived isolates to KpSC isolates from other sources.Here, we use long‐read DNA sequencing to complete the genomes of 13 KpSC isolates including 30 K. pneumoniae, one K. variicola subsp. variicola and eight K. africana were previously isolated from four different grey‐headed flying fox colonies  was not utilized in this study due to DNA contamination issues identified during high‐resolution analysis. See Table Thirty‐nine et al., Illumina (short‐read) whole‐genome sequencing data were generated and reported previously   Watts, .et al., https://doi.org/10.6084/m9.figshare.16609054)  were identified using RedDog version 1b.10.4  was explored, in comparison to KpSC from other host and/or environmental sources for which metabolic reconstructions have been published previously  was also inverted compared to the pFF1003_1 reference plasmid  . These included representatives of mid Fig. .KpSC plasmid (pINF116_1). This plasmid was identified from K. pneumoniae ST36 strain INF116, isolated from an Australian human urine sample in 2013 (GenBank accession: CP031793.1). Compared with pINF116, pFF1003_1 lacked many of the amino acid transport genes such as hisQ, hisJ and glnQ, but contained the additional tyrosine recombinase xerC, tRNA(fMet)‐specific endonuclease vapC and the putatively intact sialic acid degradation nan locus  showed 64% BLASTn coverage and 99% identity to the publicly available 141 kb human‐derived cus Fig. .KpSC have specific nutrient and metabolic requirements for growth, which likely influence their host range. To predict whether or not flying fox isolates could potentially colonize humans or other sources and vice versa, we constructed genome‐scale metabolic models for the grey‐headed flying fox isolates along with KpSC from other sources to identify metabolic commonalities and differences. We then simulated growth phenotypes in silico and overlaid these on the core genome phylogeny of 72 KpSC genomes. All KpSC isolates were predicted to utilize a core set of substrates accounting for 49.6% of carbon, 40% nitrogen, 72.9% of phosphorus and 40% of sulfur substrates tested  and FF930 , were separated by just 21 chromosomal SNVs  and FF1010 (K. pneumoniae ST1412) were highly similar , supporting a recent transmission event . In contrast, the plasmid variant harboured by FF1023 (K. pneumoniae ST5037) showed at least six deletions as well as a structural rearrangement, indicating a plasmid transmission likely occurred at some point in the more distant evolutionary history of these strains (either directly or indirectly via intermediary hosts). In that regard, it is possible that the pFF1003‐like plasmid may have been circulating within the Camellia Gardens colony for some time and/or has been introduced from a common reservoir multiple times. Aside from the presence of several selfish genetic elements including a higAB toxin–antitoxin system, intact conjugative tra locus (except in the case of pFF1023_1)  Fig. , this pFK. pneumoniae clinical isolate causing a urinary tract infection in a patient in a Melbourne hospital in 2013  with generally high coverage   Table  to at leKpSC strains and genetic material between niches , the results of the preliminary metabolic analyses presented here are consistent with niche overlap . We hypothesised that there may be metabolic differences between KpSC from flying foxes and those from other sources because occupation of different niches/hosts is likely associated with different nutrient availability, which are impacted by elements such as host diet. We note that our analysis was constrained to a small sample size and that there are likely many metabolic traits which are uncaptured within the metabolic models used in this study, as well as limitations of the current input database. Over time, this approach should become more robust as databases become more complete (https://www.genome.jp/kegg/docs/upd_map.html) (Kanehisa and Goto, KpSC such as K/O loci, previously discussed within the context of flying fox isolates by McDougall et al. (While much more work is required to fully understand the distribution and flow of l et al. ; howeverAppendix S1. Supporting Information.Click here for additional data file.


Loneliness is a public health concern that is associated with poor mental and physical health. Caregiving spouses of community-dwelling older adults often have high levels of caregiving burden, which make them more vulnerable to social isolation and loneliness. There has been a growing interest in third places as mediums for social interaction. Research on third places shows a positive association of greater access to third places with social networks and social health. However, this has not been tested in the context of caregiving. In this paper, we examined the role of various types of third places in reducing loneliness among caregiving spouses. We used the 2006-2016 Health and Retirement Study and the National Neighborhood Data Archive to examine the relationship between the availability of third places per square mile and loneliness. Third places include food outlets (e.g. grocery stores), eating and drinking places , commercial establishments , entertainment organizations , exercise facilities , religious organizations , civic and social organizations , personal care services , and social services for older adults . We found that caregiving spouses living in neighborhoods with greater availability of third places had lower levels of loneliness. We also found gender differences in the association. For instance, greater availability of eating and drinking places was associated with loneliness only among females. Increasing access to places that provide opportunities for social interactions may prevent social isolation and reduce loneliness among caregiving spouses.


Since 2013 the MCH Bureau has supported the National MCH Workforce Development Center to strengthen the Title V MCH workforce. This article describes the Center’s Cohort Program and lessons learned about work-based learning, instruction, and coaching.The Cohort Program is a leadership development program that enrolls state-level teams for skill development and work-based learning to address a self-identified challenge in their state. Teams attend a Learning Institute that teaches concepts, skills, and practical tools in systems integration; change management and adaptive leadership; and evidence-based decision-making and implementation. Teams then work back home on their challenges, aided by coaching. The Program’s goals are for teams to expand and use their skills to address their challenge, and that teams would strengthen programs, organizations, and policies, use their skills to address other challenges, and ultimately improve MCH outcomes.This process evaluation is based on evaluation forms completed by attendees at the three-day Learning Institute; six-month follow-up interviews with team leaders; and a modified focus group with staff.Participants and staff believe the Cohort Program effectively merges a practical skill-based curriculum, work-based learning in teams, and coaching. The Learning Institute provides a foundation of skills and tools, strengthens the team’s relationship with their coach, and builds the team. The work-based learning period provides structure, accountability, and a “practice space” for teams to apply the Cohort Program’s skills and tools to address their challenge. In this period, teams deepen collaborations and often add partners. The coach provides accessible and tailored guidance in teamwork and skill application. These dimensions helped teams in develop skills and address state-level MCH challenges.Continuing professional development programs can help leaders learn to address complex state-level MCH challenges through integrated classroom-based skills development, work-based learning on state challenges, and tailored coaching. What is already known about this subject? Prior studies have described public health team-based leadership development programs that combine instruction, team work-based learning, and coaching. Such programs can strengthen participants’ knowledge, skills, confidence, practices, and networks and help them improve programs, organizations, systems, and policies.What this study adds This study provides more detail about how interactive instructional methods, extensive work-based learning in teams, tailored coaching, and an evidence-based curriculum can help leaders learn to address complex state-level MCH challenges, including how learners experience the benefits of these methods.To improve public health (PH) today, leaders must develop partnerships and steer performance improvement at organizational and system levels  studies have concurred. A 2008 report identified systems thinking, change management, and general management as skills that MCH professionals needed to develop AMCHP, . The MCHIn response, the federal MCH Bureau (MCHB) has supported the National MCH Workforce Development Center since 2013. Headquartered at the University of North Carolina at Chapel Hill and with academic and practice partners around the nation, the Center offers training and development programs to equip the Title V workforce to meet today’s challenges and transform organizations and systems , a 6–8-month leadership development program that enrolls state-level teams and includes work-based learning to address a self-identified MCH-related problem at the state level . The article then describes what the Center has learned about how to structure the Cohort Program to improve “collaborative” or “shared" leadership skills.The Cohort Program builds on wider calls for professional development to use multiple learning methods over time to enable professionals to improve their workplace performance  in-person Learning Institute (LI) and 2) post-LI support. Its curriculum centers on three interrelated skills . Frequent team goals have included improving services for Children and Youth with Special Health Care Needs (CYSHCN) (25% of teams), building systems to improve services spanning multiple populations or topics (19%), improving child health (10%), improving adolescent health, women’s health, developmental screening, and family engagement in MCH (8% each), among others. To address these topics, teams have used Center skills to strengthen partnerships (19%), enhance service delivery (17%), strengthen and streamline screening systems (15%), strengthen health systems (15%), and enhance care coordination (12%), among other objectives. Box Box 1: Example Team ChallengesTeam Leaders from the state’s Medicaid, Oral Health, and Perinatal and Women’s Health units and the state’s Children’s Health Insurance Program (CHIP).Team challenge Update the state’s Children’s Health Insurance Program (CHIP) reimbursement policies to align with state Medicaid policies. Communicate the state Medicaid’s new policy of expanded coverage for fluoride varnish reimbursement to stakeholders, including medical and dental providers, in order to expand fluoride varnish use and ultimately reduce Early Childhood Caries.Approach to addressing the challenge The team used Center skills and tools, such as system support mapping and action planning, to plan how they would tell providers about the expanded varnish coverage and new billing procedures. The Cohort program enhanced the team’s strategic thinking and relationship-building skills, leading to many successes.Results The team celebrated two major accomplishments:Updated the state’s CHIP coverage policy to align with the State’s Medicaid policy.Surveyed nearly 180 providers statewide to assess their awareness and practices related to American Academy of Pediatric fluoride varnish recommendations. Used findings to identify opportunities for continuing education and referral systems.Team Department of Health unit leaders from the state’s Bureau of Family Health (BFH), Office of Health Equity, and Office of the Deputy Secretary for Health Promotion and Disease Prevention.Team challenge Build health equity skills of BFH staff so that staff can improve internal BFH progress on health equity and help BFH vendors develop health equity plans, ultimately improving MCH outcomes through better serving underserved communities.Approach to addressing the challenge The team used Center skills and tools to address their challenge, such as the 30/30, 5R’s, causal loop diagramming, measurement tables, and appreciative inquiry. These tools helped the team plan, engage with BFH employees and stakeholders, and measure progress.Results The team developed a health equity technical assistance document for internal administrators, implemented a BFH employee survey about health equity, and organized.BFH sub-teams. They developed a three-year work plan for the BFH Health Equity committee and began helping their vendors and grantees incorporate equity concepts into their work.This process evaluation is based on data from the following sources.At the LI's conclusion, travel team members complete an evaluation form that captures the most and least helpful aspects of the LI. Of 190 participants in the first five cohorts, 165 (86%) completed the form. Qualitative data from these evaluations from the first five cohorts were reviewed and categorized using inductive coding methods, with codes emerging from individual responses.A Center evaluator interviewed one self-selected team leader from each of the teams in the first five cohorts; a few states included a second team member in the interview. Interviews focused on this evaluation question: How did the Cohort Program help them advance their MCH population health goals through their team challenge? The interview guide included multiple choice, listing, and open-ended questions. Respondents were encouraged to circulate the guide to the other team members to solicit their input. The 32 interviews each lasted approximately one hour and were recorded and transcribed. Evaluators used ATLAS.ti software to code and analyze the transcripts using deductive codes based on the Cohort Program’s objectives and inductive codes that emerged from the interviews. The evaluators used the “Sort and Sift, Think and Shift” qualitative analysis approach developed by ResearchTalk, Inc. . A combination of small group discussions and a summative full group discussion were used to promote candid feedback and provide everyone with adequate opportunity to share their thoughts. Both small and summative group discussions focused on these questions: (1) What is most effective about our current approaches? (2) What are the primary tasks of the workforce we serve? How is the Center helping them get their tasks done? (3) How can we improve? The evaluation team recorded the responses, and then coded and analyzed them for major themes. For this paper, the evaluators used the data and themes that pertained to the Cohort Program.We present insights from participants and staff about how the Cohort Program’s structure and processes help it accomplish its objectives, in three categories: Work-Based Learning in Teams; the Learning Institute; and Coaching Fig. .Fig. 2BeWork-based learning requires teams to apply new skills to concrete challenges and provides structures and accountability for doing so, while also building their teams.I’ve had implementation science as part of a college … program but being able to actually have the didactic … [along] with the real live world problem just helped it come to life.One learner stated that the Cohort Program provided a “practice space” to progress from understanding a concept or skill to using it with a real challenge. This allows the skills and tools to “come to life” and become part of the leader’s active repertoire:…[T]he Center differs [from other training programs] in the sense that it was completely state-driven in terms of what projects [challenges] we wanted to work on.You all approve the project and then you let us drive the project. You gave us tools that we needed to drive the project, but we were the actual drivers on the project.The Cohort Program’s “practice space” allows each team to choose a challenge and design its adaptive solution to it. These participants noted:You guys didn’t give us a magic pill or a magic answer. You gave us tools to help us critically think through … this project but then [also apply] those tools to help us critically think and tease-out other complex problems that we had.Center staff concurred, noting that teams learn to apply conceptually difficult “skills and concepts to specific MCH contexts, to make them more real and applicable to Title V,” and that “learning happens in the context of hard, often adaptive Title V challenges being addressed.” In this way the Cohort Program “supports actual implementation practice” and systems strengthening “around something states are already struggling with.” This is aided by Center staff “stick[ing] with folks over time,” often enabling the staff to see organizational or practice improvements by the Cohort Program’s end. Staff said the Cohort Program “teaches people to fish” and participants “feel empowered rather than overwhelmed” in addressing systemic challenges.Other participants emphasized the benefits of the Cohort Program’s requirement for the team to reflect on a difficult challenge and select, integrate, and apply skills to develop creative solutions. This is central to the Cohort Program’s emphasis on teaching teams to use “adaptive leadership” to develop tailored “adaptive solutions” instead of relying on outside experts or simple “technical solutions” already in their repertoire. Participants referred to this benefit as making them “sit down and think … outside the box” and giving them the “time where we could really explore the mutual learning [model] and use tools to think about things and be creative.” In this quotation, “mutual learning” refers to a teamwork model that encourages members to listen to others’ reasoning to construct shared solutions, rather than trying to win the argument. Thus, these benefits—developing adaptive solutions through mutual learning—flow from critically reflecting on a challenge as a team:Work-based learning also strengthened teams’ ability to collaborate to address challenges.One way the Cohort Program strengthened teams was simply by requiring them. One participant said that the Cohort Program “made us come together to focus on a population health initiative.” Another noted that while their team members—as staff of state agencies—had worked together to some degree beforehand, the Cohort Program “provid[ed] the opportunity formally through the initial [LI and] through the site visit, for us to be brought together and be able to spend … a few days … together. I think that was really valuable because we—all of us—move at such a rapid pace.”[W]henever I talk about home visiting, I automatically think of early intervention. I mean… we remember each other more. We’re more intentional in terms of how we talk about the system…. I think that was transformative as well.The Cohort Program also built teams through LI activities that fostered mutual understanding and collaboration. One participant explained that although their team previously “kind of knew each other,” convening for the LI was “kind of like a golden age where you’re in the incubator” and that the “personal time we had in Chapel Hill really sealed the deal.” As a result, this participant explained that they now “automatically” take the perspective of their teammates and consider the entire “system” when reflecting on their team challenge:[What] our team… found most helpful was the actual team building…. There are a couple of partners who … work quite a distance from us and having that time together really built those relationships, really kind of instilled more trust among those partners.[The] in-person training was really great…. it really did help us kind of bring together a group of stakeholders throughout the state to do this work and really align the efforts, which was the goal of the project.Others also described team building at the LI as beneficial:One participant noted, “Just being intentional [in bringing in new team members at the LI] really kind of refocused us on being intentional… when we have new people come into [the team]—how we kind of integrate them into that process….” Another noted that the LI had given them “the capacity to do this work and [learn] how to bring people together to do this work…. By being able to bring us together and create the partnerships that we’ve had has really created a trust in this work that people are doing in breastfeeding.”[W]hat [the Program] really did allow for our team to do is when we came out with our finished product and our plan, we had an entire statewide team that was on board with the vision and … we had a united front within ourselves… [W]ithout the Center being there to help be that facilitator, we would not have, we wouldn’t be where we are now.Center staff agreed that the Cohort Program helps “states partner across organizational/disciplinary lines” and “strengthens collaboration with other agencies [and] groups” because it “provide[s] a reason to interact, build relationships, and tools/coaching to support effective relationship-building.” Another staff member said this added credibility in building partnerships gives the Title V agency additional influence and authority, placing its leaders in the center of efforts in which they might otherwise be sidelined.One participant noted, “The Center really provided us a lot of credibility.… For our MCO’s [Managed Care Organizations], for our other partners… the Center gave us that credibility that helped to bring them to the table.” Another said the Cohort Program had helped them convene a large team that enhanced the credibility of their deliverable:[T]his [program] was more so really about accountability and keeping us moving forward… focused on results… which is something that we needed.... [M]ost … [training programs] you go to are usually for like a day and then you’re done. People take the training and they throw it on a shelf and they move on but when you have somebody that interacts you with people a little while, it’s kind of hard to just let it drop.One participant said the Cohort Program “forced us to set aside time and really focus on … these specific activities which is sometimes what you need to do,” while another said the “Center was helpful in keeping us on task and making sure that we followed through.” One attributed this to the Center’s structured approach, noting that “there’s so much value to doing … this structured work. It really … helps with accountability. It moves our project along. Whenever we start deviating, we can always go back to like the intent of the project and look at our tools and the logic model and get back on track.” Another attributed accountability to the proactive work of the coach, who helped keep the work “front and centered.” Another commented:The LI provided skills along with instruction and experience with building teams and an opportunity to learn about other teams’ work.The tools like the system support map helped us understand one another’s responsibility and expectations.When asked to explain how they found the LI useful, some respondents described learning to use all the Cohort Program’s skills and tools. Others mentioned specific skills:[take] tools to team time and using them to further define our project aims, goals, objectives, and outcomes.”When asked to describe the LI’s most effective aspects, many participants noted its instructional design, which involves presenting a concept or skill along with an applied tool that will help the team use it in practice; demonstrating with an example how the tool may be used; and “team time” to apply the tool to the team challenge with the coach’s help. One participant said it was helpful to “As we discussed fully above, the Cohort Program requires that teams enroll and collaborate intensively at the LI to address their challenge. The LI also teaches them to use several tools specifically designed to build teams. In these ways, the LI strengthens leaders’ capacity to build professional teams.Learners also reported that the Cohort Program’s accessible and tailored coaching was invaluable in helping them apply skills and tools to their work.[The LI] gave us the backbones of what we can do. But then when … [the] coaches came [for the site visit] - I felt like it was then, “Okay now we can apply this to what we’re doing.”I think coaching was 90 percent of the [Program] experience. I mean, the [3-day] meeting in North Carolina was a good orientation and foundational piece of it, but I think that the coaching was the primary part that was helpful.Some participants also said that while the LI provided a “backbone” or “orientation and foundation,” their new skills and tools were deepened by the subsequent coaching to address their challenge.I felt like I had great support during the past several months. You know, I could always call up [the coach] and ask questions, kind of talk through some ideas.Many participants noted that coaches' accessibility and responsiveness helped teams make progress on their challenges:[In the Program] you have a coach that seems dedicated to your team… It’s not one size fits all. It seems very tailored.The difference between [other training] and the workforce Center was we developed really close relationships with the people from the workforce Center and it just felt like, “We know these people or they know us” and we’re comfortable in saying “You know, this is what we have right now, this is the problem. How can we resolve this? Can you help us?” - without trying to hide anything.Having [our coach] sit at our table [at the LI] the entire time, work with us, know where we started from, having the calls and the coaching, [helped us] know we’re not having to catch her up every single time we talk. She knew where we were; that was incredibly helpful.Center staff agreed that a helpful feature of the coaching was that it offers “tailored navigation through the tools and resources available” that is “customized to whatever state needs dictate.” They noted that a success factor is the coaches’ "interpersonal expertise” and that teams have “a dedicated coach … [resulting in] a rich relationship that supports and connects teams over time to Center resources” and adapt to teams’ evolving needs.Participants appreciated the coaches’ tailored guidance:Many participants commented that the LI was very intensive and taught too many concepts in a short period of time. This led to inadequate time for teams “to process and apply what we have learned” to challenges and “to reflect and let [a concept] sink in at the moment it's taught,” as participants put it. Relatedly, many teams wished for additional time with coaches to help them apply the material to the challenges and plan their approach. Others asked for more time to rest. The staff responded to these suggestions by greatly decreasing the amount of content addressed in later cohorts. Others recommended increasing opportunities to network with other teams and simplifying the Cohort Program’s learning management system, among other technical concerns. A few participants suggested that the staff could reduce the LI’s intensity by providing readings or webinars on key concepts before the LI so that more time at the LI could be given to application. In the focus group, the staff made several suggestions that the program took up, including moving some content to short asynchronous modules for use after the LI by participants and their teams, and structuring shorter synchronous skill-training institutes that participants could use to review the material or promote to their teams.Participants and staff believe that the Cohort Program effectively merges a practical skill-based curriculum, work-based team learning, and coaching. The LI provides skills and tools with opportunities for practice, strengthens teams’ relationships with their coach, and builds the team. Subsequent work-based learning provides a lengthy “practice space” for teams to think through their challenge and creatively apply skills to address it. Teams value close relationships with their coach, who provides accessible and tailored guidance in navigating team relationships and their challenge.This article contributes to the literature by describing in detail a program that helps participants learn to use in the workplace skills that are essential for improving PH systems today, including systems thinking and integration, evidence-based decision-making and implementation, change management, adaptive leadership, and improving equity in services and outcomes . Much of this evaluation’s improvement-oriented data was gathered after the Learning Institute; future process evaluations could ask more systematically at the program’s conclusion for participant input about ways to improve it. Additionally, efforts could be made to ask for participant feedback at multiple time points throughout program implementation. Future evaluations should also more formally record staff views on program strengths and areas for improvement, such as the focus group notes that this evaluation used; Cohort Program leaders have quite often, but mostly informally, sought and used staff ideas to improve the program. Staff focus group participants may have hesitated to share areas for program improvement since Center leaders were present, but we think staff felt free to offer corrective feedback because the program culture encouraged transparency and continuous improvement.Too often, continuing professional development programs still rely on the “update model” described by Nowlen , in whic


Listening programs enable hearing aid (HA) users to change device settings for specific listening situations and thereby personalize their listening experience. However, investigations into real-world use of such listening programs to support clinical decisions and evaluate the success of HA treatment are lacking.We aimed to investigate the provision of listening programs among a large group of in-market HA users and the context in which the programs are typically used.First, we analyzed how many and which programs were provided to 32,336 in-market HA users. Second, we explored 332,271 program selections from 1312 selected users to investigate the sound environments in which specific programs were used and whether such environments reflect the listening intent conveyed by the name of the used program. Our analysis was based on real-world longitudinal data logged by smartphone-connected HAs.Speech in Noise, which is frequent among users and often provided when other additional programs are also provided. We also identified 2 secondary additional programs (Comfort and Music), which are frequent among users who get ≥3 programs and usually provided in combination with Speech in Noise. In addition, 2 programs (TV and Remote Mic) were related to the use of external accessories and not found to be associated with other programs. On average, users selected Speech in Noise, Comfort, and Music in louder, noisier, and less-modulated  environments compared with the environment in which they selected the default program, General. The difference from the sound environment in which they selected General was significantly larger in the minutes following program selection than in the minutes preceding it.In our sample, 57.71%  of the HA users had programs for specific listening situations, which is a higher proportion than previously reported, most likely because of the inclusion criteria. On the basis of association rule mining, we identified a primary additional listening program, This study provides a deeper insight into the provision of listening programs on a large scale and demonstrates that additional listening programs are used as intended and according to the sound environment conveyed by the program name. Untreated hearing loss is a widespread condition  that hasSpeech in Noise and Music) [Therefore, programmable multimemory HAs have been introduced, which enable providing the user with multiple listening programs for specific listening situations. Currently, 41% of HA owners have such programs . Listenid Music) . Thus, pTo benefit from listening programs, HA users need to be able to characterize the listening environment adequately and actively select the appropriate program . PreviouAlthough different listening programs can potentially be beneficial and discernible for HA users, little is known about their real-world use. De Graaff et al  performeThese studies suggest that some HA users value and use the option to switch between listening programs. However, the existing literature is sparse and dated.Speech in Noise program in noisy environments) during everyday life [While listening programs investigated in older studies used to set a constant level for an audiological parameter , nowadays listening programs set dynamic rules for contextually adapting the parameters . However, some questions remain unanswered. First, it is not clear what motivates an HA user to obtain a multimemory HA and manually switch between programs and in which listening situations users particularly seek device personalization. Second, as highlighted in the aforementioned systematic review, little is known about the correct use of programs designated for a specific listening environment . Indeed,day life .Furthermore, most of these studies relied on self-reported measures collected over a short period. Indeed, they used diaries or questionnaires in which HA users reported use, preferences, and details of the listening environments. Whether the appropriate program is used in each listening environment cannot be derived from these data . MoreoveWe aimed to investigate the provision and context of use of multimemory HAs by leveraging objective data logged by smartphone-connected HAs from in-market users across several countries. First, we investigated the provision of multiple listening programs for various listening environments. Namely, we examined how many and which programs HA users have and use and whether some programs are commonly provided together. Second, we explored whether HA users use specific programs in distinct listening situations and whether such situations reflect the listening intent conveyed by the name of the program. We did so by focusing on users who repeatedly use specific programs and investigating the sound environment in which such programs are selected.This study used data from a large-scale internal (Oticon A/S) database, which stores logs of HA use of HA owners who have signed up for the HearingFitness feature  via the No additional ethics approval was necessary for this study according to the Danish National Scientific Ethical Committee .Using the fitting software, the hearing care professional can provide an HA user with up to 4 listening programs , by selecting from a list of predefined listening programs, by fine-tuning and renaming predefined listening programs, or by freely creating new ones. The hearing care professional can decide on both the quantity and the order of the provided listening programs by assigning a specific program to the preferred memory slot. In addition, when the user uses some accessories , the HA adds special programs on top of the 4 available memory slots.When the HAs are connected to the smartphone, the HearingFitness feature logs time-stamped data about the interactions with the HAs, such as the selection of specific listening programs. To account for different phrasing or different languages adopted by hearing care professionals when naming the programs, similar program names were coded in fewer categories. Moreover, when the HAs were connected to the smartphone, time-stamped continuous data about the sound environment were collected every 10 minutes, and every time a listening program was selected by the user. Such data represent acoustic characteristics of the momentary sound waves sensed by calibrated HA microphones at ear level. Namely, the sound pressure level (SPL), the noise floor (NF), and the sound modulation level (SML) in decibels were measured across a broad frequency band (0.1-10 kHz) .The SPL is the level output estimate from a low-pass infinite impulse response filter with a time constant of 63 milliseconds . The SPLThe provision of listening programs was investigated by including users who have usage information for at least 20 hours and analyzing, for each user, the programs that have been selected at least once in the 4-month period. The 20-hour threshold was adopted to ensure that the program provision was evaluated for users logging sufficient data while still including as many users as possible.1,p2,…,pn}p and a set of users U={1,u2,…,um}u, where each user is provided with a subset of the programs in P, a rule is defined as an implication of the form X⇒Y, where X is the antecedent, Y is the consequent, X,Y⊆P, and X∩Y=∅ [General) was excluded. Indeed, the default program is available (chosen or prescribed) for nearly all users and including it in the association rules would not be of interest. Instead, the association rules related to the 5 most frequent additional listening programs were inspected. The rules were evaluated based on several metrics, including support, coverage, confidence, and lift [arules package [We explored the provision of listening programs by computing the number of programs provided per user and by analyzing the name and usage of the most frequently provided programs. Furthermore, we investigated the relationships between programs by determining the association rules  using thnd X∩Y=∅ . In deteand lift . The supand lift . The conand lift , measuriand lift . Finally package .Provision of Listening Programs section, only a relevant subset of the listening programs was included.Contextual program use was evaluated by analyzing the sound environment  during program selection. For each logged selection of a specific listening program, the sound environment measured in a 10-minute time window centered on the program selection was considered . For each program, only users with at least 5 selections were included. Such a threshold was chosen to ensure that users’ behavior was inferred from a representative sample of program selections while, at the same time, not discarding too many users. Moreover, based on the analysis described in the General).For visualization purposes, the sound environments occurring during repeated selections of a specific program by the same user were averaged. We visually compared the distribution of users by their average sound environments occurring when selecting a specific listening program versus their average sound environments occurring when selecting the default program , associations between program selections and sound environment were analyzed by using linear mixed effect (LME) models, as recommended by Oleson et al . Specifii indexes all observations , j indexes the participants (J=1312), k indexes the time of the day (K=24), and Y is the sound environment  occurred in a 10-minute time window centered on program selection. The selected listening program (PROGRAM) was treated as fixed effect, while  and  are the random intercepts, respectively for the j-th participant and k-th time of day (in hours).where In addition, to account for differences in participant behavior, we fitted the data with 3 random intercept and slope models defined as the following:1jPROGRAMijku, where  is the random slope varying across participants for the program effect. These relatively more complex models (equation 2) were compared with simpler models (equation 1) by conducting likelihood ratio tests.where compared with the simpler model (equation 1), the only additional term is Furthermore, we investigated whether the sound environment changed before or after the program selection by analyzing the sound environment measured in the 5 minutes preceding each program selection and the 5 minutes following it. The difference in sound environment before and after program selection was assessed by 3 separate LME models defined as the following:i indexes all observations , j indexes the participants (J=825), k indexes the time of the day (K=24), and Y is the sound environment . The selected listening program (PROGRAM) and the time window  were treated as fixed effect. The interaction between PROGRAM and TIMEWINDOW was introduced to test whether the difference in sound environment levels before and after program selection depends on which program is selected. Finally,  and  are the random intercepts, respectively, for the j-th participant and k-th time of day (in hours). By conducting likelihood ratio tests, these models were compared with simpler models excluding PROGRAM. Moreover, by conducting post hoc ANOVA tests, the significance of the variables included in equation 3 was tested. Finally, pairwise comparison (ANOVA) tests were performed on the estimated marginal means from the interaction model to test the difference in the sound environment before and after selection of each listening program.where lmerTest  and emmn 1.74-1 ) packageMethods section resulted in a total of 32,336 users and 67,996 programs provided. On average, the sampled users had a connected HA use of 5.88 hours per day. However, when only considering days with at least 1 hour of connected HA use, the average connected HA use amounted to 8.81 hours per day.The data processing described in the General  and 11.67%  of the users had a TV and Remote Mic program, respectively. These programs are related to the use of an accessory, such as a television adapter and a remote microphone.Among the HA users, 57.71%  had >1 listening program . Almost General . This meGeneral was the most used program, accounting on average for 78% of the HA use time. Speech in Noise, Music, and Comfort, respectively, accounted for 13%, 7%, and 15% of HA use time. TV and Remote Mic accounted for 20% and 2% of HA use time, respectively.In addition to the provision of programs, their use was investigated by computing the percentage of time spent in each program for users with that program and at least another program. General was not considered as it is uniformly provided and is not an additional listening program. The detailed metrics of the selected rules are presented in Speech in Noise was not only the most common additional listening program but also a primary program that users get when also getting secondary programs. Indeed, Speech in Noise was the consequent of all selected rules, while either Comfort or Music was always in the antecedent set. As shown by the confidence metric in Music (rule 1) or Comfort (rule 2), respectively, also had Speech in Noise. Similarly, 78.76% (801/1017) of the users who had both Music and Comfort (rule 3) also had Speech in Noise. For these rules, the lift is >1, indicating that users are more likely to have Speech in Noise when they also have Music or Comfort. In contrast, although TV was a frequently provided program, users who had such programs were not more likely to have other listening programs.Investigating the association rules with support ≥0.02 and confidence >0.5  enables General program regardless of the number of additional programs. Among the users that have 2 programs, Speech in Noise, TV, and, to a lesser extent, Remote Mic are more likely to be available than Music and Comfort. For users with 3 or 4 programs, the likelihood of having the primary program Speech in Noise grows linearly, the likelihood of having TV or Remote Mic remains relatively constant, and the likelihood of having secondary programs Music and Comfort increases.Provision of Listening Programs section, we investigated the sound environments in which a relevant subset of the listening programs was used. We focused on programs that convey a specific listening intent, whether they are primary (Speech in Noise) or secondary (Comfort and Music). These 3 programs are meant to be used in specific listening situations and are not related to the use of an accessory. The data processing described in the Methods section resulted in a total of 332,271 program selections from 1312 users.Since the findings presented in the Speech in Noise) was selected in different listening situations compared with the default program . The upper graphs in Speech in Noise and General. Users selected Speech in Noise in louder (higher SPL), noisier (higher NF), and less-modulated (lower SML) sound environments. Indeed, on average, users selected Speech in Noise at 55.1 (SD 7.4) dB SPL, 46.9 (SD 7.0) dB NF, and 17.1 (SD 4.9) dB SML, while they selected General at 53.0 (SD 5.6) dB SPL, 44.5 (SD 5.2) dB NF, and 18.2 (SD 3.5) dB SML. The likelihood ratio tests documented that the more complex LME models  fit the data significantly better than the simpler model (equation 1) with only a random intercept for each participant . The more complex model (equation 2) was fitted by setting the General program as the baseline condition. The coefficients of the more complex LME models . The coefficients also indicate that the scale of the difference ranges from around 0.09 to 0.19 SDs (z-score); that is, 9% to 19% of the overall SD. Moreover, inspecting individual users, the lower graphs in Speech in Noise in environments characterized by higher SPL, higher NF, and lower SML.First, we analyzed whether the primary program (E models  confirmeComfort and Music) were selected in specific listening situations. As shown in P<.01) sound environments compared with the sound environment in which they selected General. Subsequently, equation 2 was refitted by changing the contrast so that the Speech in Noise program represented the baseline condition. This made it possible to compare whether Comfort and Music were selected in different listening situations compared with Speech in Noise. Comfort was selected in less-loud  and less-modulated  environments, whereas Music was selected in less-loud  and less-noisy  environments.Second, we analyzed whether the secondary programs  and all 3 sound environment features , a difference from General was observed throughout the whole 10-minute time window. In addition, the sound environment difference appeared to increase after program selection.Finally, we investigated the extent to which the sound environment changed from before to after the program selection. 26=711.0, P<.001χ; NF: 26=1597.4, P<.001χ; and SML: 26=749.2, P<.001χ) showed that the more complex models  fit the data significantly better than the simpler model (only including TIMEWINDOW).The likelihood ratio tests . This suggests that the difference in sound environment before and after program selection depends on the specific program. The marginal effects predicted by the interaction term PROGRAM×TIMEWINDOW are shown in Before and After) confirmed that the sound environment gets quieter, less noisy, and more modulated  in the time window after the selection of General (compared with the time window before the selection). In contrast, the sound environment became louder, noisier, and less modulated  after the selection of Speech in Noise (compared with before the selection); noisier and less modulated (both P<.001) after the selection of Comfort; and louder and noisier (both P<.05) after the selection of Music.Moreover, post hoc ANOVA tests revealed that the interaction between This study investigated the provision and context of use of HA listening programs by analyzing real-world data logged through smartphone-connected HAs.General default program. According to a previous study analyzing self-reported data, 41% of HA owners have a program button or switch to change the HA response for different listening environments [Most HA users in our sample  were found to have listening programs for specific listening situations in addition to the ronments . The incronments .Speech in Noise was the most commonly provided program. By association rule mining, Speech in Noise was also found to be a primary additional program that users tend to get when also getting other secondary programs, such as Comfort and Music; that is, it rarely occurs that users are provided with Comfort and Music but not with Speech in Noise. This suggests that when users either request or are recommended additional listening programs for specific listening situations, Speech in Noise is provided as the primary step. This finding is consistent with previous studies reporting that HA users most frequently struggle when there is background noise [Comfort and Music resulted to be secondary programs, frequently provided in combination with Speech in Noise and more likely to be provided to users having 3 or 4 programs. Similar to Speech in Noise, these programs signal the interest in personalizing the listening experience in a specific listening situation; that is, when it is noisy but there is no need to communicate and when listening to music. Although these situations are not as prevalent as communicating in noise, users highly motivated to personalize their experience can still benefit from adopting specific listening programs for these situations. The prevalence of the Music program is consistent with previous studies finding that between 30% and 67% of HA users may encounter difficulties with listening to music [In addition to the default program, nd noise ,12,13 ornd noise , and connd noise . Comfortto music ,52 and ito music . A listeto music .TV and Remote Mic were provided differently than the other programs. They were frequently provided to users having only 2 programs , but they were not frequently provided in connection with other additional programs, and their prevalence did not increase among users having >2 programs. This might be explained by the fact that such programs are related to the use of a television adapter  or a remote microphone. Therefore, such programs show an interest in using the accessory more than in contextually adapting the HA settings through a listening program. The TV program was the most used program (20% of the time) besides the default program. In contrast, the Remote Mic program was only used 2% of the time. These findings suggest that the television adapter is extensively used by its owners, while the remote microphone is used in isolated occasions. In addition, it should be noted that selecting the TV program can actively modify the sound environment by either silencing the television or maintaining a normal level for other members of the household while reproducing the sound directly into the HAs. Therefore, TV and Remote Mic were not included in the sound environment analysis.Despite being common programs, Speech in Noise, Comfort, and Music were selected. First, we found that, on average, users selected Speech in Noise in louder, noisier, and less-modulated environments compared with the environment in which they selected General. This proves that HA users select the Speech in Noise program in environments that possess distinct characteristics and that better resembles a conversation in noise. Second, Comfort was also selected in louder, noisier, and less-modulated listening environments compared with General, suggesting that HA users select it when they want to get relief in noisy environments. Interestingly, HA users selected Comfort in less-loud and less-modulated environments than when selecting Speech in Noise, indicating that Comfort is activated in situations with fewer auditory signals and likely with the intent of increasing the pleasantness of nonspecific listening. Third, Music was selected in louder, noisier, and less-modulated listening environments compared with General, but in less-loud and less-noisy environments compared with Speech in Noise. The music playing in the environment might explain the higher loudness and noise, although not as extreme as the Speech in Noise scenarios. Overall, considering that HA users are typically counseled to use a program in a specific listening situation [Subsequently, we analyzed the sound environment in which ituation , our finSpeech in Noise, Comfort, or Music than when selecting General. Specifically, the sound environment gets louder, noisier, and less-modulated in the time window following a selection of Speech in Noise, while a selection of Comfort leads to nosier and less-modulated environments, and a selection of Music leads to louder and nosier environments  are promising candidates for predicting the selection of an additional listening program over the default program. Complementing such objective sound environment features with more subjective contextual features and with an evaluation of the listening experience  might also enable a deeper understanding of the provision and use of HA listening programs.


In 2013 the Royal Australian and New Zealand College of Ophthalmologists partnered with the Cambodian Ophthalmological Society (COS) to develop a continuing professional development program for COS using a college-college twinning model. The program was reviewed seven years after launch. No evidenceof a functioning CPD program was identified. Reasons may include lack of engagement by ophthalmologists and lack of COS resources. A planning checklistfor international CPD collaborations is discussed. In 2013, under the auspices of the International Agency for the Prevention of Blindness and Vision2020 Australia East Asia Vision Program, the Royal Australian and New Zealand College of Ophthalmologists (RANZCO) accepted an invitation to partner with the Cambodian Ophthalmological Society (COS) to collaboratively develop a Continuing Professional Education program (CPD) for COS [CPD programs may be reviewed using a modified Kirkpatrick model where the lowest level measures attendance at CPD events and the highest-level measures improvement in public health outcomes , such ascambodiacos.com) and by email and printed mail to past and present office-bearers. We intended to survey Cambodian eye-care practitioners using the same questionnaire as previously [We attempted to contact COS via its website (eviously  and to pCOS and its office-bearers were not able to be contacted. The COS website was inactive. We have no evidence of development of a community of practice of Cambodian ophthalmologists. The Cambodian Medical Council did not respond to email. We concluded the CPD program to be non-functional, although it is not possible to exclude ophthalmologists undertaking self-initiated and self-recorded CPD activities. Similarly, the LINKS program was not able to develop online CPD, although there was some progress in regional CPD .Likely multiple reasons underpin the apparent failure of the CPD program. Lack of engagement from Cambodian ophthalmologists was identified early as a potential problem and probably continued despite efforts at engagement by educational meetings and instructional workshops . Lack ofLessons learnt are consistent with the requirements for successful collaboration recommended by Eastwood et al. , includiMore research is necessary to determine optimum methods to establish CPD programs in low resource countries. Development of CPD programs might be better addressed using a ‘greenfield model,’ relying on local leaders to engage members, or, by implementing a regional program designed and implemented collaboratively within bodies such as the Asia-Pacific Academy of Ophthalmology. Ideally all future projects include public health outcomes as a metric.


Healthcare professionals involved in adverse events may suffer severe physical and emotional distress in the aftermath. Adequate support is critical to an overall culture of safety for any healthcare institution. This study evaluates a formalised peer support program, ‘the Buddy Study’, in two Danish university hospital departments. The program consists of a 2-h seminar about second victims and self-selected buddies to provide peer support after adverse events.The study design involved a cross-sectional survey comprised of two close-ended questionnaires evaluating the Buddy Study seminar (Q1) and the Buddy Study program (Q2), along with two open-ended questions and three individual interviews for more elaborate answers.Out of the 250 HCPs employed in both departments, 191 midwives, physicians, and nursing assistants completed Q1 and 156 completed Q2. The seminars were evaluated positively; 91.6% were satisfied with the overall content of the seminar, and 69.1% agreed that insight into how other people may react to adverse events has helped them contain their own reactions or emotions. Assessments of having the Buddy Study program in the department or using or being used as a buddy were more diverse, yet overall positive. Three benefits of the program were identified: the program i) has encouraged an open and compassionate culture; ii) has caused attentiveness to the wellbeing of colleagues; and iii) the self-selected buddy relationship has created a safe space for sharing. Additionally, three challenges or shortcomings were identified: i) although peer support is valuable, it should not stand alone; ii) informal peer support is already in place, hence making a formalised system redundant; and iii) the buddy system requires continuous maintenance and visibility.The overall evaluation of the Buddy Study program was positive, suggesting that this type of formalised peer support may contribute to a rapid and accessible second-victim support program in healthcare institutions. A key principle for the Buddy Study program is that relationships are crucial, and all buddy relationships are based on self-selection. This seems to offer a safe space for health care professionals to share emotional vulnerability and professional insecurity after an adverse event. Multiple studies have demonstrated the impact of adverse events on healthcare professionals (HCPs), and the term ‘second victim’, coined by Wu in 2000 , is now While patient safety efforts target preventative measures to reduce adverse events, the management of their aftermath seems to be trailing behind, especially regarding support for the HCPs involved. This lack of support may impair their health, reduce job satisfaction, and compromise their ability to provide safe, compassionate, and high-quality health care , 8. A reSeveral reasons may explain this lack of sufficient empirical data. Firstly, this is still a young research field, and the development, implementation, and evaluation of support programs require several years. Consequently, many papers have only aimed to describe the development and the implementation of the programs . SecondlAll these reasons were considered when ‘The Buddy Study’; a new peer support program for second victims was developed and implemented in two Danish hospital departments. The aim of this study is to evaluate the Buddy Study program by assessing HCPs’ experiences with having the program in the department, attending the compulsory seminar, and using a buddy or being activated as a buddy.The study was designed as a cross-sectional questionnaire survey. In addition, three individual interviews with participants were conducted to include more elaborate answers in the evaluation.The objective of the Buddy Study program is to facilitate peer support after adverse or traumatic events through a formalised buddy system and a compulsory seminar about second victims and peer support. Adverse events were defined as patient events with unanticipated adverse outcomes, medical error and/or patient related injuries. Traumatic events could include situations not associated with safety incidents, such as patient death or workplace violence.i) Recognition of exposure to adverse or traumatic events as a fundamental condition for HCPs. In modern healthcare, the prevention of adverse events is pivotal. However, the management of the aftermath of these events is also crucial, and HCPs should be acknowledged for working in complex systems with the risk of involvement in severe adverse or traumatic events. ii) Organisational responsibility towards all employees every time. Focus groups revealed inconsistency in the support offered after adverse events, even within the same department. Second-victim support resources should be reliable for all HCPs and not based on inconsistent or random assessments of when support or debriefings should be facilitated. iii) Relationships are of central importance. Second victims may feel guilt, fear, and loss of self-esteem, which are emotions one may prefer to disclose only in an already established and safe relationship. In recognition of the importance of a personal relationship, HCPs should be able to select a peer supporter of their own choice. iv) Build on existing resources in the departments. Although management may have the will to invest in the safety and health of the employees, the general soaring healthcare budget may only allow minor additional costs. HCPs are all trained to care for people in crisis, and studies have shown that colleagues are the preferred resource of support for second victims. They are a valuable resource for a support program. v) Research-based evaluation of the intervention. The program should be designed as a research intervention to contribute to the body of evidence on the effectiveness of second-victim support resources.On the basis of literature searches, our previous research, and five focus groups with a total of 21 midwives and physicians , the resGrounded in these underlying principles, the Buddy Study was designed to encompass 1) a compulsory seminar, 2) a self-selection of two Buddies, and 3) a system for buddy activation and response after adverse events.The purpose of the compulsory 2-h seminar was to provide participants with knowledge about the second victim phenomenon and stress responses that may be associated with a traumatic or adverse event. The seminars were conducted for smaller groups of 5–15 participants at the time. Through interactive exercises, participants shared their experiences and became aware of support needs after a traumatic or adverse event. Furthermore, participants were informed about the buddy system program, how to activate one’s buddy, how to respond as someone’s buddy, and when to seek further support from management or a psychologist. The seminar addressed all participants as both potential second victims and buddies. The seminar was compulsory in order to communicate that adverse events are a general risk for all (junior as well as senior staff) and promote a shared understanding of second victims and peer support.At the end of the seminar, all participants named two colleagues whom they would want to be their buddies in case of an adverse event (on a note in a closed envelope). The selected colleagues were then asked to consent to be that person’s buddy. Eventually, a list with names of all HCPs and names of their two buddies was created, and the support program was ready for implementation.colleagues provided meaningful and sustained support after the event [sustained support for the involved HCP balanced with the potential risk of burdening the buddy over time. After four weeks, other measures should be offered, sooner if needed. The only stipulation was that the buddy encounters would happen outside working hours to ensure a space for private, unguarded conversations. The buddy would be paid for the 2 h of work.In case of an adverse or traumatic event, the buddy system can be activated through the involved HCP, a colleague, or the manager. Although it was compulsory to participate in the seminar and to select two buddies, using a buddy after an adverse event was voluntary. If the involved HCP provided consent, the manager or charge midwife would contact their buddy. No information about the event would be passed on, nor any assessment of the emotional state of the HCP. The only information provided would state that ‘NN has been involved in an adverse event and he/she wants to activate his/her buddy’. Subsequently, it was the responsibility of the buddy to reach out and contact the HCP, preferably within the first 24 h. The time frame for a buddy contact was 2 h, which could be spent in any way the HCP and the buddy agreed on—phone calls or encounters in or out of the workplace, several shorter sessions, or fewer longer sessions—over a 4-week period. In a previous study, less than half of the respondents agreed to a great or some extent that their he event . ConsequThe Buddy Study program was implemented, and the evaluation was conducted 18 months after the last seminar.HCPs from two departments at Odense University Hospital in Denmark participated in the Buddy Study program: all midwives in the Department of Obstetrics and Gynaecology (OB-GYN) in Odense and Svendborg and all physicians at the Internal Medicine and Emergency Department (IME) in Svendborg. Both departments are involved in high degrees of acute patient care and decision-making.The first questionnaire (Q1) evaluating the Buddy Study seminars was handed out to all participants at the seminars between May 2018 and April 2019. The seminar programme included time to complete and return the questionnaire. A second questionnaire (Q2) evaluating the Buddy Study program was handed out at general staff meetings in October and November 2020. Because of COVID-19 restrictions, only small groups could attend these meetings, and questionnaires were subsequently distributed via e-mail invitation with a survey link to increase the response rate. The survey was created using REDCap (Research Electronic Data Capture), and all paper versions were entered into the same database in REDCap.Both departments have a high turnover of staff because of temporary employment during training for resident doctors, maternity leave, etc. Therefore, the study population changed during the 18 months and was not identical for Q1 and Q2.During the study period, the use of the buddy system was registered, including the type of event that activated the need to use one’s buddy.To assess the participants’ experiences with the Buddy Study program, 22 close-ended items were created. The first questionnaire (Q1) included nine items addressing satisfaction with the seminar, learning outcomes, sense of safety, and attitudes towards the buddy program. In the second questionnaire (Q2), five items evaluated the Buddy Study program, addressing the overall experience with the program—including the seminar and the derived change in supportive culture, awareness, and sense of security. Furthermore, eight items specifically addressed the experiences of those who had either used a buddy or been activated as a buddy.All 22 items were specifically constructed to evaluate the Buddy Study program and were face validated by three HCPs, resulting in only minor adjustments. All items were composed of a five-point Likert scale ranging from ‘strongly disagree’ to ‘strongly agree’.Furthermore, the survey included two open-ended questions: 1) ‘In your own words, how did you experience using your buddy?’ and 2) ‘In your own words, how did you experience being a buddy for a colleague?’. An additional box for free-text comments was available at the end of the survey.Finally, both questionnaires (Q1 and Q2) contained three categorical items on gender, professional background, and seniority, and Q2 included three additional items regarding the length of employment in the department, attendance at the Buddy Study seminar (yes/no), and whether two buddies were chosen (yes/no). Within a time period of 18 months, there is a turnover of staff, and items on seminar attendance and selection of buddies were included to keep track on the level of implementation of the Buddy Study program.Upon the completion of Q2, an e-mail invitation to participate in an individual online interview was distributed to all participants in both departments. Because of COVID-19 restrictions, interviews were conducted and recorded via Zoom. A semi-structured interview guide based on preliminary results from the survey was developed, which focused on i) experiences with having a buddy program in the department, ii) peer support in general, iii) the meaning of self-selected relations, and iv) shortcomings of the program. Interviews were conducted by the first author (KS).Questionnaires with three or more missing responses were excluded, and the remaining missing responses were omitted from the final analyses. Respondents’ characteristics are expressed as proportions. To compare the two groups of respondents, chi-square tests were performed. The response options of the nine items assessing the participants’ experiences with the seminar, four items on using a buddy, and four items on being activated as a buddy were collapsed into three categories: ‘agree’ (agree/strongly agree), ‘neither agree nor disagree’, and ‘disagree’ (disagree/strongly disagree). The results are expressed as proportions. The five items evaluating the buddy program in general in Q2 were collapsed into’agree’ (to a large extent/ to some extent), ‘neither agree nor disagree’ (do not know), and ‘disagree’ . The results are expressed as proportions. Data analyses were performed using STATA 16.0 software .Each event leading to a Buddy contact was registered by type and number.When performing qualitative data analysis, audio recordings of the interviews were listened to several times, and selected excerpts were transcribed, as proposed by Miles et al. . The traA total of 250 HCPs  were employed in the two departments, of which 198 participated in the seminars, where all attendees responded to Q1 (response rate 79% of the entire population/100% of the attendees). Seven questionnaires were excluded because of missing responses, leaving 191 for data analyses. After 18 months, 167 responded to Q2 (response rate of 67%). Because of missing responses, 11 questionnaires were excluded, leaving 156 for data analysis. Of the 156, 106 (67.9%) replied that they had participated in and evaluated the Buddy Study seminar, and 120 (76.9%) replied that they had chosen two buddies.In total, 26 HCPs used their buddy, and 32 were activated as a buddy. Eight out of ten respondents were women, and more than 95% were midwives or physicians Table .Table 1CThe Buddy Study seminar was evaluated positively Table . Most paOverall, the Buddy Study program was evaluated positively, yet more diverse than the evaluation of the seminar. The majority replied that the program had increased attentiveness to one another and sense of feeling safe. But only a third felt that the program had led to more openness after adverse events Table .Table 3EOf the 156 respondents, 26 used one of their buddies during the study period. Of the 26 respondents, 34.6% had seniority of 0–4 years, 15.4% had seniority of 5–9 years, and 50.0% had seniority of 10 years or more (data not shown in table).Positive experiences with using one’s buddy ranged from 65.4% to 80.8%, whereas the proportion of those who disagreed that the experience was positive ranged from 11.5% to 15.4%, and the proportion of those who neither agreed nor disagreed ranged between 7.7% and 19.2% .Positive experiences (‘agree’) with being activated as a buddy ranged from 68.8% to 81.3%, negative experiences (‘disagree’) ranged from 3.1% to 9.3%, and the proportion of those who neither agreed nor disagreed ranged from 15.6% to 25.0% (Table n = 12), cardiac arrest (n = 1), unexpected adverse outcomes (n = 4), medical error (= 1), complaints from patients (n = 2), violent or threatening behaviour from patients or relatives (n = 4) and other/don’t know (n = 5).During the 18-month study period, 29 buddy calls were registered. The types of events causing the activation of a buddy were death   encouragement of an open and compassionate culture, ii) attentiveness to the wellbeing of colleagues, and iii) self-selected relationships create a safe space for sharing. Additionally, we identified three challenges or shortcomings of the program: i) peer support is valuable but should not stand alone, ii) informal peer support is already in place, and iii) the Buddy system requires continuous updating and visibility. Table Most participants evaluated the Buddy Study seminar positively, whereas the evaluation of the Buddy Study program in the department was more diverse, with only 37–58% of participants agreeing on positive experiences of the program. Assessments of either using or being used as a Buddy were positive overall. Three benefits and three challenges or shortcomings of the program were identified.The Buddy Study program is similar to other support programs , they chose not to participate (5%), or they did not remember the reason (7%). This indicates that the program did not achieve full implementation and possibly, that HCPs commencing at the department during the study period were not introduced to the program.Although participation in the seminar and choosing two buddies was compulsory, using a buddy after an adverse event was voluntary. The underlying reason for this distinction was a comprehensive understanding of the diversity in reactions and supporting the needs of the individual HCPs. Although the organisation has a responsibility towards all employees every time (the second principle), this does not imply a normative approach to the support needs of the individual. Hence, a buddy could only be activated when the HCP had provided consent. Furthermore, adverse events have a broad range of content and the consequences of, and support needs may vary according to the severity or the frequency of the events. This may explain why only 77% agreed that they their buddy had given them emotional support after the event—some events may call for professional advice and evaluation of the cause of events rather than emotional support.After 18 months, 26 HCPs had activated their buddy  and evaluated that experience very positively. Other support programs reported that smaller numbers use the programs than anticipated and justified this by the limited awareness of the program or fear of blame and reluctance to show vulnerability [The third principle, that relations are of central importance, was emphasised during the interviews. Self-selected relations were considered to add a greater sense of safety and to encourage a general sense of responsibility toward each other. Moreover, talking to a peer with the same background and training was considered to provide more qualified professional assessment of clinical decision-making than calling a hotline would be able to provide. Similarly, a Dutch interview study found that most interviewees were sceptical about a hospital-wide solution because this was considered to emphasise the presence of a cultural problem with the acceptance of vulnerability and support needs. They found that physicians should ideally receive support from a direct peer who could help them cope with their emotions and reflect on their professional performance. Contrary to recent developments in healthcare organisations, participants did not request a hospital-wide support team . ConcernThe positive evaluations of being activated as someone’s buddy indicate an unexploited potential to build on existing resources in the departments (the fourth principle). Placing the support program within the department may ensure long-term support and awareness, firstly because the buddies will remain co-workers long after the event, and secondly because the program involves the entire group of co-workers in the department, which potentially sustains a supportive and compassionate culture.The fifth and final principle of the programme was to conduct a research-based evaluation of the intervention. Therefore, we developed and face-validated a questionnaire for this specific purpose. The content of all questions was found to be relevant, comprehensible, and comprehensive after minor adjustments. However, the questionnaire was not psychometric tested. A risk of HCPs over-reporting what was socially acceptable to others was reduced as both questionnaires were completed anonymously. Furthermore, our results indicate a variety of responses.Due to the pressure of Covid-19 in the clinical departments, we only managed to recruit three HCPs for the qualitative interviews.An essential aspect of the evaluation is to consider to which level the intervention was implemented. Almost 30% of all employees in the two departments did not attend the seminar, which means that they were not fully informed, and the intervention was not fully implemented. The response rate for Q1 was 100% of the attendees at the seminars, and for Q2 it was 67%. Unfortunately, we are unable to account for non-attender and non-responder characteristics and are thus unable to account for potential non-response bias. During the study period, the use of the Buddy system was registered manually in a folder. Since 32 participants to Q2 responded that they had been activated as a buddy, and only 29 registrations were found, it seems that the registration is inadequate or that a few activated both buddies. These limitations illustrate the challenges of conducting interventional research in a busy clinical setting on a subject that is not possible to protocolise as a clinical trial. Consequently, the findings may have been influenced by external factors not accounted for in the scope of our study.The intervention was performed in two departments at a single institution, included only physicians, midwives and nurse assistants and the majority of participants were women. This makes it difficult to generalise the findings to other institutions. However, we believe that the results are relevant for other healthcare institutions aiming to improve their support of second victims. Both departments decided to continue with the Buddy program after the research period since staff and management considered it to be an important and useful support tool to handle the aftermath of adverse events.The Buddy Study program provides peer support to HCPs after adverse events. It is built on the pre-existing resources in the departments, and it is considered a strength that all Buddy relations are self-selected, which creates a safe space for disclosing emotional vulnerability and professional insecurity.The compulsory 2-h seminar was evaluated positively, particularly because it allowed participants to gain knowledge about the second victim phenomenon and obtain mutual insight and understanding with colleagues. Some of the participants reported that having the Buddy Study program in the department made them feel safe, that it encouraged attentiveness to one another after adverse events, and that it encouraged an open and compassionate culture. Using a buddy after adverse events was found to be helpful, and most of the respondents found both professional and emotional support with their buddy. Being activated as a buddy for a colleague was found to be rewarding both in terms of being able to help someone else and as an opportunity to reflect upon one’s own experiences.However, the formalised peer support program should not stand alone. Management plays a significant role in handling the aftermath of an adverse event. For those who already had well-established relationships and a compassionate culture in their team, the formalised buddy program seemed less relevant.


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