Teledermatology has been utilized in the United States Department of Veterans Affairs (VA) for decades but continues to have incomplete penetration. VA has funded an initiative to enhance access to dermatology services since 2017 to support asynchronous teledermatology for Veterans living in rural areas. As part of an ongoing evaluation of this program, we assessed the teledermatology activity between the fiscal years 2020 and 2022. We focused on the second cohort of the initiative, comprising six VA facilities and their 54 referral clinics.We studied teledermatology programs at cohort facilities using the reach, effectiveness, adoption, implementation, and maintenance framework. We used a mixed-methods design including annual online reports completed by participating facilities and VA administrative data. When possible, we compared the data from the 3 years of teledermatology funding with the baseline year prior to the start of funding.Reach: Compared with the baseline year, there was a 100% increase in encounters and a 62% increase in patients seen at the funded facilities. Over 500 clinicians and support staff members were trained. Effectiveness: In FY 2022, primary or specialty care clinics affiliated with the funded facilities had more dermatology programs than primary or specialty care clinics across the VA (83% vs. 71% of sites). Adoption: By the end of the funding period, teledermatology constituted 16% of dermatology encounters at the funded facilities compared with 12% nationally. This reflected an increase from 9.2% at the funded facilities and 10.3% nationally prior to the funding period. Implementation: The continued funding for staff and equipment facilitated the expansion to rural areas. Maintenance: By the end of the funding period, all facilities indicated that they had fully implemented their program for patients of targeted primary care providers. The Program Sustainability Index scores generally increased during the funding period.Targeted funding to support asynchronous teledermatology implementation for rural Veterans increased its reach, adoption, and implementation, ultimately improving access. Providing program guidance with staffing and training resources can increase the impact of these programs. Ongoing efforts to maintain and increase communication between primary care and dermatology will be needed to sustain success. Department of Veterans Affairs (VA) –5 but coTo address these disparities in access to healthcare services, the VA Office of Rural Health (ORH) has supported the use of telehealth technology, including teledermatology . In partVA is the largest single provider of healthcare services in the United States . Their kWithin the VA, store and forward or asynchronous teledermatology is a multi-step consultative process, typically involving a primary care provider (PCP), an imager, and a dermatologist. The process begins when a PCP initiates a consult request for skin imaging in the EHR, including pertinent medical history. A trained imager then schedules the patient for imaging and transfers information from the consult request of the PCP to a teledermatology reader, typically a board-certified dermatologist. If needed, the imager obtains additional medical history from the patient according to a scripted set of questions recorded in an EHR note. The imager also captures images of the patient's skin using a digital camera and manually uploads and links them with the patient's EHR. The reader reviews the history and images and writes an EHR note that includes an impression and recommendations for the PCP responsible for enacting them. Thus, aside from its dependency on technology, teledermatology implementation principally requires effort on the part of imagers to photograph the skin, dermatologists to read cases, and PCPs to initiate and later follow up with patients.The teledermatology EWI provided 3 years of funding to facilities, primarily for PCPs and dermatologists, specifically for the following: (1) dermatologist salaried effort to perform teledermatology reading; (2) up to half-time administrative support staff if the facility read for other facilities VISN-wide or multi-VISN; (3) up to one-fifth time of a PCP per spoke ; (4) travel for PCPs, including physician assistants or nurse practitioners, to be trained in performing minor dermatologic procedures; and (5) modest budgets for digital cameras and related equipment. The inclusion of funds for administrative support and equipment, including cameras and dermatoscopes, was new in Cohort 2 after receiving feedback from facilities in the first cohort.The 16 facilities of Cohort 1 received the first round of funding from FY 2017–2019. Cohort 2 was funded from FY 2020–2022 and included six facilities, four of which had preexisting programs. Funded facilities (hubs), where dermatologists read teledermatology consults, were required to identify one or more affiliated spokes that send consults to the dermatologists at the hubs. Spokes are typically CBOCs, but two hubs also read for other facilities. For applications to be fully funded, at least 50% of patients served at the funded spokes were required to reside in a rural area. Cohort 1 hubs were ineligible for Cohort 2 funding.We used the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) implementation framework to translate innovations into practice with data for Cohort 2 and evaluate impact at the individual and institutional levels –14. We e2.Six hubs received funding from FY 2020–2022 (October 2019–September 2022). We used three data sources: (1) VA Corporate Data Warehouse (CDW) for demographic and encounter data—hub data includes spoke activity unless otherwise specified (2) ORH's Management and Analysis Tool (OMAT) [migrated to the New ORH Management and Analysis Database (NOMAD) system in FY 2022] containing self-reported quarterly data entered by hubs, and (3) an online survey completed by each hub at the end of each FY, designed by our evaluation team to capture additional quantitative and qualitative data.The online survey included the Program Sustainability Index (PSI) , a questTo examine skin cancer outcomes, we used the CDW to identify International Classification of Diseases-10 (ICD-10) encounters associated with various types of skin cancers to determine the incidence at the funded facilities for dermatology patients overall as well as for patients who received care via teledermatology. To determine dermatology penetration in VA, we used the online OCC Quality and Training FY 2022 Scorecard, which drew upon CDW data, examining the presence of dermatology or teledermatology at VA facilities, nationally and at funded facilities.Quantitative data were analyzed using frequencies and crosstabs (incorporating the chi-squared test to identify significance). To analyze the qualitative data, three co-investigators reviewed the responses for each open-ended survey question. They grouped them first by topic and then identified similarities and differences and whether the comments identified positive or negative impacts.3.3.1.3.1.1.There were 17,212 teledermatology encounters among 13,615 unique patients in FY 2022 at the six hubs, representing a 30% increase in encounters and 34% increase in patients compared with FY 2021 and a 100% increase in encounters and 62% increase in patients from the FY 2019 baseline . Followi3.1.2.3.1.3.The six hubs reported training 524 VA staff members for work related to teledermatology over the 3-year period. In FY 2020, FY 2021, and FY 2022, 49, 244, and 231 staff members were trained, respectively. Early during the funding period, there was a lack of hired staff at three of the hubs. Most hubs in FY 2021 and at least one hub in FY 2022 conducted their trainings remotely because of COVID-19. Those trained included 26 teledermatology readers (range = 1–6 at each facility), 199 PCPs (range = 0–125 at each facility), and 299 telehealth clinical technicians (TCTs) and/or nurses trained as imagers (range = 0–200 at each facility). The hubs determined the selection of staff members for training.3.2.3.2.1.Data from the OCC Quality and Training Scorecard and ORH rurality data showed that, by the end of FY 2022, dermatology encounters had been completed at 71%  of national primary or specialty care clinics. These values were exceeded by funded facilities, where dermatology encounters had been completed at 83% (50 of 60) of primary or specialty care clinics. Nationally, 74% of rural primary or specialty care clinics had dermatology encounters, compared with 69% of urban clinics see . AdditioAmong patients with at least one dermatology encounter in FY 2022, those at funded facilities had travel distances to primary and specialty care clinics similar to those at non-funded facilities. As expected, larger differences were seen between rural and urban Veterans . There w3.2.2.The diagnosis rates for skin cancers and pre-cancerous lesions were higher in all dermatology encounters in FY 2020–2022 compared with those in teledermatology encounters alone, a pattern also seen across the years . In cont3.3.3.3.1.Hubs continued to increase the number of overall teledermatology encounters from FY 2019–2022 . In FY 23.3.2.Four hubs provided care to an increasing number of spokes during the EWI. Each hub, identified by letters in Hubs received teledermatology consults from spokes that are administratively connected to them (intrafacility) and spokes that otherwise report to other facilities (interfacility). 3.3.3.All hubs supplemented their reading staff payment for existing duties with the EWI funding. Only one hub reported having dermatologists who travel to spokes or Veterans’ homes to provide skin care across all 3 years. In FY 2021–2022, three hubs reported they were providing traveling care.All hubs had a dermatology residency program and/or fellowship program throughout the funding period. One hub expanded its reading program to include dermatology residents in FY 2020 and defined this step as an enhancement to its program. Three hubs involved their dermatology residents in reading teledermatology consults in FY 2022. None of the facilities used nurse practitioners or physician assistants to read teledermatology cases.3.4..To understand facilitators of and barriers to implementing teledermatology, we asked the funded facilities if their key stakeholders had concerns about support and resources for teledermatology, followed by open-ended questions about the motivation for participation, barriers, successes achieved, and role of PCP training3.4.1.In the second year, with the disruption that occurred because of COVID-19, a decreasing number of patients were seen at spokes; concerns increased among dermatologists, dermatology nurses, and telehealth support staff. By the third year, only two hubs reported major concerns, which were all from non-clinical staff. From qualitative data, much of this concern can be attributed to difficulties retaining TCTs for all 3 years at one hub and new staffing concerns communicated by the second hub. All the hubs continued to report minor concerns from primary care clinicians and nursing staff at the end of the EWI funding. Qualitative data reveal that this continued concern may be at least partially due to inadequate staffing levels of imagers.3.4.2.The hubs’ motivation for implementing teledermatology did not change over time. The program enabled them to fund desired expansion, particularly to rural areas and geographically distant clinics. One hub was motivated by findings of increased dermatology access from a pilot program.3.4.3.All hubs discussed the expansion of participating spokes as a success.One hub expanded to five other VA facilities, creating interfacility partners, unlike most other hubs, which primarily or only handled intrafacility consults. In FY 2020, hubs added new protocols to address COVID-19, such as teledermatology at home. In FY 2021, hubs largely mentioned their success implementing teledermatology at new spokes. In FY 2021 and FY 2022, four hubs mentioned their ability to continue hiring new staff members, primary care and dermatology providers, and imagers, contributing to their programs’ successes. In FY 2022, hubs highlighted their growth, such as their increase in encounters.Across all years, hubs highlighted the importance of communication and education for success, such as starting an interdisciplinary workgroup in FY 2020 and having dermatologists participate in regular primary care meetings. To encourage collaboration and enhance communication between dermatology and primary care, hubs continued or added training sessions and/or continuing education programs between dermatology and primary care, although COVID-19 prevented some in-person events in FY 2020–2021. One hub communicated to their dermatologists to write less clinical and more patient-friendly notes so PCPs could easily send the interpretations to patients.Hubs took additional measures to enhance the implementation of their teledermatology program. For example, one hub focused on Veteran outreach using the Veterans’ Service Office, local military radio, direct patient education, and websites. They also aspired to perform same-day imaging to enhance patient convenience and established a performance goal that 95% of Veterans would receive their results within 1 week. This hub also aimed to improve the process for teledermatology readers by setting a goal to increase image readability. In the second year, a different hub required that their spokes send all dermatology consults first through teledermatology to increase use. In the final year, another hub enhanced their teledermatology program by introducing dermoscopy, which enhances skin images through additional magnification and illumination, making some lesions more easily identifiable.3.4.4.Staffing is the primary barrier identified by hubs. There was concern that with the increase in consults, it would be difficult to manage demand until new dermatology readers were hired. Although the program provided funding to hire additional readers, one hub said, “Our greatest challenge has been authorization to recruit and hire the full 1.0 FTE of Teledermatology readers as approved through ORH EWI,” and another lost a provider because of retirement. As a result, those hubs shifted reading responsibilities to other providers in the interim. A different hub enabled their dermatologist to read during virtual work hours from home as an adaptation to ensure they had enough readers. By the end of the program, only one hub reported two or more dermatologists on staff for reading. Two hubs with at least two dermatologists throughout the program lacked consistently available imagers because of turnover and increased duties. One of these hubs also identified having difficulty obtaining buy-in from leadership at a few spokes, which may have contributed to their staffing concerns. Two hubs mentioned the inability to provide competitive salaries as a reason for not being able to retain staff.Closed spokes because of COVID-19 were a hindrance when the program first started. During the second year, two hubs stated that COVID-19 still impacted their implementation by hindering their expansion efforts, highlighting staffing challenges and the need to perform more teledermatology at home. One of those hubs stated that decreased patient encounters impacted their program.Other challenges included an organizational realignment that led to a loss of several spokes from their system. Consequently, these spokes were no longer able to provide teledermatology services. In addition, the hub that had enhanced their program with dermatoscopes mentioned difficulty implementing their use.3.4.5.Hubs largely discussed their focus on enhancing their implementation of primary care through education and communication via virtual webinars, email, and one-on-one training. One hub identified the need to address a hesitancy to use the program, while others focused their training on same-day imaging, image readability, completion of consults, and reporting results to patients.3.5.3.5.1.SIC is a general instrument used to follow implementation by documenting when key milestones have been reached , 17. Fig3.5.2.Over the 3 years, most hubs provided quarterly reports regarding their teledermatology program to leadership, with some variation across the years and some hubs reporting monthly or annually. In FY 2020 and FY 2022, two hubs indicated that they were uncertain about the frequency of reporting to leadership . In FY 2021, all hubs responded with their reporting plan. From qualitative data, in 2020, one hub stated that monthly reporting to the executive leadership team enhanced its program. Hubs mentioned support from VISN and executive leadership as an important facilitator to implementation.3.5.3.After the first year of the program, four hubs were uncertain about their future funding plans, while the remaining two planned to fund their program at the local facility level. In the second year, one hub that previously did not know its future funding plan expected to be funded by its VISN. At the end of the program, one more hub identified that its future funding source would be from the facility. Two hubs reported that their future funding source was still unknown.3.5.4.We assessed the potential sustainability of teledermatology efforts at each site utilizing the Mancini and Marek Model of Community-Based Program Sustainability . The valProgress was observed in the 3 years of funding. In FY 2021, only one hub averaged less than a mean of three in any element (Strategic Funding), and none in FY 2022, compared with three hubs with less than three mean values for multiple elements  in FY 2020. While the mean sustainability index of the hubs was lower in FY 2022 (5.1) than in FY 2021 (5.3), the mean is higher than in the previous cohort and increased from the first year (4.6). This drop is mostly attributable to two hubs; when they are removed, the mean sustainability value is 6.0, indicating that the other hubs improved in FY 2022 compared with the previous year.The overall mean sustainability values of these two hubs dropped from 6.2 to 3.6 and 5.5 to 4.0 in FY 2021 and FY 2022, respectively. The hub with the largest reduction is the one that lost several spokes because of realignment with another facility, although it reported that the program is fully implemented for the targeted spokes and providers. The second hub with a notable drop in their mean sustainability value continued the growth of the teledermatology program but experienced challenges related to the retirement of their reader.The greatest maintenance uncertainties for hubs during the first 2 years of the program are related to the availability of future funding and the ability of the program to adapt to changing Veteran needs. However, by the final year, while there was no change in the mean value of the hubs regarding Program Responsivity to changing Veteran needs, the overall mean regarding Strategic Funding increased from 4.2 in FY 2020 to 4.7 in FY 2022 in line with four of the six who identified future funding as a concern in FY 2022.Staff Involvement and demonstrating Program Results have the highest mean values. Unlike in FY 2021, when Staff Involvement was more highly rated than demonstrating Program Results, they flipped in rank in FY 2022. The average for demonstrating Program Results increased from 4.5 in FY 2020 to 5.8 in FY 2022. One notable difference from the previous cohort is that these six hubs reported a much higher ability to demonstrate Program Results at the end of the program than the previous cohort, which completed their program involvement during the beginning of the COVID-19 pandemic.4.VA is an attractive environment to operationalize and study evidence-based practices such as teledermatology because it is a nationwide healthcare system with a unified mission to care for Veterans, with standardized policies, EHRs, training, and funding mechanisms. Our study reveals that asynchronous teledermatology is widely and successfully used in VA, with over 140,000 encounters in FY 2022  and more4.1.The participating hubs increased the number of clinics where teledermatology was provided overall, specifically in rural areas. Teledermatology grew faster at hubs (76% increase in encounters) compared with the national average (15% increase in encounters). By the end of the program, Veterans at the ORH-funded hubs had better access to dermatology than Veteran patients overall. Such improved access to dermatology enables expedited identification of skin diseases, including skin cancer, and is associated with decreased morbidity –22.Our evaluation's finding of lower rates of skin cancer diagnoses for teledermatology compared with in-person and higher rates of a code for NUB is understandable, given that most teledermatology encounters are consultations to evaluate new, undiagnosed skin concerns. Receiving a NUB diagnosis typically leads to a follow-up in-person encounter . We surm4.2.Our evaluation showed that the ORH teledermatology EWI, which focused on funding for staff and equipment to support teledermatology, was highly successful. The importance of funding for staff and equipment to encourage teledermatology has also been found in non-VA settings , 24–26.The successful implementation of teledermatology by Cohort 2 was fairly robust compared with that of Cohort 1, especially in the face of COVID-19, which was unique to this cohort. In fact, Cohort 2 may have benefited from the focus on telehealth that many healthcare systems, including the VA, turned to during the COVID-19 pandemic , 27–29. This second cohort showed even greater gains in program success than the previous cohort . This diIndividual facilities have autonomy in the VA to innovate unique solutions to fit their needs. All the hubs found continued education to be an important facilitator in the success of initiating and sustaining their teledermatology programs, as have other studies , 30, 31.Support from the VISN  level/executive leadership was an important facilitator for the continued success of the program, including approvals for hiring new staff to read and image, which we have found in previous works , 18, 34.Although a minor concern across hubs, continuing challenges related to the involvement of primary care providers and allocation of resources may stem from the common perception in primary care that asynchronous teledermatology can disrupt established workflows , 18, 26.The findings from Cohort 1  and otheA meta-analysis similarly identified the importance of cooperation from PCPs . The CohA key indication of sustainability is clearly identifying plans for future funding . An explChanges in staffing and organizational structure can also impact sustainability. Of the two hubs that experienced a drop in their mean sustainability value, one hub experienced a loss in spokes because of changes in the organizational structure, and the second was due to the retirement of their reader. Organizations that can plan for these changes will likely retain the sustainability of their programs.By the end of the program, all hubs indicated that they had fully implemented their program for patients of targeted PCPs (as measured by the one-question modified SIC). While there was a drop in the measure of sustainability during the onset of the COVID-19 pandemic, a rebound among hubs in the last year of funding indicated a willingness to continue their teledermatology program. Hubs’ experience working virtually and in conjunction with a resurgence of in-person primary care visits led to a rebound in the number of in-clinic teledermatology consultations and a more optimistic view of sustainability. In fact, one hub mentioned just that.While this study was performed in the VA, some findings can be applicable to other healthcare systems interested in expanding asynchronous consultative teledermatology to rural sites through supplemental time-limited funding. For example, leadership support for expansion and identifying future funding sources can increase the likelihood of longer-term success of a program.5.Although participation in the EWI was available to all facilities, the six hubs we studied were, to some degree, self-selected. Thus, they may have been better positioned and more highly motivated to achieve success than other VA facilities. Furthermore, a comparison of survey results for SIC and PSI across the 3 years and among the different facilities should be interpreted cautiously because of potential changes in individuals completing the facility report each year. Lastly, our study does not include patient-reported outcomes reflecting the most important teledermatology stakeholder.6.The second cohort of a VA teledermatology initiative targeting rural sites reported a high degree of implementation, as the RE-AIM framework documented, consistent with findings from the first cohort. The initiative increased dermatology access to rural Veterans. Facilitating factors for sustainability included communication between primary care and dermatology and maintenance of leadership support to ensure adequate staffing and funding for the program. Asynchronous telehealth programs have great potential to increase access to specialty care in areas with low access to care . Providing program guidance with staffing and training resources can increase the impact of these programs.


Community-based exercise programs delivered through healthcare-community partnerships (CBEP-HCPs) are beneficial to individuals with balance and mobility limitations. For the community to benefit, however, these programs must be sustained over time.To identify conditions influencing the sustainability of CBEP-HCPs for people with balance and mobility limitations and strategies used to promote sustainability based on experiences of program providers, exercise participants, and caregivers.Using a qualitative collective case study design, we invited stakeholders  from sites that had been running a CBEP-HCP for people with balance and mobility limitations for ≥4 years; and sites where the CBEP-HCP had been discontinued, to participate. We used two sustainability models to inform development of interview guides and data analysis. Qualitative data from each site were integrated using a narrative approach to foster deeper understanding of within-organization experiences.n = 6) and British Columbia (n = 2), Canada, participated. Sites with sustained programs were characterized by conditions such as need for the program in the community, presence of secure funding or cost recovery mechanisms, presence of community partners, availability of experienced and motivated instructors, and the capacity to allocate resources towards program marketing and participant recruitment. For sites where programs discontinued, diminished participation and/or enrollment and an inability to allocate sufficient financial, human, and logistical resources towards the program affected program continuity. Participants from discontinued sites also identified issues such as staff with low motivation and limited experience, and presence of competing programs within the organization or the community. Staff associated the absence of referral pathways, insufficient community awareness of the program, and the inability to recover program cost due to poor participation, with program discontinuation.Twenty-nine individuals from 4 sustained and 4 discontinued sites in Ontario (Sustainability of CBEP-HCPs for people with balance and mobility limitations is influenced by conditions that exist during program implementation and delivery, including the need for the program in the community, and organization and community capacity to bear the program's financial and resource requirements. Complex interactions among these factors, in addition to strategies employed by program staff to promote sustainability, influence program sustainability. Over the past decade, community-based exercise programs (CBEPs) have emerged to meet the demand for accessible and supervised exercise programs for individuals with balance and mobility limitations within their own communities . For peoNot all CBEPs are informed by research evidence. CBEPs that integrate a novel healthcare-community partnership (CBEP-HCP) take advantage of complementary missions, infrastructure, and expertise of healthcare and recreation organizations to deliver an evidence-informed community-based exercise program . In thisEffective programs must be sustained to ensure continued access and benefit for community-dwelling people with balance and mobility limitations –21. Not The elements of program sustainability can be narrowed down to three domains: factors that exist within the organization implementing the program; factors that exist outside of the organization (broader community); and program features. Shediac–Rizkallah and Bone  proposedIn previous research, factors contributing to the sustainability of government- or research–funded health initiatives in the areas of mental health , cancer We used a qualitative collective case study design to understand the experiences of key stakeholders involved with sites that sustained or discontinued a licensed CBEP-HCP called the Together in Movement and Exercise (TIME™) program . A case We selected the TIME™ program for the exploration of sustainability as developers have maintained records of program implementation, delivery and discontinuation. Following a demonstration of safety, feasibility, and potential benefit , the TIMThe TIME™ program is a task-oriented, group exercise program designed to improve independence in everyday functioning among individuals with balance and mobility limitations . TrainedThe sampling frame consisted of a list of 52 sites with a license to offer the TIME™ program, including 37 sites currently offering the TIME™ program, and 15 sites that had discontinued the TIME™ program (as of April 2019). In consultation with TIME™ developers and members of the Canadian Advisory Collaborative for TIME™ (CAN-ACT), we developed a list of 8 sustained programs that had been running for at least 4 years and whose team would be potentially willing to share their experiences. Examining multiple cases spanning the spectrum of organizational identities, priorities and experiences was expected to provide a better understanding of the drivers and barriers of CBEP-HCP program sustainability. Similarly, we created a list of 8 discontinued programs where individuals who were involved with the program were still available and would potentially be willing to share their experiences. Each case was selected for its similarities or differences with respect to the outcome of interest  – ensuring theoretical replication, where the outcomes are contradictory (failed vs. successful sites) . Such coSites were considered eligible if they held a valid license from the University Health Network  to run the TIME™ program, and fitness instructors that had been trained to deliver the TIME™ program. A sustained site had to meet the following additional criteria: currently offering or delivering the TIME™ program; have a healthcare partner; have delivered the TIME™ program at least once per year for the past four years; and intend to offer the TIME™ program for the next two years. A discontinued site had to meet the following criteria: have delivered at least one TIME™ program; discontinued offering the TIME™ program; have no plans to resume offering the TIME™ program.Information regarding the organization, its priorities, resources, and the processes involved can be best obtained from stakeholders involved in the organization, program delivery and program utilization . In the via emails to the recreation manager or program coordinator. In sites where managers/coordinators agreed to participate, they were asked to identify and connect the lead researcher (GA) with at least one individual who was involved with the program as an instructor, healthcare partner, participant, caregiver, and volunteer, and expressed interest in knowing more about the study. The lead researcher contacted interested participants via telephone and obtained verbal informed consent from individuals who agreed to participate.Sites were recruited Sustainability models by Shediac–Rizkallah and Bone  and Manca priori, which was reviewed by two members of the research team , based on the primary objective and the factors described in the two sustainability models. Two researchers  independently reviewed and coded transcripts from one site and met to discuss codes. Based on this review, new codes were developed to capture information that could not be coded using existing codes based on the sustainability frameworks (codebook available on request). Then the lead researcher (GA) and the RA coded the remaining transcripts using NVivo 12. Data for each site were analyzed separately to develop case summaries. First, the lead researcher reviewed node reports and created within-site summaries that outlined the context of the setting, the mechanisms by which the program was implemented, and the description of how the sites continued to deliver the program or conditions that ultimately led to program discontinuation. Second, members of the research team  met to review case summaries and discuss emerging themes and key concepts. Third, the lead researcher compared and contrasted the case summaries within the sustained and discontinued categories, and then across all cases. Conditions identified as influencing sustainability and actions taken to resolve challenges and ensure sustainability were compared across sustained and discontinued cases. An inductive approach was used to identify overlap in conditions and strategies across the sites. Finally, based on the recommendations and reflections of the study participants, the team created a list of questions that existing and new programs can use to guide program implementation and sustainability planning.De-identified transcripts were analyzed using a directed content analysis approach  and inclTrustworthiness was enhanced by the development of a detailed research protocol and maintenance of an audit trail that allowed for transparency of the methods used to arrive at the conclusion , 43. Then = 6) and British Columbia (n = 2)) participated in 27 interviews between April and August of 2019. Participants included 6 program coordinators, 8 fitness instructors, 3 program managers, 1 healthcare partner, 1 regional stroke coordinator/healthcare partner, 6 TIME™ participants, and 3 caregivers of TIME™ participants. Duration of participant involvement with the program ranged from 6 months to 8 years. Twenty-eight individuals from programs at eight unique sites  alignment of program and organizational goals, (2) perceived need for program in the community, (3) presence of supportive partners and partnerships to create a referral pathway and increase awareness of program in the community, (4) presence of an experienced and motivated team of individuals involved in program implementation and delivery, and (5) organizational capacity, resources, and funding to support, promote and sustain the program.The majority of existing research in the area of health program sustainability surround programs related to mental health, addiction, primary and acute care settings, discusses medical interventions or education programs. These programs are either led by researchers as a part of a research study or by government/local authorities as a part of health promotion programs and are supported by ear-marked funding . While tSustainability literature divides the factors influencing sustainability into certain sub-groups. Shediac–Rizkallah and Bone  model diTogether the characteristics of the inner setting, outer setting and program design interact and influence each other to create an environment where a program thrives and grows or fails to achieve expectations and naturally discontinues or is terminated. For example, the environment for the sustained program can be described as one where the program staff support and encourage the allocation of resources towards a program for which there is an ongoing need in the community. The staff are in turn supported by partnerships and networks that provide ongoing assistance to program delivery. They employed strategies such as fundraising to financially support the program, building networks with a source of participants to promote referral, and providing subsidies to encourage participation.With discontinued programs, challenging conditions were aggravated by unsuccessful strategies. For example, poor program enrollment due to the presence of competing programs led to reduced motivation among program staff and poor cost recovery. Strategies such as program promotion or reducing number of staff to minimize costs were not sufficient to revive the program and led to program termination. Authors , 50 haveOur study also expanded on the descriptions  of some The need for the program must be complemented by a pathway that connects those who need the program to the program. Both sustained and discontinued programs underscored the need for secure and consistent sources that can refer participants to the program, and for an individual who is responsible for developing networks with these sources of potential participants. For this role, three of the four sustained programs relied on a program staff  who had connections and experience in both healthcare and community setting and were able to bridge the gap between the two. Referred to as a boundary spanner , these iResults showed that for a program that involves long-term clients, having experienced and motivated instructors facilitates participant retention. Participants, especially individuals with disabilities, rely on developing long-standing associations with instructors who become aware of the participants’ needs and abilities, and can develop a sense of trust over time . ExperieResource availability is inextricably connected to the availability of funds to support program implementation and delivery. Funding is a complex factor as it depends on the type of organization , their business model (for-profit vs. not-for-profit), their source of funds , and the assurance of ongoing availability funds for the program. As seen in this study, the availability of ear-marked funding for the program provided a secure foundation for two sustained programs allowing them to engage more staff, offer incentives for participation, and dedicate resources towards the program. The importance of financial support for sustainability while not novel, assumes greater significance when program implementation is initiated at grassroot levels rather than those driven by academic research or government initiatives. Organizations can benefit from resources that indicate the costs involved in program implementation to help with planning for program implementation and continued delivery .The ultimate aim of program sustainability is to ensure that the health benefits to the target population are maintained and that the program is continually accessible to existing and new participants. In the absence of other alternatives, discontinuation of effective programs may result in participants discontinuing engaging in exercises due to a fear or adverse effects, or lack of knowledge of how to exercise safely when experiencing balance and mobility limitations , 61. TheThis study demonstrates that program sustainability cannot be guaranteed by the mere presence of positive factors. It depends on the conditions surrounding the program at the time as well as the strategies employed by the program staff to promote positive influences and overcome challenges. These conditions may change over time. Some authors , 65 arguIt is important to note that the discontinued programs did not anticipate challenges at the time of implementation. Regular monitoring of the conditions surrounding the program could allow program staff to prospectively engage corrective strategies when required. Bodkin and Hakami  suggest Studies on program sustainability recommended that planning for sustainability should begin early in a program's life cycle , 67. AskThe sites that participated in this study reflect the heterogeneity of the recreation centres in the community including sites run by the local government/municipality, as well as private, for-profit and not-for-profit organizations. All the programs in this study, however, were located in urban or sub-urban centres; the experience of programs in rural centres is missing. This is important as the priorities and needs of rural centres and the resources available may be unique. The participating sites also belonged to two provinces in Canada: Ontario and British Columbia. The outcomes of programs implemented in other provinces may differ based on their priorities and the resources available to them. These factors may impact the transferability of the findings to other regions.Sustainability of CBEP-HCPs for people with balance and mobility limitations is influenced by a complex interaction of conditions surrounding the program and the actions taken by the individuals involved in program implementation and delivery. Understanding what the conditions are and how they interact before implementing the program can stimulate corrective actions, where required, to prevent discontinuation of effective CBEP-HCPs for people with balance and mobility limitations.


Ms 6.06. Considering the geological structure in the earthquake region and the fault source parameters, we infer that the Kepingtag reverse fault is responsible for the earthquake, and the improved IDW interpolation tropospheric decomposition model can perform atmospheric correction more effectively, which is also beneficial for the source parameter inversion of the Jiashi earthquake.Due to some limitations associated with the atmospheric residual phase in Sentinel-1 data interferometry during the Jiashi earthquake, the detailed spatial distribution of the line-of-sight (LOS) surface deformation field is still not fully understood. This study, therefore, proposes an inversion method of coseismic deformation field and fault slip distribution, taking atmospheric effect into account to address this issue. First, an improved inverse distance weighted (IDW) interpolation tropospheric decomposition model is utilised to accurately estimate the turbulence component in tropospheric delay. Using the joint constraints of the corrected deformation fields, the geometric parameters of the seismogenic fault and the distribution of coseismic slip are then inverted. The findings show that the coseismic deformation field (long axis strike was nearly east–west) was distributed along the Kalpingtag fault and the Ozgertaou fault, and the earthquake was found to occur in the low dip thrust nappe structural belt at the subduction interface of the block. Correspondingly, the slip model further revealed that the slips were concentrated at depths between 10 and 20 km, with a maximum slip of 0.34 m. Accordingly, the seismic magnitude of the earthquake was estimated to be  Ms earthquake on 19 January 2020, which resulted in a number of casualties  and building damage . Although the earthquake was on the northwestern edge of Tarim Basin at the intersection of the South Tianshan fold belt, Parmir arcuate tectonics, and Tarim Basin, there are numerous active Cenozoic faults with varying properties in this region, in addition to mountains and basins that coexist [Western China’s Jiashi County experienced a 6.4  coexist . Since t coexist ,5,6. In  coexist . TherefoExisting research classifies tropospheric atmospheric delay correction techniques into two categories ,10,11,12Ms 6.4 earthquake that occurred in Jiashi, Western China on 19 January 2020. The primary contributions of our work are as follows: (1) An improved inverse distance weighted interpolation tropospheric decomposition optimisation model was proposed to improve the precision of turbulence component delay estimation and realise tropospheric atmospheric delay phase correction. (2) The coseismic deformation field and deformation characteristics of the Jiashi earthquake were successfully obtained by using ascending and descending SAR data. (3) The fault slip distribution parameters of the Jiashi earthquake were inverted using coseismic deformation field data. Correspondingly, the results of this study can support and serve as a reference for the extraction of the coseismic deformation field and inversion of fault slip distribution parameters.In summary, based on the structural and topographic characteristics of the Jiashi area, the influence of the tropospheric delay on the results of seismic coseismic deformation, and the ascending and descending Sentinel-1A SAR data, this study carried out the tropospheric delay correction, coseismic deformation field extraction, and coseismic slip distribution parameters inversion of the Ms 6.4 occurred in Jiashi County, China. The long axis of the isoseismal line caused by the earthquake was east–west, and the focal mechanism of the earthquake comprised thrust. Following the earthquake, various institutions reported focal mechanism solution outcomes , the epicentre was located at 39.83° N and 77.21° E with a focal depth of approximately 16 km. In addition, the focal mechanism solutions reported by the United States Geological Survey (USGS) and the CENC suggest that this earthquake was most likely a thrust event in the fold belt on the southern margin of the Kepingtag nappe structural belt  program. Sentinel-1 is comprised of Sentinel-1A and Sentinel-1B. In this study, C-band (radar wavelength of 5.6 cm) Sentinel-1A images were used for both the ascending and descending tracks to measure the displacement of the Jiashi earthquake. The data were collected utilising a very advanced scanning mode known as Terrain Observation with Progressive Scans (TOPS) in the IW mode, which can effectively reduce the scalloping effect and enhance the interference performance. The detailed parameters of each interferometric pair are listed in n GPS stations exist in the study area, the enhanced IDW model can be expressed as follows:The traditional iterative tropospheric decomposition method estimates the turbulence component using the inverse distance weighted (IDW) method . This meThe following are the processing steps for the enhanced inverse distance weighted interpolation tropospheric decomposition:(a) Assuming that the turbulence component in the iterative tropospheric decomposition model is 0, the vertical component index coefficient and vertical component delay at sea level in the study area can be initially estimated based on the total zenith delay observed by all GPS stations to obtain the vertical component index coefficient;(b) The residual component consists of the unmodelled component and the turbulence component, which can be obtained by subtracting the vertical component from the site-by-site iterative tropospheric decomposition model;(c) Using the enhanced IDW model, the turbulence component can be determined from the residual component:(d) By subtracting the updated turbulence component from the iterative tropospheric decomposition model of each station, the index coefficient and vertical component delay at sea level in the study area were recalculated;(e) Steps (b)–(d) were repeated until the exponential coefficient and the vertical component at the sea level of the study area delayed the convergence. The output results include the turbulence component, the vertical component, and the residual component at each observation station. The iterative tropospheric decomposition model value at the location of interest is then obtained by improved inverse distance weighted interpolation.m is the initial constraint of the fault’s geometric parameters, The Monte Carlo algorithm is a prevalent method for solving inversion problems . It is aThe likelihood function needs to be established using the M-H global optimisation algorithm. Assuming that it obeys a Gaussian distribution, the mean and standard deviation are N is the number of sampling points. Subsequently, Equation (2) can be rewritten asIn general, the seismic background noise conforms to the normal distribution with a mean value of 0 and a variance of To obtain the posterior probability density function distribution m. The probability of a transition is then calculated as follows:The posterior probability density distribution must satisfy the stationary distribution Finally, the model parameters were continuously disturbed under the M-H sampling algorithm. Accordingly, multiple random simulations were performed on the initial model parameters of the fault’s geometry, and the posterior mean was used as the optimal solution for the model parameters.2 [d is the observed LOS displacement from InSAR, G is the Green function linking the predicted displacement to the unit model slip, m is the slip amount of sub-fault, including the strike-slip and dip-slip components, D is the finite difference approximation of the Laplacian operator, which was used to avoid a slip distribution characterised by nonphysical oscillations, and To comprehend the fine slip distribution on the fault plane, the fault geometry parameters are obtained via nonlinear inversion. Accordingly, we set the fault plane to be 50 km long along the strike and 30 km wide on the basis of the distribution range of the coseismic deformation field, and it was subdivided into 375 sub-faults, each measuring 2 × 2 km2 . As a reMs 6.4 Jiashi earthquake based on ascending and descending images from Sentinel-1A. According to Using two-track differential interferometry and the GAMMA software, the coseismic deformation fields of the ascending and descending Sentinel-1A tracks were obtained. To reduce phase noise, interferograms were downsampled to ten looks in the azimuth and two looks in the range and filtered using an adaptive filter function. The accuracy of the azimuth registration (better than 0.001 pixel) was acquired to prevent phase jumps between successive bursts, and the effects of topography were removed from the interferograms using a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) with a 30 m resolution. In addition, the minimum-cost flow (MCF) method was utilised for phase unwrapping. The Jiashi earthquake occurred in the Kepingtag thrust nappe structural belt between the Southern Tianshan Mountains and the Tarim Basin; this region is characterised by strong topographic fluctuations; the influence of the tropospheric delay phase is significant; therefore, residual atmospheric phases remain in the interferogram acquired with the DInSAR. We used the improved IDW interpolation tropospheric decomposition method to remove atmospheric effects in order to reduce the influence of atmospheric effects even further. Clearly, the deformation field caused by the earthquake was predominantly distributed in the southernmost region of the Kepingtag thrust nappe structural belt, and it was concentrated in the Kepingtag fold belt and the Ozgertau fold belt. From the perspective of space, the long-axis direction of the deformation field is nearly EW, indicating that the strike of the seismogenic fault is nearly EW. There are two obvious deformation areas in the LOS deformation fields: the deformation in the Ozgertau fold belt was subsidence, with a maximum value of approximately 0.04 m, while an uplift LOS deformation with a maximum value of 0.06 m is located in the Kepingntag fold belt. The displacement between the two deformation areas is continuously distributed, and there is no decoherence area caused by surface rupture, indicating that the rupture of the seismic fault did not reach the surface. The signs of the LOS deformation observed in the descending and ascending deformation fields are identical, indicating that the seismogenic fault deforms primarily vertically. Moreover, the uplift in the south  is significantly greater than the subsidence in the north , indicating that the seismogenic fault dips northward, which is consistent with the focal mechanism solutions reported by USGS, GCMT, and other institutions . Since tIn this study, the optimal geometric parameters of the fault were determined using the Monte Carlo method and ascending and descending deformation data as constraints. In addition, the uniform fault sliding model and the joint probability density distribution of the Monte Carlo Markov chain were obtained. Finally, the optimal geometric model of the fault was obtained. In summary, the uniform slip results provide a single fault geometry of 50 km in length and 31 km in width. The strike, dip, and rake angles are 270°, 22°, and 90°, respectively, which are comparable to the USGS-reported focal mechanism solution. In addition, the strike is consistent with the long axis of the interferograms, and the dip angle is consistent with the available geological data.18 N·m, which corresponds to a moment magnitude of 6.06, which is consistent with the seismic moments reported by the USGS and GCMT. The fault slip model indicates that the Jiashi earthquake was a typical thrust fracture event with a small component of strike slip. The source parameters of the fault geometry inversion and the slip distribution inversion are extremely similar, and the results of the two inversions can be independently validated.We inverted the slip distribution of the Jiashi earthquake using the Steepest Decent Method (SDM) and finally obtained the slip distribution of the Jiashi earthquake . SignifiThe Jiashi earthquake fault activity did not cause a surface fracture, and the thrust strike-slip Keping fault is located near the source area . In addiThe observed and modelled deformation were found to be generally consistent, indicating that there is no break exposed at the surface. In addition, it suggests that the fault closest to the focal area is the Keping fault, which is a thrust slip fault. The results of the relocated Jiashi earthquake sequence indicate that the aftershocks were primarily distributed along the strike of the fault and concentrated between 5 and 20 km beneath the surface. The depth of the focal region gradually increased from north to south, with a distinct northward dip. According to the focal mechanism solutions reported by various institutions for the Jiashi earthquake , the fauMs 6–7 earthquake swarm from 1997 to 2003 and the Jiashi Ms 6.4 earthquake should be distinct rupture events in the foreland tectonic environment of the Southern Tianshan Mountains. They were identical occurrences brought on by tectonic activity in the thrust nappe structure of the Southern Tianshan Mountains.Furthermore, both the 1997–2003 Jiashi earthquake swarm and the earthquake occurred within the Southern Tianshan thrust nappe structural belt. The thrust nappe has the Keping fault and a concealed thrust fault zone as its tectonic background. The formation of the concealed fault zone may have resulted from the heterogeneous deformation and ongoing tectonic movement along the northern margin of the Tarim Basin. Some faults extend beneath the Tarim Basin and are concealed by Cenozoic sedimentary layers, thereby forming concealed faults. These concealed faults can generate earthquakes of moderate intensity. In the thrust nappe structural belt, a small-scale normal fault may occur; a transverse strike-slip fault may even form nearly perpendicular to the strike of the thrust fault beneath the thrust nappe structure due to differences in the mechanical properties of the rocks and the regional tectonic stress fields. These normal faults and strike-slip faults are also capable of causing moderately powerful earthquakes. Consequently, based on the analysis of the regional tectonic dynamic background and the regional tectonic distribution, we believe that the occurrence mechanism of the Jiashi This study proposes an improved IDW interpolation tropospheric decomposition optimisation model to estimate the turbulence component in the tropospheric delay in order to reduce the effect of atmospheric residual phase on the spatial distribution of the LOS surface deformation fields with Sentinel-1 data interferometry in the Jiashi earthquake. Using ascending and descending data from Sentinel-1A, the LOS deformation fields of the earthquake were then extracted. Based on this information, the fault geometry and slip distribution of the earthquake are inverted. In particular, the results presented in the paper demonstrate that:18 N·m, equivalent to Ms 6.06. The Jiashi earthquake was a northward-dipping thrust earthquake with a small strike-slip component, which was consistent with the geological tectonic background of the region. In addition, based on the focal mechanism and regional structural characteristics, we conclude that the seismogenic structure of the Jiashi earthquake could be the Keping fault at the leading edge of the Kepingtag nappe structural belt.(1) The coseismic deformation field of the Jiashi earthquake was approximately 60 km wide in the strike direction and 50 km wide in the dip direction. In the southern and northern parts of the deformation field, there were two deformation centres with nearly elliptical distributions. The maximum northward subsidence was 0.04 m, while the maximum southward uplift was 0.06 m. The absence of a spatial decoherence zone and the continuity of the interference fringes between the subsidence area and the uplift area indicate that the seismic rupture did not reach the earth’s surface. The results of the inversion indicate that the fault has a strike of 274.87°, a dip of 20° N, an average rake of 90.59°, and a maximum slip of approximately 0.34 m at a depth of 5.3 km. The total geodetic moment for a shear modulus of 30 GPa was 6.93 × 10Ms 6–7 earthquakes. The comprehensive analysis of the regional tectonic dynamic background and the deep and shallow regional structures led us to the preliminary conclusion that the seismogenic mechanisms of the Jiashi Ms 6.4 earthquake and the Jiashi Ms 6–7 earthquake swarm from 1997 to 2003 were fault rupture events formed by cracks at different levels in the foreland environment of the Southern Tianshan Mountains, which are jointly controlled by the thrust nappe of the Southern Tianshan Mountains.(2) The earthquake that struck Jiashi on 19 January 2020, was a typical thrust rupture event that occurred in the foreland of the South Tianshan Mountains. Between 1997 and 2003, this region experienced an intense swarm of (3) Using DInSAR deformation observation data, the geometric and kinematic parameters of the seismogenic fault of the Jiashi earthquake were inverted, and a preliminary explanation for the dynamic physical mechanism of the seismogenic fault was provided, which has significant implications for earthquake prevention and disaster reduction. In the following step, we will combine GPS and other data to conduct research on source parameters and source rupture process inversion, as well as discuss the change in stress distribution after the earthquake, to comprehensively analyse scientific problems such as co-earthquake and post-earthquake stress and strain.


Intensive tennis practice is known to generate sport-specific adaptations at the shoulder region and influence the sagittal spinal curvature. However, increased thoracic kyphosis decreases the shoulder functional capacity, which could limit tennis performance. Therefore, the aim of this study was to investigate the effects of an 8-week multimodal program on thoracic posture, glenohumeral range of motion, and serve performance in competitive young tennis players.Eighteen male and four female players  performed their regular training during 8 weeks, which was used as a reference period, and implemented a multimodal program including stretching, strengthening, and myofascial release exercises, four times per week during 8 additional weeks, which corresponded to the intervention period. The thoracic curvature angle and mobility, the biacromial and interscapular distances, the glenohumeral range of motion and the tennis serve performance were assessed three times, i.e., before and after the regular training and after the 8-week multimodal program.p = 0.06–0.46] and mobility , biacromial  and interscapular distances , ranges of motion in glenohumeral internal  and external rotation , and tennis serve accuracy  and velocity . The 8-week multimodal program increased moderately the thoracic mobility , moderately to strongly the serve accuracy and velocity , strongly decreased the interscapular distance , and strongly increased the range of motion in glenohumeral internal  and external rotation .The results showed that the 8-week regular training had no significant effects on thoracic curvature angle [effect size (ES) = 0.02–0.36, These findings indicated that an 8-week multimodal program, including spine and glenohumeral mobility and shoulder girdle strength exercises, performed four times per week during 8 weeks, is moderately relevant to rectify the sagittal thoracic curvature in competitive tennis players, while such a program may help regain the range of motion in glenohumeral rotation without tennis serve performance impairment. Due to To preserve tennis players' shoulder functions, previous studies –28 have Therefore, the aim of this study was to investigate the effects of an 8-week multimodal program on thoracic posture, glenohumeral range of motion, and serve performance in competitive young tennis players. It was hypothesized that this program would straighten the thoracic spine, increase glenohumeral rotational range of motion, and improve tennis serve performance.2.2.1.a priori statistical power analysis indicated a sample size of a minimum of 18 participants assessed three times, with α = 0.05, statistical power = 0.95, and effect size f = 0.40. Given the duration of the study (16 weeks), we expected a risk of 20% of players lost to follow-up.A sample size calculation was performed using a large effect size, based on the results of the meta-analysis reported by Gonzalez-Galvez et al. . The a pEighteen male and four female tennis players . The distance was measured twice and averaged for subsequent analysis. Short biacromial distance reflects the forward shoulder posture.The biacromial distance was measured using a spreading caliper. While the player is in a neutral standing position, the examiner puts the ends of the caliper on the acromion anterior part of each shoulder to measure the biacromial distance  and p-value. For all the statistical tests, Rcmdr package of the software R 4.1.0  was used, and the level of significance was set at p ≤ 0.05.All data are presented as mean ± SD. After checking the normality and homoscedasticity of the raw data with the Shapiro–Wilk and Levene tests, respectively, ANOVAs for three repeated measures , while a significant effect of time was found in flexion  and extension  positions. In the flexion position, no significant changes were found either after the control period or after the intervention period (the significant effect between T0 and T2 was out of interest for our purpose). In the extension position, the mean thoracic spine angles were similar between T0 and T1  and decreased significantly between T1 and T2 . The changes in thoracic curvature angles are presented in For the thoracic spine angles , ANOVA rp = 0.13), while a significant effect of time was found when mobility was measured between neutral standing and flexion positions , and extension and flexion positions . For these last two mobilities, no changes were reported after the control period , while significant increases were observed after the intervention period .For the thoracic spine mobility , no signp = 0.18). ANOVA revealed a significant effect of time on the interscapular distance , which were similar at T0 and T1 , and significantly lower at T2 compared to T1 .For the shoulder girdle distances , no effep < 0.001), EROM , and TAM . IROM, EROM, and TAM were similar at T0 and T1 , and increased significantly between T1 and T2 .For the glenohumeral ranges of motion , ANOVA rp < 0.001), rate of successful serves , and velocity . The mean accuracy, rate of successful serves, and velocity remained similar between T0 and T1 , and all increased significantly between T1 and T2 .Regarding the serve performance , ANOVA r4.This study aimed to investigate the effects of an 8-week multimodal program on thoracic posture, glenohumeral range of motion, and serve performance in competitive young tennis players. The main findings were that the 8-week multimodal program erected the thoracic posture in trunk extension position, improved thoracic mobility, increased scapular medially rotated position, increased internal and external rotation range of motion at the dominant glenohumeral joint, and improved tennis serve performance.Long-term exposure to tennis practice leads to morphological , musculaThe achievement of tennis strokes, especially tennis serve, applies asymmetric loads, creating the progression of muscular asymmetry and spine alterations . ParticuThis study presents limitations that warrant discussion. First, strength assessments were not performed neither for glenohumeral muscles nor for scapular muscles, not allowing the effects of strength exercises to be related to scapular positioning. Second, a tennis serve kinematic analysis may help evaluate whether a transfer of the decreased thoracic curvature during trunk extension occurred during the tennis serve motion. Third, the effects of the multimodal program on postural and shoulder adaptations may be influenced by the large range in tennis experience due to age dispersion of our players and/or by the natural evolution of the tennis practice when control and intervention periods were performed successively in different periods of the tennis season. This study was, however, the first investigating the effects of a multimodal program acting on both the spine and shoulder girdle region in competitive young tennis players. Further studies need to evaluate whether such a multimodal program may have effects on the forward posture in the long term, as well as to better understand the transfer of such multimodal program effects into the sport-specific performance.5.A multimodal program focusing on upper trunk and shoulder including stretching, strengthening, mobility, and respiratory exercises performed four times per week during 8 weeks has no effect on the thoracic spine alignment; but it is relevant to gain in thoracic, scapular, and glenohumeral mobility in competitive young tennis players. Such a program could be implemented regardless of the season periodization because its gains are transferred to the tennis-specific performance.6.The findings of the present study showed that a multimodal program including spine and glenohumeral mobility and shoulder girdle strength exercises resulted in improved thoracic mobility, decreased interscapular distance, increased glenohumeral rotation range of motion, and increased tennis serve performance. This study brings new knowledge to tennis and strength and conditioning coaches, and clinicians to prevent shoulder function limitations without altering sport performance in overhead athletes.


L ≥ 1.5, which occurred along the main segments of the East Anatolian Fault (EAF) since 2014. We find the EAF fault segments showing different temporal patterns in the proportion of nonclustered seismicity, which we interpret as temporal variation of coupling. We also study the evolution of the b-value, fractal dimension and energy rate. These seismic features show for the Amanos and Pazarcık fault segments a long-term trend during the period 2020–2022 that might correspond to a quiescence phase. The latter is followed by a change in earthquakes clustering and characteristics that starts about eight months before the Mw 7.8 Kahramanmaraş event. Our observations confirm the existence of a long-lasting preparatory phase for the 2023, Mw 7.8 Kahramanmaraş earthquake and can stimulate new investigations on the East Anatolian Fault mechanic. Intercepting when a fault starts deviating from its steady behavior, might be the key for identifying the preparatory phase of large earthquakes and mitigate seismic risk.To verify the existence of a preparatory process for the 6 February 2023, Mw 7.8 Kahramanmaraş earthquake, southern Türkiye, we analyze the temporal evolution of seismic catalog information for ~ 7500 earthquakes with magnitudes M Just 9 h after, another strong earthquake (Mw 7.5) struck the same region on the Sürgü-Misis-Fault with the epicenter near the city of Ekinözü, Türkiye2. These two earthquakes, and the consequent aftershock sequence caused near 60,000 fatalities and more than 100,000 injured. The Anatolian region is characterized by a counterclockwise movement and exhibit a rigid block behavior with the main deformations that appear on the North Anatolian Fault (NAF) and on the East Anatolian Fault (EAF)4, which is mainly characterized by a sinistral strike-slip behavior. The 2023 sequence took place in the EAF, a fault system approximately 580 km long and which ranges from the triple junction of Karlıova (Eastern Türkiye) going in the Southwest direction to Antakya near the Mediterranean Sea boarding Türkiye-Syria border6. Geological and geomorphological studies show the slip-rate varying significantly along the EAF system, with a maximum of 10 mm·year−1 near Karlıova in the east to 2.5 mm·year−1 in the west8. Here, we consider, from east to west, the five EAF fault segments of Palu, Pütürge, Erkenek, Pazarcık and Amanos8. The historical and instrumental seismicity of the area is well documented11 and the Mw 7.8, 6 February 2023 Kahramanmaraş earthquake is the strongest event ever happened on the EAF in historical record; eventually comparable with the 995 Palu earthquake, which magnitude, however, remains uncertain11. It is worth to note that the 2023 earthquakes filled a well-known gap in the seismicity12, but the high magnitude of the event was unexpected considering the historical seismicity of the area. The Mw 7.8 Kahramanmaraş earthquake initiated on a small fault extending southwestward from the main branch of the EAF13, and then developing into a bilateral rupture that involved at least the Amanos, Pazarcık and Erkenek segments14.On 6 February 2023, at 01:17:34, a strong earthquake of Mw 7.8 struck the region between Türkiye and Syria with the epicenter near the city of Kahramanmaraş, Türkiye8 estimated a maximum magnitude Mmax equal to 7.4 every 772–915 years. On the other hand, looking at historical stress accumulation, Nalbant et al.12 stated that the Pazarcık segment was “the most likely location of the next damaging earthquake on the EAF … likely to produce a very large (Mw ≥ 7.3) event”.For the Amanos and Pazarcık segments, Güvercin et al.1. In a very short time after the Mw 7.8 earthquake, many studies have been published regarding the source characteristics19. Results from different techniques, such as back-projection and remote sensing14, consistently point out that the Mw 7.8 mainshock originated from an unmapped structure connected to the Pazarcık segment ent Fig. 14,16,18.23, which took place on the Pazarcık segment. The latter earthquake was mainly a left-lateral strike-slip, with a small portion of source slip presenting a down-dip behavior22. It is worth noting that Xu et al.22 recognized in this event a new activation of the EAF and they warned the seismic hazard community to give particular attention to the seismic gaps previously indicated by Nalbant et al.12. Of outmost importance, Güvercin et al.8 showed that the 2020 Mw 6.8 Elazığ earthquake “was preceded by an accelerated seismic activity” started one month before with a Mw 5.2 event on the same fault. Moreover, Konca et al.23 showed that the aftershocks remained on the area of the mainshock for three months after they started to migrate southwards.Looking at the recent past seismic activity in the region, the most significant previous earthquake along the EAF was the January 2020 Mw 6.8 Elazığ earthquake24 and on the spatio-temporal variation of the Gutenberg-Richter b-values at regional scale25.The existence of a one-month preparatory process for the 2020 Mw 6.8 Elazığ earthquake stimulates us to investigate the existence of generation processes for the 2023 Mw 7.8 Kahramanmaraş earthquake. Studies aiming at identifying a preparatory phase for the latter earthquake has been recently carried out focusing on the evolution and properties of seismic clusters within few tens of kilometers from the Kahramanmaraş earthquake epicentre30, especially megathrusts, are showing us that main ruptures are often anticipated by preparatory processes, though their identification is difficult because the precursory patterns vary depending on the tectonic environment30 .Retrospective studies of past large earthquakesDifferences in the preparatory phase of large earthquakes highlight that crustal processes leading to them are influenced by unforeseeable combination of heterogeneous fault properties, stress interactions and crustal fluids. Such complexity lets the background physical processes generating large earthquakes not fully understood yet. Despite, how, when, and where large earthquakes are generated remain fundamental unsolved scientific questions, studying the preparatory phase represents a challenge that the seismological community is called urgently to address to mitigate seismic risk.35. Kato and Ben-Zion31 made a review of decades of observational, laboratory and theoretical studies, which leads them to suggested large earthquakes being generated by a progressive localization of shear deformation around a rupture zone that progressively evolves into a final rapid loading of a crustal volume localized nearby the hypocenter of the major dynamic rupture. During the latter process, small magnitude earthquakes, commonly called foreshocks, are generated, and their pattern and peculiar dynamic characteristics37 might be the key for identifying the preparatory phase of large earthquakes. Similar patterns in damage evolution have been observed by studying acoustic emissions during triaxial tests on rock samples38, suggesting that the process generating earthquakes may be universal.Promising observations come from patterns in small magnitude seismicity and crustal deformation preceding larger earthquakesL 1.5 that occurred along the main segments of the East Anatolian Fault (EAF) since 2014. We analyze the spatiotemporal clustering and physical based features describing different aspects of the seismicity evolution seeking for clues of stress accumulation32 and/or transfer among EAF segments, and changes in coupling conditions39. Observing the evolution in the proportion of nonclustered seismicity, which is interpreted as a proxy for coupling40, we find different temporal patterns and insights of a progressive decoupling process interesting both the Pütürge segment before the 2020 Mw 6.8 Elazığ earthquake and the Pazarcık one before the Mw 7.8 EQ. The preparatory phase of the Mw 7.8 EQ is also identified by the temporal evolution of b-value, fractal dimension and energy rate. Observing these seismic features, which can be considered as proxy for the crustal stress32, we can identify a first long-term trend in the earthquake characteristics for the Amanos and Pazarcık fault segments following the 2020 Mw 6.8 Elazığ earthquake on the Pütürge segment that can be interpreted as quiescence. The latter was followed by a final stage in the preparatory process lasting ~ 8 months before the Mw 7.8 EQ.As it is currently impossible to identify whether an earthquake is a foreshock or not, and such label is assigned to events retrospectively only, we focus our analyses on the spatio-temporal evolution of earthquakes with magnitude larger than ML ≥ 1 within a buffer of variable width between 30 and 50 km from east to west of the EAF, respectively . The latter considers the local magnitude (ML) for earthquake smaller than about ML 4 and the moment magnitude (Mw) for the larger ones. The temporal evolution of magnitude suggests inhomogeneous completeness for the years before 2013 . We thus select for the following analyses the earthquakes occurred in the period 2014–2023 and magnitude ML ≥ 1.5, for a total of 7502 events  from 2014 to 2019, (ii) 2020, and (iii) from 2021 to 2023. Periods (i) and (iii) presents very similar η distribution, with a clear distinction between clustered and background seismicity . The analysis is performed by considering moving time-windows of 100 events, and we move them of one event at a time , we combine the datasets for the two segments and calculate the seismic features considering: (i) all the events, (ii) only the background seismicity. Although there are some differences between the two datasets  and we move them of one event at time. The value of each feature is assigned to the last event in a window. The seismic features  are computed for each EAF’s segment and included in the supplemental material (Supplementary_S2_Amanos_R1.csv 4758 applying the maximum likelihood approach59 and the maximum-curvature method60.(i) The b-value is estimated by analyzing the frequency-magnitude distribution by the Gutenberg–Richter law46. Estimates of the radiated energy of earthquakes E is derived from the local magnitude ML of the earthquake61 .(ii) The energy rate max and m0 correspond to the largest magnitude and to the Mc in the considered time window, A is the area of finite extension including the events (in km2). The seismic rate λ is obtained considering the number of events ΔN with magnitude larger than the completeness magnitude, Mc, that occurred in a time window ΔT in areas of finite extension A. The latter is computed as the convex Hull of the epicenters in each time window. The seismic rate is thus computed as follows:2)].Therefore, 43 computes the generalized distance between pairs of earthquakes, η, by an analysis of the time–space distances between pairs of earthquakes. η is obtained by estimating the distances in time  and space  between an event i and its parent j, where both distances are normalized by the magnitude of the parent event. The rescaled time and distance are computed as follows:m is the magnitude, b is the parameter of the Gutenberg–Richter law, which plays the role of exponential weight of the earlier event i by its magnitude, and Dc is the fractal dimension. Finally, η is defined as:The nearest-neighbor approach62, we set the b equal to 0 to mitigate the presence of artifacts due to the overlap of earthquakes’ domain of attraction with background seismicity, and we use Dc equal to 1.5.We compute η considering the epicentral location of the earthquakes. According to Zaliapin and Ben-Zion44 and we split the earthquakes population in clustered (C) and background (B) seismicity. Then, the proportion of nonclustered seismicity (PNS) is estimated for each fault segment and year as the ratio between the number of events (n) belonging to B and those of both C and B: PNS = nB/(nB + nC).We model the η distribution with a sum of a log-Gaussian functionSupplementary Figures.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.Supplementary Information 6.Supplementary Information 7.