Perinatally acquired HIV infection (PHIV) can confer neurodevelopmental risk. As children with PHIV increasingly survive through adolescence and into adulthood, understanding its long-term central nervous system (CNS) impacts is critical for maximizing adult outcomes and quality of life.Recently published neurocognitive and neuroimaging findings show impacts on the CNS associated with early HIV disease progression that endure into adolescence and young adulthood. Although developmental trajectories in adolescence largely appear stable, further research on maturational processes is indicated.Although early antiretroviral therapy in infancy appears to be protective, it is not universally available and current youth largely developed without its benefit. The neurocognitive effects of HIV and the multiple other risks to neurodevelopment experienced by youth with PHIV call for further longitudinal research and a multifaceted approach to prevention and intervention. Despite our ability to prevent mother to child transmission of HIV through administration of antiretroviral therapy (ART) during pregnancy, birth, and breastfeeding, pediatric HIV continues to be a global concern, with 150,000 new pediatric infections worldwide in 2019 , 4. As gThat HIV can have significant neurologic and neurocognitive effects has been well known since the early years of the epidemic, and prior to the introduction of ART, particularly combination ART (cART) in 1995, perinatal acquisition was associated with a high risk for poor brain development, encephalopathy and other neurologic sequelae , 7. In bA number of recent reviews have summarized the literature on cognitive and neuroimaging findings among children with PHIV , 8–15. IAcross the pediatric HIV literature, a key predictor of altered neurodevelopment has been history of HIV disease severity, generally with stronger associations than current immune functioning or viral activity. Significantly lower functioning is often reported among children with PHIV and a history of CDC Class C, or AIDS, diagnosis , particuGiven this, it is clear that research on children more recently born with PHIV cannot easily be extrapolated to those who are currently adolescents or, particularly, young adults who progressed through neurodevelopment in an earlier era of HIV treatment. Although there is wide variability across countries, current adolescents with PHIV in lower-income settings such as sub-Saharan Africa initiated ART at a median of almost 8 years of age  and haveThis research remains relevant despite significant changes in treatment strategies for two reasons. First, youth with PHIV have the prospect of long lives, accompanied by the opportunities and responsibilities faced by any young adult. By addressing the unique experience and effects of PHIV for youth, scientists and clinicians can prepare and assist them in their transition to adulthood and maximize their long-term health and quality of life. Neurocognitive functioning has been linked with a variety of daily functioning, educational/occupational, and behavioral outcomes  among children with PHIV –35. HoweSecond, despite guidelines for initiating ART during infancy for those with PHIV, there continue to be significant numbers of children who do not receive early ART, with only about half of children with PHIV in sub-Saharan Africa having access to ART in 2019 . A far lThe goal of this article is to highlight selected recent (since 2015) articles on CNS functioning and integrity among adolescents and young adults with PHIV, primarily studies focused on youth age 10 and up to reflect current definitions of adolescence . Relevanhttps://phacsstudy.org/About-Us) [Several longitudinal cohort studies of children and youth with PHIV, ongoing on several continents, have in recent years published findings regarding neurocognitive functioning in participants as they reach and proceed through adolescence. Among the larger cohort studies now following adolescents are the PREDICT study of the impact of early versus deferred ART initiation conducted in Thailand and Cambodia , 39, 40 bout-Us) .n=125) and without  PHIV exposure [The RESILIENCE substudy of PREDICT examined long-term cognitive and behavioral functioning of 231 youth with PHIV age 10-24 and age- and sex-matched youth with , PHIV and Class C diagnosis , and PHEU (n=79). A series of publications [The Memory and Executive Functioning substudy of PHACS assessed youth age 9–18 with PHIV and no Class C diagnosis  and 17 . Although both groups were majority Black, those with PHIV were more likely to be born in sub-Saharan Africa and to be adopted or in foster care. Youth with PHIV had lower performance than those without on most measures, both groups performing lower than standardization samples. However, although change was similar on most measures, the performance of youth with PHIV on executive functioning tasks dropped over time despite good overall viral control, while that of the HIV- group remained stable. The authors interpreted the increasing difference in executive functioning over time according to the “growing into deficit” hypothesis, i.e. impact on executive functioning will become more apparent as youth enter a stage of rapid maturation of that domain. Thus, although stability in most cognitive domains in these studies is reassuring, the suggestion of a decline in executive functioning relative to age expectations among those with PHIV requires additional study, particularly in light of this domain’s importance to maintenance of health, acquisition of skills for transition to adulthood, and decision-making in behavioral risk contexts. In addition, their functioning remains depressed compared to societal age expectations, emphasizing the importance of preventive and rehabilitative interventions. A recent study including younger children, limited to PHIV, that used group-based trajectory analysis identified three distinct trajectories; risks for poor outcomes included older age at ART initiation and poverty [Most recently published analyses of adolescent neurocognitive functioning have been cross-sectional, but increasingly, change is being examined. A two-year follow-up of youth enrolled in the PHACS memory and executive functioning study described above showed stable functioning over time for all three groups . It shou poverty .As more youth with PHIV have survived into adulthood, an increasing number of publications have presented findings regarding their neurocognitive functioning, largely in North America and Europe where effective ART first became widely available but in some cases including a large proportion of immigrants. The Adolescents and Adults Living with Perinatal HIV (AALPHI) study in England  enrolledRobbins and colleagues • enrolleOther recently published studies of young adults are limited by small sample sizes or the lack of a matched comparison group. Willen and colleagues used MRI and a brief assessment of cognitive functioning focused on executive functioning to compare 29 young adults with PHIV, ages 18–24, to 13 healthy community controls in the USA . They foCoutifaris and colleagues took an interesting approach to examining the influence of age at HIV infection on neurobehavioral functioning . In thisSeveral recent systematic reviews have summarized neuroimaging studies of children and adolescents with PHIV across both higher- and lower resource settings , 14, 57.The majority of recent studies address brain structural findings by comparing youth with PHIV to age-matched youth without HIV infection –62 or toSeveral recent papers have focused on structural measures such as cortical thickness, surface area, and gyrification , 65•, 66As of yet, few longitudinal neuroimaging studies have examined maturational changes during adolescence in the context of PHIV. Yu and colleagues followed 16 Chinese youth with PHIV and 25 without, age 11–17, for one year with repeat measurement of gray matter volume and cortical thickness along with cognitive testing . AlthougFew studies published since 2015 have examined functional connectivity and brain networks among adolescents to young adults with PHIV. In the only recent study to use resting state functional MRI (rs-fMRI) with young adults with PHIV, Sarma  showed hSeveral decades of both human and animal research have shown that the developing CNS is vulnerable to HIV and that its effects are distinctive and potentially clinically profound. In recent years, sufficient numbers of young people with PHIV have reached adolescence and young adulthood for a literature regarding neurocognitive and neuroimaging complications during this period of life to develop. The youth participating in this research largely represent those survivors who passed through infancy and early childhood prior to current guidelines recommending cART initiation upon diagnosis of HIV, preferably in early infancy. Many of those now in young adulthood experienced monotherapy, resistance to some medications, and second line therapies during development. Thus, the findings of these studies do not represent the ideal scenario for CNS development of children with PHIV; however, sadly, this ideal scenario often does not occur even today for many children, with significant impairment and encephalopathy remaining issues in lower resource settings . This giIn general, the results of recent studies involving adolescents and young adults with PHIV are consistent with previous observations of an enduring impact on CNS structure and functioning among those with past significant disease progression. This impact is apparent, particularly in specific cognitive domains and brain systems, even following periods of good viral control and extending into adulthood. There is greater variability across studies regarding youth without Class C diagnoses, with some showing differences from PHEU or unexposed youth and others finding that they are comparable once potential sociodemographic influences are taken into account. As longitudinal analyses of maturation across adolescence and into young adulthood have appeared, they have generally shown similar trajectories of development among youth with and without PHIV . HoweverAs shown in previous studies of children and younger adolescents, this literature suggests optimism in that the majority of youth with PHIV do not have severe impairments  and dispThe prevention and treatment of CNS sequelae among youth require a multifaceted approach. The most important strategy currently known for prevention of PHIV impacts on the CNS is early and effective antiretroviral therapy. Thus, the goal of ensuring the best youth outcomes requires global efforts to provide early ART for those children who are born with HIV. Because of the sensitivity of the developing CNS, studies on optimization of ART to balance effectiveness with neurotoxicity and address issues such as penetrance of medications through the blood-brain barrier are critical , 10, 12,A second class of prevention strategies is through addressing the multiple other neurodevelopmental risks faced by children and adolescents with PHIV outlined above. These include structural change to reduce poverty, trauma and adversity, food insecurity, air pollution, systemic inequality and racism, educational and health inequity, and other risks to which children with PHIV are disproportionately exposed –105. ComBoth research and clinical care regarding long-term CNS problems among those with PHIV rely on measures sensitive to neurocognitive impacts of HIV and treatment that may be subtle. Cognitive and neuroimaging measures should be able to distinguish influences of other developmental risks as well as HIV, reflect maturational processes specific to adolescence and young adulthood, and be appropriate to use longitudinally, minimizing or controlling for repeated measurement effects. Most studies in both the pediatric and adult HIV literatures have used standardized measures of developmental and neuropsychological functioning, sometimes examining their contextual validity or developing local normative data and more commonly by using matched comparison groups . IncreasUltimately, prevention of the CNS complications of PHIV is best achieved through prevention of PHIV itself. As the world works towards achieving that goal, strategies to maximize adult outcomes for children now being born with PHIV, and those youth living with its effects, will require the commitment of significant resources towards research, prevention, and intervention .


The purpose of this article is to demonstrate and evaluate aspects of a Stakeholder-Driven Community Diffusion (SDCD)–informed intervention with a group of stakeholders drawn from a large coalition seeking a novel approach for promoting policy, systems, and environmental-level change. The objectives were to implement an SDCD intervention, assess changes in participants’ perspectives, and evaluate where the group’s actions fit within the context of a systems map that the group created during the intervention.An SDCD-informed intervention convened 12 multisector stakeholders from the Early Ages Healthy Stages coalition in Cuyahoga County, Ohio. They participated in group model building activities to promote systems thinking related to childhood obesity prevention, reviewed evidence about topics of interest to the group, and were provided with technical assistance and seed funding to guide the selection and implementation of actions prioritized by the group.Data were collected via meeting notes and group model building outputs to demonstrate implementation and action prioritization; online surveys and qualitative interviews to measure perspective change among stakeholders; and a follow-up survey to the broader coalition assessing actions coalition members were taking.An SDCD-informed intervention guided the development of a systems map and the selection of 4 actions: 1) develop a better understanding of the local early childcare environment; 2) assess the effectiveness and impact of Ohio Healthy Programs (OHP); 3) advocate for OHP and improved early childhood education quality; and 4) hold OHP designees accountable to high-quality programming. Data collected from surveys and interviews showed increased awareness of programs, resources, and collaboration opportunities among stakeholders. Follow-up survey results showed ongoing coalition action throughout the systems map.Using an SDCD-informed intervention among a coalition of community stakeholders provided a unique approach for implementing, assessing, and analyzing collaborative efforts to prevent childhood obesity in Cuyahoga County. Our approach can be applied to help researchers and stakeholders improve efforts to address childhood obesity in their communities. Obesity is a complex problem with many interconnected drivers and impacts. Combining systems science thinking and policy, systems, and environmental-level change, as implicated in the Stakeholder-Driven Community Diffusion (SDCD) theory, has been successful in addressing obesity.This report describes how an SDCD-informed intervention was used to engage a small group of multisector stakeholders drawn from an existing coalition to collectively prioritize obesity prevention action steps and work together to implement those steps. The report also describes use of a systems map to evaluate where action was taking place after the intensive intervention phase concluded.The findings from this report offer an approach for community coalitions interested in using a theory-informed approach for facilitating policy, systems, and environmental-level changes to promote healthy weights among children in their communities.Many public health challenges, including obesity, are complex in that they are driven by multiple factors that interact over time ,2. ApplyPSE change adoption, implementation, and maintenance requires buy-in from various stakeholders and collaboration across settings and sectors . Cross-sStakeholder-Driven Community Diffusion (SDCD) is a theory that aims to address that gap by proposing a mechanism of how cross-sector collaborations such as community coalitions influence stakeholder members, and in turn, how these members influence the PSEs that shape child health ,16. SDCDOur research team used the SDCD theory to inform an intervention that targets specific constructs and processes. The intervention was pilot tested  and was The purpose of this study was to evaluate aspects of an SDCD-informed intervention with a group of stakeholders drawn from a large, existing community coalition seeking a novel approach for promoting PSE change in their community. The objectives of the study were to assess changes in participants’ perspectives after taking part in the intervention and evaluate where the group’s actions fit within the context of a systems map that the group of convened stakeholders created during the intervention.Early Ages Healthy Stages (EAHS) is a coalition led by the Cuyahoga County Board of Health focused on early childhood health and wellness in Cuyahoga County, Ohio. The EAHS coalition grew out of a 2014 task force that was assembled by a group of funders, political leaders, and decision makers to reduce early childhood obesity in Cuyahoga County. EAHS now includes 85 agencies representing sectors influencing early childhood health . The coalition supports programs and initiatives by providing technical assistance and promotes resource and information sharing between member organizations. One initiative is the Ohio Healthy Programs (OHP), a free training and technical assistance program for early childcare and education professionals in Ohio, focused on promoting policies and practices that encourage healthy eating, physical activity, and family engagement strategies to prevent and reduce early childhood obesity . OHP inchttps://childobesity180.org/) to implement and evaluate an SDCD-informed intervention in their community.Despite widespread community support for early childhood health and EAHS’s strategic goal of expanding OHP in Cuyahoga County, the coalition’s work remained siloed within sectors while nontraditional partners such as mental health care providers struggled to see the role that they and their organizations played in early childhood obesity prevention in Cuyahoga County. These barriers inspired EAHS leadership to investigate how a systems approach could unite community efforts, leading to the development of a partnership with ChildObesity180 at Tufts University . The group of multisector stakeholders that was convened for the intervention was called the Action Building Committee (henceforth referred to as the “Committee”) and included 12 key stakeholders selected from the EAHS Coalition. EAHS leaders identified 10 Committee members, with input from the research team on sector representation. The 2 remaining positions were chosen by coalition-wide nomination. The Committee represented 8 sectors: nutrition assistance programs, early education, center-based childcare, home-based childcare, public health department, community-based organization, private business, and philanthropy. The Committee received a stipend for participating in approximately 50 hours of intervention and evaluation activities over 10 months.The SDCD-informed intervention was implemented in 2 phases in Cuyahoga County: 1) an intensive phase in which the research team facilitated Committee meetings and 2) a technical assistance phase in which the research team, which included EAHS leadership, continued to work to advance priorities identified by the Committee. The first step of the intervention was to convene the Committee . Next, tIn Cuyahoga County, the intervention included monthly meetings with the Committee that were facilitated by the research team. The first 7 meetings used group model building to gain a deeper understanding of factors driving and impacted by early childhood health in Cuyahoga County. The research team used free group modeling building scripts from Scriptapedia to plan and facilitate group model building activities . ScriptsThe research team planned the monthly meetings. Each meeting followed a general structure: introduction, brief evidence shares, group model building activity, group discussion, and reflection . HoweverStarting with the second meeting, the research team shared evidence from peer-reviewed and gray literature related to each meeting theme to increase Committee members’ understanding of topics related to early childhood health. In response to Committee members’ expressed interests, evidence share topics included the connection between early childhood education and health, promoting community health through equitable food systems, assessment of child health and health care in Ohio, and a roundtable discussion on obesity solutions with local leaders.Data collection included meeting notes and group model building outputs to demonstrate implementation, online surveys and interviews to assess Committee member perspective shifts, and a follow-up survey to identify actions taken by the EAHS following the SDCD-informed intervention with the Committee .The research team recorded meeting notes at each Committee meeting to document meeting facilitation, activities, and actions that the group prioritized. Additionally, Committee members developed tangible outputs during group model building activities, including graphs and system maps that depict key concepts and relationships discussed by the group . The resCommittee members were surveyed about shifts in their perspective related to early childhood obesity prevention in Cuyahoga County. Participants were asked via multiple-choice questions whether they had experienced a perspective change related to early childhood obesity prevention and whether a person in the Committee, participation in the Committee, or both influenced the change. Questions about perspective shifts were embedded in a longer survey that took approximately 20 minutes to complete. The survey was written in English and disseminated using Qualtrics, an online survey platform, and was administered during months 5 and 9 of Committee meetings. Only data from month 9 were used in this study to assess perspective shifts at the final stage of Committee meetings. Survey questions about perspectives shifts were tallied and frequencies were reported.One member of the research team (J.A.) conducted interviews with Committee members at baseline and at the conclusion of the study. That member of the research team also assisted with Committee meeting facilitation. The same interview questions were asked at both points. An SDCD-informed interview guide was designed to capture perspective changes related to early childhood health and early childhood obesity prevention between baseline and the end of Committee meetings . QuestioFourteen months after the conclusion of Committee meetings, the research team distributed another online survey to all members of the EAHS coalition (n = 387) to understand the actions that had been taken related to early childhood health in Cuyahoga County. This survey was different than the one used to assess shifts in perspectives. The survey was sent 14 months after the Committee meetings ended to capture actions that may have been inspired by the intervention but that take time to initiate. Using the systems map developed by the Committee , particiThroughout the study, an average of 90.7% of the 12 Committee members attended either originally scheduled  or make-up meetings , except for the final meeting. Only 3 Committee members attended the final meeting due to poor weather and the meeting being scheduled on a holiday. Committee members who did not attend received an email that provided information from the meeting. Committee members produced outputs throughout the series of group model building activities, including graphs depicting obesity-related variables changing over time and multiple versions of a causal loop diagram . Over seThe final systems map developed by the Committee included 81 variables, organized into 8 main themes: healthy diet, engagement, political will, health care, physical activity, social emotional health, funding, and health and wellness in early childhood education settings . The sysAn impact feasibility grid was the last group model building output from the Committee. Committee members brainstormed intervention ideas or actions they could take to improve the system depicted in their systems map and ranked each idea based on its potential impact and feasibility. Next, the group voted on the items, reviewed relevant scientific evidence provided by the research team, and ultimately identified 4 actions.After participating in group model building activities and reviewing evidence, the Committee prioritized the following actions to promote PSE change in early childcare settings: 1) develop a better understanding of the early childhood education system in Cuyahoga County, 2) assess the effectiveness and impact of OHP, 3) advocate for OHP and improved early childhood education quality, and 4) hold OHP designees accountable to meeting their objectives. Each of these actions reinforced an overarching goal of strengthening OHP, a goal chosen for its broad impact potential as seen in the systems map and impact feasibility grid, as well as its alignment with the EAHS strategic plan.The Committee and research team worked together to advance the 4 prioritized actions . To deveSurvey responses by Committee members showed perspective changes after engaging in group model building activities. After 9 months, 9 Committee members (75%) noted a change in their perspective on early childhood obesity prevention, specifically, an increase in awareness of programs, resources, and collaboration opportunities in the early childhood education setting. Five members indicated that another member of the Committee influenced the change. The 9 members who reported a perspective change all reported that their involvement in the Committee influenced the change, referring to the following specific aspects of their participation: exposure to diverse perspectives, participating in committee meeting activities, working with committee members, exposure to diverse roles, and scientific evidence presented to the Committee.Similar perspective shifts were reported in qualitative interviews of Committee members that were conducted at baseline and at the conclusion of Committee meetings, with all 12 members of the Committee completing both interviews. The interviews highlighted an appreciation for the Committee experience and new collaboration opportunities within the group (“I enjoyed strengthening the relationships with the other persons that were participating . . . I definitely have a newfound appreciation and feel like I know more now than I did a year ago”). These interviews also demonstrated increased knowledge of resources and of county-wide childhood obesity prevention efforts that are under way , as well as a recognition of systems influencing childhood health in the county .Sixty-three (16%) of 387 EAHS coalition members completed the follow-up survey 14 months after the conclusion of Committee meetings. Of respondents, 30% identified their primary sector as center-based childcare; 19%, early education; 15%, community-based organization; 11%, home-based childcare; and the remaining 25% of respondents representing health care, Cuyahoga County Board of Health, philanthropic organizations, parents, university, and other sectors. The survey asked participants to select variables they were working on within the systems map generated during group model building activities. Of the 81 variables, the most frequently selected were physical activity (n = 19 selections), family engagement (n = 18), food access (n = 15), social emotional health (n = 15), Child and Adult Care Food Program (n = 12), community engagement (n = 8), Step Up To Quality standards (n = 8), and trauma-informed care (n = 8). Although not conclusive given the low response rate, these variables show ongoing work in the engagement, healthy diet, social-emotional health, and physical activity subsystems of the systems map, while also indicating a potential lack of activity in the political will, funding, health care, and health and wellness in early childhood education settings subsystems. The results of this follow-up survey suggest that sustained efforts are needed in early childhood health, building on the actions prioritized by the Committee. Results of this survey provide EAHS with a rough estimate of where work is ongoing within the system and where the coalition could focus their efforts to reinforce existing efforts or to fill in gaps.This study demonstrates how the SDCD theory can inform PSE-level initiatives and sustained community-led action. The study engaged 12 stakeholders from the EAHS coalition in Cuyahoga County to develop a holistic view of the system influencing early childhood obesity in their county and use those insights to generate and implement action in their community. The research team shared information throughout the intervention to encourage the group to select evidence-based actions. The actions focused on the early childcare system in Cuyahoga County and strategies for expanding OHP, which includes PSE approaches to support healthy eating and physical activity among young children. Stakeholders reported that the SDCD theory–informed intervention influenced their knowledge of the problem of early childhood obesity and their awareness of resources and collaboration opportunities to address the problem. Additionally, the follow-up action survey provides a unique approach for assessing ongoing work in a community. The systems map developed by the Committee allows EAHS leadership to better understand what is driving and what is affected by the work of the coalition and create or adapt coalition priorities as necessary.Our approach in Cuyahoga County responds to the call for researchers and practitioners to use systems thinking and community engagement to promote public health ,37. ImprOur approach is generalizable in many ways. Community coalitions exist across the US, and decades of research indicate that coalitions may be amenable to working with scientists to try new strategies and engage in data collection activities. Conducting group model building activities that yield meaningful systems insights that can be shared within a group takes skill and training, which can be a limiting factor when using group model building to implement an SDCD-informed intervention as described here. Increasing training opportunities for group model building and community-based system dynamics could increase the pool of graduates and professionals who could implement interventions that use those methods. The main costs of implementing this intervention are salaries for those implementing and evaluating the intervention, stipends for intervention participants, and seed funding to initiate community-based actions. Grant funding was secured from a foundation to cover the costs of implementing the intervention described in this study. Finally, the SDCD theory and SDCD-informed intervention could be applied to a variety of public health concerns beyond childhood health, because the theory describes processes and mechanisms not specific to a single public health concern.This study also has limitations. We cannot isolate the effect of our SDCD process from the effects of general facilitation with a group because we had no control group. Future studies should include a comparison group. Building on systems thinking and modeling capabilities developed within this group, future work using group model building as a process for engaging stakeholders in Cuyahoga County could work toward more rigorous causal loop diagrams or formal system dynamics models with simulation to enable deeper system insights . FurtherTo conclude, an SDCD-informed intervention offered the EAHS coalition a new approach for member engagement, leading to a large systems map of factors driving childhood obesity and health in Cuyahoga County. This galvanized community-level action intended to improve the system influencing early childhood health in the community. The coalition continues to use the systems map to communicate the interconnectedness of childhood obesity–related factors across sectors. The coalition also uses the systems map to plan and evaluate their work toward their vision.


Chinese students are extremely vulnerable to developing mental illness. The stigma associated with mental illness presents a barrier to seeking help for their mental health.Linking Hearts—Linking Youth and ‘Xin’ (hearts) project is an implementation science project that seeks to reduce mental illness stigma and promote the mental health of university students in Jinan, China. The Linking Hearts project consists of 3 components. In this paper, we outline the protocol for the first component, that is, the contextual assessment and analysis of the mental health needs of university students as the first step to inform the adaptation of an evidence-based intervention to be implemented in Jinan, China.The Six local universities will participate in the Linking Hearts project. A total of 100 students from each university (n=600) will engage in the contextual assessment through self-report surveys on depression, anxiety, stress, mental health knowledge, and mental health stigma. Quantitative data will be analyzed using several descriptive and inferential analyses via SPSS. A small number of participants (144 students and 144 service providers) will also be engaged in focus groups to assess the socio-environmental contexts of university students’ health and availability of mental health resources. Qualitative data will be transcribed verbatim and NVivo will be used for data management. Social network analysis will also be performed using EgoNet.Linking Hearts was funded in January 2018 for 5 years. The protocol of Linking Hearts and its 3 components was approved by the research ethics boards of all participating institutions in China in November 2018. Canadian institutions that gave approval were Ryerson University (REB2018-455) in January 2019, University of Alberta (Pro00089364), York University (e2019-162) in May 2019, and University of Toronto (RIS37724) in August 2019. Data collection took place upon ethics approval and was completed in January 2020. A total of 600 students were surveyed. An additional 147 students and 138 service providers took part in focus groups. Data analysis is ongoing. Results will be published in 2021.Acceptance and Commitment to Empowerment-Linking Youth N’ Xin intervention model. The results of this contextual assessment will be used to inform the adaptation and refinement of the mental health intervention to promote the mental health of Chinese university students in Jinan.Findings from this contextual assessment and analysis will generate new knowledge on university students’ mental health status, mental health knowledge, and resources available for them. These findings will be used to adapt and refine the RR1-10.2196/25009 Young people constitute a particularly vulnerable population for the onset of major mental illness . In ChinA number of evidence-based strategies have been used in the past to address system-level challenges, promote mental health, reduce stigma, and build capacity in individuals. One particular approach is the use of acceptance and commitment therapy (ACT), which is an evidence-informed, transdiagnostic intervention approach that is grounded on mindfulness . ACT hasAnother approach that may be effective is group-based empowerment psychoeducation (GEP). This evidence-based approach is an adoption of traditional psychoeducation, whereby education extends beyond the provision of health information to include dialogue and critical reflection on the structural determinants of health and approaches that promote collective empowerment and capacity building among participants . GEP hasContextual Assessments and Analysis, co-designed by the original intervention team and the knowledge user team, can provide critical information about the “who,” “what,” and “how” that are essential to ensure that the adapted intervention is relevant and effective to meet the sociocultural contexts of the intended end users and local stakeholders [A growing body of evidence suggests that effective application and uptake of an evidence-based intervention must be informed by the contextual needs of the intended new users of the intervention ,19. The eholders . The useeholders .Linking Hearts—Linking Youth and ‘Xin’ (hearts) project is an implementation research undertaken by a Canada-China research partnership. The Linking Hearts team consists of over 30 interdisciplinary Canadian and Chinese researchers. This project is guided by a socio-ecological approach with the theoretical assumption that people’s experiences and health are influenced by factors at the individual, organizational, community, and societal levels. Since individuals shape and are shaped by their social contexts and environments, mental health challenges are too complex to be addressed from single-level analyses, and effective mental health interventions must consider multi-level contexts [The contexts .Acceptance and Commitment to Empowerment-Linking Youth N’ Xin (ACE-LYNX) for use with university students.The objectives of Linking Hearts are to (1) improve access to quality mental health care for university students in Jinan, Shandong Province, China; (2) reduce stigma against mental illness that impedes help-seeking, targeted prevention, early identification, timely treatment, and optimal recovery; (3) improve interdisciplinary collaboration through collective empowerment and capacity building; and (4) advance implementation of science knowledge in the field of community mental health practices/interventions that can be scaled up in other real-life contexts. The overarching goal of Linking Hearts is to evaluate and document the process of intervention implementation and the resultant knowledge uptake by stakeholders and decision makers to transform existing professional capital in health and social care into expanded capacity in mental health care for university students. The processes of adaptation and implementation utilize an integrated, evidence-informed mental health intervention model, namely, acceptance and commitment to empowerment (ACE), which combines concepts and processes from ACT and GEP, and were found to be effective in reducing mental illness stigma and promoting mental health among Asians and other racialized groups in Canada . Specificontextual assessment and analysis with service providers and students to inform the adaptation of the ACE intervention; (2) implementation of the refined ACE intervention with service providers and university students; and (3) integrated knowledge translation to engage diverse groups of knowledge users throughout all stages of this study. The Linking Hearts project activities are informed by the implementation science RE-AIM  framework of project planning that seeks to improve the sustainability of interventions by examining the reach, effectiveness, acceptability, implementation, and maintenance [contextual assessment and analysis of mental health needs of Chinese students. In this component, we will engage service providers and university students to explore and identify the common mental health issues faced by students, their mental health literacy, and the contextual factors relevant to their mental health and resilience.The Linking Hearts project consists of 3 components: (1) ntenance . This paAs Linking Hearts is an international multi-interdisciplinary collaborative implementation research and the ACE intervention was developed and tested with Asian and racialized people in Canada, it is critical for the team to first conduct a contextual assessment and analysis of the needs of the students in Jinan. To effectively adapt ACE into the ACE-LYNX intervention for use with university students in Jinan, we will engage service providers and university students from 6 universities to identify the contexts and socio-environmental factors that determine the acceptability, feasibility, and effectiveness of ACE-LYNX. We will assess the psychological, cultural, social, and environmental contexts of university students in Jinan to gain a better understanding of their mental health needs in terms of not only challenges but also the resilience and protective factors of their mental health ,24. KnowThe conceptualization of the Linking Hearts Project was developed during a field visit by Canadian team members to Jinan. During this field visit, Canadian team members met with student groups, researchers, service providers at a community health center, and clinicians at the provincial mental health center. When the Linking Hearts Project was funded, the Jinan team also did a field visit to Toronto to meet with clinicians, on-campus counsellors, and community-based service providers to learn about community mental health. After these 2 field visits, the 2 teams held many teleconferences to develop the contextual assessment questions and data collection tools. The Linking Hearts Project was developed collaboratively between academic researchers and knowledge user researchers from Jinan, including counsellors on university campus and clinicians working in the mental health field. This study engages 2 participant populations—service providers and students. The researchers, professors, and service providers who are collaborators will be involved in the outreach and promotion to participants but not in direct recruitment.The Linking Hearts project and study protocols have been approved by the research ethics boards of all participating institutions in China and Canada. Canadian institutions include Ryerson University (REB 2018-455), University of Toronto (RIS 37724), University of Alberta (Pro00089364), and York University (e2019-162). Informed consent will be obtained from all participants prior to data collection. The team will employ both qualitative and quantitative tools for data collection, including self-reported questionnaires, general response surveys, and focus groups conducted with students and service providers .The survey and questionnaire instruments will include the following:Student demographics: To better understand the social, economic, and cultural contexts of the university students whom we will engage in ACE-LYNX training, we will collect information on their background characteristics, program of study and year in program, living arrangement, family history, and family socioeconomic background.Self-reported psychological symptoms: We will use the depression, anxiety, and stress scale (DASS-21), a widely used measure of self-reported mental health symptoms . This meMental health literacy: Mental health knowledge and literacy will be evaluated using the mental health knowledge questionnaire (MHKQ) . This meMental illness stigma: The community attitudes toward mental illness (CAMI) scale is a 40-item questionnaire that measures externalized stigmatizing attitudes toward those with mental illness . These iIn addition to surveys and quantitative measures, participants will also be asked to identify their top mental health concerns, perceptions of the causes of mental illness, and areas of prioritization for service provision and training of health care professionals. We will list mental health resources based on information from the regional research team and advisory committees and ask participants to indicate whether they are aware of or have utilized them personally. In addition, participants will also be asked to list who they would turn to for advice regarding mental health issues. A small number of participants (144 university students and 144 service providers) will be recruited equitably from participating institutions by using stratified random sampling to participate in focus groups to explore (1) participants’ perspectives on mental health and mental illness, (2) common mental health needs of university students and the influencing factors, (3) how university students understand and respond to their mental health needs, (4) facilitators and barriers to accessing mental health care, (5) strategies to engage university students in mental health promotion and to improve access to care, and (6) participants’ perceived acceptability of the ACE-LYNX intervention to promote mental health among university students.The target populations are health and social care providers and university students at 6 universities in Jinan, Shandong, China. The 6 universities were chosen based on (1) the diversity of the student population, that is, students from local and rural areas, (2) the diversity of disciplines and programs, and (3) their locations in each of the 3 regions within Shandong, China.We will recruit 600 participants (100 per university site) to take part in a survey of general mental health-related symptoms, including depression, anxiety, and stress (DASS-21), stigma of mental illness (CAMI), mental health literacy (MHKQ), and mental health resources. Other measures evaluating clinical mental health symptomology were not included, as the purpose of the contextual analysis is to observe trends in mental health and resources supporting mental well-being. Inclusion criteria for participation include students, self-identified as 18 years of age or older, and attending 1 of the 6 partnering universities in Jinan . They wiAt each university, we will host 2 focus groups (12 people each) with a total of 144 service providers to take part in a needs assessment. Inclusion criteria are service providers who self-identified as 18 years of age or older and provide health care, social care, or supportive services to university students in Jinan. Participants will first complete basic demographics information and information to identify concerns and needs in mental health care. Service providers participating will include psychiatrists, primary care physicians, nurses, social workers, university counsellors, and youth league leaders. Similar to above, focus groups will explore the complex contexts and factors of mental health issues among university students as well as identify training needs.Partner organizations will keep track of and establish a 6-month baseline on quantities and types of services used by students. These organizations will include university counselling centers, individual school/faculty/departments at the 6 partner universities, community hospitals and clinics, and other regional organizations with stakes in the promotion of mental health and well-being of university students. These data will be used to measure reach and effectiveness.Quantitative data, including demographic information and descriptive statistics of the psychometric measures, will be tabulated from the student surveys by using SPSS (IBM Corp). Quantitative data will provide descriptive and inferential details regarding mental health trends and identify important resources for students and areas of needs regarding mental health support and service utilization. In addition, these mental health resources, including use of institutional programs and trusted advisors/consultants, will be collected, analyzed, and visualized with social network analysis methods using EgoNet (University of Florida). Qualitative data from focus groups will be transcribed verbatim, and NVivo  will be used to aid in data management. We will use both inductive and deductive approaches to analyze the data. We will start with repeated readings of the transcripts to gain a broad understanding of the data. We will then perform line-by-line coding of key themes specific to the ideas articulated by the participants, followed by coding concepts/ideas posed in our research questions and derived from our theoretical understanding .Linking Hearts was funded in January 2018 for 5 years. The protocol of Linking Hearts and its 3 components was approved by the research ethics boards of all participating institutions in China in November 2018. Canadian institutions that gave approval were Ryerson University (REB2018-455) in January 2019, University of Alberta (Pro00089364), York University (e2019-162) in May 2019, and University of Toronto (RIS37724) in August 2019. Data collection took place upon ethics approval and was completed in January 2020. A total of 600 students were surveyed. An additional 147 students and 138 service providers took part in focus groups. Data analysis is ongoing. Results will be published in 2021.The results of the 3 types of data, that is, quantitative, qualitative, and social network, will form the basis of the contextual framework to guide the adaptation of the intervention to best suit the unique contexts and needs of Chinese university students in Jinan. Specifically, they will inform the adaptation of the psychoeducational component of the intervention . For example, aggregated survey results and relevant local statistics will be used to highlight the current trends of the mental health status and needs of university students. In addition, thematic analyses from the focus groups will inform the development of case examples used in the mental health education. Findings from the contextual assessment will be made available on the Linking Hearts project website.


Poor bone health in children increases the risk for fracture. Further, conditions that impact the structural framework of bone and its mineralization may lead to deformed bones. The childhood and adolescent years are a critical period for bone accrual with 50% of peak bone mass being achieved during the adolescent years, and more than 80% by 18 years  and intramuscular depot medroxyprogesterone acetate (DMPA) on bone accrual in adolescents; COCs by reducing insulin like growth factor-1 (IGF-1) levels, and DMPA by reducing estrogen levels. In contrast, the few studies that have examined effects of progestin implants and progestin releasing IUDs (long acting reversible contraception) on bone do not demonstrate deleterious effects. Some studies, but not all, suggest a higher risk of fracture among COC users during adolescence, and a higher risk of fracture is reported in those using DMPA. Bachrach concludes that further studies are necessary to clarify the impact of dose, duration of use, and route of administration of hormonal contraception on bone in adolescents.Use of hormonal contraception is now widespread, and while its benefits are well known, there is concern regarding its effects on bone, particularly during peak bone accrual. Allaway et al. expands on this theme and examines whether effects of oral and vaginal contraceptives on bone formation in young women are mediated via the growth hormone (GH)-IGF-1 axis. The authors use the IGF-1 generation test to test their hypotheses and report suppression of the peak IGF-1 response following recombinant GH (rGH) administration in the COC group, but not the contraceptive vaginal ring (CVR) or control groups, suggesting route dependency of this effect. They also report suppression of the bone formation marker, N-terminal propeptide of Type 1 procollagen, in both contraceptive groups, but not in controls, suggesting a route independent effect. The authors conclude that larger studies are necessary at all ages to expand on these results. Further, studies comparing the COC and CVR to the contraceptive patch are necessary.The paper by Schindeler et al. and Boyce et al. focus on disorders of phosphate metabolism. While our understanding of these disorders has increased markedly over the past two decades, much work is necessary to optimize management. Schindeler et al. review data regarding treatment with burosumab (a fibroblast growth factor 23 (FGF23) neutralizing antibody) for X-linked hypophosphatemia (XLH) and conditions such as tumor induced osteomalacia (TIO), epidermal nevus syndromes (ENS), and cutaneous skeletal hypophosphatemia syndrome. Short-term studies suggest that burosumab is both efficacious and safe in adults and children with XLH, TIO and ENS. However, studies are necessary to ensure that there is not an increased longer-term risk for nephrocalcinosis and cardiac calcifications with burosumab. The review by Boyce et al. focuses on the pathogenesis, presentation and management challenges of hyperphosphatemic familial tumoral calcinosis (HFTC), a rare disorder caused by either a deficiency or resistance to FGF23. The review describes the genetic basis for HFTC and also describes an acquired autoimmune form of hyperphosphatemic tumoral calcinosis. The paper discusses current approaches to therapy including a low phosphate diet, phosphate lowering, anti-inflammatory and anti-mineralization strategies, surgical resection, and physical and occupational therapy. Overall, no definitive therapies have been identified for this condition thus far.The reviews by Levine discusses treatment of rare genetic defects in the vitamin D pathway and difficulties in management. VDDR can be classified as: 1) the inability to either complete 25-hydroxylation or 1-hydroxylation of calciferols; 2) resistance to 1,25 (OH)2D from mutations in the vitamin D receptor (VDR) gene or the presence of a ribonucleoprotein that interferes with VDR-DNA interaction; or 3) excessive inactivation of vitamin D metabolites. The goal of treatment for these various forms is similar, and includes normalization of bone metabolism biochemistries  while monitoring for rickets and nephrocalcinosis, by replacing the deficient vitamin D metabolite and aggressive vitamin D and calcium supplementation.While vitamin D deficient rickets (VDDR) has been largely prevented/cured by supplementation, Ward outlines a blueprint for monitoring osteoporosis in children treated with glucocorticoids and provides guidance as to whether osteoporosis therapy may be indicated, discussing potential use of bisphosphonates as the current standard of care versus alternative potential agents that remain unstudied, including denosumab, teriparatide, and romosozumab.Glucocorticoid-induced osteoporosis in the pediatric population is unique with early vertebral compression fractures that have the ability to reshape depending on growth potential. Ferriero et al. report on the safety and efficacy of denosumab in the treatment of four children with multiple giant cell lesions of the jaw with Noonan syndrome. All children had improvement in clinical and radiographic symptoms. Adverse effects were as expected and included hypocalcemia during treatment and rebound hypercalcemia following cessation of denosumab. One child also experienced significant arthralgia on treatment independent of calcium dysregulation.Overall, the Research Topic covers a wide array of pediatric bone health conditions and treatment approaches that will become an important resource for professionals managing children and adolescents.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.JLC received funding support from the US National Institutes of Health . MM received funding support from the US National Institutes of Health .MM has served on the scientific advisory board of Abbvie and Ipsen, and as a consultant for Abbvie and Sanofi.The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Switzerland’s fragmented healthcare system mirrors its federal structure and mix of cultures and languages. Although the Swiss have a higher life expectancy than most of their neighbours, their healthcare system faces similar challenges that call for more integrated care (IC).This article aims to provide insight into the specificities of and latest developments in Switzerland’s healthcare system and how they may have influenced the development and implementation of IC there.The number of local IC initiatives has been growing steadily for 20 years. With a certain lag, various policies supporting IC have been established. Among them, a recent democratic debate on the federal mandatory health insurance law could either induce a radical move towards centralised support for IC or continue to support scattered local IC initiatives.In the future, Switzerland’s healthcare system will probably navigate between local IC initiatives and centralised, federal support for IC initiatives. This will be the reflection of a very Swiss way forward in a world without clear evidence on whether centralised or decentralised initiatives are more successful at developing IC. Switzerland’s slightly more than 8.5 million inhabitants live in the heart of Europe, unevenly separated into three main linguistic regions . Swiss r25Switzerland is a federal state in which government health responsibilities are split between the national, cantonal and municipal levels . The fedIn Switzerland, universal access to healthcare was established through a mandatory health insurance (MHI) introduced in 1994 . Followi11In addition to MHI, healthcare services have other funding streams, such as out-of-pocket payments, direct and indirect public funding, and other social insurance schemes. These streams vary  between Healthcare in Switzerland is provided by an array of private and public providers, ranging from individual to group practices and specialised institutions , to large hospitals and health networks . AdditioThis article aims to provide some insight into the specificities of and latest developments in Switzerland’s healthcare system and to discuss their influence on the development and implementation of IC.Over the past ten years, several programmes and policies have directly or indirectly favoured the development of IC in Switzerland. They are presented chronologically and succinctly described below.Endorsed by both the national and cantonal governments, these strategies aimed to develop common frameworks for managing these conditions. The strategies highlighted the specific professional expertise available but also the limited incentives for collaboration and coordination. Their recommendations included specific focuses on the continuity of care and on an optimised framework for interprofessional coordination and networking providers. Based on this, several cantons developed their own policy, and the recommendations above were included in subsequent national policies (see below).In 1998, a National Health Policy Dialogue was initiated by the national and cantonal governments to iteratively address the challenges facing Switzerland’s healthcare system. The resulting 2015 report on New Models for Primary Care called for IC and a more global approach to patients’ needs. Building upon the Chronic Care Model , this reThe Smarter Healthcare research programme, launched by the Swiss National Science Foundation, included 34 projects aimed at providing fresh insights and potential improvements to healthcare structures and utilisation. The synthesis of this programme is expected in 2022, and policy briefs will be issued in six areas: quality; patient choice; coordination and care models; costs and reimbursement; healthcare data; and communities of researchers, decision-makers and practitioners.disease management, focussing on health outcomes, towards care/case management, focussing on care processes—in line with recommendations from the literature on multimorbidity [This project aims to enhance the quality of care by focussing on improved processes for meeting patient’s various needs and ensuring the continuity of care. Without explicitly saying so, it is an attempt to shift from orbidity . This prorbidity  and the orbidity .Under the umbrella of a larger initiative tackling shortages of qualified healthcare professionals, this programme intended to foster the coordination of care and interprofessional collaboration. Good practice models were identified in educational as well as clinical settings 33. AdditThis strategy aims to redirect the healthcare system towards the prevention and management of chronic conditions. To this end, it strengthens health promotion and prevention, and it is also designed to improve health literacy, especially of vulnerable populations. Furthermore, it considers various health determinants and promotes inter-sectoral collaboration . Innovatively, it prompts federal and cantonal synergies in prevention.This national strategy aims to foster the process of digitalisation in health, thus increasing the quality of care and patient safety. The law on electronic health records (EHRs) was adapted concomitantly . AlthougGuide to Integrated Care [To celebrate its 100th anniversary, the Conference of Cantonal Health Directors commissioned a ted Care  providinBuilding on 2013’s National Health Strategy and lessons learned from the policies above, the 2020–2030 strategy has eight main objectives: i) exploit health data and technologies; ii) strengthen health literacy; iii) make more professionals and funding available; iv) enable healthy ageing; v) increase the quality and coordination of care; vi) control costs and their burden on deprived households; and improve health through better vii) natural and viii) work environments. This strategy promotes “coordinated care” - a synonym for IC in Switzerland - through various policy initiatives at the micro (between providers), meso (between organisations) and macro levels .Whereas the previous section reflects the cautious but steady calls for IC across Switzerland’s healthcare system, this section describes the actual advances in the implementation of IC.A national survey carried out in 2015 and 2016 aimed to produce a comprehensive overview of IC initiatives in Switzerland . The surSpecific groups ; ii) Mental health (26%); iii) Coordination of care (16%); iv) Healthcare centres (13%); v) Physicians’ networks (6%); and vi) Drug management (5%). Findings showed that the implementation of IC had accelerated over the past three decades. Indeed, whereas half of the 155 initiatives had started between 1990 and 2009, the other half had started between 2010 and 2016. The largest increase was found in the Specific groups and Mental health categories, two types of initiatives that require strong coordination and integration. Moreover, whereas Specific groups initiatives increased 3.5-fold between 1996 and 2009, but only 2-fold between 2010 and 2016, Coordination of care initiatives increased 4-fold and 4.2-fold, respectively. This might reflect an emerging shift towards initiatives fostering coordination of care processes instead of disease-centred initiatives.The survey allocated the 155 initiatives identified to one of the six following categories: i) Physicians’ networks and Healthcare centre initiatives, whereas in French- and Italian-speaking regions had more initiatives targeting Specific groups, Drug management and the Coordination of care. The range of professionals involved in initiatives varied too. The broadest spectrum was found in Healthcare centre initiatives , followed by Specific group initiatives .The survey also showed that until 2012, most initiatives occurred in Switzerland’s German-speaking regions. However, by 2016, 52% were being implemented in French- and Italian-speaking regions, 45% were in German-speaking regions, and 3% were across Switzerland. Furthermore, the types of IC initiatives were different between the regions. Indeed, German-speaking regions had more Secondary data analyses of this national IC survey explored the influences of organisation and the funding of care on the implementation of interprofessional collaboration. Findings suggested that financial barriers hindered the association of interprofessional collaboration and organisational improvements .Readiness to Change, Structure and Governance, Standardisation and Simplification, Funding, Breadth of Ambition, Innovation Management and Capacity Building). Results also varied slightly, with German-speaking respondents giving lower ratings to three items  than did French- and Italian-speaking respondents and higher ratings to Readiness to Change and Structure and Governance. Furthermore this survey highlighted several barriers to IC at two levels: at the professional level  and at the system level  [A more recent nationwide survey showed that the Swiss healthcare system’s readiness for IC could be improved . Indeed,al will) .Health patterns worldwide and in Switzerland have been changing 46. Indee34849These elements call out for improvements to IC. However, its potential to improve efficiency, patient safety and the quality of outcomes is only being exploited minimally in Switzerland, despite the various policies previously described showing that IC is acknowledged by growing numbers of stakeholders at the national, cantonal and local levels. This can probably be explained by Switzerland’s federal system . From a 95259606117Against this background, the most recent developments regarding IC in Switzerland are of particular interest. Indeed, an adaptation of the MHI law is currently going through Switzerland’s democratic discussion process , and it A mandatory first point of contact: all individuals would choose a first point of contact  for advice, treatment prescription or referral to another healthcare provider; the first point of contact would receive a flat-rate payment for each insured patient; exceptions to this mandatory contact would include emergency and gynaecological consultations.Coordinated care networks: these networks would bring together professionals from different disciplines to coordinate the entire care process; all services—including coordination activities—would be covered by a flat-rate payment.Patient care programmes: more evidence-based, structured processes of care—such as disease-management, prevention or rehabilitation programmes—would be developed; patients would be included in such initiatives more systematically.These three measures would bring major changes to Switzerland’s healthcare system. Indeed, they would i) recognize the worth and importance of coordination activities, ii) partly replace fee-for-service payments by flat-rate payment systems, and iii) mitigate the central role of single physicians and facilitate care and case-management activities by a range of professionals. Because of Switzerland’s democratic processes, these measures are still far from implementation. Indeed, the dichotomy between centralised control and decentralised autonomy—representing the extremities of Switzerland’s spectrum of political combinations—has long been the subject of debate both inside and about the country’s health systems 65. The dThe number of local integrated care (IC) initiatives in Switzerland has been steadily growing over the last 20 years. With a certain lag, momentum in favour of IC policies has developed. In the future, Switzerland’s healthcare system will probably navigate between centralised support for IC and scattered local IC initiatives. This will be the reflection of a very Swiss way forward in a world without much clear evidence of whether centralised (state) incentives or decentralised (field) initiatives are more successful at developing and scaling up IC.


In global climate change, improving carbon productivity holds great importance for China’s sustainable growth. Based on panel data of 30 Chinese provinces and cities from 1997–2017, the drivers, spatial effects, and convergence characteristics of carbon productivity in China are explored by combining a factor decomposition framework and a spatial panel model. The findings show that (1) China’s carbon productivity shows continuous positive growth, and the substitution effect of capital for energy dominates this changing pattern; (2) There is a β-convergence trend and club convergence in China’s carbon productivity, and the spatial technology spillover accelerates the convergence rate; (3) With its accelerated industrial transformation and technological upgrading, China’s current carbon productivity converges faster than its earlier stage, and the role of physical capital investment has gradually shifted to suppression. In contrast, the positive push of human capital investment has been strengthened; (4) From the perspective of the realization mechanism, the convergence of carbon productivity in China mainly comes from the convergence of energy restructuring and capital-energy substitution. These findings can help China narrow the inter-provincial carbon productivity gap in terms of improving factor structure, upgrading technology, etc., and provide references for sustainable growth decision making in China and around the world. In recent years, climate change issues such as extreme weather and glacier retreat have received widespread attention from academic and political circles. Climate change and its impacts have become one of the world’s most severe environmental problems . The lar2 emissions per unit of GDP by 2030 compared to 2005. By the end of 2020, China’s carbon intensity had fallen by 48.4% compared to 2005, exceeding the autonomous commitment target and reducing cumulative CO2 emissions by about 5.8 billion tons, basically reversing the rapid growth of CO2 emissions [Since its reform and opening-up, China’s economy has maintained rapid double-digit growth for a long period of time, providing Chinese experience and solutions for developing countries. Environmental pollution and ecological imbalance inevitably emerged during the industrialization process in developed Western countries, and China has now surpassed the USA as the largest carbon emitter. China is actively participating, leading, and contributing to global climate change prevention and control to assume its significant power to reduce emissions and strengthen climate change action . As the The Carbon Productivity Challenge: Stemming Global Change, Sustaining Economic Growth states that successful climate change action must support the goals of stabilizing greenhouse gases and sustaining economic growth, i.e., there must be a significant increase in total GDP output per unit of carbon equivalent emissions. Therefore, improving carbon productivity is an effective way to achieve coherence between emissions reductions and economic growth [Carbon Productivity (CP) is a core concept in evaluating low-carbon economic development  and is ac growth ,11, and c growth . TherefoThe environmental Kuznets curve (EKC) literature provides a starting point for this paper, as empirical evidence suggests that the pattern of change between carbon productivity and economic growth arises from the influence of different drivers ,14. With2 emissions [The existing literature does not provide direct evidence of the relationship between carbon productivity and economic growth. Since carbon productivity is precisely the ratio of output to emissions, a logical starting point for this paper can be established from the literature that explores the relationship between carbon emissions and economic growth. Therefore, the literature on the relationship between carbon productivity and economic growth can be traced back to the study of the EKC hypothesis . The EKCmissions . Still, missions . Since tIn a recent study, an empirical test based on a larger sample provided strong evidence for the EKC hypothesis of the relationship between carbon emissions and economic growth, by estimating a panel smooth transition regression model for 40 countries over the period of 1994–2016 , upper-mThe available studies more and more strongly support a nonlinear relationship between carbon emissions and economic growth. Due to the advantages of energy structure ,28, finaHypothesis 1 (H1). China’s carbon productivity growth exhibits a nonlinear pattern of change.The existing literature most often uses parametric regression and nonparametric decomposition to identify drivers of carbon productivity.Parametric regressions are mainly based on parametric tests of econometric models, which analyze the impact of relevant factors on carbon productivity. Numerous studies have shown that industrial development’s effects on carbon productivity are heterogeneous and do not behave precisely in different countries or regions. For example, the concrete industry in Canada , the met2 emissions into five different factor effects: industrial activity, structural change, energy intensity, fuel mix, and emission intensity. Further analysis showed that increased energy-intensive industrial activity could largely offset the positive effects of improved energy efficiency and decarbonization measures [2 emission factors across 30 Chinese provinces. Energy intensity and GDP per capita played a dominant role in suppressing and promoting industrial CO2 emissions [Nonparametric methods often use exponential decomposition analysis (IDA) to separate the drivers of carbon productivity. Among them, the log-averaged Divisia index (LMDI) method is the most widely used in practice, for its advantages of leaving no residuals, simplifying interpretation, and consistency of decomposition formulas . The LMDmeasures . The litmissions . By consmissions  In additmissions .Although the existing literature has made many valuable explorations into the drivers of carbon productivity, the economic mechanisms and policy interface are not sufficiently discussed. A complete accounting framework reveals that the drivers’ contributions are still lacking. The IDA method contains information that factor effects overlap, and it is difficult to provide a reasonable economic explanation for carbon productivity changes . In receHypothesis 2 (H2). Capital-to-energy substitution dominates the pattern of carbon productivity change in China, and the role of total factor productivity is not sufficient.Hypothesis 3 (H3). The asynchrony of capital-to-energy substitution is the main reason for China’s regional differences in carbon productivity.A basic consensus is that economic convergence originates from productivity convergence under knowledge spillovers in the study of growth convergence. In academic discourse, neoclassical growth theory assumes that differences in per capita income and capital will disappear as the economic growth rate declines and the economy eventually stabilizes. Endogenous growth theory argues that there are spillover effects of intellectual and human capital accumulation in economic growth, and that low-productivity countries rely mainly on latecomer advantages to catch up with high-productivity countries . In rece2 emissions diverge in pairwise tests [2 emissions found that emissions are converging in most countries, independent of national development patterns [The literature on the convergence of sustainable growth can be divided into two lines. The first uses the traditional parametric approach to test for absolute, conditional, and stochastic convergence. The literature that tests the carbon convergence hypothesis using pairwise and club convergence tests shows that club convergence occurs in many countries, while COse tests . Per capse tests . Panel dse tests . Panel dse tests . Recent se tests . Anotherse tests . In addise tests . A statipatterns .There is already considerable literature that has explored the environmental convergence hypothesis to some extent. However, further research on carbon productivity convergence is yet to provide additional empirical evidence. Although some of the literature has noted the influence of spatial variation on the convergence characteristics of carbon emissions, the examination of spatial factors of carbon productivity convergence is still missing. On the other hand, technological progress in one economy may be transmitted to other economies, meaning that the closed economy assumption of neoclassical growth theory may be invalid. Moreover, from an econometric perspective, spatial dependence can lead to unreliable statistical inferences if spatial spillover effects exist and are ignored. Based on the above analysis, the following research hypotheses are proposed.Hypothesis 4 (H4). There are overall convergence and club convergence characteristics of carbon productivity growth in China.Hypothesis 5 (H5). The spatial spillover effect further increases carbon productivity’s convergence rate.Hypothesis 6 (H6). The drivers play different roles in achieving carbon productivity convergence.From a review of the above literature, it is easy to find that the uncertainty in the pattern of carbon productivity change mainly comes from the differential influence of the relevant drivers. These drivers’ differences also determine the mechanism of achieving regional carbon productivity convergence. While exploring carbon productivity changes, drivers, and convergence trends in isolation provides limited evidence for sustainable growth, a convergence factor decomposition and convergence analysis framework appears to provide richer empirical evidence and insights for decision making. Therefore, the following extensions are attempted in this paper to enrich the existing literature: first, construct a DEA decomposition framework that can reflect the growth mechanism by unifying factor substitution, total factor productivity, and single-factor carbon productivity, and then account for the contribution of drivers to carbon productivity improvement. Second, we construct a convergence equation for carbon productivity based on panel data, introduce spatial dependence to test the regional data of China, and then analyze the impact of spillover effects on the rate of convergence and growth potential. Finally, we integrate the power decomposition and convergence equation to further explore the impact of drivers on the intersection of carbon productivity and growth potential.Carbon productivity is defined as the GDP output per unit of carbon equivalent emissions in a certain period. Since different types of energy consumption can estimate carbon equivalent emissions, and energy consumption per unit of emissions reflects the influence of energy mix, we further isolate the energy mix based on the defining equation, which can be obtained as:CP is carbon productivity, Y is GDP, C is carbon equivalent emissions, and E is fossil energy consumption. ES is the energy consumption per unit emission, reflecting the influence of energy structure on carbon productivity; YE is the GDP per unit energy consumption output, which is the energy productivity. According to the production theory, energy productivity can form an output relationship with the unit energy factor input. Thus, the effects of factor accumulation and total factor productivity can be further separated. The global DEA model is used in this paper to ensure the continuity and stability of the decomposition of technological progress. KE and LE denote the capital input and labor input per unit of energy consumption, respectively, and In Equation (1), YEC and TFP denote GDP growth and total factor productivity change per energy consumption unit, respectively. Since the factor input per unit of energy consumption reflects the substitution relationship of capital and labor for energy input, XEC is called the factor substitution effect here. According to the principle of DEA model solving, In Equation (2), CPC and ESC denote carbon productivity change and energy mix change, respectively. Equation (3) shows that three mechanisms mainly drive carbon productivity growth: first, energy structure optimization, i.e., the reduction in carbon emissions due to the substitution of low-carbon energy for high-carbon energy; second, total factor productivity growth, i.e., the increase in energy production due to the improvement of global technical efficiency in two adjacent periods; third, the factor substitution effect, i.e., the change in global optimal unit productivity due to the substitution of capital and labor for energy under the same technological conditions.Combining single-period DEA with global DEA, TFP can be further decomposed into technological progress changes and technical efficiency changes. Let TPC and TEC denote the change in technical progress and the change in technical efficiency, respectively, KEC) and labor substitution effect (denoted as LEC) in the global DEA framework. To avoid the uncertainty of the fixed factor reference, the geometric mean under the two-period consideration was chosen to respectively measure the capital substitution effect and labor substitution effect in this paper, and we have:XEC) and is easily verifiable. Carbon productivity growth is mainly driven by the factor substitution effect and the total-factor productivity. The former includes low-carbon energy substitution, capital energy substitution, and labor energy substitution, and the latter contains technical progress and efficiency improvement. Therefore, by plugging the decomposition equations of total-factor productivity and factor substitution effect into Formula (3), the decomposition equation of the quintuple growth drivers of carbon productivity can be obtained as below:According to the nature of the metafrontier DEA model, production units with the same combination of factor input have the same output projection in the frontier, i.e., It is easy to see that the change in carbon productivity is mainly driven by the energy structure effect, technological progress change, technical efficiency improvement, capital substitution effect, and labor substitution effect. Based on the above decomposition framework, growth accounting for carbon productivity changes in a country or region can be performed to assess the pattern of temporal changes dominated by the contributions of different factors.Convergence models derived from economic growth theory can examine whether economic variables in different regions have normal and other steady states, i.e., whether lagging areas can catch up with the trends in developed areas. Common steady-state convergence is often referred to as absolute β-convergence. In contrast, different steady-state convergence is conditional β-convergence when considering the impact of differences in resource endowments and technological conditions between regions on steady-state equilibrium. We use the Mankiw–Romer–Weil (MRW) convergence model  as the bBased on the proof of the MRW model, In Equation (10), The traditional literature ignores the spatial dependence of carbon productivity, leading to bias in estimation convergence models. The resource endowments and market conditions of neighboring provinces are generally more similar, factor flows and technological cooperation between regions will be adequate, and carbon productivity exhibits significant spatial clustering characteristics. Therefore, it is necessary to adopt a spatial panel model to revise the traditional convergence model, and we start from a spatial Durbin model (SDM) of panel data.For the convenience of writing, the subscripts of the variables in Equation (11) are omitted to represent them in matrix and vector form. Among these, the In Equation (12), Further, the spatial convergence mechanism of carbon productivity can be further tested by combining the power decomposition Equation (8) and the spatial convergence Equation (11). Substituting Thus, by examining the magnitude and direction of the parameters of each driver around the ce model .2, the direct use of CO2 emission coefficients is likely to cause estimation bias, so we used uniform carbon equivalents and reconstructed them according to provincial CO2 emission inventories; GDP and physical capital stock were adjusted to compare prices in 2000, and individual missing data were completed by linear interpolation.According to the guidelines developed by the United Nations Intergovernmental Panel on Climate Change (IPCC), the reference method accounts for fossil energy production sites. Still, many primary energy sources do not enter final consumption, resulting in severe risk of overestimation , so thisRegarding economic growth theory, the logarithm of the ratio of capital investment rate to effective depreciation rate  for mixed data and reported the estimation results for the panel fixed effects (FE) model, panel SLM, SEM, and SDM, in turn, as shown in From the test results of absolute in China . There iNext, we examined the regional conditional convergence characteristics of China’s carbon terature  estimateIn addition, conditional convergence also implies that the relative positions of steady-state growth levels between regions are difficult to eliminate automatically in the long-term, mainly determined by regional characteristic variables’ direct and spillover effects. From the estimation results of SDM, only the spatial lag coefficient of the effective investment rate of human capital passed the significance test at the 10% statistical level. In contrast, the significance of other variables was relatively low. The differences in the effects of the control variables on the five major driving factors may obscure their significance in the total convergence equation of carbon productivity, so further identification with the help of the associative convergence model is needed.To further examine the stage convergence and club convergence characteristics of regional carbon productivity in China, we further estimated the SDM conditional The results showed that China’s carbon productivity exhibited a spatial conditional From the regional equation estimates, the coefficients To further investigate the spatial convergence mechanism of carbon productivity, uctivity ; on the In terms of the mechanism of influence of the effective investment rate, both physical and human capital investment rates were mainly mediated by capital–energy substitution and total factor productivity. Among these, the direct effect of the physical capital investment rate on capital substitution (0.090) was significantly positive, while the effect on technological progress (0.031) and technical efficiency (−0.105) was in the opposite direction. This finding is consistent with China’s long-standing capital-driven growth approach, where overinvestment is also bound to cause general deterioration in total factor productivity. The coefficients of physical capital investment rates in neighboring regions passed significance tests only in Equations (2) and (4), and both had negative signs, suggesting that blindly following up on expanding investment reduces capital substitution (−0.045) and technological progress (−0.042). The local human capital investment rate helps labor substitution (0.010) and technical efficiency (0.04) to obtain significant improvements. In contrast, human capital accumulation in neighboring provinces (0.058) only showed a significant positive spatial spillover to the local capital substitution effect. Nevertheless, human capital investment’s direct and spillover effects were significantly positive. In recent years, their contribution to carbon productivity growth was further strengthened, which is also highly correlated with China’s cross-regional talent mobility trait.The paper re-estimated the joint cubic equation using the inverse weight matrix of the latitude and longitude distances to examine further the robustness of the carbon productivity spatial convergence mechanism. We further used data averaged every four years, i.e., 1997–2000, 2001–2004, 2005–2008, 2009–2012, and 2013–2016, and a total of This study provides preliminary evidence of a nonlinear relationship between carbon productivity and economic growth in China, indicating that the EKC hypothesis is not valid in China. A study using autoregressive distribution lag (ARDL) modeling for Arctic countries provides similar evidence, suggesting that the EKC curves revealed by panel data may not apply to a single specific country or region . EvidencDistinct from the EKC approach, this study provides a body of evidence on the drivers of carbon productivity and regional convergence in China within a new framework. Capital-to-energy substitution dominates the pattern of carbon productivity growth in China as a whole, in the East, the Center, and the West, and at the provincial level. The literature on parametric method decomposition provides similar findings , with thThe existing literature provides evidence of convergence in carbon intensity and energy productivity ,71. ThisTherefore, policymakers should develop new policies to attract low-carbon-oriented extraterritorial investments and promote information exchange and technology transfer, which may provide the basis for re-establishing sustainable growth ambitions. Policymakers in lagging regions should strengthen environmental regulations to prevent increased environmental degradation due to energy-intensive and emission-intensive capital inflow . From a Carbon productivity has a richer economic connotation as a core variable of sustainable growth. Based on the global DEA model, the present paper constructed the relation between factor substitution, technical progress, technical efficiency, and carbon productivity. The present study measured the five driving forces of carbon productivity growth in 30 provinces, autonomous regions, and cities based on the data sample during 1997–2017. The work further tested and analyzed the spatial convergence mechanism of provincial carbon productivity in China using the spatial panel model.The empirical results show that the capital substitution growth pattern generally dominates China’s provincial carbon productivity. Energy restructuring mostly has positive effects, and labor substitution effects show different degrees of deterioration. The regional differences in total factor productivity are significant, with more pronounced efficiency-based growth in the Eastern region and a general deterioration in the Central and Western areas. These empirical findings are consistent with China’s economic growth, as sloppy growth that relies on rapid capital accumulation is bound to undermine a sustainable growth path centered on carbon productivity. China’s provincial carbon productivity growth has robust spatial absolute β-convergence and spatial conditional β-convergence trends. Low-carbon-productivity regions have catch-up effects relative to high-carbon-productivity regions, and spatial spillover effects significantly accelerate regional convergence. SDM is more suitable for testing China’s carbon productivity convergence pattern. The spatial conditions of carbon productivity in China exhibit two stages of convergence. After entering the medium and low growth stage, the economic transition accelerates the rate of carbon productivity convergence. Similarly to economic convergence, China’s carbon productivity exhibits typical club convergence characteristics, with faster convergence in the Central and Western regions than in the East. While energy mix and capital substitution dominate each province’s carbon productivity growth pattern, they also determine the overall carbon productivity convergence trend. The mechanism of effective investment rate on carbon productivity growth rate is mainly mediated by capital substitution and total factor productivity. Physical capital investment has gradually shifted to an inhibitory effect, while the positive push of human capital investment is strengthening. Expanding physical capital investment can directly improve the local capital substitution effect. Still, it is gradually offset by the deterioration of efficiency caused by investment imbalance, which is more serious in terms of spatial effects. Expanding human capital investment can significantly improve local factor allocation, and factor mobility and mutual imitation across regions can significantly enhance the contribution of human capital spillovers to carbon productivity growth. China’s sustainable growth will increasingly rely on human capital accumulation in the form of technology spillovers.The above findings have important policy implications for China in the promotion of sustainable growth, with carbon productivity at its core. Since capital energy substitution has dominant empirical evidence, policymakers should continuously optimize the design and implementation strategies, strengthen the structure and quality of capital inputs, and restrain the excessive growth of energy factors. Policymakers should impose strict restrictions on those backward industries with high energy consumption and high emissions, and control the carbon productivity decline caused by their production scale expansion. The adoption of low-energy consumption capital and the development of independent innovation capacity are the main policy instruments. Given the positive effect of human capital on carbon productivity improvement, policymakers should strengthen the guidance of human capital investment to improve the factor input structure. In economically backward inland regions, policymakers should fully consider the technology spillover effects of human capital investment to benefit local and global sustainable growth. The spatial technology spillover effect accelerates the overall convergence process. This finding provides a scientific basis for policymakers to sustain innovation support and regional cooperation in low-carbon, energy, and other environmental technologies. It enables the sustainable growth advantages of lagging provinces and cities to be fully unleashed. Inter-regional trade and technical exchanges are inseparable from supporting an excellent infrastructure and institutional system. Therefore, promoting the construction of infrastructures such as transportation and information transmission and improving the institutional mechanism of inter-regional exchange and cooperation should also attract the full attention of policymakers. In addition, the results of this study provide Chinese experiences and Chinese cases for global energy conservation and emission reduction, especially for developing countries or regions that adopt intensity reduction strategies. A formal unified constraint system, effective regulation of energy-intensive capital, and enhanced cooperation in low-carbon technologies remain valuable references for decision-making.The above findings have important practical implications for carbon intensity reduction practices and sustainable growth programs in China and other countries. The policy implications are as follows: firstly, we should continue to deepen the structural reform on the supply side of energy, further strengthen the control of excessive accumulation of energy factors, optimize the energy consumption structure, accelerate the technological transformation of coal energy consumption, and improve energy utilization efficiency. Secondly, we should pay attention to the guiding role of fixed asset investment efficiency, strengthen the control of regional investment growth rates and spatial structure regulation, and gradually realize the reasonable and orderly substitution of capital factors for energy factors. Again, improving human capital investment, especially in economically less-developed inland areas, gives full play to the technological spillover effect of human capital investment and actively promotes the joint innovation and coordinated development of production technology, energy technology, and environmental technology. Finally, we should develop and implement differentiated regional development strategies, promote infrastructure construction such as transportation and information transmission, increase the depth and breadth of exchanges and cooperation between regions, especially between developed and less-developed regions, and further release the spatial spillover effects of factor flows and technology diffusion.The relatively short period of the dataset provides a potential limitation of this study, while the natural process of convergence may take decades or even longer to end. Our findings may indicate initial signs of convergence in carbon productivity, and it may be easier for provinces to collaborate in future synergies in emission reduction targets. It is crucial to investigate this relationship further. In addition, our study only provides empirical evidence. It does not provide a more in-depth theoretical proof of the spatial convergence mechanism of carbon productivity, which is also missing in the existing literature, and is undoubtedly an important research topic for sustainable growth theory.