child health and nutrition research initiative

Cochrane Methods Priority Setting

Child health and nutrition research initiative (chnri) approach to research priority setting.

Paper summarised:Igor Rudan, Jennifer L. Gibson, Shanthi Ameratunga, Shams El Arifeen, Zulfiqar A. Bhutta, Maureen Black, Robert E. Black, Kenneth H. Brown, Harry Campbell, Ilona Carneiro, Kit Yee Chan, Daniel Chandramohan, Mickey Chopra, Simon Cousens, Gary L. Darmstadt, Julie Meeks Gardner, Sonja Y. Hess, Adnan A. Hyder, Lydia Kapiriri, Margaret Kosek, Claudio F. Lanata, Mary Ann Lansang, Joy Lawn, Mark Tomlinson, Alexander C. Tsai, Jayne Webster. Setting Priorities in Global Child Health Research Investments: Guidelines for Implementation of CHNRI Method . Croat Med J. 2008;49:720-33. doi:10.3325/cmj.2008.49.720

Summary of the paper by Jill Pooler

Introduction

The authors (Child Health and Nutrition Research Initiative (CHNRI)) propose a systematic yet flexible method for setting research priorities for global child health. The rationale for this project is the view that current research prioritization approaches may be flawed and thereby partly responsible for persistent high levels of mortality among children globally. Moreover it is argued that whilst the purpose of all health research is to reduce the existing burden of disease and disability and improve health, many investments in research will never sufficiently achieve these goals.  The purpose of the CHNRI priority setting method is to inform those who invest in research about the risks associated with their investments.  The target audience are international agencies, large research funding donors, national governments and policy makers.  

This paper sets out the method in fifteen steps. These are summarised in the table below:

The advantages of this method are i) transparent presentation of the context and criteria in the priority setting process ii) management of the process by stakeholders/investors over its entire duration iii) structured way of scoring which should limit specific interest or personal biases iv) involvement of non-technical stakeholders v) flexibility of the process according to context  vi) potential to revise weights and thresholds  according to context vii) simple presentation of the strengths and weaknesses of competing research options viii) ability to rank research options ix) a simple quantitative outcome x) exposure of points of agreement and controversy.

The authors report that whilst the process outlined above attempts to deal with complex issues, it would benefit from independent validation. Concerns relate to the potential for a limited number of research options/questions, and the role of bias by involving a very limited group of technical experts and stakeholders.  

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Research Article

Setting global research priorities for child protection in humanitarian action: Results from an adapted CHNRI exercise

Roles Data curation, Formal analysis, Methodology, Writing – original draft

Affiliation Columbia University School of Social Work, New York, New York, United States of America

Roles Conceptualization, Supervision, Writing – review & editing

Affiliation Save the Children, London, United Kingdom

* E-mail: [email protected]

Affiliations Department of Population and Family Health, Columbia University Mailman School of Public Health, New York, New York, United States of America, George Warren Brown School of Social Work, Washington University in Saint Louis, St. Louis, Missouri, United States of America

• Laura Gauer Bermudez, 
• Katharine Williamson, 
• Lindsay Stark

• Published: August 22, 2018
• https://doi.org/10.1371/journal.pone.0202570
• Reader Comments

Armed conflict, natural disaster, and forced displacement affect millions of children each year. Such humanitarian crises increase the risk of family separation, erode existing support networks, and often result in economic loss, increasing children’s vulnerability to violence, exploitation, neglect, and abuse. Research is needed to understand these risks and vulnerabilities and guide donor investment towards the most effective interventions for improving the well-being of children in humanitarian contexts.

The Assessment, Measurement & Evidence (AME) Working Group of the Alliance for Child Protection in Humanitarian Action (ACPHA) identified experts to participate in a research priority setting exercise adapted from the Child Health and Nutrition Research Initiative (CHNRI). Experts individually identified key areas for research investment which were subsequently ranked by participants using a Likert scale. Research Priority Scores (RPS) and Average Expert Agreement (AEA) were calculated for each identified research topic, the top fifteen of which are presented within this paper.

Intervention research, which aims to rigorously evaluate the effectiveness of standard child protection activities in humanitarian settings, ranked highly. Child labor was a key area of sector research with two of the top ten priorities examining the practice. Respondents also prioritized research efforts to understand how best to bridge humanitarian and development efforts for child protection as well as identifying most effective way to build the capacity of local systems in order to sustain child protection gains after a crisis.

Conclusions

Rigorous, scientific research that assesses the scope of child protection risks, examines the effectiveness of interventions to improve child well-being, and translates evidence to practice is critical. Findings from this research priority setting exercise offer guidance for a global research agenda on child protection in humanitarian settings, encouraging cooperation among donors, implementers, and academics to pursue a coordinated approach to evidence generation.

Citation: Bermudez LG, Williamson K, Stark L (2018) Setting global research priorities for child protection in humanitarian action: Results from an adapted CHNRI exercise. PLoS ONE 13(8): e0202570. https://doi.org/10.1371/journal.pone.0202570

Editor: Emma Sacks, Johns Hopkins School of Public Health, UNITED STATES

Received: February 16, 2018; Accepted: August 6, 2018; Published: August 22, 2018

Copyright: © 2018 Bermudez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its supporting information files.

Funding: The study was made possible with funds from Save the Children provided to the Alliance for Child Protection in Humanitarian Action, https://www.savethechildren.net . Co-author, Katharine Williamson, is a co-leader of the Alliance's AME task force and is also an employee of Save the Children, serving as their Senior Humanitarian Child Protection Advisor.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: ACPHA, Alliance for Child Protection in Humanitarian Action; AEA, Average Expert Agreement; AME, Assessment, Measurement & Evaluation Working Group; CHNRI, Child Health and Nutrition Research Initiative; CP AoR, Child Protection Area of Responsibility; RPS, Research Priority Scores; UNHCR, United Nations High Commissioner for Refugees; NGO, Non-Governmental Organizations; UN, United Nations; UNICEF, United Nation Children’s Fund

Introduction

The number of people affected by humanitarian crises is on the rise, perpetuated by armed conflict and natural disasters [ 1 ]. In 2017, there were over 65 million forcibly displaced people, over half of whom were under the age of 18 [ 2 ]. In addition, over one billion children live in countries affected by armed conflict [ 3 ]. Environmental factors, including climate change, are likely to increase the number of conflicts and intensify the severity of natural disasters [ 4 – 5 ]. Armed conflicts and large-scale disasters increase the potential for family separation and the erosion of existing support systems, putting children at risk of abuse, exploitation, violence, and neglect. The widespread economic shocks that often accompany humanitarian crises create further vulnerabilities for children when households employ negative coping strategies to manage economic stress. In Lebanon, where over one million Syrian refugees have been registered with the United Nations High Commissioner for Refugees (UNHCR), child marriage and child labor have been reported as families struggle financially [ 6 – 7 ]. Children in circumstances of economic and physical insecurity are also at risk of child trafficking, sexual exploitation, and recruitment by armed forces and extremist groups.

Within these contexts, child protection experts in non-governmental organizations (NGO), multilateral institutions such as the UN Children’s Fund and the United Nations High Commissioner for Refugees, work to prevent and respond to incidents of abuse, neglect, exploitation, and violence against children. These efforts can take the form of broader systems-strengthening interventions that seek to build the capacity of national actors to implement effective social support systems that care for children and families, both in formal and informal spheres. As a complement to systems strengthening, child protection initiatives may also take the form of direct implementation, such as the establishment of “Child Friendly Spaces (CFS)” that allow children safe zones to play, parenting trainings that emphasize alternatives to physical punishment, or family tracing and reunification for unaccompanied or separated children. Yet, the assumptions that drive such child protection efforts in humanitarian practice have not yet been fully based on scientific evidence. Protection risks are often estimated and prioritized based on anecdotal accounts [ 8 ], definitions of child protection concepts are often not standardized [ 9 ], and there is scant evidence on the effectiveness of many of the sector’s universally agreed upon standard interventions [ 10 – 12 ].

To begin addressing these gaps in empirical research within the sector of child protection in humanitarian contexts, a research priority setting exercise, adapted from the Child Health and Nutrition Research Initiative (CHNRI), was undertaken to identify and rank research priorities. This manuscript presents the process and results of this participatory ranking methodology designed to guide future research investment.

The Child Health and Nutrition Research Initiative (CHNRI) was designed as a tool to help guide policy and investment in global health research, specifically children’s health. CHNRI has since been used to establish research priorities across a broad array of global health disciplines [ 13 – 20 ]. The method is comprised of four stages (i) determining the boundaries of investigation and creating evaluation criteria; (ii) obtaining and systematically listing input from key stakeholders on critical priorities/tasks (referred to as “research questions”) to address gaps in sectoral evidence or knowledge; (iii) enlisting stakeholders to rank the research questions based on a pre-defined set of evaluation criteria; (iv) calculation of research priority scores and agreement between experts ( Fig 1 ]. A more detailed explanation of the CHNRI method has been published elsewhere [ 21 – 23 ].

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https://doi.org/10.1371/journal.pone.0202570.g001

The present study was commissioned by the Assessment, Measurement and Evidence Working Group of the Alliance for Child Protecton in Humanitarian Action (ACPHA) and was informed by prior consensus-building efforts in the sector [ 24 – 25 ]. In collaboration with a Lead Researcher, the CHNRI method was adapted to prioritize research topics in the sector of child protection in humanitarian settings. For the purposes of this exercise, a ‘humanitarian setting’ was defined as “acute or chronic situations of conflict, war or civil disturbance, natural disaster, food insecurity or other crises that affect large civilian populations and result in significant excess mortality” [ 26 ]. The goal of ‘child protection’ efforts are “to protect children from abuse, neglect, exploitation, and violence” [ 27 ]. And ‘children’ were defined as “individuals under the age of 18” [ 28 ].

Experts working on issues of child protection in humanitarian settings were then invited to take part in semi-structured interviews to discuss the gaps in knowledge and evidence that existed within the sector and to generate research priorities to address these gaps. Forty-seven experts participated in this first round of evidence generation with representatives from Non-Governmental Organizations (NGOs), United Nations (UN) agencies, donor agencies, and research institutions. Experts were initially identified through three coordination bodies–the Alliance for Child Protection in Humanitarian Action (ACPHA), the Child Protection Area of Responsibility (CP AoR), and UNHCR with the network extended through snowball sampling. Respondents were strategically diversified to include inputs from those involved in various child protection job functions including implementation, coordination, policy development, and academia from a range of geographic locations ( Table 1 ]. Recruitment continued on a rolling basis and ended once data saturation, defined as the point at which no new data were being generated, was achieved. The final sample was consistent with previous research that identified 45–55 as the number of experts at which collective opinion stabilizes [ 29 ].

https://doi.org/10.1371/journal.pone.0202570.t001

Aligned with prior CHNRI studies in humanitarian contexts [ 14 ], interviews were held via Skype with experts notified in advance that they would be requested to provide their opinions on the most important areas for investment to improve the state of evidence in the field of child protection in humanitarian settings in the next 3–5 years. Participants were encouraged to follow up by email in the event they were able to generate further ideas after the interview had concluded.

Through an iterative process, the Lead Researcher then collated 24 hours of interview notes to identify 90 unique research priorities, condensing interrelated research ideas and simplifying concepts for use in the ranking exercise. The priorities were then thematically organized into the following pre-determined themes—Epidemiological Research; Policy and Systems Research; and Intervention Research ( Table 2 ]. The research team provided review and consensus on the themes and categorization after which the areas for research were listed within the online survey. The survey was pilot tested by individuals who were not involved in the development of research questions but who had general knowledge of humanitarian concepts and survey design. Further, to ensure that question order did not bias results, we implemented a page randomization that shuffled page order within the survey for each new respondent.

https://doi.org/10.1371/journal.pone.0202570.t002

Experts who participated in the interview process were invited to take part in the online ranking portion of the prioritizatio exercise. Two additional experts who were either not previously available or who reached out to participate after the period for interviews had passed, were also invited to take part in survey.

Each of the 90 research priorities were ranked on four criteria: (i) Relevance–research will support learning that contributes to the prevention and response to abuse, neglect, exploitation, or violence in humanitarian settings; (ii) Feasibility–research is feasible to conduct in an ethical way; (iii) Originality–research will generate new findings or methods; and (iv) Applicability–research will be readily applied to programs and policies. Relative weights were not assigned to scoring criteria. For each research question, participants were offered six possible responses: strongly agree (5 points); agree (4 points); undecided (3 points); disagree (2 points); strong disagree (1 point); and insufficiently informed (considered non-applicable/no response). The scoring matrix was a deviation from past CHNRI studies which typically offered four possible responses–yes (1 point), no (0 points), undecided (0.5 points), and insufficiently informed/no response. In the development of the present research design, the study team elected to use a full Likert scale to allow for greater granularity when analyzing scores.

Aligned with the CHNRI methodology [ 13 – 20 ], every research question was provided a priority score under each of the four judging criterion, calculated by taking the point totals and dividing them by the maximum number of points available, after excluding from the denominator those who did not answer the question or reported they were insufficiently informed, a percentage was calculated [ 14 ]. For each question, the overall Research Priority Score (RPS) was then calculated by taking the mean of the total priority scores for each judging criterion, as calculated above. Research questions were then ranked from highest to lowest on overall priority scores and the top fifteen presented in Table 3 . Standard deviations for RPS are also included to show the variation between total priority scores for each judging criterion ( Table 3 , S1 Annex ).

https://doi.org/10.1371/journal.pone.0202570.t003

In addition, the Average Expert Agreement (AEA) was calculated for each research question. In order to obtain AEA values, we consolidated “strongly agree” and “agree” as well as “strongly disagree” and “disagree”. For each judging criterion, the number of modal responses was then divided by the total number of scorers for that question, again excluding those who did not answer the question or who reported they were insufficiently informed on the research question being assessed. Following this calculation, the ratios were then summed and divided by the number of judging criteria.

Both RPS and AEA were calculated for the entire group of respondents as well as for sub-groups, in order to analyze differences in priorities for those located in field settings as compared to those based in non-operational settings. Data were analyzed using Microsoft Excel.

Ethics statement

Formal ethics review is usually not requested for undertaking CHNRI exercises [ 13 – 20 ] as the exercise does not involve personal or otherwise sensitive data. Participants were solicited via established professional networks whose purpose is to facilitate and enable information-sharing. Prior to participation in initial Skype interviews, all participants were informed on the nature of the research and the anonymity of their feedback.

Of the 49 respondents invited to take part in the online ranking, 41 experts participated, eliciting a response rate of 83.7 percent. Research questions from all three of the research domains (epidemiological research; policy and systems research; and intervention research) featured in the top 15 research priorities. Intervention research was the most predominant domain voted upon by experts with 8 of the top 15 priorities identified falling within this realm. Policy and systems research followed with 5 priorities and epidemiologic research with only 2 featured priorities ranking in the top 15 ( Table 3 ).

The range of overall RPS was 63.28 to 86.33, with the highest ranked priority being the rigorous evaluation of the effectiveness of cash-based social safety nets to improve child well-being. Within the top 15 priorities, RPS ranged from 80.70 to 86.33. Intervention research which aims to rigorously evaluate the effectiveness of standard child protection activities provided in humanitarian settings ranked highly. Two questions concerning child labor, specifically estimating the prevalence and understanding the effectiveness of interventions to reduce the practice, ranked in the top ten priorities. Respondents also prioritized research efforts to understand how best to mobilize local systems, including the local social service workforce and para-social work models, in order to sustain child protection gains after international actors have departed a crisis.

AEA scores ranged from 41.55 to 85.63, representing the percentage of respondents who provided the same score on a research priority (averaged across four judging criteria). For the top 15 research investment options, AEA ranged from 69.04 (to build the capacity of child protection sector staff in empirical research design and data analysis planning) to 85.75 (to evaluate the effectiveness of interventions to reduce child labor) ( Table 3 ). We found higher levels of respondent agreement among research questions with higher RPS rankings, demonstrating that a certain level of consensus was attained in order for research topics to be prioritized in the higher ranks ( Fig 2 ).

https://doi.org/10.1371/journal.pone.0202570.g002

Standard deviations (SD) were also analyzed in order to assess variation between the judging criterion. Among the top 15 reserch priorities, SDs ranged between 2.5 and 5.4 with the exception of the evaluation of psychosocial programming with an SD of 8.2 due to the comparatively lower score provided on Originality. This is likely due to the recent work on this particular topic that has been widely circulated [ 30 ] and therefore was deemed less original in the ranking process.

When comparing all RPS scores among respondents who resided within an operational setting versus those who did not, there was a correlation co-efficient of 0.32, indicating a weak but positive association. The top ten research priorities differed between the two groups ( Table 4 ). With the exception of rigorously evaluating family strengthening programs, which ranked highly for both groups of respondents, there were no other priorities that jointly ranked among the top ten. For field-based respondents, the most important initiative was to identify best practices for bridging humanitarian and development initiatives for child protection system strengthening. Field-based respondents tended towards the identification of best practices while also prioritizing capacity building for child protection sector staff in empirical research design and data analysis planning. In contrast, respondents who were not based in operational settings showed greater enthusiasm for the rigorous evaluation of interventions, with an examination of the effects of cash-based social safety nets on child well-being outcomes ranking highest.

https://doi.org/10.1371/journal.pone.0202570.t004

The limitations to rigorous research on child protection in humanitarian crises are notable, with harsh operational conditions, short project cycles, and inadequate funding all considered hindrances to scientific inquiry on child protection within these contexts [ 31 – 32 ]. However, recent efforts have begun to demonstrate that robust social science methodologies within the sector are both needed and possible [ 33 – 35 ]. This prioritization exercise, which is among the first known systematic inquiries on research investments for child protection in humanitarian contexts using the CHNRI methodology, offers initial insight on the research interests and evidence needs of sector experts.

Intervention research comprised three of the top four research priorities, aligning with many previous CHNRI studies that have similarly found intervention research to be of importance to stakeholders [ 36 ]. As previously noted, there is a dearth of rigorous evaluation to determine the effectiveness of common child protection interventions in humanitarian settings. The lack of quantitative data to document intervention effectiveness inhibits the ability of humanitarian actors to design evidence-based programs, a hindrance increasingly problematic for funding appeals and policy advocacy. This prioritization suggests that understanding intervention effectiveness is of particular interest to the sector, ranging from examinations of family-strengthening to capacity-building interventions to activities aimed at reducing child labor. Because the sample more heavily represents individuals in technical advisory and other operational capacities, the interest in intervention research most visibly highlights the needs of practitioners to have their programming rigorously tested and evaluated with respect to child well-being outcomes.

As the top priority among both intervention research topics and the entire ranking exercise, understanding the effects of cash-based social safety nets on child well-being outcomes has emerged as highly importance for the sector. Cash transfers have gained prominence as multiple studies have found them effective in improving the welfare of children, including through improved health and nutrition outcomes as well as increased educational attainment [ 37 – 39 ]. The assumption driving the proliferation of cash-based social safety net interventions in humanitarian contexts is that they are an effective way of mitigating crisis-induced economic shocks, thereby preventing the use of coping strategies that may have negative effects on children such as school drop-out, child labor, and family separation. Yet, these assumptions have not been fully tested within disaster, conflict-affected, or displacement contexts, environments where children face unique risks and vulnerabilities. Further, the majority of existing evidence on the effects of cash transfers do not examine child protection outcomes such as reductions in violence, abuse, and exploitation, information of great interest to sector experts.

In addition to understanding the effectiveness of singular child protection interventions on child-well-being outcomes, experts indicated a need to also evaluate multi-sectoral interventions, considering this one of the highest priorities for research. A relatively broad mandate, this methodological research priority underscores the need for study designs that allow for the rigorous evaluation of multiple components within increasingly complex program designs, including analyses on how various components interact with one another. Such research endeavors are inherently more complicated, yet recent guidance from the global health sector has shown this to be a priority that spans disciplines within development and humanitarian assistance [ 40 – 42 ].

Similarly, as multi-sectoral and interdisciplinary interventions are prioritized by funders, experts within this study have identified a need to quantitatively demonstrate the added value of child protection interventions when mainstreamed within other sectors, such as health, nutrition, or education. Prior research on the effects of nutrition supplementation and play/stimulation on stunted children in Jamaica provides an example of how social scientists have captured the additive effects of non-sector related interventions [ 43 ]. If protection interventions are found to be effective in improving non-protection related outcomes for children, this type of evidence would support an argument that child protection considerations and/or program components are necessary to achieve desired results in other areas of humanitarian relief.

Child labor in humanitarian settings was also a common theme with both intervention effectiveness and prevalence data among the top 10 priorities for research investment. Similar to cash transfers, child labor has been examined across multiple development settings [ 44 – 46 ], however, data from humanitarian contexts is extremely sparse and generally limited to anecdotal information. As urban environments have become a more common setting for humanitarian crises, there is an increased risk that children will be used for begging, street vending, and other forms of exploitation [ 47 – 48 ]. There is a need to understand the prevalence, dynamics, and effective interventions to reduce this protection risk for children who have been displaced as well as children from affected host communities.

In order for child protection programming to be more responsive to current humanitarian contexts, experts felt that there was value in 1) better understanding the protection risks of children with disabilities (particularly non-observable disabilities) and 2) translating any existing evidence on implementing humanitarian programs in urban settings into more tangible guidance for CP practitioners. Disability inclusion has gained traction as a critical component within humanitarian assistance, however, experts noted this work to primarily address physical disabilities where programmatic accommodations are often tangible and straightforward, such as the fitting and distribution of assistive devices. In contrast, many experts noted feeling ill-equipped to properly serve children with cognitive and intellectual disabilities, agreeing that an examination of the protection risks for children with disabilities, particularly non-observable disabilities, should be prioritized.

Similarly, experts felt more guidance on child protection programming in urban humanitarian crises would be beneficial. Indeed, as rapid urbanization has resulted in more densely population cities and towns, the potential impacts of a humanitarian crisis increase, particularly in areas with weak infrastructure and insufficient governance [ 49 ]. The Syrian refugee crisis has seen over 5 million people flee to neighboring countries, seeking refuge predominately in the cities and towns of Lebanon and Jordan with another 6 million internally displaced within Syria, again primarily in urban and peri-urban settings [ 50 ]. This trend differs from past decades of humanitarian assistance that was largely provided within camp-based settings, requiring a new framework for understanding how best to support children in crisis. Other actors within humanitarian response have begun to give this issue greater attention in the past several years [ 51 – 52 ] enabling the identified priority of secondary literature review and as relevant, the translation and integration of evidence into child protection strategies and program design.

Localization and sustainability were also key themes. Within the top 15 research priorities, experts conveyed a need to identify best practices for both engaging the local social service workforce in emergency settings and establishing sustainable para-social work models such that structures will exist past the duration of humanitarian intervention. At the same time, respondents would like to understand best practices for bridging humanitarian and development initiatives for child protection systems strengthening. Taken together, these items demonstrate a desire to understand how best to engage local social service structures (formal and informal) and connect the work done during a crisis to a longer-term development agenda.

When scrutinizing the findings further, three trends emerged. First, among the top 15 research priorities, participants routinely scored research questions much higher for relevance than originality. It is speculated that this score variation may be a result of recent efforts by the sector to discuss and advocate for a more robust evidence base in humanitarian contexts [ 53 – 55 ]. The relatively frequent discussion about these evidence needs may have made a number of research questions appear unoriginal to participants yet still highly relevant because the research had yet to be carried out. This finding highlights the readiness of child protection experts to move forward an actionable research agenda for humanitarian settings.

Next, there were notable differences in the priorities of field and non-field based staff with only one research topic ranking within the top ten for both sub-groups (rigorously evaluate the effectiveness of family strengthening interventions to improve child well-being). As compared to non-field based respondents, those residing within an operational setting were less likely to identify rigorous evaluation within their top priorities. Instead, these respondents tended towards the identification of best practices, a logical reaction given that such research would presumably result in straight-forward guidance to program design. At the same time, field-based staff highly ranked capacity building in empirical research design and data analysis planning for the child protection sector, demonstrating a desire to build the skills required to further evidence generation.

Lastly, our study explored research topics within the professional sector of “child protection in humanitarian settings”, which had a rather expansive purview. As such, some of the research priorities identified by experts were similarly broad in scope. It is our hope that as the sector progresses in the collection and translation of rigorous evidence that future priority setting exercises on child protection in humanitarian settings will be able to focus on particular needs within narrower sub-specialties.

Limitations

The CHNRI method is based on purposive sampling where individuals are invited to participate based on their expertise in a given field. This method relies on a non-representative sample to aggregate knowledge and experiences. The findings are therefore limited to the perceptions of a discrete group of individuals and it is possible that additional areas for research investment may have emerged if a larger sample was recruited though, as earlier noted, prior quantitative work has demonstrated collective opinion to stabilize with as few as 45–55 participants [ 29 ], however, this finding was based on binary “yes” or “no” responses as opposed to the Likert scale implemented in this project. Further, given the low-cost and replicability of the procedure, it is attractive to a variety of sectors as a means of fostering transparency and enhancing systematization in the creation of a research agenda.

In our study. non-field based staff were more likely to respond to requests for interviews and as such, had greater representation within the study ( Table 1 ). This created a certain level of bias towards the insights and experiences of child protection experts currently based in non-operational settings. When secondarily analyzing results based on whether respondents resided in operational or non-operational settings, we did find variation in the prioritization of research items ( Table 4 ). These findings indicate that even when saturation appears to have been reached, the rank ordering of priorities can be influenced by the characteristics of the sample.

Deviating from standard CHNRI procedure, we requested that participants rank research priorities against pre-determined criteria using a Likert scale as opposed to binary “yes” or “no” responses. This decision was informed by the lack of existing evidence within the sector of child protection in humanitarian action and the anticipation that a large majority of research items would be affirmatively ranked by respondents, making it difficult to discern which were of highest priority. While Likert scales have been used extensively in other crowdsourcing methods [ 56 – 58 ], more research is needed to examine the benefits and drawbacks of using a Likert scale within an adapted CHNRI framework.

Lastly, our study did not include “impact” as a ranking criterion. Such a criterion would have participants rank research based on the likelihood it would result in a reduction of protection risks or improved responses to child protection violations. While our research criterion of “relevance” included similar language, it did not explicitly request input on the ability of a research question, once answered, to impact the lives of children. Further research priority setting exercises on child protection may wish to include “impact” as a ranking criterion separate from “relevance” in order to further ascertain the merit of a research idea.

Rigorous, scientific research that assesses the scope of child protection risks, examines the effectiveness of existing child protection interventions, and translates evidence to practice is critical to move the sector forward and respond to donor calls for programming that is evidence-based. This CHNRI adaptation solicited inputs from a range of sector experts with variation across geographic location and job function. It is our hope that findings can guide a global research agenda, facilitating cooperation among donors, implementers, and academics to pursue a coordinated approach to evidence generation.

Supporting information

S1 annex. full ranking..

https://doi.org/10.1371/journal.pone.0202570.s001

Acknowledgments

The authors express gratitude to the participants who took time from their busy schedules to generate and rank research priorities for this exercise.

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Cholera Roadmap Research Agenda

Accelerating Roadmap progress through evidence, optimization, and innovation

Home  -  Resources - Cholera Roadmap Research Agenda

The Cholera Roadmap Research Agenda identifies knowledge gaps most important to cholera experts and stakeholders and establishes a prioritized list of research questions that, when answered, will have a significant impact on achieving the Cholera Roadmap goals.

Together, the cholera control community can align our efforts and resources to answer the most pressing cholera research questions of our time and encourage discovery research and innovation.

To achieve the ambitious goals of Ending Cholera: A Global Roadmap to 2030 , the partners of the GTFCC and cholera-affected countries need to accelerate progress in the coming years. In response to requests by the cholera control community, GTFCC partners launched a process to develop a prioritized Cholera Roadmap Research Agenda using the Child Health and Nutrition Research Initiative (CHNRI) approach. A prioritized list of cholera research questions was identified through consultations with 177 cholera experts and other stakeholders operating at global, regional and country levels.

The agenda provides a list of the top 20 highest-priority research questions, along with the top 5 priorities per Roadmap Pillar – oral cholera vaccine (OCV), water, sanitation and hygiene (WaSH), surveillance, and case management. In addition, it outlines the three highest priority areas for discovery research.

Call to Action

The GTFCC partners call on all stakeholders to use the Cholera Roadmap Research Agenda to advance our collective effort in ways that are suitable and beneficial to their role:

• Researchers: Use the Research Agenda to prioritize design and execution of research activities
• Donors: Fund research projects that will have the most impact on practice and policy
• National Policy-Makers: Incorporate research priorities, goals and findings into National Cholera Plans (NCPs)
• Programme Implementers: Incorporate research priorities, goals and findings into operational plans

These efforts will provide more effective tools and strategies and a stronger evidence base to accelerate progress towards the goals of the Cholera Roadmap and, ultimately, towards a world free from the threat of cholera.

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IARC study on nutrition and childhood cancer included in stakeholders meeting on nutrition and childhood noncommunicable diseases, a side event to the World Health Assembly

The International Agency for Research on Cancer (IARC), the International Initiative for Pediatrics and Nutrition (IIPAN) at Columbia University Irving Medical Center (New York, USA), and other researchers involved in the World Health Organization (WHO) Global Initiative for Childhood Cancer will convene a stakeholders meeting on the topic of how recent advances in nutrition and childhood cancer have affected health outcomes globally. The meeting will be held at 7:00–9:00 CEST on 28 May 2024 at the President Wilson Hotel in Geneva, Switzerland. This will be a side event to the Seventy-seventh World Health Assembly, which is taking place in Geneva from 27 May to 1 June 2024.

The meeting will convene international stakeholders who are advancing nutrition within the context of chronic diseases, with a focus on challenges, solutions, and opportunities in building institutional capacity (with a region and country focus), clinical education, and advances in the delivery of care to advance policy initiatives. The meeting participants will include stakeholders from the World Bank and the WHO Hepatitis Programme, Sexually Transmitted Infections (STI) Programme, and Noncommunicable Diseases Programme, as well as national experts from Ethiopia, the Philippines, Slovakia, and the United Republic of Tanzania. IARC scientists Dr Inge Huybrechts and Dr Zisis Kozlakidis will provide details of the ongoing InterNatIonal CHildhood Leukemia Microbiome/MEtabolome (NICHE) study. Dr Bente Mikkelsen, the Director of Noncommunicable Diseases in the division of Universal Health Coverage/Communicable and Noncommunicable Diseases at WHO, will provide the closing remarks.

More information about the programme

Read more about the WHO Global Initiative for Childhood Cancer

Published in section: IARC News

Publication date: 27 May, 2024, 0:09

Direct link: https://www.iarc.who.int/news-events/iarc-study-on-nutrition-and-childhood-cancer-noncommunicable-diseases-wha/

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• Finding the place for nutrition in healthcare education and practice
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• http://orcid.org/0000-0002-5048-2939 Ebiambu Agwara 1 ,
• http://orcid.org/0000-0003-2920-9847 Kathy Martyn 1 ,
• Elaine Macaninch 1 ,
• Wanja Nyaga 1 ,
• http://orcid.org/0000-0002-6589-4880 Luke Buckner 1 ,
• http://orcid.org/0000-0003-0154-1960 Breanna Lepre 1 ,
• http://orcid.org/0000-0003-4555-1407 Celia Laur 1 and
• http://orcid.org/0000-0003-3295-168X Sumantra Ray 1 , 2 , 3
• 1 NNEdPro Global Institute for Food, Nutrition and Health , Cambridge , UK
• 2 School of Biomedical Sciences , Ulster University , Coleraine , UK
• 3 Fitzwilliam College , University of Cambridge , Cambridge , UK
• Correspondence to Professor Sumantra Ray; s.ray{at}nnedpro.org.uk

Background Malnutrition continues to impact healthcare outcomes, quality of life and costs to healthcare systems. The implementation of nutrition care in healthcare practice may improve health outcomes for patients and the community. This paper describes the iterative development and implementation of nutrition medical education resources for doctors and healthcare professionals in England. These resources are part of the Nutrition Education Policy for Healthcare Practice initiative.

Method Action research methodology was employed to develop and implement nutrition education workshops for medical students and doctors. The workshop was developed iteratively by an interdisciplinary project team, and the content was initially based on the General Medical Council outcomes for graduates. It was evaluated using quantitative evaluation tools and informal qualitative feedback captured from attendees using tools provided by the host organisations and developed by the roadshow team.

Results A total of 6 nutrition education workshops were delivered to 169 participants. This simple educational package demonstrated potential for delivery in different healthcare settings; however, formal feedback was difficult to obtain. Evaluation results indicate that workshops were better received when delivered by doctors known to the participants and included local context and examples. Reported barriers to the workshops included difficulty for participants in finding the time to attend, beliefs that peers gave a low priority to nutrition and uncertainty about professional roles in the delivery of nutrition care.

Conclusion A key outcome of this project was the development of resources for nutrition training of doctors, adapted to local needs. However, relatively low attendance and multiple barriers faced in the delivery of these workshops highlight that there is no ideal ‘place’ for nutrition training in current healthcare teaching. Interprofessional education, through relevant clinical scenarios may increase awareness of the importance of nutrition in healthcare, support the alignment of health professional roles and improve subsequent knowledge and skills.

• nutrition assessment

Data availability statement

Data are available upon reasonable request.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjnph-2023-000692

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WHAT IS ALREADY KNOWN ON THIS TOPIC

There is a great need for more nutrition within medical education, as well as a need for greater clarity of a doctor’s role in nutritional care and when to refer for specialist advice.

WHAT THIS STUDY ADDS

The development and implementation of resources for nutrition training of doctors adapted to local needs.

This paper shows that there is no one ‘place’ for nutrition; hence, the Nutrition Implementation Coalition provides a ‘hub’ of material and expertise adapted to the needs of the providers and settings.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The need for multiprofessional ‘hub’ of material and expertise that can support medical schools and healthcare professionals who may lack faculty to develop and implement nutrition education in practice.

Introduction

Malnutrition comprises the double burden of undernutrition and overnutrition including micronutrient deficiencies, which together continue to impact the healthcare outcomes and quality of life of individuals, as well as costs to the healthcare systems. 1 For example, in hospitals, rates of malnutrition remain high, averaging 35% internationally, and in 2015, it was estimated that malnutrition in England cost the National Health Service (NHS) almost £20 billion. 2

Implementing nutritional care in practice requires the application of nutrition knowledge and skills, and ideally this care is individualised to health priorities, patients’ goals, preferences and sociocultural context. 3 Dietitians are specifically trained to provide nutrition care; however, due to their limited numbers, they rely on nutritional problems being recognised by others with subsequent clinical referral. Furthermore, other health professionals, such as doctors and nurses, are well placed to initiate nutrition care and provide support of advice as they tend to have regular contact with patients and doctors are perceived by patients as a credible source of nutrition information. 4 This provides opportunities for discussions and nutrition screening. 5

However, although doctors, nurses and other health professionals perceive nutrition as important, they require the knowledge, skills and confidence to incorporate nutrition as part of patient care or to identify when an individual might benefit from a referral to a dietitian. Importantly, medical students and doctors' welcome further nutrition education, as professional bodies internationally now recommending doctors discuss diet with their patients. 6–8 Despite this perceived need, and continual focus on improving medical nutrition education, undergraduate or preregistration nutrition education for doctors is limited. 9 Moreover, there is limited information available on nutrition learning objectives or outcomes, or teaching methods. Internationally, only 45% of medical education accreditation and curriculum guidance was found to even mention nutrition, 10 and to this end, there is limited incentive for education providers to include nutrition in medical training.

In the UK, the responsibility for postgraduate medical education (PGME) is devolved to the respective professional bodies in England, Wales, Scotland and Northern Ireland. 11 The programmes are commonly referred to as foundation programmes, core training and specialty training. 12 During foundation training, junior doctors have protected learning time, and nutrition is identified as part of the syllabus followed in England, Wales, Scotland and Northern Ireland. 13 Separate curriculum exists for 32 specialty training programmes in the UK. 14 In specialty PGME, nutrition content varies depending on the perceived relevance of nutrition to the medical specialty with limited mandated content. Table 1 shows examples of where nutrition is mandated in UK postgraduate medical curriculum. In 2021, with the aim to standardise nutrition education in undergraduate medical training, a working party convened by the Association for Nutrition (AfN) published the nutrition curriculum for UK undergraduate medical students. 15 This builds on the UK General Medical Council (GMC) ‘outcomes for graduates’, 16 which stipulates the core competencies for medical graduates in the UK. However, ways to support systematic integration of nutrition into medical education are required, as there is currently no requirement to include nutrition in medical training. Even if nutrition education can be integrated into current medical training, there remains a need for nutrition education and ongoing support for medical doctors who are already qualified. 17

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Examples of where nutrition is mandated in UK postgraduate medical curriculum

With these challenges in mind, in March 2019, the NNEdPro Global Institute for Food, Nutrition and Health, which has a key focus on medical nutrition education, launched a nutrition education package as part of their ‘Nutrition Education Policy in Healthcare Practice (NEPHELP)’ project. The aims of NEPHELP were: (1) to develop, evaluate and implement nutrition education workshops and educational resources; (2) to understand the feasibility and acceptability of a nutrition education model via participant and facilitator feedback; and (3) to gain insights into where doctors and health professionals see the place for nutrition in their education. This paper primarily focuses on aim 1, and to a lesser extent, secondarily focuses on aims 2 and 3.

This paper describes the iterative development and delivery of a nutrition education workshop for junior doctors and health professionals piloted in Glasgow, then delivered at six sites across England. Feasibility and acceptability of the workshops are explored along with reflections on the place for nutrition in medical and healthcare profession education.

Methodological approach

Study design.

The development of NEPHELP used action research methodology, 18 which is considered a pragmatic approach to instigate change. The action research cycle includes problem identification (including reflection), planning, action (implementation of change and monitoring) and evaluation or reflection before starting a new situation analysis. Action research was considered rigorous in this context because it supported the aim of exploring both enablers and barriers to the implementation of nutrition education in medical practice with the research participants. 19

The project was conducted in two stages, including (1) an initial pilot workshop in Glasgow, followed by (2) the delivery of workshops across England as part of the ‘NEPHELP Nutrition Training Roadshow’ ( figure 1 ).

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Place for nutrition paper.

The NEPHELP team

The interdisciplinary teaching team consisted of medical doctors, a registered dietitian, associate and registered nutritionists, a registered nurse, academics and education professionals, all members of the NNEdPro Global Institute. The teaching team developed and delivered the workshops and the evaluation tool.

Stage 1: piloting the NEPHELP workshop

Workshop participants and recruitment.

This was conducted with a multiprofessional international audience attending the BMJ Quality and Safety in Healthcare conference at Glasgow in 2019. Participants voluntarily signed up for a 4-hour NEPHELP nutrition workshop.

Workshop content

The initial workshop content was based on GMC expected learning outcomes for medical graduates, 16 postgraduate curricula 13 20 and perceived nutrition priorities within clinical settings, based on the educational and professional experiences of the interdisciplinary team, and included an overview of nutrition science related to clinical care Case-based discussions were used to assist with the translation of nutrition knowledge into practice.

The workshop aimed for participants to: (1) understand key principles of human nutrition, (2) understand the importance of balanced diet for health, and in illness, recognise factors that impact on equitable access to healthy food, (3) explore how individuals can include nutritional screening, care and dietetic referral into their practice and (4) provide feedback on the acceptability of the workshop as a strategy for delivering nutrition education.

The NEPHELP evaluation tool included quantitative and open-ended questions, which were designed to explore the knowledge, attitude and practices in nutritional care, and perceptions of requirements for nutrition in medical education. Feedback on the workshop content and ideas on how the programme could be improved were also gathered to inform further development of the workshop.

Stage 2: delivering the NEPHELP ‘Nutrition Training Roadshow’ across England

In this second stage, termed the ‘roadshow’, the NEPHELP workshop was delivered, evaluated and adapted to six healthcare settings across England. The NEPHELP roadshow was delivered in three formats: (1) as a part of mandatory training within health settings (hospitals, primary care etc), (2) a standalone workshop or (3) as an invited workshop delivered as part of a general GP training day and organised by an external group.

Participants and recruitment

Workshop participants were invited by the PGME and NHS contacts who also circulated workshop information. The delivery of stage 2 workshops varied depending on NEPHELP facilitator availability, with some being codelivered between the NEPHELP team and local dietitians or doctors.

Following each iteration of the workshop, evaluation forms and informal reflections were captured to inform the refinement of workshop content. The NEPHELP evaluation tool (described above) was adapted to the audience in each workshop. Additional feedback was provided by PGME faculty through their own evaluation forms. This ‘in-house’ feedback differed for each centre, was designed and collected independently but shared with the NEPHELP team. NEPHELP observers took notes during workshop discussions, and after each workshop, the facilitators listened to the observations and critically reflected on the session.

The iterative nature of the action research methodology allowed for the continuous review of data as it was collected. Quantitative data collected through NEPHELP evaluation tool and PGME forms were analysed descriptively. Qualitative data collected from open questions in the evaluation tool, PGME forms, notes taken during the workshop by observers and postworkshop critical reflection sessions were subject to content analysis, 21 an approach widely used in qualitative research. Analysis was completed by two members of the NEPHELP team, who did not have prior relationships with any of the participants. EM and KM independently grouped the material into topics using a word processing package, and the main topics were then discussed with the wider NEPHELP team.

The initial 4-hour workshop was piloted in Glasgow in March 2019, with 40 interdisciplinary participants at the BMJ Quality and Safety in Healthcare conference. Following the pilot, the workshop was modified based on participant evaluations (n=4), oral feedback from participants and the NEPHELP team reflections. The roadshow was conducted between March 2019 and February 2020, with workshops conducted at 6 locations across England with 169 participants and a total of 13.5 hours ( table 2 ).

Overview of completed NEPHELP workshops (March 2019 to February 2020)

At the end of the workshop, five (12.5%) NEPHELP evaluation questionnaires were returned from two doctors working in internal medicine, one GP, one nurse and one service manager ( table 2 ). While all respondents agreed that the workshop was useful for themselves and their colleagues, there were suggestions that the workshop included greater involvement of community care and increased focus on elements of nutrition care across the care continuum. Following this feedback, the focus for NEPHELP to also consider general practitioners and other healthcare professionals was widened.

The total response rate for the NEPHELP evaluation tool was 12.5% for the pilot and 10% for subsequent workshops. In addition, 15% completed PGME evaluation tools, and 26% of participants contributed some feedback but the heterogenic nature meant there was limited consistency in evaluation methods between each session. The combined PGME and NEPHELP evaluation data are reported individually in table 3 .

Combined PGME and NEPHELP evaluation data

The roadshow

Of the six workshops held during the Roadshow, three were mandated sessions and three were voluntary, as summarised in table 2 . Mandated sessions had much higher attendance; however, there was a low response rate overall to the evaluation questionnaires. Feedback from each session was used to inform future sessions ( table 4 ).

Summary of evaluation findings from each workshop

Multiple methods for delivery were tested, spanning rapid sessions in existing training, to full day workshops, with no format perceived as being ideal. The variation in format addressed the logistical constraints on time and location, and the need to fit the workshops within existing programmes of study. For example, a full day session requested by a GP trainer (Essex) was held on a weekend, and although advertised and free, only one person attended. In contrast, the rapid session (East of England) attended by 60 participants aimed to see if the training could be added into an existing event, and if all learning objectives could be covered in the shorter time. Formal feedback from this session was limited.

NEPHELP evaluation responses

The mandated teaching in London at a teaching hospital for foundation year 2 had the highest response rate to the NEPHELP evaluation tool at 52% (n=17). Nine participants (53%) reported receiving no previous nutrition education, while eight (47%) recalled some nutrition training in their medical education. Of participants who reported receiving nutrition training, five reported receiving this education during medical school, one from a self-selected module, one during a biomedical sciences degree and one elsewhere in their foundation training. All participants felt that the clinical nutritional needs of patients were not prioritised, and as a result were poorly addressed in the hospital setting. As noted by one participant, nutrition is ‘ certainly, something that could be improved ’, but felt that it was ‘ unlikely to be top priority in a consultation ’.

When asked to give an example of where nutritional needs for a patient were met, 41% (n=7) recalled examples of acute nutrition, namely, either nasogastric or parenteral nutrition, 29% (n=5) reported seeing clinical benefit from malnutrition treatments and three specifically mentioned the benefits of dietitian involvement in secondary care. One participant noted examples “In upper GI (gastrointestinal) surgery a lot of patients were on TPN (total parenteral nutrition) or NG/NJ (naso gastric/naso jejunal) feeds.” Another mentioned “Gastro ward with dietitian input (eg, TPN patient).”

When these participants were asked about the barriers to effective nutritional care, 15 (88%) identified time as a barrier, 11 (61%) identified a lack of knowledge, 8 (47%) identified a lack of clarity on roles and responsibilities and 7 (41%) perceived a lack of interest from colleagues as a barrier to such care in practice. One participant said, “I'm aware as a junior in A&E [Accident and Emergency] it is quite slow spending time taking a good diet history and giving advice would make consultations even longer.” When questioned about including nutritional screening or history taking as part of their practice respondents reported the following reasons a lack of nutrition training (n=6, 35%), time pressures for doctors (n=5, 29%) and some participants perceived nutrition care as a dietitian’s role (n=4, 24%). Comments included, “Poor training and perception that nutrition is the preserve of dietitians. Time not allocated”. Another focused on the lack of education: “Little education in med school. Not much time. Unclear whose role it is.” The lack of interest and importance was also mentioned: “Both knowledge on importance but also lack of interest in implementing what little people do know about nutrition.”

Most respondents (88%) felt doctors had a role in nutrition care with half (n=9) identifying the role of a doctor in initial assessment to identify nutrition risks and a third (n=5) indicating the importance of onward referral to the dietitian as part of their role. As one participant mentioned, there are “Very few specialists so it needs to be taken responsibility for by all staff.” They saw their role as the “Assessing, advising, signposting and referring.” Another participant focused on actions to take, particularly regarding handover. “Reorganising when and where referrals are required. Risk assessment. Improving inter-team handover.” While one questioned the role of a doctor in nutrition care, highlighting bigger societal issues. “Some roles, but the most significant barriers lie in public health policy, food poverty and education.”

Most participants in this group (16/17) felt that nutrition education should be an essential element of medical training and found the content of the workshop relevant. When asked about the most appropriate timing of this nutrition education, 12 participants (71%) felt this should be linear, with nutrition education increasing from medical school to junior doctor, while 3 participants (18%) felt nutrition education was most relevant to junior doctors. Two participants (12%) felt nutrition training was most relevant to medical students and would be best placed in undergraduate medical education. Seven of the participants (41%) valued skill-based nutrition education and case-based learning. However, opinions varied on what was relevant nutrition content, but included, ‘practical examples and how to put into practice’ , ‘ important from Global public health perspective’, ‘common things in hospital for example, refeeding’, ‘eating disorders, intuitive eating, diet culture and how best to educate without promoting diet culture’. In contrast, one participant did not perceive nutrition as relevant in medical training as “Patient education and school age education plus socioeconomic factors far outweigh medical input” and others felt that “didactic teaching [was] less useful.”

Mandated versus voluntary attendance

Mandated sessions were better attended and evaluated. In the UK, all junior doctors have protected learning time to attend mandated teaching. 11 13 20 22 NEPHELP workshops were delivered in mandated teaching during two FY2 training sessions and one GP trainee protected teaching session. In contrast, attendance at non-mandated training was particularly poor. Participants commented on the difficulties experienced in attending non-mandated sessions due to professional and personal pressures. “If I don’t have to go it’s not something I would attend, at the end of a week I have other priorities”.

Training was generally better received when local doctors were present and less well received when other healthcare professionals individually delivered the same content. The perception was that training would have been better received if a medical role model acted as a peer educator, for example, where teaching was codelivered with another GP trainee as opposed to being delivered by non-medical members of the NEPHELP team who are unknown to the participants. Limited opportunity for interprofessional education (IPE) and poor collaboration in nutrition care across health systems was also identified as a barrier to effective nutrition care practice.

Low prioritisation of nutrition in clinical care

Many participants identified a low priority given to nutrition in clinical care. Foundation year trainees recognised that nutrition is not addressed adequately in clinical practice but did not have recommendations for how it could be improved, citing logistical challenges such as a lack of priority, time and senior recognition of nutrition in patient management, care planning and treatment. They also felt that there was limited time available for education and variation in opinion on the most important aspects of nutrition. Some topics rated as important were based on prior clinical experiences such as working in a ‘gastro’ environment, or seeing TPN/NG feeding, while others perceived a topic to be importance based on personal interests, such as the ‘low carbohydrate diet ’ . Many participants indicated that their personal nutrition knowledge, level of interest and social media informed their practice.

Lack of clarity on roles and responsibilities in nutrition care

While participants recognised the importance of nutrition, they remained unclear on their role and scope of practice (as doctors) in nutrition care. Participants attending the primary care training day did not feel that a session on nutrition was appropriate for them as GPs and perceived nutrition as relating solely to healthy eating. Many Foundation doctors found it challenging to address nutritional issues in practice and indicated that their focus was the immediate medical concern. Some participants believed that public health professionals should hold more responsibility than doctors in the delivery of nutrition care. Addressing misconceptions about the role of diet in the prevention and management of non-communicable diseases, its role in medical treatment across all settings, and how different members of the multi professional healthcare team can work synergistically to achieve favourable patient outcomes, may raise the profile of nutrition in medical practice.

It is recognised that collaboration across professions such as registered nurses, doctors and allied health professionals fosters a positive and rewarding practice environment and improves patient outcomes. 23 This collaboration has previously been identified by medical students and junior doctors with an interest in nutrition as a key factor to support the integration of nutrition into medical practice. 24

Interprofessional education (IPE) is recognised by the WHO as an ‘innovative strategy that will play an important role in mitigating the global health workforce crisis’ and address professional silo working. 25 The cross-cutting nature of nutrition, and its involvement in the promotion of health and prevention and management of disease, reiterates that nutrition should be a core element of all healthcare professional’s education. Ideally, it should be ideally through an IPE lens to foster a multidisciplinary approach in practice.

Challenges for multiprofessional learning, working and collaboration

During NEPHELP, there was a reluctance from PGME providers to include non-medical professionals within junior doctor-protected sessions, limiting the opportunity and scope for IPE. Moreover, there was a perception that the NEPHELP workshop was not as well received when a medical doctor was not part of the teaching team. For trainees, the historic paucity of nutrition education within medical training limits the number of role models who can model and advocate for nutrition care. 8 26 However, research has identified the importance of professional role models to support learning in medical education and how this authenticates the place for content and its relevance to clinical practice. 27

Using action research methodology, the NEPHELP team set out to develop an educational package based on GMC outcomes for graduates, which could be delivered in different healthcare settings. In addition, they sought to understand where doctors and health professionals see nutrition as fitting into their educational journey and considered the feasibility of this workshop approach.

Lessons learnt from NEPHELP

From this work, we recognise that there is no one ‘place’ for nutrition, but there is a need for clear curriculum content at all stages of a doctor’s education.

Undergraduate and postgraduate nutrition curriculum development

The recently published undergraduate nutrition curriculum for medical doctors represents a consensus among multiple stakeholders, nutrition professionals and medical royal colleges on the required nutrition competencies for medical graduate. 28 This benchmarks what should be taught in medical education as an accompaniment to GMC learning outcomes for graduates. In addition, the 2021 Foundation curriculum 13 supports engagement with third-sector organisations, which are at the forefront in providing services to support health prevention including services to support education or access to healthy foods or services directly addressing food poverty.

Clearer postgraduate mandated nutrition competencies within existing PGME curriculum may help to better elucidate key nutrition knowledge and skills for practicing doctors, which could be a useful accompaniment to the foundation doctor’s curriculum, helping to increase validity and visibility of nutrition while also clarifying the role of medical doctors and the wider MDT. However, F2 participants completing the NEPHELP evaluation tool indicated a preference for more linear nutrition education, suggesting a desire to advance nutrition along with other medical skills but with a clear preference for more clinically focused, case-based teaching.

To demonstrate interprofessional roles and responsibilities of care, there is a need for clinically relevant scenarios more closely aligned to existing roles and workplace expectations to ‘nudge’ professionals to raise the profile of nutrition in their practice, as part of an MDT approach. Educating doctors in the absence of the MDT may not address the issue.

Organisations such as NNEdPro, the AfN and GMC can work with educators, including medical schools and foundation programmes to create a framework for trainees to work towards achieving the role and competencies they outline.

Furthermore, recent findings from Lepre et al , 29 reflecting the expressed needs of end users within the medical/healthcare workforce, indicate the need for knowledge and skills to consider the findings from nutrition screening and assessment and coordinate nutrition care, thereby highlighting the importance of the findings from this work in implementation.

Summary of recommendations

Nutrition educators.

Nutrition content needs to reflect the context of the workplace, with most participants indicating their preference to more clinically focused practical teaching directly relevant to their roles and signposting to resources the participants can use.

Participants preferred practical-based/short-based/skills-based education, which can be easily linked back to practice and can be easily integrated into short windows of opportunity for education.

Universal nutrition education, such as NEPHELP, may offer a short, focused baseline form on which other nutrition education can be recommended to support core as well as more specialist and potentially a more expert specialist nutrition education pathway.

Clinicians in primary and secondary care

The needs of those in primary care and secondary care were noted to be significantly different, as well as a major need to reframe the communication and transfer of nutrition care between the two settings.

There is a need for IPE or discussion across professional boundaries to support nutrition pathways. Without this, it may be difficult to address some of the identified barriers. This may pose a challenge in finding a common language so that nutrition messaging is clear and breaks through professional silos within a more multiprofessional model of care.

Postgraduate medical educators

Although nutrition is mentioned in published curriculum frameworks, examples of how nutrition might be included in education for UK Junior doctors are limited 30 and should be developed to support capacity building.

Trainee GPs wanted more in-depth nutrition education suggesting we need a variety of options and opportunities; from the minimum standards to assure patient safety, to potential career pathways for further specialisation.

To support sustainability, a PGME nutrition curriculum may assist in reaching a consensus on expectations related to nutrition and professional working roles.

PGME providers can take advantage of existing multidisciplinary nutrition educators such as the UK Nutrition Implementation Coalition. Training workshops also need to be endorsed by a professional body with relevant continued professional education credits.

Strengths and limitations

Data from multiple sources of feedback were pooled to provide deeper insights into some of the potential barriers and enablers to implementing nutrition education.

Heterogenic feedback forms and processes in each setting limited analysis. Attempts to standardise data collection on participant opinions on the utility of the nutrition workshops, as well as perceptions on nutrition roles and responsibilities in practice, were made. The NEPHELP evaluation tool was not a validated tool, which limited the usefulness of the feedback captured. To minimise facilitator pre conceptions, postworkshop discussions, alongside evaluations from participants, were used.

Another limitation was the recruitment of participants to participate in the non-mandated sessions. This was particularly evident during the Essex Roadshow event, where despite the workshop being organised at the request of the primary care providers and the enthusiasm to run this workshop outside of normal working hours at the weekend, only one participant attended. Generally, due to the nature of nutrition education and its broad application across multiple areas of practice, most health practitioners would be interested in focused nutrition content that relates to their clinical setting, specialty and region. Hence, we would imagine that if the nutrition content is clinically and regionally specific, this might stimulate greater interest and enthusiasm in nutrition education and its application in their healthcare setting.

Demographics of participants completing feedback were mainly junior doctors and general practitioners. The low response rate limits the generalisability and transferability of our findings and does not consider the views of other healthcare professionals regarding enablers and barriers to nutrition education, as well as the provision of nutrition focused care on clinical practice.

The NEPHELP project successfully delivered and adapted a bespoke nutrition education programme for doctors. However, there was no clear a ‘place’ for this training and there are significant, ongoing, barriers to delivering nutrition training in the medical postgraduate setting.

For this reason, in the UK, NNEdPro, ERimNN (Education And Research In Medical Nutrition Network), Culinary Medicine UK and Nutritank have come together to form the Nutrition Implementation Coalition (2022–23). 31 A coalition encompassing multiprofessionals who can provide a central hub of material and expertise that will support medical schools and health professionals who may lack the current faculty to develop and implement nutrition education. Also, the multiprofessional nature of the coalition can act as a role model for interprofessional working to focus on developing the seamless delivery of nutritional care. Such coalitions may be one way of developing and sustaining interest in developing nutrition expertise, by work alongside mandatory training across the range of healthcare professionals in both primary and secondary care. Finding opportunities for the delivery of clinically relevant nutrition education in ‘bitesize’ sessions may tap into the need for solution-focused education. Nutrition is central to health and disease in both prevention and treatment, this has been recently highlighted through COVID-19 and its sequelae. The interest that developed during the pandemic could provide an opportunity to translate research back into fundamental nutrition training.

Recognising there is no one ‘place’ for nutrition, the Nutrition Implementation Coalition provides a strategy to provide a ‘hub’ of material and expertise that allows the content to be available yet adapted to the needs of the providers and settings. Beyond this paper, this research has continued with the development of the online NEPHELP course via a virtual learning environment and its evaluation in primary care.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants. Participants were given information sheets about the project and how their responses may be used for research, and to inform the educational evaluation and curriculum development. UK NHS National Research Ethics Service guidance indicates that ethics review was not required. Participants gave informed consent to participate in the study before taking part.

Acknowledgments

NEPHELP Team & NNEdPro Organisational Support.

• Stratton R ,
• DiMaria-Ghalili RA ,
• Mirtallo JM ,
• Tobin BW , et al
• Desbrow B ,
• Hughes RM ,
• Leveritt MD
• Leveritt MD ,
• Desbrow B , et al
• Douglas PL ,
• McCarthy H ,
• McCotter LE , et al
• Macaninch E ,
• Buckner L ,
• Amin P , et al
• Crowley J ,
• Mansfield KJ ,
• Ray S , et al
• General Medical Council
• British Medical Association
• Health Education England
• Association for Nutrition
• Macdonald MB ,
• Ferguson LM , et al
• Abramovich N ,
• Burridge J , et al
• Stevens FCJ ,
• Aryee PA , et al
• Maudsley RF
• Douglas P , et al

EA and KM are joint first authors.

X @DrBreannaLepre, @Celia_Laur

EA and KM contributed equally.

Contributors The authors confirm contribution to the paper as follows: study conception and design: EM, KM, LB, CL, BL and SR. Data collection: WN, LB, EA, LB and EM. Analysis and interpretation of results: EA, SR and KM. Draft manuscript preparation: EA, KM and SR. All authors reviewed the results and approved the final version of the manuscript. SR is the guarantor of this work.

Funding NEPHELP was developed as a nutrition education programme for healthcare professionals following a grant from the Medical Nutrition International award for 2017-2019, with initial periods of time spent surveying needs of future participants. 8 The project continued through further AIM foundation funding through 2021.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

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Arkansas defense, health, education projects to receive federal funding

W ASHINGTON, D.C. (KAIT) - The U.S. Senate recently approved a legislative package that includes funding for Arkansas defense, health, and education.

According to a news release from Sen. John Boozman, the legislation was signed into law on Saturday and will fund the following projects, including several in Northeast Arkansas:

Health Care Resources and Education

• Invests $5 million for a Women and Infants Center at the University of Arkansas for Medical Sciences (UAMS) to coordinate programs across the state to reduce infant mortality.
• Boosts dental health education in Arkansas with $15 million to support the Lyon College School of Oral Health and Dental Medicine in Little Rock.
• Invests in future generations of nurses with $15 million to construct a new nursing school building at the University of Arkansas at Pine Bluff.
• Provides $12 million for an Allied Health Building at the University of Arkansas Rich Mountain for instructional purposes, lab simulations and community health.
• Allocates $10 million for a medical education building to accommodate allied health and nursing programs at Northwest Technical Institute.
• Promotes student career development at Shorter College with a $2 million investment in a Science, Technology, Engineering, Arts, and Math (STEAM) Center.
• Funds $8 million for facilities and equipment at UAMS to improve digestive disease care in the state, with a focus on cancer detection.
• Enhances cancer screening capabilities in underserved areas by providing $4 million to purchase three mobile vans fitted with cancer screening equipment to access geographically difficult and underserved regions.
• Strengthens the UAMS milk bank with $3 million.
• Supplies $6 million to support the expansion of the Arkansas State University-Mountain Home healthcare education facility to develop the medical workforce.
• Allots $5 million for the University of Arkansas – Little Rock MidSOUTH Arkansas Youth Drug Use Reduction Program.
• Delivers robust funding for the National Institutes of Health with increased funding for the National Cancer Institute.
• Funds the Maternal and Child Health Block Grant and the Healthy Start Initiative to reduce maternal and infant mortality rates.
• Maintains vigorous funding for Community Health Centers to increase access to health care across Arkansas.
• Increases funding for the Low Income Home Energy Assistance Program (LIHEAP) to support families in need.
• Expands funding for the Children’s Hospital Graduate Medical Education Program to support training pediatric providers and bolster the pediatric care workforce.
• Maintains funding for TRIO programs to assist first-generation, low-income students in attending college.
• Increased funding for Career and Technical Education state grants to bolster the Arkansas workforce.
• Invests in the Fulbright Program, the United States’ flagship educational exchange program created by former Arkansas Senator J. William Fulbright that facilitates global connections.
• Funds global health and nutrition programs to respond to and eradicate malaria, polio and other diseases and invests in efforts to prevent worldwide hunger.
• Educates future generations about the men and women who serve in our nation’s uniform by supporting the Veterans History Project.

National Security

• Fully funds a 5.2 percent pay raise for servicemembers, the largest increase in decades.
• $207.9 million for Ebbing Air National Guard Base in Fort Smith to continue building on last year’s investments in modernizing the base to be a premier pilot training center in the U.S. This is in addition to the $83 million allocated for construction in the MilCon-VA bill signed into law March 9.
• $53.3 million to bolster production and capacity for the manufacturing of vital munitions for the Department of Defense (DoD) in Camden.
• $9.5 million to support production and manufacturing of special chemical warfare protection outfits and special munitions at Pine Bluff Arsenal.
• $36 million for the University of Arkansas to partner with DoD on research efforts.
• $10 million to develop the Army’s next-generation squad weapon system.
• $47 million to support the workforce at Red River Army Depot.
• $8 million to support training at Razorback Range.
• $51 million to fund multiple defense initiatives critical to enhance our national security within the state.
• Invests $1 billion for the National Guard and Reserve Equipment modernization fund.
• Supports Department of State efforts to strengthen its cybersecurity protocols and procedures to defend it from potential cyberattacks from foreign adversaries and other bad actors.
• Provides $2.75 million in DoD grant opportunities to support security and fire protection at the former Army and Navy Hospital in Hot Springs.

Government Oversight and Community Investments

• Encourages the U.S. Securities Exchange Commission (SEC) to provide more time for public input on rulemaking.
• Ensures SEC rules incorporate robust economic analysis.
• Requests the SEC Inspector General to audit the rulemaking process.
• Requires the General Services Administration to save taxpayer money by adopting criteria to better manage extreme weather risks for public buildings.
• Supports regulation and oversight of the contact lens marketplace.
• Provides $8 million for North Little Rock to improve stormwater drainage capabilities and prevent flooding.
• Delivers $4.7 million to Heber Springs for stormwater improvements to prevent damage from flash flooding.
• Delivers adequate funding for economic growth and rural community development.

“These bills will enhance health services access and workforce capabilities to deliver quality care in addition to expanding our state’s national defense contributions,” said Boozman.

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How Free School Meals Went Mainstream

Over the past decade, many more schools started to offer free meals to all children, regardless of family income.

More than 21 million American children now attend schools that offer free meals regardless of family income — a tenfold increase from 2010. Credit... Will Warasila for The New York Times

Supported by

By Susan Shain

• May 21, 2024

Kurt Marthaller, who oversees school food programs in Butte, Mont., faces many cafeteria-related challenges: children skipping the lunch line because they fear being judged, parents fuming about surprise bills they can’t afford, unpaid meal debts of $70,000 districtwide.

But at nearly half of Mr. Marthaller’s schools, these concerns have vanished. At those schools, all students get free breakfast and lunch, regardless of their family’s income. At one school, West Elementary, children grab milk cartons, cereal bars and bananas from folding tables on their way to class, with almost 80 percent of students eating breakfast there each school day.

“We’ve done a lot of good things to feed kids here in Butte,” Mr. Marthaller said. But introducing universal free meals, he added, was “probably the best thing we ever did.”

Advocates for free school meals have pushed for them to be offered to every student for a long time, but saw significant progress in the last decade and a half. Their first big win came quietly, in 2010, when Congress passed an under-the-radar policy called the community eligibility provision , which made it easier for schools to serve free meals to all. Then, during the Covid-19 pandemic, the federal government let every public school student eat for free, rapidly transforming the nation’s thinking around school meals.

Eight states have passed their own universal free meal legislation since the federal largesse ended in 2022. Dozens more have introduced similar bills or have one in the works. A surge of additional schools — nearly 7,000 — have signed up for the community eligibility program that West Elementary participates in: As of the 2022-23 school year, roughly four in 10 public schools were enrolled.

In total, more than 21 million American children now attend schools that offer free meals to all — a tenfold increase from 2010. “Schools did not want to go back to charging some kids,” said Crystal FitzSimons, the director of child nutrition programs and policy at the nonprofit Food Research and Action Center. “They saw the huge benefits of providing free meals to all students: supporting families, supporting kids, changing the culture of the cafeteria.”

A tale of two lunches

From above, Butte looks as if it were carved out of a mountain range with an ice cream scoop. Once known as “ the richest hill on Earth ” for its copper mines, Butte was one of the largest cities west of the Mississippi in its heyday. Today it has approximately 35,000 residents, many of whom have been there for generations.

Amber Moore lives on the east side of town, in a blue house with a view of Our Lady of the Rockies, a 90-foot-tall mountaintop statue of the Virgin Mary. A stay-at-home mom, she lives with her husband, Jake, a telecommunications technician, and their five children, four cats and two dogs.

The Moores’ house is zoned for Whittier Elementary School, which, unlike West, does not participate in community eligibility and does not have universal free meals. So five nights a week, Ms. Moore clears off a patch of her kitchen counter and sets out five lunchboxes. In goes the SunnyD, the cheese stick, the ham-and-cheese sandwich, the Lay’s, the clementine and the fruit snacks. Ms. Moore uses three loaves of bread each week just on lunches. Add breakfast to the equation and she spends about $250 per month on the two meals.

“That’s like a power bill,” she said. “It’s not a small amount.” That bill was eliminated during the pandemic. For those two years, Ms. Moore’s children ate breakfast and lunch at school every day. Then, like the majority of schools around the country, Whittier returned to charging for meals in August 2022. And Ms. Moore returned to packing lunches.

Though low-income students at all American public schools technically qualify for free and reduced-price meals, one-third of eligible students do not participate, according to a Food Research and Action Center estimate. One reason is stigma: Because the school-provided meal, often called “hot lunch,” has long been viewed as a form of welfare , eating it can be a painful marker of poverty.

Parents may also fail to complete the requisite paperwork because they have volatile incomes, face language barriers or are embarrassed about their finances. (As Mr. Marthaller put it, “I think it’s a pride thing.”) Others may be struggling but ineligible: To receive free or reduced-price meals, a family of four must earn less than $55,500 per year . When meals are free to all, advocates say, these obstacles are eliminated.

The Moores don’t qualify for reduced-price meals: Mr. Moore’s income puts them over the limit by $465 a month. “It’s one of those frustrating things,” Ms. Moore said. “I’m sure a lot of parents are in that middle area where it’s like, well, shoot.”

‘Their brains are fired up’

The push for a national school lunch program initially came during the Great Depression , when children were hungry and farmers had surpluses to sell. In the 1960s, school breakfast was added. School meals have since become the nation’s second-largest food safety net , after food stamps.

As childhood obesity rates soared, however, the lunch program was criticized as a contributing factor. In 2010, the first lady, Michelle Obama, who made childhood obesity a signature issue, pressed for the passage of the Healthy, Hunger-Free Kids Act, which led school cafeterias to serve more fruits, vegetables and whole grains and less salt, sugar and unhealthy fats. Policymakers also saw it as an opportunity to feed more hungry children. So, without much fanfare, they tucked the community eligibility provision, or C.E.P., inside the bill.

Under the C.E.P., offering universal free meals became less cumbersome: If 40 percent of a school or district’s students qualify for programs like food stamps or Head Start or are homeless, migrants or in foster care, it can serve free meals to everyone . It does not need to collect individual applications; it simply applies for the program and is qualified for the next four years.

Even the C.E.P.’s architects have been surprised by its impact. “I certainly did not foresee that a little more than 10 years later, 20 million kids would be enrolled in schools that were doing C.E.P.,” said Cindy Long, administrator of the Food and Nutrition Service of the Agriculture Department, who helped design the 2010 act.

The benefits of universal free meals are myriad, experts say. Most crucially, more children eat , helping to combat hunger in a country where 17 percent of households with children experience food insecurity. They also eat more healthful food . When students are well fed, they learn better: Some research suggests that schoolwide free meals can improve test scores , attendance and behavior . Such programs also help schools, by lessening paperwork, and parents, by reducing food expenses .

Like most people, Amanda Denny, a fourth-grade teacher at West Elementary, had never heard of the C.E.P. But she has seen the difference that universal school meals can make. “In my classroom, when those kids do eat breakfast, they are ready to start their day,” she said. “Their brains are fired up, and they’re ready to learn.”

Last October, the threshold to qualify for the C.E.P. was lowered , making more schools and districts eligible. The Moores’ school, Whittier, is now eligible, as are most other schools in Butte. But because of how the federal government calculates reimbursements for school meals, only schools with high populations of needy students break even using the C.E.P.; the rest usually lose money by participating . Advocates have been pushing for higher reimbursement rates so more schools can afford the program.

But in one draft federal budget, House Republicans proposed ending the C.E.P. altogether, arguing that public funds shouldn’t pay for wealthy children to eat lunch . Jonathan Butcher, an education researcher at the Heritage Foundation, believes school lunch aid has ballooned far beyond its original intent. He would like to see the provision repealed.

“They’re not just saying, ‘How can we better get food to kids that need it? They’re saying: ‘Eh, let’s not bother with the details. Let’s just give it to everybody’,” Mr. Butcher said. “That’s not being respectful to taxpayers, nor is it advancing the idea that we should improve a very wasteful school lunch program.”

Most of the states that have passed their own free school meal legislation did so with bipartisan support. To pay for the programs, California, Maine, Minnesota, New Mexico, Vermont and Michigan tapped general revenue or education funds ; Massachusetts and Colorado raised taxes on their highest earners. (In Colorado, the program has been so popular that it is facing a $56 million funding shortfall this year.)

Ms. FitzSimons, of the Food Research and Action Center, believes food is just as integral to public education as transportation and books, which are typically offered to students at no charge. “We spend billions of dollars on funding for education,” she said. “If kids are sitting in class unable to learn because they’re hungry, because their stomachs are growling, then we’re wasting our money.”

At West Elementary, a stuffed bison head presides over the cafeteria. There is no cash register, and at lunchtime, children whiz through the line, grabbing trays of applesauce and teriyaki-doused “steakettes.” They plop down next to friends eating peanut-butter-and-jelly sandwiches from colorful lunchboxes.

Ryder is a third grader who wants to be a YouTuber or a police officer when he grows up (and, he said, “if that doesn’t work out, NASA”). He was shocked to learn that children at other schools have to pay for lunch. “That’s mean,” he said. His friend Louis agreed: “That is cold.”

Things were different for Kaylee Rabson, a fifth-generation Butte resident whose son attends West. “When we were younger, it was definitely very separated,” she said. “Like, if you went to hot lunch, you were kind of embarrassed.” Now, all her son’s friends eat the school lunch — at least when pizza or walking tacos (ground beef, veggies and cheese in a Doritos bag) are on the menu.

“It’s ‘I eat hot lunch because it sounds good, not because I need to.’ It really has erased the stigma,” Ms. Rabson said. “They’re just there having lunch together.”

What are your experiences with free or reduced-price lunch?

This story was published by The New York Times’s Headway team in partnership with High Country News.

The Headway initiative is funded through grants from the Ford Foundation, the William and Flora Hewlett Foundation and the Stavros Niarchos Foundation (SNF), with Rockefeller Philanthropy Advisors serving as a fiscal sponsor. The Woodcock Foundation is a funder of Headway’s public square. Funders have no control over the selection or focus of stories or the editing process and do not review stories before publication. The Times retains full editorial control of the Headway initiative.

Susan Shain is a reporting fellow for Headway, a section of The Times that explores the world's challenges through the lens of progress. More about Susan Shain

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Setting Global Research Priorities in Pediatric and Adolescent HIV Using the Child Health and Nutrition Research Initiative (CHNRI) Methodology

Affiliations.

• 1 HIV Programmes and Advocacy, International AIDS Society, Geneva, Switzerland.
• 2 Department of HIV and Global Hepatitis Programme, World Health Organization, Geneva, Switzerland.
• 3 Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, CA.
• 4 Department of Maternal, Newborn, Child and Adolescent Health, World Health Organization, Geneva, Switzerland.
• PMID: 29994913
• PMCID: PMC6075898
• DOI: 10.1097/QAI.0000000000001742

Background: WHO and the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER) of the International AIDS Society (IAS) led a collaborative process to set global prioritized research agendas, aiming to focusing future research, funding, and stakeholder's efforts. This study describes the methodology used to establish the research agendas.

Methods: The Child Health and Nutrition Research Initiative methodology was adapted in parallel exercises on pediatric and adolescent HIV. After definition of scope by an expert working group, priority questions were collected from stakeholders through an online survey. Submitted questions were coded, analyzed, and collated. The same respondents were asked to score the collated lists through a second online survey. The top 10 ranked questions per thematic area (testing, treatment, and service delivery) were reviewed and priority themes developed with consideration of existing policy, systematic reviews, and planned, ongoing, and recently published research.

Results: A total of 375 respondents submitted 1735 priority research questions. The majority of respondents were from Africa; 55% self-identified as researchers. The final collated lists included 51 and 61 research questions for pediatric and adolescent HIV, respectively. The response rate for the second survey was 48%. The final research agendas include 5 priority research themes per area, discussed in 2 separate publications.

Conclusions: To date, this is the largest example of the Child Health and Nutrition Research Initiative method in pediatric and adolescent HIV in terms of stakeholders reached, and the first to incorporate top thematic areas based on current evidence. Its impact on improving outcomes for these populations will require strong political and financial commitment.

Publication types

• Research Support, Non-U.S. Gov't
• Adolescent Health*
• Child Health*
• Global Health*
• HIV Infections / prevention & control*
• Health Priorities*
• Nutritional Status
• Online Systems
• Research Design
• Surveys and Questionnaires

Grants and funding

• 001/WHO_/World Health Organization/International

Carbohydrates and Blood Sugar

When people eat a food containing carbohydrates, the digestive system breaks down the digestible ones into sugar, which enters the blood.

• As blood sugar levels rise, the pancreas produces insulin, a hormone that prompts cells to absorb blood sugar for energy or storage.
• As cells absorb blood sugar, levels in the bloodstream begin to fall.
• When this happens, the pancreas start making glucagon, a hormone that signals the liver to start releasing stored sugar.
• This interplay of insulin and glucagon ensure that cells throughout the body, and especially in the brain, have a steady supply of blood sugar.

Carbohydrate metabolism is important in the development of type 2 diabetes , which occurs when the body can’t make enough insulin or can’t properly use the insulin it makes.

• Type 2 diabetes usually develops gradually over a number of years, beginning when muscle and other cells stop responding to insulin. This condition, known as insulin resistance, causes blood sugar and insulin levels to stay high long after eating. Over time, the heavy demands made on the insulin-making cells wears them out, and insulin production eventually stops.

Glycemic index

In the past, carbohydrates were commonly classified as being either “simple” or “complex,” and described as follows:

Simple carbohydrates:

These carbohydrates are composed of sugars (such as fructose and glucose) which have simple chemical structures composed of only one sugar (monosaccharides) or two sugars (disaccharides). Simple carbohydrates are easily and quickly utilized for energy by the body because of their simple chemical structure, often leading to a faster rise in blood sugar and insulin secretion from the pancreas – which can have negative health effects.

Complex carbohydrates:

These carbohydrates have more complex chemical structures, with three or more sugars linked together (known as oligosaccharides and polysaccharides).  Many complex carbohydrate foods contain fiber, vitamins and minerals, and they take longer to digest – which means they have less of an immediate impact on blood sugar, causing it to rise more slowly. But other so called complex carbohydrate foods such as white bread and white potatoes contain mostly starch but little fiber or other beneficial nutrients.

Dividing carbohydrates into simple and complex, however, does not account for the effect of carbohydrates on blood sugar and chronic diseases. To explain how different kinds of carbohydrate-rich foods directly affect blood sugar, the glycemic index was developed and is considered a better way of categorizing carbohydrates, especially starchy foods.

The glycemic index ranks carbohydrates on a scale from 0 to 100 based on how quickly and how much they raise blood sugar levels after eating. Foods with a high glycemic index, like white bread, are rapidly digested and cause substantial fluctuations in blood sugar. Foods with a low glycemic index, like whole oats, are digested more slowly, prompting a more gradual rise in blood sugar.

• Low-glycemic foods have a rating of 55 or less, and foods rated 70-100 are considered high-glycemic foods. Medium-level foods have a glycemic index of 56-69.
• Eating many high-glycemic-index foods – which cause powerful spikes in blood sugar – can lead to an increased risk for type 2 diabetes, ( 2 ) heart disease, ( 3 ), ( 4 ) and overweight, ( 5 , 6 ) ( 7 ). There is also preliminary work linking high-glycemic diets to age-related macular degeneration, ( 8 ) ovulatory infertility, ( 9 ) and colorectal cancer. ( 10 )
• Foods with a low glycemic index have been shown to help control type 2 diabetes and improve weight loss.
• A 2014 review of studies researching carbohydrate quality and chronic disease risk showed that low-glycemic-index diets may offer anti-inflammatory benefits. ( 16 )
• The University of Sydney in Australia maintains a searchable database of foods and their corresponding glycemic indices.

Many factors can affect a food’s glycemic index, including the following:

• Processing : Grains that have been milled and refined—removing the bran and the germ—have a higher glycemic index than minimally processed whole grains.
• Physical form : Finely ground grain is more rapidly digested than coarsely ground grain. This is why eating whole grains in their “whole form” like brown rice or oats can be healthier than eating highly processed whole grain bread.
• Fiber content : High-fiber foods don’t contain as much digestible carbohydrate, so it slows the rate of digestion and causes a more gradual and lower rise in blood sugar. ( 17 )
• Ripeness : Ripe fruits and vegetables tend to have a higher glycemic index than un-ripened fruit.
• Fat content and acid content : Meals with fat or acid are converted more slowly into sugar.

Numerous epidemiologic studies have shown a positive association between higher dietary glycemic index and increased risk of type 2 diabetes and coronary heart disease. However, the relationship between glycemic index and body weight is less well studied and remains controversial.

Glycemic load

One thing that a food’s glycemic index does not tell us is how much digestible carbohydrate – the total amount of carbohydrates excluding  fiber – it delivers. That’s why researchers developed a related way to classify foods that takes into account both the amount of carbohydrate in the food in relation to its impact on blood sugar levels. This measure is called the glycemic load. ( 11 , 12 ) A food’s glycemic load is determined by multiplying its glycemic index by the amount of carbohydrate the food contains. In general, a glycemic load of 20 or more is high, 11 to 19 is medium, and 10 or under is low.

The glycemic load has been used to study whether or not high-glycemic load diets are associated with increased risks for type 2 diabetes risk and cardiac events. In a large meta-analysis of 24 prospective cohort studies, researchers concluded that people who consumed lower-glycemic load diets were at a lower risk of developing type 2 diabetes than those who ate a diet of higher-glycemic load foods. ( 13 ) A similar type of meta-analysis concluded that higher-glycemic load diets were also associated with an increased risk for coronary heart disease events. ( 14 )

Here is a listing of low, medium, and high glycemic load foods. For good health, choose foods that have a low or medium glycemic load, and limit foods that have a high glycemic load.

Low glycemic load (10 or under)

• Bran cereals
• Kidney beans
• Black beans
• Wheat tortilla

Medium glycemic load (11-19)

• Pearled barley: 1 cup cooked
• Brown rice: 3/4 cup cooked
• Oatmeal: 1 cup cooked
• Bulgur: 3/4 cup cooked
• Rice cakes: 3 cakes
• Whole grain breads: 1 slice
• Whole-grain pasta: 1 1/4 cup cooked

High glycemic load (20+)

• Baked potato
• French fries
• Refined breakfast cereal: 1 oz
• Sugar-sweetened beverages: 12 oz
• Candy bars: 1 2-oz bar or 3 mini bars
• Couscous: 1 cup cooked
• White basmati rice: 1 cup cooked
• White-flour pasta: 1 1/4 cup cooked ( 15 )

Here’s a list of the glycemic index and glycemic load for the most common foods.

2. de Munter JS, Hu FB, Spiegelman D, Franz M, van Dam RM. Whole grain, bran, and germ intake and risk of type 2 diabetes: a prospective cohort study and systematic review.  PLoS Med . 2007;4:e261.

3. Beulens JW, de Bruijne LM, Stolk RP, et al. High dietary glycemic load and glycemic index increase risk of cardiovascular disease among middle-aged women: a population-based follow-up study.  J Am Coll Cardiol . 2007;50:14-21.

4. Halton TL, Willett WC, Liu S, et al. Low-carbohydrate-diet score and the risk of coronary heart disease in women.  N Engl J Med . 2006;355:1991-2002.

5. Anderson JW, Randles KM, Kendall CW, Jenkins DJ. Carbohydrate and fiber recommendations for individuals with diabetes: a quantitative assessment and meta-analysis of the evidence.  J Am Coll Nutr . 2004;23:5-17.

6. Ebbeling CB, Leidig MM, Feldman HA, Lovesky MM, Ludwig DS. Effects of a low-glycemic load vs low-fat diet in obese young adults: a randomized trial.   JAMA . 2007;297:2092-102.

7. Maki KC, Rains TM, Kaden VN, Raneri KR, Davidson MH. Effects of a reduced-glycemic-load diet on body weight, body composition, and cardiovascular disease risk markers in overweight and obese adults.  Am J Clin Nutr . 2007;85:724-34.

8. Chiu CJ, Hubbard LD, Armstrong J, et al. Dietary glycemic index and carbohydrate in relation to early age-related macular degeneration.  Am J Clin Nutr . 2006;83:880-6.

9. Chavarro JE, Rich-Edwards JW, Rosner BA, Willett WC. A prospective study of dietary carbohydrate quantity and quality in relation to risk of ovulatory infertility.  Eur J Clin Nutr . 2009;63:78-86.

10. Higginbotham S, Zhang ZF, Lee IM, et al. Dietary glycemic load and risk of colorectal cancer in the Women’s Health Study.  J Natl Cancer Inst . 2004;96:229-33.

11. Liu S, Willett WC. Dietary glycemic load and atherothrombotic risk.  Curr Atheroscler Rep . 2002;4:454-61.

12. Willett W, Manson J, Liu S. Glycemic index, glycemic load, and risk of type 2 diabetes.  Am J Clin Nutr . 2002;76:274S-80S.

13. Livesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies.  Am J Clin Nutr . 2013;97:584-96.

14. Mirrahimi A, de Souza RJ, Chiavaroli L, et al. Associations of glycemic index and load with coronary heart disease events: a systematic review and meta-analysis of prospective cohorts.  J Am Heart Assoc . 2012;1:e000752.

15. Foster-Powell K, Holt SH, Brand-Miller JC. International table of glycemic index and glycemic load values: 2002.  Am J Clin Nutr . 2002;76:5-56.

16. Buyken, AE, Goletzke, J, Joslowski, G, Felbick, A, Cheng, G, Herder, C, Brand-Miller, JC. Association between carbohydrate quality and inflammatory markers: systematic review of observational and interventional studies. The American Journal of Clinical Nutrition Am J Clin Nutr . 99(4): 2014;813-33.

17. AlEssa H, Bupathiraju S, Malik V, Wedick N, Campos H, Rosner B, Willett W, Hu FB. Carbohydrate quality measured using multiple quality metrics is negatively associated with type 2 diabetes. Circulation . 2015; 1-31:A:20.

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The legacy of the Child Health and Nutrition Research Initiative (CHNRI).

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Journal of Global Health , 01 Jun 2016 , 6(1): 010101 https://doi.org/10.7189/jogh.06.010101   PMID: 26955468  PMCID: PMC4766789

Abstract 

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The legacy of the Child Health and Nutrition Research Initiative (CHNRI)

Under the Global Forum for Health Research, the Child Health and Nutrition Research Initiative (CHNRI) began its operations in 1999 and became a Swiss foundation in 2006. The vision of CHNRI was to improve child health and nutrition of all children in low– and middle–income countries (LMIC) through research that informs health policy and practice. Specific objectives included expanding global knowledge on childhood disease burden and cost–effectiveness of interventions, promoting priority setting in research, ensuring inclusion of institutions and scientists in LMIC in setting priorities, promoting capacity development in LMIC and stimulating donors and countries to increase resources for research. CHNRI created a knowledge network, funded research through multiple rounds of a global competitive process and published research papers and policy briefs. A signature effort was to develop a systematic methodology for prioritizing health and nutrition research investments. The “CHNRI method” has been extensively applied to global health problems and is now the most commonly used method for prioritizing health research questions.

In the early 1990s there was growing recognition that low– and middle–income countries (LMIC) continued to have longstanding threats from infectious diseases, malnutrition and maternal and perinatal conditions, but were also increasingly facing non–communicable diseases and injuries. Research was considered essential to address these diverse problems, but given limited resources and capacity it was thought that priorities must be set. In 1994 the World Health Organization named an Ad Hoc Committee on Health Research Relating to Future Investment Options. The report [ 1 ] issued by this Committee provided cogent arguments for better aligning research priorities with the global disease burden and building capacity for research, especially in LMIC. The report proposed a five step process to inform research and development resource allocation: 1) How big is the health problem?; 2)Why does the disease burden persist?; 3) Is enough known about the problem now to consider possible interventions?; 4) How cost–effective will these interventions be?; and 5) how much is already being done about the problem? These questions were usually asked broadly about a disease such as malaria or problem area such as emerging microbial threats. Others built upon that for research topics within these broad areas, but methods were not proposed to more systematically prioritize specific research questions. The call in this report for a focus on operational research to make existing interventions more efficient and responsive to the needs of households was largely unheard, possibly in part because the report itself named as “best buys” the development of new drugs, vaccines, tests and other technologies, rather than studies of how to enable health systems to deliver existing services more effectively and equitably.

As a follow–up to the Investing in Health Research and Development Report, The Global Forum for Health Research began as an international foundation headquartered in Geneva, Switzerland in 1997. Its aim was to increase the amount of research on global health issues. In its advocacy it pointed to the “10/90 gap”, identifying that only 10% of the world’s health research spending is targeted at 90% of global health problems. The Forum continued to promote the five step process to advocate for research and held international meetings on research. As part of its mandate, the Forum facilitated the creation of more specific research initiatives, one of which was the Child Health and Nutrition Research Initiative (CNHRI). Begun under the Forum in 1999, CHNRI became a Swiss foundation in 2006. The vision of CHNRI was to improve child health and nutrition of all children in LMIC through research that informs health policy and practice. Specific objectives included expanding global knowledge on childhood disease burden and cost–effectiveness of interventions, promoting priority setting in research, ensuring inclusion of institutions and scientists in LMIC in setting priorities, promoting capacity development in LMIC and stimulating donors and countries to increase resources for research. With an international foundation Board and a Secretariat, based sequentially in Geneva, Dhaka and New Delhi, CHNRI played an active role in Global Forum annual conferences, created a knowledge network, funded research through multiple rounds of a global competitive process and published research papers and policy briefs.

A signature effort of CHNRI was to develop a systematic methodology for prioritizing health and nutrition research investments. This method included asking a wide selection of stakeholders and experts for specific research questions addressing a topic area. These questions were then curated and scored for priority using criteria such as the question’s answerability and the resulting intervention’s effectiveness, impact on disease, contribution to equity and deliverability. The “CHNRI method” has been extensively applied to global health problems and is now the most commonly used method for prioritizing health research questions [ 2 , 3 ].

In the 15 years that CHNRI operated before the foundation was dissolved in 2015, there have been substantial increases in child health and nutrition research and more reliance on sound evidence for policy and programs. The capacity for research in LMIC has improved; much more capacity building is needed, especially because research funding for global problems has improved. There has been much greater use of systematic and transparent methods involving multiple stakeholders in prioritizing and focusing research funding. The CHNRI method may be a lasting legacy of the foundation and the efforts of its Board, Secretariat and many contributors.

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Setting global research priorities for private sector child health service delivery: Results from a CHNRI exercise.

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The Crisis in youth mental health: what can be done?

The Briefing

Youth populations worldwide are experiencing a mental health crisis. The 2024 World Happiness report (WHR24) found a steep decline in the mental wellbeing of youth. Findings from New Zealand-specific research paint a similar picture. 

Significant factors impacting young people’s mental health and wellbeing include the effect of child poverty, stress, perceptions of the future as bleak, experiences of racism and discrimination, the influence of social media and digital technology, and a lack of intergenerational connection. Importantly, these are issues that will not be addressed quickly or simply. As such, we recommend a focus on positioning mental health based programs and policies as long-term cross-party initiatives. Meaningful actions which tangibly address the sources of declining wellbeing are essential for long-term change. Therefore, we recommend prioritising interventions that target sources of distress, such as those that reduce the financial burden on young adults. We also recommend commitment to training and supporting more youth-friendly clinicians, and ensuring that youth-informed community and mental health services are sufficiently funded to meet population needs. 

What does the latest research say?

Worsening mental health among young people is a significant public health problem across the world. The 2024 World Happiness report (WHR24) has revealed a steep drop in the mental wellbeing of young people. Happiness levels have fallen significantly in the United States, Canada, Australia and New Zealand, by twice as much for the young as for older people. 1 

In New Zealand, poor mental health among youth is consistently inequitable, and growing. 2 In 2020, a Koi Tū commentary piece called for urgent action based on findings of rapidly rising rates of youth depression, with 23% of students (year 7-13) in the 2019 Youth19 survey reporting symptoms of depression - almost doubling from the rate in 2012. 3 Reported psychological distress among young people has also increased dramatically ( see figure). While suicide is a rare outcome, Aotearoa’s national teenage suicide rate has consistently been among the highest in the OECD in recent years. 4

There is strong evidence of socioeconomic inequity in youth mental health, with rates of attempted suicide doubling between each deprivation classification: low (2.7%), medium (6%) and high (11%). 5 Additionally, rangatahi Māori report higher rates of depressive symptoms - for example, 38% for Māori female youths compared to 24% for their Pākehā counterpart. 5

Why is this happening?

The reasons for this decline are multifactorial. A 2023 Koi Tū literature review explored four factors consistently reported by New Zealand youth: perceptions of their future as bleak; experiences of racism and discrimination; the influence of social media and digital technology; and inter-generational connection. 6 Other New Zealand research has identified factors like nutrition 7 , the environment a young person lives in 8,9 , and the effect of child poverty. 10

What can we learn from this research in Aotearoa?

Mental health as public health

While treatment by the clinical health system plays an important role in addressing mental health challenges, and we need to address the severe underfunding of the health sector if we are to meet this need 10,11 , we also need a public health approach focused on prevention.

Preventing the decline of young people’s wellbeing requires us to address the issues that cause distress for youth, including child poverty 10 , discrimination, stress, and lack of connection. Even more importantly there are no silver bullets - we cannot address one issue and expect significant change to wellbeing at a population level. 

The incidence of mental health conditions among children and adolescents can be reduced by addressing severe and persistent poverty, especially during the early years of a child’s life. 10 Interventions that address poverty and the effects of poverty on children are likely to break intergenerational cycles of poor mental health 10 , and there are clear recommendations available for what these would look like. 12 These interventions conceptualise child poverty as multi-factorial - requiring action across domains like economic policy, housing, employment, education, health, and justice. 12 Child poverty has been acknowledged as a pressing issue by successive governments, yet actions have often remained partisan. Cross-party action must be a priority, and has the potential to create tangible and sustainable change to mental health and wellbeing. 13  

The power of youth voice

Youth input in policy and health system decision-making is essential to meet the mental health needs of young people. The Global Mental Health Action Network’s (GMHAN) guidelines for Effective Youth Engagement Practices noted evidence of a strong bidirectional relationship between young people’s wellbeing and their meaningful participation in the decisions that affect them. 14 The GMHAN’s Child and Youth Working Group recognised youth engagement as a policy priority for the mental health sector. The Group also recommended a multi-sectoral approach: for example, the mental health sector can work with teachers to engage young people in developing mental health education as part of school curricula. 15

Examples of effectively engaging youth in the co-design of interventions are available around the world: for example, Singapore’s national digital mental health programme, mindline.sg ( see appendix for an overview ).

In New Zealand, ‘ Youth One Stop Shops’ v operate as community-based centres providing free or low-cost primary healthcare, mental health, and social development services to young people. Despite evidence of therapeutic benefits 16 , the One Stop Shops are sparsely located across Aotearoa, likely due to funding restraints and a lack of government support. 17 Yet, the One Stop Shop model has the potential to closely align with what young New Zealanders ask for in mental health care - holistic, accessible spaces based in our communities with the flexibility to meet young people’s needs. 18 International and local evidence offers us clear examples of how we can listen to young people’s voices in designing services, and the potential value of this approach.

Actions that could be taken to address the crisis in youth mental health are:

• An all of government response that allows for more cross-agency collaboration. 19
• Cross-party commitments to sustainable action. 20
• Taking action on issues young people ask for, such as - stronger action on climate change, reducing the financial burden on young adults, education on digital literacy, more youth-friendly trained clinicians, and youth-informed mental health services that are funded to meet the needs of the population. 21

What this Briefing adds

• New evidence shows that youth mental health is on the decline in New Zealand, and across the Western world.
• Existing interventions are severely underfunded and are susceptible to government changes, stalling prevention efforts.

Implications for policy and practice

• To ensure sustainable action, public mental health approaches must be implemented with multi-sector and inter-agency collaboration.
• We need more youth input in the designing of mental health interventions, and more action on the socioeconomic issues that are putting pressure on young people.

Author details

Ronan Payinda , Chair, Public Health Association of New Zealand Youth Caucus, and Medical Student, University of Auckland. 

Dr Jessica Stubbing , R esearch fellow, Koi Tū: The Centre for Informed Futures, University of Auckland

Appendix: Singapore case study

In 2022, Singapore’s Ministry of Health launched a national digital mental health programme, mindline.sg . A ground-up youth co-design project, its first Youth Advisory Group was founded to conduct research, generate ideas and co-create solutions to address systemic gaps in mental health support locally. 15 In-depth interviews with young people from diverse demographics, previous experiences of mental health conditions and services, and current life stage informed a service that was generally perceived as usable and acceptable by individuals with a diagnosed mental disorder in Singapore. 22 Visited by 80,000 users in its first year 23 , evidence suggests that policymakers and mental healthcare service providers may be able to use mindline.sg data trends to project demand for mental health services and increase resourcing to cope with anticipated increases in needs. 24

• World Happiness Report (2024). https://worldhappiness.report/  
• Menzies R, Gluckman P, Poulton R (2020). Youth mental health in Aotearoa New Zealand: Greater urgency required. Koi Tū: Centre for Informed Futures Report. https://informedfutures.org/youth-mental-health-in-aotearoa-nz/
• Youth19 (2020). Youth19 Rangatahi Smart Survey. https://www.youth19.ac.nz/publications/2020/8/24/youth19-rangatahi-smart-survey-webinar-initial-findings
• OECD (2017). Teenage suicides (15-19 years old). OECD Family Database.  http://www.oecd.org/els/family/CO_4_4_Teenage-Suicide.pdf
• Menzies R, Gluckman P, Poulton R (2020). Youth mental health in Aotearoa New Zealand: Greater urgency required. Koi Tū: The Centre for Informed Futures Commentary. https://informedfutures.org/youth-mental-health-in-aotearoa-nz/
• Stubbing J, Simon-Kumar N, Gluckman P (2023). A summary of literature reflecting the perspectives of young people in Aotearoa on systemic factors affecting their wellbeing. Koi Tū: The Centre for Informed Futures Evidence Summary. https://www.mhwc.govt.nz/news-and-resources/youth-wellbeing-insights/attachment/330/
• Rucklidge JJ, Johnstone JM, Kaplan BJ (2021). Nutrition provides the essential foundation for optimizing mental health . Evidence-Based Practice in Child and Adolescent Mental Health , 6(1):131-54. https://www.tandfonline.com/doi/full/10.1080/23794925.2021.1875342
• Hobbs M, Bowden N, Marek L, Wiki J, Kokaua J, Theodore R, Ruhe T, Boden J, Thabrew H, Hetrick S, Milne B. (2023). The environment a young person grows up in is associated with their mental health: A nationwide geospatial study using the integrated data infrastructure, New Zealand. Social Science & Medicine . 1;326:115893. https://linkinghub.elsevier.com/retrieve/pii/S0277-9536(23)00250-2
• Youthline (2020). Youthline COVID-19 Research (Archived). https://web.archive.org/web/20230129075700/https://www.youthline.co.nz/uploads/2/9/8/1/29818351/youthline_covid-19_research.final.pdf
• Gibson K, Abraham Q, Asher I, Black R, Turner N, Waitoki W, McMillan N (2017). Child poverty and mental health: A literature review (Commissioned for New Zealand Psychological Society and Child Poverty Action Group). https://www.cpag.org.nz/publications/17051620cpagchildpovertyandmentalhealthreport-cs6webpdf .
• RNZ (2023). The ‘rolling crisis’ in youth mental health that leaves thousands waiting weeks for help (14 Dec 2023).  https://www.rnz.co.nz/programmes/in-depth-special-projects/story/2018919377/the-rolling-crisis-in-youth-mental-health-that-leaves-thousands-waiting-weeks-for-help  
• Children’s Commissioner (2012). Summary of Solutions to Child Poverty in New Zealand.  https://www.manamokopuna.org.nz/documents/109/Summary-of-proposed-solutions-to-child-poverty.pdf
• Children’s Commissioner (2018). Release: Children’s Commissioner commends cross-party support for Child Poverty Reduction Bill (4 Oct 2018). https://www.manamokopuna.org.nz/publications/media-releases/childrens-commissioner-commends-cross-party-support-for-child-poverty-reduction-bill/
• UNICEF (2022). ‘Young people’s participation and mental health’. https://www.unicef.org/reports/young-peoples-participation-and-mental-health
• Global Mental Health Action Network (2023). ‘Guiding Principles and Recommendations for Effective Lived Experience Youth Engagement Practices’. GMHAN Child and Youth Working Group. https://www.mhinnovation.net/resources/collaborative-resource-guiding-principles-and-recommendations-effective-lived-experience
• Hetrick SE, Bailey AP, Smith KE, Malla A, Mathias S, Singh SP, O'Reilly A, Verma SK, Benoit L, Fleming TM, Moro MR, Rickwood DJ, Duffy J, Eriksen T, Illback R, Fisher CA, McGorry PD (2017). Integrated (one-stop shop) youth health care: best available evidence and future directions. Med J Aust . 207(10):S5-S18. https://doi.org/10.5694/mja17.00694
• Haycock IG (2024). Is the mental health system in Aotearoa New Zealand providing quality care to young people? A critical analysis utilising the perspectives of mental health professionals and sociological insights (Doctoral dissertation, The University of Waikato). https://hdl.handle.net/10289/16466
• Cross-party Mental Health and Addiction Wellbeing Group (2023). Under One Umbrella: Integrated mental health, alcohol and other drug use care for young people in New Zealand. https://www.platform.org.nz/assets/WorkDetail/Cross-Party-Report-Under-One-Umbrella-MHAC-Web-Accessible-FINALv.pdf
• Chuang E, Lucio R (2011). Interagency collaboration between child welfare agencies, schools, and mental health providers and children's mental health service receipt. Advances in School Mental Health Promotion . 4(2):4-15. https://www.tandfonline.com/doi/abs/10.1080/1754730X.2011.9715625
• Clark H, Royal P, Robillard Webb L, Doughty B, Howells K, Kamaldeep B, Pinfold V, Hodgson A, Purvey C, Lowe D, Godfrey K (2023). The Major Conditions Strategy: A 10-year Failure for Mental Health: A Report by the All-Party Parliamentary Group on a Fit and Healthy Childhood. https://www.mqmentalhealth.org/wp-content/uploads/APPG-Report-10-year-failure-for-Mental-Health.pdf
• Muir K, Powell A, McDermott S (2012). ‘They don’t treat you like a virus’: youth‐friendly lessons from the Australian National Youth Mental Health Foundation. Health & social care in the community . 20(2):181-9. https://onlinelibrary.wiley.com/doi/10.1111/j.1365-2524.2011.01029.x
• Phang YS, Heaukulani C, Martanto W, Morris R, Tong MM, Ho R (2023). Perceptions of a Digital Mental Health Platform Among Participants With Depressive Disorder, Anxiety Disorder, and Other Clinically Diagnosed Mental Disorders in Singapore: Usability and Acceptability Study. JMIR Human Factors . 10:e42167. https://humanfactors.jmir.org/2023/1/e42167
• Heaukulani C, Phang YS, Weng JH, Lee J, Morris RJ (2024). Deploying AI Methods for Mental Health in Singapore: From Mental Wellness to Serious Mental Health Conditions. Proceedings of Machine Learning for Cognitive and Mental Health Workshop (Feb 26 2024) Paper 13. https://ceur-ws.org/Vol-3649/Paper13.pdf
• Othman NA, Panchapakesan C, Zhang M, Loh S, Gupta R, Martanto W, Phang YS, Morris R, Loke WC, Tan KB (2023), Subramaniam M. Predicting public mental health needs in a crisis using situational indicators and social media emotions: A Singapore big data study. Research Square preprint.  https://doi.org/10.21203/rs.3.rs-2813440/v1

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Setting Priorities in Global Child Health Research Investments: Guidelines for Implementation of the CHNRI Method

* These authors contributed equally to this work.

1 Croatian Center for Global Health, University of Split School of Medicine, Split, Croatia

2 Department of Public Health Sciences, University of Edinburgh Medical School, Scotland, UK

Jennifer L. Gibson

3 Joint Centre for Bioethics, University of Toronto, Toronto, Canada

Shanthi Ameratunga

4 School of Population Health, University of Auckland, Auckland, New Zealand

Shams El Arifeen

5 Child Health Unit, Centre for Health and Population Research, Dhaka, Bangladesh

Zulfiqar A. Bhutta

6 Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan

Maureen Black

7 Department of Pediatrics, University of Maryland, Baltimore, Md, USA

Robert E. Black

8 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md, USA

Kenneth H. Brown

9 Program in International and Community Nutrition, University of California, Davis, Calif, USA

Harry Campbell

Ilona carneiro.

10 London School of Hygiene and Tropical Medicine, London, UK

Kit Yee Chan

11 Nossal Institute for Global Health, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Australia

Daniel Chandramohan

Mickey chopra.

12 Health Systems Research Unit, Medical Research Council, Cape Town, South Africa

Simon Cousens

Gary l. darmstadt, julie meeks gardner.

13 Caribbean Child Development Centre, University of West Indies, Mona, Jamaica

Sonja Y. Hess

Adnan a. hyder, lydia kapiriri, margaret kosek, claudio f. lanata.

14 Nutrition Research Institute, Lima, Peru

Mary Ann Lansang

15 University of the Philippines College of Medicine, Manila, Philippines

16 Saving Newborn Lives/Save the Children-US, Cape Town, South Africa

Mark Tomlinson

Alexander c. tsai.

17 Langley Porter Psychiatric Institute, University of California, San Francisco, Calif, USA

Jayne Webster

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

This article provides detailed guidelines for the implementation of systematic method for setting priorities in health research investments that was recently developed by Child Health and Nutrition Research Initiative (CHNRI). The target audience for the proposed method are international agencies, large research funding donors, and national governments and policy-makers. The process has the following steps: (i) selecting the managers of the process; (ii) specifying the context and risk management preferences; (iii) discussing criteria for setting health research priorities; (iv) choosing a limited set of the most useful and important criteria; (v) developing means to assess the likelihood that proposed health research options will satisfy the selected criteria; (vi) systematic listing of a large number of proposed health research options; (vii) pre-scoring check of all competing health research options; (viii) scoring of health research options using the chosen set of criteria; (ix) calculating intermediate scores for each health research option; (x) obtaining further input from the stakeholders; (xi) adjusting intermediate scores taking into account the values of stakeholders; (xii) calculating overall priority scores and assigning ranks; (xiii) performing an analysis of agreement between the scorers; (xiv) linking computed research priority scores with investment decisions; (xv) feedback and revision. The CHNRI method is a flexible process that enables prioritizing health research investments at any level: institutional, regional, national, international, or global.

Proposals for health research funding are far exceeding available resources. Increasingly, there is a need to set priorities in health research investments in a fair, transparent, and systematic way. In 2005, Child Health and Nutrition Research Initiative (CHNRI, www.chnri.org ), an initiative of the Global Forum for Health Research, launched a project to develop a systematic method for setting priorities in health research investments and to apply it to global child health ( 1 ). This effort was motivated by a notion that current research investment prioritization approaches suffer from many shortcomings which may partly be responsible for persisting high levels of mortality in children globally ( 2 - 4 ). The target audience for the proposed method are international agencies, large research funding donors, and national governments and policy-makers. The CHNRI method is a flexible process that enables prioritizing health research investments at any level: institutional, regional, national, international, or global.

Selecting managers of the process

CHNRI method is a process managed by a relatively small team of persons. This team needs to appropriately represent investors in health research, their interests, and visions. Like any other investing, health research funding is associated with possible gains and profits, but also risks and losses. The key concept of CHNRI’s methodology is that all health research should have a common ultimate goal, which is to reduce existing burden of disease and disability and improve health. Future reductions in the existing disease burden that will result from supported health research are considered “profits.” However, because of many uncertainties inherent to health research, many investments will never sufficiently contribute to reduction in disease burden to justify the investments.

The purpose of the CHNRI priority setting method is to inform the investors in health research about the risks associated with their investments. Each research investment option needs to be judged according to a set of criteria. Those criteria will assess likelihood that proposed research option could realistically contribute to disease burden reduction within the context in which investments are taking place ( 4 ).

Specifying context and risk management preferences

Priority setting in health research investments is not an abstract, theoretical exercise with a single possible correct outcome, such as a mathematical problem. It is a process that occurs within complex circumstances of the real world. The decisions will, therefore, strongly depend on the context in which the process takes place and on risk preferences of the investors.

At this point, a small group of process managers (who represent the investors) needs to specify the context and their risk preferences. The context is specified by thoroughly discussing and carefully defining the following: (i) context in space; (ii) disease, disability, and death burden; (iii) context in time; (iv) stakeholders; and (v) risk management preferences. Box 1 provides guidelines on how this should be done.

Box 1Guidelines on defining the context in which research priorities will be set

(i) Context in space: What is the population in which the investments in health research should contribute to disease burden reduction and improved health? (eg, all developing countries/all children under 5 years of age/people exposed to a specific risk factor);

(ii) Disease, disability, and death burden: What is known about the burden of disease, disability, and death that will be addressed by supported health research? Can it be measured and quantified (eg, in disability-adjusted life years – DALYs – or in some other way)?

(iii) Context in time: In how many years are the first results expected (in terms of reaching the endpoints of health research, translating and implementing them, which is then expected to achieve detectable disease burden reduction)?

(iv) Stakeholders: Who are the main groups in the society whose values and interests should be respected in setting health research investment priorities?

(v) Risk management preferences: What will be investment strategy in health research with respect to risk preferences? Will all the funding support a single (or a few) expensive high-risk high-profit research options (eg, vaccine development), or will the risk be balanced and diversified between many research options which will have different levels of “risks” and “profits” associated with them?

Discussing criteria for setting health research priorities

There is a large number of nearly independent criteria that can be used to discriminate between any two competing “health research investment options,” giving one of them preference over the other. The central challenge is that the decisions on investment priorities based on different criteria will necessarily conflict each other. This means that, when choosing between any two proposed research options, some criteria will give preference to one of them, while other will prefer the other.

At this point, managers of the priority setting process should try to list possible criteria appropriate to their specific context. Box 2 provides a list of criteria that can serve as an example and starting point. There is no real limit to a number of priority setting criteria that may seem appropriate to different contexts. However, with inclusion of more criteria to the list, they will begin to overlap with the already listed ones, so their potential usefulness as independent criteria will soon begin to decrease.

Box 2Examples of the possible criteria which can be used for setting priorities in health research investments

• Answerability? (some health research options will be more likely to be answerable than the others)

• Attractiveness? (some health research options will be more likely to lead to publications in high-impact journals)

• Novelty? (some health research options will be more likely to generate truly novel and non-existing knowledge)

• Potential for translation? (some health research options will be more likely to generate knowledge that will be translated into health intervention)

• Effectiveness? (some health research options will be more likely to generate/improve truly effective health interventions)

• Affordability? (the translation or implementation of knowledge generated through some health research options will not be affordable within the context)

• Deliverability? (some health research options will lead to/impact health interventions that will not be deliverable within the context)

• Sustainability? (some health research options will lead to/impact health interventions that will not be sustainable within the context)

• Public opinion? (some health research options will seem more justified and acceptable to general public than the others)

• Ethical aspects? (some health research options will be more likely to raise ethical concerns than the others)

• Maximum potential impact on burden? (some health research options will have a theoretical potential to reduce much larger portions of the existing disease burden than the others)

• Equity? (some health research options will lead to health interventions that will only be accessible to the privileged in the society/context, thus increasing inequity)

• Community involvement? (some health research options will have more additional positive side-effects through community involvement)

• Cost and feasibility? (all other criteria being equal, some research options will still require more funding than the others and thus be less feasible investments)

• Likelihood of generating patents/lucrative products? (some research options will have greater likelihood of generating patents or other potentially lucrative products, thus promising greater financial return on investments, regardless of their impact on disease burden)

Choosing limited set of most useful and important criteria

In this step, managers of priority setting process need to select a set of priority setting criteria from the longer list that should be sufficiently informative to discriminate between the competing research options. Figure 1 shows an example of how this can be done. Competing research options are expected to initially generate new knowledge, which then needs to be translated into health intervention. This translation may either lead to improvement of an existing intervention, or development of a new one. The implementation of that intervention will eventually reduce disease burden, which is the ultimate aim of any health research investment ( Figure 1 ).

A simple framework developed by Child Health and Nutrition Research Initiative, which identifies some of the apparent criteria that can be used for setting priorities between the proposed health research options.

The criteria that assess the likelihood of the progress through this simple framework are: (i) answerability, (ii) effectiveness, (iii) deliverability, (iv) maximum potential for disease burden reduction, and (v) the effect on equity. CHNRI recommends these five criteria to be used in almost all contexts. Some of them may even be merged – eg, “effectiveness” and “deliverability” criteria could be merged in some contexts into a more general criterion called “usefulness.” Also, “maximum potential for disease burden reduction” and “effect on equity” criteria can be merged into a more general criterion called “impact.”

Additional criteria (those shown in Box 2 , or any other useful criteria) may be added to these ones suggested here, if the management team decides that they are important within their context. It is entirely up to the team of process managers to decide on the final list of criteria that will be useful for their particular exercise in priority setting in health research investments. Examples on how this was achieved in practice can be found in some published examples of implementation ( 5 , 6 )

Developing means to assess the likelihood that proposed health research options will satisfy selected criteria

After the managers selected the criteria, they should invite a group of technical experts. The experts should take the process through the next three steps (listing, checking, and scoring research options), working closely with the management team.

The first task for technical experts is to develop a set of three simple questions that will address each of the selected criteria. These questions should jointly help to assess the likelihood that proposed research options will satisfy the selected criteria. It is recommended that the questions should be simple, sufficiently informative, easily understandable, and answerable simply as “yes” or “no.” Box 3 shows an example of how the questions were developed in some of the conducted exercises to address the set of 5 criteria: answerability, effectiveness, deliverability, maximum potential for disease burden reduction, and the effect on equity ( 5 , 6 ).

Box 3Example of yes/no questions that can be used to assess likelihood whether proposed health research options satisfy the chosen priority-setting criteria

CRITERION 1: ANSWERABILITY

1. Would you say the research question is well framed and endpoints are well defined?

2. Based on: (i) the level of existing research capacity in proposed research and (ii) the size of the gap from current level of knowledge to the proposed endpoints; would you say that a study can be designed to answer the research question and to reach the proposed endpoints of the research?

3. Do you think that a study needed to answer the proposed research question would obtain ethical approval without major concerns?

CRITERION 2: EFFECTIVENESS

1. Based on the best existing evidence and knowledge, would the intervention which would be developed/improved through proposed research be efficacious?

2. Based on the best existing evidence and knowledge, would the intervention which would be developed/improved through proposed research be effective?

3. If the answers to either of the previous two questions are positive, would you say that the evidence upon which these opinions are based is of high quality?

CRITERION 3: DELIVERABILITY

1. Taking into account the level of difficulty with intervention delivery from the perspective of the intervention itself (eg, design, standardizability, safety), the infrastructure required (eg, human resources, health facilities, communication and transport infrastructure) and users of the intervention (eg, need for change of attitudes or beliefs, supervision, existing demand), would you say that the endpoints of the research would be deliverable within the context of interest?

2. Taking into account the resources available to implement the intervention, would you say that the endpoints of the research would be affordable within the context of interest?

3. Taking into account government capacity and partnership requirements (eg, adequacy of government regulation, monitoring and enforcement; governmental intersectoral coordination, partnership with civil society and external donor agencies; favorable political climate to achieve high coverage), would you say that the endpoints of the research would be sustainable within the context of interest?

CRITERION 4: MAXIMUM POTENTIAL FOR DISEASE BURDEN REDUCTION

1. Taking into account the results of conducted intervention trials or for the new interventions the proportion of avertable burden under an ideal scenario, would you say that the successful reaching of research endpoints would have a capacity to remove 5% of disease burden or more?

2. To remove 10% of disease burden or more?

3. To remove 15% of disease burden or more?

CRITERION 5: EFFECT ON EQUITY

1. Would you say that the present distribution of the disease burden affects mainly the underprivileged in the population?

2. Would you say that the underprivileged would be the most likely to benefit from the results of the proposed research after its implementation?

3. Would you say that the proposed research has the overall potential to improve equity in disease burden distribution in the long term (eg, 10 years)?

Systematic listing of large number of proposed health research options

Research priorities will usually be set under two types of circumstances. In the first scenario, a funding agency/government will aim to distribute its annual budget in the most rational way, without having already received any specific funding proposals. It will need to define its funding priorities and launch the calls for research proposals, while deciding in advance how much funding will be made available for each call.

In the second scenario, an existing source of funding (such as a donor agency or a national ministry) will receive demands for research support from many research groups. The sum of their demands will greatly exceed the available funds.

In both scenarios, it is useful to systematically list (or categorize) all the competing research options. In the first scenario, this systematic list will ensure that all apparent research options are given a fair chance to compete against each other. In the second scenario, the systematic categorization will expose avenues of research in which there is fierce competition and those in which there seems to be no research capacity or research interest.

The number of possible health research options is endless and limited only by imagination of all living researchers. Theoretical framework that enables systematic listing of such an endless spectrum of options is rather complex ( 1 , 4 ). However, the CHNRI methodology developed a process of systematic listing of all competing research options that respects that theoretical framework, but is also practical and intuitive. In both scenarios, the way we propose that all competing health research options should be listed (or categorized, if they have already been proposed for funding) is shown in a Table 1 .

Framework developed by Child Health and Nutrition Research Initiative that enables systematic listing of a very large number of proposed research options and research questions.

There is different “depth” of health research. The most fundamental categorization of all health research is shown in the first column, which we call “research domains.” There are three main domains: (i) health research to assess burden of health problem (disease) and its determinants; (ii) health research to improve performance of existing capacities to reduce the burden; and (iii) health research to develop new capacities to reduce the burden. All imaginable health research options should fall under one of those “domains.”

The next level of “depth” are broad “research avenues,” shown in the second column. Within each of those avenues, large number of “research options” can be envisaged (the third column). In practice, prioritization in health research investments will usually be made between the competing “research options,” as they correspond to 3-5-year research projects. That is a concept that both investors and researchers are familiar with and the level at which investment prioritization is already taking place (competition for research grants).

Finally, there is an even more specific level of “depth” of health research, which we call “research questions.” Each “research option” will propose to answer a number of “research questions.” These are very specific lines of research that correspond to a title of a single research article, which is another concept the researchers are familiar with.

In some instances, eg, when the process is conducted as a mainly theoretical exercise to identify the most important specific questions that should be investigated within a given context, the prioritization using CHNRI methodology can be performed between the competing research questions.

Table 1 is an example of how research options (or questions) should be categorized before they are scored against the relevant criteria in order to be prioritized for investments. It should also be stressed that this step is not really necessary to identify priorities and can even be skipped, but it has an advantage of ensuring that the process is systematic, that it gives a fair chance to all types of health research, and that it exposes areas of fierce competitiveness and also of low interest and capacity.

Pre-scoring check of all competing health research options

Once that all competing research options have been systematically listed, technical experts should read them all again very carefully before the scoring. The experts need to ensure that scoring of all proposed research options against all proposed criteria should be possible. If problems are envisaged, research options should be reworded to enable their structured scoring by the experts.

The easiest way to do this is by keeping in mind the simple framework shown in Figure 1 . The research options (or questions) must always suggest what is the new knowledge that they intend to generate. Also, it should be possible to envisage an uninterrupted link between this knowledge and its proposed effect on disease burden reduction through translation and implementation.

Scoring of health research options using the chosen set of criteria

At this stage, technical experts are expected to use their knowledge and experience to systematically score research options against the criteria chosen by process managers. The more experts agree to participate in the scoring, the more reliable is the outcome of the process. The experts should score all research options independently of each other. Each technical expert scores each research option by answering three questions per each criterion about that particular option. The answers to each question are simply:

– “I agree” (1 point), or

– “I disagree” (0 points).

There will be cases in which technical experts will not feel informed enough to answer some questions. In all such cases, they should leave those answers blank (no answer). Furthermore, when technical experts are sufficiently informed to answer the question, but can neither agree nor disagree, they are allowed to enter a score of 0.5 (half a point). In this way, such choice is distinguished from “no answer.”

When finished with scoring, each technical expert should submit his/her own scores to the process management team independently from other experts. This will ensure that the overall scores represent a measure of their collective optimism toward each of the scored research options.

Calculating intermediate scores for each health research option

Each research option will first achieve its intermediate scores. The number of intermediate scores equals the number of selected criteria, as each intermediate score informs process managers on likelihood that the research option would satisfy a specific criterion (eg, answerability, effectiveness, equity, etc.). Once all the scores from all technical experts are submitted to process managers, intermediate scores for each criterion can be easily computed. Table 2 presents how this should be done. In this simple example, 12 competing research options (options 1-12) are being scored, only one criterion is used (criterion 1), research options are assessed by three scoring technical experts (TE1-3) based on three related questions (question 1-3). In reality, there will be more research options, criteria, and scoring technical experts, but all the principles of calculating the intermediate scores will remain exactly the same as shown in Table 2 .

An example of scoring of 12 hypothetical proposed research options by 3 technical experts (TE1-TE3) using a single criterion and computation or intermediate score for that criterion.

The intermediate scores are computed by adding up all the informed (ie, non-blank) answers (“1,” “0,” or “0.5”). The achieved sum is then divided by the number of received informed answers. Blanks are left out of the calculation in both numerator and denominator. All intermediate scores for all research options will, therefore, be assigned a value between 0 and 100%. In this way, the methodology deals with missing answers because it should not be expected that all technical experts would be sufficiently informed on each possible research option to score it against each possible criterion.

In the hypothetical case shown in Table 2 , the values for intermediate score 1 (for criterion 1) ranged from 31% (option 11) to 78% (option 4). These figures now represent a measure of collective optimism among technical experts toward the likelihood that each of the proposed research options would satisfy the priority-setting criterion 1. They can now be prioritized and ranked according to this criterion based on the scores they received. Some of the expected advantages of this approach in comparison with other priority-setting methodologies are its transparency, limitation of personal biases through a structured survey, a systematic process with very specific outcomes and intuitive quantitative scores ( 3 , 4 ). The concerns over subjectivity of this approach are discussed in the concluding paragraph, where possible biases and limitations of the methodology are addressed.

Obtaining further input from stakeholders

One of the biggest challenges in prioritizing health research investments is involving relevant stakeholders and the wider community in the process ( 7 ). The term “stakeholders” refers to all individuals and/or groups who have interest in prioritization of health research investments. Stakeholders will therefore comprise a large and very heterogeneous group. Examples of stakeholders include research funding agencies (eg, governmental agencies, private organizations, public-private partnerships, international and regional organizations, taxpayers of a certain region), direct recipients of the funding (eg, researchers and research institutions), users of the research (eg, policy makers, industry, or the general population of a country), and any other group with interest in prioritization process (eg, advocacy groups, journalists and media, lawyers, economists, experts in ethics, and many others). To ensure legitimacy and fairness of priority setting decisions in health research investments, involvement of a wide range of stakeholders is recommended.

Stakeholders from the wider community are usually not included in the process because they lack sufficient technical expertise. The CHNRI methodology developed a strategy of involving the stakeholders in the process regardless of their technical expertise. This can be done by modifying intermediate scores (which are entirely based on the structured input from technical experts) according to the stakeholders’ system of values. In this way, the final research priority score for each research option will contain the input from both technical experts and the stakeholders. Although the stakeholders do not have enough technical expertise to score research options according to chosen priority-setting criteria, they can still score the chosen criteria. This is expected to reveal how much each criterion matters to them relative to the others. In this way, the wider group of stakeholders may still substantially influence the final outcome of the process. The stakeholders can: (i) define minimal score (threshold) for each intermediate score (criterion) that needs to be achieved to consider any research option a funding priority; and (ii) allocate different weights to intermediate scores, so that the overall score is not a simple arithmetic mean of the intermediate scores, but rather the weighted mean that reflects relative values assigned to each criterion by the stakeholders.

Thresholds will prevent investments in research options that dramatically fail any of the criteria to which stakeholders are particularly sensitive, regardless how well these research options were scored against other criteria. Weights will ensure that some intermediate scores, which relate to priority setting criteria that are seen as more important, would influence the value of the final score more than the others. Values for thresholds and weights can be obtained through a simple survey conducted among the appropriate group of representatives of the stakeholders (“larger reference group”). Table 3 shows an example. Further details are available in the article by Kapiriri et al ( 8 ).

An example of a simple questionnaire that can be used to survey different stakeholders and obtain their input into the Child Health and Nutrition Research Initiative process

Adjusting intermediate scores taking into account the values of stakeholders

The managers of the process need to compute average thresholds and weights for each criterion based on the suggestions obtained from the survey in a larger reference group of stakeholders. They need to check if all intermediate scores for all research options pass all the suggested thresholds. Research options that fail to pass all the thresholds should be disqualified at this stage and not considered funding priorities.

Then, every intermediate score received by each research option should be multiplied by the average weight (amount of assigned US$) suggested by the larger reference group of stakeholders. The products represent “weighted intermediate scores.” These scores will be used to compute an overall score (see next step), which will reflect both the input from technical experts and the stakeholders.

The actual size and composition of the larger reference group of stakeholders will depend on the context. Small reference group of stakeholders is appropriate when several major donors to any health research-funding organization want to influence priority setting process. They can set very specific thresholds and weights for each criterion. Large and diverse reference group of stakeholders is more appropriate for priority setting for health research on problems of regional or global importance.

Calculating overall priority scores and assigning ranks

Intermediate scores for each research option that are based on the scores received from technical experts will range between 0%-100%. At that point, the managers of the process can simply agree that all criteria that they initially chose for priority setting are equally important (because all of them are needed to get from new knowledge to decrease in disease burden). In that case, an overall research priority score (RPS) will be a simple mean of all intermediate scores.

In a hypothetical example shown in Figure 2 , research option received five intermediate scores from technical experts: 60%, 80%, 70%, 60% and 80%, respectively. This would mean that its overall RPS can be computed as follows:

Calculation of overall research priority score (RPS) based on 5 hypothetically chosen priority setting criteria (C1-C5); values W1-W5 are factors by which each criterion is weighted (computed as average weights for each criterion obtained from the survey among stakeholders (in dark gray), achieved intermediate scores (IS1-IS5) for each research option (in light gray); the required thresholds for intermediate scores for each criterion (computed as average thresholds for each criterion obtained from the survey among stakeholders). The final research priority score for each proposed research option is defined as their weighted average: [W1 × IS1 + W2 × IS2 + … + Wn × ISn/(W1+W2+…+Wn). In the hypothetical case below, the overall RPS should equal (15 × 0.6 + 15 × 0.8 + 15 × 0.7 + 30 × 0.6 + 25 × 0.8)/100 = 69.5%.

However, if stakeholders were also involved and a survey was undertaken among them to include their values in the process, it could provide hypothetical average thresholds for the five criteria (50%, 50%, 40%, 20%, and 60%, respectively), and also hypothetical average weights (US $15, $15, $15, $30, and $25, respectively). In this case, the initial check will establish that all thresholds have been passed and that the research option from the example below remains in the contest for the funding. Then, the weights are applied as shown below and the overall RPS is corrected to 69.5%. After computing weighted RPS for all research options that passed all the thresholds, the options can be ranked by priority according to their achieved RPS.

Performing an analysis of agreement between scorers

Scoring performed by technical experts is both independent and transparent to process managers. Therefore, the CHNRI methodology offers the potential to expose the points of the greatest agreement and the greatest controversy among the experts. Identification of these points should allow more focused discussion on the priorities after the completion of the process. In this way, in addition to the information on how each research option complies with the chosen priority-setting criteria, investors and policy makers are informed about the amount of agreement between the experts on each research option.

The level of agreement can be assessed for each specific research option using agreement statistics (κ). This calculation becomes extremely complicated when the number of scorers exceeds 2 and the number of rating categories exceeds 2. We suggest that all observations where the expert reviewer chose 0.5 (“knowledgeable, but the answer is indeterminate”) should first be recoded as missing values, restricting the number of rating categories to 2 and making the calculation of the κ statistics more meaningful. The decision to choose 0.5 is nearly equivalent to choosing to leave the answer field blank, since in both situations the expert reviewer is revealing that his or her answer to the question is unknown.

Kappa value should be computed for each research question as a measure of the level of agreement among the scorers. When the number of scorers is variable across subjects, statistical significance testing cannot be performed. Interpreting κ statistics is arbitrary, and the greater the κ, the greater the level of agreement. Further details on calculation of κ can be found elsewhere ( 9 ).

Linking computed research priority scores with investment decisions

There are two main scenarios in which process managers will link research priority scores with investment decisions. The first one is designing an investment strategy before actual investments are made. The second one is modifying an already existing investment portfolio to reduce risk and/or increase returns on investments.

In the first scenario, a donor agency or organization will conduct an informative CHNRI process to define its priorities before it commits to funding and launching of the calls for grant proposals. In this case, we argue that investing in health research is fundamentally not much different than investing in stocks of different companies on the stock market. Rather than making investment decisions by comparing companies, investors in health research will be choosing between many groups of health researchers and their research grant proposals. Seen in this way, investors in health research should learn from the vast experience and literature on investment in financial markets ( 10 ).

Among many analogies, “high risk” health research investment is the one with very uncertain (or unlikely) answerability, transferability (usefulness) or potential impact on disease burden reduction. “High profit” health research investment is the one offering very high reduction in disease burden if successful. There will be investments in health research that offer lower “profits,” but also at lower “risks” (such as research on improvement of existing interventions); and also “high-risk high-profit” investment options (eg, research to develop new and non-existent vaccines against malaria or AIDS).

There is always a risk and a potential profit associated with any investment. The risk preference of the investors will therefore represent an important determinant of their investment strategy. For a rational investor, the probability of success always needs to be balanced against the probability of failure. The preferences of both those who tend to seek or to avoid risk have costs in terms of reduced expected profits, which is easy to demonstrate with standard expected utility theory ( 11 ). While this theory does not normatively qualify some preferences as better than others, a common suggestion is that rational actors who are sufficiently large for risk pooling should base investment decisions on preferences that are risk-neutral, as this strategy leads to highest profits in the long run ( 11 , 12 ). This implies that an unbalanced investment portfolio, in which large majority of investments are in “low-risk low-profit” health research options or in “high-risk high-profit” options, is neither rational nor responsible. However, because there is very little accountability for poor investment decisions in health research and their evaluation in terms of benefits for the society, we are witnessing an increasing trend of global research portfolio becoming unbalanced and favoring “high-risk high-profit” health research options ( 12 ).

In an alternative scenario, international funding agency or national government has already been funding health research for several years and would like to improve the mix of supported research options. In this case, a classical “program budgeting and marginal analysis would be appropriate:” (i) identifying funding cut-off points and RPSs for funded research options; (ii) comparing research options that have no allocated funding to existing funding programs; (iii) assessing relative value of each priority using the same criteria; (iv) releasing resources from existing programs to support additional new priority research areas ( 13 ). All decisions that need to be made within this scenario are based on: (i) defining RPS and cost of each research option, either already supported or proposed as an alternative; (ii) maximizing the sum of RPS values of supported research options within a given fixed budget; (iii) if the sum of RPS scores within an existing program is lower than the sum of the alternative, resources should be shifted from the existing into the new research options.

Feedback and revision

CHNRI methodology is a process which does not end with definition of health research priorities and allocation of funding. The investments are expected to lead to changes in the context over time in terms of disease burden. Other components of the contexts may also change substantially, from stakeholders’ system of values to limits in space or risk management preferences. All these changes can be accounted for by: (i) adding further research options to the list; (ii) adding additional criteria; (ii) re-scoring all research options in the redefined context; and (iii) revising thresholds and weights placed on intermediate scores. In this way, the research investment portfolio will continuously be adjusted to the context and aim to reduce the existing disease burden most cost-effectively and in an equitable way.

Some of the possible advantages of CHNRI’s research priority-setting methodology include: (i) transparent presentation of the context and criteria in the priority setting process; (ii) management of the process by investors themselves over its entire duration; (iii) structured way of scoring, which should limit specific interests or personal biases; (iv) · involvement of non-technical stakeholders in priority setting; (v) the flexibility of the process provided by adding or subtracting the criteria; (vi) potential to revise weights and thresholds based on the changes in the context; (vii) · simple presentation of the strengths and weaknesses of each competing research option; (viii) possibility to rank research options according to each individual criterion; (ix) a simple quantitative outcome that is easy to present, justify, and explain to policy-makers; (x) exposure of the points of the greatest agreement and controversy. Although the proposed guidelines are based on wide consultations and extensive review and assessment of previous approaches, the CHNRI method will eventually benefit from independent validation in various settings in the future. It will be even more challenging to define the real impact of the process on shifting global research priorities. That is the ultimate goal of CHNRI method and the one that will leverage support for health research to make more impact on the disease burden in the real world.

Still, the methodology is not free of several possible biases. Although the advantages mentioned above represent a serious attempt to deal with many issues inherent to a highly complex process of research investment priority setting, there are still concerns over the validity of the CHNRI approach and related biases. One of them is related to the fact many possible good ideas (“research investment options”) may not have been included in the initial list of research options that was scored by the experts, and to the potential bias toward items that get the greatest press. The spectrum of research investment options listed initially in this exercise was derived through a systematic process, but it is not endless and it cannot ever cover every single research idea. Specific research methodologies (ie, randomized clinical trials) are not mentioned because the research questions listed in that exercise are unlikely to be answered by a single well-defined study. Therefore, the CHNRI process aims to achieve reasonable coverage of the spectrum of possible ideas.

Another concern over the CHNRI process is that its end product represents a possibly biased opinion of a very limited group of involved people. In theory, a chosen group of experts can have biased views in comparison with any other potential groups of experts. However, the number of people who possess enough experience, expertise, and knowledge on the issue to be able to judge a very diverse spectrum of research questions is rather limited. If one thinks of this “pool of technical experts” as the whole population that could theoretically be used to solicit expert opinion on the questions that need to be asked, we then propose selection of a “sample” from that population, based on their track record. The larger and the more diverse this sample is, the less likely it is that there would be considerable differences in the composition of the initial list of questions (or results of the scoring process) if some other group of experts had been selected.

Acknowledgment

Child Health and Nutrition Research Initiative (CHNRI) of the Global Forum for Health Research was supported by The World Bank in conducting this work.

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Implementing a Maternal health & PRegnancy Outcomes Vision for Everyone (IMPROVE) Initiative Connecting the Community Research Showcase

July 11, 2024 (Noon-1:30 p.m. eastern time)

Sponsor/Co-Sponsor

NICHD, NIH; Office of Research on Women’s Health (ORWH), Office of the Director, NIH; National Institute of Nursing Research (NINR), NIH

NIH VideoCast and Zoom; registration is free but required  

IMPROVE is an NIH-wide initiative led by NICHD, ORWH, and NINR, with participation from multiple NIH institutes, centers, and offices, that was established in response to the rising U.S. rates of pregnancy-related deaths. This multipronged, innovative research effort is designed to address maternal mortality and morbidity, including severe maternal morbidity, and improve maternal health before, during, and after pregnancy. IMPROVE includes a special focus on health disparities and populations disproportionately affected, such as African Americans, American Indians/Alaska Natives, Asians and Pacific Islanders, Hispanics/Latinas, very young women and women of advanced maternal age, and people with disabilities.

This showcase will spotlight the efforts of eight local community organizations taking part in IMPROVE’s Connecting the Community for Maternal Health Challenge. This challenge’s goal is to help nonprofit organizations overcome structural barriers and enhance their capabilities, infrastructure, and experience to compete for federal funding and conduct research projects to improve maternal health outcomes in their communities.

Through a series of engaging presentations, the organizations in the final phase of the challenge will unveil their current research findings, providing insights into the state of maternal health within their local communities. Presenters will share the lessons learned throughout their research journey and will outline their next steps, prompting discussions on how to translate research into actionable solutions to positively impact maternal health outcomes.

Individuals with disabilities who need reasonable accommodation to participate in this event should contact Amy Buckley at [email protected] or 571-520-2279.

More Information

For registration-related questions: Amy Buckley  Email: [email protected]   Phone: 571-520-2279

For program-related questions: [email protected]