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The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research.

ABSTRACT: Conceptual frameworks are useful in research because they can highlight priority research domains, inform decisions about interventions, identify outcomes and factors to measure, and display how factors might relate to each other to generate and test hypotheses. Discovery, translational, and implementation research are all critical to the overall mission of genomic medicine and prevention, but they have yet to be organized into a unified conceptual framework. To fill this gap, our diverse team collaborated to develop the Genomic Medicine Integrative Research (GMIR) Framework, a simple but comprehensive tool to aid the genomics community in developing research questions, strategies, and measures and in integrating genomic medicine and prevention into clinical practice. Here we present the GMIR Framework and its development, along with examples of its use for research development, demonstrating how we applied it to select and harmonize measures for use across diverse genomic medicine implementation projects. Researchers can utilize the GMIR Framework for their own research, collaborative investigations, and clinical implementation efforts; clinicians can use it to establish and evaluate programs; and all stakeholders can use it to help allocate resources and make sure that the full complexity of etiology is included in research and program design, development, and evaluation.

SUBMITTER: Horowitz CR

PROVIDER: S-EPMC6556906 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research.

Horowitz Carol R CR Orlando Lori A LA Slavotinek Anne M AM Peterson Josh J Angelo Frank F Biesecker Barbara B Bonham Vence L VL Cameron Linda D LD Fullerton Stephanie M SM Gelb Bruce D BD Goddard Katrina A B KAB Hailu Benyam B Hart Ragan R Hindorff Lucia A LA Jarvik Gail P GP Kaufman Dave D Kenny Eimear E EE Knight Sara J SJ Koenig Barbara A BA Korf Bruce R BR Madden Ebony E McGuire Amy L AL Ou Jeffrey J Wasserstein Melissa P MP Robinson Mimsie M Leventhal Howard H Sanderson Saskia C SC

American journal of human genetics 20190516 6

Conceptual frameworks are useful in research because they can highlight priority research domains, inform decisions about interventions, identify outcomes and factors to measure, and display how factors might relate to each other to generate and test hypotheses. Discovery, translational, and implementation research are all critical to the overall mission of genomic medicine and prevention, but they have yet to be organized into a unified conceptual framework. To fill this gap, our diverse team c ...[more]

PMID: 31104772

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Project description:BACKGROUND:Prognostic research has many important purposes, including (i) describing the natural history and clinical course of health conditions, (ii) investigating variables associated with health outcomes of interest, (iii) estimating an individual's probability of developing different outcomes, (iv) investigating the clinical application of prediction models, and (v) investigating determinants of recovery that can inform the development of interventions to improve patient outcomes. But much prognostic research has been poorly conducted and interpreted, indicating that a number of conceptual areas are often misunderstood. Recent initiatives to improve this include the Prognosis Research Strategy (PROGRESS) and the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Statement. In this paper, we aim to show how different categories of prognostic research relate to each other, to differentiate exploratory and confirmatory studies, discuss moderators and mediators, and to show how important it is to understand study designs and the differences between prediction and causation. MAIN TEXT:We propose that there are four main objectives of prognostic studies - description, association, prediction and causation. By causation, we mean the effect of prediction and decision rules on outcomes as determined by intervention studies and the investigation of whether a prognostic factor is a determinant of outcome (on the causal pathway). These either fall under the umbrella of exploratory (description, association, and prediction model development) or confirmatory (prediction model external validation and investigation of causation). Including considerations of causation within a prognostic framework provides a more comprehensive roadmap of how different types of studies conceptually relate to each other, and better clarity about appropriate model performance measures and the inferences that can be drawn from different types of prognostic studies. We also propose definitions of 'candidate prognostic factors', 'prognostic factors', 'prognostic determinants (causal)' and 'prognostic markers (non-causal)'. Furthermore, we address common conceptual misunderstandings related to study design, analysis, and interpretation of multivariable models from the perspectives of association, prediction and causation. CONCLUSION:This paper uses a framework to clarify some concepts in prognostic research that remain poorly understood and implemented, to stimulate discussion about how prognostic studies can be strengthened and appropriately interpreted.

Project description:The increasing emphasis on translational approaches to complex neuropsychiatric and neurodevelopmental conditions research requires scientists from a broad range of disciplines to build dynamic collaborations when formulating hypotheses and framing study designs. The need to integrate the knowledge and perspectives not only from multiple scientific silos but also from the populations impacted by these conditions presents a significant challenge to researchers, particularly for a heterogeneous condition like autism. As one path toward addressing these challenges, we have previously introduced Autism Genetics Outcomes (AutGO), an initiative to support broad stakeholder partnerships and promote a new integrated concept called GO (i.e., research approaches that draw on both genetics and clinical outcomes perspectives). Herein, we developed a workflow for collecting stakeholders' feedback toward the development of a GO hypothesis. AutGO is an evolving initiative, and here we describe how its three essential components (conceptual framework, applicability, and implementation) have been developed. As a proof-of-concept, the AutGO team sought to demonstrate how a GO hypothesis could be developed using a semi-structured literature review workflow. We also developed a prototype from published reports and formulated a GO hypothesis for autism. Rather than seeking community stakeholder input after a research project is conceptualized and designed, the developed conceptual framework demonstrates the feasibility of formulating scientific hypotheses by engaging stakeholders in retrospective semi-structured literature reviews. The presented workflow, prototype, and discussed recommendations will bring awareness in the autism research community about the benefits of applying the GO approach in order to promote translational aspects in genetics research. LAY SUMMARY: We used a community-based engagement approach to develop AutGO (Autism Genetics Outcomes), an initiative to establish stakeholder partnerships and to promote research approaches (we refer to as GO) that draw on both genetics and clinical outcomes perspectives. Specifically, we developed a conceptual framework that includes a literature review process for developing GO hypotheses and stakeholder feedback collection protocol. Our work will bring awareness in the autism research community about the benefits of integrating patient perspectives in genetics research. Autism Res 2020, 13: 1286-1299. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.

Project description:BackgroundImplementing mental health recovery into services is a policy priority in Canada and globally. To that end, a 5 year study was undertaken with seven organisations providing mental health and housing services to people living with a mental health challenge to implement guidelines for the transformation of services and systems towards a recovery-orientation. Multi-stakeholder implementation teams were established and a facilitated process guided teams to choosing and planning for the implementation of one recovery innovation. The recovery innovations chosen were hiring peer support workers, Wellness Recovery Action Planning (WRAP), a family support group, and staff recovery training.MethodsThis study reports on data collected at the post-implementation stage. 90 service users, service providers, family members, managers, other actors and knowledge users participated in 41 group, individual or dyad semi-structured interviews. The interview guides included open-ended questions eliciting participants' impressions regarding the impact of implementing the innovation on service users, service providers and organisations. We applied a collaborative qualitative content analysis approach in NVivo12 to coding and interpreting the data generated from these questions.ResultsEighteen impacts of implementing recovery innovations from the perspectives of diverse stakeholder groups were identified. Three impacts of working as an implementation team member and as part of a research project were also identified. Impacts were developed into a conceptual framework organised around four overall categories of impact: Ways of being, Ways of interacting, Ways of thinking, and Ways of operating and doing business.ConclusionsThe IMpacts of Recovery Innovations (IMRI) framework version 1 can assist researchers, evaluators and decision-makers identify, explore and understand impact in the context of recovery innovations. The framework helps fill a gap in conceptualising service and organisation-level impacts. Future research is needed to validate the framework and map it to existing methods for studying impact.

Dataset Information

The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research.

Publications

The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research.

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