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Enregistrement W3089576719 · doi:10.1097/qad.0000000000002640

Toward respectful research with Indigenous people

2020· letter· en· W3089576719 sur OpenAlexaboutno aff
Bernard Lo

Notice bibliographique

RevueAIDS · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueHIV, Drug Use, Sexual Risk
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIndigenousRacismContext (archaeology)MedicinePrejudice (legal term)CriminologyGender studiesSociologySocial psychologyPsychologyGeography

Résumé

récupéré en direct d'OpenAlex

An article in AIDS by Brumme et al.[1] addressed the accelerated progression of HIV infection in a Canadian province whose very high number of cases is predominantly in Indigenous persons. This article was sharply criticized in a letter published in this issue of AIDS. Brumme et al.[1] reported that HIV adaptation to human leukocyte antigen (HLA) alleles commonly expressed in Indigenous populations is a ‘plausible explanation’ for accelerated progression to AIDS. Chelico et al.[2] allege in their letter that a quotation in the media by the authors ‘further stigmatized HIV-1 in a province already dealing with the ongoing effects of colonialism and racism and chronic under-resourcing’ for HIV-1 infection. Further allegations are that the study interfered with the ‘right of Indigenous peoples to control their own data’ and disregarded their ‘community or collective interests in not being stigmatized and marginalized.’ This commentary will discuss the ethical issues raised by research with existing specimens and data and how they might be better addressed. The study by Brumme et al.[1] should be viewed in the context of deep anger in Indigenous people (and in the United States, Blacks and Latinx persons) over long-standing disparities in health outcomes, inequalities in educational and employment opportunities, and discrimination. Because these groups suffer disproportionately from HIV, other infectious diseases such as coronavirus disease 2019, and many chronic medical diseases, they could greatly benefit from well designed research on these conditions. However, their willingness to participate in research may be undermined by mistrust related to highly publicized cases of research misconduct, such as the Tuskegee syphilis study and the Henrietta Lacks case in the United States [3,4]. In Canada, Nuu-chah-nulth Indigenous communities provided samples for research on rheumatic diseases, but the samples were subsequently used to study human migration and retrovirus infections [5,6]. Use of existing specimens and data increases the efficiency of important research because no new specimens need to be collected. Moreover, there is no additional physical risk or inconvenience to research participants. The main risk to individual participants in secondary research studies is breaches of confidentiality, which might lead to stigmatization or loss of employment. Research participants who agree to research on one medical condition, such as heart disease, are generally willing to agree to research on other medical conditions, such as dementia or cancer [7]. However, some research projects using existing specimens and data touch on racial and ethnic identity and foundational cultural beliefs. The studies may be considered objectionable by some participants. In a highly publicized case, the Havasupai Native American tribe in the United States, who had supported a study of diabetes in their nation, objected strongly when the samples were later used to study the genetics of schizophrenia, inbreeding, and migration [3]. According to the tribe, these additional studies were stigmatizing, violated their beliefs about their tribal origins, and were outside the scope of the original consent to donate samples. To settle a lawsuit, the research university apologized and agreed to return the samples to the tribe. This Havasupai Native American case highlights difficulties with consent for secondary research with existing specimens. Not all future uses of a specimen can be anticipated, and, when giving consent, research participants may not have in mind sensitive studies that they would object to if they knew about them [7]. As this case illustrates, anonymization of specimens does not address the ethical concern. Blanket consent to all future research and presumed consent (i.e., an individual is regarded as consenting unless they object) are now regarded as ethically problematic. An ethically preferred solution is for a checklist in which the study participants agree to certain types of research or topics but not others. In addition, there should be a governance mechanism in which the biobank or institution that holds the samples screens requests for secondary use and reviews requests that may be considered sensitive or objectionable by a substantial minority of persons who provided the original materials [7]. The study by Brumme et al.[1] differs from the Havasupai case in important ways. The Brumme samples were not collected under the auspices of an Indigenous sovereign nation but as part of routine clinical care for persons with HIV infection. The topic of the study was the condition for which patient received care. The study did not carry out new analyses on the specimens. Institutional review boards approved the study and waived informed consent because the accessed existing data were anonymized. Of note, sharing of genomics sequencing data with other researchers, with appropriate protections against reidentification of participants, is good research practice and is required in National Institutes of Health-funded studies. Simply following the legal requirements for research, however, may fall short of high ethical standards and aspirations. The study by Brumme et al.[1] can be expected to raise concerns about respect, discrimination, and group stigma because it addressed genetic susceptibility to a stigmatized condition disproportionately prevalent in Indigenous persons, who lack access to good healthcare. How can researchers carry out important research on sensitive topics with members of Indigenous communities and other populations who have suffered and continue to suffer severe injustice? For future studies involving participants from vulnerable communities, researchers should engage these communities as the study is being planned. Community engagement can be tailored to the nature of the study. In Canada, the 2018 Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans, must be followed in research funded by the Canadian Institutes of Health Research [8]. The equivalent in the United States is the National Institutes of Health. The Tri-Council Policy Statement contains requirements for research involving Indigenous peoples. It is not clear that such engagement was required in the project by Brumme et al.[1], a secondary analysis of HLA subtypes that inferred conclusions about Indigenous peoples. Nonetheless, researchers in similar studies would be well advised to ‘seek culturally informed advice before the use of such data to determine if harms may result and if other considerations, such as sharing of the research results, should be explored with the original source community [8].’ In contrast, research projects that involve collection of new specimens and data generally require an ongoing, long-term partnership with the community to assure that their research priorities and concerns are addressed and that risks are acceptable. In the United States, there is no advice from government agencies similar to the Canadian Tri-Council Policy Statement. Seeking culturally informed advice regarding the perspectives of Indigenous persons is always a good starting point. Of note, in projects involving secondary use of existing data, the issue is not obtaining approval from a tribal ruling body to carry out the project. Rather, the goal of engagement in this context is to strengthen the project by seeking ‘culturally informed advice before the use of such data to determine if harms may result and if other considerations, such as sharing of the research results, should be explored with the original source community [8].’ When planning such a secondary analysis project, investigators can be advised to initiate discussions about the study with representatives of leaders of community organizations providing services to Indigenous people [9]. During the data analysis and writing, these leaders might suggest changing some wording to be more respectful, giving appropriate attention to poor access to healthcare and social determinants of health disparities as alternative explanations for findings. Then, results can be presented effectively to Indigenous communities and to the press. Although researchers cannot prevent misrepresentations of their work, they should anticipate misunderstandings and take steps to prevent them. Such engagement can help both researchers and critics achieve their common ultimate goal – to improve outcomes for Indigenous and other disadvantaged persons living with HIV infection. Acknowledgements Conflicts of interest There are no conflicts of interest.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,110
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,007
Charge utile insuffisante (le modèle a refusé de juger)0,0010,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,150
Tête enseignante GPT0,391
Écart entre enseignants0,242 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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