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Record W2547212508 · doi:10.1093/eurpub/ckw198

Written informed consent in health research is outdated

2016· article· en· W2547212508 on OpenAlexaboutno aff
Reinder Broekstra, Els Maeckelberghe, Ronald P. Stolk

Bibliographic record

VenueEuropean Journal of Public Health · 2016
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsBiobankMantraInformed consentAutonomyDeclaration of HelsinkiResearch ethicsEconomic JusticePublic relationsPolitical scienceEngineering ethicsData Protection Act 1998MedicineAlternative medicineMedical educationPsychologyLawEngineering

Abstract

fetched live from OpenAlex

Reference to the Declaration of Helsinki as assurance for ethical principles for medical research involving human subjects has become a meaningless mantra. The participants’ relationship with researchers has been distrusted-based with Written Informed Consent (WIC) hereinafter referred to as WIC) placed as an important barrier to protect participants’ autonomy. Today the mantra is dictated by many details in consent forms and ever more strict regulations. Globally, especially in Europe as well the USA, establishment of privacy and protection of research subject regulations reveal similar obstacles and critiques, for example in the recently accepted European General Data Protection Regulation and the proposed changes to the Common Rule from September 2015. In a digital revolution ethical principles need to be reassured in a novel way, especially for the increasing use of data collected outside traditional clinical trial research such as patient records and biobank/cohort studies linked with other data sources (‘Big Data in Healthcare’). WIC as used in research in medical sciences are static and not appropriate for the use of untraditional and innovative research methods. We will argue that dynamic, continuous, and interactive methods of informing do more justice to the underlying principles of informed consent. This by honouring rights of participants and to facilitate them in their decision to participate based on a qualified presumed consent, while being more transparent. In a clinical setting where the relationship between researcher and participant is strongly interdependent and of a personalized nature, WIC might be effective.1 However, medical research has dramatically changed into a context of more complexity, collaboration, and variety. Research becomes less invasive with the advent of genetic research, innovative methods, and the access to huge amounts of personal and clinical digital data. In this less (directly) invasive context this mechanism of informed consent is limited in effectiveness due to opacity and lack of transitivity.2 Only relevant and important consequences and implications of participation can be communicated, in order to prevent an overload of information and to get a clear consent. In a broad data collection with no single research question, such as biobanks, there are struggles as well with informed consent. First, it is hard to thoroughly inform participants about specific future research projects since these are still unidentified. Second, a valid informed consent is difficult to generate in big data research, because of a transparency paradox.1,3 Moreover, some scholars have pointed out that these WIC’s undermine their assumed primary function of preserving welfare and autonomy. First, WIC neglects the risk of qualitative bad decision making, since human beings often apply imperfect reasoning. Therefore researchers should protect participants for these fallacies.4 Second, the argument of trust-promotion that is made in response to the limitations as proposed by O’Neill faces its own challenges, such as damaging and underemphasising trust. First, by diminishing interpersonal trust with a distrust-based starting point. Second, by addressing lack of trust by promoting trustworthiness instead of trust, which seems to be symptomatic approach.5 The Council of Europe, the US government, and the World Medical Association defined informed consent as an obligation for research to inform participants extensively and to ask their explicit consent. Hence, traditional informed consent models consist of two obligations, namely inform and explicit consenting. This should provide a juridical authorization that aims to protect participants’ autonomy. Therefore participants’ autonomous choice is formalised to an administrative procedure, which should provide sufficient material to catalyse trust. However, such a definition does not ensure protection of participants’ autonomy and preservation of trust in reality. Researchers’ accountability and their transparency are limited to a minimum amount with one-time WIC. In practice an informed consent form is often signed without full understanding, giving the researcher the possibility of an escape to unethical behaviour. Moreover consent forms seem to have minor influence on trust, since trust is established in enduring interaction.6 Furthermore, while informed consent is highly valued by the research community, participants and general public tend to see less value in WIC. In a recent study a majority of the general population in the Netherlands considered explicit consent unnecessary if research and doctors fulfil their information duty.7 This is in line with Canadian findings of unanimity about the importance of being informed and diversity in opinions regarding preferences in consent types.8 Even scientist have challenged the current informed consent procedure and proposed alternatives like dynamic consent, meta-consent, participation pact, enhanced consent, and one-off consent. In the same vein, a National Acadamies Panel recently insisted on a ‘time-out’ for the proposed update of the Common Rule in the USA.9 Attitudes towards sharing information are changing, with people becoming more willing to share personal information while being more conscious about their rights. Autonomy as we know in the Kantian tradition takes in account the interests of other human beings. Hence, an autonomous choice requires clarifying and weighing of personal and others’ relevant interests. Participants’ autonomy is at stake if the context or aim of research changes during participation. Such a change asks for re-evaluation of relevant interests in order to ensure that qualifications still meet personal preferences. Therefore instruments are needed that provide a dynamic, continuous, and interactive method of informing. For example, a global informed consent can presumed to be effective when participants are maximally informed and their consent is qualified, as much as possible.1 Based on the described practical and ethical arguments we propose to replace the static WIC by a system with a variety of instruments that assure maximum information and communication. This system will enable a dynamic and interactive involvement of participants. Patient/participant web portals that are increasingly being developed, should include a two way connection to establish a proper information flow.10 Although participants can always decide to discontinue their participation, a system of maximum information and communication will enhance trust in research, since they are able to re-evaluate their balance of interests at any desired moment. Participation will be tailored on personal preferences and needs. Moreover this would stimulate participatory deciding which is important for trust. In conclusion, with a growing complexity in research and data, protection mechanisms need to become dynamic and interactive. Moreover, collaboration between researcher and participant needs to be based on trust rather than on distrust. Researchers and legislators from EU and US should join their forces to prevent parochialism. The static informed consent procedure does not fit this new thinking. Conflicts of interest: None declared. This viewpoint is partly funded by a grant of the Netherlands Organisation for Scientific Research (313-99-313).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.222
metaresearch head score (Gemma)0.110
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2220.110
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.894
GPT teacher head0.670
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations12
Published2016
Admission routes1
Has abstractyes

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