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Reasons for Participation in Pain Research: Can They Indicate a Lack of Informed Consent?

2008· article· en· W1983368590 on OpenAlexaff
Ajay D. Wasan, Simone P. Taubenberger, Walter M. Robinson

Bibliographic record

VenuePain Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInformed consentContext (archaeology)Chronic painRemunerationMedicineQualitative researchAffect (linguistics)Coping (psychology)Clinical trialPsychologyAlternative medicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To ascertain the self-reported reasons for participation in the clinical research of chronic low back pain and to evaluate those reasons in the context of informed consent and the concept of therapeutic misconception. This is the belief that research participation is equivalent to clinical care. DESIGN: Qualitative descriptive study with semistructured interviews. SETTING: Phone interviews with subjects with chronic low back pain after they completed a double-blind controlled trial. PARTICIPANTS: Fifty-two of 60 (86%) randomized controlled trial completers. RESULTS: Seventy-seven percent had more than one reason for study participation, including the following: to contribute to research; to seek relief of pain (both short- and long-term); to try a different drug; monetary remuneration; and to have their pain taken seriously. An initial altruistic reason for participation was often followed later in the interview by reasons of personal benefit. In most cases, the single question, "why did you participate?" was insufficient to reveal these multiple reasons. "Personal benefit" had many individual meanings, framed in the context of an illness narrative of coping with chronic pain. Despite reasons of personal benefit, subjects were still able to make the distinction between research and clinical treatment. CONCLUSIONS: Assessing the adequacy of informed consent requires a thorough understanding of how subjects viewed a study and their reasons for participation. Quantitative-based surveys may not capture the complexities of reasons for study participation. Reasons of personal benefit, seemingly contradictory reasons for participation, or overriding desire for relief may all affect the quality of informed consent. Yet, these issues may not automatically signal the presence of TM.

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)0.072
metaresearch head score (Gemma)0.511
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0720.511
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.858
GPT teacher head0.666
Teacher spread0.192 · 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 designObservational
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".

Quick stats

Citations37
Published2008
Admission routes1
Has abstractyes

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