Determinants of a Subject’s Decision to Participate in Clinical Anesthesia Research

Balajonda, Naraida; Bisanar, Tiffany; Mathew, Joseph P.; Pang, Herbert; Voils, Corrine I.

doi:10.1213/ane.0b013e318277dd7d

Cited by 9 publications

(9 citation statements)

References 22 publications

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“…A highly significant disincentive to participation was related to inconveniences, including travel to the study site and invasive procedures such as blood-sampling. This finding is confirmed by previous studies [12,39,40]. Patients' perception of additional risk or pain resulting from participation to a trial had a negative impact on willingness to participate [40].…”

Section: Discussionsupporting

confidence: 86%

“…Several factors negatively influencing willingness to participate have previously been identified, including patient fear of side effects or of receiving a less effective treatment [7,8], a poor understanding of the randomization or blinding process or of the placebo treatment principle [9,10], or patient a priori preference for a specific treatment [11]. In addition, studies requiring additional testing, such as blood sampling [12], an extra visit [13,14] or long commuting to the study site [15], are also less likely to recruit patients. Finally, patients can also develop distrust of study investigators and refuse to participate if they do not understand the research subject [16], develop the feeling of being a "guinea pig" [17] and fear that the treatment is beyond their control [18,19].…”

Section: Introductionmentioning

confidence: 99%

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Factors associated with patient willingness to participate in anaesthesia clinical trials: a vignette-based cross-sectional study

Noirmain

Gil-Wey

Pichon

et al. 2020

BMC Med Res Methodol

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Background: Clinical trials are essential to improve knowledge of anesthesia and perioperative medicine. Unfortunately, many studies face participant-recruitment issues and fail to include the planned number of participants. There is limited published data about how information delivered about the study or how the experiences and attitudes of prospective participants influence willingness to participate. The purpose of this study was to identify such factors in the domain of anesthesia care. Methods: We performed a cross-sectional study at the Geneva University Hospitals (Switzerland) using a newly developed paper-based questionnaire on a sample of outpatients with a recent hospital stay and that were aged over 18 years, confident speaking French and free of any disease that could hinder participation. We explored patient personal factors, such as current health, past exposure to clinical research and anesthesia, as well as study-related factors. Six different scenarios for clinical studies were assessed. Linear regression modeling was used to assess the specific association between personal and study-related factors and willingness to participate in the studies described in the scenarios. Results: On the 1318 eligible patients, 398 fully completed the questionnaire. Multivariable adjustment revealed that factors related to altruistic values (β, 9.6, 95% CI 3.4 to 15.7, P = 0.002), to the feeling of benefiting from a more effective treatment (β, 4.7, 95% CI 0.2 to 9.2, P = 0.041) and to the absence of fear about double blinding (β, 5.7, 95% CI 1.3 to 10.2, P = 0.012) were positively associated with willingness to participate. Conversely, concerns about drug-related adverse effects (β, − 11.7, 95% CI − 16.9 to − 6.5, P < 0.001) and anxiety about surgery (β, − 5.2, 95% CI − 10.0 to − 0.5, P = 0.031) were negatively associated with willingness to participate. Conclusion: Our study was based on vignettes illustrating typical scenarios of clinical trials performed in anesthesia. However, their similarities with real studies still remains hypothetical and our results should be interpreted as such. Nevertheless, the study contributes to improve understanding of factors that may act as incentives or barriers to participation in clinical trials. It highlights the importance of providing appropriate information and reassurance to patients.

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Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Factors associated with patient willingness to participate in anaesthesia clinical trials: a vignette-based cross-sectional study

Noirmain

Gil-Wey

Pichon

et al. 2020

BMC Med Res Methodol

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“…We will further assess associations, if any, between baseline patient and infection characteristics and willingness or ability to provide informed consent, whether oral or written. 37–41 Given the difficulties of obtaining follow-up information in this type of population, patients’ clinical outcomes will be followed only through day 30±7 (with day 1 being the first day of microbiologically appropriate antibiotic therapy).…”

Section: Observational Substudiesmentioning

confidence: 99%

PIRATE project: point-of-care, informatics-based randomised controlled trial for decreasing overuse of antibiotic therapy in Gram-negative bacteraemia

et al. 2017

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IntroductionAntibiotic overuse drives antibiotic resistance. The optimal duration of antibiotic therapy for Gram-negative bacteraemia (GNB), a common community and hospital-associated infection, remains unknown and unstudied via randomised controlled trials (RCTs).Methods and analysisThis investigator-initiated, multicentre, non-inferiority, informatics-based point-of-care RCT will randomly assign adult hospitalised patients receiving microbiologically efficacious antibiotic(s) for GNB to (1) 14 days of antibiotic therapy, (2) 7 days of therapy or (3) an individualised duration determined by clinical response and 75% reduction in peak C reactive protein (CRP) values. The randomisation will occur in equal proportions (1:1:1) on day 5 (±1) of efficacious antibiotic therapy as determined by antibiogram; patients, their physicians and study investigators will be blind to treatment duration allocation until the day of antibiotic discontinuation. Immunosuppressed patients and those with GNB due to complicated infections (endocarditis, osteomyelitis, etc) and/or non-fermenting bacilli (Acinetobacter spp, Burkholderia spp, Pseudomonas spp) Brucella spp, Fusobacterium spp or polymicrobial growth with Gram-positive organisms will be ineligible. The primary outcome is incidence of clinical failure at day 30; secondary outcomes include clinical failure, all-cause mortality and incidence of Clostridiumdifficile infection in the 90-day study period. An interim safety analysis will be performed after the first 150 patients have been followed for ≤30 days. Given a chosen margin of 10%, the required sample size to determine non-inferiority is roughly 500 patients. Analyses will be performed on both intention-to-treat and per-protocol populations.Ethics and disseminationEthics approval was obtained from the cantonal ethics committees of all three participating sites. Results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.Trial registration numberThis trial is registered at www.clinicaltrials.gov (NCT03101072; pre-results).

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“…Patients who are a priori thought to benefit most from the intervention are recruited on the basis of inclusion criteria, and patients who are a priori thought to be at the greatest risk are excluded on the basis of exclusion criteria. ( ii) Patient self‐selection into clinical trials . Patients often volunteer for RCTs or are allowed to opt out of the trial at any time.…”

Section: Introductionmentioning

confidence: 99%

“…( ii) Patient self-selection into clinical trials. [9][10][11][12][13][14] Patients often volunteer for RCTs or are allowed to opt out of the trial at any time.…”

Section: Introductionmentioning

confidence: 99%

Generalizability analysis for clinical trials: a simulation study

Wang

Huang

et al. 2017

Statistics in Medicine

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Subjects are rarely selected on a random basis from a well-defined patient population of interest into a clinical trial, with women, children, the elderly, and those with common comorbidities who are frequently underrepresented. Decades of clinical experience have demonstrated that the application of trial findings to individual patients is permissible by using efficacy as a measure of effectiveness and assuming that the characteristics of patients are sufficiently similar. In order to investigate this issue in greater depth, we simulated a patient population with treatment effect size of 0.5 (Cohen's d) and five covariates that included gender, health insurance, comorbidity, age, and motivation. To demonstrate how selection of patients for a clinical trial can bias the results when treatment effect varies across individuals, we created 50 nonrandom clinical trials based on this patient population and showed relative bias to range from 1.68% to 99.70%. We calculated and evaluated three indexes: C-statistics, standardized mean difference (SMD), and Tipton's index (β) of generalization for the 50 nonrandom trials. Findings indicated that (i) the ranges were 0.56-0.98, 0.23-11.17, and 0.99-0.73 for C-statistics, SMD, and β, respectively, when treatment effect bias increased from 1.68% to 99.70% and (ii) C-statistics < 0.86, SMD < 1.95, and β > 0.91 when treatment effect bias <50%. Recommendations are made using existing generalization indexes on the basis of our simulation results. An example from a real clinical trial is provided for illustration. Copyright © 2017 John Wiley & Sons, Ltd.

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Determinants of a Subject’s Decision to Participate in Clinical Anesthesia Research

Cited by 9 publications

References 22 publications

Factors associated with patient willingness to participate in anaesthesia clinical trials: a vignette-based cross-sectional study

Factors associated with patient willingness to participate in anaesthesia clinical trials: a vignette-based cross-sectional study

PIRATE project: point-of-care, informatics-based randomised controlled trial for decreasing overuse of antibiotic therapy in Gram-negative bacteraemia

Generalizability analysis for clinical trials: a simulation study

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