Explorations of the Normal Neural Behavioral and Pathological Bases of Metacognition (METASENS)

Metacognition is the ability to introspect and report one's own mental states, or in other words to know how much one knows. It allows us to form a sense of confidence about decisions one makes in daily life, so one can commit to one option if our confidence is high, or seek for more evidence before commitment if our confidence is low. Although this function is crucial to behave adequately in a complex environment, confidence judgments are not always optimal. Notably, individuals with schizophrenia are prone to overconfidence in errors and underconfidence in correct answers. In schizophrenia, confidence is less correlated with performance compared to controls.

These aspects are held to be at the origin of delusions, disorganization, poor insight into illness and into cognitive deficit and poor social functioning.

Our study aims at identifying the cognitive and neural processes involved in metacognitive deficits in schizophrenia. Participants will perform metacognitive judgments on a low-level perceptual task (visual motion discrimination). Participants will do the first-order perceptual task by clicking on the correct answer with a mouse. During the first order task completion, the investigators will record several behavioral, physiological and neural variables. Then, participants will perform the metacognitive task with a visual analog scale.

The study will address four research questions:

• Q1: is schizophrenia associated with a decrease in metacognitive efficiency? Is the metacognitive deficit due to under- or over-confidence?
• Q2: is the metacognitive impairment reflected at a decisional level as measured by behavioral variables (mouse tracking and reaction times)?
• Q3: which physiological markers (EEG, skin conductance, heart rate) are predictors of metacognitive efficiency in individuals with schizophrenia and healthy controls?
• Q4: which clinical symptoms correlate with metacognitive deficits?

The investigators make several hypotheses related to the previous research questions:

• Q1: the investigators expect metacognitive deficits in schizophrenia, based on results from several studies using both qualitative and quantitative measures. The investigators will rule out that quantitative deficits are not confounded with impairments in type 1 performance, with a generalized cognitive deficit in schizophrenia (lower premorbid and current Intelligence Quotient (IQ), and deficits in executive functioning and particularly in planning and working memory abilities), with depression or with statistical flaws during analysis of confidence.
• Q2: the investigators expect behavioral cues (mouse tracking and reaction times) to be less correlated with confidence in patients vs. controls. The investigators thus make the hypothesis that the metacognitive deficit in schizophrenia may stem from an inability to integrate pre-decisional cues while performing an explicit metacognitive judgment.
• Q3: the investigators expect physiological cues (EEG with Error-Related Negativity, Lateralized Readiness Potential and alpha suppression, and arousal of the autonomic nervous system with skin conductance and heart rate ) to be less correlated with confidence in patients vs. controls.
• Q4: based on previous findings, the investigators expect that several clinical dimensions of schizophrenia may correlate with metacognitive performance. The metacognitive deficit would be greater for patients with high levels of positive and disorganized symptoms, and greater for patients with low levels of clinical and cognitive insight, and low levels of social functioning.

Study Overview

• Status: Recruiting
• Conditions: Schizophrenia; Social Skills; Behavior; Insight Impaired

Detailed Description

SAMPLING PLAN

1. Existing data Registration before the creation of data: As of the date of submission of this research plan for preregistration, the data have not yet been collected, created, or realized.
2. Data collection procedures. Healthy volunteers will be recruited from the general population. Individuals with schizophrenia will be recruited from community mental health centers and outpatient clinics in the Versailles area and among the FACE-SZ (FondaMental Academic Centers of Expertise for Schizophrenia) cohort in Versailles. All participants will be naive to the purpose of the study, give informed consent in accordance with institutional guidelines and the Declaration of Helsinki, and receive a monetary compensation (10€ / h).
3. Sample size Maximum of 50 healthy controls vs. 50 individuals with schizophrenia.

4. Sample size rationale The estimated sample sizes allow testing effects of medium size between individuals with schizophrenia and healthy controls with a power of 0.8, based on one-sided two-sample t-test power calculation with Cohen's d = 0.5, α = 0.05. They allow measuring medium correlations within groups with a power of 0.7, based on approximate correlation-power calculation with r = 0.3, α = 0.05.

   Sample sizes for electrophysiological recordings are based on previous a study, with 20 patients vs. 20 controls, resulting in 13 vs. 13 after outlier exclusion.

5. Stopping rule Optional stopping will be avoided by using sequential Bayes factor analyses. Data collection will stop whenever a critical comparison reaches the threshold of BF = 3 or BF = 1/3.

   DESIGN PLAN

6. Study design The investigators will ask participants to discriminate the motion direction of a random dot kinetogram (type 1 task). They will use a mouse to indicate whether the dots were mostly moving rightward or leftward, by clicking on the side they think corresponds to a correct answer (red and blue circles, see Figure 1). The mouse trajectory corresponding to the type 1 task will be recorded and analyzed. Motion variance will be adapted for each subject before the experiment using a 1up/2down staircase, so to reach an average performance of 71%. An auditory feedback will be played if participants answer in more than 6s. On each trial, participants will then indicate on a visual analog scale the confidence in their response (type 2 task). The scale will range from 0% ("Certain my response is right") to 100% ("Certain my response is wrong"). The initial position of the cursor will always correspond to 50% confidence ("Uncertain of my response)". The experiment will consist in 10 blocks of 30 trials and last about 1h.

7. Randomization Motion direction (left or right) will be pseudo-randomized, with no more than 4 successive trials with the same direction.

   ANALYSIS PLAN

8. Statistical models 8.1. Behavioral data All analyses will be performed with R, using notably the afex, BayesFactor, ggplot2, lme4, lmerTest, and effects packages. In all ANOVAs, degrees of freedom will be corrected using the Greenhouse-Geisser method.

   The groups' socio-demographic (age, sex, education), cognitive (premorbid and current IQ, and executive performance with planning and working memory) and mood (depression) characteristics will be compared using the Student t test or Χ² tests when appropriate. Only variables that significantly differ between the two groups will be included as covariates in the following analyses.

   The metacognitive performance will be primarily analyzed with binomial mixed-effects models between accuracy and confidence, with group (patient vs. control) and several covariates (premorbid and current IQ, depression and executive performance with planning and working memory) as between-subject factors. Regression slope will be taken as an indicator of metacognitive performance and asymptotes as a marker of confidence bias, i.e. the tendency to report high or low confidence ratings independent of task performance. Likelihood ratio tests will assess significance.

   Predecisional behavioral variables (reaction times, mouse trajectory parameters) will be added to the model in a secondary analysis after main differences between patients and controls are established. Geometric features of mouse trajectories (motion entropy on the x-axis) will be quantified using the EMOT and Mousetrap packages. Correlations between motion entropy and confidence will be quantified by R², adjusted for the number of dependent variables relative to the number of data points.

   8.2. Correlation between metacognitive performance and clinical characteristics in schizophrenia

   The investigators will run correlation analyses between metacognitive performance (regression slope between metacognitive judgments and accuracy of the first order task) and several clinical variables. The clinical variables will be:

   • The positive and disorganization scores for the Positive and Negative Syndrome Scale (PANSS), according to the 5-factor model proposed by van der Gaag et al.
   • The total score on the Birchwood Insight Scale (BIS) for insight into illness
   • The total score on the Beck Cognitive Insight Scale (BCIS) for cognitive insight
   • The total score on the Personal and Social Performance Scale (PSP) for social functioning The investigators will use a Spearman rank-order correlation test with false discovery rate to correct for multiple comparisons.

   8.3. Electrophysiological data Preprocessing: continuous EEG will be acquired at 1200 Hz with a 64-channels Gtec HIamp system. Signal preprocessing will be performed using custom Matlab (Mathworks) scripts using functions from the EEGLAB toolbox. Following visual inspection, artifact-contaminated electrodes will be removed for each participant, and epoching will be performed at type 1 response onset. For each epoch, the signal from each electrode will be centered to zero and average-referenced. Following visual inspection and rejection of epochs containing artifactual signals, an independent component analysis will be applied to individual data sets, followed by a semi-automatic detection of artifactual components based on measures of autocorrelation, focal channel topography, and generic discontinuity. After artifacts rejection, artifact-contaminated electrodes will be interpolated using spherical splines.

   Statistical analysis: voltage amplitude will be averaged within temporal windows (e.g., 20ms), and analyzed with linear mixed effects models using R together with the lme4 and lmerTest packages. This method allows analyzing single trial data, with no averaging across condition or participants, and no discretization of confidence ratings. Models will be performed on each latency and electrode for individual trials, including raw confidence rating and accuracy as fixed effects, and random intercepts for subjects. Statistical significance for electrophysiological data within regions of interest (e.g., frontocentral and left parietal scalp regions) will be assessed after correction for false discovery rate. When possible, cluster-based permutation test will be used.

9. Transformations Data will be transformed in case they violate the assumption of normality (e.g., inverse reaction times).

10. Follow-up analyses Besides mixed logistic regressions, metacognitive performance will be analyzed using second-order signal detection theory: meta-d' will reflect the amount of perceptual evidence available when performing confidence judgments. Confidence biases will also be computed with receiver operating characteristic curves (ROC): the area between the ROC and major diagonal will be divided by the minor diagonal, and confidence bias will be defined as the log ratio of the lower and upper area. An ANOVA with group and appropriate covariates as between-subject factors will test for a decrease in metacognitive efficiency and an increase in confidence bias in patient vs. control participants.

    Drift-diffusion modeling will allow us to determine which aspects of reaction times during the type 1 task differ between schizophrenic patients and healthy controls (e.g., drift rate and boundary separation), and assess how such differences might determine confidence judgments, thereby allowing testing the existence of metacognitive deficits at a decisional-locus.

11. Inference criteria Two-tailed tests with group as the between-subject factor will be used. The threshold for significance will be set to alpha = 5%. When possible, Bayes factors will be computed to support null findings and set stopping rules (see above).

12. Data exclusion The first trials of each condition will be excluded from analysis if they contain large variations of the perceptual signal.

    Only trials with reaction times between 100 ms and 6 s for the type 1 task will be kept.

    Participants will be excluded in case they cannot reach 71% accuracy on the type 1 task, respond in more than 6 s in a majority of trials, or in case they do not use the confidence scale properly (e.g., no variance in confidence reports).

13. Missing data The use of mixed models applied to behavioral and electrophysiological data will allow dealing with unbalanced datasets so that data imputation will not be needed.
14. Exploratory analysis (optional) 14.1. Correlation between metacognitive bias and clinical characteristics in schizophrenia The investigators will run exploratory Spearman rank-order correlation analyses between metacognitive bias (asymptotes of the regression line between metacognitive judgments and accuracy of the first order task) and several clinical variables (positive and disorganization scores for the PANSS, the total score for BIS, BCIS, and PSP).

14.2. Heart rate Heart rate will be measured with a Gtec plethysmographic pulse sensor and quantified as a function of type 2 performance. Based on previous findings in healthy participants, the investigators expect greater confidence to be associated with faster heart rate between stimulus onset and type 2 response. The investigators will attempt to replicate these findings following the same methods as Allen and colleagues and extend it to patients.

14.3. galvanic skin response (GSR) As for heart rate, GSR will be measured with a Gtec dedicated sensor and quantified as a function of type 2 performance using the Ledalab toolbox under Matlab. To our knowledge, no study has quantified the link between GSR and metacognition so that the investigators will conduct exploratory analyses.

• Study Type: Observational
• Enrollment (Anticipated): 100

Contacts and Locations

Study Locations

• France
  • Grenoble, France
    • Not yet recruiting
    • CHU Grenoble
  • Le Chesnay, France, 78150
    • Recruiting
    • Centre Hospitalier de Versailles
  • Saint-Égrève, France
    • Not yet recruiting
    • CH Alpes Isère

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 65 years (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Patients:

Patients will be stabilized and will be recruited from community mental health centers and outpatient clinics in the Versailles area and among the FACE-SZ (FondaMental Academic Centers of Expertise for Schizophrenia) cohort in Versailles.

Controls:

Healthy volunteers will be recruited from the general population. The control group will be screened for current or past psychiatric illness and participants will be excluded if they meet criteria for any disorder of the DSM-V

All participants will be naive to the purpose of the study, give informed consent in accordance with institutional guidelines and the Declaration of Helsinki, and receive a monetary compensation (10€ / h).

Description

Inclusion Criteria:

• DSM-V criteria for schizophrenia (Structured Clinical Interview for Disorders)
• Normal or corrected-to-normal vision

Exclusion Criteria:

• a moderate or severe substance used disorder within the past 6 months (DSM-V criteria)
• current or prior history of untreated significant medical illness or of neurological illness
• electroconvulsive therapy in the last three months
• dyschromatopsia

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Control
• Time Perspectives: Cross-Sectional

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Individuals with schizophrenia; Behavioral variables: Type 1 task (motion discrimination) accuracy (binary: correct/incorrect) / Type 1 reaction time (continuous: time to respond to the type 1 task in ms) / Confidence (continuous: visual analog scale) / Type 2 reaction time (continuous: time to report confidence in ms) / Mouse trajectory (pixel coordinates) Physiological variables: Electroencephalogram (continuous: 64ch. time-locked to type 1 response) / Heart rate (continuous: time-locked to type 1 response) / Galvanic skin response (continuous: time-locked to type 1 response) Clinical variables: Positive and Negative Syndrome Scale / Birchwood Insight Scale / Beck Cognitive Insight Scale / Personal and Social Performance Scale / Calgary Depression Scale / Chlorpromazine equivalents Neuropsychological variables: National Adult Reading Test (French) / Wechsler Adult Intelligence Scale version IV (WAIS-IV) subtests (matrix reasoning, vocabulary, letter-number sequencing)
Controls; Behavioral variables: Type 1 task (motion discrimination) accuracy (binary: correct/incorrect) / Type 1 reaction time (continuous: time to respond to the type 1 task in ms) / Confidence (continuous: visual analog scale) / Type 2 reaction time (continuous: time to report confidence in ms) / Mouse trajectory (pixel coordinates) / Physiological variables: Electroencephalogram (continuous: 64ch. time-locked to type 1 response) / Heart rate (continuous: time-locked to type 1 response) / Galvanic skin response (continuous: time-locked to type 1 response) / Clinical variables: Calgary Depression Scale Neuropsychological variables: National Adult Reading Test (French) / WAIS-IV subtests (matrix reasoning, vocabulary, letter-number sequencing)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Metacognitive performance	Regression slope between accuracy and confidence, in a binomial mixed-effects model including appropriate covariates (variables that are significantly different between patients and controls, among the following: age, sex, education, premorbid and current IQ, executive performance with planning and working memory; and depression)	Repeated measures within a 2 hours long experiment
Predecisional behavioral variables	Reaction times and mouse trajectory parameters (motion entropy on the x-axis)	Repeated measures within a 2 hours long experiment
EEG markers	Error-Related Negativity, Lateralized Readiness Potential and alpha suppression	Repeated measures within a 2 hours long experiment

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Metacognitive bias	Asymptote of the regression line between accuracy and confidence, in a binomial mixed-effects model including appropriate covariates (variables that are significantly different between patients and controls, among the following: age, sex, education, premorbid and current IQ, executive performance with planning and working memory; and depression)	Repeated measures within a 2 hours long experiment
Positive symptoms of schizophrenia	The following items of the the Positive and Negative Syndrome Scale: P1+P3+G9+P6+P5+G1+G12+G16-N5	One measure per subject, assessed during a 30 min long interview
Disorganization symptoms of schizophrenia	The following items of the the Positive and Negative Syndrome Scale: N7+G11+G10+P2+N5+G5 +G12 +G13 +G15+G9	One measure per subject, assessed during a 30 min long interview
Insight into illness	Total score on the Birchwood Insight Scale, a self-report scale with 8 items	One measure per subject, assessed with a 10 min long autoquestionnaire
Cognitive insight	Total score on the Beck Cognitive Insight Scale, a self-report scale with 15 items	One measure per subject, assessed with a 20 min long autoquestionnaire
social functioning	Total score on the Personal and Social Performance Scale	One measure per subject, assessed during a 20 min long interview

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Heart rate	Measured with a Gtec plethysmographic pulse sensor	Repeated measures within a 2 hours long experiment
Galvanic skin response	Measured with a Gtec dedicated sensor	Repeated measures within a 2 hours long experiment

Collaborators and Investigators

• Sponsor: Versailles Hospital
• Collaborators: Versailles Saint-Quentin-en-Yvelines University; Centre National de la Recherche Scientifique, France

Publications and helpful links

General Publications

• Beck AT, Baruch E, Balter JM, Steer RA, Warman DM. A new instrument for measuring insight: the Beck Cognitive Insight Scale. Schizophr Res. 2004 Jun 1;68(2-3):319-29. doi: 10.1016/S0920-9964(03)00189-0.
• Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13(2):261-76. doi: 10.1093/schbul/13.2.261.
• Birchwood M, Smith J, Drury V, Healy J, Macmillan F, Slade M. A self-report Insight Scale for psychosis: reliability, validity and sensitivity to change. Acta Psychiatr Scand. 1994 Jan;89(1):62-7. doi: 10.1111/j.1600-0447.1994.tb01487.x.
• Perrin F, Pernier J, Bertrand O, Echallier JF. Spherical splines for scalp potential and current density mapping. Electroencephalogr Clin Neurophysiol. 1989 Feb;72(2):184-7. doi: 10.1016/0013-4694(89)90180-6.
• Allen M, Frank D, Schwarzkopf DS, Fardo F, Winston JS, Hauser TU, Rees G. Unexpected arousal modulates the influence of sensory noise on confidence. Elife. 2016 Oct 25;5:e18103. doi: 10.7554/eLife.18103.
• Bagiella E, Sloan RP, Heitjan DF. Mixed-effects models in psychophysiology. Psychophysiology. 2000 Jan;37(1):13-20.
• Bruno N, Sachs N, Demily C, Franck N, Pacherie E. Delusions and metacognition in patients with schizophrenia. Cogn Neuropsychiatry. 2012;17(1):1-18. doi: 10.1080/13546805.2011.562071. Epub 2011 Jun 28.
• Calcagni A, Lombardi L, Sulpizio S. Analyzing spatial data from mouse tracker methodology: An entropic approach. Behav Res Methods. 2017 Dec;49(6):2012-2030. doi: 10.3758/s13428-016-0839-5.
• Charles L, Gaillard R, Amado I, Krebs MO, Bendjemaa N, Dehaene S. Conscious and unconscious performance monitoring: Evidence from patients with schizophrenia. Neuroimage. 2017 Jan 1;144(Pt A):153-163. doi: 10.1016/j.neuroimage.2016.09.056. Epub 2016 Sep 23.
• Chaumon M, Bishop DV, Busch NA. A practical guide to the selection of independent components of the electroencephalogram for artifact correction. J Neurosci Methods. 2015 Jul 30;250:47-63. doi: 10.1016/j.jneumeth.2015.02.025. Epub 2015 Mar 16.
• Chiu CY, Liu CC, Hwang TJ, Hwu HG, Hua MS. Metamemory in patients with schizophrenia measured by the feeling of knowing. Psychiatry Res. 2015 Dec 15;230(2):511-6. doi: 10.1016/j.psychres.2015.09.046. Epub 2015 Oct 3.
• Fleming SM, Dolan RJ, Frith CD. Metacognition: computation, biology and function. Philos Trans R Soc Lond B Biol Sci. 2012 May 19;367(1594):1280-6. doi: 10.1098/rstb.2012.0021.
• Fox, J. (2003). Effect displays in R for generalised linear models. Journal of statistical software 8(15): 1-27.
• Kepecs A, Mainen ZF. A computational framework for the study of confidence in humans and animals. Philos Trans R Soc Lond B Biol Sci. 2012 May 19;367(1594):1322-37. doi: 10.1098/rstb.2012.0037.
• Kieslich, P. J., D. U. Wulff, et al. Mousetrap: An R package for processing and analyzing mouse-tracking data (Version 3.0.0). 2017
• Koren D, Seidman LJ, Poyurovsky M, Goldsmith M, Viksman P, Zichel S, Klein E. The neuropsychological basis of insight in first-episode schizophrenia: a pilot metacognitive study. Schizophr Res. 2004 Oct 1;70(2-3):195-202. doi: 10.1016/j.schres.2004.02.004.
• Kother U, Veckenstedt R, Vitzthum F, Roesch-Ely D, Pfueller U, Scheu F, Moritz S. "Don't give me that look" - overconfidence in false mental state perception in schizophrenia. Psychiatry Res. 2012 Mar 30;196(1):1-8. doi: 10.1016/j.psychres.2012.03.004. Epub 2012 Apr 5.
• Kuznetsova, A., P. B. Brockhoff, et al. Package 'lmerTest'. R package version 2. 2015
• Lysaker PH, McCormick BP, Snethen G, Buck KD, Hamm JA, Grant M, Nicolo G, Dimaggio G. Metacognition and social function in schizophrenia: associations of mastery with functional skills competence. Schizophr Res. 2011 Sep;131(1-3):214-8. doi: 10.1016/j.schres.2011.06.011. Epub 2011 Jul 13.
• Maniscalco B, Lau H. A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings. Conscious Cogn. 2012 Mar;21(1):422-30. doi: 10.1016/j.concog.2011.09.021. Epub 2011 Nov 8.
• Morey, R. D., J. N. Rouder, et al. BayesFactor: Computation of Bayes factors for common designs. R package version 0.98. 2014.
• Moritz S, Woodward TS, Jelinek L, Klinge R. Memory and metamemory in schizophrenia: a liberal acceptance account of psychosis. Psychol Med. 2008 Jun;38(6):825-32. doi: 10.1017/S0033291707002553. Epub 2008 Jan 21.
• Nasrallah H, Morosini P, Gagnon DD. Reliability, validity and ability to detect change of the Personal and Social Performance scale in patients with stable schizophrenia. Psychiatry Res. 2008 Nov 30;161(2):213-24. doi: 10.1016/j.psychres.2007.11.012. Epub 2008 Oct 11.
• Rausch M, Muller HJ, Zehetleitner M. Metacognitive sensitivity of subjective reports of decisional confidence and visual experience. Conscious Cogn. 2015 Sep;35:192-205. doi: 10.1016/j.concog.2015.02.011. Epub 2015 Mar 7.
• Singmann, H., B. Bolker, et al. afex: Analysis of factorial experiments. R package version 0.15-2. 2015.
• Team, R. C.R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. 2016.
• van der Gaag M, Hoffman T, Remijsen M, Hijman R, de Haan L, van Meijel B, van Harten PN, Valmaggia L, de Hert M, Cuijpers A, Wiersma D. The five-factor model of the Positive and Negative Syndrome Scale II: a ten-fold cross-validation of a revised model. Schizophr Res. 2006 Jul;85(1-3):280-7. doi: 10.1016/j.schres.2006.03.021. Epub 2006 May 26.
• Wickham, H. ggplot2: elegant graphics for data analysis, Springer. 2016.
• Yeung N, Summerfield C. Metacognition in human decision-making: confidence and error monitoring. Philos Trans R Soc Lond B Biol Sci. 2012 May 19;367(1594):1310-21. doi: 10.1098/rstb.2011.0416.

Study record dates

Study Major Dates

• Study Start (ACTUAL): April 27, 2017
• Primary Completion (ANTICIPATED): July 27, 2024
• Study Completion (ANTICIPATED): September 27, 2024

Study Registration Dates

• First Submitted: May 2, 2017
• First Submitted That Met QC Criteria: May 2, 2017
• First Posted (ACTUAL): May 4, 2017

Study Record Updates

• Last Update Posted (ACTUAL): February 8, 2023
• Last Update Submitted That Met QC Criteria: February 7, 2023
• Last Verified: February 1, 2023

More Information

Terms related to this study

• Keywords: Depression; EEG; Metacognition; Event related potentials; Mousetracking; Frequency analysis
• Additional Relevant MeSH Terms: Mental Disorders; Schizophrenia Spectrum and Other Psychotic Disorders; Schizophrenia
• Other Study ID Numbers: P16/25_METASENS/METACTION; 2016-A01612-49 (OTHER: ANSM)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No