NCT05244122

PROJECT 2 EXAMPLE: Feedback X Prevalence Using Dermatology Stimuli

Completed NA Results posted Last updated 26 October 2022

What this trial tests

NA trial testing Feedback in Decision Making in 1,121 participants. Completed in 27 June 2021.

Timeline

22 June 2021

Primary endpoint
27 June 2021

27 June 2021

Quick facts

Lead sponsor	Brigham and Women's Hospital
Phase	NA
Status	Completed
Study type	INTERVENTIONAL
Allocation	na
Design	single group
Masking	none
Primary purpose	basic science
Enrollment	1,121
Start date	22 June 2021
Primary completion	27 June 2021
Estimated completion	27 June 2021
Sites	1 location across United States

Drugs / interventions tested

• Feedback
• Prevalence

Conditions studied

• Decision Making — all drugs for Decision Making →

Sponsor

Brigham and Women's Hospital

Who can join

18 and older, any sex, with Decision Making. Patients with the condition only — healthy volunteers not accepted.

Results — posted to ClinicalTrials.gov

Per-arm endpoint measurements with 95% confidence intervals where reported. Source: trial results section.

Change in D' Between Pairs of Blocks. Primary · Participants could be in the study for as little as two blocks in one day up to 24 blocks collected over 6 days.

D' (d-prime) is defined as z-transform of the true positive rate - z-transform of false positive rate. True positive is when you say that a real melanoma is a melanoma. False positive is when you say that a nevis is a melanoma. A correction of 0.5 error is added to avoid calculation problems when z=0 or z=1. D' of zero indicates no ability to discriminate. D' \> zero indicates some ability to discriminate. The change of interest is the D' for Block 2 when it follows Block 1 compared to the D' for Block 2 averaged across all conditions.

Group	Value	95% CI
Low Prevalence No Feedback First, Then Low Prevalence No Feedback	-0.138	-0.335 – 0.0585
Low Prevalence No Feedback First, Then Low Prevalence With Feedback	.0754	-0.126 – 0.277
Low Prevalence No Feedback First, Then High Prevalence No Feedback	0.023	-0.0459 – 0.0920
Low Prevalence No Feedback First, Then High Prevalence With Feedback	-.129	-0.232 – -0.0259
Low Prevalence With Feedback First, Then Low Prevalence No Feedback	-0.0654	-0.169 – 0.0382
Low Prevalence With Feedback First, Then Low Prevalence With Feedback	-0.139	-0.259 – -0.0192
Low Prevalence With Feedback First, Then High Prevalence No Feedback	0.0603	-0.0432 – 0.164
Low Prevalence With Feedback First, Then High Prevalence With Feedback	0.0582	-0.0366 – 0.153
High Prevalence No Feedback First, Then Low Prevalence No Feedback	0.0792	-0.0177 – 0.176
High Prevalence No Feedback First, Then Low Prevalence With Feedback	0.0452	-0.0759 – 0.166
High Prevalence No Feedback First, Then High Prevalence No Feedback	-0.0123	-0.168 – 0.143
High Prevalence No Feedback First, Then High Prevalence With Feedback	0.035	-0.0883 – 0.158

Change in Criterion Between Pairs of Blocks. Primary · Participants could be in the study for as little as two blocks in one day up to 24 blocks collected over 6 days.

Criterion, c, corresponds to the position of the midpoint between the z-transformed probabilities of hits (correct yes responses) and false alarms (incorrect yes responses). It is calculated as -\[z(p(h))+z(p(FA))\]/2. The criterion, c, z-score quantifies the distance away from being unbiased in units of standard deviations. A Z-score of 0 is said to be unbiased. Negative values for c indicate a more relaxed criterion for saying yes. Positive numbers indicate a more strict criterion for saying yes.

Group	Value	95% CI
Low Prevalence No Feedback First, Then Low Prevalence No Feedback	0.0488	-0.131 – 0.228
Low Prevalence No Feedback First, Then Low Prevalence With Feedback	0.00147	-0.0734 – 0.0763
Low Prevalence No Feedback First, Then High Prevalence No Feedback	-0.026	-0.0813 – 0.0293
Low Prevalence No Feedback First, Then High Prevalence With Feedback	-0.0582	-0.110 – -0.00631
Low Prevalence With Feedback First, Then Low Prevalence No Feedback	0.182	0.114 – 0.249
Low Prevalence With Feedback First, Then Low Prevalence With Feedback	0.131	0.0674 – 0.195
Low Prevalence With Feedback First, Then High Prevalence No Feedback	0.236	0.166 – 0.305
Low Prevalence With Feedback First, Then High Prevalence With Feedback	0.0458	0.0134 – 0.0783
High Prevalence No Feedback First, Then Low Prevalence No Feedback	-0.0124	-0.0752 – 0.0503
High Prevalence No Feedback First, Then Low Prevalence With Feedback	0.0136	-0.0407 – 0.0678
High Prevalence No Feedback First, Then High Prevalence No Feedback	-0.00091	-0.125 – 0.124
High Prevalence No Feedback First, Then High Prevalence With Feedback	0.0186	-0.0311 – 0.0683

Sponsor's own description

Imagine that a dermatologist spends the morning seeing patients who have been referred for suspicion of skin cancer. Many of them do, in fact, have skin lesions that require treatment. For this set of patients, disease 'prevalence' would be high. Suppose that the next task is to spend the afternoon giving annual screening exams to members of the general population. Here disease prevalence will be low. Would the morning's work influence decisions about patients in the afternoon? It is known from other contexts that recent history can influence current decisions and that target prevalence has an impact on decisions. In this study, decisions were decisions about skin lesions from individuals with varying degrees of expertise, using an online, medical imaging labelling app (DiagnosUs). This allowed examination of the effects of feedback history and prevalence in a single study. Blocks of trials could be of low or high prevalence, with or without feedback. Over 300,000 individual judgements were collected. (taken from Wolfe, J. M. (2022). How one block of trials influences the next: Persistent effects of disease prevalence and feedback on decisions about images of skin lesions in a large online study. . Cognitive Research: Principles and Implications (CRPI), 7, 10. doi: https://doi.org/10.1186/s41235-022-00362-0

Publications & conference data

No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.