↓ Skip to main content

A virtual experimenter to increase standardization for the investigation of placebo effects

Overview of attention for article published in BMC Medical Research Methodology, July 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users
facebook
1 Facebook page

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
77 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A virtual experimenter to increase standardization for the investigation of placebo effects
Published in
BMC Medical Research Methodology, July 2016
DOI 10.1186/s12874-016-0185-4
Pubmed ID
Authors

Bjoern Horing, Nathan D. Newsome, Paul Enck, Sabarish V. Babu, Eric R. Muth

Abstract

Placebo effects are mediated by expectancy, which is highly influenced by psychosocial factors of a treatment context. These factors are difficult to standardize. Furthermore, dedicated placebo research often necessitates single-blind deceptive designs where biases are easily introduced. We propose a study protocol employing a virtual experimenter - a computer program designed to deliver treatment and instructions - for the purpose of standardization and reduction of biases when investigating placebo effects. To evaluate the virtual experimenter's efficacy in inducing placebo effects via expectancy manipulation, we suggest a partially blinded, deceptive design with a baseline/retest pain protocol (hand immersions in hot water bath). Between immersions, participants will receive an (actually inert) medication. Instructions pertaining to the medication will be delivered by one of three metaphors: The virtual experimenter, a human experimenter, and an audio/text presentation (predictor "Metaphor"). The second predictor includes falsely informing participants that the medication is an effective pain killer, or correctly informing them that it is, in fact, inert (predictor "Instruction"). Analysis will be performed with hierarchical linear modelling, with a sample size of N = 50. Results from two pilot studies are presented that indicate the viability of the pain protocol (N = 33), and of the virtual experimenter software and placebo manipulation (N = 48). It will be challenging to establish full comparability between all metaphors used for instruction delivery, and to account for participant differences in acceptance of their virtual interaction partner. Once established, the presence of placebo effects would suggest that the virtual experimenter exhibits sufficient cues to be perceived as a social agent. He could consequently provide a convenient platform to investigate effects of experimenter behavior, or other experimenter characteristics, e.g., sex, age, race/ethnicity or professional status. More general applications are possible, for example in psychological research such as bias research, or virtual reality research. Potential applications also exist for standardizing clinical research by documenting and communicating instructions used in clinical trials.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Unknown 75 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 13%
Student > Master 9 12%
Student > Bachelor 9 12%
Researcher 7 9%
Student > Doctoral Student 5 6%
Other 12 16%
Unknown 25 32%
Readers by discipline Count As %
Psychology 14 18%
Computer Science 7 9%
Neuroscience 6 8%
Nursing and Health Professions 4 5%
Medicine and Dentistry 4 5%
Other 12 16%
Unknown 30 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 July 2016.
All research outputs
#13,985,702
of 22,880,691 outputs
Outputs from BMC Medical Research Methodology
#1,355
of 2,022 outputs
Outputs of similar age
#205,985
of 363,150 outputs
Outputs of similar age from BMC Medical Research Methodology
#29
of 41 outputs
Altmetric has tracked 22,880,691 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,022 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 363,150 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.