TY - JOUR
T1 - Optimizing expectations via mobile apps: A new approach for examining and enhancing placebo effects.
AU - Gruszka, Piotr
AU - Burger, Christoph
AU - Jensen, Mark P.
N1 - Publisher Copyright:
Copyright © 2019 Gruszka, Burger and Jensen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
PY - 2019/5/31
Y1 - 2019/5/31
N2 - There is growing interest in interventions that enhance placebo responses in clinical practice, given the possibility that this would lead to better patient health and more effective therapy outcomes. Previous studies suggest that placebo effects can be maximized by optimizing patients' outcome expectations. However, expectancy interventions are difficult to validate because of methodological challenges, such as reliable blinding of the clinician providing the intervention. Here we propose a novel approach using mobile apps that can provide highly standardized expectancy interventions in a blinded manner, while at the same time assessing data in everyday life using experience sampling methodology (e.g., symptom severity, expectations) and data from smartphone sensors. Methodological advantages include: 1) full standardization; 2) reliable blinding and randomization; 3) disentangling expectation effects from other factors associated with face-to-face interventions; 4) assessing short-term (days), long-term (months), and cumulative effects of expectancy interventions; and 5) investigating possible mechanisms of change. Randomization and expectancy interventions can be realized by the app (e.g., after the clinic/lab visit). As a result, studies can be blinded without the possibility for the clinician to influence study outcomes. Possible app-based expectancy interventions include, for example, verbal suggestions and imagery exercises, although a large number of possible interventions (e.g., hypnosis) could be evaluated using this innovative approach.
AB - There is growing interest in interventions that enhance placebo responses in clinical practice, given the possibility that this would lead to better patient health and more effective therapy outcomes. Previous studies suggest that placebo effects can be maximized by optimizing patients' outcome expectations. However, expectancy interventions are difficult to validate because of methodological challenges, such as reliable blinding of the clinician providing the intervention. Here we propose a novel approach using mobile apps that can provide highly standardized expectancy interventions in a blinded manner, while at the same time assessing data in everyday life using experience sampling methodology (e.g., symptom severity, expectations) and data from smartphone sensors. Methodological advantages include: 1) full standardization; 2) reliable blinding and randomization; 3) disentangling expectation effects from other factors associated with face-to-face interventions; 4) assessing short-term (days), long-term (months), and cumulative effects of expectancy interventions; and 5) investigating possible mechanisms of change. Randomization and expectancy interventions can be realized by the app (e.g., after the clinic/lab visit). As a result, studies can be blinded without the possibility for the clinician to influence study outcomes. Possible app-based expectancy interventions include, for example, verbal suggestions and imagery exercises, although a large number of possible interventions (e.g., hypnosis) could be evaluated using this innovative approach.
UR - http://www.scopus.com/inward/record.url?scp=85068205133&partnerID=8YFLogxK
U2 - 10.3389/fpsyt.2019.00365
DO - 10.3389/fpsyt.2019.00365
M3 - Journal article
SN - 1664-0640
VL - 10
JO - Frontiers in Psychiatry
JF - Frontiers in Psychiatry
IS - MAY
M1 - 365
ER -