What are the best ways to handle Hawthorne and John Henry effects in a randomized control trials?

What are the best ways to handle Hawthorne and John Henry effects in a randomized control trial where agricultural extension messages are applied to increase consumption of organic vegetables in rural Nigeria
Environmental health Occupational and Public health Occupational health Pharmacology Public health
Zubia Mumtaz
I would launch the study and for a pre- determined period of time, not use the data. Discard the data for a few weeks immediately after start of your study. I have noticed respondents can ‘act’ for only a short period of time before reverting to their normal behaviour.
Mohammad Asaduzzaman Chowdhury
A randomized controlled trial (RCT) is a type of scientific experiment that is used to regulate variables that are not under direct experimental control. Clinical trials comparing the effects of medications, surgical techniques, medical devices, diagnostic procedures, or other medical treatments are examples of RCTs.

RCT participants differ from one another in known and unknown ways that can influence study outcomes but cannot be controlled directly. An RCT allows statistical control of these variables by randomly allocating individuals among compared treatments. An RCT may achieve adequate control over these confounding factors to give a valid comparison of the therapies examined if it is effectively designed, conducted, and enrolls enough participants. A randomized controlled trial (RCT) is an experimental type of impact evaluation in which the population receiving the program or policy intervention is randomly selected from the eligible population, and a control group is likewise randomly selected from the same eligible population. It measures how well specified, pre-planned effects are realized. The random assignment of units (people, schools, villages, etc.) to the intervention or control groups is a distinctive element of an RCT. One of its virtues is that it gives a powerful response to problems of causation, allowing evaluators and program implementers to know that the results are the consequence of the intervention and nothing else.
Akhil Dhanesh Goel
Hawthorne effect where the subject under intervention modifies her/his behaviour because of the knowledge of being observed might not be completly "adjusted" in prospective studies - only way to ensure this may be use of secondary data for analysis.

For addressing John Henry effect, the subjects in both intervention and control groups may initially be observed for a pre-determined time before actually starting the intervention. This can help in adjusting for any any resulting bias.

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