Addressing Antimicrobial Resistance (AMR) and Self-Medication Practice (SMP) in Developing Countries: a Field Experiment in Bangladesh

Last registered on June 24, 2024


Trial Information

General Information

Addressing Antimicrobial Resistance (AMR) and Self-Medication Practice (SMP) in Developing Countries: a Field Experiment in Bangladesh
Initial registration date
August 13, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 16, 2023, 10:20 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
June 24, 2024, 2:42 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator

University of Cologne

Other Primary Investigator(s)

PI Affiliation
MIG, University of Cologne
PI Affiliation
National University of Singapore

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
According to the World Health Organization (WHO), antimicrobial resistance (AMR) is a slow-motion pandemic. Knowledge constraints and lack of awareness regarding the adverse health impact of antibiotics are prevalent in third-world countries. Ahmed (2019) shows that many cherry-picked drugs are ineffective in Bangladesh as an outcome of antimicrobial resistance. Village doctors (quacks) are the leading healthcare providers in rural areas who are also not aware of the adverse impact of antibiotics on the human body and are one of the primary sources of antibiotic consumption. Often, reaching out to government hospitals or registered doctors impose transportation costs, so individuals go to medicine shops to buy medicine without registered doctors' concern. Local pharmacy owners provoke customers to buy antibiotics and other unnecessary drugs, boosting their sales. People routinely purchase commonly prescribed antibiotics over the counter to facilitate a speedy recovery. Overall, knowledge constraints and lack of awareness regarding the adverse health impact of antibiotics among mass people is a huge issue in addressing the Antimicrobial Resistance (AMR) problem. In this study, We will introduce an innovative information intervention to fight this problem that will potentially restrict unnecessary antibiotic take-up among mass people by targeting their medication behavior in Bangladesh.
External Link(s)

Registration Citation

Goette, Lorenz, Khalid Imran and Daniel Wiesen. 2024. "Addressing Antimicrobial Resistance (AMR) and Self-Medication Practice (SMP) in Developing Countries: a Field Experiment in Bangladesh." AEA RCT Registry. June 24.
Experimental Details


Informational Intervention: The goal of this intervention is to increase the target population's awareness and comprehension about the use of antibiotics. It entails disseminating pertinent information about the appropriate use of antibiotics, the risks associated with their improper use, and the significance of adhering to recommended dosages and schedules.

Behavioural Nudge Intervention: This intervention will promote constructive changes in behavior related to antibiotic use by drawing on insights from behavioral science. We will provide boxes to keep all medications purchased without registered doctor's prescriptions. That means we will ask our respondents to put their self-purchased , quack prescribed medicines to the provided box. The box will work as physical reminder of the provided information regarding dangers of antimicrobial resistance.

Intervention with Financial Incentives: This intervention will make use of financial incentives to encourage prudent antibiotic usage. We will provide transportation costs to nearest government medical facilities to reduce frequent use unauthorized and informal medical practices.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Frequency of Government Hospital Visits
Incidence of Self-Purchased Medication
Antibiotic Consumption
Visits to Non-Registered Physicians (quacks)
Knowledge of Antimicrobial resistance
Trust in Government Medical Facilities vs. Non-Registered Providers
Primary Outcomes (explanation)
Hospital Visits: An important factor is the participants' increased frequency of hospital visits. Given that participants are anticipated to seek expert medical advice more frequently, this suggests enhanced healthcare seeking behaviour. This outcome will be constructed by counting the number of times an individual visits a government hospital between our . Data will be sourced from hospital records/tickets..

Self-Purchased Medication: Data will be collected through pharmacy records, receipts, or from recalling where respondent will indicate their medication purchases within the time.

Consumption of Antibiotics: We will collect the name and details of consumed medicine by households in each round of survey. Then we will figure out the antibiotics

Visits to Quack Doctors: Prescription of quacks or reported by the respondent.

Knowledge of Antibiotics: It will assess participants' prior and post-intervention knowledge of antibiotics. It will be constructed using standardized questionnaire that assesses knowledge about the causes, consequences, and prevention of antimicrobial resistance.

Trust in Government Medical Facilities vs. Non-Registered Providers:
This outcome will measure an individual's level of trust in government medical facilities compared to non-registered providers. It will be constructed using a Likert scale where individuals will rate their trust in each type of provider.

Secondary Outcomes

Secondary Outcomes (end points)
Quality of Life
Healthcare Expenditure
Community Awareness
Health Literacy
Behavioural Change
Secondary Outcomes (explanation)
Quality of Life: This outcome will be assessed using standardized Quality of Life (QoL) questionnaires or scales. Participants will rate various aspects of their life, including physical health, psychological well-being, social relationships, and environment. Scores from these domains will be aggregated to provide an overall QoL score. Data can be sourced from periodic surveys or interviews.

Healthcare Expenditure
This outcome will measure the total amount an individual or household spends on healthcare services, medications, and related expenses within a specified period.

Community Awareness:
This outcome will gauge the level of awareness within a community about antimicrobial resistance. Additionally, to gauge the dissemination of provided information, respondents will be asked about their efforts in sharing or spreading provided knowledge regrading antimicrobial resistance within their community.

Behavioural Change:
Description: This outcome will measure the health-related behaviors, such as dietary habits and medication adherence. Data will be sourced from self-reported surveys or diaries where individuals detail their behaviors over time. The outcome can be constructed by comparing baseline behaviors to behaviors after intervention or over our study period.

Experimental Design

Experimental Design
We have collaborated with a Bangladeshi NGO named "EHHD Foundation". We will conduct our study on the member households of an ongoing program named "kemon achen" or "how are you?".
The "Kemon Achen" program is dedicated to improving the health and welfare of rural women. We a have access to the database of member households, which will be resource in our research. Our experiment will be conducted specifically with the participants of the "Kemon Achen" program located in two upazilas (sub-districts) within the Dinajpur district of Bangladesh.

In our randomized controlled study, our objective is to identify the most effective strategy to reduce the prevalence of self-medication and visits to unregistered physicians, commonly referred to as "village quacks." Our primary goal is to curtail the unnecessary consumption of medications, a trend intrinsically tied to these practices. To achieve this, we plan to inform our treatment participants about the adverse consequences of antibiotic misuse and explore different channels to emphasize and reinforce this message. Our subjects will be divided between control(T0) and treatment groups(T1,T2).

T0: Control
T1: Information+ box(physical reminder )
T2: Information+ financial incentive(transport cost to nearest govt hospital)

With the information intervention, we will investigate the effectiveness of visual nudges (physical reminders) as a supportive tactic to reduce needless antibiotic consumption. We will give one treatment group containers/box to store medicines purchased without a prescription from an authorized physician. Each time they go for the medicine box, this tactic serves to remind people of the possible risks involved with self-medication, which encourages better judgment. By distinguishing between prescription and over-the-counter medications, this tangible reminder would act as a nudge, subtly dragging them towards better health behavior.
We will also look at the incentive approach combined with information treatment to reduce antibiotic abuse. Despite the subsidies and nearly free treatments provided by government hospitals, we observe that financial limitations, particularly transportation costs, are a significant deterrent to seeking treatment from registered (MBBS) doctors. So we plan to provide transportation costs as financial incentives if member households visit government facilities. They will be reimbursed for their transportation cost once they show the ticket to government hospitals.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
Due to the close proximity of member households in the study area, providing information treatment presents a high probability of spillover and contamination effects between treatment and control group, which rejects the individual household-level randomization technique. Cluster Randomization offers a potential solution to address spillover and contamination effects. However, power calculations reject Village-level clusters as a feasible approach, given the limited number of 37 villages with two treatment and one control wing. On the other hand, we have GPS coordinates of each household, which facilitates us to adopt grid-based clusters. We will create 800 / 1000 square meter grid on the map of study area. It will give us approximately 75 grids. First we will randomize our grids between treatment and control group. Around 25 grid will enter into control group, households under these grids will get no treatments. The rest 50 grids (approx) will get treatment. In treatment group, everyone will get information treatment. Then we will randomize households at individual level with visual nudge(box) and financial incentives.

So, first we will randomize grids between treatment and control groups. After that we will randomize treatments at household level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Around 1 square kilometer grid areas on the map will be our clusters. Given the location of households, we assume that there will be around 75 clusterss. So, one third (around 25) grids will serve as controls, receiving no information, while the remaining 50 will be treatment clusters where all individuals receive information.
Sample size: planned number of observations
Approximately 800 observations (households) grouped into 75 clusters
Sample size (or number of clusters) by treatment arms
There will be around 250 households in 25 (approx.) control clusters. The other around 50 treatment clusters ( "Information + Box" and "Information + Financial Incentive"), will have round 550 households. Overall, there will be around 800 households.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee of the Faculty of Economic and Social Sciences (ERC-FMES), UNIVERSITY OF COLOGNE
IRB Approval Date
IRB Approval Number