Adaptation needs of an intervention to facilitate tobacco cessation among men attending emergency departments in Nairobi, Kenya
This study utilized a systematic adaptation process involving intercept interviews and stakeholder prioritization to identify and address key barriers—such as rigid response formats, message length, and cost concerns—thereby optimizing the US-based Text2Quit mHealth intervention for effective tobacco cessation among men in Nairobi, Kenya.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer
In many parts of the world, cancer remains a devastating burden, with three-quarters of all deaths from the disease occurring in low- and middle-income countries. A major driver of this crisis is tobacco use, a habit that is particularly prevalent among men in places like Kenya, where nearly 85 percent of smokers are male. These men often face a unique challenge: they are less likely to visit regular doctors for check-ups, meaning they miss out on the standard advice and support that could help them quit. To reach this group, health experts have turned to mobile phones. Text messaging has proven effective in wealthier nations, offering a steady stream of encouragement and reminders to people trying to stop smoking. However, a program designed for the United States cannot simply be copied and pasted into a different setting. The technology, the culture, and the daily lives of people in Nairobi differ significantly from those in Washington, D.C. For a digital health tool to work, it must fit the hands and minds of the people it is meant to serve.
Researchers set out to adapt a successful American text-message program called Text2Quit for use by men in Nairobi, Kenya. The goal was not just to translate the words, but to understand how real people interact with the technology in their own environment. The team recruited thirteen men who smoked and were visiting the emergency department of Kenyatta National Hospital. These men were not just asked about their smoking habits; they were given a prototype version of the Kenyan text program on their own phones and asked to use it right then and there. As they received messages and tried to reply, researchers watched closely, noting where the men got stuck, what confused them, and what made them lose interest. This was a hands-on test of the user experience, designed to catch problems before the program was rolled out to thousands of people.
The testing revealed three main hurdles that prevented the men from engaging with the program. First, the system was too rigid. The computer program expected replies in a very specific format, such as a date written as numbers in a strict order. When a man typed the date in a slightly different way, which is how he might naturally write it, the system rejected his message. One participant tried to enter the date twice, received error messages both times, and eventually gave up in frustration. Second, the messages were too long. Many of the men used basic feature phones with small screens that required them to scroll down repeatedly to read a single text. The researchers found that some men simply stopped reading after a few lines, describing the effort of scrolling through long blocks of text as mentally exhausting. Third, and perhaps most surprisingly, many men were afraid the service would cost them money. Even though the program was free, the men worried that replying to the texts would use up their prepaid phone credit. This fear of hidden costs stopped them from participating, regardless of how helpful the advice might have been.
To solve these problems, the research team brought together doctors, designers, and local experts to brainstorm fixes. They used a structured group discussion method where everyone shared ideas and then voted on the best solutions. The group agreed on five key changes to make the program work better for Kenyan men. The most important fix was to make the system more forgiving. Instead of rejecting a reply because of a small formatting error, the program would now accept slight variations, such as different ways of writing a date or common abbreviations for "yes." The team also decided to shorten the text messages significantly, ensuring they could be read on a small screen without excessive scrolling and that each message asked for only one simple action.
The team also realized that the way the program was introduced needed to change. They decided that when a man first signed up, a counselor would sit with him in person to explain exactly how the service worked. This person would demonstrate how to find and reply to the messages on the specific phone the man was holding, and they would explicitly state that the service is free and will not deduct money from his phone account. Finally, the researchers planned to add a layer of personal follow-up. If a man stopped replying for a day, the system would send a gentle nudge, and if he still did not respond, a counselor would call him to see if he was having trouble with the technology.
These findings highlight that the success of a health intervention depends as much on the details of its design as on the medical advice it offers. By listening to the users and adapting the tool to their specific realities—whether it is the type of phone they own, how they write dates, or their fears about cost—the researchers turned a rigid American program into a flexible tool suited for Nairobi. The study suggests that with these adjustments, text-based support could become a powerful way to help Kenyan men quit smoking, a critical step toward reducing the burden of cancer in the region. The adaptations identified in this process are now being tested in a larger trial to see if they truly help people stop smoking.
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