From Skepticism to Support: Healthcare Providers’ Acceptance of Digital Interventions in Substance Used Disorders Treatment in Kenya
Introduction
Substance use disorders (SUDs) present a significant global and local health concern. According to the World Drug Report 5.8% of the population aged 15-64 in the year 2021, equivalent to 296 million individuals, had used drugs. Alcohol, cannabis, and cigarette smoking are the most commonly used abused substances in Kenya, reflecting a significant prevalence of SUDs in the country. While opioids are less prevalent, they contribute significantly to the disease burden and mortality associated with SUDs.
Moreover, digital interventions in healthcare, such as those delivered via computers, mobile phones, web-based platforms, text messages, or smartphone applications, significantly enhance treatment access. These technologies mitigate the shortage of skilled healthcare providers by providing scalable solutions, reducing referrals, and minimising barriers to healthcare access.
Treatment Landscape
Healthcare providers commonly combine pharmacotherapy and psychosocial therapies to treat SUDs, delivering these interventions in face-to-face settings. Even though these traditional techniques have shown to be effective in improving outcomes for people with SUDs, there is still a sizeable treatment gap, which has led researchers to investigate supplementary strategies including digital interventions to improve overall quality of patient care.
The Technology Acceptance Model (TAM) is a foundational framework in healthcare settings that focuses on perceived usefulness and ease of use that influence technology adoption. Understanding healthcare providers’ attitudes and acceptance towards digital interventions is crucial for their successful integration into standard care practices. A recent study evaluates the attitudes of healthcare practitioners toward the adoption of digital interventions for psychosocial SUD treatment.
Data Collection and Analysis
Conducting a descriptive cross-sectional survey, healthcare providers at the methadone clinic, a public facility in Nairobi, Kenya. The data collection involved a structured questionnaire addressing sociodemographic variables, prior digital intervention experience, and attitudes towards SUD treatment. Statistical analysis, employing Pearson’s coefficient, assessed the relationship between TAM constructs.
Key Observations
The results revealed a high level of acceptance of digital treatments for the treatment of substance use disorders. One of the main outcomes was that majority of participants, primarily psychologists or counsellors, had received mental health training, with 71.4% having undergone such training, and 23.8% had worked with digital interventions before. 66.7% of participants had experience with text-based interventions, and the same percentage agreed on their effectiveness in substance use behaviour. A strikingly high rate, with 90.5% of respondents, agreed that psychological treatment through digital platforms is effective. Participants also acknowledged the positive aspects of cost-effectiveness, enhanced accessibility, and potential patient benefits.
Future Research
In order to assess the long-term cost reductions and patient outcome enhancements linked to digital therapies, longitudinal research is required. When comparing various digital intervention modalities (such as text-based, app-based, or telemedicine) to traditional in-person therapies, comparative effectiveness research could look at how well they perform in terms of both clinical efficacy and cost-effectiveness in low- and middle-income countries (LMICs). To understand adoption factors, qualitative research must explore practitioners’ financial perspectives on digital integration. Implementation and policy studies are crucial for affordable, scalable solutions in LMIC healthcare systems. This will guarantee fair access and long-term results for people with SUDs.
