JMIR Formative Research

Process evaluations, early results, and feasibility/pilot studies of digital and non-digital interventions

Editor-in-Chief:

Amaryllis Mavragani, Scientific Editor (Acting)


Impact Factor 2.2

JMIR Formative Research (JFR, ISSN 2561-326X, Impact Factor 2.2publishes peer-reviewed, openly accessible papers containing results from process evaluations, feasibility/pilot studies and other kinds of formative research and preliminary results. While the original focus was on the design of medical- and health-related research and technology innovations, JFR publishes studies from all areas of medical and health research.

Formative research is research that occurs before a program is designed and implemented, or while a program is being conducted. Formative research can help

  • define and understand populations in need of an intervention or public health program
  • create programs that are specific to the needs of those populations
  • ensure programs are acceptable and feasible to users before launching
  • improve the relationship between users and agencies/research groups
  • demonstrate the feasibility, use, satisfaction with, or problems with a program before large-scale summative evaluation (looking at health outcomes)

Many funding agencies will expect some sort of pilot/feasibility/process evaluation before funding a larger study such as a Randomized Controlled Trial (RCT).

Formative research should be an integral part of developing or adapting programs and should be used while the program is ongoing to help refine and improve program activities. Thus, formative evaluation can and should also occur in the form of a process evaluation alongside a summative evaluation such as an RCT.

JFR fills an important gap in the academic journals landscape, as it publishes sound and peer-reviewed formative research that is critical for investigators to apply for further funding, but that is usually not published in outcomes-focused medical journals aiming for impact and generalizability.

Summative evaluations of programs and apps/software that have undergone a thorough formative evaluation before launch have a better chance to be published in high-impact flagship journals; thus, we encourage authors to submit - as a first step - their formative evaluations in JFR (and their evaluation protocols to JMIR Research Protocols). 

In 2023, JMIR Formative Research received an inaugural Journal Impact Factor™ of 2.2 (Source: Journal Citation Reports™ from Clarivate, 2023)JFR is indexed in PubMed, PubMed CentralDOAJ, Scopus, Sherpa/Romeo, EBSCO/EBSCO Essentials, and the Emerging Sources Citation Index (Clarivate).

Recent Articles

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Formative Evaluation of Digital Health Interventions

Supported self-management interventions, which assist individuals in actively understanding and managing their own health conditions, have a robust evidence base for chronic physical illnesses, such as diabetes, but have been underused for long-term mental health conditions.

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Formative Evaluation of Digital Health Interventions

Mental health care provision in the United Kingdom is overwhelmed by a high demand for services. There are high rates of under-, over-, and misdiagnosis of common mental health disorders in primary care and delays in accessing secondary care. This negatively affects patient functioning and outcomes. Digital tools may offer a time-efficient avenue for the remote assessment and triage of mental health disorders that can be integrated directly into existing care pathways to support clinicians. However, despite the potential of digital tools in the field of mental health, there remain gaps in our understanding of how the intended user base, people with lived experiences of mental health concerns, perceive these technologies.

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Early Results in Infodemiology and Infoveillance

Health misinformation and myths about treatment for opioid use disorder (OUD) are present on social media and contribute to challenges in preventing drug overdose deaths. However, no systematic, quantitative methodology exists to identify what types of misinformation are being shared and discussed.

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Pilot studies (ehealth)

Emergency departments play a pivotal role in the US health care system, with high use rates and inherent stress placed on patients, patient care, and clinicians. The impact of the emergency department environment on the health and well-being of emergency residents and nurses can be seen in worsening rates of burnout and cardiovascular health. Research on clinician health has historically been completed outside of clinical areas and not personalized to the individual. The expansion of digital technology, specifically wearable devices, may enhance the ability to understand how health care environments impact clinicians.

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Formative Evaluation of Digital Health Interventions

Accurate and timely assessment of children’s developmental status is crucial for early diagnosis and intervention. More accurate and automated developmental assessments are essential due to the lack of trained health care providers and imprecise parental reporting. In various areas of development, gross motor development in toddlers is known to be predictive of subsequent childhood developments.

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Formative Evaluation of Digital Health Interventions

Online mindfulness based cognitive therapy (eMBCT) has been shown to reduce psychological distress in people with cancer. However, this population has reported lack of support and asynchronous communication as barriers to eMBCT, resulting in higher nonadherence rates than with face-to-face MBCT. Using a co-creation process, we developed 2 formats of eMBCT: group, blended (combination of therapist-guided group and individual online sessions) and individual, unguided (individual, unguided online sessions only). Group, blended eMBCT offers peer support and guidance, whereas individual, unguided eMBCT offers flexibility and the possibility of large-scale implementation.

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Formative Evaluation of Digital Health Interventions

Access to health care services is a critical determinant of population health and well-being. Measuring spatial accessibility to health services is essential for understanding health care distribution and addressing potential inequities.

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Development and Evaluation of Research Methods, Instruments and Tools

Globally, heart failure (HF) affects more than 64 million people, and attempts to reduce its social and economic burden are a public health priority. Interventions to support people with HF to self-manage have been shown to reduce hospitalizations, improve quality of life, and reduce mortality rates. Understanding how people self-manage is imperative to improve future interventions; however, most approaches to date, have used self-report methods to achieve this. Wearable cameras provide a unique tool to understand the lived experiences of people with HF and the daily activities they undertake, which could lead to more effective interventions. However, their potential for understanding chronic conditions such as HF is unclear.

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Formative Evaluation of Digital Health Interventions

In the coming years, telemedicine will play a key role in health care. Especially in rural areas with weak infrastructure, telemedicine could be crucial to providing adequate and personalized medical care.

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Formative Evaluation of Digital Health Interventions

Young sexual minority men (YSMM) engage in cardiometabolic risk behaviors (eg, substance use) at higher rates than their heterosexual counterparts. Theory and previous research suggest that these risk behaviors may stem, in part, from exposure to minority stress (ie, discrimination based on sexual identity and other identities such as race).

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Formative Evaluation of Digital Health Interventions

To address the anticipated rise in mental health symptoms experienced at the population level during the COVID-19 pandemic, the Ontario government provided 2 therapist-assisted internet-delivered cognitive behavioral therapy (iCBT) programs to adults free of charge at the point of service.

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Formative Evaluation of Digital Health Interventions

The increasing prevalence of nonalcoholic fatty liver disease (NAFLD) in China presents a significant public health concern. Traditional ultrasound, commonly used for fatty liver screening, often lacks the ability to accurately quantify steatosis, leading to insufficient follow-up for patients with moderate-to-severe steatosis. Transient elastography (TE) provides a more quantitative diagnosis of steatosis and fibrosis, closely aligning with biopsy results. Moreover, machine learning (ML) technology holds promise for developing more precise diagnostic models for NAFLD using a variety of laboratory indicators.

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Preprints Open for Peer-Review

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