Journal of Medical Internet Research
The leading peer-reviewed journal for digital medicine and health and health care in the internet age.
Editor-in-Chief:
Gunther Eysenbach, MD, MPH, FACMI, Founding Editor and Publisher; Adjunct Professor, School of Health Information Science, University of Victoria, Canada
Impact Factor 6.0 CiteScore 11.7
Recent Articles
Sexually transmitted infections (STIs) such as chlamydia are common among young people and can lead to serious health issues if untreated. Although condoms are recommended for prevention, many young people report inconsistent use during penetrative sex. Web-based STI testing is becoming increasingly popular, but these services typically offer minimal support or guidance on preventing future infections. The “Wrapped” intervention aims to help young users of web-based STI testing use condoms consistently and correctly during penetrative sex, thus reducing future STI incidence.

Virtual reality (VR) technology holds significant potential for chronic pain management in children and adolescents by providing an alternative and complementary approach to traditional methods of alleviating pain and improving quality of life. Parents play an important role in the successful adoption of VR technologies for children, influencing how children accept, use, and benefit from it. However, little is known about parents’ views on integrating VR technology into pediatric and adolescent chronic pain management.

In Japan, the human papillomavirus (HPV) vaccination rate has dropped to nearly zero since the suspension of proactive government recommendations in 2013. Following the termination of vaccination suspension in 2021 and subsequent proactive vaccination recommendation in 2022, it is crucial to promote catch-up vaccinations for those who missed their initial opportunity.

Regular engagement in physical activity and exercise is associated with a multitude of physical and mental health benefits. Hence, it has been widely encouraged as a measure by which to combat somatic and psychological ailments. In view of the technical progress, the ageing society and the public life restrictions issued during the COVID-19 pandemic, the delivery of interventions using digital devices has become highly popular.

Primary healthcare (PHC) is critical for delivering accessible and continuous care but faces persistent challenges such as workforce shortages, administrative burden, and rising multimorbidity. Artificial intelligence (AI) has the potential to support PHC by enhancing diagnosis, workflow efficiency, and clinical decision-making. However, existing research often overlooks how AI tools function within the complex realities of primary care and how they are experienced by clinicians and patients.

Globally, the pursuit of exclusive breastfeeding (EBF) remains a formidable challenge. The surge in popularity of mobile health interventions demonstrates its potential as a promising avenue for promoting breastfeeding practices. Nevertheless, research investigating breastfeeding monitoring interventions via mobile health remains scarce among diverse populations.

This concept paper delineates the design of a socio-technical ecosystem for ethical screening and promotion of mental health and wellbeing, building on the convergence of digital technologies with modern human-centred design methods. Access to individuals’ health and wellbeing data will enable the generation of actionable insights with different degrees of granularity, for the benefit of individuals, care providers, and business organisations. Critical to the success of the ecosystem are proactive involvement of all stakeholders, the definition of incentives to encourage engagement, and the promotion of consistent narratives as public institutional messages. The article posits working hypotheses, including the idea that creative externalisation of health and wellbeing data, augmented by advanced physico-digital interactivity, can sustain positive psychological and behavioural change. The theoretical underpinning consists of the integration of existing frameworks across wellbeing, behaviour change, and sustainable business. The article defines a research agenda for expanding socially-inclusive dialogue on data governance and policy implications.

The DC Cohort is a longitudinal HIV cohort study of people with HIV receiving care at 14 clinical sites in Washington, DC led by George Washington University (GW). Data are routinely linked to DC Department of Health (DC Health) HIV surveillance databases to increase data completeness and accuracy and to help identify people with HIV enrolled at multiple sites. The ATra Black Box (Black Box) is a novel privacy technology developed by Georgetown University (GU) which is currently deployed in 40 public health jurisdictions. The Black Box provides a secure mechanism to link private health information across data systems.

Unstructured patient feedback (UPF) allows patients to freely express their experiences without the constraints of predefined questions. The proliferation of online healthcare rating websites has created a vast source of UPF. Natural language processing (NLP) techniques, particularly sentiment analysis and topic modelling, are increasingly being used to analyse UPF in healthcare settings, however the scope and clinical relevance of these technologies is unclear.

The association between loneliness and problematic media use has been evaluated in longitudinal studies and meta-analyses. However, previous meta-analyses have relied heavily on Pearson correlation coefficients, which may not fully account for the complexities of this association. Therefore, an updated meta-analysis incorporating more robust statistical models is needed.

Mixed methods research is essential to development of patient reported outcome measures, digital technology, and endpoint selection for clinical drug trials, and to advance clinical care, when complex health-related experiences cannot be fully understood by quantitative or qualitative approaches alone. New technology and opportunities for remote data collection have changed the ways in which qualitative and quantitative data can be collected, enabling researchers to capture human experiences in ways not previously possible. This paper describes Perspective Mapping, a new online interviewing technique that uses mind mapping software to capture in-depth qualitative data inside a quantitative measurement framework to understand and measure individual experiences. The objective of this tutorial is to review the theoretical underpinnings, present instructions for study design and implementation, and address strengths, limitations, and potential applications of this technique in health and behavioral sciences. During online interviews, mind-mapping software is used to visually depict experiences. Structured concept maps are co-created in real time with participants, focusing on building detailed narrative descriptions about experiences and categorizing these within a predefined quantitative framework, such as the relative importance of different experiences relevant to a phenomenon. The approach combines semi-structured interviewing with technology enhanced card-sorting techniques, allowing participants to define and prioritize what matters most. The method ensures narrative richness alongside structured data collection, facilitating deeper understanding of phenomena. Perspective Mapping emphasizes participant engagement in data generation and analysis and enables the simultaneous collection of qualitative narratives and quantitative assessment of key concepts. The technique has been successfully applied in research on chronic illness, symptom burden, and digital health technology. Advantages of the approach include systematic collection of qualitative data, transparent and structured data outputs, real-time data validation, and ability to return maps to participants as a form of reciprocity. Feasibility factors such as interviewer capabilities, participant literacy, interview duration, and technology resources must be considered. Perspective Mapping offers an innovative and engaging way to gather complimentary qualitative and quantitative data remotely. By blending qualitative depth with quantitative structure, the technique supports richer, more actionable insights for health research, policy, and beyond. This technique holds promise for applications in health, psychology, education, and other social sciences where comprehensive understanding of experiences is essential.
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