Privacy risks and low trust holding back healthcare IoT

Technological factors such as perceived ease of use and perceived usefulness play major roles in adoption decisions. These findings align with classic acceptance theory. Users gravitate toward systems that feel simple, reliable and beneficial. However, the review finds that personalization and device flexibility, which are essential in patient centered care, receive little attention in existing research.

A major new systematic review has found that the global healthcare sector is struggling to keep pace with the rapid rise of Internet of Things technologies, despite their potential to improve diagnosis, treatment and patient monitoring. The study reveals that adoption is uneven, security concerns remain underexamined and the human factors that shape acceptance and resistance are still poorly understood. These findings come as hospitals and clinics worldwide increasingly rely on connected devices for real time health data, chronic disease management and remote patient supervision.

The research, “Exploring Factors Affecting the Adoption of IoT in Healthcare: A Systematic Literature Review,” published in Healthcare, maps the most important influences on IoT adoption. It also highlights where research is falling short, particularly in cybersecurity and human experience, at a time when connected systems continue to multiply across medical environments.

The authors screened more than three thousand studies and ultimately analyzed seventy nine peer reviewed publications focused on IoT use in hospitals, clinics, home care and personal health devices. Their findings reveal a rapidly expanding field that remains deeply fragmented, shaped by uneven technological readiness and gaps in safety, privacy and awareness.

Global adoption rising but driven by narrow research trends

The review shows that IoT adoption has accelerated across healthcare systems, largely driven by the popularity of wearable devices and smart home health technologies. Many of the studies analyzed focus on personal IoT devices such as smartwatches and health trackers. These devices remain the most researched technologies in the field, reflecting their accessibility and strong consumer uptake. Smart homes, mobile health platforms and clinical management systems also appear regularly across the literature, but a significant share of studies fail to specify which IoT technologies they examine. This lack of precision makes it difficult to compare research efforts and measure progress across regions.

Geographically, research output is concentrated in India, Saudi Arabia, the United States, China, Malaysia and Pakistan. Very few studies come from Africa, Latin America or lower income regions, leaving major gaps in understanding how IoT is used or resisted in diverse healthcare environments. Many papers do not identify their regional context at all, which further limits global perspective.

The review identifies 2019 and 2022 as peak years for IoT adoption research, with a second surge in 2023. These trends reflect the wider digital acceleration triggered by the COVID nineteen pandemic, when remote monitoring and telehealth tools increased sharply in use and visibility.

Despite this growth, the authors found that most studies rely on quantitative survey methods. Qualitative research, which could provide deeper insight into user experience, motivations and concerns, remains limited. The authors note that nearly one in five studies does not clearly describe its research design. This inconsistency signals a need for stronger methodological standards in future IoT adoption work.

The study examines the theoretical foundations used in IoT research and identifies twenty eight different frameworks. The Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology dominate the field. Additional theories such as the Health Belief Model and Innovation Diffusion Theory appear frequently. Cybersecurity oriented frameworks are less common even though IoT devices raise significant risks in medical settings. This imbalance shows that research still centers on ease of use, usefulness and attitude, while security and privacy remain underrepresented despite growing threats.

Security risks understudied as human concerns drive adoption and resistance

The investigation reveals that human factors drive IoT adoption more than technological considerations. The authors classify 139 indicators influencing adoption into five categories: individual, technological, security, environmental and other factors. Individual factors dominate, accounting for the highest share of influence. Attitude toward technology appears as the most common driver. People with more positive attitudes are more likely to adopt IoT, while those with concerns about complexity or consequences are less willing.

Individual characteristics such as trust, motivation, health consciousness, perceived norms, age and gender also shape adoption decisions. However, many deeper psychological and cultural drivers remain understudied. For example, willingness to learn and personal desire to use IoT are rarely analyzed even though they may be critical in chronic care or long term monitoring.

Technological factors such as perceived ease of use and perceived usefulness play major roles in adoption decisions. These findings align with classic acceptance theory. Users gravitate toward systems that feel simple, reliable and beneficial. However, the review finds that personalization and device flexibility, which are essential in patient centered care, receive little attention in existing research.

Security factors make up less than ten percent of the indicators studied, despite the high risk IoT devices pose to patient privacy and safety. Privacy concerns are the most frequently studied security issue, followed by trust and data security. The authors emphasize that cybersecurity is underrepresented in IoT adoption research. Many studies treat security as an afterthought rather than a central challenge. This is concerning because healthcare systems are frequent targets of cyberattacks, and IoT devices often serve as entry points into hospital networks.

Environmental and organizational factors also shape adoption. Social influence, professional recommendations, institutional culture and management support all affect whether IoT is integrated into clinical practice. Some technologies rely heavily on physician endorsement, yet many studies do not examine the role of doctors in promoting or discouraging IoT use. This gap limits understanding of how IoT spreads within hospitals, where decision making is often hierarchical.

Cost is one of the most important factors under the “other” category. High perceived cost deters both institutions and individuals from adopting IoT. However, the effort required to learn or maintain IoT systems is rarely examined. This leaves a major gap in understanding how healthcare workers adapt to new digital workloads.

To sum up, the study asserts that slow IoT adoption in healthcare is caused not only by technology limitations but also by human concerns and insufficient security focus. Patients and healthcare workers do not simply accept technologies because they exist. Their acceptance depends on trust, comfort, awareness and perceived safety.

Call for security standards, patient education and user-centered design

The authors outline several steps required to accelerate safe and effective IoT adoption. First, they argue that healthcare institutions must invest in stronger cybersecurity protections. IoT systems produce highly sensitive health data and connect multiple devices across networks. Without strong standards, they create vulnerabilities that attackers can exploit. The review calls for robust, standardized frameworks to govern IoT cybersecurity across hospitals and clinics.

Patient education is another essential requirement. Many individuals do not understand how IoT devices store, transmit or process their health information. Clear communication about privacy safeguards, system limitations and benefits can increase trust and encourage adoption. Education is also needed for clinicians, technicians and administrative staff. The review notes that technicians and mid level professionals receive little research attention even though they play a critical role in IoT deployment.

Developers and vendors must adopt user centered design approaches. Many IoT systems are built with a technology first mindset rather than a patient first mindset. Devices that automatically adjust settings, provide strong privacy protections and simplify data management can reduce resistance. The authors highlight the need for continuous innovation to address emerging privacy threats.

Policy makers also have a significant role. Laws similar to HIPAA in the United States and GDPR in Europe provide valuable foundations but may not fully accommodate IoT specific risks. As IoT ecosystems expand, regulators must update frameworks to cover device interoperability, data sharing, cross border data flows and real time monitoring.

For future research, the authors identify several priority areas. These include secure multimedia streaming in mobile healthcare systems, decentralized identity management, privacy preserving federated learning and blockchain based trust models. The review stresses that ongoing research must align with global regulations and remain adaptable as IoT capabilities evolve.