The Impact of Digital Technologies and AI-Powered Personalized Lifestyle Interventions on Health-Related Outcomes

A special issue of Healthcare (ISSN 2227-9032).

Deadline for manuscript submissions: 27 June 2026 | Viewed by 365

Special Issue Editor


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Guest Editor
School of Sport Exercise and Rehabilitation Sciences, University of Hull, Hull HU6 7RX, UK
Interests: obesity; physiology; pathophysiology; metabolic medicine; diabetes & cardiovascular disease; lifestyle interventions; digital technologies

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to our journal in a highly contemporary area of healthcare. Digital technologies are revolutionizing healthcare by improving patient outcomes, increasing efficiency, and lowering costs. Digital healthcare apps have also revolutionized how individuals access and manage health services. These apps span a wide range of functions, from personal wellness and fitness tracking to chronic disease management. Digital technologies and artificial intelligence (AI) in healthcare are not only enhancing patient care but also driving innovations that could redefine healthcare delivery globally.

This Special Issue aims to establish the impact of digital technologies and AI-powered personalized lifestyle interventions on health-related outcomes. Articles on lifestyle interventions should focus on exercise, nutrition, sleep, stress, and alcohol/smoking cessation, either singularly or as part of a multi-component intervention, and on how these impact health outcomes across a wide age span and multiple medical specialties.

In this Special Issue, original research, proof-of-concept papers, and reviews are most welcome, alongside perspective/opinion papers from service users or healthcare and healthcare management professionals and developers.

We look forward to receiving your valued contributions.

Dr. James Philip Hobkirk
Guest Editor

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Keywords

  • digital technologies
  • artificial intelligence
  • personalization
  • lifestyle and health outcomes

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Published Papers (1 paper)

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Research

16 pages, 442 KB  
Article
Concordance of an Artificial Intelligence Model (ChatGPT 4.0) with Physician Decisions in Smoking Cessation Clinics: A Comparative Evaluation
by Yagmur Gokseven Arda and Guzin Zeren Ozturk
Healthcare 2025, 13(18), 2283; https://doi.org/10.3390/healthcare13182283 - 12 Sep 2025
Viewed by 25
Abstract
Background: Smoking is one of the leading causes of preventable mortality worldwide. Smoking cessation treatments require personalized therapeutic approaches. Artificial intelligence (AI) is increasingly utilized in clinical decision support systems; however, its role in smoking cessation treatment remains underexplored. This study aims to [...] Read more.
Background: Smoking is one of the leading causes of preventable mortality worldwide. Smoking cessation treatments require personalized therapeutic approaches. Artificial intelligence (AI) is increasingly utilized in clinical decision support systems; however, its role in smoking cessation treatment remains underexplored. This study aims to evaluate the concordance between ChatGPT-4.0-generated treatment recommendations and physician decisions in smoking cessation therapy. Methods: This retrospective and descriptive study was conducted by reviewing the electronic records of patients who presented to a Smoking Cessation Clinic. The ChatGPT-4.0 model was used to compare AI-generated treatment recommendations with physician-prescribed therapies. Concordance rates and the quality of AI-generated information (inappropriate, useful, or perfect information) were assessed. Statistical analyses were performed using SPSS 25.0. Results: A total of 82 patient records were analyzed. The mean age was 40.71 ± 12.87 years (range: 19–69). The overall concordance rate between physicians and ChatGPT-4.0 was 67.1%. Regarding ChatGPT-4.0-generated information quality, 32.9% of cases received inappropriate recommendations, 36.6% received useful recommendations, and 30.5% received optimal recommendations. ChatGPT-4.0 provided inappropriate recommendations in 81.5% of cases involving chronic diseases and 77.8% of cases involving regular medication use (p = 0.021, p = 0.030, respectively). ChatGPT-4.0 achieved the highest rate of optimal recommendations (52.0%) for cytisine therapy. Conclusions: ChatGPT-4.0 can serve as a supportive tool in smoking cessation treatment. However, it remains insufficient in managing complex clinical cases, emphasizing the necessity of physician oversight in final decision-making. Enhancing AI models with larger and more diverse datasets may improve the accuracy of treatment recommendations. Full article
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