AI Models Show Human-Like Personality Patterns in Groundbreaking Psychology Study

A groundbreaking study has demonstrated that artificial intelligence systems exhibit consistent personality patterns similar to humans when assessed through standardized psychological tests. Researchers administered personality assessments to four major AI models, discovering that each displayed unique behavioral tendencies. Claude 3 Opus emerged as highly introverted and analytical, while ChatGPT-3.5 showed more extroverted characteristics. The research utilized both Myers-Briggs-style typological assessments and Big Five personality measurements across multiple testing sessions. These findings have significant implications for the deployment of AI in healthcare settings, particularly mental health applications where personality compatibility between AI and patients could affect treatment outcomes. The study suggests that AI personality profiling should become a standard component of responsible AI deployment protocols, especially in patient-facing roles where interpersonal dynamics are crucial for therapeutic success. 

Beyond P-Values: How the Relative Risk Index Enhances Statistical Reliability in Orthopaedic Research

 Orthopaedic researchers increasingly recognize the limitations of traditional statistical measures. In a recent letter to the Journal of the American Academy of Orthopaedic Surgeons, Dr. Thomas Heston introduces the Relative Risk Index (RRI) as a valuable complement to the established Fragility Index (FI). The core difference lies in their focus: while FI measures susceptibility to P-value changes based on minimal outcome alterations, RRI evaluates the magnitude of change needed to reach therapeutic equivalence across all data. This distinction proves significant in tranexamic acid research, where FI suggests fragility but RRI indicates robustness. The RRI's value stems from its independence from arbitrary P-value thresholds and its alignment with clinical decision-making processes. As orthopaedic surgery continues advancing evidence-based practice, adopting complementary statistical approaches like RRI could enhance research reliability and ultimately improve surgical outcomes through more nuanced evaluation of intervention efficacy.
Citation: Heston TF. Letter to the Editor: The Relative Risk Index: A Complementary Metric for Assessing Statistical Fragility in Orthopaedic Surgery Research. J Am Acad Orthop Surg. 2025 Apr 1;33(7)
doi: 10.5435/JAAOS-D-24-00473

The Role of Prompt Engineering in Transforming Primary Care

 Prompt engineering is emerging as a critical skill in healthcare, particularly in primary care settings. By designing and optimizing input prompts, healthcare providers can guide AI systems to generate more accurate and valuable outputs. This article highlights the importance of prompt engineering in medical education and its various applications, including enhancing patient–provider communication, streamlining clinical documentation, supporting medical education, and facilitating personalized care. By adopting best practices such as incorporating domain-specific knowledge, engaging in iterative refinement and validation, and addressing ethical considerations, healthcare providers can ensure the effective and responsible use of generative AI. Embracing prompt engineering will be crucial for transforming primary care delivery and improving patient outcomes.

Citation: Patil R, Heston TF, Bhuse V. Prompt Engineering in Healthcare. Electronics. 2024;13(15):2961. doi:10.3390/electronics13152961 

Beyond p-values: Assessing Statistical Fragility with Robustness and Percent Fragility Indices

While p-values have been the traditional measure of statistical significance in scientific research, they often fail to capture the complexity of statistical evidence. Fragility metrics such as the robustness index and percent fragility index offer a more nuanced approach to evaluating the strength of research findings. By quantifying the impact of small changes in data on statistical significance, these indices provide a valuable complement to p-values. Incorporating fragility metrics into research practices can be seen as a step toward a more responsible form of data-driven decision-making that recognizes the conditional nature of statistical evidence.

Citation: Heston TF. Redefining significance: robustness and percent fragility indices in biomedical research. Stats. 2024;7(2):537-48. https://doi.org/10.3390/stats7020033 

Balancing the Benefits and Risks of Nuclear Medicine: A Safety Imperative

 Nuclear medicine offers remarkable diagnostic and therapeutic capabilities, revolutionizing patient care. However, the use of radioactive materials presents inherent risks that demand unwavering attention to safety protocols. Regulatory authorities, such as the Nuclear Regulatory Commission, establish comprehensive standards for radiopharmaceutical handling, administration, and disposal. Compliance with these regulations requires specialized training for authorized users, meticulous documentation, and regular safety audits. As nuclear medicine continues to evolve, the integration of advanced technologies and the expansion of theranostic agents further emphasize the need for enhanced safety measures. By fostering a culture of education, accountability, and adherence to best practices, the nuclear medicine community can responsibly harness the power of radioactivity to improve patient outcomes while prioritizing safety.

Citation: Heston TF, Tafti D. Nuclear Medicine Safety. [Updated 2024 Mar 14]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK603730/

The Synergy of AI and Blockchain: Driving the Next Generation of Telemedicine

The convergence of artificial intelligence (AI) in the form of large language models (LLMs) and blockchain technology is poised to drive the next generation of telemedicine. LLMs can rapidly analyze patient records, providing contextualized recommendations and enhancing diagnostic processes. Blockchain technology enables secure, decentralized storage and sharing of medical data, ensuring patient privacy and cross-organizational interoperability. The synergy between these technologies can lead to improved care personalization, automated triage, and secure remote patient monitoring. However, the responsible adoption of AI and blockchain in telemedicine requires addressing challenges such as bias, unclear responsibility, and integration with existing systems while prioritizing patient interests and ethical considerations.

Citation: Heston TF. Perspective Chapter: Integrating Large Language Models and Blockchain in Telemedicine. IntechOpen; 2024. DOI: 10.5772/intechopen.1005063

Study Highlights Limitations of ChatGPT-4 in Cardiac Risk Assessment

 Heston and Lewis conducted a study to evaluate the performance of ChatGPT-4 in risk-stratifying patients with atraumatic chest pain. The researchers compared ChatGPT-4's risk scores with established tools like TIMI and HEART scores using simulated patient data. Although the mean scores correlated well, ChatGPT-4 provided different risk scores for identical patient data when presented on separate occasions. This inconsistency suggests that further refinement and customization are necessary before integrating ChatGPT-4 into clinical practice for cardiac risk assessment.

Citation: Heston TF, Lewis LM (2024) ChatGPT provides inconsistent risk-stratification of patients with atraumatic chest pain. PLOS ONE 19(4): e0301854. https://doi.org/10.1371/journal.pone.0301854