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The experience sampling method as an mHealth tool to support self‐monitoring, self‐insight, and personalized health care in clinical practice
Background The experience sampling method (ESM) builds an intensive time series of experiences and contexts in the flow of daily life, typically consisting of around 70 reports, collected at 8–10 random time points per day over a period of up to 10 days. Methods With the advent of widespread smartphone use, ESM can be used in routine clinical practice. Multiple examples of ESM data collections across different patient groups and settings are shown and discussed, varying from an ESM evaluation of a 6‐week randomized trial of mindfulness, to a twin study on emotion dynamics in daily life. Results Research shows that ESM‐based self‐monitoring and feedback can enhance resilience by strengthening the capacity to use natural rewards. Personalized trajectories of starting or stopping medication can be more easily initiated and predicted if sensitive feedback data are available in real time. In addition, personalized trajectories of symptoms, cognitive abilities, symptoms impacting on other symptoms, the capacity of the dynamic system of mental health to “bounce back” from disturbance, and patterns of environmental reactivity yield uniquely personal data to support shared decision making and prediction in clinical practice. Finally, ESM makes it possible to develop insight into previous implicit patterns of thought, experience, and behavior, particularly if rapid personalized feedback is available. Conclusions ESM enhances clinical practice and research. It is empowering, providing co‐ownership of the process of diagnosis, treatment evaluation, and routine outcome measurement. Blended care, based on a mix of face‐to‐face and ESM‐based outside‐the‐office treatment, may reduce costs and improve outcomes.
Journal Article
Emerging Applications of Nanotechnology in Healthcare and Medicine
Knowing the beneficial aspects of nanomedicine, scientists are trying to harness the applications of nanotechnology in diagnosis, treatment, and prevention of diseases. There are also potential uses in designing medical tools and processes for the new generation of medical scientists. The main objective for conducting this research review is to gather the widespread aspects of nanomedicine under one heading and to highlight standard research practices in the medical field. Comprehensive research has been conducted to incorporate the latest data related to nanotechnology in medicine and therapeutics derived from acknowledged scientific platforms. Nanotechnology is used to conduct sensitive medical procedures. Nanotechnology is showing successful and beneficial uses in the fields of diagnostics, disease treatment, regenerative medicine, gene therapy, dentistry, oncology, aesthetics industry, drug delivery, and therapeutics. A thorough association of and cooperation between physicians, clinicians, researchers, and technologies will bring forward a future where there is a more calculated, outlined, and technically programed field of nanomedicine. Advances are being made to overcome challenges associated with the application of nanotechnology in the medical field due to the pathophysiological basis of diseases. This review highlights the multipronged aspects of nanomedicine and how nanotechnology is proving beneficial for the health industry. There is a need to minimize the health, environmental, and ethical concerns linked to nanotechnology.
Journal Article
Precision oncology in metastatic colorectal cancer — from biology to medicine
Remarkable progress has been made in the development of biomarker-driven targeted therapies for patients with multiple cancer types, including melanoma, breast and lung tumours, although precision oncology for patients with colorectal cancer (CRC) continues to lag behind. Nonetheless, the availability of patient-derived CRC models coupled with in vitro and in vivo pharmacological and functional analyses over the past decade has finally led to advances in the field. Gene-specific alterations are not the only determinants that can successfully direct the use of targeted therapy. Indeed, successful inhibition of BRAF or KRAS in metastatic CRCs driven by activating mutations in these genes requires combinations of drugs that inhibit the mutant protein while at the same time restraining adaptive resistance via CRC-specific EGFR-mediated feedback loops. The emerging paradigm is, therefore, that the intrinsic biology of CRC cells must be considered alongside the molecular profiles of individual tumours in order to successfully personalize treatment. In this Review, we outline how preclinical studies based on patient-derived models have informed the design of practice-changing clinical trials. The integration of these experiences into a common framework will reshape the future design of biology-informed clinical trials in this field.Progress in precision medicine for colorectal cancer continues to lag behind the rapid improvements seen in patients with certain other solid tumour types. Nonetheless, owing largely to the availability of better translational models, novel and effective targeted therapy strategies based on tumour biology are beginning to be developed for subsets of patients. In this Review, the authors summarize these developments and discuss future directions in this rapidly evolving area of research.
Journal Article
A mixed methods process evaluation of the implementation of a peer coaching intervention to improve the execution of preventive tasks by occupational physicians
Objectives
This study aimed to evaluate the process of implementation of a peer coaching intervention program for occupational physicians (OPs) to improve the execution of preventive tasks. Specifically, the evaluation seeks to: (1) describe the reach and uptake of the intervention program; (2) determine the extent to which the program was implemented as intended; (3) provide insights into experiences of OPs, and (4) identify factors influencing the implementation.
Methods
This study employed a mixed-methods design. To address the four research aims, seven process indicators were used: acceptability, adoption, appropriateness, feasibility, fidelity, penetration and sustainability. Data were collected between March and June 2024 by means of an online questionnaire (
N
= 98), and 17 semi-structured interviews with group coordinators and OPs. The questionnaire included questions on attendance and reasons for non-attendance, experiences, and ratings of several aspects of the intervention program. Interviews focused on why and how OPs participated, experiences with the intervention program and how it can be improved, and how attention to prevention can be sustained.
Results
Reach and uptake: 20 out of 21 groups allocated to the intervention program participated in the intervention and 98 out of 115 participants (85%) filled in the questionnaire. Three-quarters of the participants completed the entire program. Implementation as intended: 96% of the OPs successfully discussed barriers to the execution of preventive tasks, and 83% were able to formulate strategies for these barriers. Barriers and facilitators: Most participants managed to implement their formulated goals in practice. When they were unable to do so, time constraints and resistance from employers and their occupational health services often played a role. Participants’ experiences: OPs valued the program’s structure, interaction with colleagues, and the increased awareness it generated.
Discussion and conclusion
The peer coaching group program was well-implemented and positively evaluated by OPs. The program can be improved by allocating more time to it, for instance by integrating it into the educational curriculum, and by paying more attention to the specific working conditions of OPs, such as the different sectors in which they are employed.
Trial registration
ISRCTN registry; ISRCTN15394765. Registered on 27 June 2023.
Journal Article
Artificial intelligence for individualized treatment of persistent atrial fibrillation: a randomized controlled trial
Although pulmonary vein isolation (PVI) has become the cornerstone ablation procedure for atrial fibrillation (AF), the optimal ablation procedure for persistent and long-standing persistent AF remains elusive. Targeting spatio-temporal electrogram dispersion in a tailored procedure has been suggested as a potentially beneficial alternative to a conventional PVI-only procedure. In this multicenter, randomized, controlled, double-blind, superiority trial, patients with drug-refractory persistent AF were randomly assigned to a tailored ablation procedure targeting areas of spatio-temporal dispersion, as detected by an artificial intelligence (AI) algorithm, in addition to PVI (tailored arm,
n
= 187, 23% women) or to a conventional PVI-only procedure (anatomical arm,
n
= 183, 19% women). The primary efficacy endpoint was freedom from documented AF with or without antiarrhythmic drugs at 12 months after a single ablation procedure. Secondary endpoints included freedom from any atrial arrhythmic events, and the secondary composite safety endpoint consisted of death, cerebrovascular events, or treatment-related serious adverse events. One year post-procedure, the trial met its primary efficacy endpoint, which was achieved in 88% of patients in the tailored arm compared with 70% of patients in the anatomical arm (log-rank
P
< 0.0001 for superiority). However, no significant difference between arms was observed for the freedom from any atrial arrhythmia endpoint after one ablation. The safety endpoint did not differ between arms, with procedure and ablation times being twice as long in the tailored arm. These results show that AI-guided ablation of spatio-temporal dispersion areas in addition to PVI is superior to PVI alone in eliminating AF at 1-year follow-up in patients with persistent and long-standing persistent AF. Ablation of subsequent organized atrial tachycardias may be needed to maintain sinus rhythm long term. ClinicalTrials.gov identifier:
NCT04702451
.
In a randomized controlled trial in individuals with persistent atrial fibrillation, an individualized ablation procedure, in which areas with abnormal electrophysiological characteristics—as detected by an AI algorithm—were targeted for ablation, led to improved efficacy for reducing arrhythmia recurrence at 12 months following the ablation procedure.
Journal Article