Background: Psychoeducation positively influences the psychological components of chronic low back pain (CLBP) in conventional treatments. The digitalization of health care has led to the discussion of virtual reality (VR) interventions. However, CLBP treatments in VR have some limitations due to full immersion. In comparison, augmented reality (AR) supplements the real world with virtual elements involving one's own body sensory perception and can combine conventional and VR approaches.
Objective: The aim of this study was to review the state of research on the treatment of CLBP through psychoeducation, including immersive technologies, and to formulate suggestions for psychoeducation in AR for CLBP.
Methods: A scoping review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was performed in August 2024 by using Livivo ZB MED, PubMed, Web of Science, American Psychological Association PsycINFO (PsycArticle), and PsyArXiv Preprints databases. A qualitative content analysis of the included studies was conducted based on 4 deductively extracted categories.
Results: We included 12 studies published between 2019 and 2024 referring to conventional and VR-based psychoeducation for CLBP treatment, but no study referred to AR. In these studies, educational programs were combined with physiotherapy, encompassing content on pain biology, psychological education, coping strategies, and relaxation techniques. The key outcomes were pain intensity, kinesiophobia, pain catastrophizing, degree of disability, quality of life, well-being, self-efficacy, depression, attrition rate, and user experience. Passive, active, and gamified strategies were used to promote intrinsic motivation from a psychological point of view. Regarding user experience from a software development perspective, user friendliness, operational support, and application challenges were recommended.
Conclusions: For the development of a framework for an AR-based psychoeducational intervention for CLBP, the combination of theories of acceptance and use of technologies with insights from health psychological behavior change theories appears to be of great importance. An example of a theory-based design of a psychoeducation intervention in AR for CLBP is proposed and discussed.
Unstructured: Physicians could improve the efficiency of the healthcare system if a reliable resource were available to aid them in better understanding, selecting, and interpreting the diagnostic laboratory tests. It has been well established and widely recognized that (a) laboratory testing provides 70-85% of the objective data that physicians use in diagnosis and treatment of their patients, (b) orders for laboratory tests in the U.S. have increased with an estimated volume of 4-5 billion tests per year , (c) there is a lack of user friendly tools to guide physicians in their test selection and ordering, and (d) laboratory test overutilization and underutilization continue to represent a pervasive source of inefficiency in healthcare system. These inappropriate tests ordering not only lead to slower or incorrect diagnoses for patients but also add a significant financial burden. In addition, many ordered tests are not reimbursed from Medicare because they are not appropriate for the medical condition or were ordered with the wrong ICD-10 diagnostic code, not meeting the medical necessity. Therefore, current clinical laboratory test ordering procedures suffer from a quality gap. Often providers do not have access to an appropriate tool that uses evidence-based guidelines or algorithms to make sure that tests are not duplicated, over-, or under-utilized. This viewpoint lays out potential use of an automated laboratory Clinical Decision Support System (CDDS) that helps providers to order the right test for the right disease and documents the right reason or medical necessity to pay for the testing.
Background: Adherence to antiretroviral therapy is a critical component in achieving viral suppression in people living with HIV in addition to increasing overall quality of life. Several indirect methods have been used to measure adherence including the Simplified Medication Adherence Questionnaire (SMAQ).
Objective: The objective of this study is to evaluate the reliability and validity of the SMAQ in men living with HIV/AIDS attending a Mexican national hospital.
Methods: A cross-sectional analytical design study was carried out in a Mexican National Hospital in Jalisco, including men aged >18 years with at least 3 months of antiretroviral treatment, excluding those with cognitive difficulties in answering the survey. A minimum sample size was calculated to detect the contribution of the variables within the model. The analysis included descriptive tests, confirmatory factor analysis, reliability and validity assessment, correlation between adherence and viral load, and association between viral load and adherence.
Results: The final analysis included a total of 260 patients with a mean age of 43 (SD 12) years and an average of 8.97 (SD 6.33) years on antiretroviral treatment. The SMAQ showed sufficient structural validity (comparative fit index=1, root-mean-square error of approximation=0, 90% CI 0-0.085) with satisfactory factor loadings on most questions except item 2 (Do you always take your medication at the prescribed time?). The reliability of the scale is acceptable (Cronbach α=0.702, ω=0.718). Adherence correlated with viral load significantly but not with recent TCD4 lymphocyte levels. Patients classified as adherent were three times more likely to be undetectable than nonadherent patients (odds ratio 3.31, 95% CI 1.13-9.64, P=.04).
Conclusions: The SMAQ represents an adequate tool to assess adherence in men living with HIV in the Mexican context, this will contribute to this study and compression of adherence to establish future intervention programs.
Background: Research on personality types among doctors reveals its impact on medical specialty choices, suggesting that considering personality in career planning may enhance work satisfaction and reduce burnout risks.
Objective: This study, encompassing 2104 medical students, explores how personality types, traits, and gender relate to specialty preferences.
Methods: Participants of this study were medical students from various universities in Poland. The study surveyed 2104 participants. Each participant completed a general questionnaire and a NERIS Type Explorer personality test, based on the Myers-Briggs Type Indicator inventory and the "Big Five" personality traits concept. The questionnaire was distributed on social media groups for medical students from all Polish universities. An exploratory statistical analysis was performed to find relationships. For each tested relationship a Fisher exact test was conducted and the significance level was P<.05. Each test resulted in a P value and odds ratio (OR) with a CI. To ensure we included undecided students and obtained meaningful data, we allowed participants to select up to three medical specialties from the 77 available in Poland at the time of the study.
Results: The findings unveil significant relationships between gender, personality types, traits, and specialty preferences. Women tended to favor Neonatology (OR 9.15, 95% CI 3.02-45.46), while men leaned toward Orthopedics and traumatology of the locomotor system (OR 7.53, 95% CI 4.87-11.94). Extroverted, Intuitive, Feeling, Prospecting, and Turbulent students showed a heightened interest in Psychiatry (OR 2.23, 95% CI 1.64-3.01), whereas Introverted, Observant, Feeling, Judging, and Turbulent types favored Family Medicine (OR 2.98, 95% CI 2.08-4.24) and Pediatrics (OR 2.13, 95% CI 1.51-2.99).
Conclusions: In conclusion, this research establishes a link between personality and medical specialty selection. Taking into account the significant role of personality traits, it should be considered to integrate them into the process of selecting a medical career or designing a medical curriculum. This approach may allow for the customization of programs to match students' traits, thereby cultivating improved clinical communication skills, fostering interprofessional collaboration and ultimately enhancing treatment outcomes and professional fulfillment among physicians. The main limitation of this study is that it was conducted on medical students, who lack the full knowledge of the work as a specific specialist. A study surveying medical doctors with longer internships across different wards could be conducted to check for any variabilities. Moreover, there are other significant factors that influence one's medical specialty choice. Certainly, this area could be further explored.
Government policies in the United States and the European Union promote standardization and value creation in the use of FAIR (findability, accessibility, interoperability, and reusability) data, which can enhance trust in digital health systems and is crucial for their success. Trust is built through elements such as FAIR data access, interoperability, and improved communication, which are essential for fostering innovation in digital health technologies. This Viewpoint aims to report on exploratory research demonstrating the feasibility of testing a patient-centric data flow model facilitating semantic interoperability on precision medical information. In this global trend, the interoperable interface called Sync for Science-J (S4S-J) for linking electronic medical records (EMRs) and personal health records was launched as part of the Basic Policy for Economic and Fiscal Management and Reform in Japan. S4S-J controls data distribution consisting of EMR and patient-generated health data and converts this information into QR codes that can be scanned by mobile apps. This system facilitates data sharing based on personal information beliefs and unlocks siloed Internet of Things systems with a privacy preference manager. In line with Japanese information handling practices, the development of a mobile cloud network will lower barriers to entry and enable accelerated data sharing. To ensure cross-compatibility and compliance with future international data standardization, S4S-J conforms to the Health Level 7 Fast Health Care Interoperability Resources standard and uses the international standardized logical observation identifiers names and codes (LOINC) to redefine medical terms used in different terminology standards in different medical fields. It is developed as an applied standard in medical information intended for industry, health care services, and research through secondary use of data. A multicenter collaborative study was initiated to investigate the effectiveness of this system; this was a registered, multicenter, randomized controlled clinical trial, the EMBRACE study of the mobile health app M♡Link for hyperglycemic disorders in pregnancy, which implements an EMR-personal health record interoperable interface via S4S-J. Nevertheless, the aforementioned new challenges, the pivotal Health Level 7 Fast Health Care Interoperability Resources system, and LOINC data mapping were successfully implemented. Moreover, the preliminary input of EMR-integrated patient-generated health data was successfully shared between authorized medical facilities and health care providers in accordance with the patients' preferences. The patient-centric data flow of the S4S-J in Japan is expected to guarantee the right to data portability, which promotes the maximum benefit of use by patients themselves, which in turn contributes to the promotion of open science.
Background: Artificial intelligence is experiencing rapid growth, with continual innovation and advancements in the health care field.
Objective: This study aims to evaluate the application of artificial intelligence technologies across various domains of respiratory care.
Methods: We conducted a narrative review to examine the latest advancements in the use of artificial intelligence in the field of respiratory care. The search was independently conducted by respiratory care experts, each focusing on their respective scope of practice and area of interest.
Results: This review illuminates the diverse applications of artificial intelligence, highlighting its use in areas associated with respiratory care. Artificial intelligence is harnessed across various areas in this field, including pulmonary diagnostics, respiratory care research, critical care or mechanical ventilation, pulmonary rehabilitation, telehealth, public health or health promotion, sleep clinics, home care, smoking or vaping behavior, and neonates and pediatrics. With its multifaceted utility, artificial intelligence can enhance the field of respiratory care, potentially leading to superior health outcomes for individuals under this extensive umbrella.
Conclusions: As artificial intelligence advances, elevating academic standards in the respiratory care profession becomes imperative, allowing practitioners to contribute to research and understand artificial intelligence's impact on respiratory care. The permanent integration of artificial intelligence into respiratory care creates the need for respiratory therapists to positively influence its progression. By participating in artificial intelligence development, respiratory therapists can augment their clinical capabilities, knowledge, and patient outcomes.
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