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Behavioral science, the scientific study of human behavior and the elucidation of its laws, is also applied to medicine, and is included in pre‐graduate education.Understanding patient behaviors that correspond to behavior‐based medical diagnosis and interpreting the clinical information suggested by these patient behaviors can be useful in avoiding diagnostic errors in clinical practice. [ABSTRACT FROM AUTHOR]

Background: Telediagnosis (TD), which uses information and communications technology, has recently undergone rapid development. Since no studies have compared the diagnostic precision of TD to that of face-to-face diagnosis (FD), we examined and compared the diagnostic accuracy of these diagnostic approaches among general medicine outpatients. Methods: Data of 97 patients (45 men and 52 women with a mean age of 52 years) who underwent initial examinations at a regional hospital were analyzed. Two fully trained general medicine physicians were selected from a group of three physicians to perform FD and TD. Levels of agreement (as κ coefficients) were determined between TD and FD diagnoses as well as between final diagnoses and TD and FD diagnoses. Results: The κ coefficients were 0.75 for TD and FD and 0.81 for both, the final diagnoses and the TD and FD diagnoses, revealing a sufficiently high level of diagnostic agreement. Conclusions: TD can provide the same level of diagnostic accuracy as FD among general medicine outpatients for adults. The help of medical assistants and the utilization of physical examination devices might enable medical staff to provide TD care similar in quality to FD. TD could be a useful diagnostic tool when medical work force is limited (e.g., in remote areas, during natural disasters, and in at-home care). [ABSTRACT FROM AUTHOR]

Background: Evidence for the pathogenesis and treatment of postacute coronavirus disease 2019 (COVID-19) (long COVID) is lacking. As long COVID symptoms are predicted to have an impact on the global economy, clarification of the pathogenesis is urgently needed. Our experiences indicated that some symptoms were complicated by diseases established before the COVID-19 pandemic., Methods: Using a retrospective, cross-sectional study, we aimed to evaluate the diseases complicating long COVID. Using the medical records of patients with confirmed COVID-19 exhibiting residual symptoms lasting ≥60 days postinfection who visited our clinic in January 2021-February 2023, we investigated the symptoms and diseases observed. We identified diseases that occurred after COVID-19 and excluded those that were exacerbations of existing diseases., Results: During the first visit, the most common symptoms reported in a total of 798 patients were fatigue (523 patients), anxiety (349 patients), and lack of motivation (344 patients). Complicating diseases were observed in 452 patients (57%). There were 115, 65, and 60 patients with postural tachycardia syndrome, postural syndrome without tachycardia, and mood disorders, respectively. Some diseases requiring immediate treatment included pulmonary thromboembolism, purulent shoulder arthritis, cerebellopontine angle tumors, myasthenia gravis, and cervical myelopathy., Conclusion: Not all symptoms that occur after COVID-19 should be treated as long COVID. Similar to normal medical treatment, a list of differential diagnoses should be maintained based on symptoms to obtain definitive diagnoses., Competing Interests: The authors declare no conflict of interest for this article., (© 2024 The Author(s). Journal of General and Family Medicine published by John Wiley & Sons Australia, Ltd on behalf of Japan Primary Care Association.)

This study tests whether comprehensively gathering information from medical records is useful for developing clinical decision support systems using Bayes' theorem. Using a single-center cross-sectional study, we retrospectively extracted medical records of 270 patients aged ≥16 years who visited the emergency room at the Tokyo Metropolitan Tama Medical Center with a chief complaint of experiencing headaches. The medical records of cases were analyzed in this study. We manually extracted diagnoses, unique keywords, and annotated keywords, classifying them as either positive or negative. Cross tables were created, and the proportion of combinations for which the likelihood ratios could be calculated was evaluated. Probability functions for the appearance of new unique keywords were modeled, and theoretical values were calculated. We extracted 623 unique keywords, 26 diagnoses, and 6,904 annotated keywords. Likelihood ratios could be calculated only for 276 combinations (1.70%), of which 24 (0.15%) exhibited significant differences. The power function+constant was the best fit for new unique keywords. The increase in the number of combinations after increasing the number of cases indicated that while it is theoretically possible to comprehensively gather information from medical records in this way, doing so presents difficulties related to human costs. It also does not necessarily solve the fundamental issues with medical informatics or with developing clinical decision support systems. Therefore, we recommend using methods other than comprehensive information gathering with Bayes' theorem as the classifier to develop such systems., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Yokokawa et al.)

Background: Mentorship is a dynamic reciprocal relationship, wherein a novice (mentee) grows with the encouragement of an advanced careerist (mentor). It is widely implemented in medical training programs. However, there are few reports on mentorship's educational effects in the Japanese context. This study investigated the association between mentorship and in-training examination scores during a clinical residency program in Japan., Methods: A cross-sectional study was conducted in Japan, involving first and second year postgraduate (PGY-1 and PGY-2) residents set to take the General Medicine In-Training Examination (GM-ITE) at the end of the academic year of 2021. The GM-ITE, developed by a non-profit organization in 2012, assesses the overall clinical knowledge of PGY-1 and PGY-2 residents. Data on mentorship were obtained through an electronic survey, conducted immediately after the GM-ITE. The association between a resident's self-reported identification of at least one mentor and GM-ITE score was analyzed at multiple levels., Results: Of the total 4929 residents, 3266 (66.3%) reported having mentors. However, there was no association between mentorship and GM-ITE scores (adjusted score difference [aSD] = -0.22; 95% confidence interval [95% CI]: -0.64 to 0.19)., Conclusions: Among Japanese residents, in-training examination scores were not associated with mentorship., Competing Interests: Dr. Yuji Nishizaki received an honorarium from the JAMEP as the General Medicine In‐Training Examination (GM‐ITE) project manager. Dr. Yasuharu Tokuda is the JAMEP director, and he received an honorarium from JAMEP as a speaker of the JAMEP lecture. Dr. Taro Shimizu and Dr. Yu Yamamoto received an honorarium from JAMEP for their roles as exam preparers of GM‐ITE. Dr. Yuji Nishizaki and Dr. Takashi Watari are the Editorial Board members of the Journal of General and Family Medicine and co‐authors of this article. To minimize bias, they were excluded from all editorial decision making related to the acceptance of this article for publication., (© 2024 The Author(s). Journal of General and Family Medicine published by John Wiley & Sons Australia, Ltd on behalf of Japan Primary Care Association.)

Background: Mentorship is a dynamic, reciprocal relationship in which an advanced careerist (mentor) encourages the growth of a novice (mentee). Mentorship may protect the mental health of residents at risk for depression and burnout, yet despite its frequent use and known benefits, limited reports exist regarding the prevalence and mental effects of mentorship on residents in Japan., Methods: We conducted a cross-sectional study involving postgraduate year 1 and 2 (PGY-1 and PGY-2) residents in Japan who took the General Medicine In-Training Examination (GM-ITE) at the end of the 2021 academic year. Data on mentorship were collected using surveys administered immediately following GM-ITE completion. The primary outcome was the Patient Health Questionaire-2 (PHQ-2), which consisted depressed mood and loss of interest. A positive response for either item indicated PHQ-2 positive. We examined associations between self-reported mentorship and PHQ-2 by multi-level analysis., Results: Of 4929 residents, 3266 (66.3%) residents reported having at least one mentor. Compared to residents without any mentor, those with a mentor were associated with a lower likelihood of a positive PHQ-2 response (adjusted odds ratio [aOR] 0.75; 95% confidence interval [95% CI] 0.65-0.86). Mentor characteristic significantly associated with negative PHQ-2 response was a formal mentor (aOR; 0.68; 95% CI 0.55-0.84)., Conclusions: A mentor-based support system was positively associated with residents' mental health. Further research is needed to determine the quality of mentorship during clinical residency in Japan., Competing Interests: Dr. Yuji Nishizaki received an honorarium from the JAMEP as the General Medicine In‐Training Examination (GM‐ITE) project manager. Dr. Yuji Nishizaki and Dr Takashi Watari are Editorial Board members of Journal of General and Family Medicine and co‐authors of this article. To minimize bias, he was excluded from all editorial decision‐making related to the acceptance of this article for publication. Dr. Yasuharu Tokuda is the JAMEP director, and he received an honorarium from JAMEP as a speaker of the JAMEP lecture., (© 2023 The Authors. Journal of General and Family Medicine published by John Wiley & Sons Australia, Ltd on behalf of Japan Primary Care Association.)

Background: Coronavirus disease 2019 (COVID-19) sequelae, also known as long COVID, can present with various symptoms. Among these symptoms, autonomic dysregulation, particularly postural orthostatic tachycardia syndrome (POTS), should be evaluated. However, previous studies on the treatment of POTS complicated by COVID-19 are lacking. Therefore, this study aimed to investigate the treatment course of long COVID complicated by POTS., Methods: The medical records of patients who complained of fatigue and met the criteria for POTS diagnosis were reviewed. We evaluated the treatment days, methods and changes in fatigue score, changes in heart rate on the Schellong test, and social situation at the first and last visits., Results: Thirty-two patients with long COVID complicated by POTS were followed up (16 males; median age: 28 years). The follow-up period was 159 days, and the interval between COVID-19 onset and initial hospital attendance was 97 days. Some patients responded to β-blocker therapy. Many patients had psychiatric symptoms that required psychiatric intervention and selective serotonin reuptake inhibitor prescription. Changes in heart rate, performance status, and employment/education status improved from the first to the last visit. These outcomes were believed to be because of the effects of various treatment interventions and spontaneous improvements., Conclusions: Our study suggests that the condition of 94% of patients with POTS complicated by long COVID will improve within 159 days. Therefore, POTS evaluation should be considered when patients with long COVID complain of fatigue, and attention should be paid to psychological symptoms and the social context., Competing Interests: The authors have stated explicitly that there are no conflicts of interest in connection with this article., (© 2023 The Authors. Journal of General and Family Medicine published by John Wiley & Sons Australia, Ltd on behalf of Japan Primary Care Association.)

Prolonged symptoms that occur after COVID-19 (long-COVID) vary from mild, which do not interfere with daily life, to severe, which require long-term social support. This study assessed the secular trend in online searches on long-COVID in Japan. We conducted an observational study using data provided by Yahoo! JAPAN on the monthly search volume of query terms related to long-COVID from January 2020 to December 2022, including the search volume of the query "コロナ" (long-COVID in Japanese). The number of new cases of COVID-19 by month was used as a control for search trends, and the symptoms retrieved in conjunction with long-COVID were compared. Trends in online searches for each symptom of long-COVID were analyzed. The symptoms of long-COVID were classified according to "Component 1-Symptoms and Complaints" of the International Classification of Primary Care, 2nd edition (ICPC-2). Interest in long-COVID increased in response to peaks in the number of new cases of COVID-19 in Japan. The most frequent symptom searches with long-COVID were hair loss/baldness (3,530, 21,400, and 33,600 searches in 2020, 2021, and 2022, respectively), cough (340, 7,900 and 138,910 searches in 2020, 2021, and 2022, respectively), disturbance of smell/taste (230, 13,340, and 44,160 searches in 2020, 2021, and 2022, respectively), and headache (580, 6,180, and 42,870 searches in 2020, 2021, and 2022, respectively). In addition, the ranking of interest in "weakness/tiredness, general" in long-COVID increased each year (not in the top 10 in 2020, seventh in 2021, and second in 2022), and the absolute number of searches also increased. To our knowledge, this is the first study to investigate secular trends in online interest in long-COVID in the world. Continued monitoring of online interest in long-COVID is necessary to prepare for a possible increase in the number of patients with long-COVID., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ishizuka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: The long-term symptoms of coronavirus disease 2019 (COVID-19), i.e., long COVID, have drawn research attention. Evaluating its subjective symptoms is difficult, and no established pathophysiology or treatment exists. Although there are several reports of long COVID classifications, there are no reports comparing classifications that include patient characteristics, such as autonomic dysfunction and work status. We aimed to classify patients into clusters based on their subjective symptoms during their first outpatient visit and evaluate their background for these clusters., Methods: Included patients visited our outpatient clinic between January 18, 2021, and May 30, 2022. They were aged ≥ 15 years and confirmed to have SARS-CoV-2 infection and residual symptoms lasting at least 2 months post-infection. Patients were evaluated using a 3-point scale for 23 symptoms and classified into five clusters (1. fatigue only; 2. fatigue, dyspnea, chest pain, palpitations, and forgetfulness; 3. fatigue, headache, insomnia, anxiety, motivation loss, low mood, and forgetfulness; 4. hair loss; and 5. taste and smell disorders) using CLUSTER. For continuous variables, each cluster was compared using the Kruskal-Wallis test. Multiple comparison tests were performed using the Dunn's test for significant results. For nominal variables, a Chi-square test was performed; for significant results, a residual analysis was conducted with the adjusted residuals., Results: Compared to patients in other cluster categories, those in cluster categories 2 and 3 had higher proportions of autonomic nervous system disorders and leaves of absence, respectively., Conclusions: Long COVID cluster classification provided an overall assessment of COVID-19. Different treatment strategies must be used based on physical and psychiatric symptoms and employment factors., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Objective: The pathophysiological concepts of diseases are encapsulated in patients' medical histories. Whether information on the pathophysiology or anatomy of "infarction" can be preserved and objectively expressed in the distributed representation obtained from a corpus of scientific Japanese medical texts in the "infarction" domain is currently unknown. Word2Vec was used to obtain distributed representations, meanings, and word analogies of word vectors, and this process was verified mathematically., Materials & Methods: The texts were abstracts that were obtained by searching for "infarction," "abstract," and "case report" in the Japan Medical Journal Association's Ichushi Data Base. The abstracted text was morphologically analyzed to produce word sequences converted into their standard form. MeCab was used for morphological analysis and mecab-ipadic-NEologd and ComeJisyo were used as dictionaries. The accuracy of the known tasks for medical terms was evaluated using a word analogy task specific to the "infarction" domain., Results: Only 33 % of the word analogy tasks for medical terminology were correct. However, 52 % of the new original tasks, which were specific to the "infarction" domain, were correct, especially those regarding anatomical differences., Discussion: Documents related to "infarction" were collected from a corpus of Japanese medical documents and word-embedded expressions were obtained using Word2Vec. Terminology that had similar meanings to "infarction" included words such as "cavity" and "ischemia," which suggest the pathology of an infarction., Conclusion: The pathophysiological and anatomical features of an "infarction" may be retained in a distributed representation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Competing Interests: Competing interests: None declared.

Towards early detection of Alzheimer dementia (AD), this paper focuses on time-series instability of heart rate of AD patient, and proposes the AD detection method based on heart rate acquired by an unconstrained mattress sensor for daily life use. Through the human subject experiments on 124 days of heart rate of one AD patient and 39 days of heart rate of 21 healthy subjects, the following implication have been revealed: (1) an accuracy of the proposed AD detection method based on the time-series features of heart rate is approximately 98%; and (2) the time-series instability of heart rate is found in the rapid oscillation of heart rate (i.e., an increase/decrease of heart rate over 2 seconds).

Background: To investigate whether speech recognition software for generating interview transcripts can provide more specific and precise feedback for evaluating medical interviews., Methods: The effects of the two feedback methods on student performance in medical interviews were compared using a prospective observational trial. Seventy-nine medical students in a clinical clerkship were assigned to receive either speech-recognition feedback (n = 39; SRS feedback group) or voice-recording feedback (n = 40; IC recorder feedback group). All students' medical interviewing skills during mock patient encounters were assessed twice, first using a mini-clinical evaluation exercise (mini-CEX) and then a checklist. Medical students then made the most appropriate diagnoses based on medical interviews. The diagnostic accuracy, mini-CEX, and checklist scores of the two groups were compared., Results: According to the study results, the mean diagnostic accuracy rate (SRS feedback group:1st mock 51.3%, 2nd mock 89.7%; IC recorder feedback group, 57.5%-67.5%; F(1, 77) = 4.0; p = 0.049), mini-CEX scores for overall clinical competence (SRS feedback group: 1st mock 5.2 ± 1.1, 2nd mock 7.4 ± 0.9; IC recorder feedback group: 1st mock 5.6 ± 1.4, 2nd mock 6.1 ± 1.2; F(1, 77) = 35.7; p < 0.001), and checklist scores for clinical performance (SRS feedback group: 1st mock 12.2 ± 2.4, 2nd mock 16.1 ± 1.7; IC recorder feedback group: 1st mock 13.1 ± 2.5, 2nd mock 13.8 ± 2.6; F(1, 77) = 26.1; p < 0.001) were higher with speech recognition-based feedback., Conclusions: Speech-recognition-based feedback leads to higher diagnostic accuracy rates and higher mini-CEX and checklist scores., Trial Registration: This study was registered in the Japan Registry of Clinical Trials on June 14, 2022. Due to our misunderstanding of the trial registration requirements, we registered the trial retrospectively. This study was registered in the Japan Registry of Clinical Trials on 7/7/2022 (Clinical trial registration number: jRCT1030220188)., (© 2023. The Author(s).)