Identification of Recent Trends in Research on Vitamin D: A Quantitative and Co-Word Analysis

Yang, Aolin; Lv, Qingqing; Chen, Feng; Wang, Difei; Liu, Ying; Shi, Wanying

doi:10.12659/msm.913026

Cited by 35 publications

(26 citation statements)

References 38 publications

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“…Cluster analysis of these words based on co-occurrence frequency can reflect the association between multiple words [36]. Co-occurrence of keywords was considered to be the main approach for identifying research themes and knowledge structure by displaying the relationship between keywords [37]. This study used the co-occurrence analysis and clustering analysis methods to study the relationship between multiple questions from patients with hypertension on the internet.…”

Section: Co-occurrence Analysis and Clustering Analysismentioning

confidence: 99%

Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study

Luo¹,

Xin²,

Yuan³

et al. 2020

J Med Internet Res

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Background With the rapid development of online health communities, increasing numbers of patients and families are seeking health information on the internet. Objective This study aimed to discuss how to fully reveal the health information needs expressed by patients with hypertension in their questions in a web-based environment and how to use the internet to help patients with hypertension receive personalized health education. Methods This study randomly selected 1000 text records from the question data of patients with hypertension from 2008 to 2018 collected from Good Doctor Online and constructed a classification system through literature research and content analysis. This paper identified the background characteristics and questioning intention of each patient with hypertension based on the patient’s question and used co-occurrence network analysis and the k-means clustering method to explore the features of the health information needs of patients with hypertension. Results The classification system for the health information needs of patients with hypertension included the following nine dimensions: drugs (355 names), symptoms and signs (395 names), tests and examinations (545 names), demographic data (526 kinds), diseases (80 names), risk factors (37 names), emotions (43 kinds), lifestyles (6 kinds), and questions (49 kinds). There were several characteristics of the explored web-based health information needs of patients with hypertension. First, more than 49% of patients described features, such as drugs, symptoms and signs, tests and examinations, demographic data, and diseases. Second, patients with hypertension were most concerned about treatment (778/1000, 77.80%), followed by diagnosis (323/1000, 32.30%). Third, 65.80% (658/1000) of patients asked physicians several questions at the same time. Moreover, 28.30% (283/1000) of patients were very concerned about how to adjust the medication, and they asked other treatment-related questions at the same time, including drug side effects, whether to take the drugs, how to treat the disease, etc. Furthermore, 17.60% (176/1000) of patients consulted physicians about the causes of clinical findings, including the relationship between the clinical findings and a disease, the treatment of a disease, and medications and examinations. Fourth, by k-means clustering, the questioning intentions of patients with hypertension were classified into the following seven categories: “how to adjust medication,” “what to do,” “how to treat,” “phenomenon explanation,” “test and examination,” “disease diagnosis,” and “disease prognosis.” Conclusions In a web-based environment, the health information needs expressed by Chinese patients with hypertension to physicians are common and distinct, that is, patients with different background features ask relatively common questions to physicians. The classification system constructed in this study can provide guidance to health information service providers for the construction of web-based health resources, as well as guidance for patient education, which could help solve the problem of information asymmetry in communication between physicians and patients.

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Section: Co-occurrence Analysis and Clustering Analysismentioning

confidence: 99%

Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study

Luo¹,

Xin²,

Yuan³

et al. 2020

J Med Internet Res

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“…In the light of the evidence from various groups regarding the beneficiary effect of these vitamins, we investigated their interaction with the Spike protein. There are two forms of vitamin D—cholecalciferol (vitamin D3) and ergocalciferol (vitamin D2) [ 44 ]. Here, we found that vitamin C (∆G = −2.95 kcal/Mol) and vitamin D3 (∆G = −5.52 kcal/Mol) can directly interact with the Spike protein of SARS-CoV-2 ( Table S3 ), which further reaffirmed the possibility of their use as a drug for the treatment of COVID-19.…”

Section: Discussionmentioning

confidence: 99%

Viroinformatics-Based Analysis of SARS-CoV-2 Core Proteins for Potential Therapeutic Targets

Agrawal

Poullikkas

et al. 2021

Antibodies

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SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel coronavirus for which no known effective antiviral drugs are available. In the present study, to accelerate the discovery of potential drug candidates, bioinformatics-based in silico drug discovery approaches are utilized. We performed multiple sequence alignments of the Spike (S) protein with 75 sequences of different viruses from the Orthocoronavirinae subfamily. This provided us with insights into the evolutionarily conserved domains that can be targeted using drugs or specific antibodies. Further, we analyzed the mechanism of SARS-CoV-2 core proteins, i.e., S and RdRp (RNA-dependent RNA polymerase), to elucidate how the virus infection can utilize hemoglobin to decrease the blood oxygen level. Moreover, after a comprehensive literature survey, more than 60 antiviral drugs were chosen. The candidate drugs were then ranked based on their potential to interact with the Spike and RdRp proteins of SARS-CoV-2. The present multidimensional study further advances our understanding of the novel viral molecular targets and potential of computational approaches for therapeutic assessments. The present study can be a steppingstone in the selection of potential drug candidates to be used either as a treatment or as a reference point when designing a new drug/antibody/inhibitory peptide/vaccine against SARS-CoV-2.

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“…The impact of LVC de-implementation on the patient experience may be service-speci c. In the present survey, not receiving LVC-vitamin D resulted in a greater impact to the patient-clinician relationship than the three other services. While this nding may be associated with the popularity of vitamin D in the scienti c literature and popular media, 45,46 further research on variation in patient-reported outcomes in response to de-implementation at the service level is needed.…”

Section: Discussionmentioning

confidence: 99%

Does De-Implementation of Low Value Care Impact the Patient-Clinician Relationship? A Mixed Methods Study

Rockwell¹,

Michaels²,

Epling³

2021

Preprint

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Background: The importance of reducing low-value care (LVC) is increasingly recognized, but the impact of de-implementation on the patient-clinician relationship is not well understood. This mixed-methods study explored the impact of LVC de-implementation on the patient-clinician relationship. Methods: Adult primary care patients from a large Virginia health system volunteered to participate in a survey (n=232) or interview (n=24). Participants completed the Patient-Doctor Relationship Questionnaire (PDRQ-9) after reading a vignette about a clinician declining to provide a low-value service: antibiotics for acute sinusitis (LVC-antibiotics); screening EKG (LVC-EKG); screening vitamin D test (LVC-vitamin D); or a comparison vignette about a high-value service, and imagining that their own primary care clinician had acted in the same manner. A different sample of participants was asked to imagine that their own primary care clinician did not order LVC-antibiotics or LVC-EKG and then respond to semi-structured interview questions. Outcomes data included participant demographics, PDRQ-9 scores (higher score = greater relationship integrity), and content analysis of transcribed interviews. Differences in PDRQ-9 scores were analyzed using one-way ANOVA. Data were integrated for analysis and interpretation. Results: Although participants generally agreed with the vignette narrative (not providing LVC), many demonstrated difficulty comprehending the broad concept of LVC and potential harms. The topic triggered memories of negative experiences with healthcare (typically poor-quality care, not necessarily LVC). The most common recommendation for reducing LVC was for patients to take greater responsibility for their own health. Most participants believed that their relationship with their clinician would not be negatively impacted by not receiving the described service because they trusted their clinician’s guidance. Participants emphasized that trusted clinicians are those who listen to them, spend time with them, and offer understandable advice. Some felt that not providing LVC would actually increase their trust in their clinician. Similar PDRQ-9 scores were observed for LVC-antibiotics (38.9), LVC-EKG (37.5), and the comparison vignette (36.4), but LVC-vitamin D was associated with a significantly lower score (31.2) (p<0.05). Conclusions: Findings suggest minimal impact of LVC de-implementation on the patient-clinician relationship, although service-specific differences may exist. Further research on enhancing patient trust through LVC de-implementation is needed.

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Identification of Recent Trends in Research on Vitamin D: A Quantitative and Co-Word Analysis

Cited by 35 publications

References 38 publications

Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study

Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study

Viroinformatics-Based Analysis of SARS-CoV-2 Core Proteins for Potential Therapeutic Targets

Does De-Implementation of Low Value Care Impact the Patient-Clinician Relationship? A Mixed Methods Study

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