Analysis and prospect of clinical psychology based on topic models: hot research topics and scientific trends in the latest decades

Decoding the language of first impressions: Comparing models of first impressions of faces derived from free-text descriptions and trait ratings

First impressions formed from facial appearance predict important social outcomes. Existing models of these impressions indicate they are underpinned by dimensions of Valence and Dominance, and are typically derived by applying data reduction methods to explicit ratings of faces for a range of traits. However, this approach is potentially problematic because the trait ratings may not fully capture the dimensions on which people spontaneously assess faces. Here, we used natural language processing to extract 'topics' directly from participants' free-text descriptions (i.e., their first impressions) of 2222 face images. Two topics emerged, reflecting first impressions related to positive emotional valence and warmth (Topic 1) and negative emotional valence and potential threat (Topic 2). Next, we investigated how these topics were related to Valence and Dominance components derived from explicit trait ratings. Collectively, these components explained only ~44% of the variance in the topics extracted from free-text descriptions and suggested that first impressions are underpinned by correlated valence dimensions that subsume the content of existing trait-rating-based models. Natural language offers a promising new avenue for understanding social cognition, and future work can examine the predictive utility of natural language and traditional data-driven models for impressions in varying social contexts.

Research Trends and Highlights Toward Virtual Reality in Patients With Cancer: Bibliometric Analysis

This retrospective bibliometric analysis was conducted to explore research trends and identify studies in fields of nursing, virtual reality, and cancer. Data were obtained from the Web of Science database using an advanced search strategy. The study data were analyzed using the R Studio software and visualized using VOSviewer. A total of 594 studies were retrieved and analyzed from January 1995 to December 2021. It was determined that 59.4% of the studies were research articles and that these studies had been conducted by 2771 authors. The reviewed studies were produced by researchers from 25 countries and were published in 29 different journals. Of these, 169 were conducted by researchers in the United States. "Virtual reality" and "nursing" were found to be prominent topics. Studies on virtual reality in patients with cancer in the field of nursing have increased over the past 8 years. Researchers have actively conducted studies in this field. Prominent studies have covered various patients with cancer in all age groups and palliative care processes. It was seen that the majority of the studies were randomized controlled trials, reviews, and systematic reviews. In addition, studies have used virtual reality as a distraction method in the management of symptoms in patients with breast, lung, and pediatric cancers undergoing chemotherapy treatment. This study provides a detailed and up-to-date analysis of the findings obtained from the Web of Science database by emphasizing bibliometric models of virtual reality technologies in nursing patients with cancer. We believe that the current data on the use of virtual reality applications in patients with cancer will guide the clinical practice and scientific studies of healthcare professionals.

Leadership and care in nursing research: A bibliometric analysis

AIM

This study aimed to analyse the study focus, thematic trends and evolution of studies on the leadership and care in nursing by using a bibliometric analysis.

DESIGN

Descriptive and bibliometric analyses were employed.

METHODS

The study universe included 3558 articles on the leadership and care in the Web of Science (WoS) database. The data analysis and graphical presentation were conducted using Bibliometrix Package in R software.

RESULTS

Within the scope of the study, articles published by 10,255 authors in 184 different sources between 1982-2021 were reached. Five thousand eight hundred and twenty-eight author keywords were found in these studies. The most frequent author keywords included "leadership," "nursing," "nurse," "evidence-based practice," "management," "nursing leadership" and "patient safety." It was further suggested that the most frequently used trend topics in early years were "new roles," "faculty practice," "research implementation" while trend topics such as "systematic review," "older adults" and "COVID-19' have become popular in recent years.

CONCLUSION

The number of studies on the leadership and care in nursing has gradually increased over the years, and this subject has already become an active field of study in nursing research. In addition, nurse-related themes such as job satisfaction, teamwork and retention have been reviewed more intensively while patient-based and fundamental care-based themes have been less studied.

IMPACT

This study was the first bibliometric analysis to focus on the research focus, thematic trends and evolution of research on the leadership and care in nursing. Only a limited amount of data are available on the current knowledge structure, research focus, thematic trends and evolution of research on leadership and care in nursing. The results of this study may establish a solid ground to design further studies and provide guidance.

Detecting the research structure and topic trends of social media using static and dynamic probabilistic topic models

Purpose

A huge volume of published research articles is available on social media which evolves because of the rapid scientific advances and this paper aims to investigate the research structure of social media.

Design/methodology/approach

This study employs an integrated topic modeling and text mining-based approach on 30381 Scopus index titles, abstracts, and keywords published between 2006 and 2021. It combines analytical analysis of top-cited reviews with topic modeling as means of semantic validation. The output sequences of the dynamic model are further analyzed using the statistical techniques that facilitate the extraction of topic clusters, communities, and potential inter-topic research directions.

Findings

This paper brings into vision the research structure of social media in terms of topics, temporal topic evolutions, topic trends, emerging, fading, and consistent topics of this domain. It also traces various shifts in topic themes. The hot research topics are the application of the machine or deep learning towards social media in general, alcohol consumption in different regions and its impact, Social engagement and media platforms. Moreover, the consistent topics in both models include food management in disaster, health study of diverse age groups, and emerging topics include drug violence, analysis of social media news for misinformation, and problems of Internet addiction.

Originality/value

This study extends the existing topic modeling-based studies that analyze the social media literature from a specific disciplinary viewpoint. It focuses on semantic validations of topic-modeling output and correlations among the topics and also provides a two-stage cluster analysis of the topics.

A Bibliometric Analysis of COVID‐19 Publications in Nursing By Visual Mapping Method

Aim

This study conducted a bibliometric analysis of nursing publications on the COVID‐19 between 1 January 2020, and 24 October 2021.

Background

COVID‐19 has been a hot research topic that has attracted many researchers from various disciplines. One of the ways to combat the COVID‐19 pandemic is to produce knowledge and present it with a holistic approach. Therefore, it is crucial to make bibliometric and content analyses of scientific publications. Scientific data should be evaluated to keep up with the developments in the nursing profession and practices during the COVID‐19 pandemic.

Methods

Data were collected from the Web of Science database. The sample consisted of 1280 publications that met the inclusion criteria. The data were analysed using descriptive content and bibliometric analysis. The VOSviewer, a mapping and visualization software program, was used for bibliometric analysis.

Results

The United States is one of the countries with the highest number of publications, citations and international cooperation during the pandemic. Of all these publications, 1183 (92.42%) are original articles. The Journal of Nursing Management has the highest number of publications and citations. The publications focus primarily on the topics of COVID‐19, pandemic, nursing, coronavirus and nurses. The current topics that the publications address are online education, online learning, practice, nursing student, perceived stress, stress, fear, quality of life and experience to determine the impacts of the pandemic on mental health nursing education.

Conclusions

The COVID‐19 pandemic has an impact on nursing, and the number of publications is increasing worldwide. In the early days of the pandemic, researchers focused on the topics of coronavirus infections, infection control, global health, health policy and nursing policy. Afterward, they addressed current topics, such as education and the psychological effects of the pandemic.

Implications for nursing management

Our results will help nurse managers identify issues related to COVID‐19 that have not been researched yet and have not been adequately explained in their own institutions. They will also help them choose appropriate journals to get their studies published, appropriate countries to cooperate with and access information about the studies on the subject matter. Our results will also help them make evidence‐based decisions about mental health and nursing education.

Trends and hot topics in nurse empowerment research: A bibliometric analysis

AIM

The characteristics of the publications on nursing empowerment should be investigated in order to get an idea about the development of the field and to determine the developments in nursing practices and research. This study aimed to investigate the characteristics of the current knowledge structure and developmental process in nurse empowerment by using bibliometric methods.

METHODS

The data of this retrospective descriptive study were obtained from the Web of Science (WoS). All relevant studies conducted before 2020 were included in the study. The data analysis was conducted with Excel, SPSS and VOSviewer.

RESULTS

Five hundred eighty-nine studies conducted between 1974-2019 were included in the study. It was found that 72.15% of these studies were journal articles and these studies were conducted by 1,450 authors. The studies were published in 109 journals and were produced by researchers from 49 different countries. Also 47.5% of these studies were conducted in the United States. Hot topics were "empowerment", "nursing," "structural empowerment," "nurses," "job satisfaction" and "psychological empowerment."

CONCLUSION

There has been a noteworthy increase in the number of studies on nurse empowerment and this field offers an active field of study for nursing researchers. The focus of the studies varies from nurses to nurse managers.