\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{The evolutionary paths of clinical psychology studies in the United
States: a bibliometrics illustration of 69k publications}



\author[1]{Mingzhu Gao}%
\author[2]{Wen Lou}%
\affil[1]{East China Normal University College of Economics and Management}%
\affil[2]{East China Normal University Department of Information Management and Information Systems}%


\vspace{-1em}



  
  \date{June 18, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
\emph{Objective:} Clinical psychology, a pivotal aspect of psychology,
combines research and practice. This study aims to assess the recent
decade's clinical psychology research, particularly post-COVID-19
paradigm shifts. \emph{Method:} Analyzing 69,295 clinical psychology
publications from 2010 to 2022 in the Web of Science database, we used
advanced bibliometrics tools (CiteSpace and Mapequation) to scrutinize
authorship networks, publishing trends, and research focus in the US,
the field's rigin. \emph{Results:} We found a significant upswing in
clinical psychology research prompted by the advent of the pandemic,
particularly in the study of psychological trauma caused by issues such
as family conflict, elder abuse, collective trauma, and so on. Clinical
psychology research has been profoundly formed with a dynamic group of
scholars and institutions, surrounding mainly higher education systems.
Research participants are widely diverse, with a progressive focus
transition to the populations on gender and race minorities, maternal,
and adolescents. Mental disorder, such as PTSD, anxiety, and suicidal
behaviors have caught more attention especially during the pandemic.
Therapeutic approaches have long been another focus in clinical
psychology, interventions such as mindfulness-based practice and
AI-assisted technologies have started to gain prominence.
\emph{Conclusions:} This paper serves as the first large-scale
bibliometrics analysis in clinical psychology, which offers an
interdisciplinary collaboration potential with information science
besides the originality of documenting publication trends in psychology.
The integration of open data initiatives, machine learning, augmented
reality, and virtual reality technologies shows promise in assessing
mental health and fostering well-being, indicating an evolving landscape
in clinical psychology research.%
\end{abstract}%



\sloppy


\textbf{The evolutionary paths of clinical psychology studies in the
United States:}

\textbf{a bibliometrics illustration of 69k publications}

\section*{Abstract}

{\label{abstract}}

Objective: ~Clinical psychology, a pivotal aspect of psychology,
combines research and practice. This study aims to assess the recent
decade's clinical psychology research, particularly post-COVID-19
paradigm shifts.~Method:~ Analyzing 69,295 clinical psychology
publications from 2010 to 2022 in the Web of Science database, we used
advanced bibliometrics tools (CiteSpace and Mapequation) to scrutinize
authorship networks, publishing trends, and research focus in the US,
the field's rigin.~Results:~~ We found a significant upswing in clinical
psychology research prompted by the advent of the pandemic, particularly
in the study of psychological trauma caused by issues such as family
conflict, elder abuse, collective trauma, and so on. Clinical psychology
research has been profoundly formed with a dynamic group of scholars and
institutions, surrounding mainly higher education systems. Research
participants are widely diverse, with a progressive focus transition to
the populations on gender and race minorities, maternal, and
adolescents. Mental disorder, such as PTSD, anxiety, and suicidal
behaviors have caught more attention especially during the pandemic.
Therapeutic approaches have long been another focus in clinical
psychology, interventions such as mindfulness-based practice and
AI-assisted technologies have started to gain prominence.~Conclusions:~
This paper serves as the first large-scale bibliometrics analysis in
clinical psychology, which offers an interdisciplinary collaboration
potential with information science besides the originality of
documenting publication trends in psychology. The integration of open
data initiatives, machine learning, augmented reality, and virtual
reality technologies shows promise in assessing mental health and
fostering well-being, indicating an evolving landscape in clinical
psychology research.

Public Health Significance Statement: The works in this review suggest
that the changing landscape of clinical psychology, especially
post-COVID-19. The increased research post-pandemic emphasizes
addressing psychological trauma arising from societal issues like family
conflicts, elder abuse, and collective trauma. A positive shift towards
inclusivity is evident in research, focusing on diverse groups like
gender minorities, racial minorities, mothers, and adolescents.

Additionally, the amplified focus on mental disorders like PTSD,
anxiety, and suicidal behaviors during the pandemic stresses the need
for tailored interventions and support systems. Exploring innovative
methods such as mindfulness-based practices and AI-assisted technologies
showcases the field's adaptability in mental health interventions.

\section*{Keywords: Clinical Psychology; Bibliometrics; Hot topics;
Research
trends}

{\label{keywords-clinical-psychology-bibliometrics-hot-topics-research-trends}}

Mental health issues have gained increased global prominence (Graham,
2019). Confronting social stressors such as intense competition,
fast-paced lifestyles, economic instability, and the prevalence of
social media may contribute to elevated levels of social comparison and
anxiety, thus adversely affecting individuals' self-esteem and
self-worth. The increased prevalence of mental health issues such as
anxiety, depression, and substance abuse has led to more people seeking
clinical psychology services. Moreover, the global impact of the
COVID-19 pandemic on mental health has been profound (Kumar et al.,
2021). Individuals experience psychological stressors associated with
health, social isolation, as well as occupational and economic
instability. Consequently, there has been a swift upsurge in the demand
for mental health support and interventions (Ho et al., 2021).

In the context of summarizing, synthesizing, and analyzing existing
research literature, systematic reviews and meta-analyses stand out as
the most frequently employed research methods in clinical psychology.
While systematic reviews and meta-analyses excel at integrating
quantitative research findings to answer specific research questions,
they may have limitations in offering a broader perspective on research
trends and the quantitative data within the field's literature. Although
the use of bibliometrics for analysis is relatively uncommon in clinical
psychology, it has been more prevalent in the broader field of
psychology. For example, bibliometric methods have been used to identify
publications related to COVID-19 in psychology (Ho et al., 2021),
forecast trends in the field (Krampen et al., 2011), and conduct reviews
of treatment research (Van Raan et al., 2003). These approaches have
been especially prominent when investigating specific perspectives or
topics, such as yoga therapy interventions (Jeter et al., 2015),
postpartum depression (Bai et al., 2021), and the mental health of
university students. In the current context, there is a recognized need
for research that concentrates on evaluating and visually representing
publications within the field of clinical psychology.

Psychologists from the United States hold a prominent position in the
field of psychological science, as evidenced by their higher number of
published articles and citations in comparison to researchers from other
countries (Arnett, 2016;). At present, the clinical psychology research
literature in the United States primarily centers around topics such as
evidence-based treatments, psychotherapy interventions, assessment
tools, and mental health outcomes. While these areas play a crucial role
in advancing the field, there is an increasing demand to delve into
emerging trends and underrepresented areas of research, which are
currently lacking in the existing literature.

Therefore, in this study, we will concentrate on examining the research
dynamics of clinical psychology in the United States. Utilizing a
bibliometric approach, we seek to fill this gap by employing a
substantial dataset consisting of 68,922 publications to explore the
research trends in American clinical psychology from 2010 to 2022. Our
goal is to offer insights into the evolution of research themes,
interdisciplinary partnerships, and the changing landscape of clinical
psychology.

\section*{Materials and Methods}

{\label{materials-and-methods}}

\subsection*{Data and Search Strategy}

{\label{data-and-search-strategy}}

We sourced our data from the Clarivate Web of Science Core Collection
(WoS, www.webofscience.com). It offers a comprehensive collection of
citation indexes that map out the intricate web of scholarly
connections. With an extensive database comprising more than 89 million
records (Clarivate, 2023), it covers a wide array of fields.

We utilized advanced Boolean search techniques to facilitate our
research, employing the following search terms: WC= (Psychology,
Clinical) and CU= (USA) and PY= (2010-2022). To minimize potential bias
resulting from database updates, all searches and data downloads were
conducted on the same date, which was July 25, 2023. In line with our
search strategy, the initial search retrieved a total of 69,295 studies
conducted between 2010 and 2022. For this article, we will exclusively
focus on publications in English, as it is the primary language in which
clinical psychology studies in the United States are conducted.
Publications in languages other than English are notably
underrepresented in bibliometric databases (Larivi\selectlanguage{ngerman}ère and Macaluso,
2011). By applying our eligibility criteria, we excluded 192 studies due
to non-English language publications. We arrived at a final set of
68,922 publications for inclusion in the study. All of these entries
were retrieved and saved as a bibliographic document file in .txt
format, preserving all relevant bibliographic details and citations.

\subsection*{Methods}

{\label{methods}}

Bibliometric method is employed in this study to provide an overview in
clinical psychology, involves the use of statistical methods and
quantitative models to delineate the frontiers of scientific research.

Collaboration network analysis assists researchers in identifying key
collaborators within specific fields or research topics. We employed
CiteSpace V6.2.R4 to calculate the betweenness centrality of authors or
institutions in collaboration networks, particularly co-authorship
networks. In collaboration networks, each node represents an institution
or author. The use of betweenness centrality is a crucial measure for
evaluating the importance of these nodes within the network and
assessing the extent of collaborative interactions. A higher value of
betweenness centrality indicates a greater level of importance for a
specific node within the network, indicating closer and more direct
collaborations with other nodes (Chen, 2012).

The key components of citation analysis include Bibliographic Coupling,
Direct Citation, and Co-citation. Bibliographic Coupling involves the
relationship when a paper appears in the reference lists of multiple
other papers. Direct Citation, on the other hand, refers to the
frequency with which a published paper is cited in subsequent works,
with a higher citation frequency indicating a greater impact.
Co-citation occurs when two papers are simultaneously cited in the
reference list of a third paper. Co-citations are especially valuable
for unveiling the internal relationships and dynamic evolution of
scientific literature. Their forward-looking perspective, compared to
retrospective methods like bibliographic coupling, makes them
well-suited for studying contemporary intelligence science (Garfield,
2001).

In this study, we used CiteSpace, a scientific literature analysis tool.
It helps analyze literature in specific fields to identify key
developments. We imported data from Web of Science into CiteSpace,
removed duplicates, and then conducted co-occurrence analyses of
authors, institutions, and keywords. The results were visually presented
as a map, with node size indicating frequency or citations. Thicker
lines between nodes indicated stronger connections. Clustering was used
to identify research domains and themes, and burst detection identified
significant frequency increases. This method helps measure an entity's
influence beyond cumulative metrics.

\section*{Results}

{\label{results}}

\subsection*{The characteristics of
publications}

{\label{the-characteristics-of-publications}}

\subsubsection*{\texorpdfstring{\emph{The numbers of
publications}}{The numbers of publications}}

{\label{the-numbers-of-publications}}

The annual number of publications is an important indicator of trends in
a field. During the period of our observations (2010 to 2022), the
number of studies in clinical psychology in the U.S. exhibited a
consistent upward trend. It increased from 4,124 in 2010 to 6,277 in
2022, with the most rapid growth observed from 2017 to 2019 (Figure 1).
Furthermore, research in clinical psychology in the United States
experienced a minor peak in 2021. This may be associated with societal
factors, where the impact of the COVID-19 pandemic in 2019 has led to an
increased emphasis on clinical psychology.

\subsubsection*{\texorpdfstring{\emph{Journals publishing research in
clinical
psychology}}{Journals publishing research in clinical psychology}}

{\label{journals-publishing-research-in-clinical-psychology}}

All these articles were distributed in 214 journals, of which a total of
56 journals that have published more than 500 of these articles. These
journals cover a wide range of topics in psychology and mental health,
including, mental disorders, psychological assessment, psychotherapy,
cognitive-behavioral therapy, sexual health, and various other areas of
psychology and psychotherapy. Table 1 displays the top 10 journals with
the highest number of publications in clinical psychology. These ten
journals collectively accounted for more than 20\% of the total
publications. Notably, Addictive Behaviors and Journal of Clinical
Psychiatry were the most prolific among them.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\emph{Figure 1.} Number of publications in clinical psychology between
2010 and 2022.

Table1

\emph{Top 10 journals with the most publications in clinical psychology
from 2010 to 2022}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Rank & Journal & Publications & N (\%)\tabularnewline
\midrule
\endhead
1 & Addictive Behaviors & 2,839 & 4.59\%\tabularnewline
2 & Journal of Clinical Psychiatry & 1,647 & 2.66\%\tabularnewline
3 & Journal of Substance Abuse Treatment & 1,555 & 2.52\%\tabularnewline
4 & Psychological Medicine & 1,330 & 2.15\%\tabularnewline
5 & Archives of Sexual Behavior & 1,272 & 2.06\%\tabularnewline
6 & International Journal of Behavioral Medicine & 1,198 &
1.94\%\tabularnewline
7 & International Journal of Eating Disorders & 1,182 &
1.91\%\tabularnewline
8 & Journal of Family Psychology & 1,149 & 1.86\%\tabularnewline
9 & Health Psychology & 1,138 & 1.84\%\tabularnewline
10 & Psychological Assessment & 1,122 & 1.82\%\tabularnewline
\bottomrule
\end{longtable}

\subsubsection*{\texorpdfstring{\emph{Institutions and collaboration
network}}{Institutions and collaboration network}}

{\label{institutions-and-collaboration-network}}

The analysis of countries and research institutions is of paramount
importance as it assists researchers in identifying prominent teams in
the field of clinical psychology and in fostering broader collaborative
efforts. In our search strategy, the country/region specification is
denoted by CU=USA, referring to the location listed in the ''address''
field of the search record within WoS. When considering the volume of
publications, it is noteworthy that Canada (2,734), England (1,708),
Australia (1,611), Netherlands (1,096), Germany (1,009), and China (947)
emerge as significant collaborative partners with the United States in
the field of clinical psychology research.

More than 2000 institutions have done research in clinical psychology.
As depicted in Table 2, the top twenty institutions that publish the
highest number of papers in clinical psychology are presented. Among
these, the University of California System claims the top position with
5,473 publications, while the top five institutions include the US
Department of Veterans Affairs, Harvard University, Veterans Health
Administration (VHA), and the State University System of Florida.

Table 2

\emph{Top 10 most productive institutions, 2010-2022}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Rank & Institution & Publications & Centrality\tabularnewline
\midrule
\endhead
1 & University of California System & 5,473 & 0.39\tabularnewline
2 & US Department of Veterans Affairs & 4,265 & 0.94\tabularnewline
3 & Harvard University & 4,172 & 0.35\tabularnewline
4 & Veterans Health Administration & 4,165 & 1.56\tabularnewline
5 & State University System of Florida & 3,654 & 0.65\tabularnewline
6 & Pennsylvania Commonwealth System of Higher Education & 3,359 &
0.21\tabularnewline
7 & University System of Ohio & 2,988 & 0.05\tabularnewline
8 & University Of Texas System & 2,673 & 0.16\tabularnewline
9 & University Of North Carolina & 2,316 & 0.21\tabularnewline
10 & Yale University & 1,973 & 0.85\tabularnewline
\bottomrule
\end{longtable}

For each year, we screen the top 50 institutions. The size and color of
nodes and links represent the extent of cooperation and the time periods
of institutions' collaborations. When two institutions collaborate, a
line is drawn between them. The darker the color of the link, the closer
the collaboration occurred to 2010, while lighter colors indicate
collaborations closer to 2022. Larger labels on nodes indicate higher
centrality within the network. Nodes with purple circles represent
institutions that play a more central intermediary role in the network.
Figure 2 illustrates the most significant clusters, which include highly
productive institutions. Notably, within this network, the Veterans
Health Administration (VHA) plays a crucial role as a bridge-builder and
leader, facilitating collaborations. It is also evident that specific
productive institutions serve as intermediaries in the collaborative
network, such as the US Department of Veterans Affairs, Yale University,
and the State University System of Florida. These findings highlight the
establishment of stable and long-lasting partnerships among several
institutions in the field of clinical psychology research.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\emph{Figure 2.} The collaboration network of institutions

\subsubsection*{\texorpdfstring{\emph{Author
analysis}}{Author analysis}}

{\label{author-analysis}}

Among all authors, Zvolensky stands out as the author with the highest
number of publications, having published 295 articles in the field of
clinical psychology from 2010 to 2022 (Table 3). Their significant
contribution to this field is noteworthy. The top 20 most productive
authors have all exceeded 100 publications. They have primarily focused
on a wide range of psychological symptoms, including distress tolerance,
smoking, anxiety sensitivity, binge eating, anorexia nervosa, panic
disorder, suicide, and collaborative longitudinal personality disorders.
Additionally, their research has delved deeply into the study of
therapeutic approaches, including cognitive-behavioral therapy,
acceptance and commitment therapy, and exposure therapy, among others.

Table 3

\emph{Top 20 highly productive authors, 2010-2022}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
Rank & Author & Publications & Rank & Author &
Publications\tabularnewline
\midrule
\endhead
1 & Zvolensky, M. J & 295 & 11 & Miller, Joshua & 123\tabularnewline
2 & Crosby, Ross D & 203 & 12 & Storch, Eric A & 122\tabularnewline
3 & Schmidt, Norman B & 188 & 13 & Wonderlich, Stephen A &
118\tabularnewline
4 & Joiner, Thomas E & 149 & 14 & Kessler, Ronald C & 117\tabularnewline
5 & Le Grange, Daniel & 144 & 15 & Hofmann, Stefan G &
116\tabularnewline
6 & Michelle G. Craske & 142 & 16 & Foa, Edna B & 116\tabularnewline
7 & Bulik, Cynthia M & 140 & 17 & Krueger, Robert F & 112\tabularnewline
8 & Kendall, Philip C & 130 & 18 & Wright, Aidan & 112\tabularnewline
9 & Grilo, Carlos M & 126 & 19 & Resick, Patricia A. A &
109\tabularnewline
10 & Kendler, Kenneth & 125 & 20 & Rodgers, Rachel F &
107\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\emph{Figure 3} . The collaboration network of authors

We screened out the top 10\% authors each year, set the threshold
greater than 5 by frequency. Figure 3 shows the top 5 clusters composed
of productive authors. The size of the nodes represents the frequency
with which the author's papers have been cited, while the thickness of
the links indicates the strength of collaboration. The color of the
nodes and links is indicative of the period, with nodes (or links)
closer to yellow signifying a time closer to 2022, and those closer to
purple indicating a time closer to 2010. Among these authors, including
Zvolensky, Schmidt, Crosby, and Wright, not only serve as leaders and
anchors in the field of clinical psychology research in the United
States, but they also play significant roles in knowledge sharing and
collaboration (Figure 3).

\subsection*{Research hotspots}

{\label{research-hotspots}}

\subsubsection*{\texorpdfstring{\emph{The temporal changes of research
hotspots}}{The temporal changes of research hotspots}}

{\label{the-temporal-changes-of-research-hotspots}}

Keywords play a crucial role in identifying research hotspots. To do so,
we specifically extracted the top 50 co-occurrence noun phrases from the
keywords of clinical psychology-related publications every two years
(excluding the final period). These phrases were used to create
pathfinder networks through the use of CiteSpace and Mapequation
(Rosvall and Bergstrom, 2010). Figure 4 presents an alluvial diagram
that illustrates the evolution of research hotspots and changes in
clustering within the field of clinical psychology. In each time period,
the top 100 noun phrases formed a pathfinder network. In the alluvial
diagram, each column represents the cluster network for a specific
period, with each block in a column representing a cluster within the
network. The height of each block corresponds to the proportion of
co-occurrence phrases in that cluster. In this study, we utilize
PageRank values to indicate the importance of noun phrases. A higher
PageRank value suggests that the noun phrase has a greater co-occurrence
frequency. Table 1-2 in the Appendix show the top 10 keywords ranked
according to Page rank value for each time period.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\emph{Figure 4.} Alluvial diagram of research hotspots over time

From 2010 to 2022, it is evident that research themes have been
broadening and becoming less focused on specific topics, as illustrated
in Figure 4 and Table 1-2 in the Appendix. Substance abuse, prevalence,
and posttraumatic stress have been important research topics from
2010-2015, and after 2015, research on mental health has increased
rapidly, with the 2020-2021 and 2022 periods seeing mental health's Page
rank (\%) reached 10.70\% and 12.20\% respectively and is likely to
continue to grow in the future.

\subsubsection*{\texorpdfstring{\emph{Keywords
Burstiness}}{Keywords Burstiness}}

{\label{keywords-burstiness}}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\emph{Figure 5.} Top 25 Keywords with the Strongest Citation Bursts

To gain a deeper understanding of the keywords, we have also conducted a
burst analysis. Keyword emergence refers to the keywords that appear
very frequently in the published articles within a short period of time,
from the beginning to the end of the keyword emergence to form a black
horizontal line marking, indicating the importance of the keywords in
the field of research and the degree of attention, the longer the length
of the emergence, the longer the duration of the keyword heat, the more
cutting-edge research. The 25 keywords with the highest emergent
intensity are displayed in Figure 5. Among them, the keyword with the
longest duration is alcohol dependence (2010-2015); creativity in
counseling with the highest emergent intensity, followed by social
phobia and sexual and gender minorities.

\subsubsection*{\texorpdfstring{\emph{Keyword co-occurrence
network}}{Keyword co-occurrence network}}

{\label{keyword-co-occurrence-network}}

The correlation between high frequency keywords can also reveal the
intrinsic connection of knowledge in the field to some extent. The
hotspot keywords in clinical psychology research are relatively
concentrated, and the frequency of these keywords is higher than 100
(Figure6). Among them, mental health, symptoms, substance abuse,
depression, posttraumatic stress and prevalence have higher frequency
and importance in the network.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\emph{Figure 6.} keyword co-occurrence map in clinical psychology from
2010 to 2022

\subsubsection*{\texorpdfstring{\emph{Keyword
clustering}}{Keyword clustering}}

{\label{keyword-clustering}}

The keyword clustering analysis is based on the keyword a co-occurrence
map. Based on the keyword co-occurrence map, we use the logarithmic
great likelihood rate (LLR) clustering algorithm to search for the
largest clusters and adjust the cluster labels, and the ID numbers of
the cluster labels are inversely proportional to the size of the
clusters. The weighted average contour value formed at home and abroad
is 0.9381, and the calculated modularity value is 0.885, which indicates
that the clustering results are credible.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

\emph{Figure 7.} Keyword clustering map

Among 48 clusters found, 26 effective clustering were obtained (with
silhouette score 0.71--1). Cluster \#0 (borderline personality disorder)
was the largest one, followed by cluster \#1 (suicidal ideation),
cluster \#2 (treatment outcome), cluster \#3 (sexual abuse) and cluster
\#4 (posttraumatic stress disorder). The five largest clusters and their
main keywords are displayed in Table 4. The five largest clusters relate
to some clinical psychological symptoms such as borderline personality
disorder, anxiety sensitivity, suicide, and the causes of these
psychological problems such as posttraumatic stress, sexual abuse, or
emotional contagion, and also mention some therapies such as behavior
therapy, tailoring psychotherapy. (Appendix 1, Table 3 for the complete
list of 26 clusters and key keywords.)

Table 4

\emph{Description of the 5 largest clusters}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
ID & Size & Silhouette & mean(Year) & Main Keywords &\tabularnewline
\midrule
\endhead
0 & 41 & 0.97 & 2013 & borderline personality disorder; confirmatory
factor analysis; emotion regulation; anxiety sensitivity; distress
tolerance & borderline personality disorder; confirmatory factor
analysis; emotion regulation; anxiety sensitivity; distress
tolerance\tabularnewline
1 & 41 & 0.98 & 2013 & suicidal ideation; suicide attempt; emotion
regulation; emotion contagion; family expressiveness & suicidal
ideation; suicide attempt; emotion regulation; emotion contagion; family
expressiveness\tabularnewline
2 & 36 & 0.96 & 2013 & treatment outcome; treatment adaptation;
tailoring psychotherapy; specific phobia; behavior therapy & treatment
outcome; treatment adaptation; tailoring psychotherapy; specific phobia;
behavior therapy\tabularnewline
3 & 35 & 0.99 & 2014 & sexual abuse; emotion regulation; posttraumatic
stress; incarcerated women; goal commitment & sexual abuse; emotion
regulation; posttraumatic stress; incarcerated women; goal
commitment\tabularnewline
4 & 34 & 0.99 & 2014 & posttraumatic stress disorder; anxiety
sensitivity; cortisol rhythm; posttraumatic stress symptoms; college
students & posttraumatic stress disorder; anxiety sensitivity; cortisol
rhythm; posttraumatic stress symptoms; college students\tabularnewline
\bottomrule
\end{longtable}

In order to identify historical milestones and analyze emerging trends
in clinical psychology, we have created a timeline visualization of
co-citation clusters based on a keyword network. Each node in the
co-citation network represents a keyword. If two nodes are linked, it
indicates that they are used in the same article. The size of nodes
reflects the frequency of keyword occurrences (Figure 8). In our pursuit
of identifying historic milestones and analyzing emerging trends in
clinical psychology, we have constructed a timeline view of co-citation
clusters based on a network of keywords (Figure 8). CiteSpace can
provide a timeline view that presents topical knowledge related to
clinical psychology (Figure 7). Through the legend, we can trace the
thematic trends and temporal evolution of research in clinical
psychology disorders. This network comprises highly frequent keywords
within a specific time frame. Nodes are organized in rows, and clusters
are numbered to highlight groups with a larger number of keywords.
Darker links and citations are associated with 2010, whereas lighter
ones are related to 2022.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image8/image8}

\end{center}
\end{figure}

\emph{Figure 8} . Timeline view of clustering

In the temporal clustering graph, the horizontal axis represents time,
while the vertical axis corresponds to cluster labels. This combination
enables the observation of when each keyword was studied. Among these 26
clusters, the keywords that occur most frequently have been researched
as early as 2010, and many relevant studies in these areas continue to
the present day. Furthermore, other significant bursts of research
activity have occurred in the intervening years, and in certain
clusters, such bursts have repeated multiple times.

\section*{Discussion}

{\label{discussion}}

The primary objective of clinical psychology is to understand, predict,
and address disorders, disabilities, and maladjustments (Schmidt
\&Power, 2005). This encompasses assessments, problem formulation, and
treatment recommendations. A secondary goal is to proactively enhance
human adaptation, personal development, and mental health for
prevention. Research in clinical psychology has shown its significant
differentiations from other aspects in psychology on centering its own
features. Some scholars specialize in research related to psychological
assessment tools, including the development of measures,
neuropsychological tests, and scales. They employ methods such as factor
analysis, latent class analysis, functional analysis, evidence-based
assessment, randomized controlled trials, and motivational interviewing,
which find extensive application in clinical psychology research.
Furthermore, some studies utilize techniques like structural equation
modeling, network analysis, and multilevel modeling to investigate
factors linked to clinical psychological disorders. Since 2011, clinical
psychology integrated with virtual reality. As open data and
standardized data have advanced, clinical psychology has been able to
conduct research based on more extensive datasets. Machine learning,
content analysis, and other methodologies have also been introduced.

\subsection*{The prevalence of population
features}

{\label{the-prevalence-of-population-features}}

The primary demographic factors influencing clinical psychology research
development include gender, age, ethnicity, cultural background, and
societal roles. Different age groups exhibit varying clinical
psychological disorders and responses to therapies, with particular
focus on older adults, emerging adults, children, and adolescents.
Additionally, research has narrowed down to shorter age periods like
high school or mid childhood. Gender-related issues have been a
continuous area of interest, with a growing focus on sexual and gender
minorities and research on transgender mental disorders since 2015.
Racial and cultural backgrounds are central in clinical psychology
research, covering mental disorders arising from racial differences,
discrimination, and variations in mental disorder occurrence among
different racial groups. Furthermore, there is increasing research on
psychological issues in military personnel, including military families
and child soldiers, as well as psychological problems associated with
maternity and, more recently, medical students.

Children and adolescents are a central focus of research, examining
developmental challenges, childhood trauma, peer relationships, and
domestic violence. These issues can lead to problems like depression,
previous suicidal attempts, and substance abuse (Carballo et al., 2020).
Adverse experiences in childhood, such as physical aggression and
parental conflict, contribute to psychological disorders in adulthood.
Psychological distress in older adults is linked to challenges
associated with aging, including cognitive decline, physical health,
social isolation, loneliness, and elder abuse (Bo et al., 2020; Chalise
et al., 2020). Social isolation and loneliness have been explored in
''Typologies of Loneliness,'' revealing associations with not having a
spouse or partner, sleep disturbances, lower prosocial behaviors, and
smaller social networks. Lower social self-efficacy and higher anxiety
are linked to worse loneliness (Nguyen et al., 2020). Emerging
adulthood, spanning from late teens to early twenties, involves identity
formation, peer relationships, academic or occupational pressures, and
financial independence, which can lead to psychological issues like
anxiety, depression, and identity crises. Adults are influenced by
familial and societal factors contributing to mental disorders,
including intimate partner violence, marital satisfaction, parental
conflicts (Ran et al., 2021), parenting-related stress, and emotional
abuse. Social interactions and individual personalities, particularly
those who fear both positive and negative evaluations, as well as people
who perceive greater stress and have lower tolerance for uncertainty and
pain, can impact mental well-being, as highlighted in the study by
Eccles et al. (2020).

Research on gender differences investigates the impact of social
expectations (Satu et al., 2021), hormonal factors, and perceived social
support on the development of psychological issues. These factors
contribute to variations in mental health outcomes between men and
women. For instance, the odds ratio for gender differences in major
depression is 1.95 (Hyde et al., 2020), with studies (Markkula et al.,
2015; Bromet et al., 2011) indicating that women in the Western world
are more prone to psychological distress, depression, and anxiety.
Sexual and gender minorities have been a focus of research in recent
years, including transgender, homosexual, and bisexual individuals.
Among these groups, youth, particularly those assigned female at birth,
face an elevated risk of intimate partner violence (IPV) attributed to
minority stressors (Whitton et al., 2019). Additionally, minority group
pressures, such as discrimination related to gender, race, religion, or
sexual orientation, can significantly contribute to mental health
problems (Pettigrew et al., 2020). However, it is noteworthy that much
of the research on sexual and gender minorities has primarily centered
on family dynamics, specifically within gay, lesbian, and same-sex
families. This focus has led to an oversight of diverse family
structures that include single individuals, intersex, asexual, and queer
individuals. Additionally, there is a lack of integration in
understanding the experiences of sexual and gender minorities across the
lifespan, from childhood to old age (Reczek, 2020).

Several studies have examined various ethnic and racial populations,
including Americans, Africans, Asian Americans, Black women, Mexican
women, and individuals from South Africa, as well as Sub-Saharan Africa.
Across these diverse groups, the findings suggest minimal differences in
psychotherapy outcomes related to factors such as ethnocultural
background, gender, or their intersections (Joiner et al., 2022). Higher
ethnocentricity, such as African American adolescents and Hispanic
adolescents, may have higher initial levels of academic and emotional
peer support, with emotional peer support strongly associated with
mental health (Hoffman et al., 2019). Furthermore, research findings
indicate that a prevalent USA-centric sampling bias in psychology may
lead to biased assumptions about people from the United States,
particularly those of White ethnicity, being disproportionately
representative of humanity (Cheon et al., 2020).

The emphasis on social justice is further underscored in the context of
issues related to racism (ethnic and racial diversity), sexism (sexual
minorities), and heterosexism (lesbian, gay, bisexual, and transgender
issues) within clinical psychology. Research not only examines the
influence of ethnic identity and the varying life experiences of
individuals from diverse racial and ethnic backgrounds on their mental
health but also exposes the deep-seated biases, stereotypes, and
historical discriminatory practices prevalent in psychological research
and clinical care (Thrift \& Sugarman, 2019; Fisher, 2020). This
heightened awareness of social justice stresses the need to ensure that
individuals, regardless of their cultural or ethnic backgrounds, receive
mental health care that is equitable, inclusive, and culturally
sensitive.

The emergence of the COVID-19 pandemic in 2019 has cast a spotlight on
social justice issues within clinical psychology and everyday life. This
global crisis has not only intensified research into collective trauma
(Stanley et al., 2021), shedding light on the profound mental health
consequences experienced by individuals and communities exposed to
traumatic events like natural disasters, acts of terrorism, or
epidemics, but it has also brought forth a fresh wave of mental health
challenges. These challenges encompass anxiety, depression, social
isolation, fear, uncertainty, and post-traumatic stress disorder (Cullen
et al., 2020). In response, a plethora of studies has emerged, each with
its unique focus. These studies delve into the experiences of diverse
populations, encompassing children and adolescents (Fegert et al.,
2020), the elderly, healthcare professionals (Romero et al., 2022),
patients with mental disorders (Wang et al., 2020), as well as the
general public. The intersection of the COVID-19 crisis and its impact
on mental health emphasizes the importance of providing equitable,
inclusive, and culturally sensitive mental health support during these
trying times.

\subsection*{Studies on mental disorders and therapeutic
approaches}

{\label{studies-on-mental-disorders-and-therapeutic-approaches}}

Clinical psychology research in the United States covers a broad
spectrum of psychological symptoms and therapies, addressing the diverse
needs of various populations. First, Post-Traumatic Stress Disorder
(PTSD) is a substantial area of research focus within clinical
psychology in the United States. PTSD is characterized by the
psychological and emotional consequences of exposure to a traumatic
event. Clinical psychologists utilize evidence-based treatments, such as
cognitive-behavioral therapy, prolonged exposure therapy, and cognitive
processing therapy, to assist individuals with PTSD in managing their
symptoms, processing trauma, and enhancing their overall mental
well-being. Another prominent area of focus involves eating disorders,
including binge eating and anorexia nervosa (Hay et al., 2020).
Substance and opioid abuse (Henderson et al., 2019), as well as nicotine
dependence, are significant issues in American society that necessitate
tailored treatment.

Anxiety disorders, which encompass conditions like social anxiety
disorder and generalized anxiety disorder (Haslam et al., 2019),
constitute another crucial area of research within clinical psychology.
Various therapeutic approaches, including cognitive-behavioral therapy
and psychodynamic therapy, are employed to assist patients in managing
symptoms of depression and anxiety while improving their emotional
coping skills (Tonge et al., 2020). Treatment strategies for personality
disorders, such as borderline personality disorder, frequently involve
dialectical behavioral therapy and psychodynamic therapy, aiming to
enhance emotional stability and interpersonal relationships. Suicide
risk associated with borderline personality disorder or other
psychological disorders (Paris, 2019) necessitates prompt intervention.
Psychotherapy and mental health support play a crucial role in
mitigating suicide risk. These areas represent the diversity of clinical
psychology research in the United States and will continue to evolve to
meet changing mental health needs.

Cognitive assessment (Naglieri, et al, 1997), ecological momentary
assessment (Shiffman et al., 2008), ambulatory assessment (Trull et al.,
2013), and psychological assessment (Hodges, 2017) are among the most
frequently utilized methods for assessing mental health. Scales related
to these assessments are continually under development and enhancement.
Regarding therapeutic interventions, the most commonly employed
approaches include acceptance and commitment therapy (Hayes et al.,
2011), cognitive-behavior therapy (Thoma et al., 2020), group therapy,
couple therapy, and marriage and family therapy. These therapies have
found application in addressing various mental health concerns.
Additionally, cognitive therapy, behavior therapy, dialectical behavior
therapy (Lynch et al., 2006), cognitive processing therapy,
evidence-based psychotherapy, psychodynamic therapy, and sex therapy
have demonstrated effectiveness in treating a wide range of mental
health issues. Intensive therapy, peer support, mindfulness-based
interventions, and psychotherapy integration have gained prominence as
leading therapeutic approaches in recent years.

In addition, researchers have examined various approaches to address
distinct mental health disorders. For instance, fear conditioning, peer
support, and social media support are considered for social appraisal,
while approaches like daily diary, positive psychology, and guided
self-help (Schotanus-Dijkstra et al., 2015) are explored for anxiety.
Additionally, body appreciation, bariatric surgery, or weight loss
interventions are considered for body image concerns. Cognitive bias
modification, bariatric surgery, weight loss strategies, attentional
control techniques are being considered for attention deficit disorder.
Experiential avoidance is being explored for trauma and life
experiences, while drug therapy and smoking cessation interventions are
implemented to address drug and nicotine dependence.

\section*{Conclusion}

{\label{conclusion}}

This study provides the first comprehensive qualitative and quantitative
overview of clinical psychology research in the United States over the
last 12 years (2010--2022). The primary contents encompass the most
productive countries, institutions, key authors, research focal points,
and emerging trends. The number of pertinent publications has shown a
consistent increase over the years. Notably, in the wake of the
2019-covid pandemic, issues like family conflict, elder abuse,
collective trauma, and other factors affecting mental health have
contributed to a peak in publications in 2021.

Addictive Behaviors, the Journal of Clinical Psychiatry, and the Journal
of Substance Abuse Treatment are arguably the most popular and
influential academic journals in the field of clinical psychology
research in the United States, publishing the highest number of relevant
papers. The University of California System, the US Department of
Veterans Affairs, Harvard University, and the Veterans Health
Administration are the four institutions at the forefront of clinical
psychology research, with the Veterans Health Administration holding a
significant position in the network of institutional collaborations. In
addition, Aldao has emerged as the most influential author, with their
papers being the most cited in the field. Notable researchers like
Blevins, Hofmann, and Crosby are also prominent leaders within the
co-authorship network.

By employing keyword co-occurrence analysis and citation analysis, we
have identified a significant emphasis in the field of clinical
psychology in the United States on the mental well-being of diverse
populations. Specifically, in recent years, there has been an increased
emphasis on the mental health of pregnant women and gender minority
groups. Simultaneously, there is ongoing research and analysis of the
mental health of adolescents and children, as well as the psychological
health challenges brought about by life stress and the COVID-19
pandemic. In addition to traditional approaches such as acceptance and
commitment therapy, cognitive behavior therapy, psychodynamic therapy,
evidence-based psychotherapy, interpersonal psychotherapy, music
therapy, researchers are progressively investigating the efficacy of
interventions like mindfulness-based approaches, online interventions,
peer support, intensive treatments, and other innovative therapeutic
methods. Furthermore, with the advancement of open data initiatives and
the development of machine learning, as well as augmented reality and
virtual reality technologies, there is a growing exploration and
utilization of artificial intelligence technologies for assessing
individual mental health status and the potential for promoting
well-being.

\section*{Data Transparency}

{\label{data-transparency}}

The data presented in this manuscript were sourced from publicly
available data via Web of Science (https://webofscience.clarivate.cn).
We declare that the variables and relationships investigated in this
manuscript have not been previously explored or addressed in our
published works or those presently under review. To the best of our
knowledge, the data analyzed in this article have not been previously
examined or discusse d in any existing or forthcoming publications.

\section*{Reference}

{\label{reference}}

Aldao, A., Nolen-Hoeksema, S., \& Schweizer, S. (2010).
Emotion-regulation strategies across psychopathology: A meta-analytic
review. Clinical psychology review, 30(2), 217-237.

Arnett, J. J. (2016). The neglected 95\%: why American psychology needs
to become less American.

Bai, X., Song, Z., Zhou, Y., Wang, X., Wang, Y., \& Zhang, D. (2021).
Bibliometrics and visual analysis of the research status and trends of
postpartum depression from 2000 to 2020. Frontiers in Psychology, 12,
665181.

Buchanan, N. T., \& Wiklund, L. O. (2020). Why clinical science must
change or die: Integrating intersectionality and social justice. Women
\& Therapy, 43(3-4), 309-329.

Carballo, J. J., Llorente, C., Kehrmann, L., Flamarique, I., Zuddas, A.,
Purper-Ouakil, D., \ldots{} \& Arango, C. (2020). Psychosocial risk
factors for suicidality in children and adolescents. European child \&
adolescent psychiatry, 29, 759-776.

Chalise, H. N., \& Paudel, B. R. (2020). Elderly abuse among
community-living older adults of least developed country-Nepal. Arch
Phys Rehabil Med, 1(1), 1-8.

Chen, C., Hu, Z., Liu, S., \& Tseng, H. (2012). Emerging trends in
regenerative medicine: a scientometric analysis in CiteSpace. Expert
opinion on biological therapy, 12(5), 593-608.

Cheon, B. K., Melani, I., \& Hong, Y. Y. (2020). How USA-centric is
psychology? An archival study of implicit assumptions of
generalizability of findings to human nature based on origins of study
samples. Social Psychological and Personality Science, 11(7), 928-937.

Cullen, W., Gulati, G., \& Kelly, B. D. (2020). Mental health in the
COVID-19 pandemic. QJM: An International Journal of Medicine, 113(5),
311-312.

Eccles, J. S., \& Wigfield, A. (2020). From expectancy-value theory to
situated expectancy-value theory: A developmental, social cognitive, and
sociocultural perspective on motivation. Contemporary educational
psychology, 61, 101859.

Fegert, J. M., Vitiello, B., Plener, P. L., \& Clemens, V. (2020).
Challenges and burden of the Coronavirus 2019 (COVID-19) pandemic for
child and adolescent mental health: a narrative review to highlight
clinical and research needs in the acute phase and the long return to
normality. Child and adolescent psychiatry and mental health, 14, 1-11.

Fisher, E. S. (2020). Cultural humility as a form of social justice:
Promising practices for global school psychology training. School
Psychology International, 41(1), 53-66.

Garfield, J. L., Peterson, C. C., \& Perry, T. (2001). Social cognition,
language acquisition and the development of the theory of mind. Mind \&
Language, 16(5), 494-541.

Graham, S., Depp, C., Lee, E. E., Nebeker, C., Tu, X., Kim, H. C., \&
Jeste, D. V. (2019). Artificial intelligence for mental health and
mental illnesses: an overview. Current psychiatry reports, 21, 1-18.

Haslam, C., Cruwys, T., Chang, M. X. L., Bentley, S. V., Haslam, S. A.,
Dingle, G. A., \& Jetten, J. (2019). GROUPS 4 HEALTH reduces loneliness
and social anxiety in adults with psychological distress: Findings from
a randomized controlled trial. Journal of consulting and clinical
psychology, 87(9), 787.

Hay, P. (2020). Current approach to eating disorders: a clinical update.
Internal medicine journal, 50(1), 24-29.

Hayes, S. C., Strosahl, K. D., \& Wilson, K. G. (2011). Acceptance and
commitment therapy: The process and practice of mindful change. Guilford
press.

Henderson, C. E., Liddle, H., \& Boustani, M. M. (2019). Family-Based
Treatments for Adolescent Substance Abuse: Advances Yield New
Developmental Challenges. In The Oxford Handbook of Adolescent Substance
Abuse. Oxford University Press.

Ho, Y. S., Fu, H. Z., \& McKay, D. (2021). A bibliometric analysis of
COVID-19 publications in the ten psychology-related Web of Science
categories in the social science citation index. Journal of Clinical
Psychology, 77(12), 2832-2848.

Hodges, J. R. (2017). Cognitive assessment for clinicians. Oxford
University Press.

Hoffman, A. J., Agi, A. C., Rivas-Drake, D., \& Jagers, R. J. (2019).
Peer support development among Black American and Latinx adolescents:
The role of ethnic--racial centrality. Developmental Psychology, 55(12),
2637--2648. https://doi.org/10.1037/dev0000829

Hofmann, S. G., Sawyer, A. T., Witt, A. A., \& Oh, D. (2010). The effect
of mindfulness-based therapy on anxiety and depression: A meta-analytic
review. Journal of consulting and clinical psychology, 78(2), 169.

Hyde, J. S., \& Mezulis, A. H. (2020). Gender differences in depression:
biological, affective, cognitive, and sociocultural factors. Harvard
review of psychiatry, 28(1), 4-13.

Jeter, P. E., Slutsky, J., Singh, N., \& Khalsa, S. B. S. (2015). Yoga
as a therapeutic intervention: a bibliometric analysis of published
research studies from 1967 to 2013. The Journal of Alternative and
Complementary Medicine, 21(10), 586-592.

Joiner, T. E., Robison, M., Robertson, L., Keel, P., Daurio, A. M.,
Mehra, L. M., \& Millender, E. (2022). Ethnoracial status,
intersectionality with gender, and psychotherapy utilization, retention,
and outcomes. Journal of Consulting and Clinical Psychology.

Krampen, G., Von Eye, A., \& Schui, G. (2011). Forecasting trends of
development of psychology from a bibliometric perspective.
Scientometrics, 87(3), 687-694.

Kumar, A., Rajasekharan, K. N. (2021). COVID 19 and its mental health
consequences, Journal of Mental Health, 30(1), 1-2.

Larivi\selectlanguage{ngerman}ère, V., \& Macaluso, B. (2011). Improving the coverage of social
science and humanities researchers' output: The case of the Érudit
journal platform. Journal of the American Society for Information
Science and Technology, 62(12), 2437-2442.

Lynch, T. R., Chapman, A. L., Rosenthal, M. Z., Kuo, J. R., \& Linehan,
M. M. (2006). Mechanisms of change in dialectical behavior therapy:
Theoretical and empirical observations. Journal of clinical psychology,
62(4), 459-480.

Markkula, N., Suvisaari, J., Saarni, S. I., Pirkola, S., Peña, S.,
Saarni, S., \ldots{} \& Härkänen, T. (2015). Prevalence and correlates
of major depressive disorder and dysthymia in an eleven-year
follow-up--results from the Finnish Health 2011 Survey. Journal of
affective disorders, 173, 73-80.

Naglieri, J. A., Das, J. P., Gallart, C. T., \& Álvarez, F. P. (1997).
Cognitive assessment system (Vol. 96, No. 1, pp. 174-181). Itasca, IL:
Riverside.

Nguyen, T. T., Lee, E. E., Daly, R. E., Wu, T. C., Tang, Y., Tu, X.,
\ldots{} \& Palmer, B. W. (2020). Predictors of loneliness by age
decade: study of psychological and environmental factors in 2,843
community-dwelling Americans aged 20-69 years. The Journal of clinical
psychiatry, 81(6), 15111.

Paris, J. (2019). Suicidality in borderline personality disorder.
Medicina, 55(6), 223.

Pettigrew, T. F., \& Martin, J. (2020). Organizational inclusion of
minority groups: A social psychological analysis. In Ethnic minorities
(pp. 169-200). Garland Science.

Ran, G., Niu, X., Zhang, Q., Li, S., Liu, J., Chen, X., \& Wu, J.
(2021). The association between interparental conflict and youth
anxiety: A three-level meta-analysis. Journal of youth and adolescence,
50, 599-612.

Reczek, C. (2020). Sexual\selectlanguage{english}-and gender\selectlanguage{english}-minority families: A 2010 to 2020
decade in review. Journal of Marriage and Family, 82(1), 300-325.

Romero, C. S., Delgado, C., Catala, J., Ferrer, C., Errando, C., Iftimi,
A., \ldots{} \& Otero, M. (2022). COVID-19 psychological impact in 3109
healthcare workers in Spain: The PSIMCOV group. Psychological medicine,
52(1), 188-194.

Satu, M. S., Howlader, K. C., Mahmud, M., Kaiser, M. S., Shariful Islam,
S. M., Quinn, J. M., \ldots{} \& Moni, M. A. (2021). Short-term
prediction of COVID-19 cases using machine learning models. Applied
Sciences, 11(9), 4266.

Schmidt, S., Power, M., Bullinger, M., \& Nosikov, A. (2005). The
conceptual relationship between health indicators and quality of life:
results from the cross\selectlanguage{english}-cultural analysis of the EUROHIS field study.
Clinical Psychology \& Psychotherapy: An International Journal of Theory
\& Practice, 12(1), 28-49.

Schotanus-Dijkstra, M., Drossaert, C. H., Pieterse, M. E., Walburg, J.
A., \& Bohlmeijer, E. T. (2015). Efficacy of a multicomponent positive
psychology self-help intervention: study protocol of a randomized
controlled trial. JMIR research protocols, 4(3), e4162.

Shiffman, S., Stone, A. A., \& Hufford, M. R. (2008). Ecological
momentary assessment. Annu. Rev. Clin. Psychol., 4, 1-32.

Stanley, B. L., Zanin, A. C., Avalos, B. L., Tracy, S. J., \& Town, S.
(2021). Collective emotion during collective trauma: A metaphor analysis
of the COVID-19 pandemic. Qualitative Health Research, 31(10),
1890-1903.

Thoma, N., Pilecki, B., \& McKay, D. (2015). Contemporary cognitive
behavior therapy: A review of theory, history, and evidence.
Psychodynamic Psychiatry, 43(3), 423-461.

Thrift, E., \& Sugarman, J. (2019). What is social justice? Implications
for psychology. Journal of Theoretical and Philosophical Psychology,
39(1), 1.

Trull, T. J., \& Ebner-Priemer, U. (2013). Ambulatory assessment. Annual
review of clinical psychology, 9, 151-176.

Van Raan, A. F., Visser, M. S., Van Leeuwen, T. N., \& Van Wijk, E.
(2003). Bibliometric analysis of psychotherapy research: performance
assessment and position in the journal landscape. Psychotherapy
Research, 13(4), 511-528.

Wang, S., Wen, X., Dong, Y., Liu, B., \& Cui, M. (2020). Psychological
influence of coronovirus disease 2019 (COVID-19) pandemic on the general
public, medical workers, and patients with mental disorders and its
countermeasures. Psychosomatics, 61(6), 616-624.

Whitton, S. W., Dyar, C., Mustanski, B., \& Newcomb, M. E. (2019).
Intimate partner violence experiences of sexual and gender minority
adolescents and young adults assigned female at birth. Psychology of
Women Quarterly, 43(2), 232-249.

\section*{Appendix}

{\label{appendix}}

\textbf{Table 1}

\emph{Research hotspots every 2 years during the periods 2010--2011,
2012--2013, 2014--2015}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
2010-2011 & Page rank (\%) & 2012-2013 & Page rank (\%) & 2014-2015 &
Page rank (\%)\tabularnewline
\midrule
\endhead
Substance abuse & 6.36\% & substance abuse & 8.17\% & substance abuse &
8.46\%\tabularnewline
posttraumatic stress & 6.26\% & prevalence & 6.07\% & posttraumatic
stress & 7.04\%\tabularnewline
prevalence & 5.91\% & posttraumatic stress & 5.55\% & cognitive behavior
therapy & 6.96\%\tabularnewline
binge eating & 4.70\% & cognitive behavior therapy & 4.67\% & prevalence
& 6.27\%\tabularnewline
children & 4.63\% & children & 3.53\% & validation &
5.14\%\tabularnewline
cognitive behavior therapy & 4.24\% & mental health & 3.17\% &
depression & 4.20\%\tabularnewline
depression & 3.93\% & validity & 2.96\% & adolescents &
3.43\%\tabularnewline
women & 3.54\% & mental disorder & 2.87\% & mental health &
3.41\%\tabularnewline
bulimia nervosa & 3.51\% & depression & 2.84\% & validity &
3.00\%\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2}

\emph{Research hotspots every 2 years during the periods 2016--2017,
2018--2019, 2020--2021, 2022}\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
2016-2017 & Page rank (\%) & 2018-2019 & Page rank (\%) & 2020-2021 &
Page rank (\%) & 2022 & Page rank (\%)\tabularnewline
\midrule
\endhead
posttraumatic stress & 9.21\% & substance abuse & 7.95\% & mental health
& 10.70\% & mental health & 12.20\%\tabularnewline
prevalence & 7.34\% & depression & 7.09\% & depression & 7.45\% &
posttraumatic stress & 8.75\%\tabularnewline
cognitive behavior therapy & 5.68\% & mental health & 6.93\% & substance
abuse & 6.05\% & prevalence & 5.97\%\tabularnewline
mental health & 5.38\% & posttraumatic stress & 5.87\% & posttraumatic
stress & 5.70\% & depression & 4.86\%\tabularnewline
substance abuse & 5.37\% & cognitive behavior therapy & 5.15\% &
prevalence & 5.06\% & substance abuse & 4.44\%\tabularnewline
binge eating & 5.09\% & prevalence & 5.06\% & cognitive behavior therapy
& 4.54\% & binge eating & 3.76\%\tabularnewline
depression & 4.63\% & validation & 4.04\% & binge eating & 3.90\% &
adolescents & 2.88\%\tabularnewline
anorexia nervosa & 3.09\% & validity & 3.33\% & validation & 3.90\% &
children & 2.84\%\tabularnewline
children & 2.97\% & symptoms & 3.11\% & validity & 3.03\% & validity &
2.80\%\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 3}

\emph{Description of the 26 clusters and their main keywords}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Cluster ID & Size & Silhouette & mean(Year) & Main
Keywords\tabularnewline
\midrule
\endhead
0 & 41 & 0.966 & 2013 & borderline personality disorder; confirmatory
factor analysis; emotion regulation; anxiety sensitivity; distress
tolerance\tabularnewline
1 & 41 & 0.984 & 2013 & suicidal ideation; suicide attempt; emotion
regulation; emotion contagion; family expressiveness\tabularnewline
2 & 36 & 0.963 & 2013 & treatment outcome; treatment adaptation;
tailoring psychotherapy; specific phobia; behavior
therapy\tabularnewline
3 & 35 & 0.987 & 2014 & sexual abuse; emotion regulation; posttraumatic
stress; incarcerated women; goal commitment\tabularnewline
4 & 34 & 0.986 & 2014 & posttraumatic stress disorder; anxiety
sensitivity; cortisol rhythm; posttraumatic stress symptoms; college
students\tabularnewline
5 & 32 & 0.965 & 2014 & emotion regulation; distress tolerance; binge
eating; affective lability; of-control eating\tabularnewline
6 & 31 & 0.959 & 2013 & functional analysis; discrete trials; critical
race theory; human operant; multielement design\tabularnewline
7 & 31 & 0.978 & 2014 & anorexia nervosa; eating disorders; quantitative
genetics; emotional abuse; animal models\tabularnewline
8 & 30 & 0.988 & 2012 & performance validity; symptom validity;
pre-exposure prophylaxis; sexual networks; health
insurance\tabularnewline
9 & 29 & 0.964 & 2013 & sexual orientation; sexual risk; mental health;
young women; sexual abuse characteristics\tabularnewline
10 & 28 & 0.939 & 2013 & social phobia; social anxiety disorder;
confirmatory factor analysis; multi-sample analysis; interaction
anxiety\tabularnewline
11 & 28 & 0.98 & 2013 & ecological momentary assessment; smoking
cessation; social overload; health insurance; factor mixture
modeling\tabularnewline
12 & 28 & 0.983 & 2015 & health behavior; health psychology; public
health psychology; military spouse caregiver; sleep
health\tabularnewline
13 & 28 & 0.977 & 2013 & depressive symptoms; sexual minority; major
depressive disorder; qualitative methodology; intergenerational
issues\tabularnewline
14 & 28 & 0.957 & 2016 & contingency management; cocaine dependence;
treatment outcome; trauma-informed care; prolonged exposure
therapy\tabularnewline
15 & 28 & 0.972 & 2013 & physical activity; cardiovascular disease;
cognitive function; heart failure; anorexia nervosa\tabularnewline
16 & 28 & 0.901 & 2013 & alzheimers disease; daily living; injection
drug use; hepatitis c virus; alcohol use\tabularnewline
17 & 26 & 0.951 & 2014 & mental health; hydraulic fracturing; technology
intervention; proactive aggression; parent death\tabularnewline
18 & 26 & 0.964 & 2012 & intimate partner violence; domestic violence;
sexual assault; sexual abuse; therapeutic use\tabularnewline
19 & 26 & 0.987 & 2013 & body dissatisfaction; eating disorders; dietary
restraint; taxometric analysis; psychosocial functioning\tabularnewline
20 & 26 & 0.94 & 2014 & smoking cessation; ecological momentary
assessment; critical race theory; treatment reengagement; treatment
dropout\tabularnewline
21 & 26 & 0.984 & 2013 & executive function; episodic memory; executive
attention; educational disruption; learning disability\tabularnewline
22 & 25 & 0.937 & 2016 & counselor education; online learning; student
engagement; informant discrepancies; lay-delivered
interventions\tabularnewline
23 & 24 & 0.95 & 2015 & substance use; primary care; brief intervention;
parenting management training; siblings\tabularnewline
24 & 23 & 0.975 & 2014 & sexual assault; sexual harassment;
patient-provider communication; emotional abuse; suicide
risk\tabularnewline
25 & 12 & 1 & 2013 & couple therapy; relationship satisfaction; intimate
relationship functioning; intersystem approach; oppositional defiant
disorder\tabularnewline
\bottomrule
\end{longtable}

\selectlanguage{english}
\FloatBarrier
\end{document}

