Jiyang Li,1,* Xinxing Fei,2,* Shiqi Wang,3,4,* Zhangyu Xu,5,6 Fangyuan Xu,5,6 Jianxiong Wang,5,6 Yaqian Gao,7 Yue Hu5,6

1Department of Rehabilitation Medicine, Sichuan Tianfu New Area People’s Hospital, Chengdu, People’s Republic of China; 2Department of Psychiatry, Chengdu Eighth People’s Hospital (Geriatric Hospital of Chengdu Medical College), Chengdu, People’s Republic of China; 3Department of Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 4Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, Sichuan, People’s Republic of China; 5Department of Rehabilitation Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China; 6Rehabilitation Medicine and Engineering Key Laboratory of Luzhou, Luzhou, People’s Republic of China; 7Department of Rehabilitation Medicine, the First Affiliated Hospital of Chengdu Medical College, Chengdu, People’s Republic of China

Background: Many studies have been conducted on the use of selective serotonin reuptake inhibitors (SSRIs) for the treatment of depression. However, the overall trends in research publications in this field remain elusive. There is still little quantitative analysis of the literature in this field. Therefore, we conducted a bibliometric analysis to explore the research patterns surrounding SSRIs for depression, aiming to gain a deeper understanding of their development and impact.
Methods: Publications about the use of SSRIs for the treatment of depression were identified in the Web of Science Core Collection. Visualization analysis was performed with Bibliometrix, VOSviewer, and CiteSpace.
Results: A total of 1149 publications published from 1990 to 2024 were included in the bibliometric analysis. Since 1990, the annual number of published papers has increased annually, reaching the maximum value of output in 2004. Fitted curve showed that after 2004, the number of publications per year was essentially stable The United States dominates the field. Among these institutions, University of Pittsburgh excels in this field. Fava M has the highest scientific productivity and extensive academic influence. European Neuropsychopharmacology is the most active journal in this field. The three most relevant keywords were “fluoxetine”, “double-blind”, and “major depression”. The trend topics in recent years were “connectivity”, “c-reactive protein”, and “anhedonia”.
Conclusion: Research on the use of SSRIs for the treatment of depression continues to receive increased attention but still requiraes further exploration and innovation. We further analyze the current research hotspots and frontiers in this field.

Keywords: selective serotonin reuptake inhibitors, depression, bibliometrics, double-blind, fluoxetine, major depression

Introduction

Depression is characterized by persistent symptoms such as low mood, loss of interest, slowed thinking, and changes in appetite and sleep patterns and can significantly impact a person’s daily life, even leading to suicidal tendencies.1,2 The etiology of depression is multifaceted. Physiologically, depression is often associated with imbalances in brain neurotransmitters, particularly a decrease in serotonin levels.3,4 Psychologically, stress, traumatic events, and personality traits can all increase the risk of developing depression. In short, depression places a great burden on families and society.5

Selective serotonin reuptake inhibitors (SSRIs) have been extensively studied for the treatment of depression, with a wealth of research supporting their effectiveness in managing this mood disorder.6–8 SSRIs work by specifically targeting the serotonin system in the brain, inhibiting the reuptake of serotonin and thereby increasing its availability at synaptic junctions.9 This action is believed to alleviate symptoms of depression by restoring the balance of serotonin levels in the brain. Over the years, numerous studies have investigated the therapeutic benefits of SSRIs for depression.10–12 These studies included randomized controlled trials, meta-analyses, and long-term observational studies, providing a comprehensive understanding of the efficacy, safety, and tolerability of drugs.

Bibliometrics plays a pivotal role in the field of medicine. By employing mathematical and statistical methods, deep and quantitative analyses of medical literature can be performed, enabling researchers to comprehensively and accurately understand the current research status, historical trends, and future directions within the medical domain.13 This approach allows medical researchers to systematically evaluate the quality and impact of various research outcomes, identify emerging topics and research hotspots, and provide valuable guidance for their work.

Despite many studies on the use of SSRIs for the treatment of depression, the overall research trend in this area remains unclear. To bridge this knowledge gap, we conducted a bibliometric analysis to explore the research patterns surrounding SSRIs for depression, aiming to gain a deeper understanding of their development and impact.

Methods

The last search date was April 22, 2024. Both the Web of Science Core Collection (WoSCC) and Scopus are popular search tools for bibliometric analysis.14 Considering the long history and wide recognition of the WoSCC, as well as its rich citation indexing capabilities, we selected the WoSCC as the search tool.15 We used “selective serotonin reuptake inhibitors” and “depression” as the main search terms. Publications in languages other than English were excluded. The two researchers used search strategies to search simultaneously, and when disagreements arose, they resolved them through discussion. The specific search strategy is shown in Table 1. The specific process is shown in Figure 1.

Table 1 Search Strategy

Figure 1 Search flow chart.

In recent years, a significant number of studies on bibliometrics have emerged across various fields.16–21 These studies employ diverse visualization methods. Building upon prior research, we selected the Bibliometrix package in R (version 4.3.1), VOSviewer (version 1.6.18), and CiteSpace (version 6.4 R1) as our visualization analysis tools. The synergy between these software applications enhances the visualization process. The use of these data can make full use of our data and result in clearer and more comprehensible visualizations. All visualization software parameters were set to the defaults. Data obtained from database searches were analyzed with Bibliometrix, and basic data such as publications, citations, annual scientific productivity, and average citations per year were recorded via the overview function. Word frequency and word cloud maps were obtained via keyword analysis. In terms of cooperative relationships, VOSviewer was used to generate a cooperative relationship diagram of authors, institutions, countries/regions, and keyword co-occurrence. CiteSpace was applied mainly to the dual-map overlay of journals.

Results Publications and Citations

A total of 1149 publications published from 1990 to 2024 were included in the analysis. The distribution of article types is shown in Figure 2A. There were 528 articles. There are an average of 5.29 authors per article. As shown in Figure 2B, since 1990, the annual number of published papers has increased annually, reaching the maximum value of output in 2004 (n=85), and the growth rate of published papers during this period was 18.2 per year. We further assessed the trend in the number of publications by fitting a curve, which showed that after 2004, the number of publications per year was essentially stable, with the number fluctuating between 29 and 62. The average annual number of cited articles did not fluctuate greatly, with an average of 1.64 citations per article. Among them, the highest annual number of cited articles was in 2008 (3.06 citations per paper) (Figure 2C).

Figure 2 Publication characteristics. (A) Article type proportions. (B) Annual number of publications. (C) Annual number of publications forecast.

Countries/Regions

We listed the top 10 most popular countries/regions ranked by publication (Table 2). In terms of both the number of articles published and the total number of citations, the United States was in the lead, with the United Kingdom ranking second. In terms of publications, China ranked third. Canada ranked third in terms of total citations. Among them, Denmark ranked first in average citations per article, with a result of 56.10. We used VOSviewer to further analyze the cooperation between countries/regions. The United States, the United Kingdom, China, France, Japan, Germany, Italy, Spain, Canada, and Australia were the countries with the most cooperation (Figure 3A).

Table 2 Top 10 Popular Countries/Regions

Figure 3 Collaboration among individuals. (A) Map of collaboration among countries/regions. (B) Map of collaboration among Institutions. (C) Map of collaboration among authors.

Institutions

We obtained data from the most essential universities using Bibliometrix (Table 3). The University of Pittsburgh led the way in the use of SSRIs for the treatment of depression. Harvard University and Columbia University came next. In terms of the institutions’ cooperative relationships, we discovered that there was strong collaboration. The University of Pittsburgh, Columbia University, University of Oxford, University of Texas Southwestern Medical Center, University of Gothenburg, and Eli Lilly Company were the institutions that collaborated the most (Figure 3B).

Table 3 Top 10 Institutions in Terms of Publication Volume

Authors

Table 4 presents a ranking of the top ten notable authors on the basis of publication, H-index, or citation. With 48 publications, Fava M ranked first in terms of number. Papakostas GI was second, with 26 articles published. Thase ME and Trivedi MH, with twenty publications, ranked third. Fava M had the highest H-index of 28. Furthermore, with 3894 citations overall, Fava M had the most citations. Effective research could not be conducted in isolation from author cooperation. Figure 3C shows who collaborated with the other authors most closely: Fava M, Hieronymus F, Mann JJ, and Papakostas GI. We also examined the author’s time frame for publishing the literature (Figure 4). Among them, Fava M, a prolific author, published related studies from 1997 until 2024. His highest annual volume was in 2004, when he published 6 articles. The second most prolific author, Papakostas GI, concentrated his production between 2004 and 2024.

Table 4 The Top 10 Popular Authors Ranked by Publication/H-Index/Citation

Figure 4 The time distribution of the authors’ publications.

Journals

The publications were drawn from 311 distinct journals in total. With 81 published papers, European Neuropsychopharmacology was the most relevant journal in terms of publication volume (Table 5). With 48 and 47 publications, respectively, the Journal of Clinical Psychiatry and the Journal of Affective Disorders came in second and third place. A hybrid quantitative indicator known as the H-index can be used to compare the level of academic output with the quantity of academic output produced by a researcher or journal. As a result, we further analyzed these journals’ H-indexes in this domain. The top three journals according to H-index rankings were the Journal of Clinical Psychiatry (H-index=33), the Journal of Affective Disorders (H-index=22), and International Clinical Psychopharmacology (H-index=18). Moreover, the journal with the highest impact factor (IF) was Biological Psychiatry, which has an IF of 10.6. More than 70% of these journals are included in area Q1 of the Journal Citation Reports (JCR) partition.

Table 5 Top 10 Popular Journals

As displayed in Table 6 and Figure 5, among Journals cocitations, the most cited journal was the American Journal of Psychiatry (n=495), closely followed by the Journal of Clinical Psychiatry (n=488). Archives of General Psychiatry (n=417), the Journal of Affective Disorders (n=384), and Biological Psychiatry (n=348) are other highly cited journals. The majority of these journals focus on research areas related to psychiatry, drug therapy, and neuroscience. The citation counts for British Journal of Psychiatry and the Journal of Clinical Psychopharmacology were 343 and 280, respectively, indicating the significant impact these publications have on the field of medicinal psychology research. Furthermore, scholarly medical journals such as the Journal of the American Medical Association (JAMA) were mentioned 244 times, suggesting that scholarly journals hold a particular academic standing in psychiatry and drug research in addition to having a significant influence on the medical sector.

Table 6 The Top 10 Cited Journals and Co-Occurrence Discipline

Figure 5 Dual-map overlay of journals in which research was published (left) or cited (right).

Psychiatry has the greatest frequency of occurrence (731 times) among the subject co-occurrence data, reflecting the discipline’s dominance in all the cited journals. Pharmacology and Pharmacy was ranked second with 387 times, indicating the importance of drugs in mental health research. The high frequency of occurrence observed in both neuroscience (336 times) and clinical neurology (284 times) highlights the importance of neuroscience in understanding the molecular underpinnings of mental disease. Furthermore, there were notable disciplinary contributions from clinical psychology (77 times) and internal medicine (89 times). Pediatrics (25 times), genetics (24 times), cardiology (23 times), and gerontology (19 times) were among the low-frequency disciplines.

Keywords

The map of keyword co-occurrence is shown in Table 7. The three most relevant keywords were “fluoxetine”, “double-blind”, and “major depression”. Among them, “fluoxetine” occurred 160 times, “double-blind” 153 times, and “major depression” 130 times. There was little difference in the frequency of the top two keywords. VOSviewer was used to further analyze the co-occurrence of keywords (Figure 6). The keywords associated with “double-blind” were “placebo-controlled trial”, “imipramine”, “amitriptyline”, and “suicide”. In addition, “risk”, “disorder”, “efficacy”, “augmentation”, and “anxiety” were also important keywords. Moreover, the trend topics in recent years were “connectivity”, “C-reactive protein”, and “anhedonia” (Figure 7).

Table 7 Keyword Occurrence Frequency

Figure 6 Map of keyword co-occurrence.

Figure 7 Trend topics between 1995 and 2023.

Discussion

Our study is the first to delve deeply into the relevant research on the use of SSRIs for depression from the perspective of bibliometrics. From 1990 to 2024, research on SSRIs for depression exhibited a remarkable level of activity, with a total of 1149 publications included in the analysis. Among them, 309 articles had an average of 5.29 authors per article, indicating a trend toward teamwork and multiperson participation and highlighting the depth and breadth of research in this field. The annual number of publications has been increasing annually since 1990, reaching a peak in 2004, reflecting the popularity and recognition of SSRIs in the treatment of depression. However, since 2004, although the number of publications has remained stable, fluctuating between 29 and 62; this may suggest that research in this field has entered a mature stage and is awaiting breakthroughs and hotspots. Overall, research on the use of SSRIs for the treatment of depression continues to receive increased amounts of attention but still requires further exploration and innovation.

Our study highlights national/regional and institutional contributions and collaborative models for the use of SSRIs in the treatment of depression. The United States dominates the field, followed by the United Kingdom and China, reflecting the global diversity of research efforts. Denmark stands out for its high-quality research, topping the list in average citations per article. Notably, China ranks third in terms of publications but only tenth in terms of citations, indicating a need to improve the quality of articles. Most of these articles are products of domestic collaborations, with relatively few international collaborations, suggesting that efforts to strengthen international cooperation are necessary.22 Through a deeper comparison with the results of other bibliometric studies in similar fields, we find that the country with the highest ranking in terms of the number of articles and international collaboration in depressive-related fields is the United States, which is similar to the results of this study. The United States has dominated depression research.23–25 Among institutions in the United States, the University of Pittsburgh excels in this field, with Harvard and Columbia Universities also demonstrating strength. Close collaboration among institutions, including frequent partnerships between University of Pittsburgh, Columbia University, and the pharmaceutical company Eli Lilly and Company, underscores the advantages of industry-academia collaboration. Overall, the research in this area has exhibited globalization and diversification, with cooperation and exchange among different countries and institutions driving its in-depth development. In the future, we anticipate that more nations and institutions will collaborate to advance research on depression treatment.

Fava M stands out as the most prolific author with 40 articles as well as the highest H-index, reflecting the quality of his research. Fava M also tops the list in terms of citations, indicating widespread influence. The authors have different distributions of active research time, both in recent years of continuous production and in early concentrated creation. Notably, Fava M, Hieronymus F, Mann JJ, and Papakostas GI collaborate closely with other authors, fostering a collaborative environment that leverages collective strengths to drive progress in the field. There is high-frequency cooperation between Papakostas GI and Fava M.26–29 Their collaborative study focused on the use of selective serotonin reuptake inhibitors to treat major depressive disorder, as well as treating depressive disorders that are particularly resistant to these drugs. In 2024, the two had their most recent collaboration. They published a paper in the journal Molecular Psychiatry entitled Comparative effectiveness research trial for antidepressant incomplete and nonresponders with treatment resistant depression (ASCERTAIN-TRD), a randomized clinical trial”. 30 The results of the study revealed that patients with treatment-resistant depression responded better to recurrent transcranial magnetic stimulation-augmented therapy than to antidepressant medication switching. The shift in direction of their research also suggests that research on treatment-resistant depression has moved toward a new stage of nondrug treatment. More importantly, The findings of their latest collaboration revealed a breakthrough in nondrug treatments for treatment-resistant depression. Studies found that nondrug treatments have been used in patients with mental or behavioral disorders, type 2 diabetes, and liver disease, with some success.31–33 Overall, the diverse mix of authors with varying degrees of productivity, impact, and collaboration provides a rich foundation for continued innovation and advancement in this area of research.

After a thorough analysis of the distribution of journals published in this field, we found that European Neuropsychopharmacology is the most active journal, with the highest number of articles published. Moreover, the Journal of Clinical Psychiatry stands out in terms of its h-index, reflecting its high-level research output and influence. Additionally, the American Journal of Psychiatry has a high IF, demonstrating its academic quality and influence. These journals not only provide researchers with a platform to publish high-quality research results but also promote academic exchange and progress in this field.34,35 The dual map reveals the close connection between highly cited journals in the fields of psychiatry, pharmacology, neuroscience, and the disciplines they cover. As a core discipline, psychiatry is led by highly cited journals such as the American Journal of Psychiatry, which highlights its significant position in this field. Simultaneously, the substantial involvement of neuroscience and pharmacology has promoted the creation and implementation of new knowledge and further enhanced the body of knowledge in psychiatry through cross-disciplinary research. Furthermore, combining the disciplines of clinical medicine and psychology affords a multifaceted outlook for the growth of therapeutic regimens and fosters an all-encompassing comprehension of psychological to biological processes. Importantly, the addition of foundational fields such as molecular biology, along with highly cited journals such as Biological Psychiatry and Molecular Psychiatry, has aided in the growth and depth of psychiatric research and created new avenues for the development of individualized treatment plans, preventative measures, and psychiatric drugs. The close cooperation and knowledge sharing between these disciplines jointly promote frontier progress in the field of psychiatry and provide a solid theoretical basis and innovative direction for clinical practice.

Through an in-depth analysis of the keywords in this field, we gain a glimpse of its research hotspots. The high frequency of keywords such as “fluoxetine”, “double-blind”, and “major depressive disorder” underscores the focus of the current research. Double blinding, as a scientific method to ensure research objectivity, plays a crucial role in the treatment of depression.10,36,37 The efficacy and safety of fluoxetine, a representative antidepressant, has attracted widespread attention. Researchers in this field have continuously explored its effectiveness when used alone or in combination with other drugs, aiming to improve treatment outcomes.38,39 Meanwhile, major depressive disorder, another significant research focus, has garnered significant attention regarding its treatment methods and effectiveness evaluation.40 Researchers are striving to provide patients with diverse treatment options and delve deeper into their pathogenesis and pathophysiological processes.41 These studies not only enhance our understanding of the nature of depression but also offer better therapeutic prospects for patients.

We further discovered a close connection between these hotspots via keyword co-occurrence analysis. Terms related to double-blind trials, such as placebo-controlled trials, imipramine, and amitriptyline, reflect commonly used methods and approaches in antidepressant research. Imipramine and amitriptyline are tricyclic antidepressants (TCAs). Although the anticholinergic effects and membrane-stabilizing properties of TCAs contribute to their poor tolerability and overdose safety, they are still considered viable options for treating depression in certain circumstances.42 The mention of these drugs indicates researchers’ ongoing concern and attention toward the efficacy and safety of traditional antidepressant medications. For example, the common issues with many studies on the safety of antidepressant medications are small sample sizes and short follow-up periods.43,44 Additionally, some studies are limited by a lack of randomization with intervention blinding.45 It is important to consider larger sample sizes and longer time periods in future research. In addition to focusing on drug efficacy and experimental design, current research has focused on various aspects of depression treatment. Keywords associated with major depressive disorder, including suicide, risk, and barriers, highlight the challenges this illness poses to patients’ quality of life and safety.46,47 Researchers are striving to provide more comprehensive and effective treatment plans for patients with depression by exploring new treatment methods, assessing risk factors during the treatment process, and giving attention to the mental health of patients.48,49

Trend topic analysis can help researchers further identify the frontiers of the field. Connectivity reveals the effect of changes in functional connectivity in different brain regions on depression, and SSRIs improve these connections by regulating serotonin levels, thereby relieving symptoms.50–52 This study not only deepens our understanding of the neural mechanisms of depression but also provides a scientific basis for the optimized use of SSRIs. C-reactive protein, an inflammatory marker, plays an important role in the pathogenesis of depression.53 SSRIs may exert their therapeutic effects by regulating the inflammatory response.54 Therefore, studying the relationship between C-reactive protein and the efficacy of SSRIs is crucial for predicting treatment response and recurrence risk. Anhedonia, as a core symptom of depression, significantly impacts patients’ quality of life, emphasizing the need for researchers in this field not only to focus on the disease itself but also to give more attention to managing improvements in patient functioning.55 Moreover, anhedonia may be a significant negative prognostic indicator of treatment-resistant depression.56 It is also a crucial metric for evaluating the efficacy of antidepressant drugs or nondrug treatments.57

There are several limitations in this study. First, the publications included in our analysis were limited to the WoSCC, and our search strategy may not be able to cover all the publications in this field. Second, our bibliometric analysis focuses mainly on evaluating the research performance of scientific publications. This means that our analysis is primarily based on quantitative indicators such as the number of publications, citation count, and author influence. Although these indicators can provide an assessment of research quality and impact to a certain extent, they cannot fully reflect the depth, innovativeness, and practical application value of the research. Finally, with the advent of the digital age, the number and variety of academic publications are increasing dramatically. Bibliometrics must update its data sources in real time to ensure the comprehensiveness and accuracy of the analysis.

Conclusions

Research on the use of SSRIs for the treatment of depression continues to receive increasing attention but still requires further exploration and innovation. The United States dominates the field, and researchers from China need to further improve the quality of their publications. Among these institutions, the University of Pittsburgh excels in this field, with Harvard and Columbia Universities also demonstrating strength. Fava M has the highest scientific productivity and extensive academic influence. European Neuropsychopharmacology is the most active journal in this field.

The high frequency of the key terms “double-blind”, “fluoxetine”, and “major depressive disorder” underscores the focus of the current research. Moreover, ‘connectivity’, ‘C-reactive protein’, and ‘anhedonia’ are the frontiers of future research. In the future, bibliometrics can be incorporated into mainstream literature retrieval tools, including Scopus and Google Academic, to enrich the data sources. Moreover, the literature analysis tools of some databases can be used to check the gaps in the existing analysis tools, which makes the literature metrology results more abundant.

Data Sharing Statement

All the data are available from the corresponding authors upon reasonable request.

Funding

This work was supported by the Southwest Medical University Student Innovation and Entrepreneurship Project Fund (Grant Numbers: 202310632045 and 202310632059).

Disclosure

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

1. Bai Y, Cai Y, Chang D, Li D, Huo X, Zhu T. Immunotherapy for depression: recent insights and future targets. Pharmacol Ther. 2024;257:108624. doi:10.1016/j.pharmthera.2024.108624

2. Chao S. Overview of depression. Emerg Med Clin North America. 2024;42(1):105–113. doi:10.1016/j.emc.2023.06.013

3. Dean J, Keshavan M. The neurobiology of depression: an integrated view. Asian J Psychiatr. 2017;27:101–111. doi:10.1016/j.ajp.2017.01.025

4. Polityńska B, Pokorska O, Wojtukiewicz AM, et al. Is depression the missing link between inflammatory mediators and cancer? Pharmacol Ther. 2022;240:108293.

5. Yang L, Zhao Y, Wang Y, et al. The effects of psychological stress on depression. Curr. Neuropharmacol. 2015;13(4):494–504. doi:10.2174/1570159X1304150831150507

6. Parissis J, Fountoulaki K, Paraskevaidis I, Kremastinos DT. Sertraline for the treatment of depression in coronary artery disease and heart failure. Expert Opinion on Pharmacotherapy. 2007;8(10):1529–1537. doi:10.1517/14656566.8.10.1529

7. De Berardis D, Conti CM, Serroni N, et al. The effect of newer serotonin-noradrenalin antidepressants on cytokine production: a review of the current literature. Inter j Immuno Pharmacol. 2010;23(2):417–422. doi:10.1177/039463201002300204

8. Sheehan DV, Kamijima K. An evidence-based review of the clinical use of sertraline in mood and anxiety disorders. Int Clin Psychopharmacol. 2009;24(2):43–60. doi:10.1097/YIC.0b013e3282f4b616

9. Murphy SE, Capitão LP, Giles SLC, Cowen PJ, Stringaris A, Harmer CJ. The knowns and unknowns of SSRI treatment in young people with depression and anxiety: efficacy, predictors, and mechanisms of action. Lancet Psychiatry. 2021;8(9):824–835. doi:10.1016/S2215-0366(21)00154-1

10. Findling RL, DelBello MP, Zuddas A, et al. Vortioxetine for major depressive disorder in adolescents: 12-week randomized, placebo-controlled, fluoxetine-referenced, fixed-dose study. J Am Acad Child Adolesc Psychiatry. 2022;61(9):1106–1118.e1102. doi:10.1016/j.jaac.2022.01.004

11. McIntyre RS, Florea I, Pedersen MM, Christensen MC. Head-to-head comparison of vortioxetine versus desvenlafaxine in patients with major depressive disorder with partial response to SSRI therapy: results of the VIVRE study. J Clini Psych. 2023;84(4). doi:10.4088/JCP.23m14780

12. Rudzki L, Ostrowska L, Pawlak D, et al. Probiotic Lactobacillus Plantarum 299v decreases kynurenine concentration and improves cognitive functions in patients with major depression: a double-blind, randomized, placebo controlled study. Psychoneuroendocrinology. 2019;100:213–222. doi:10.1016/j.psyneuen.2018.10.010

13. Fei X, Wang S, Li J, Zeng Q, Gao Y, Hu Y. Bibliometric analysis of research on Alzheimer’s disease and non-coding RNAs: opportunities and challenges. Front Aging Neurosci. 2022;14:1037068. doi:10.3389/fnagi.2022.1037068

14. Vitali FC, Pires KM, Cardoso IV, et al. Endodontic therapy in primary teeth: a bibliometric analysis of the 100 most-cited papers. Brazilian Oral Res. 2022;36(e049). doi:10.1590/1807-3107bor-2022.vol36.0049.

15. Goebel MC, Rocha AO, Santos PS, et al. A bibliometric analysis of the top 100 most-cited papers concerning dental fluorosis. Caries Res. 2023;57(4):509–515. doi:10.1159/000530831

16. Huang T, Zhong W, Lu C, et al. Visualized analysis of global studies on cervical spondylosis surgery: a bibliometric study based on web of science database and VOSviewer. Indian j Orthop. 2022;56(6):996–1010. doi:10.1007/s43465-021-00581-5

17. Li B, Tan W, Wang Z, et al. Progress and prospects of gene therapy in ophthalmology from 2000 to 2022: a bibliometric analysis. Heliyon. 2023;9(7):e18228. doi:10.1016/j.heliyon.2023.e18228

18. Li H, Li L, Huang QQ, et al. Global status and trends of metabolomics in diabetes: a literature visualization knowledge graph study. World J Diabetes. 2024;15(5):1021–1044. doi:10.4239/wjd.v15.i5.1021

19. van Eck NJ, Waltman L. Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics. 2017;111(2):1053–1070. doi:10.1007/s11192-017-2300-7

20. Wei D, Zhao L, Hua XY, Zheng MX, Wu JJ, Xu JG. A bibliometric analysis of brachial plexus injury from 1980 to 2022. Heliyon. 2024;10(4):e26175. doi:10.1016/j.heliyon.2024.e26175

21. Xiao P, Li L, Qu J, Wang G. Global research hotspots and trends on robotic surgery in obstetrics and gynecology: a bibliometric analysis based on VOSviewer. Front Surg. 2024;11(null):1308489. doi:10.3389/fsurg.2024.1308489

22. Campbell K, Cooper D, Dias B, et al. Strengthening international cooperation for health and biodiversity. EcoHealth. 2011;8(4):407–409. doi:10.1007/s10393-012-0764-8

23. Bai X, Song Z, Zhou Y, Wang X, Wang Y, Zhang D. Bibliometrics and visual analysis of the research status and trends of postpartum depression from 2000 to 2020. Front Psychol. 2021;12(null):665181. doi:10.3389/fpsyg.2021.665181

24. Zhou F, Zhang T, Jin Y, et al. Unveiling the knowledge domain and emerging trends of olfactory dysfunction with depression or anxiety: a bibliometrics study. Front Neurosci. 2022;16(null):959936. doi:10.3389/fnins.2022.959936

25. Zou X, Sun Y. Bibliometrics analysis of the research status and trends of the association between depression and insulin from 2010 to 2020. Front Psychiatry. 2021;12(null):683474. doi:10.3389/fpsyt.2021.683474

26. Papakostas GI, Petersen TJ, Nierenberg AA, et al. Ziprasidone augmentation of selective serotonin reuptake inhibitors (SSRIs) for SSRI-resistant major depressive disorder. J Clin Psychiatry. 2004;65(2):217–221. doi:10.4088/JCP.v65n0212

27. Papakostas GI, Shelton RC, Smith J, Fava M. Augmentation of antidepressants with atypical antipsychotic medications for treatment-resistant major depressive disorder: a meta-analysis. J Clin Psychiatry. 2007;68(6):826–831. doi:10.4088/JCP.v68n0602

28. Papakostas GI, Shelton RC, Zajecka JM, et al. L-methylfolate as adjunctive therapy for SSRI-resistant major depression: results of two randomized, double-blind, parallel-sequential trials. Am J Psychiatry. 2012;169(12):1267–1274. doi:10.1176/appi.ajp.2012.11071114

29. Papakostas GI, Stahl SM, Krishen A, et al. Efficacy of bupropion and the selective serotonin reuptake inhibitors in the treatment of major depressive disorder with high levels of anxiety (anxious depression): a pooled analysis of 10 studies. J Clin Psychiatry. 2008;69(8):1287–1292. doi:10.4088/JCP.v69n0812

30. Papakostas GI, Trivedi MH, Shelton RC, et al. Comparative effectiveness research trial for antidepressant incomplete and non-responders with treatment resistant depression (ASCERTAIN-TRD) a randomized clinical trial. Mol Psychiatry. 2024;null(null):null.

31. Abbas S, Ihle P, Adler JB, et al. Predictors of non-drug psychiatric/psychotherapeutic treatment in children and adolescents with mental or behavioural disorders. Eur Child Adolesc Psychiatry. 2017;26(4):433–444. doi:10.1007/s00787-016-0900-z

32. Wang PP, Huang X, Yang MW, Fang SY, Hong FF, Yang SL. Effects of non-drug treatment on liver cells apoptosis during hepatic ischemia-reperfusion injury. Life Sci. 2021;275(null):119321. doi:10.1016/j.lfs.2021.119321

33. Wei JP, Wang QH, Zheng HJ, Wei F. Research progress on non-drug treatment for blood glucose control of type 2 diabetes mellitus. Chin j Integr Med. 2018;24(10):723–727. doi:10.1007/s11655-018-2844-2

34. Akmal M, Hasnain N, Rehan A, et al. Glioblastome multiforme: a bibliometric analysis. World Neurosurg. 2020;136:270–282. doi:10.1016/j.wneu.2020.01.027

35. Brandt JS, Hadaya O, Schuster M, Rosen T, Sauer MV, Ananth CV. A bibliometric analysis of top-cited journal articles in obstetrics and gynecology. JAMA network open. 2019;2(12):e1918007. doi:10.1001/jamanetworkopen.2019.18007

36. Cipriani A, Furukawa TA, Salanti G, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet. 2018;391(10128):1357–1366. doi:10.1016/S0140-6736(17)32802-7

37. Davey CG, Chanen AM, Hetrick SE, et al. The addition of fluoxetine to cognitive behavioural therapy for youth depression (YoDA-C): a randomised, double-blind, placebo-controlled, multicentre clinical trial. Lancet Psychiatry. 2019;6(9):735–744. doi:10.1016/S2215-0366(19)30215-9

38. Lapierre YD, Joffe R, McKenna K, et al. Moclobemide versus fluoxetine in the treatment of major depressive disorder in adults. J Psychiatr Neurosci. 1997;22(2):118–126.

39. Nilsson M, Joliat MJ, Miner CM, Brown EB, Heiligenstein JH. Safety of subchronic treatment with fluoxetine for major depressive disorder in children and adolescents. J Child Adolesc Psychopharmacol. 2004;14(3):412–417. doi:10.1089/cap.2004.14.412

40. Kim YK. Molecular neurobiology of major depressive disorder. Prog Neuro Psychopharmacol Biol Psychiatry. 2016;64:275–276. doi:10.1016/j.pnpbp.2015.07.004

41. Cui L, Li S, Wang S, et al. Major depressive disorder: hypothesis, mechanism, prevention and treatment. Signal Transduct Target Ther. 2024;9(1):30. doi:10.1038/s41392-024-01738-y

42. Harmer CJ, Duman RS, Cowen PJ. How do antidepressants work? New perspectives for refining future treatment approaches. Lancet Psychiatry. 2017;4(5):409–418. doi:10.1016/S2215-0366(17)30015-9

43. Riblet NB, Young-Xu Y, Shiner B, Schnurr PP, Watts BV. The efficacy and safety of buprenorphine for the treatment of depression: a systematic review and meta-analysis. J Psychiatr Res. 2023;161(null):393–401. doi:10.1016/j.jpsychires.2023.03.037

44. Włodarczyk A, Cubała WJ, Gałuszko-Węgielnik M, Szarmach J. Central nervous system-related safety and tolerability of add-on ketamine to antidepressant medication in treatment-resistant depression: focus on the unique safety profile of bipolar depression. Ther adv psychopharm. 2021;11(null):20451253211011021.

45. Szarmach J, Cubała WJ, Włodarczyk A, Gałuszko-Węgielnik M. Somatic comorbidities and cardiovascular safety in ketamine use for treatment-resistant depression. Medicina-Lithuania. 2021;57(3):null.

46. Dolsen EA, Cheng P, Arnedt JT, et al. Neurophysiological correlates of suicidal ideation in major depressive disorder: hyperarousal during sleep. J Affective Disorders. 2017;212:160–166. doi:10.1016/j.jad.2017.01.025

47. Miret M, Ayuso-Mateos JL, Sanchez-Moreno J, Vieta E. Depressive disorders and suicide: epidemiology, risk factors, and burden. Neurosci Biobehav Rev. 2013;37(10 Pt 1):2372–2374. doi:10.1016/j.neubiorev.2013.01.008

48. DeFilippis M, Wagner KD. Management of treatment-resistant depression in children and adolescents. Paediatric Drugs. 2014;16(5):353–361. doi:10.1007/s40272-014-0088-y

49. Edinoff AN, Akuly HA, Hanna TA, et al. Selective serotonin reuptake inhibitors and adverse effects: a narrative review. Neurol Int. 2021;13(3):387–401. doi:10.3390/neurolint13030038

50. DeMaster D, Godlewska BR, Liang M, et al. Effective connectivity between resting-state networks in depression. J Affective Disorders. 2022;307:79–86. doi:10.1016/j.jad.2022.03.041

51. Lee KH, Shin J, Lee J, Yoo JH, Kim JW, Brent DA. Measures of connectivity and dorsolateral prefrontal cortex volumes and depressive symptoms following treatment with selective serotonin reuptake inhibitors in adolescents. JAMA network open. 2023;6(8):e2327331. doi:10.1001/jamanetworkopen.2023.27331

52. Vai B, Bulgarelli C, Godlewska BR, Cowen PJ, Benedetti F, Harmer CJ. Fronto-limbic effective connectivity as possible predictor of antidepressant response to SSRI administration. Eur Neuropsychopharmacol. 2016;26(12):2000–2010. doi:10.1016/j.euroneuro.2016.09.640

53. Zhou J, Zhou J, Sun Z, et al. The association of C-reactive protein with responses to escitalopram antidepressant treatment in patients with major depressive disorder. J Affective Disorders. 2022;306:32–38. doi:10.1016/j.jad.2022.02.069

54. Bambling M, Edwards SC, Hall S, Vitetta L. A combination of probiotics and magnesium orotate attenuate depression in a small SSRI resistant cohort: an intestinal anti-inflammatory response is suggested. Inflammopharmacology. 2017;25(2):271–274. doi:10.1007/s10787-017-0311-x

55. Höflich A, Michenthaler P, Kasper S, Lanzenberger R. Circuit mechanisms of reward, anhedonia, and depression. Int J Neuropsychopharmacol. 2019;22(2):105–118. doi:10.1093/ijnp/pyy081

56. McMakin DL, Olino TM, Porta G, et al. Anhedonia predicts poorer recovery among youth with selective serotonin reuptake inhibitor treatment-resistant depression. J Am Acad Child Psy. 2012;51(4):404–411. doi:10.1016/j.jaac.2012.01.011

57. Yee A, Chin SC, Hashim AH, et al. Anhedonia in depressed patients on treatment with selective serotonin reuptake inhibitor anti-depressant--A two-centered study in Malaysia. Int j psychiat clin. 2015;19(3):182–187. doi:10.3109/13651501.2015.1031139