Distribution of publications across journals
Annual publication output showed an overall upward pattern during the study period, increasing from 32 publications in 2016 to 72 in 2024, with year-to-year fluctuations.
From 2016 to 2025, the ten most productive journals published 132 articles, accounting for 25.5% of the 518 included publications, with a mean Impact Factor (IF) of 2.9 (Table 1). Journal of Music Therapy published 52 articles, representing 39.4% of the 132 articles in the top ten journals. Other journals publishing at least ten articles were the International Journal of Environmental Research and Public Health (n = 16), Acta Paediatrica (n = 13), PLOS One (n = 11), and Journal of Pediatric Nursing (n = 10). International Journal of Environmental Research and Public Health had the highest IF, at 4.8. Among the ten journals, 20% were classified as Journal Citation Reports (JCR) Q1 and 70% as Q2. Journal of Music Therapy had the largest publication count but a lower IF and quartile ranking than several other journals in the group. The journals represented the disciplines of music therapy, pediatrics, nursing, public health, and complementary therapy.
Network analysis of collaborative relationships
Analysis of national collaboration
Country names were standardized according to the preprocessing rules described in the Protocol. The resulting country-collaboration network was visualized using SCImago Graphica (Figure 2A). Collaboration links involved the United States, China, Australia, Canada, Norway, Denmark, Israel, Poland, Turkey, and Italy, while China was also connected with Finland, Brazil, Iran, and Singapore. Publication output was led by the United States (n = 140) and China (n = 65), followed by Australia (n = 38), Canada (n = 31), Germany (n = 29), Norway (n = 26), the Netherlands (n = 24), and Turkey and Italy (n = 22 each); France also appeared among the top ten countries (Figure 2B). Output was therefore concentrated in North America, Asia, and Europe.
Researcher collaboration and academic influence
The VOSviewer author network identified several collaboration groups (Figure 3). Connected authors included Monika Geretsegger, Grace Thompson, Christian Gold, Cochavit Elefant, Łucja Bieleninik, Shulamit Epstein, Ingrid Kvestad, Jörg Assmus, Mark Ettenberger, Tora Söderström Gaden, Bente Johan Vederhus, and Shmuel Arnon. The ten authors with the highest publication output were Christian Gold, Cochavit Elefant, Łucja Bieleninik, Qiang Chen, Hua Cao, Jörg Assmus, Shmuel Arnon, Dirk Bassler, Nienke H. van Dokkum, and Ya Li Huang (Table 2). These authors were affiliated with institutions in Norway, Israel, Poland, China, Switzerland, and the Netherlands. The network included several regional and cross-national teams, including established groups in Europe and Israel, as well as contributors from Fujian Province, China.
Analysis of keywords and research hotspots
Analysis of the keyword co-occurrence network
CiteSpace identified 286 keyword nodes and 253 co-occurrence links, with a network density of 0.0062 (Figure 4). Node size represented keyword frequency, purple rings indicated high betweenness centrality, red tree rings indicated burst periods, and links represented keyword co-occurrence, with thicker links indicating stronger associations. The low density indicated a sparse network with limited co-occurrence among topics14. Keywords were standardized according to the preprocessing rules described in the Protocol before construction of the co-occurrence network. Prominent themes included music therapy, art therapy, systems analysis, mental health, and quality of life.
Table 3 presents the twenty keywords with the highest reported frequency and centrality values. "Music therapy" occurred 147 times and had a centrality of 0.71; "systematic review" occurred 18 times with a centrality of 0.14; "mental health" occurred 6 times with a centrality of 0.12; "art therapy" occurred 14 times with a centrality of 0.11; "autism spectrum disorder" occurred 14 times with a centrality of 0.10; and "music intervention" occurred 8 times with a centrality of 0.10. Betweenness centrality reflects the extent to which a node connects otherwise separated parts of a network. Thus, "music therapy" was the principal connecting term, while "systematic review" had the second-highest centrality despite its lower frequency.
Overall, the low-density co-occurrence network was sparse, with limited integration among its principal topics. Mental health and music intervention were among the themes identified for further investigation.
Analysis of keyword cluster and emerging terms
Keyword clustering was performed using the log-likelihood ratio algorithm with one year per time slice14. This approach has been used to identify research hotspots and thematic trends in previous bibliometric studies15. The resulting keyword-cluster map is shown in Figure 5. The analysis yielded a Modularity Q of 0.85 and a Weighted Mean Silhouette S of 0.98. These values exceeded the stated thresholds of Q > 0.3 and S > 0.7, indicating well-separated and internally coherent clusters. The ten largest clusters were music therapy, art therapy, systematic review, integrative medicine, preterm infant, music intervention, autism spectrum disorder, complementary medicine, cardiac surgery, and mental health (Figure 5). The map showed several distinct thematic groupings, with links between neighboring clusters indicating overlap among related research topics. Cluster labels were numbered #0–#9, with lower numbers denoting clusters containing more keywords.
Burst terms are keywords whose frequency increases sharply during a defined period. CiteSpace identified 23 burst terms in the current dataset (Figure 6). Early burst terms included "hematopoietic stem cell transplantation," "cochlear implant," "qualitative research," and "music reminiscence activity." These terms describe changes in keyword attention and do not by themselves establish clinical importance or intervention effectiveness.
Several burst terms were confined to short intervals. From 2018 to 2019, acute pain, auditory integration training, complementary and alternative medicine, and developmental care appeared as burst terms. From 2020 to 2021, neonatal intensive care unit (NICU), critical care, and cardiac surgery appeared. Mental health and the COVID-19 pandemic were observed from 2021 to 2023, followed by terms including intensive care unit, hospitalized children, and pain management after 2022. These patterns indicate shifts in publication emphasis rather than a validated sequence of clinical development.
In the current analysis, "music intervention" had the strongest burst intensity (2.43), followed by "creative arts therapy" and "intensive care unit" (1.46 each). The burst analysis suggests that publication attention broadened from rehabilitation and complementary approaches toward critical-care settings, evidence synthesis, and more systematic descriptions of music interventions. Because burst strength measures changes in keyword frequency, it should not be interpreted as evidence of treatment effectiveness or clinical maturity.
Research frontiers and temporal evolution
Figure 7 displays the temporal distribution of keyword clusters #0–#9 in the cluster-timeline analysis. The earliest clusters included music therapy, systematic review, music intervention, cardiac surgery, and mental health. The preterm infant cluster first appeared in 2018. Music therapy, systematic review, and mental health persisted across the full ten-year period, whereas cardiac surgery had the shortest duration, at five years. Art therapy, qualitative research, and complementary medicine became visible from 2017 onward.
The time-zone map contained 286 nodes and 309 edges, with a density of 0.0076, a Modularity Q of 0.85, and a Weighted Mean Silhouette S of 0.99 (Figure 8)16. The sparse network nevertheless contained well-separated clusters. Three descriptive periods were observed. During 2016–2017, prominent terms included music therapy, mental health, heart rate, and anxiety. During 2018–2021, terms included preterm infant, quality of life, auditory integration training, sensory processing, and pediatric oncology. During 2022–2025, terms increasingly referred to specific clinical settings, including intensive care and neonatal intensive care, as well as evidence-synthesis terms such as systematic review and bibliometric analysis. Keywords appearing during 2021–2025 also included digital health, connected health, auditory novelty detection, and kangaroo care. These patterns describe changes in keyword attention and should not be interpreted as evidence of increasing intervention precision or effectiveness.
Data Availability:
The bibliographic data underlying this study have been deposited in Zenodo and are publicly available at https://zenodo.org/records/22171844. The deposited files include the original PubMed records retrieved using the search strategy described in the Protocol, the cleaned and standardized dataset used for bibliometric analysis, the keyword and synonym normalization table, and the relevant analysis output files used to generate the reported results and figures. No new primary data were collected for this study.

Figure 1: Research flowchart. PubMed retrieval yielded 527 records. After data cleaning, deduplication, and eligibility screening, 5 retracted records and 4 records that did not meet the eligibility criteria were excluded, leaving 518 articles for analysis. Excel was used for publication statistics; CiteSpace for keyword co-occurrence, clustering, burst detection, and temporal analyses; VOSviewer for author- and country-level collaboration networks; and SCImago Graphica for visualization of the country-collaboration network. Please click here to view a larger version of this figure.

Figure 2: Country collaboration network and top 10 countries by publication output in pediatric music therapy research (2016–2025). (A) Links represent country-level collaboration, with thicker links indicating stronger connections and colors indicating collaboration groups. (B) Publication output was concentrated in a limited number of countries, led by the United States and China, followed by Australia, Canada, Germany, Norway, the Netherlands, Turkey, Italy, and France. Please click here to view a larger version of this figure.

Figure 3: Author collaboration network in pediatric music therapy research (2016–2025). Nodes represent authors, links represent co-authorship relationships, and colors indicate collaboration clusters. The network contains several distinct research groups, with Christian Gold among the authors connecting collaborative teams. Please click here to view a larger version of this figure.

Figure 4: Keyword co-occurrence map in pediatric music therapy research (2016–2025). Nodes represent keywords; node size indicates frequency; purple rings indicate high betweenness centrality; red tree rings indicate periods of keyword burst; and links indicate keyword co-occurrence. The map identifies frequently occurring and structurally central topics, including music therapy, systematic review, art therapy, quality of life, and mental health. Please click here to view a larger version of this figure.

Figure 5: Keyword cluster analysis of pediatric music therapy research (2016–2025). The CiteSpace cluster map displays the ten largest keyword clusters, labeled #0–#9, with lower cluster numbers indicating larger clusters. Major clusters included music therapy, art therapy, systematic review, integrative medicine, preterm infant, music intervention, autism spectrum disorder, complementary medicine, cardiac surgery, and mental health. The clustering yielded a Modularity Q of 0.85 and a Weighted Mean Silhouette S of 0.98, indicating well-separated and internally coherent clusters. Please click here to view a larger version of this figure.

Figure 6: Top 23 keywords with the strongest citation bursts. Burst detection identifies keywords whose frequency increased sharply during specific periods between 2016 and 2025. The figure describes temporal changes in keyword attention; burst strength does not measure clinical importance or intervention effectiveness. Please click here to view a larger version of this figure.

Figure 7: Keyword-cluster timeline in pediatric music therapy research (2016–2025). Each horizontal line represents a keyword cluster, and node positions indicate when keywords within that cluster appeared and persisted. The timeline describes changes in the occurrence of keyword clusters over the study period. Please click here to view a larger version of this figure.

Figure 8: Keyword time-zone map in pediatric music therapy research (2016–2025). Individual keywords are arranged by year of appearance, and links show relationships across successive periods. The network contains 286 nodes and 309 edges, with a density of 0.0076, Modularity Q of 0.85, and Weighted Mean Silhouette S of 0.99. The combination of low density and high Q and S values indicates a sparse network containing well-separated clusters. Please click here to view a larger version of this figure.
| Journal | Count | Percentage of included publications (N = 518) | Impact factor (2021-2025) | JCR quartile |
| Journal of music therapy | 52 | 10.00% | 1.9 | Q4 |
| International journal of environmental research and public health | 16 | 3.10% | 4.8 | Q2 |
| Acta paediatrica | 13 | 2.50% | 2.5 | Q2 |
| PloS one | 11 | 2.10% | 3.2 | Q2 |
| Journal of pediatric nursing | 10 | 1.90% | 2.7 | Q1 |
| Complementary therapies in clinical practice | 7 | 1.30% | 3.3 | Q2 |
| BMC pediatrics | 6 | 1.20% | 2.5 | Q2 |
| BMJ open | 6 | 1.20% | 2.7 | Q2 |
| Medicine | 6 | 1.20% | 1.6 | Q2 |
| Complementary therapies in medicine | 5 | 1.00% | 3.8 | Q1 |
| / | 132 | 25.50% | 2.9 | / |
Table 1: Top 10 journals by publication output in pediatric music therapy (2016–2025). The ten journals published 132 articles, representing 25.5% of the included publications. Percentages for individual journals were calculated using the full included dataset (N = 518) as the denominator. Two journals were classified as JCR Q1, seven as Q2, none as Q3, and one as Q4.
| Number | Author | Count | Percentage (N=518) | Institutions, and Countries |
| 1 | Gold, Christian | 17 | 3.28% | University of Bergen, Norway |
| 2 | Elefant, Cochavit | 11 | 2.12% | University of Haifa, Israel |
| 3 | Bieleninik, Łucja | 11 | 2.12% | Gdańsk University, Poland |
| 4 | Chen, Qiang | 9 | 1.74% | Fujian Maternity and Child Health Hospital, China |
| 5 | Cao, Hua | 8 | 1.54% | Fujian Maternity and Child Health Hospital, China |
| 6 | Assmus, Jörg | 8 | 1.54% | Norwegian Research Centre, Norway |
| 7 | Arnon, Shmuel | 7 | 1.35% | Tel Aviv University, Israel |
| 8 | Bassler, Dirk | 7 | 1.35% | University Hospital Zurich and University of Zurich, Switzerland |
| 9 | Van Dokkum, Nienke H | 5 | 0.97% | University of Groningen, Netherlands |
| 10 | Huang, Ya-Li | 5 | 0.97% | Fujian Maternity and Child Health Hospital, China |
Table 2: Top 10 authors by publication output in pediatric music therapy (2016–2025). The table reports each author's publication count and institutional affiliation. The listed authors were affiliated with institutions in Europe, the Middle East, and Asia, reflecting the international distribution of research activity.
| Frequency | Centrality | Year | Keywords |
| 147 | 0.71 | 2016 | music therapy |
| 18 | 0.14 | 2016 | systematic review |
| 14 | 0.1 | 2018 | autism spectrum disorder |
| 14 | 0.11 | 2017 | art therapy |
| 8 | 0.04 | 2019 | quality of life |
| 8 | 0.1 | 2016 | music intervention |
| 8 | 0.02 | 2021 | preterm infant |
| 7 | 0.01 | 2018 | neonatal intensive care unit |
| 6 | 0.12 | 2016 | mental health |
| 6 | 0.01 | 2017 | qualitative research |
| 6 | 0.01 | 2020 | pain management |
| 5 | 0.04 | 2017 | randomized controlled trial |
| 5 | 0.02 | 2017 | complementary medicine |
| 4 | 0 | 2016 | cochlear implant |
| 4 | 0.01 | 2018 | preterm infant |
| 4 | 0.01 | 2018 | creative arts therapy |
| 4 | 0.01 | 2020 | heart rate variability |
| 4 | 0.04 | 2019 | physical activity |
| 4 | 0.01 | 2019 | child development |
| 3 | 0.01 | 2016 | speech therapy |
Table 3: Top 20 keywords in pediatric music therapy research (2016–2025). The table reports keyword frequency, betweenness centrality, and year of first occurrence. Music therapy had the highest frequency and centrality; other prominent terms included systematic review, mental health, art therapy, autism spectrum disorder, and music intervention.