Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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PloS one
High-frequency vs. low-frequency MIDI-assisted group music therapy in psychiatric inpatients: A randomized controlled trial
BACKGROUND: Music therapy has been increasingly incorporated into psychiatric inpatient care as an adjunctive intervention; however, evidence regarding its comparative effectiveness, particularly with respect to intervention intensity during brief psychiatric hospitalizations, remains limited. Most randomized trials have evaluated interventions delivered over several weeks, leaving uncertainty about the potential differential effects of higher versus lower intervention intensity within short inpatient stays. METHODS: This randomized controlled trial with a parallel-group design was conducted in an adult psychiatric inpatient unit in Bogotá, Colombia. Participants were randomly assigned (1:1) to either a high-frequency music therapy group, which received five sessions delivered on consecutive days within a single inpatient week, or a low-frequency group, which received one session during the same period. Allocation concealment was ensured through computer-generated randomization performed by an independent researcher not involved in participant recruitment or outcome assessment. Primary outcomes were symptoms of depression, anxiety, and stress, assessed using the Depression Anxiety Stress Scale-21 (DASS-21) at baseline and at the end of the intervention week. Secondary outcomes included emotional responses to music therapy, assessed using selected items from the Questionnaire of the Impact of Music Therapy Sessions in Adults (CISMA instrument), and global life satisfaction, measured with the Satisfaction With Life Scale (SWLS). Between-group changes over time were analyzed using repeated-measures mixed-effects linear models. RESULTS: A total of 91 participants were randomized, of whom 74 (37 per group) completed post-intervention assessments and were included in the per-protocol analysis. Between-group analyses revealed a statistically significant group × time interaction for the DASS-21 stress subscale only. Participants in the high-frequency music therapy group showed a greater reduction in stress scores compared with the low-frequency group, with a statistical between-group difference (6.49 ± 5.55 vs. 7.03 ± 5.81; p = 0.023). No statistically significant between-group differences were observed for the DASS-21 anxiety subscale (p = 0.339) or the depression subscale (p = 0.270). Global life satisfaction, as measured by the SWLS, did not differ significantly between groups (p > 0.05). For secondary outcomes assessed using selected CISMA items related to emotional change, between-group differences were small and not statistically significant across all items. Overall, except for stress symptoms, outcomes did not differ significantly between the high-frequency and low-frequency intervention groups. CONCLUSIONS: In this randomized controlled trial, a higher frequency of music therapy sessions was associated with a greater reduction in stress symptoms compared with a lower-frequency intervention during a brief psychiatric hospitalization. However, no between-group differences were observed for anxiety, depression, life satisfaction, or emotional response measures. Overall, these findings indicate limited evidence of differential effectiveness by intervention intensity and should be interpreted cautiously in light of the study's methodological limitations. TRIAL REGISTRATION: ISRCTN registry: ISRCTN87861817 (https://www.isrctn.com/ISRCTN87861817).
18 Apr 2026
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Adaptive Feature Fusion Gate and Gated Channel-Spatial Attention in CNN-Transformer Models for Music Genre Classification
With the rapid growth of music data, automatic music genre classification has become a critical task in music information retrieval. Traditional methods based on handcrafted features are increasingly inadequate when handling large-scale analysis. This paper proposes the Convolutional Neural Network-Gated Transformer Network (CT-GateNet), a hybrid architecture that integrates a gated channel-spatial attention mechanism with an adaptive feature fusion gating mechanism to achieve discriminative feature learning and efficient feature integration. To mitigate data scarcity, a data augmentation strategy based on a denoising diffusion probabilistic model is introduced. Experiments are conducted on three public music genre datasets: GTZAN, FMA-SMALL and FMA-Medium. The method achieves classification accuracies of 98.72%, 89.42%, and 69.07% on GTZAN, FMA-SMALL and FMA-Medium, respectively, demonstrating outstanding performance and robust generalization capabilities. These results validate CT-GateNet's effectiveness in music genre classification and provide valuable insights for audio classification research.
11 Apr 2026
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