Algorithmic Music for Therapy: Effectiveness and Perspectives

Feasibility of therapeutic music listening in fibromyalgia: a randomised controlled pilot study

BACKGROUND

Fibromyalgia patients can benefit from music approaches as complementary treatments. In the literature, it was shown that these interventions managed pain conditions as well as reduced complaints, increased relaxation, and improved moods.

OBJECTIVE

This study aimed at evaluating music therapy, in the form of therapeutic music listening, specifically for patients with fibromyalgia, to treat chronic pain by reducing pain perception, increasing well-being, and improving quality of life.

METHODS

Twenty-four patients with fibromyalgia were recruited to take part in this feasibility pilot study that adopted a between-subject and within-subject design. Participants were randomised into three groups: (1) standard care, (2) standard care plus preferred music listening, (3) standard care plus Melomics-Health music listening, composed by an algorithm. Participants in experimental groups listened to 30 min of music at home, twice a day for a month. Patients' perceptions of changes following the listening, the intensity of pain and its interference in their lives, physical and mental well-being, and reported attitudes towards listening to music were evaluated respectively through the patients' global impression of change, the brief pain inventory, the Short Form Healthy Survey-12, and the cognitive behavioural assessment-outcome evaluation.

RESULTS

The study showed that music listening can significantly affect mental well-being compared to no music. Moreover, the effects in the Melomics-Health group are maintained at follow-up. No significant effect on pain perception was noted.

CONCLUSIONS

The study provides information supporting a possible role of music listening in improving well-being of patients with fibromyalgia.

Effect of Algorithmic Music Listening on Cardiac Autonomic Nervous System Activity: An Exploratory, Randomized Crossover Study

It is proven that music listening can have a therapeutic impact in many clinical fields. However, to assume a curative value, musical stimuli should have a therapeutic logic. This study aimed at assessing short-term effects of algorithmic music on cardiac autonomic nervous system activity. Twenty-two healthy subjects underwent a crossover study including random listening to relaxing and activating algorithmic music. Electrocardiogram (ECG) and non-invasive arterial blood pressure were continuously recorded and were later analyzed to measure Heart Rate (HR) mean, HR variability and baroreflex sensitivity (BRS). Statistical analysis was performed using a general linear model, testing for carryover, period and treatment effects. Relaxing tracks decreased HR and increased root mean square of successive squared differences of normal-to-normal (NN) intervals, proportion of interval differences of successive NN intervals greater than 50 ms, low-frequency (LF) and high-frequency (HF) power and BRS. Activating tracks caused almost no change or an opposite effect in the same variables. The difference between the effects of the two stimuli was statistically significant in all these variables. No difference was found in the standard deviation of normal-to-normal RR intervals, LF_power in normalized units and LF_power/HF_power variables. The study suggests that algorithmic relaxing music increases cardiac vagal modulation and tone. These results open interesting perspectives in various clinical areas.

Special Issue: Generative Models in Artificial Intelligence and Their Applications

In recent years, artificial intelligence has been used to generate a significant amount of high-quality data, such as images, music, and videos [...]

Conventional and Algorithmic Music Listening before Radiotherapy Treatment: A Randomized Controlled Pilot Study

Music listening is a widespread approach in the field of music therapy. In this study, the effects of music listening on anxiety and stress in patients undergoing radiotherapy are investigated. Sixty patients with breast cancer who were candidates for postoperative curative radiotherapy were recruited and randomly assigned to three groups: Melomics-Health (MH) group (music listening algorithmically created, n = 20); individualized music listening (IML) group (playlist of preferred music, n = 20); no music group (n = 20). Music listening was administered for 15 min immediately before simulation and during the first five radiotherapy sessions. The State-Trait Anxiety Inventory (STAI) and the Psychological Distress Inventory (PDI) were administered before/after treatment. Cochran’s Q test and McNemar test for paired proportions were performed to evaluate if the proportion of subjects having an outcome score below the critical value by treatment and over time was different, and if there was a change in that proportion. The MH group improved in STAI and PDI. The IML group worsened in STAI at T1 and improved STAI-Trait at T2. The IML group worsened in PDI at T2. The No music group generally improved in STAI and PDI. Clinical and music listening-related implications are discussed defining possible research perspectives in this field.