The study recruited 90 participants, evenly split between 45 males and 45 females, and divided them into three age bands: 20 to 24 years, 25 to 30 years, and 31 to 35 years. Participants were selected through convenience sampling, a common approach in psychology research in which volunteers are drawn from an accessible population rather than randomly from the wider public. Each respondent completed two standardized instruments. The Brief Music in Mood Regulation Scale, developed by Saarikallio, measures the ways people deliberately use listening to manage their emotional states, from reviving a flagging mood to discharging tension. The Oxford Happiness Questionnaire, created by Hills and Argyle, provides a compact measure of broader psychological well-being and life satisfaction.

The statistical design was straightforward but rigorous. The researchers computed descriptive statistics for each group and then ran a two-way analysis of variance, or ANOVA, to test whether age, gender, or the combination of the two influenced music-based mood regulation. A two-way ANOVA is useful here because it can separate the independent contribution of each factor from any interaction between them; for example, it can reveal whether gender differences in music use depend on how old a person is. When the ANOVA flagged significant differences, Tukey’s honestly significant difference post hoc test was applied to pinpoint exactly which age groups differed from one another. Finally, Pearson’s correlation coefficient was calculated to assess whether scores on the mood-regulation scale tracked scores on the happiness questionnaire across individuals.

The results were striking in their asymmetry. For music-based mood regulation, both main effects were statistically significant. Age produced a large effect, with an F statistic of 48.687 and a p value of .001, meaning the probability of observing such a difference by chance alone is roughly one in a thousand. Gender also mattered, with an F of 5.024 and a p value of .028, a more modest but still reliable difference between males and females. Crucially, however, the interaction between age and gender was not significant, indicating that the age-related pattern of music use held broadly across both sexes rather than being driven by one particular combination of age and gender.

The post hoc comparisons added texture to the age effect. Participants aged 25 to 30 differed significantly from both the 20-to-24 group and the 31-to-35 group in how much they used music to regulate their moods. This non-linear pattern is intriguing: the middle band of young adulthood, a period often marked by career consolidation, relationship transitions, and mounting responsibilities, appears to be the stage at which music is deployed most intensively as an emotional tool. The youngest adults, still close to student life, and the oldest participants, approaching midlife, reported less reliance on music for mood management than those navigating the demands of the late twenties.

When the researchers turned to happiness, the picture changed completely. Neither age, nor gender, nor their interaction produced a significant effect on Oxford Happiness Questionnaire scores. Happiness, in this sample, was remarkably flat across the demographic categories the study examined. More surprising still was the correlation analysis: the relationship between music-based mood regulation and happiness was essentially nonexistent, with a Pearson’s r of .017 and a p value of .876. A correlation coefficient of that magnitude is indistinguishable from zero, meaning that knowing how often or how deliberately someone uses music to manage moods tells you almost nothing about how happy they report being overall.

Why would a behavior so universally associated with emotional relief fail to predict happiness? The authors argue that the answer lies in the distinction between short-term emotional regulation and long-term well-being. Music appears to be an effective strategy for managing immediate emotional experiences, smoothing over transient states of stress, boredom, or sadness. Happiness, however, is a more durable construct shaped by a constellation of psychological and contextual factors, including personality, social relationships, economic circumstances, and life meaning. A tool that works in the moment does not necessarily accumulate into lasting life satisfaction, and the near-zero correlation in this study is a quantitative expression of that gap.

The findings sit within a rich body of prior research. Earlier work by Saarikallio and Erkkilä established that adolescents routinely use music for mood regulation, and subsequent studies have documented the practice across cultures and age groups. Research during the early stages of the COVID-19 pandemic found that people turned to music as a coping resource during lockdowns, and a 2025 meta-analysis of music-based interventions reported benefits for subjective well-being in both clinical and nonclinical populations. Other studies have explored gender differences in emotional reactions to music, finding variations in autonomic reactivity and self-reported responses. The new Indian study adds an important data point by showing that demographic variation in music use does not translate into demographic variation in happiness, at least among young adults in an Indian sample where such evidence has been scarce.

The practical implications are nuanced. The authors suggest that music-based interventions retain real value in mental health, educational, and community settings, particularly for helping people manage acute emotional states. Programs such as Tuned In, which uses music listening to teach emotion-regulation skills to adolescents, exemplify how structured music use can be embedded in schools and clinics. At the same time, the study cautions against overselling music as a route to happiness. If the goal is to raise durable well-being, music may need to be paired with interventions that target the broader determinants of life satisfaction rather than treated as a standalone solution. The finding that the 25-to-30 age band uses music most intensively also hints that this group, often juggling the heaviest work and family pressures, may be a natural audience for such programs.

As with any study, the design carries limitations that shape how far the conclusions can travel. The sample of 90 participants recruited by convenience is small and may not represent the diversity of young adults in India or elsewhere, and the cross-sectional design captures a single moment in time rather than tracking individuals as they age. The authors recommend that future research employ larger and more varied samples, longitudinal designs that follow participants over years, and a wider set of psychological variables to build a fuller picture of how music and well-being interact. Raw data were not made public owing to privacy considerations, though the researchers note it can be shared on reasonable request. Even with these caveats, the study delivers a memorable message for anyone who has ever reached for headphones in a difficult moment: music is a genuine and widely used instrument of emotional self-regulation, one whose intensity shifts with age and differs between men and women, but the happiness it delivers is real-time relief rather than a lasting foundation, and a good life continues to depend on much more than a well-curated playlist.

Subject of Research: The influence of age and gender on music-based mood regulation and its relationship to happiness in young adults

Article Title: Music-based mood regulation and happiness among young adults: understanding the role of age and gender

Article References: Parida, M., & Das, P. P. P. (2026). Music-based mood regulation and happiness among young adults: understanding the role of age and gender. SN Social Sciences, 6(8), Article 353. https://doi.org/10.1007/s43545-026-01632-0

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01632-0

Keywords: music, mood regulation, happiness, young adults, emotion regulation, well-being, age differences, gender differences, psychology, Oxford Happiness Questionnaire, BMMR scale, India