| Literature DB >> 33828512 |
Hannah Gibbs1, Hauke Egermann1.
Abstract
Nostalgic music is defined as that which evokes feelings of nostalgia through reminders of certain periods of life, places or people. Feelings of nostalgia are said to occur during times of hardship and difficult transitionary periods, such as the first COVID-19 lockdown in the United Kingdom in 2020. Here, the reassurance of the past might have held certainty that could sustain a sense of meaning and purpose in life and influence wellbeing. The aims of the presented study were to explore the nature of music-induced nostalgia during the lockdown, by analysing participants' narratives conjured by the music and their emotional responses to them, and to determinethe extent that using nostalgic music listening as an emotion regulation strategy had an impact on wellbeing. Data was collected by means of an online questionnaire, which retrospectively investigated nostalgic music during the lockdown. Participants listened to a self-selected piece of music that they had listened to 3 months prior whichinduced feelings of nostalgia, reported their resulting emotion and the content of memories associated with their nostalgia, and completed a questionnaire rating their experienced effect of nostalgia in relation to their piece of music. Following this, we investigated the functions that nostalgic music tends to have in regulating emotions through means of a pre-validated scale. 570 participants (34% identified as male) were recruited (age years M = 44, SD = 16). Concurrent with existing research, the findings suggest that there are significant differences in the affective and narrative content of nostalgicmusic listening in relation to which emotion regulation strategy was used, and that employing nostalgic music listening as a form of approaching difficult emotions can have a positive impact on wellbeing.Entities:
Keywords: COVID-19; emotion; listening; lockdown; music; nostalgia; regulation; wellbeing
Year: 2021 PMID: 33828512 PMCID: PMC8019926 DOI: 10.3389/fpsyg.2021.647891
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
How often have you found yourself listening to nostalgic music, either intentionally or coincidentally, over the last 3 months?
| Frequency | Percent | Cumulative percent | |
| At least once a day | 117 | 20.5 | 20.5 |
| At least once a week | 271 | 47.5 | 68.1 |
| At least once a fortnight | 85 | 14.9 | 83.0 |
| At least once a month | 60 | 10.5 | 93.5 |
| Less than once a month | 28 | 4.9 | 98.4 |
| Never | 9 | 1.6 | 100.0 |
| Total | 570 | 100.0 |
Frequency table for coded valence response groups to nostalgic music.
| Frequency | Percent | |
| Never listen to nostalgic music | 9 | 1.6 |
| Mixed or complex emotions | 107 | 18.8 |
| Negative emotions | 65 | 11.4 |
| Neutral emotions | 15 | 2.6 |
| Positive emotions | 374 | 65.6 |
| Total | 570 | 100.0 |
Pearson correlation matrix for nostalgic effects (EEN) (Garrido, 2016).
| Variable | |||||||
| – | |||||||
| 0.01 | – | ||||||
| 0.189*** | −0.187*** | – | |||||
| −0.175*** | 0.332*** | 0.108* | – | ||||
| 0.405*** | 0.225*** | 0.158*** | 0.117** | – | |||
| –0.029 | 0.54*** | 0.029 | 0.492*** | 0.234*** | – |
Analysis of Variance table for nostalgic effects (EEN) and coded valence groups.
| Dependent | Source | d | η | ||
| Between valence groups | 3 | 21.456 | < 0.001*** | 0.104 | |
| Within groups | 557 | ||||
| Between valence groups | 3 | 33.106 | <0.001*** | 0.151 | |
| Within groups | 557 | ||||
| Between valence groups | 3 | 12.066 | <0.001*** | 0.061 | |
| Within groups | 557 | ||||
| Between valence groups | 3 | 24.294 | <0.001*** | 0.116 | |
| Within groups | 557 | ||||
| Between valence groups | 3 | 2.612 | 0.051† | 0.014 | |
| Within groups | 557 | ||||
| Between valence groups | 3 | 32.476 | <0.001*** | 0.149 | |
| Within groups | 557 | ||||
| Total | 560 |
FIGURE 1Tukey HSD post hoc paired comparisons for nostalgic effects (EEN items) and coded valence groups with 95% Confidence Interval error bars.*p <0.05, **p <0.01, ***p <0.001, n = 561.
Linear regression coefficient estimates for predicting nostalgic effects (EEN items) (outcome variables) with coded reasoning categories1 (predictor variables).
| β | β | β | β | β | β | |
| 0.105* | –0.040 | 0.035 | –0.059 | 0.042 | 0.012 | |
| 0.099* | 0.034 | 0.001 | –0.039 | 0.079† | 0.009 | |
| 0.107* | 0.219*** | –0.034 | 0.022 | 0.219*** | 0.132** | |
| 0.108* | 0.038 | –0.006 | –0.049 | –0.006 | 0.060 | |
| 0.046 | 0.048 | 0.099* | 0.058 | 0.039 | 0.118** | |
| 0.017 | 0.090* | 0.018 | 0.010 | 0.085* | 0.072 | |
| 0.002 | < 0.001 | 0.018 | 0.027 | –0.039 | 0.015 | |
| –0.062 | –0.041 | 0.085* | 0.020 | 0.046 | –0.016 | |
| −0.100* | 0.064 | 0.039 | 0.194*** | 0.084* | 0.162*** | |
| 0.079† | –0.003 | 0.040 | –0.019 | 0.089* | 0.072 | |
| 3.291*** | 4.472*** | 1.342 | 3.176** | 5.181*** | 3.770*** | |
| Adjusted | 0.039 | 0.058 | 0.006 | 0.037 | 0.069 | 0.047 |
FIGURE 2Confirmatory factor analysis model of emotion regulation strategies.
Linear regression coefficient estimates for predicting nostalgic effects EEN items (outcome variables) with emotion regulation (ERS-ACA) factors (predictor variables).
| β | β | β | β | β | β | |
| 0.247*** | −0.158* | 0.104† | −0.186** | 0.037 | −0.190** | |
| 0.079 | 0.111 | 0.297*** | 0.237** | 0.115 | 0.105 | |
| 0.018 | 0.008 | –0.005 | –0.026 | 0.167* | 0.139 | |
| 20.845*** | 2.887* | 28.874*** | 6.433*** | 18.085*** | 5.286** | |
| Adjusted | 0.096 | 0.010 | 0.130 | 0.028 | 0.084 | 0.022 |
General linear model univariate tests for coded valence categories (predictor variable) and emotion regulation (ERS-ACA) factors (outcome variables).
| Variable | Mean | d | d | Partial η | |||||
| 3 | 557 | 10.553 | <0.001 | 0.054 | |||||
| Positive | 0.117 | 0.703231 | 374 | ||||||
| Negative | –0.128 | 0.811588 | 65 | ||||||
| Mixed | –0.214 | 0.695407 | 107 | ||||||
| Neutral | –0.583 | 0.707007 | 15 | ||||||
| 3 | 557 | 5.773 | 0.001 | 0.030 | |||||
| Positive | 0.059 | 0.584664 | 374 | ||||||
| Negative | –0.033 | 0.641602 | 65 | ||||||
| Mixed | –0.062 | 0.563217 | 107 | ||||||
| Neutral | –0.529 | 0.488616 | 15 | ||||||
| 3 | 557 | 6.878 | < 0.001 | 0.036 | |||||
| Positive | 0.08160 | 0.704497 | 374 | ||||||
| Negative | –0.15115 | 0.782687 | 65 | ||||||
| Mixed | –0.06549 | 0.615078 | 107 | ||||||
| Neutral | –0.60966 | 0.582824 | 15 | ||||||
FIGURE 3Tukey HSD post hoc paired comparisons for emotion regulation (ERS-ACA) factors and coded valence groups with 95% Confidence Interval error bars. *p <0.05, **p <0.01,***p <0.001, n = 561.
Stepwise linear regression coefficient estimates for predicting wellbeing (SWEMWBS) through emotion regulation strategies (ERS-ACA factor score variables) and impairment (WSAS)(as covariate).
| Model | Adjusted | β | ||
| 1 | (Intercept) | 0.000 | 136.056*** | |
| 2 | (Intercept) | 0.268 | 84.172*** | |
| Impairment (WSAS) Total Score | –0.518 | −14.437*** | ||
| 3 | (Intercept) | 0.278 | 84.646*** | |
| Impairment (WSAS) Total Score | –0.526 | −14.701*** | ||
| CFA Approach Score | 0.100 | 2.782** |