Validation of the Chinese Involuntary Musical Imagery Scale and its Application in Mainland China

Abstract

This study aimed to examine the validity and reliability of the Chinese version of the Involuntary Musical Imagery Scale and its application in mainland China. Two studies were conducted. In Study 1, the Involuntary Musical Imagery Scale contents were translated into Chinese and semi-structured interviews were conducted with 10 undergraduate students; on this basis, a preliminary version of the Chinese Involuntary Musical Imagery Scale was generated. Subsequently, the psychometric properties of the Chinese Involuntary Musical Imagery Scale were analyzed based on 443 questionnaires; a four-factor model was found to achieve the best fit to the collected data and the Chinese Involuntary Musical Imagery Scale showed excellent internal consistency. In Study 2, the Chinese Involuntary Musical Imagery Scale was used to investigate the experience of involuntary musical imagery in mainland China (n = 426), where we explored the correlations among its factors and mental control, obsessive-compulsive traits, neuroticism, and openness; the results suggest that the frequency of involuntary musical imagery in Chinese individuals was lower than that of individuals in Western samples, and there were significant correlations between characteristics of involuntary musical imagery and various individual traits. Additionally, differences in involuntary musical imagery between students from urban areas and those from rural areas, as well as between only-child students and students with siblings, were found for the first time.

Keywords

Involuntary musical imagery (INMI)Chinese IMIS factor analysis frequency of INMI obsessive-compulsive traits

Introduction

Research on involuntary musical imagery (INMI), also known as earworms, has gradually increased over the past 10 years. This psychological phenomenon refers to the internal experience of a section or whole piece of music which comes to the mind unintended and repeats outside of conscious control despite the absence of a stimulus from the external environment (Floridou, 2016; Floridou et al., 2015; Liikkanen, 2012a; Williamson et al., 2012). INMI is an extremely common psychological phenomenon. One big data research project involving the analysis of data collected in 173 countries demonstrated that INMI is widespread across the globe (Liikkanen et al., 2015). Moreover, in a survey of 11,910 Finnish internet users, Liikkanen (2012b) discovered that 99.8% of the subjects reported experiencing INMI.

INMI is different from other types of musical imagery (e.g., voluntary musical imagery and anticipatory musical imagery; the former refers to a universal ability to recall a musical memory, while the latter occurs in parallel to perception when the features of an ephemeral incoming sound stream are predicted based on prior experience) and musical hallucination (Floridou, 2016; Liikkanen, 2012a; Moseley et al., 2018; Zatorre & Halpern, 2005). Moreover, this phenomenon is considered to be valuable in the study of spontaneous cognition and involuntary memory. On the one hand, INMI, as a type of involuntary semantic memory, a concept that refers to an involuntary conscious occurrence of brief items (e.g., a word, a name, a tune) of one’s network of semantic knowledge (Kvavilashvili & Mandler, 2004), is most prevalent in involuntary memories (Liikkanen, 2012a). On the other hand, INMI is ubiquitous and can be induced in the lab unlike other elusive types of spontaneous psychological phenomena. Previous studies reported that INMI could be induced through experimental operations such as increasing music exposure, tasking of lyric recall, and changing cognitive load and difficulty (Floridou et al., 2017; Hyman et al., 2013; Liikkanen, 2012b). The study of INMI may therefore open up a channel for the investigation of elusive spontaneous cognition that occupies a significant portion of our waking thoughts (Floridou, 2016; Kane et al., 2007; Killingsworth & Gilbert, 2010).

From the perspective of research approaches, studies regarding INMI can be divided into three main categories. The first one, which is the most common, consists of studies of the relationship between INMI and personality traits such as the Big Five, mental control, subclinical obsessive-compulsive (OC) traits, schizotypy, and transliminality (Beaman & Williams, 2013; Cotter et al., 2016; Floridou et al., 2012; Hyman et al., 2015; Müllensiefen et al., 2014; Wammes & Barušs, 2009; Williamson & Müllensiefen, 2012), as well as the relationship between INMI and demographic variables (e.g., gender, age; Beaman & Williams, 2010; Hyman et al., 2013; Kellaris, 2003), and engagement with music such as training or performance (Liikkanen, 2012a). For instance, Beaman and Williams (2013) found that mental control was associated with the length, disruptiveness, and interference of INMI, while Müllensiefen et al. (2014) indicated that high OC traits were positively related to INMI frequency and disturbance, and Cotter et al. (2016) reported that the frequency of INMI was correlated with neuroticism and openness to experience. Further, Liikkanen (2012a) suggested that the amount of music practice and listening was positively related to the frequency of INMI. These relationships are investigated and verified in this study using Chinese samples.

The second category of studies involves experimental research regarding the factors that influence the induction of INMI (e.g., familiarity, levels of processing, vocal and physical involvement) and reactions to them (Beaman et al., 2015; Byron & Fowles, 2015; Campbell & Margulis, 2015; Floridou et al., 2017; Hyman et al., 2013; Liikkanen, 2012b), including a neuroimaging study that explores brain structures related to INMI (Farrugia et al., 2015).

The third category involves studies of individual states (cognitive and physical), reactive strategies, and external conditions using experience sampling, diary methods, and other types of qualitative analysis (Beaman & Williams, 2010; Floridou & Müllensiefen, 2015; Williamson & Jilka, 2014; Williamson et al., 2014). Thus, the methods for investigating INMI are flexible and varied. For example, some studies explored musical characteristics, including the melodic features and tempo of INMI (Jakubowski et al., 2016; Williamson & Müllensiefen, 2012), while another compared the accuracy of voluntary musical imagery and INMI using a wearable accelerometer (Jakubowski et al., 2018).

These studies are based, however, on samples of Western individuals using music from Western countries. Even a big data research project based on a corpus from Twitter (Liikkanen et al., 2015) did not include non-English content about INMI. To the best of our knowledge, there is currently no research on the INMI experience of non-native English speakers, specifically that of Eastern Asian participants. It would be interesting to identify the characteristics of various aspects of the INMI experience of the Eastern Asian population, as well as the similarities and differences between Eastern Asian and Western research findings. We therefore aimed to translate and revise an existing questionnaire developed to assess INMI among Western participants for use with Chinese samples.

There are currently three questionnaires for assessing INMI: the Involuntary Musical Imagery Scale (IMIS) developed by Floridou et al. (2015), the INMI questionnaire developed by Müllensiefen et al. (2014), and the Musical Imagery Questionnaire (MIQ) developed by Wammes and Barušs (2009). For the purposes of our study, we chose to revise the IMIS for three reasons. First, the IMIS was developed most recently, so it is likely to be the most up-to-date of the three questionnaires. Second, the development of the IMIS followed strict psychometric standards; it has a stable structure, good reliability and validity, and has been used in previous research (Farrugia et al., 2015). Third, the IMIS includes various dimensions to investigate different factors of INMI (Floridou, 2016; Floridou et al., 2015).

The current study is the first to investigate the INMI experience in mainland China using a revised IMIS to provide INMI evidence from the Eastern Asian population. We assumed that INMI is widespread among participants from Eastern Asia, as has been seen among Western populations; this may differ somewhat between demographic groups in mainland China. On the basis of the results of studies with Western samples, we hypothesized that INMI would be correlated with the following personality traits: mental control, OC traits, neuroticism, and openness.

Study 1: Reliability and Validity of Chinese Involuntary Musical Imagery Scale

Method

Materials

Involuntary Musical Imagery Scale

The original IMIS (Floridou et al., 2015) has 15 items reflecting four factors: negative valence (7 items); movement (3 items); personal reflections (3 items); and help (2 items). Moreover, 3 additional items were designed to assess the frequency and length (section, episode) of INMI for a total of 18 items. Each item is rated on a five-point frequency scale ranging from 1 (never) to 5 (always). The internal reliability of the four subscales associated with each factor was excellent, with Cronbach’s alpha coefficients spanning from .76 to .91. Items from this scale also demonstrated satisfactory test-retest reliability coefficients across the subscales, ranging from .65 to .79.

Floridou et al. (2015) also applied confirmatory factor analysis (CFA) to examine the four-factor structure of the IMIS. Four different factor models were assessed, and the model that allowed inter-factor correlations between all four factors showed the best confirmatory fit to the data: comparative fit index (CFI) = .96; standardized root mean residual (SRMR) = .05; root mean square error of approximation (RMSEA) = .06; χ² = 819.99; and degrees of freedom (df) = 80. The competing models’ fit statistics can be found in Floridou et al. (2015).

Chinese Involuntary Musical Imagery Scale

The Chinese version of the IMIS was approved by the first author of the original scale. First, two authors of the present study translated all scale items into Chinese, then a professional Chinese–English translator translated the items back into English. The first author of the original scale checked the back-translated version and put forward suggestions for adjustment. Second, considering that the INMI has never been used as an investigative tool in China, semi-structured interviews based on the content of the 18 items were conducted with 10 undergraduate students to ensure the understandability of the contents of the scale. Third, based upon conclusions drawn from suggestions of the first author of the original scale and the interview results, 15 items from the English IMIS were retained, three items were deleted because they were not supported in the interviews (the interviewees claimed to be confused by these descriptions: “Earworms help me when I’m trying to get things done,” “Personal issues trigger my earworms,” “My earworms result from unresolved matters”), and nine new items were added (as a synthesis of the interviewees’ statements regarding their INMI experiences, e.g., “I sing along when the earworm happens”, “I am prone to have earworms when I’m alone”). This resulted in a preliminary questionnaire containing 21 items with three additional questions.

Participants

A total of 600 undergraduate students from three universities in China took part in Study 1, completing pen-and-paper surveys in class or an online survey after class between November 2018 and February 2019. All participants were informed of the purpose and content of the study, and ethical approval was obtained from the Ethics Committee of Fujian Normal University. After excluding the invalid answers, questionnaires from 581 participants (313 females, mean age = 19.5, SD = 3.64) were included. Two weeks later, using a simple and convenient sampling, we recruited 22 participants (19 females) to complete the retest. Using the methodology established by Floridou et al. (2015) as a reference, questionnaires in which the item “frequency of earworm” was answered as “never” were excluded. A total of 443 questionnaires were therefore included in the final statistical analysis.

Procedures

The statistical analyses were performed with IBM SPSS Statistics 22.0 and Mplus 7.4. The questionnaires were divided in half randomly; 207 were allocated to Sample 1 (116 females) and 236 questionnaires were allocated to Sample 2 (135 females). The statistical analysis involved three steps. First, item analysis was used to examine discrimination. Second, exploratory factor analysis (EFA) and CFA were used to inspect construct validity. Third, the reliability of the scale was tested using the internal consistency coefficient (Cronbach’s alpha) and test-retest reliability coefficient. Sample 1 was used for item analysis and EFA, while Sample 2 was used for CFA and reliability analysis.

Results and Discussion

Item Analysis

Participants obtaining the highest 27% of total scores in Sample 1 were selected to represent a “high-score” group, and those obtaining the lowest 27% of total scores in Sample 1 were selected to represent a “low-score” group. An independent samples t-test was used to analyze the discrimination of 21 items (excluding three additional items designed to assess the frequency and length of INMI). There were significant differences between the high-score and low-score groups for each item (p < .01), indicating that the discrimination of these 21 items was acceptable. Subsequently, the correlation between each item score and the total IMIS score was analyzed using the Pearson correlation coefficient, which indicated that two items were unsatisfactory (r < .30) and could therefore be eliminated: “My earworms can help me focus on what I’m doing” (r = .22) and “When I focus on something, the earworm stops” (r = .26). A total of 19 items was therefore deemed acceptable (r = .39 – .57, p < .01, Table 1) and retained for EFA and CFA.

Table 1.

Pearson’s Correlations Between Each Item Score and Total Score on Chinese Involuntary Musical Imagery Scale.

Item	R	Item	r	Item	r
1	.54**	8	.49**	14	.57**
2	.55**	9	.48**	15	.54**
3	.53**	10	.47**	16	.45**
4	.51**	11	.49**	17	.45**
5	.56**	12	.49**	18	.44**
6	.55**	13	.51**	19	.39**
7	.42**

Correlation is significant at the p < .05 level (2-tailed); **correlation is significant at the p < .01 level (2-tailed).

Construct Validity Analysis

Exploratory Factor Analysis

The Kaiser-Meyer-Olkin (KMO) test and Bartlett’s sphericity test indicated that Sample 1 was suitable for EFA (KMO = .87, χ² = 2056.00, p < .01, df = 171). Four factors, extracted through principal component analysis and maximum variance rotation, explained 65.48% of variance. The percentages of variance explained by each factor were 29.46%, 20.85%, 8.89%, and 6.28%. The eigenvalues of the four factors were 5.60, 3.96, 1.69, and 1.19. According to the factor loadings, the dimensions of the original scale, and previous studies of INMI (Floridou, 2016; Floridou et al., 2017), the four factors were named negative valence, movement, spare cognitive capacity, and mind-wandering. All 19 items met the requirements of the critical value of factor loading. Details of the four factors (items and loadings) are presented in Table 2. The content of the Chinese IMIS can be found in the Appendix.

Table 2.

Structure Matrix and Item Loadings for Chinese Involuntary Musical Imagery Scale.

Negative valence		Movement		Spare cognitive capacity		Mind-wandering
Item	Loading	Item	Loading	Item	Loading	Item	Loading
6	.87	11	.86	17	.73	14	.81
4	.87	12	.85	16	.73	15	.80
3	.85	13	.82	18	.65
2	.84	10	.74
1	.83	19	.48
5	.80	9	.48
7	.75
8	.65

Confirmatory Factor Analysis

The maximum likelihood method was used to analyze the data for Sample 2 with Mplus Version 7.4. The validity analysis of the structural equation model showed that the four-factor model of the Chinese IMIS had a good fit to the data: χ² = 504.55, df = 146, Tucker-Lewis index (TLI) = .97, CFI = .97, Akaike information criterion (AIC) = 13366.95, Bayesian information criterion (BIC) = 13600.08, and RMSEA = .09.

Reliability Analysis

Internal Consistency

Using Sample 2, the Cronbach’s alpha of the Chinese IMIS was analyzed. The results are shown in Table 3. Cronbach’s alpha was .82 for the total scale and above .65 for each dimension.

Table 3.

Internal Consistency Reliability and Test-retest Reliability of Chinese Involuntary Musical Imagery Scale (IMIS).

	Negative valence	Movement	Spare cognitive capacity	Mind-wandering	IMISscore
Cronbach’s alpha	.90	.82	.67	.66	.82
Test-retest reliability	.72**	.80**	.84**	.55**	.78**

Correlation is significant at the p < .05 level (2-tailed); **correlation is significant at the p < .01 level (2-tailed).

Test-retest Reliability

A total of 22 participants were retested 2 weeks later after completing the questionnaire and the test-retest reliability of the total score on the Chinese IMIS was .78 (p < .01). The test-retest reliability of each factor is shown in Table 3.

Study 2: Correlates of Chinese Involuntary Musical Imagery Scale Scores

In Study 1, we developed the Chinese version of the IMIS, confirmed its four-factor structure, and examined its reliability. The purpose of Study 2 was to apply the Chinese IMIS to investigate the phenomenon of INMI in mainland China and examine the correlations among INMI, mental control, OC traits, neuroticism, and openness in Chinese individuals.

Method

Materials

In addition to the Chinese IMIS, subjects completed the Chinese Obsessive-Compulsive Inventory-Revised (OCI-R), which consists of six factors: washing, checking, ordering, obsessing, hoarding, and mental neutralizing; Cronbach’s alpha of the Chinese OCI-R was .90, and test-retest reliability was .63 (Tang et al., 2011). We also used the Chinese White Bear Suppression Inventory (WBSI), which had a Cronbach’s alpha of .83 and test-retest reliability of .82 (Zhou et al., 2012). Additionally, subjects completed two subscales (i.e., neuroticism and openness) from the Chinese Big Five Personality Inventory (CBF-PI) Brief Version; Cronbach’s alpha for neuroticism and openness were .81 and .78 respectively, and the test-retest reliability of both subscales was .81 (Wang et al., 2011).

Participants

A total of 427 undergraduate students (mean age = 19.58, SD = 1.45, 215 females) from four universities in China took part in Study 2, completing pen-and-paper or online surveys between March 2019 and June 2019. One participant did not complete the survey; 426 questionnaires were therefore allocated to Sample 3 and used for descriptive statistical analysis. Questionnaires in which the item “frequency of earworm” was answered as “never” were excluded from the correlational analysis.

Procedures

First, considering the current economic and cultural differences between urban and rural areas in mainland China, participants’ demographic information was collected and differences in INMI frequency were analyzed between groups according to participants’ characteristics (gender, place of origin, musician or not,¹ etc.). A correlation analysis was subsequently conducted for the sample of participants who did not answer “never” to the item “frequency of earworm” (n = 318, 168 females). IBM SPSS 22 and GPower 3.1 were used to perform all statistical analyses in Study 2.

Results and Discussion

Descriptive Statistics and Between-group Analyses

The demographic information for the 426 participants is presented in Table 4. A total of 318 participants (74.65%) reported experiencing INMI: 210 participants (49.30%) reported experiencing it at least once a week and 45 (10.56%) every day. These proportions are substantially lower than those reported in Western research (more than 90% experienced INMI at least once a week and 33.2% every day; Liikkanen, 2012a). The INMI frequency data did not conform to a normal distribution potentially because the participants were undergraduate students, a sample that does not cover all ages so the data were analyzed using a non-parametric statistical test. A Mann-Whitney U test comparing the average INMI frequency ratings for males (M = 2.61, SD = 1.45) and females (M = 2.84, SD = 1.38) indicated no significant difference between them (U = 20404.00, p = .07), which is consistent with previous research (Beaman & Williams, 2013).

Table 4.

Background Characteristics of Participants and Frequency of Involuntary Musical Imagery (INMI) (n = 426).

	N	%
Gender
Male	211	49.53
Female	215	50.47
Music listening frequency (daily)
< 0.5 h	117	27.59
0.5-1 h	171	40.33
1-2 h	76	17.92
2-3 h	33	7.78
3-4 h	15	3.54
> 4 h	12	2.83
Experience of musical training
Yes	67	15.73
No	359	84.27
Musician
Yes	21	4.93
No	405	95.07
Place of origin
Urban	175	41.08
Rural	251	58.92
Only child
Yes	152	35.68
No	274	64.32
Frequency of INMI
Never	108	25.35
Once a month	108	25.35
Once a week	60	14.08
Several times a week	105	24.65
Several times a day	33	7.75
Almost continuously	12	2.82

Additionally, there were no significant differences in INMI frequency between musicians (M = 3.10, SD = 1.76) and non-musicians (M = 2.71, SD = 1.40; U = 3781.50, p = .38), nor between participants with and without musical training (U = 10582.00, p = .11), a result identical to those of Beaman and Williams (2010) but different from others (Hyman et al., 2013; Kellaris, 2003; Levitin, 2006; Liikkanen, 2012a). Nevertheless, a Kruskal-Wallis test revealed that the frequency of INMI varied significantly with the amount of time spent listening to music per day (χ² = 18.71, df = 5, p < .01), which is consistent with the results of Liikkanen (2012b) and Hyman et al. (2013).

Furthermore, the frequency of INMI among undergraduates from urban areas (M = 3.00, SD = 1.43) was significantly higher than that among undergraduates from rural areas (M = 2.53, SD = 1.38; Mann-Whitney U = 17849.50, p < .01, effect size d = .33). Moreover, the INMI frequency of only-child students (M = 2.96, SD = 1.54) was significantly higher than that of students with siblings (M = 2.59, SD = 1.33; Mann-Whitney U = 18140.50, p = .02, effect size d = .26). These results are noteworthy. On one hand, the frequency of INMI may be influenced by differences in the level of musical activities between urban and rural areas, with students from cities in mainland China being more exposed to a variety of different kinds of music. On the other hand, differences in parenting styles for only-child students and students with siblings may also play a role in the development of the individual’s personality, emotional characteristics, and thinking styles, among others.

Correlational Analyses

Spearman correlations were used to identify the relationships between INMI experience and other variables. Some correlations were consistent with previous results of Western research on INMI, but there were a few differences. The associations were not particularly strong, with most being moderate and weak, as reported in Tables 5, 6, and 7.

Table 5.

Correlations between frequency and length of Involuntary Musical Imagery (INMI) and subscales of Chinese Obsessive-Compulsive Inventory-Revised.

	Section length	Episode length	Washing	Obsessing	Hoarding	Ordering	Checking	Neutralizing
Frequency	.19**	.18**	.04	.06	.02	.12*	−.02	.01
Section length		.33**	.05	.12*	.05	.05	.09	.04
Episode length			.14*	.19**	.14*	.11*	.12*	.19**
Washing				.55**	.47**	.65**	.50**	.64**
Obsessing					.56**	.48**	.53**	.55**
Hoarding						.45**	.52**	.54**
Ordering							.48**	.66**
Checking								.53**

Correlation is significant at the p < .05 level (2-tailed); **correlation is significant at the p < .01 level (2-tailed).

Table 6.

Correlations between factors of Chinese Involuntary Musical Imagery Scale (IMIS) and mental control, obsessive-compulsive (OC) traits, neuroticism, and openness.

	Negative valence	Movement	Spare cognitive capacity	Mind-wandering	Mental control	OC traits	Neuroticism	Openness
IMIS score	.56**	.66**	.55**	.64**	.36**	.40**	.19**	.13*
Negative valence		−.05	.06	.20**	.25**	.31**	.24**	-.10
Movement			.41**	.40**	.18**	.22**	.09	.19**
Spare cognitive capacity				39**	.26**	.23**	.09	.10
Mind-wandering					.29**	.25**	.15**	.16**
Mental control						43**	.53**	.06
OC traits							.40**	.06
Neuroticism								−.20**

Correlation is significant at the p < .05 level (2-tailed); **correlation is significant at the p < .01 level (2-tailed).

Table 7.

Correlations between factors of Chinese Involuntary Musical Imagery Scale (IMIS) and Chinese Obsessive-Compulsive Inventory-Revised Subscales.

	Washing	Obsessing	Hoarding	Ordering	Checking	Neutralizing
Negative valence	.26**	.26**	.19**	.28**	.21**	.26**
Movement	.18**	.19**	.17**	.20**	.12*	.19**
Spare cognitive capacity	.10	.27**	.26**	.17**	.13*	.15**
Mind-wandering	.18**	.26**	.25**	.18**	.17**	.15**
Total IMIS score	.33**	.38*	.28**	.35**	.24**	.31**

Correlation is significant at the p < .05 level (2-tailed); **correlation is significant at the p < .01 level (2-tailed).

Regarding the frequency and length (section, episode) of INMI, we investigated the correlations between scores for three additional items designed to assess the frequency and length of INMI with scores on the Chinese OCI-R, WBSI, and CBF-PI neuroticism and openness subscales. We found that the length of INMI section was positively associated with mental control (ρ = .22, p< .01) and openness (ρ = .17, p < .01). The length of INMI episode was positively associated with mental control (ρ = .15, p = .01), OC traits (the total score on OCI-R, ρ = .19, p < .01), and openness (ρ = .13, p = .02). However, there were no associations between the frequency of INMI and neuroticism, openness, mental control, or OC traits except for one factor (ordering) of the OCI-R (ρ = .12, p = .03). This is consistent with one previous study which reported that INMI frequency was not correlated with any traits in the Big Five Inventory (Floridou et al., 2012), but different from previous reports of a positive correlation of high OC traits and neuroticism with INMI frequency (Kellaris, 2003; Williamson & Müllensiefen, 2012). More details about the correlations between frequency and length (section, episode) of INMI and the Chinese OCI-R subscales are provided in Table 5.

As shown in Table 6, total IMIS scores were positively associated with mental control, OC traits (the total score on OCI-R), neuroticism, and openness, with ρ ranging from .13 to .40 (p < .01). The correlation with mental control and OC traits was moderate, and all four subscales of IMIS showed significant positive correlations with mental control and OC traits, with ρ ranging from .18 to .31 (p < .01). Additionally, the four factors of IMIS had significant positive correlations with every dimension of the OCI-R (except for the association between spare cognitive capacity and washing) as can be seen in Table 7. Furthermore, the association between openness and two IMIS factors (movement, mind-wandering) was significant, although the correlation was weak (ρ was .19 and .16, respectively, p < .01). These results are consistent with previous results research with Western participants in some respects (Beaman & Williams, 2013; Cotter et al., 2016; Müllensiefen et al., 2014; Williamson & Müllensiefen, 2012). Consistent with previous findings (Floridou et al., 2012), the correlation between neuroticism and negative valence (ρ = .24, p < .01) suggests that individuals with high scores on neuroticism were more likely to regard the INMI as an unpleasant experience, which may be influenced by the evaluation tendency of neurotic individuals.

General Discussion

The goal of this study was to generate a Chinese IMIS and examine its applicability in mainland China. The results of Study 1 revealed that the Chinese version of the IMIS was a reliable and valid tool for use among Chinese individuals. To our knowledge, this study was the first to revise the IMIS and explore its application in mainland China. Although the Chinese IMIS retained four dimensions, two of the original factors changed. In the Chinese IMIS, the original factors personal reflection and help were not supported, and two different factors were confirmed. According to the content of their items, these new factors were named spare cognitive capacity and mental control. Additionally, one item in the original IMIS (“The content of my earworms mirrors my state of worry or concern” in personal reflection) was included in negative valence according to the EFA in the current study.

We also investigated the INMI experience of Chinese individuals for the first time. Although many Chinese participants experienced INMI, its frequency was lower than that observed in Western samples (Liikkanen, 2012a). Nevertheless, the significant relationships among IMIS scores (including its different subscales) and mental control, OC traits, neuroticism, and openness to experience were similar to the results from previous research with Western populations (Beaman & Williams, 2013; Cotter et al., 2016; Müllensiefen et al., 2014; Williamson, & Müllensiefen, 2012). It is noteworthy that we did not observe a significant association between INMI frequency and OC traits, but we did find significant correlations between OC traits and scores on IMIS and its various factors. This may indicate that the frequency of INMI and its characteristics are related to different cognitive processes; future studies could therefore be used to examine this issue further in China or other Asian countries.

The significant difference in INMI frequency between students from urban areas and those from rural areas, as well as only-child students and students with siblings, are both noteworthy. The differences between students from urban areas and those from rural areas could be due, on the one hand, to differences between these areas in mainland China in terms of the frequency with which people take part in musical activities, as urban residents may be exposed more often to musical experiences. On the other hand, some personality traits and thinking styles may play a role in these differences. In fact, we investigated the differences in IMIS scores, OC traits, mental control, neuroticism, and openness between students from urban areas and those from rural areas, as well as between only-child students and students with siblings. No significant differences were observed other than the total IMIS scores and the scores on the mind-wandering subscale.² These results suggest that other factors may affect the frequency of INMI, such as some unknown individual differences that can be traced back to the environment where individuals grew up and the way they were raised. How these individual differences influence the frequency of INMI and the underlying mechanism is a question worthy of future investigation.

Additionally, this study did not analyze the features typical of Chinese music that becomes INMI. Future studies could compare the characteristics of the music that becomes INMI in Western and Eastern cultures, such as tempo and melodic features, that have been shown to be related to the catchiness of music, its popularity, and the likelihood of a tune becoming INMI (Jakubowski et al., 2015; Jakubowski et al., 2016; Müllensiefen & Halpern, 2014). This sort of research may be valuable to the understanding of differences between esthetic preferences for music among different cultures.

Supplemental Material

certificate_of_English_language_editing – Supplemental material for Validation of the Chinese Involuntary Musical Imagery Scale and its Application in Mainland China

Supplemental material, certificate_of_English_language_editing for Validation of the Chinese Involuntary Musical Imagery Scale and its Application in Mainland China by Deng Jue, Ma Jianping and Ye Yiduo in Musicae Scientiae

Supplemental Material

Revision_Report – Supplemental material for Validation of the Chinese Involuntary Musical Imagery Scale and its Application in Mainland China

Supplemental material, Revision_Report for Validation of the Chinese Involuntary Musical Imagery Scale and its Application in Mainland China by Deng Jue, Ma Jianping and Ye Yiduo in Musicae Scientiae

Footnotes

Ethical approval

All subjects were informed of the purpose and content of the study, and ethical approval was obtained from the Ethics Committee of Fujian Normal University.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Ye Yiduo

Supplemental material

Supplemental material for this article is available online.

Notes

References

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