شرایط محیطی و روانی پیش بینی تجربه تصاویر موسیقایی غیر ارادی: نمونه مطالعه روش تجربه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|29705||2015||15 صفحه PDF||سفارش دهید||8078 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Consciousness and Cognition, Volume 33, May 2015, Pages 472–486
An experience sampling method (ESM) study on 40 volunteers was conducted to explore the environmental factors and psychological conditions related to involuntary musical imagery (INMI) in everyday life. Participants reported 6 times per day for one week on their INMI experiences, relevant contextual information and associated environmental conditions. The resulting data was modeled with Bayesian networks and led to insights into the interplay of factors related to INMI experiences. The activity that a person is engaged was found to play an important role in the experience of mind wandering, which in turn enables the experience of INMI. INMI occurrence is independent of the time of the day while the INMI trigger affects the subjective evaluation of the INMI experience. The results are compared to findings from earlier studies based on retrospective surveys and questionnaires and highlight the advantage of ESM techniques in research on spontaneous experiences like INMI.
Involuntary cognitions, in the form of memories, thoughts and future planning, constitute a significant fraction of mental activity in people’s everyday lives (Killingsworth and Gilbert, 2010 and Kvavilashvili and Mandler, 2004). One type of involuntary cognition that is fairly prevalent in Western populations (Liikkanen, 2012 and Williamson et al., 2012) takes the form of music and is referred to as ‘involuntary musical imagery’ (INMI, or an “earworm” as it is commonly known). INMI is a short section of music that comes to the mind spontaneously without effort and then goes on repeating itself without conscious control. Despite the fact that research on INMI only begun fairly recently (Brown, 2006 and Kellaris, 2001), a considerable number of studies during the past few years have produced a range of significant results which now allow the construction of a theoretical framework as well as the refinement of research methods which help to further investigate this by definition very inaccessible phenomenon. Thus, research findings to date have provided information on a range of environmental factors and psychological conditions that contribute and affect the experience of INMI. We will summarize these findings first before laying out the rationale and motivation for the current study. In this brief summary of the literature, we focus on transient momentary conditions and states rather than on personal traits and stable individual differences that have been covered elsewhere (Beaman and Williams, 2013 and Müllensiefen et al., 2014).
نتیجه گیری انگلیسی
The aim of this study was to examine the role of environmental conditions and psychological states of the individual in relation to the INMI experience. The study specifically looked at interactions and causal relationships between these conditions and also investigated the relationship between INMI experiences and mind wandering. This study used the ESM technique to study INMI experiences in real-life situations. An important finding is the discrepancy of the frequency of INMI experiences as obtained via ESM sampling in comparison with that obtained via retrospective estimates from the same individuals. Kvavilashvili and Mandler (2004) reported a similar discrepancy between the two different measures for the same participants in relation to ISM frequency. This suggests that, at least for certain individuals, retrospective meta-memory for involuntary semantic memories may be less accurate than measures obtained from experience sampling. A tentative explanation for this discrepancy, given by Kvavilashvili and Mandler, is that some people who do experience involuntary semantic memories may not be paying attention to them and thus may tend to assume that they never experienced them (p. 73). Our finding is particularly important for future studies based on retrospective questionnaire reports for e.g. INMI frequency and other factors of interest, where poor meta-memory for INMI experience could distort empirical results. The overall frequency of INMI reported in our study was 47% over the course of a week. This rate is substantially greater than that reported in previous ESM studies on musical imagery, with Bailes (2006) reporting a 32% INMI rate and Beaty et al. (2013) reporting a frequency of 17%. This difference could be the result of the selection criteria of the different studies. The higher overall frequency we observed in this sample could be due to a selection bias, as participants were recruited among people who had completed the earwormery survey and thus it is possible that our participants were more familiar, interested and maybe more aware of this phenomenon. The results suggested by the network models indicate that the activity that a person is engaged in plays the key role for the appearance of mind wandering, which in turn enables the appearance of INMI. Conditional on the activity, INMI occurrences are independent of time of the day, a result that agrees with Byron and Fowles (2013) and resolves previous conflicting findings in the literature (Bailes, 2007; Halpern & Bartlett, 2011). Thus, according to our results it is the activity that the person engages in that causes mind wandering and, in turn, the activity is constrained by the time of the day. Generally, activities found to favor mind wandering, and subsequently INMI appearance, are characterized by low cognitive load (e.g. just woke up, going to sleep), traveling (confirming the findings of Liikkanen, 2012), housework and physical movement. On the other hand, activities that make the appearance of mind wandering and INMI less likely are socializing, a finding that confirms the finding of Liikkanen (2012) but is in conflict to that of Bailes (2006). However one has to bear in mind that the latter study also included voluntary musical imagery episodes in which the participants might purposely have imagined the music in their heads. Audio/visual activities were found to reduce the likelihood of mind wandering experiences and subsequently INMI. This finding is in contrast with a result from a study (Liikkanen, 2012) which was based on retrospective reports. Both, socializing and audio/visual activities, involve auditory engagement. Neuroimaging findings (Kraemer et al., 2005 and Zatorre and Halpern, 2005) show that the auditory cortex is activated in voluntary but also involuntary musical imagery activities. Taking this into consideration, it seems possible that INMI may compete for the same auditory processing resources that are engaged during socializing and audio/visual activities. This could provide an explanation for why involuntary musical imagery appearance is less likely when individuals are engaged in concurrent activities that require auditory processing. Activities described by high cognitive load such as reading, playing Sudoku, and school homework, but also working and computer/leisure activities, seem to discourage INMI. This finding is at odds with the conclusion by Hyman et al. (2013) that appearance of INMI is favored by activities at both ends of the cognitive load continuum. To resolve these conflicting findings, more experimental studies based on the systematic manipulation of the amount of cognitive load, are required. With regard to the influence of mood on INMI, the picture emerging from the data of this study is quite clear. The networks described above show that mood is independent of INMI but is affected by the occurrence of mind wandering, which in turn enables INMI occurrence. In other words, mind wandering is a common cause of both INMI and the affective quality of a mood state. The distribution of mood states in all the networks shows that the participants were most often in a calm and happy mood and least likely to be in an energetic mood. This result agrees with the findings by Ruby, Smallwood, Engen, and Singer (2013) that self-generated thought (mind wandering) can temporally precede positive mood. It is also in accordance with musical imagery findings by Bailes, 2007 and Beaty et al., 2013 regarding the quality of mood states. The data of this study also provide a tentative explanation for the observation that the subjective evaluation of INMI episodes can be highly variable (Beaman and Williams, 2010 and Liikkanen, 2012; Halpern & Bartlett, 2011; Hemming, 2009). According to the output of the second network, the participant’s opinion about what triggered their INMI seems to determine how pleasant an INMI experience is perceived to be. Memory-associated triggers and music exposure increase INMI pleasantness. This could be explained by the fact that people listen to and are more exposed to music that they like and enjoy (North and Hargreaves, 2003 and North et al., 2004). Therefore, there is a higher likelihood of INMI triggers related recent exposure to songs that are perceived as pleasant. However, when the person cannot identify the trigger, experiences an INMI more than once in a day and/or experiences his/her default INMI (i.e. INMI that reoccurs frequently), then the pleasantness of the INMI experience decreases. This could be because of the repetitive quality of INMI that can lead to negative evaluation of the experience. The individual initially enjoys the INMI but finds it unpleasant when this experience occurs and reoccurs. It could also be explained by the findings of Müllensiefen et al. (2014) that individual differences in obsessive compulsive trait – which is characterized by repetitive thought patterns – partially influence INMI valence (unpleasantness). The relative frequencies of INMI triggers found in this study confirm findings by Williamson et al. (2012) but also allow direct comparisons with triggers of involuntary semantic memories. A key characteristic of ISMs, in comparison to IAMs, is that identification of the ISM trigger is not easily traceable. In our study INMI triggers could be identified in 62.3% of the instances. Kvavilashvili and Mandler (2004) reported ISMs triggers for 37% of the cases, which is approximately half the proportion reported by our participants. This difference might suggest that INMI triggers are more identifiable than triggers of other ISMs because of their persistence that could give more time to the person to identify them. Finally turning to the relationship between INMI and mind wandering, all the networks derived in the present study reveal interesting relationships. Mind wandering often seems to be the cause of INMI that follows its occurrence, i.e. it appears that the mind starts to wonder and subsequently it enables the appearance of INMI. This finding is in accordance with mind wandering literature where a big portion of its content is reported as musical imagery (Delamillieure et al., 2010) In summary, this study has demonstrated the advantages of the ESM approach for the study of conditions surrounding the occurrence of INMI and allows a comparison to data from retrospective self-reports. One interpretation of the discrepancy between the results from the two data collection methods suggests that retrospective self-reports can suffer from memory bias. Using Bayesian Networks as an analysis technique, it was found that INMI triggers determine whether INMI is experienced as pleasant or not. Also that INMI does not affect mood directly, but that mind wandering is a common cause behind the two. INMI occurrence is independent of the time of day but activity is a causal link between the two. Finally, low cognitive load activities favor mind wandering occurrence and subsequently INMI appearance. This paper provides new insights into the contextual and psychological conditions that affect the occurrence and experiential quality of INMI. It uses a data collection method that is highly suited for observing these real-world contexts and a modeling approach that is suitable for identifying complex networks of interacting variables as well as causal mechanisms. The Bayesian network modeling approach appears to be appropriate for the analysis of this type of data because, as previous literature has shown, the conditions which govern INMI experiences are highly complex.