Canadian Journal of Experimental Psychology, 67 (2013), 19-31
Authors: Jonathan S. A. Carriere, Paul Seli, Daniel Smilek
University of Waterloo, Waterloo, Ontario, Canada
Contact: firstname.lastname@example.org (J. Carriere)
Anecdotal reports suggest that during periods of inattention or mind wandering, people tend to experience increased fidgeting. In four studies, we examined whether individual differences in the tendency to be inattentive and to mind wander in everyday life are related to the tendency to make spontaneous and involuntary movements (i.e., to fidget). To do so, we developed self-report measures of spontaneous and deliberate mind wandering, as well as a self-report scale to index fidgeting. In addition, we used several existing self-report measures of inattentiveness, attentional control, and memory failures. Across our studies, a series of multiple regression analyses indicated that fidgeting was uniquely predicted by inattentiveness and spontaneous mind wandering but not by other related factors, including deliberate mind wandering, attentional control, and memory failures. As a result, we suggest that only spontaneously wandering thoughts are related to a wandering body.
As highlighted in the epigraph, the importance of the embodiment of the mind was evident in the writings of the founders of our field. Accordingly, the present research was motivated by a number of early, primarily anecdotal, reports suggesting an important link between the maintenance of attention and the movement of the body. Ribot (1890), for example, remarked that “the fundamental role of the movements in attention, is to maintain the appropriate state of consciousness and to reinforce it” (p. 25). In this quote, Ribot argues that the activity of the mind and the activity of the body are importantly and inextricably linked, foreshadowing the more recent focus on embodied cognition (e.g., Anderson, 2003; Clark, 1999; Wilson, 2002). Ribot’s observation can also be interpreted in the context of recent interests on attention lapses (Cheyne, Carriere, & Smilek, 2006; Seli, Cheyne, & Smilek, 2012; Smilek, Carriere, & Cheyne, 2010) and mind wandering (Giambra, 1995; Smallwood, Beach, Schooler, & Handy, 2008; Smallwood, Fishman, & Schooler, 2007; Smallwood & Schooler, 2006). Restating Ribot’s observation in terms of these recent interests, then, we could say that if one is trying to concentrate attention to prevent attention lapses and mind wandering from occurring, then the movement of the body would likely appear to become similarly concentrated. In contrast, if attention has lapsed, as when our minds wander, then the movement of the body would likely be spontaneous and less controlled. In the present article, we hope to recover the more embodied beginnings of attention, and explore the fundamental link between attention and fidgeting.
“Fidgeting” is a familiar term, and we likely all know at least one person who we would describe as a “fidgeter.” Yet, aside from a few exceptions (Mehrabian & Friedman, 1986; Sechrest & Flores, 1971; Smith & Narayan, 2008), it is a topic that has received relatively little study in psychology. Although little has been recently done on this topic, the observation of a link between cognitive experience and fidgeting is not entirely new. In support of his own claim that the activity of the mind and body are linked, Ribot (1890) raised as an example the recent, to him, efforts by Galton to assess attentiveness through fidgeting behaviour amongst the audience members at a long and tedious lecture (which recent research has indicated dramatically increases the probability of mind wandering; Risko, Anderson, Sarwal, Engelhardt, & Kingstone, 2012). Galton described these efforts in The Measure of Fidget (1885):
When the audience is intent each person forgets his muscular weariness and skin discomfort, and he holds himself rigidly in the best position for seeing and hearing.… But when the audience is bored the several individuals cease to forget themselves and they begin to pay much attention to the discomforts attendant on sitting long in the same position. They sway from side to side, each in his own way.… The audience was mostly elderly; the young would have been more mobile. Circumstances now and then occurred that roused the audience to temporary attention, and the effect was twofold. First, the frequency of fidget diminished rather more than half; second, the amplitude and period of each movement were notably reduced. (p. 174, emphasis added)
In Galton’s report, we find evidence, though still essentially anecdotal, of a strong link between the attentiveness of the audience and the frequency and degree of fidgeting in which they engaged. The inference made by Galton is that the onset of fidgeting has a great deal to do with the discomfort involved in sitting still, which is ignored as long as attention is maintained, and so fidgeting begins when information about this discomfort is able to break through into consciousness. The explanation provided by Ribot appears to be much more cognitively based, however, and suggests a more direct and spontaneous link between the activity of the mind and the activity of the body, with discomfort likely being more epiphenomenal to the onset of fidgeting.
Given the anecdotal support for a link between fidgeting and attention and a relative dearth of research on the topic, the present research sought to better understand the potentially complex nature of this relation in the general population. To this end, we first examined the relation of everyday fidgeting behaviour and the tendency to be inattentive.
Study 1: Inattention and Body Movement
To examine the hypothesis that fidgeting behaviour is related to inattention, we explored the relations among four self-report questionnaires. Frequency of attention lapses and associated cognitive errors were assessed via the Mindful Attention Awareness Scale–Lapses Only and the Attention-Related Cognitive Errors Scale (MAAS-LO and ARCES, see Carriere, Cheyne, & Smilek, 2008), respectively. To investigate whether fidgeting was associated with attention, in particular, rather than cognitive behavior, in general, we also assessed the frequency of everyday memory failures via the Memory Failures Scale (MFS; Carriere et al., 2008). Fidgeting itself was measured via a new measure, the Spontaneous Activity Questionnaire (SAQ), which we developed for this study.
Based on previous anecdotal reports, we predicted the MAAS-LO and ARCES would be significantly positively correlated with the SAQ. We also predicted that the MFS would likely show a significant zero-order correlation with the SAQ, but that this correlation may well be spurious and explained by covariance with the MAAS-LO and ARCES. We also assessed age for all participants in order to account for the assumption (posited by Galton, 1885, and, more recently, Manini, 2010) that as individuals’ age and overall general activity energy expenditures decline, their fidgeting is likely to decrease as well.
Participants were from an international sample of 305 respondents who completed all four questionnaires via an online study conducted through the Amazon Mechanical Turk. Participants included in these analyses were allowed no more than two missing responses for any given questionnaire, eliminating one participant and reducing the sample to a total of 304 participants; 245 participants had zero missing responses. Participants received $0.75 compensation for completing the study. Most participants opted to complete a brief demographic information form, including age, gender, country, and occupation. Age ranged from 18 to 72 years, with a mean of 33.72 years (SD = 13.3). There were 156 males and 148 females, the vast majority of whom live in the United States (n = 269), with the remainder coming from other primarily English-speaking countries such as Canada (n = 8) and Great Britain (n = 6); combined, these countries accounted for 93.1% of the sample. Although occupations were not analysed, it is worth noting that only 77 participants identified themselves as students.
Participants first received a brief initial demographics questionnaire, followed by the four study questionnaires, which were completed in a randomly selected order for participants. Individual items within each questionnaire were randomly ordered as well, so that all participants would be likely to receive at least slightly different orderings of questionnaires and items within questionnaires. For each measure item, mean scores were calculated by averaging across the responses provided, allowing us to accommodate occasional missing responses.
To measure an individual’s typical experience of attention lapses, the 12-item MAAS-LO (Carriere et al., 2008) was selected. With the exception of having removed three items, and using direct rather than reverse-coded scoring of all remaining items, the MAAS-LO is identical to the MAAS originally developed by Brown and Ryan (2003) as a measure of mindfulness. The MAAS-LO thus includes items such as “I do jobs or tasks automatically, without being aware of what I’m doing,” in order to assess mindless behaviour in everyday situations. It is scored using a 6-point Likert scale ranging from almost never (1) to almost always (6), and so responses indicating a greater frequency reflect a greater propensity toward everyday attention lapses.
The current version of the Attention-Related Cognitive Errors Scale (Carriere et al., 2008) was incorporated to assess inattention in terms of the cognitive and behavioural mistakes that occur as a result of attention lapses. The ARCES is a 12-item questionnaire measuring the frequency with which one tends to experience cognitive failures. It is scored using a five-point Likert scale from never (1) to very often (5) and includes items such as “I make mistakes because I am doing one thing and thinking about another” and “I fail to see what I am looking for even though I am looking right at it.”
The current version of the 12-item MFS (Carriere et al., 2008) was selected as a measure of one’s tendency to experience memory failures in everyday life. The MFS includes items such as “I forget important dates like birthdays and anniversaries” and “Even though I put things in a special place I still forget where they are,” and uses a 5-point Likert scale ranging from never (1) to very often (5).
Perceived fidgeting behaviour was measured via the newly developed SAQ (see Appendix A). Because fidgeting can encompass a large variety of behaviours, not all of which will be engaged in by any given individual, we developed the SAQ to be nonspecific with respect to the involvement of any particular behaviour and focus instead on the extent to which the individual is likely to fidget in everyday life. The eight-item SAQ offers the simple instruction to “Please answer the following questions about your everyday fidgeting behaviour as accurately as you can,” and includes various aspects of one’s fidgeting behaviour, such as “I fidget” (scored from rarely to often), “Relative to other people, I feel I fidget” (scored from a lot less to a lot more), and “I fidget while I am deep in thought” (scored from never to always). The SAQ uses a 7-point Likert scale for all items, although the anchor points vary between questions.
Results and Discussion
As shown in Table 1, all measures were found to have good distributional and psychometric properties, with a good range of scores, no significant deviations from normality in skewness and kurtosis, and very satisfactory internal consistency. Pearson product-moment correlation coefficients are also presented in Table 1 (see Appendix A for item-total correlations for the SAQ). All questionnaire coefficients were moderate to large. Consistent with typical findings from previous studies, the MAAS-LO (inattention), ARCES (attention-related errors), and MFS (memory failures) were all highly positively correlated, and they all showed significant correlations with the SAQ (fidgeting). Overall, the correlations between attentional and fidgeting measures are consistent with the expectation that fidgeting increases when attention is lost.
Given the consistent positive correlations among all the questionnaires, including particularly the significant correlation between the MFS and SAQ, we conducted a stepwise multiple regression analysis to evaluate the unique contributions of these measures to everyday fidgeting behaviour. Age was also included in this analysis to control for natural reductions in fidgeting as a result of aging.footnote Age did not provide a significant unique prediction of the SAQ in the regression, whereas both the MAAS-LO and the ARCES provided significant unique contributions; the ARCES provided the largest prediction by a small margin (see Table 2).
Furthermore, adding the MFS at Step 2 had negligible effect on the independent contributions of these three measures, with the MFS itself providing no significant contribution. These results indicate that self-reported inattention and everyday attention-related cognitive errors are associated with increased everyday fidgeting behaviour, even when controlling for reductions in fidgeting as a result of age. Furthermore, the lack of a significant unique contribution of memory failures to fidgeting provides some discriminant validity, suggesting that the earlier anecdotal reports correctly identified attention in particular as an important contributor fidgeting behaviour.
We see, in the present findings, that the behaviour of the mind is strongly tied to the behaviour of the body in ways that perhaps extend beyond natural intuitions, such as Galton’s (1885) assertion that fidgeting increases with diminished attention as a method of alleviating physical discomfort. In particular, it appears we can apply a common distinction in both, where attention can be seen as either focused (i.e., being on-task) or lapsing (i.e., being inattentive, or off-task, as in the ARCES and MAAS-LO), and, similarly, body movement can be seen as either deliberate (i.e., goal oriented) or spontaneous (i.e., unintentional; as in the SAQ). Although one would certainly expect on-task attention to be related to the commission of deliberate and goal-oriented body movements—such as the attentionally directed movements of one’s fingers on the keyboard while typing—it is interesting and more unusual to consider spontaneous, non-goal-oriented movement behaviour as being similarly tied to the experience of off-task attention.
Study 2: Mind Wandering and Body Movement
Given the evidence in Study 1 of a link between inattention and fidgeting behaviour, we sought to extend our understanding of this link with a more direct evaluation of the association between mind wandering and spontaneous body movements. Mind wandering makes for an interesting follow-up in that it can, like bodily movement, present in both spontaneous and deliberate forms. That is, as Giambra (1995) noted, task-unrelated thoughts “may occupy awareness because they capture our attention—an uncontrolled shift—or because we have deliberately shifted our attention to them—a controlled shift” (p. 2). So mind wandering can be either a choice to deliberately direct our conscious train of thought away from the task at hand (particularly if the task at hand is not sufficiently entertaining; Giambra, 1989; Shaw & Giambra, 1993) or, more importantly for our purposes, it can be a spontaneous capture of attention to a train of thought wholly unrelated to our present experience (Shaw & Giambra, 1993; Smallwood & Schooler, 2006).
Guided by the above considerations, Study 2 assessed the relation between everyday fidgeting and mind wandering behaviour. For this study, mind wandering was measured via two scales, called the Mind Wandering: Deliberate (MW-D) and Mind Wandering: Spontaneous (MW-S) scales, which we developed in a previously unpublished study. As in Study 1, fidgeting behaviour was measured via the SAQ. We also included two additional measures of attention, the Attentional Control: Distraction (AC-D) and Attentional Control: Shifting (AC-S) scales, to further explore the link between attention and fidgeting behaviour. Based on our findings in Study 1, we predicted the MW-S would be a good predictor of the SAQ, whereas the remaining measures would likely provide weaker prediction, if any.
Participants were from an international sample of 246 respondents who completed all five questionnaires as part of a larger online pilot study conducted through the Amazon Mechanical Turk. As in Study 1, participants included in these analyses were limited in the number of missing responses allowed for any given questionnaire. For the SAQ (8 items), no more than two missing responses were allowed, and for the MW-D, MW-S, AC-D, and AC-S (each 4 items) no more than one missing response was allowed, reducing the sample by two, to a total of 244 participants; 204 participants had zero missing responses. Participants received $1.50 compensation for completing the full study. Most participants opted to complete a brief demographic information form, including age, gender, country, and occupation. Age ranged from 18 to 82 years, with a mean of 36.06 (SD = 14.61). There were 98 males and 144 females, the vast majority of whom live in the United States (n = 214), with the remainder coming from other primarily English-speaking countries like Canada (n = 10) and Great Britain (n = 4); together these three countries accounted for 93.4% of the sample. Although occupations were not analysed, it is worth noting that only 47 participants identified themselves as students. Mixed with the questionnaires used in this study were other attention-related questionnaires, and after completing these questionnaires, participants completed a brief sustained attention task followed by a questionnaire asking about their typical video-gaming behaviour.
All participants first received an initial demographics questionnaire followed by the remaining questionnaires, which were completed in random order across participants. In addition, the individual items within each questionnaire were once again randomly ordered. To accommodate occasional missing responses, item mean scores were calculated by averaging across the responses provided. In addition to the four questionnaires described here, the SAQ used in Study 1 was retained as the measure of everyday fidgeting behaviour for the present study.
The four-item MW-D scale was selected as our measure of deliberate mind wandering. The MW-D items were “I allow my thoughts to wander on purpose,” “I enjoy mind-wandering,” “I find mind-wandering is a good way to cope with boredom,” and “I allow myself to get absorbed in pleasant fantasy.” The MW-D is scored using a 7-point Likert scale ranging from rarely (1) to a lot (7) for Items 1, 2, and 4, and ranging from not at all true (1) to very true (7) for Item 3. Participants were provided the simple instruction, “For the following statements please select the answer that most accurately reflects your everyday mind wandering.” Responses indicating a higher value therefore reflect a greater tendency to deliberately engage in mind wandering in everyday life.
The four-item MW-S scale was selected as our corresponding measure of spontaneous mind wandering. The MW-S is similar to the MW-D but reflects inadvertent or uncontrolled mind wandering behaviour. Its items include “I find my thoughts wandering spontaneously,” “When I mind-wander my thoughts tend to be pulled from topic to topic,” “It feels like I don’t have control over when my mind wanders,” and “I mind-wander even when I’m supposed to be doing something else.” The MW-S is also scored using a 7-point Likert scale ranging from rarely (1) to a lot (7) for Items 1, 2, and 4, and ranging from almost never (1) to almost always (7) for Item 3. Participants were provided the same simple instruction as for the MW-D: “For the following statements please select the answer that most accurately reflects your everyday mind wandering.” Responses indicating a higher value therefore reflect a greater tendency to spontaneously engage in mind wandering in everyday life.
The two remaining questionnaires were derived from the Attentional Control Scale developed by Derryberry and Reed (2002). The Attentional Control Scale is identified as having two factors reflecting (a) attentional distraction, and (b) difficulties with attentional shifting. For the present study, these factors were reduced to four statements each, and reworded or rescored to maintain a greater overall consistency. As a result, we chose to treat them as separate questionnaires for our study. For both questionnaires, participants were provided the brief instruction, “For the following statements, please select the response that most accurately reflects your everyday attentional control ability.” The AC-D questionnaire contains the items “I have difficulty when there is music in the room around me,” “While I am working hard on something, I still get distracted by events around me,” “It’s very hard for me to concentrate on a difficult task when there are noises around,” and “When I am reading or studying, I am easily distracted if there are people talking in the same room.” The AC-S questionnaire contains the items “I am slow to switch from one task to another,” “It takes me a while to get really involved in a new task,” “It is difficult for me to alternate between two different tasks,” and “After being interrupted, I have a hard time shifting my attention back to what I was doing before.” For both questionnaires, all items are scored on a 5-point Likert scale ranging from almost never (1) to always (5).
Results and Discussion
As in Study 1, all measures were found to have good distributional and psychometric properties (see Table 3), with a good range of scores, no substantial deviations from normality in skewness and kurtosis, and very satisfactory internal consistency. Pearson product-moment correlation coefficients are also presented in Table 3 (see Appendix B for item-total correlations for the MW-D and MW-S, and Appendix C for item-total correlations for the AC-D and AC-S). Among the MW-S, AC-D, AC-S, and SAQ, the coefficients were all moderate to large, whereas the MW-D showed small correlation coefficients with all but the MW-S. All questionnaire relations were positive, and, in particular, all measures showed significant correlations with the SAQ (fidgeting). Overall, the correlations between the mind wandering, difficulty with attentional control, and fidgeting measures were once again consistent with the expectation that fidgeting increases when attention is diminished.
We conducted a stepwise multiple regression analysis to evaluate the unique contributions of each of these questionnaire measures to everyday fidgeting behaviour. Age was again included in this analysis to control for natural reductions in fidgeting as a result of aging. As shown in Table 4,
Age, the MW-S, and the AC-S all offered unique contributions to the SAQ, although the contribution of the AC-S was small and only marginally significant. Furthermore, adding the AC-D and AC-S at Step 2 affected only the contribution of the MW-S, reducing it’s β by a modest .10. These results indicate that self-reported difficulty with spontaneous mind wandering is associated with increased everyday fidgeting behaviour, and difficulties with willfully shifting attention when necessary may be as well, whereas aging, as in Study 1, offsets these effects somewhat, by providing a small decrease in everyday fidgeting. Interestingly, deliberate mind wandering provided no independent contribution to everyday fidgeting behaviour, suggesting that fidgeting behaviour increases only when one experiences greater unintentional mind wandering. At the same time, it is interesting that difficulties with attentional control provided little prediction of fidgeting independent of spontaneous mind wandering—an outcome we did not predict on the basis of Study 1. Of course, both attentional control measures did have a significant zero-order relation to the fidgeting measure, so these findings are not inconsistent with our general conclusion that inattention and mind wandering are associated with fidgeting. Rather, the regression indicates that these attentional control measures do not explain any unique variance that is not also explained by the mind wandering measures.
Overall, the present findings once again support the notion of strong ties between the behaviour of the mind and the behaviour of the body. Unlike the more general inattentiveness measured in Study 1, mind wandering was assessed in both deliberate and spontaneous forms. Under the assumption that fidgeting behaviour is spontaneous body movement, the particularly strong relation between spontaneous mind wandering and fidgeting is consistent with the embodiment hypothesis: When the mind is spontaneously released from the burden of attending to the task at hand, the body is likely to follow suit.
Study 3: A Replication
Because Studies 1 and 2 make use of several previously unused questionnaires, we sought to replicate both sets of findings in Study 3. For this study, participants completed all of the questionnaires discussed in the first two studies, and our prediction was that we would obtain the same results for the present sample. This replication should therefore reaffirm the notion that decreased everyday attention is associated with greater fidgeting behaviour. Furthermore, intentionally decreased attention, in the form of deliberate mind wandering, should be associated with fidgeting only to the extent that it is also strongly related to the tendency to spontaneously engage in mind wandering.
Participants were again from an international sample of 167 respondents who completed all of the previously discussed questionnaires via an online study conducted through the Amazon Mechanical Turk. Participants included in these analyses had no more than two missing responses for any of the longer questionnaires (SAQ, MAAS-LO, ARCES, and MFS) and no more than one missing response for any of the shorter questionnaires (MW-D, MW-S, AC-D, AC-S), removing three respondents from the sample for a total of 164 participants; 113 participants had zero missing responses. Participants received $0.75 compensation for completing the questionnaires. Most participants opted to complete a brief demographic information form, including age, gender, country, and occupation. Age ranged from 18 to 76 years, with a mean of 32.79 (SD = 12.64). There were 70 males and 94 females, the majority of whom live in the United States (n = 143), with Great Britain (n = 8) and Canada (n = 7) as the next largest contributors, together accounting for 96.3% of the final sample. As in the previous studies, occupations were not analysed except to note that only 30 participants self-identified as students.
After first receiving the initial demographics questionnaire, the SAQ, MAAS-LO, ARCES, MFS, MW-D, MW-S, AC-D, and AC-S were completed in random order across participants. In addition, the individual items within each questionnaire were randomly ordered, such that no two participants were likely to receive the exact same ordering of questionnaires and items. To allow for occasional missing responses, item mean scores were calculated for each measure by averaging the provided responses.
Results and Discussion
As expected on the basis of the first two studies, all measures had good distributional and psychometric properties, as shown in Table 5. The greatest degree of skewness was found in age, but it was not large enough to be problematic for the present analyses.
Pearson product-moment correlation coefficients are presented in Table 6. Nearly all coefficients are significant, and most are moderate to large. As predicted by the prior studies, the MAAS-LO, ARCES, and MW-S all show strong relations with the SAQ. The only relation failing to reach significance was between the MW-D and SAQ (p = .182), which was previously significant as a zero-order relation but was then eliminated in the multiple regression analyses (Study 2). Altogether, then, the present findings appear to represent a close replication of our previous findings. It is worth noting that several of the current correlation coefficients were previously unavailable (shaded in Table 6).
Although we had no specific predictions with respect to these relations, they do appear to follow a sensible pattern in that the inattention and memory measures are more strongly related to spontaneous mind wandering than to deliberate mind wandering (and of similar magnitude in each case) and are also strongly related to the attentional control measures.
To replicate the findings from Study 1, we again conducted a multiple regression analysis predicting everyday fidgeting (SAQ) with age, inattention (MAAS-LO), attention-related errors (ARCES), and memory failures (MFS). As shown in Table 7,the present findings do closely replicate those of Study 1. The magnitudes of the observed βs are quite similar to those observed in Study 1, with the ARCES providing the largest unique prediction of the SAQ. The addition of the MFS at Step 2 still had little effect on the overall pattern—although, in this case, the β for the ARCES showed a small decrease rather than a small increase. There is, however, a notable decrease in significance levels across the board, which can be interpreted as being mainly a result of the substantially reduced sample size compared with Study 1. The most notable departure from the pattern previously observed has to do with the β of the MFS itself, which was much larger in the present study, though still small and not significant.
We next sought to replicate the findings from Study 2 by conducting a multiple regression analysis predicting everyday fidgeting (SAQ) with age, deliberate mind wandering (MW-D), spontaneous mind wandering (MW-S), attentional control difficulties associated with distraction (AC-D), and attentional shifting (AC-S). As shown in Table 8, the magnitudes of the observed βs are very similar to those observed in Study 2. The largest prediction was once again provided by the MW-S, and the addition of the AC-D and AC-S at Step 2 resulted in a decrease of the β for the MW-S by .10. After age and MW-S were taken into account, the only other predictor to approach significance was the AC-S, although, again, the reduced sample size diminished significance levels across the board, and so even as a one-tailed replication, the AC-S was, at best, only marginally significant. It is worth noting that, unlike the previous multiple regression analysis, age remained a significant predictor of the SAQ for this analysis, suggesting that age exhibited a greater overlap in variance with the MAAS-LO, and ARCES in particular, for the present study.
The present findings are once again clearly consistent with a hypothesis of strong associations between attentional state and spontaneous motor behaviour, whether looking at general inattentiveness, as measured in Study 1, or more specific mind-wandering-related inattentiveness, as in Study 2. All three studies were conducted online through the Amazon Mechanical Turk, with participants coming primarily from North America, and should therefore provide a good representation of the general population. Given that most research in psychology is conducted with more homogenous undergraduate student populations, however, it seemed worthwhile to attempt to also replicate these findings using such a sample.
Study 4: A Student Population
Because the first three studies were conducted with the general population, we sought to replicate our findings using a more typical student population in Study 4. For this study, participants completed all of the questionnaires used in our previous studies, with a few modifications, and our prediction was that even with a more homogenous student sample we would obtain the same general pattern of results. For this study, we also added a second fidgeting questionnaire, developed by Mehrabian and Friedman (1986), which takes a very different approach to the measurement of everyday fidgeting tendencies by assessing people’s propensities to engage in specific movements (e.g., pen jiggling). Because both scales were designed to measure an individual’s general propensity to fidget, we anticipated a strong relation would be found between the Mehrabian and Friedman fidgeting questionnaire and our SAQ, which would help to further establish the validity of our new measure.
Participants were 201 undergraduate students from the University of Waterloo who completed the study questionnaires for partial course credit. As with the previous studies, participants included in these analyses had no more than two missing responses for any of the longer questionnaires and no more than one missing response for any of the shorter questionnaires. Because a large majority of the participants were young, we also restricted age to a maximum of 25 years; 9 participants who opted not to disclose their age were kept in the sample. The missing response and age restrictions reduced the sample size by 9 participants, to 192. Of these participants, there were 131 who had zero missing responses. In the final selection of participants age ranged from 17 to 25 years, with a mean age of 19.82 (SD = 1.66). There were 78 males and 111 females.
Participants completed a demographics questionnaire prior to the present study, during an initial mass testing and prescreening session. The study questionnaires were completed online in the same manner as the previous studies. Consistent with the previous studies, item mean scores were calculated for each measure by averaging the provided responses. There were, however, two important differences between the present study and the previous studies. First, to better establish the distinctiveness of the MW-D, MW-S, AC-D, and AC-S, these scales were combined into one 16-item Mind Wandering and Attentional Control Questionnaire when presented to the participants. All items were scored on a 5-point Likert scale ranging from almost never (1) to very often (5), and participants were provided the simple instruction, “For each of the following statements, please select the response that most accurately reflects your everyday experiences.” Second, an additional fidgeting questionnaire was provided to complement the SAQ.
The Mehrabian and Friedman (1986) Fidgeting Questionnaire (FQ) is a 40-item measure of everyday fidgeting tendencies. The FQ includes both direct- and reverse-scored (R) items, such as, “I hardly ever pinch my cheeks” (R), “I usually jiggle my pen when I am holding it, but not writing with it,” “When seated, I don’t move around restlessly in my seat” (R), and “I usually bend or play with a straw when drinking through it.” The FQ is scored using a 9-point Likert scale ranging from very strongly disagree (−4) to very strongly agree (4), with neither agree nor disagree (0) as the midpoint. The original instructions for the FQ were unknown, so for the present study, participants were instructed as follows, “The following statements are about habitual actions people might engage in from time to time. Please rate your agreement with each statement as accurately as you can.” After reverse-scoring as necessary, responses indicating a higher value reflect a greater tendency to engage in fidgeting behaviour. During its initial development (Mehrabian & Friedman, 1986), the FQ was validated against experimenter-observed fidgeting behaviour in a session where participants were required to complete a moderately frustrating game of checkers. Specifically, Mehrabian and Friedman had participants play a game of checkers and observed how much time the participants spent fidgeting during the game. The total amount of time spent fidgeting was correlated with self-report scores of habitual fidgeting.
Results and Discussion
As shown in Table 9, the majority of our measures continued to demonstrate good internal consistency and no substantial deviation from normality in skewness or kurtosis. Nonetheless, the AC-S measure failed to reach even an acceptable level of internal consistency (α = .69), and the AC-D measure and MFS both had a Cronbach’s alpha of only .77. Fortunately, because none of these three measures had reached significance as unique predictors of fidgeting in our previous regression findings, their lack of internal consistency in the present study represents only a minor problem for our subsequent analyses. Indeed, an examination of Table 10 reveals that, aside from generally diminished coefficients—particularly those involving the MFS, AC-D, and AC-S—the overall pattern of observed correlation coefficients is largely consistent with our previous findings. Importantly, the SAQ and FQ had one of the largest correlation coefficients, and both exhibited similar relations with all measures except the MW-D, which was significantly related to only the FQ. Thus, it appears that the SAQ and FQ are indeed both measuring a similar construct—namely, everyday fidgeting behaviour—but that the FQ alone may capture both spontaneous and deliberate fidgeting.
It is unclear whether the current reduction in internal consistency was due to the change in sample population (i.e., young undergraduate students vs. a broader selection of the general population) or simply chance variation that can occur between samples. It is potentially telling, however, that every one of our measures exhibited reduced internal consistency with this sample, with a mean change in α of −.051 (SD = .035) compared with each measure’s own previously observed α levels. The AC-S, however, may have been particularly affected by the fact we presented the MW-D, MW-S, AC-D, and AC-S as one single measure in the present study, given that it was the only one failing to reach an adequate level of internal consistency. To examine whether the combined scale had maintained its original four-factor design, we next conducted an exploratory factor analysis with varimax rotation. As shown in Table 11, we obtained four factors with eigenvalues greater than 1.0. Together these accounted for 64.7% of the variance in the combined measure, with 31% coming from the first factor. An examination of the factor loadings revealed an overall good separation of the items into their original measures, with only item two from the AC-D (“When I am working hard on something, I still get distracted by events around me”) having joined up with the items from the MW-S in Factor 1 rather than the other items from the AC-D in Factor 3. The AC-S items—not surprisingly, given their low internal consistency—exhibit some of the weakest overall factor loadings in Factor 4 as well as some of the greatest relative cross-loadings—with Factor 1 (the MW-S).
Having shown that the most important measures demonstrated good psychometric properties, and that inattention and mind wandering were still associated with increased fidgeting behaviour overall, we sought to replicate our previous regression analyses with this more homogenous and younger student population. Because age was intentionally restricted in this sample, it was dropped from the analysis; otherwise, we simply repeated the same stepwise multiple regression that was performed in Studies 1 and 3, as shown in Table 12.
For this sample, the results were generally consistent with our previous findings; however, the contribution of the ARCES did not reach significance, whereas in the previous studies, both the MAAS-LO and ARCES provided some significant, unique, predictive ability, and the ARCES was nominally the larger of the two. It is not clear whether this difference was due to random variation between samples or an important difference between young undergraduate students and the general population; further study may be needed. Irrespective of this outcome, the findings nonetheless corroborate the general belief that a tendency toward greater fidgeting behaviour is associated with a loss of attention, particularly inasmuch as the addition of the MFS at Step 2 once again had very little influence on the contributions of the ARCES and MAAS-LO.
We next conducted the regression analyses performed in Studies 2 and 3, as shown in Table 13. Importantly, the final model was not significant in this case, mainly due to the inclusion of the clearly problematic AC-S at Step 2. Indeed, with the poor internal consistency of the AC-S for this sample, and the cross-loading with the MW-S in the factor analysis above, it is not surprising that its inclusion here had a large detrimental effect on the final multiple regression model. Similarly, the AC-D continued to add little predictive value and had little impact on the overall model. We therefore encourage the reader to attend to the main finding at Step 1, which, although providing a model with notably diminished predictive power compared with our previous findings (R = .20, F[2, 189] = 3.89, p = .022), does nonetheless more closely replicate the results from Studies 2 and 3. In this case, we can clearly see that it is spontaneous mind wandering, rather than deliberate mind wandering, that is associated with everyday fidgeting behavior, even in this sample. This finding once again highlights that spontaneous body movements are more likely to arise if the mind has also spontaneously departed from the task at hand.
Whereas each of the first three studies was conducted online through the Amazon Mechanical Turk, the present study was conducted with a more traditional, and more homogenous, undergraduate student population. It is important not to make too strong an interpretation of the differences between the findings between these samples, but there were some notable issues that would be worthy of further study. First, all of the questionnaires exhibited reduced internal consistency in the present sample. Second, and likely to be at least to some extent a result of the first issue, most correlation coefficients were attenuated in the present sample. In spite of these differences, the results remained consistent with the overall hypothesis that fidgeting and inattention are linked, as well as with the specific hypothesis that spontaneous, but not deliberate, mind wandering predicts everyday fidgeting behaviour. Furthermore, the observed correlations showed good consistency between the SAQ and the longer FQ. As a result, the SAQ is a good alternative for the FQ, especially for researchers interested in studying fidgeting in general rather than a tendency to engage in any particular subset of fidgeting behaviour, as obtaining a high score on the FQ requires individuals to endorse a wide variety of extraneous behaviours that may be too specific to obtain a general measure of fidgeting (e.g., “I often bend paper cups or aluminum cans after I drink their contents” and “I don’t unbend paperclips”).
In three independent samples of the general population, we found strong support for earlier anecdotal reports that fidgeting behaviour is linked to decreased attention and spontaneous mind wandering. In a fourth study using a young undergraduate student population, with a few relatively minor exceptions, we found a very similar though attenuated pattern of results. More specifically, in the earlier studies (Studies 1 and 3) we found a consistent pattern whereby inattention was strongly predictive of fidgeting. In the final study, this pattern remained, but the total predictive ability was reduced and inattention that leads to cognitive–behavioural errors did not provide significant prediction of fidgeting independent of general inattention. Given the large degree of shared variance between these two predictors, however, it is not surprising to find instability with regard to which of the two measures provides the majority of the variance in the regression analysis. With respect to mind wandering behaviour, however, all three studies in which it was measured showed that the tendency to deliberately mind wander was, at most, weakly related to fidgeting behaviour, and was not a significant predictor once the tendency to spontaneously mind wander was taken into account. Similarly, difficulties with attentional control were not strongly correlated with fidgeting beyond their shared association with spontaneous mind wandering. Whereas, at first glance, this may come as a surprise, it is important to recall that difficulties with attentional control indicate attention is still engaged, but not necessarily on the right information, and, to that extent, may measure an aspect of attention that is neither clearly deliberate nor spontaneous. Notably, the observed patterns of correlations across the studies rule out the possibility that strong the relations among measures simply reflect participants’ tendencies to present themselves either positively negatively on each measure. Specifically, the results show that not all of the measures were strongly correlated with each other, that is, both measures of intentional mind wandering and memory failures, which are both ostensibly susceptible to this kind of reporting bias, were not independently predictive of mind wandering.
As we have already discussed, both mind wandering and body movements can be divided into deliberate or goal-oriented, and unintentional or spontaneous, forms. Deliberate mind wandering is analogous to daydreaming and is therefore more like paying attention than we might typically think, because it represents—as Giambra (1995) noted—an intentional shift from thinking about the task at hand to some other train of thought. Deliberate body movements are those in which we engage to get work done, like the hand movements necessary for writing. The earliest known attempt to systematically study fidgeting placed it firmly in this category, suggesting that its link with attention was due to the inability of physical discomfort to enter consciousness when attention is steadfastly focused on other concerns (Galton, 1885). That is, fidgeting reflects a release from the constraint of apperception previously imposed by attention, and fidgeting movements are directed toward relieving discomfort. The more traditional modern view of fidgeting is instead as an impulsive and spontaneous behaviour, rather than as a goal-directed one, as seen in the diagnostic criteria for attention-deficit hyperactivity disorder (ADHD; American Psychiatric Association, 2000). This modern link to attention is particularly clear in the combined subtype of ADHD, which requires the patient to exhibit both inattentiveness and hyperactivity, and may represent the majority of cases (Millstein, Wilens, Biederman, & Spencer, 1997; Craig, 2011).
ADHD, of course, is most typically recognised as a childhood disorder and, with respect to hyperactivity, is diagnosed mainly through more extreme behaviour such as running around at inappropriate times and talking excessively, although impulsive fidgeting is also one of the criteria for children (American Psychiatric Association, 2000). Despite this primary emphasis on childhood, ADHD is believed to persist into adulthood in many cases (Adler, 2004; Faraone et al., 2000; Craig, 2011), with initially very overt hyperactivity shifting more toward less obvious and certainly more socially acceptable forms, such as impulsive fidgeting and restlessness (Craig, 2011). Indeed, one study has reported fidgeting as the most common hyperactivity symptom and found that this symptom was present in more than 70% of adult ADHD patients (based on DSM–III–R criteria; Millstein et al., 1997). Even here, though, the relation between inattention and spontaneous hyperactivity is not viewed in the same way as the anecdotal reports that formed the basis of the present research. Indeed, rather than noting a primarily gross association of inattention and hyperactivity symptoms, these early anecdotal reports suggested there should be a momentary association as well—that is, fidgeting is a behavioural index of waning attention at the precise moment at which it occurs. The present findings, despite being similarly based on trait-level assessments, provide some empirical support for this perhaps more intriguing alternative view of the relation between fidgeting and attention by showing that fidgeting, as a spontaneous form of body movement, is related only to a tendency to engage in the corresponding spontaneous form of mind wandering. To better understand the possible online (i.e., in the moment) relation between mind wandering and fidgeting, future studies could measure participants’ movements (i.e., fidgeting) while they complete a sustained attention task in which their thoughts are sampled randomly throughout the task. This investigation might allow researchers to determine whether, as hypothesised here, fidgeting increases at the precise moment at which mind wandering takes place.
One possible reason for the present findings showing a strong pairing of spontaneous thought and spontaneous movement is the presence of an unmeasured third variable underlying them both, potentially in the form of a fundamental, nonspecific instability in all aspects of an individual’s experience—whether mental or physical. We describe this fundamental tendency as being driven by a variability mechanism. Such a mechanism would be adaptive, in part, because it ensures that the system does not get stuck in a rut, which is important for various reasons, but notably including learning, even in an unchanging or unstimulating external environment. A primary role of attention, then, would be to override or modulate this variability mechanism to, at times, maintain focus on a particular task and reduce the impact of task-irrelevant information and thoughts. One central aspect of the framework we present here is that spontaneous instability (i.e., variability) in consciousness and body movements is considered to be the normal default state of an individual rather than sustained attention and controlled body movements.
It is worth noting that the proposed “variability mechanism” need not be considered a single mechanism, or function of a particular brain area per se; it might simply be a general property of neural systems. Much recent work has been done on the benefits of stochastic resonance in sensory neurons (Faisal, Selen, & Wolpert, 2008; Wiesenfeld & Moss, 1995), though it is perhaps better termed stochastic facilitation (McDonnell & Ward, 2011). In stochastic facilitation, a moderate amount of “noise” added to a neural system actually improves its ability to process information by allowing neurons to detect stimuli that would otherwise remain below threshold. Too little noise provides no improvement, whereas too much will overload the neural system and degrade information processing performance (McDonnell & Ward, 2011); in other words, there appears to be a “goldilocks” zone with regard to the amount of noise that confers benefits to performance. Interestingly, other recent research suggests that attention functions primarily by limiting the correlation of noise across a population of neurons rather than affecting the activity of any specific neuron (Cohen & Maunsell, 2009). These lines of research are compatible with the notion of an attentionally modulated variability mechanism, and, if similar processes operate outside of sensory neurons, this could explain why both the mind and body wander off when constraints imposed by attention are lifted.
The present research is limited to the extent that it is reliant on questionnaire assessments of inattention, mind wandering, and fidgeting. Nonetheless, the present findings represent an important starting point for future research on fidgeting, to the extent that it provides a new measure of everyday fidgeting that is both straightforward and takes little time to administer, which should allow future researchers to easily identify populations of “fidgeters” and “nonfidgeters” for more in vivo analyses. Furthermore, the potential weaknesses of using general questionnaire measures makes the present findings all the more striking, as it could have quite easily been the case that the link between inattention and fidgeting was specific to only certain, probably boring, environments like the lecture hall in which it was first observed by Galton. That a strong relation between inattention and fidgeting was observed via general questionnaires suggests they may be more tightly bound than we might otherwise have imagined.
On the whole, the present set of studies provides good support for the initial hypothesis, put forth at the earliest beginnings of our field, that fidgeting behaviour and attention are linked. Interestingly, and to some extent in opposition to the views of Galton (1885), yet perfectly consistent with the views of Ribot (1890), fidgeting does not appear to be associated with the tendency to engage in deliberate mind wandering (i.e., to bodily discomfort). Instead, it seems an individual who has a mind that tends to spontaneously wander away from the task at hand likely has a body that tends to wander as well.
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As a reviewer noted, the assumption that fidgeting decreases with age is an interesting one and determining the truth of this assumption is a worthwhile endeavor. Such validation was not an initial goal of the present work, however, and we did not collect a sample that was diverse enough to properly assess the effects of aging on fidgeting. Nonetheless, we wanted to acknowledge this prior assumption and to control for possible influences of age on fidgeting within our sample.