Excessive boredom among adolescents: A comparison between low and high achievers.

Existing research shows that high achievement boredom is correlated with a range of undesirable behavioral and personality variables and that the main antecedents of boredom are being over- or under-challenged. However, merely knowing that students are highly bored, without taking their achievement level into account, might be insufficient for drawing conclusions about students' behavior and personality. We, therefore, investigated if low- vs. high-achieving students who experience strong mathematics boredom show different behaviors and personality traits. The sample consisted of 1,404 German secondary school students (fifth to 10th grade, mean age 12.83 years, 52% female). We used self-report instruments to assess boredom in mathematics, behavioral (social and emotional problems, positive/negative affect, cognitive reappraisal, and expressive suppression), and personality variables (neuroticism and conscientiousness). In comparing highly bored students (more than one SD above M, n = 258) who were low vs. high achievers (as indicated by the math grade, n = 125 / n = 119), results showed that there were no mean level differences across those groups for all variables. In conclusion, our results suggest that high boredom can occur in both low- and high-achieving students and that bored low- and high-achievers show similar behaviors and personality profiles.

Introduction

Boredom is one of the most commonly experienced emotions in educational settings [1,2]. Adolescents report being bored 30–40% of the time in school [3,4], but also in their spare time [5]. Highly bored students were shown to avoid schoolwork [6], to have attention problems, and reduced effort, self-regulation, and motivation [7-9]. They were also shown to use less effective learning strategies [2,9]. As a consequence, there is consistent evidence that boredom correlates negatively with academic achievement [9-17]. More generally, high boredom among adolescents has been associated with numerous serious problems like dropping out of school [4,18] or juvenile delinquency [19,20]. An important and well-documented characteristic of boredom is that it can be triggered by both over- and under-challenge [21]. However, it is unclear whether boredom is similarly severe when students are bored due to over-challenge and when they are bored due to under-challenge. In other words: Are undesirable correlates of boredom worse in the case of over-challenge, and may under-challenged students not suffer as much? Or is it the excessive boredom per se that covaries with problematic behavior and personality? To address this question, we systematically compared students who are highly bored and low-achieving, that is, likely over-challenged, and highly bored yet high-achieving, that is, likely under-challenged, in the subject of mathematics. The present study thus seeks to enrich the literature by enhancing our understanding of achievement boredom. Specifically, we add further knowledge about a potential differentiation between boredom due to being over- vs. under-challenged and offer practical implications for teachers, students, and parents.

Boredom as an unpleasant emotion with undesirable correlates

Boredom, most generally, is described as an unpleasant and distressing experience [22]. There are two widely used scales to measure general trait boredom: The Boredom Proneness Scale [BPS; 23] and the Boredom Susceptibility Scale [BSS; 24]. Research on the BPS has revealed that boredom proneness has multiple undesirable correlates, including alexithymia [25], alienation [26], anger and aggression [27-29], impulsiveness [28,30-32], loneliness [23], narcissism [33], negative affect [34], neuroticism [28,35,36] procrastination [37,38], and unsociability [31]. In turn, low levels of boredom proneness have been shown to be linked with higher levels of conscientiousness, openness to experience [6], and life satisfaction [23]. High scores on the BSS have been reported to be associated with higher levels of motor impulsivity, sensitivity to reward, gambling, alcohol, and smoking [36,39]. Going beyond such general, context-transcending findings, the present study specifically addresses boredom at school, and even more specifically, student experiences of boredom in the subject of mathematics. We thus assess boredom as a trait construct in a domain-specific way.

While mathematics boredom has been studied in several recent studies addressing, for example, the control- and value-appraisal antecedents of mathematics boredom [9,40], or boredom-achievement links [41], no study to date seems to have explored whether such domain-specific boredom is also linked with person-level behavioral and personality variables. In other words, it remains open to question if those students who report to experience intense boredom in mathematics only show undesirable levels of structs related to the domain of mathematics (e.g., poor study habits), or if they also show problematic behavior patterns beyond this context (e.g., lower sociability). In line with Bronfenbrenner’s [42] ecological systems theory, we suggest that domain-specific boredom and more general behavioral and personal variables inevitably interact with each other. Thus, the first aim of this study was to replicate prior correlational findings as demonstrated using more general instruments for the assessment of boredom in the subject of mathematics.

Boredom due to being over- vs. under-challenged

The idea of boredom being caused by under-challenge has already been brought forward by Csikszentmihalyi in 1975 [43]. In this work, he argued that boredom supposedly arises in situations in which someone’s competencies are higher than the situational opportunities or, in other words, in situations that are under-challenging. However, boredom can also be prompted when task demands are too high and cannot be interpreted in a meaningful way, implying over-challenge [8]. Integrating across both perspectives, Pekrun’s [44,45] control-value theory of achievement emotions proposes that boredom should be linked with either low or high control. In other words, according to this theory, students should experience boredom when they appraise that success is either quite easily or only barely attainable for them [40]. This implies that both low and high achievers may experience high levels of boredom. Over the past years, these theoretical propositions have been addressed by a large body of empirical research which has consistently demonstrated that boredom is, indeed, experienced in both over- and under-challenging situations [21,46-50].

Despite this compelling evidence on the meaning of differentiating between boredom due to being over- vs. under-challenged, what still seems open to question is whether experiencing intense boredom is similarly severe when students are low-achieving and thus likely over-challenged, or when students are high-achieving and thus likely under-challenged. On the one hand, the undesirable correlates of boredom may arise only for poorly performing students, while high performing students may not suffer as much from undesirable correlates of boredom. Such reasoning would be supported by the fact that high academic achievement typically is associated with conscientiousness [51,52] and high self-esteem [53]. Those factors could protect against the potential undesirable correlates of boredom. From another perspective, experiencing intense levels of boredom at school may imply undesirable correlates, irrespective of levels of challenge, and scholastic performance. Such reasoning is supported by Kannich’s [21] study which showed both being over- or under-challenged resulted in a decrease in career aspirations.

The present study

The present study addresses a gap in research on achievement boredom by systematically comparing students who are highly bored and low-achieving–thus, likely over-challenged, and highly bored yet high-achieving–thus, likely under-challenged. As potential undesirable correlates, we took into account both behavioral and personality variables. As achievement boredom has been shown to be highly domain-specific [12] and particularly salient in mathematics [49] we decided to focus on this domain. The present study takes a trait perspective [44], proposing that individuals systematically differ in their tendency to experience boredom.

The choice of constructs addressed in the present study was guided by the aim to address the central negative aspects mentioned in the general boredom proneness literature, inasmuch as they seemed relevant in our context. We thus aimed at replicating prior findings on a broad range of correlates of boredom as demonstrated using more general instruments for the assessment of boredom proneness, while assessing boredom specifically with respect to the subject of mathematics. Previous research has shown that boredom is linked with enhanced negative emotions [29], conduct problems [20,27,31], hyperactivity [54], peer problems [26], and lack of prosocial behavior [31]. Therefore, to explore potential undesirable correlates of boredom, we took all subscales of the Strength and Difficulties Questionnaire [SDQ, 55] into account. Furthermore, boredom has been shown to be positively linked with negative affect [56], expressive suppression [57], and neuroticism [36] as well as negatively with positive affect [56], cognitive reappraisal [57], and conscientiousness [6]. We therefore additionally considered general affect as measured with the Positive and Negative Affect Schedule [PANAS; 58], cognitive reappraisal and expressive suppression as measured with the Emotion Regulation Questionnaire [ERQ; 59] and finally, neuroticism and conscientiousness as measured with the Big Five Inventory-2 [BFI-2; 60].

Despite the extensive body of research examining achievement boredom in adolescents, it is still open to question whether experiencing intense boredom is similarly severe when students are low-achieving and when they are high-achieving. Therefore, we formulated the following exploratory research question: Do low-achieving students with high boredom systematically differ in their self-reported behaviors and personality traits from high-achieving students with high boredom? We propose that an answer to this question enhances the scientific understanding of achievement boredom and offers practical implications, especially with respect to potentially dealing differentially with students who are bored due to being over- vs. under-challenged.

Method

Sample

The sample consisted of N = 1.404 secondary school students from 103 classrooms of 25 schools (52% girls [n = 731], 47% boys [n = 661], 1% not indicated [n = 12]) from the Free State of Bavaria, Germany. Students were from all three tracks of the Bavarian three-track general secondary school system, with 47% (n = 662 students) from the upper (Gymnasium), 28% (n = 390) the middle (Realschule), and 25% (n = 349) the lower track (Mittelschule). This distribution across tracks is equivalent with the Bavarian secondary student statistics, with a slight overrepresentation of Gymnasium student population [61]. The students were in the fifth (n = 172), sixth (n = 197), seventh (n = 582), eighth (n = 291), ninth (n = 134), and 10th grade (n = 24) and were 9 to 17 years old, with a mean age of Mage = 12.83 years (SDage = 1.29). The vast majority of the students (92%, n = 1.287) was born in Germany while 18% of them had at least one foreign-born parent (nmother = 181, nfather = 177, nboth = 118).

The research was approved by Ludwig Maximilian University of Munich’s Ethics Review Board of the Faculty of Psychology and Education. Participation in the study was voluntary, written informed consent was obtained from all participants, parents or guardians respectively, and no identifiers that could link individual participants to their results were obtained.

Measures

The data reported here were assessed as part of a longer questionnaire which in total consisted of ten pages with open-ended and multiple-choice questions. External trained testing personnel brought the questionnaires to the schools and collected them a few weeks later. The questionnaire was filled out at home by the students and collected, inside sealed envelopes, in class by their mathematics teachers.

Boredom

Students’ class-related, habitual, trait-like boredom in mathematics was accessed using six items of the course-specific boredom scale of the Achievement Emotions Questionnaire—Mathematics [15,AEQ-M, 62]. In the AEQ, students are prompted to “Please indicate how you feel, typically, during math class”; a sample item is “I am so bored that I can’t stay awake” (see Table 1 for the full set of items used in this study in original German, and their English translation). Students responded using a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Table 1

Boredom items of the Achievement Emotions Questionnaire—Mathematics (AEQ-M).

Items German	Items English translation
Ich finde den Unterricht langweilig.	I think the mathematics class is boring.
Vor Langeweile schalte ich ab.	I can’t concentrate because I am so bored.
Vor Langeweile kann ich mich kaum wach halten.	I am so bored that I can’t stay awake.
Vor Langeweile gehen mir immer wieder Gedanken durch den Kopf, die mit Mathe nichts zu tun haben.	I think about what else I might be doing rather than sitting in this boring class.
Ich schaue ständig auf die Uhr, weil die Zeit nicht vergeht.	Because of time drags I frequently look at my watch.
Ich werde unruhig, weil ich nur darauf warte, dass die Mathestunde endlich vorüber ist.	I get restless because I can’t wait for the class to end.

Asking students to judge “Please indicate how you feel, typically, during math class.”

Achievement

Self-reported math grades from students’ last final report card were used as an indicator of achievement. The grades are summative scores based on multiple evaluations over the course of a school year and range from 6 (poor) to 1 (excellent).

Emotional and behavioral problems

The German version [SDQ-Deu-S; 63] of the one-sided self-report version [see 64] of the Strengths and Difficulties Questionnaire for 11–17 year-olds by Goodman [55] was used to measure emotional and behavioral problems. The items comprised of five subscales of five items each for emotional symptoms (e.g., “I worry a lot”), conduct problems (“I get very angry and often lose my temper”), hyperactivity (“I am restless, I cannot stay still for long”), peer problems (“I would rather be alone than with people of my age”), and prosocial behavior (“I am helpful if someone is hurt, upset or feeling ill”). Students were asked to judge these items on a scale from 1, not true, 2, somewhat true, to 3, certainly true.

Positive and negative affect

The German version by Krohne, Egloff, Kohlmann, and Tausch [65] of the Positive and Negative Affect Schedule [PANAS; 58] was used to determine students’ general affective states. This self-report scale consists of 10 positive (e.g., “excited”) and 10 negative adjectives (e.g., “upset”). Participants responded on a 5-point Likert scale ranging from 1 (not at all) to 5 (extremely) to describe their “general emotional state.”

Cognitive reappraisal and expressive suppression

The German version of the Emotion Regulation Questionnaire [see 59 for the English version,ERQ; 66] was used to measure the tendency to regulate emotions by cognitive reappraisal or expressive suppression. Participants had to rate four items on cognitive reappraisal (e.g., “When I’m faced with a stressful situation, I make myself think about it in a way that helps me stay calm”) and expressive suppression (e.g., “I keep my emotions to myself”) on a scale from 1 (not at all true) to 7 (completely true).

Conscientiousness and neuroticism

We considered two of the big five personality traits which have been reported to be systematically linked with boredom, namely conscientiousness, and neuroticism. While conscientiousness (e.g., “I am someone who is systematic, likes to keep things in order”) measures differences in organization, productiveness, and responsibility, neuroticism (e.g., “I am someone who tends to feel depressed, blue”) measures differences in the frequency and intensity of negative emotions [67]. We used the German version of the Big Five Inventory-2 for their assessment [see 60 for the English version,BFI-2; 68]. Students were asked to rate 12 items for each construct on a 5-point rating scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Data analyses

All analyses were conducted using R 3.6.1 [45]. The full analysis code is available from the Open Science Framework database (https://osf.io/zypae). To assess the internal consistency of the scales, the reliability coefficient Cronbach’s alpha (α) was calculated. As outlined in Table 2, AEQ-M boredom, PANAS positive and negative affect, and BFI-2 neuroticism and conscientiousness showed good reliabilities (α between .81 and .86). SDQ hyperactivity and prosocial behavior, ERQ cognitive reappraisal, and expressive suppression showed borderline-acceptable reliabilities, but SDQ conduct and peer problems showed low reliabilities (α between .47 and .53). However, earlier studies also documented comparably low internal consistencies for those SDQ subscales when using student ratings [69]. Therefore, this was not a peculiarity of our sample. To circumvent biased results due to scale unreliability, we chose to model all variables as latent constructs using the Lavaan 0.6–5 package [70] employing the full information likelihood method [FIML; 71] for treating missing data, and the MLR estimator (maximum likelihood estimation with robust (Huber-White) standard errors and a scaled test statistic that is (asymptotically) equal to the Yuan-Bentler test statistic).

Table 2

Means, standard deviations, and Cronbach’s alpha for the study scales.

Scale	Construct	M (SD)	Min.—Max.	α
AEQ-M	Boredom	2.39 (0.95)	1.00–5.00	.86
SDQ	Emotional symptoms	1.58 (.48)	1.00–3.00	.71
	Conduct problems	1.36 (.31)	1.00–3.00	.47
	Hyperactivity	1.73 (.45)	1.00–3.00	.68
	Peer problems	1.42 (.34)	1.00–3.00	.53
	Prosocial behavior	2.61 (.36)	1.00–3.00	.65
PANAS	Positive affect	3.53 (.62)	1.00–5.00	.80
	Negative affect	2.00 (.68)	1.00–4.80	.84
ERQ	Cognitive reappraisal	3.93 (1.25)	1.00–7.00	.68
	Expressive suppression	3.70 (1.25)	1.00–7.00	.60
BFI-2	Neuroticism	2.65 (.66)	1.00–5.00	.81
	Conscientiousness	3.40 (.67)	1.25–5.00	.82

1390 ≤ n ≤ 1404 due to missing values. α = Cronbach’s alpha.

We thus obtained latent correlations between boredom, emotional and behavioral problems, positive and negative affect, cognitive reappraisal, and expressive suppression, as well as neuroticism and conscientiousness based on structural equation modeling (SEM). To identify highly bored students, we obtained latent factor scores for each student for the six items of the AEQ-M boredom scale. In this context, we defined the high boredom group to include all students who scored higher than one standard deviation (SD = 0.7) above the standardized sample mean of zero on the AEQ-M boredom scale (n = 258). To compare across low- vs. high-achievers among these highly bored students, we used the final math grade of the previous school year as an indicator of achievement in math class. In this analysis, students with missing grades (n = 14) were excluded. Grades from 4 to 6 (4 = sufficient, 5 = poor, 6 = insufficient) were coded as 0 = low achievement and grades from 1 to 3 (1 = excellent, 2 = good, 3 = satisfactory) as 1 = high achievement (M = 3, SD = 0.9, Mdn = 4). As a result, there were 125 students in the low achievement group (boredom M = 3.98, SD = .53), and 119 students in the high achievement group (boredom M = 3.80, SD = .42). To account for multiple testing, we used the Bonferroni method to adjust the alpha level to 0.005.

Results

Preliminary analysis

Table 3 shows the latent correlations between students’ mathematics boredom and all other affective and behavioral constructs considered in this study, across the full sample. Boredom correlated significantly with all other constructs assessed. Strong relations were found for conduct problems and hyperactivity (r between .52 and .56), and medium-sized relations were found for emotional symptoms, positive and negative affect, and neuroticism and conscientiousness (r between -.45 and .45). Peer problems and prosocial behavior, as well as cognitive reappraisal and expressive suppression, showed small-sized links with mathematics boredom (r between -.29 and .13). The overall pattern of relationships was consistent with previous studies on boredom proneness in that higher levels of boredom in mathematics class were associated with higher levels of undesired behavioral and personality variables, and lower levels of desirable behavioral and personality variables.

Table 3

Behavior and personality: Latent correlations with boredom and comparison between bored low and high achievers.

				Manifest means
		Latent correlation with boredom		Low achievers	High achievers	Comparison of latent means
Scale	Construct	r	p	M (SD)	M (SD)	β	p	R2
SDQ	Emotional symptoms	.42	< .001	.90 (.52)	.79 (.53)	-.14	.067	.02
	Conduct problems	.52	< .001	.61 (.43)	.46 (.35)	-.23	.005	.05
	Hyperactivity	.56	< .001	1.07 (.46)	.99 (.49)	-.04	.555	< .00
	Peer problems	.25	< .001	.56 (.40)	.47 (.35)	-.17	.091	.03
	Prosocial behavior	-.29	< .001	1.48 (.42)	1.50 (.40)	.01	.874	< .00
PANAS	Positive affect	-.45	< .001	3.16 (.71)	3.40 (.62)	.20	.009	.04
	Negative affect	.40	< .001	2.40 (.67)	2.28 (.67)	-.12	.110	.01
ERQ	Cognitive reappraisal	-.12	.002	3.69 (1.35)	3.85 (1.16)	.12	.162	.01
	Expressive suppression	.13	.001	4.09 (1.32)	3.63 (1.26)	-.19	.041	.04
BFI-2	Neuroticism	.45	< .001	3.06 (.71)	2.91 (.64)	-.11	.199	.01
	Conscientiousness	-.44	< .001	3.02 (.67)	3.06 (.65)	-.02	.774	< .00

Bonferroni adjusted p-value < .005. R2 = coefficient of determination.

Group differences between low and high performers

Before comparing latent mean differences between low- and high-achieving students, we tested for measurement invariance of each of the latent constructs addressed in this study, using the SemTools 0.5–2 package [72]. This was to make sure that the latent scores used in the analysis were comparable across both groups. We sequentially tested for equivalence of model form (configural), equivalence of factor loadings (metric), and equivalence of item intercepts or thresholds [scalar; 73]. For comparing latent means across groups, scalar invariance is necessary [74]. We refrained from additionally testing for residual invariance, which is nugatory to the interpretation of latent mean differences [74]. As can be seen from S1 Table, scalar factorial invariance could indeed be accepted for all constructs except SDQ hyperactivity and peer problems. While hyperactivity showed metric invariance, peer problems only showed configural invariance, implying considerably different item functioning of those items for the low- as opposed to high-achieving bored students.

To investigate differences in behavioral and personality variables of highly bored students who are performing poorly vs. well in mathematics, we regressed the dichotomous variable achievement in mathematics (low vs. high) on all other constructs considered in this study, modeled as latent variables. The results (Table 3) revealed no group differences for any of the constructs. It is worth noting that those results proved to be fully robust when entering school type as dummy-coded control variables. In interpreting these results, differential item functioning for hyperactivity and peer problems must be taken into account.

Discussion

In the present study, we aimed to systematically compare students who are highly bored and low-achieving, i.e., likely over-challenged, with students who are highly bored and high-achievement, i.e., likely over-challenged. We argued that it remains open to question whether experiencing intense boredom is associated with similarly severe levels of undesirable correlates when students are low- vs. high-achieving. To this end, within the group of highly bored students in our sample, we compared across low-achieving and thus likely over-challenged, and high-achieving and thus likely under-challenged students.

As a preliminary analysis step, we examined correlates of students’ boredom in the context of mathematics, following up on previous research which has consistently reported that boredom has multiple undesirable correlates. Our results fully replicated earlier-reported patterns of relationships with undesirable boredom correlates. Specifically, we found again that student-reported experiences of boredom during mathematics classes is positively correlated with emotional and behavioral problems, negative affectivity, the use of expressive suppression to regulate emotions, and neuroticism. In contrast, students’ mathematics boredom proved to be negatively correlated with levels of prosocial behavior, positive affectivity, cognitive reappraisal, and conscientiousness.

Moreover, and most importantly, our results suggest that high boredom is associated with similar levels of problematic correlates in low- and high-achieving students. The two groups did not significantly differ in emotional symptoms, conduct problems, hyperactivity, peer problems, prosocial behavior, positive and negative affect, neuroticism, cognitive reappraisal and expressive suppression, neuroticism, and conscientiousness. In line with Pekrun’s [44,45] control-value theory of achievement emotions which posits that boredom can occur either when control is particularly high, or when it is particularly low, we find that both over- and under-challenge can lead to high boredom. Furthermore, irrespective of student’s performance, and hence irrespective of their subjective control in a certain domain, our study demonstrates that high boredom itself is associated with many of these problems. In sum, we propose that one important implication from our findings is that boredom is boredom–irrespective of its antecedents.

Limitations, suggestions for future research, and implications

By showing that bored low- and high-achievers show similar patterns in behavioral and personality variables, this study addresses a gap in boredom research and contributes to a better understanding of achievement boredom. However, the following limitations should be taken into account when interpreting our results and could be considered as directions for future research.

First of all, the present study relies on the reasoning that the combination of high boredom with good grades in mathematics implies that those students tend to be bored due to being under-challenged, while the combination of high boredom with poor grades implies that they tend to be over-challenged. It is important to note that this is an assumption, and the classification as over- vs. under-challenge may not have been fully valid for each individual student in the two groups. However, we deliberately chose to assess domain-specific boredom and domain-specific achievement separately, to first identify students with very high boredom, and then classify boredom as likely being due to over- vs. under-challenge based on students’ achievement. While this indirect approach to assess over- and under-challenge may be a point of debate, we also deem more direct self-report assessments (e.g., ‘I am bored because it's too easy’) as psychometrically problematic. Items combining reports of boredom with attributions of boredom are double-barreled and thus ambiguous–it is unclear if students who endorse those items do so because they are bored, or because they find the material easy vs. hard, or because they attribute boredom to over- or under-challenge.

Moreover, our study was conducted in math class at secondary schools in Germany. To generalize our findings, future research should consider problematic correlates of intense boredom in high- and low-achievers in other relevant contexts like elementary schools, universities, or the workplace; in domains other than mathematics; and in other cultures.

With almost 20% (n = 256) of the students in our sample indicated to be severely bored in math class, this study suggests again that no student should be left alone to endure the “torments of boredom” [75]. Given that students almost exclusively use avoidance-oriented coping strategies to deal with their boredom [76], boredom should be openly discussed in class, and more promising coping strategies such as cognitive- and behavioral-approach strategies should be addressed [77].

One of the most reported reasons for boredom is low-quality instructional design [78]. An adaptive and individualized learning environment might, therefore, contribute to preventing boredom due to being both over- or under-challenged. Most importantly, teachers, parents, and students should be aware that boredom in school needs to be taken seriously. Boredom can indicate severe problems not just in the sense of a student being lazy, too bright, over-challenged, or under-challenged, but can constitute a debilitating personality trait.

Chi-Squared difference test for the nested model comparison.

Total N = 244; group 1 n = 125; group 2 n = 119. M1: Configural invariance. M2: Metric invariance. M3: Scalar invariance. ** p ≤ .01.

(PDF)

Click here for additional data file.

1 Sep 2020

PONE-D-20-20833

Excessive boredom among adolescents: A comparison between low and high achievers

PLOS ONE

Dear Dr. Goetz,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Oct 16 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Frantisek Sudzina

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. You indicated that you had ethical approval for your study. In your Methods section, please ensure you have also stated whether you obtained consent from parents or guardians of the minors included in the study or whether the research ethics committee or IRB specifically waived the need for their consent

3. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Review PONE-D-20-20833

Excessive boredom among adolescents: A comparison between low and high achievers

The authors ask an interesting and important question about boredom in high versus low achieving students. The sample and analysis procedures were adequate to answer the research question. The results provide further insight into students’ experiences of boredom as a negative and persistent emotion.

Page 1 “Are undesirable correlates of boredom augmented” – augmented might not be the right word choice. Maybe exacerbated? Or even just simply “worse”.

In the first paragraph, reduce the use of parentheses and add the i.e., likely over/under challenged to the main sentences because it is important content. Same in later parts of the manuscript. (thus likely over/under-challenged) should be part of the sentence.

The literature review is concise, to the point, and up-to-date. However, it would be helpful to add some more details on the “correlates” of boredom rather than using this as a general descriptor. In particular, what is the current evidence on boredom and behavioral and personality variables? This content should go before “The present study” section rather than having little bits of it in that section (e.g., references 23-35).

Please check the phrase “scholastic boredom” for accuracy. I think you just mean achievement boredom?

Only 258 of the original 1404 had high boredom? This seems quite small given the introduction puts the prevalence of boredom as 30-40%. This should be discussed maybe as a limitation or direction for future research differently than it is currently done because of its mismatch with current numbers. Also in the limitations section the n=271. Please check for accuracy between the two sections.

The discussion is appropriate and does not over generalize. However, it is a bit short. Can you please add some implications for the control-value theory especially because researchers in the area constantly have to manage the “boredom by over or under challenge” critique. I think this paper helps those researchers say that it doesn’t really matter – boredom is boredom.

Reviewer #2: In the study, pupils in fifth to tenth grades who were very bored and high-achieving in mathematics were compared with students who are very bored and low-achieving in mathematics. Comparisons were made regarding different behavioral and personality variables. Results show that there are no mean-level differences across the two groups for the investigated variables with three exceptions: Conduct problems and expressive suppression were higher for very bored low achievers and positive affect was higher for very bored high achievers.

The manuscript is well written; the research questions are interesting; and the methods and data analyses are adequate. Below I list some issues that could be addressed to improve the manuscript:

1) The use of terms and the categorization of the variables under consideration varies within the manuscript, sometimes considerably. In the abstract, the authors mention that behavior and personality aspects will be considered, but in the manuscript other super-categories are often used (e.g., on p. 8: emotional and behavioral problems, positive and negative affect, emotion regulation strategies, personality traits; on p. 13: behavioral and affective variables; Table 3: emotional symptoms). A standardization of categories and terms across the entire manuscript would strengthen the manuscript and help readers to follow the authors.

2) Moreover, the authors should consider providing a somewhat more detailed justification for the selection of the variables they consider.

3) A main problem of the study is the way in which the groups of high achievers and low achievers are defined. With a grading system from 1 to 6, it seems questionable whether students with average grades of 3 and 4 can actually be described as high achievers and low achievers respectively. It would be advantageous to exclude the group whose grade averages are in the middle of the applicable grading scale. It can be assumed that the students with 3s and 4s suffer less from boredom due to being overchallenged (i.e., the students with grade averages of a 4) or underchallenged (i.e., the students with grade averages of a 3) than students who actually perform particularly well or particularly poorly, especially since we know that classroom instruction is normally adapted to the needs of average-performing students. A comparison of the two ‘fringe groups’ (possibly using non-parametric tests) therefore seems a more germane approach to answer the question the authors are posing.

4) A discussion of the differences between school types would be important. Very bored low achievers in the low-achiever track of secondary school might differ from very bored low achievers in the high-achiever track of secondary school. Differences between the tracks could be analyzed or analyses could be controlled for school type.

5) At some points in the discussion the conclusions should be softened somewhat. For example, it cannot be clearly concluded from the results that boredom itself is associated with many problems regardless of scholastic performance, or that the situation seems to be even more dramatic for low-achieving students.

6) Minor issue: On page 10, the authors write that SDQ conduct and peer problems showed low reliabilities (alpha between .47 and .71). The second value does not match the value in Table 2 (and is not small).

Reviewer #3: Thank you for offering me the chance to review this paper. Overall, I liked the paper and I think it provides a new element to the research on academic boredom. The analyses are not complex but nonetheless adequate and done in an advanced way (e.g. latent construct correlations). It should be noted that the current study uses cross-sectional data only and that it relies on self-reported data as far as I could see.

General questions I had during reading the paper were:

While boredom was assessed specifically for the math class, the other measures seem to be of a more general nature. It seems like more general personal characteristics are thus inter-mixed with math-specific ones. How does this affect the conclusions that can be drawn?

Can there a stronger case be made regarding the degree to which the two selected groups are actually over/under challenged?

More specific questions/comments per section were:

Abstract

-Are you also referring to undesirable personality traits?

-Could replace ‘no study to date…’ with ‘merely knowing that student are highly bored’

Introduction

-the framing at the start of the paper could be geared somewhat more towards the Edu context.

-it is not entirely clear what ‘it’ refers to in the 5th sentence (…whether it is similarly…)

-I would suggest summarizing the theoretical and practical relevance explicitly and right away in the first para – ideally beyond ‘this has not been done before’… Also see ‘the present study’. Now the opening reads a bit anecdotical?

-p4 second para: I would like to propose to delete statements like ‘this has not been done before’ but rather explain what we can gain from investigating these things. Why is it important to know whether or not the same correlates exist for the two groups of students? Also, I do not see why conscientiousness would protect one from being bored? Conscientiousness could even strengthen feelings of being underchallenged? In sum, I think providing a stronger and more coherent rational for doing this investigation is needed.

Method

-the effective sample-size is 245 for the analysis of the main research question, this should be stated more explicitly, probably also in the abstract. There, only an N of 1404 students is mentioned describing the entire pool of students, which may raise wrong expectations. Alternatively, a more broad/general research question could be added?

-I wonder whether students of 9 year old can reliably answer questionnaires like the ERQ?

-Achievement: I suppose grades were self-reported? Please clarify in the paper.

-please explain how the chosen analyses can account for reliabilities low as .47/.53? It would probably have been more straight forward to leave these scales out of the analyses?

-please add the mean levels of boredom in the two groups that are created (or have I overlooked this?).

-How fair is it to consider these groups to be over-/under challenged? Is there something more that can be done to show this?

Analyses

-Wouldn’t it be more fitting to test interaction terms with low/high achievement and boredom?

-in any case: have you considered to correct the alpha levels for repeated testing?

Discussion

-I think the authors rightly conclude that it is in first place boredom as such rather than the combination with achievement that correlates with problematic student characteristics aso. Therefore, it may be a little overstated (especially given the very low R2s) that the situation is ‘more dramatic’ for low achievers.

-conduct problems had measurement issues, this should be mentioned along with the conclusions. Maybe it should receive a little less attention in the conclusions as well?

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Lia M Daniels

Reviewer #2: No

Reviewer #3: Yes: Tim Mainhard

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

16 Oct 2020

See attached document.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

20 Oct 2020

Excessive boredom among adolescents: A comparison between low and high achievers

PONE-D-20-20833R1

Dear Dr. Goetz,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Frantisek Sudzina

Academic Editor

PLOS ONE

28 Oct 2020

PONE-D-20-20833R1

Excessive boredom among adolescents: A comparison between low and high achievers

Dear Dr. Goetz:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Frantisek Sudzina

Academic Editor

PLOS ONE