3.1 Participants
To obtain a representative sample, we used the sample service provided by the Questionnaire Star platform, which enrolled participants based on age and location. A total of 326 junior and senior middle school students, all Chinese native speakers from 13 provinces and regions in China, took part in our online questionnaire survey.
The survey was launched on January 16th 2022 (the winter holiday started on January 9th 2022) and closed on January 22nd 2022. We excluded three participants from our analysis due to inconsistent responses regarding age (they wrote their name or grade for age information). Therefore, the final sample comprised 323 participants. More details can be found in Table 1.
3.2 Measures (see Appendix)
Academic Procrastination Questionnaire for Chinese middle school students (APQC)
APQC (in the Chinese language) was adapted from the Procrastination Scale developed by Tuckman (1991). APQC consists of 20 items, covering homework procrastination, self-study procrastination, and exam-preparation procrastination (Xu & Wang, 2011). Each item is rated on a five-point Likert scale ranging from “never” (1) to “always” (5). The higher the score is, the more serious the procrastination is. Its reliability is high in Chinese middle school students (α=.90, Li & Lv, 2022).
Chinese version of Adolescent Time Attitude Scale (CATAS)
CATAS is the Chinese version of Adolescent Time Attitude Scale (Mello & Worrell, 2007). It consists of 30 items with five items for each dimension of time attitude: past positive, past negative, present positive, present negative, future positive, and future negative (Li, Mao, Lv & Wang, 2021). Each item is rated on a five-point Likert scale ranging from “completely agree” (1) to “completely disagree” (5). Its reliability in Chinese high school and college students ranged from 0.77 to 0.86 (Li, Mao, Lv & Wang, 2021).
Chinese version of the Brief Self Control Measure (CBSC)
CBSC is the Chinese version of the Brief Self Control Measure developed by Tangney, Baumeister and Boone (2004). It consists of 16 items, covering impulsion control, health habit, temptation resistance, concentration, and recreational control. Each item is rated on a five-point Likert scale ranging from “completely not applicable to me” (1) to “completely applicable to me” (5). Its reliability in Chinese college students is 0.85 (Tan & Guo, 2008).
In addition, we collected participants’ demographic information of age, gender, education level, location and whether they were to have make-up exams for the final exams.
3.3 Results and Discussion
All data were analyzed using IBM SPSS Statistics 25. First, the data were divided into four parts: demographic information, academic procrastination, time attitude, and self-control. Next, Cronbach’s α, mean (M), standard deviation (SD) and correlations were calculated among the four variables. Then, we used Hayes (2013) SPSS macro PROCESS (Model 4) based on a 5000 bootstrap to check the mediating role of self-control in the relationship between academic procrastination and time attitude.
3.3.1 Demographic Information
Table 1 contains the demographic information of all participants. Of them, 178 (55.11%) were female and aged between 12 and 19 years (M=15.31, SD=2.89). 175 (54.18%) of them were junior middle school students. They originated in three different regions of China: the south-east (133, 41.18%), the centre (67, 20.74%), and the north-west (123, 38.08%). 253 of them (78.33%) said they had to take make-up exams.
Table 1 Demographic Information
Age
|
Range
|
12-19
|
Mean
|
15.31 (SD=2.89)
|
|
|
Number
|
Percentage (%)
|
Gender
|
Male
|
145
|
44.89
|
Female
|
178
|
55.11
|
Education level
|
Junior Middle Schools
|
175
|
54.18
|
Senior Middle Schools
|
148
|
45.82
|
Location
|
South-east
|
133
|
41.18
|
Central
|
67
|
20.74
|
North-west
|
123
|
38.08
|
Whether make-up exams are needed
|
Yes
|
253
|
78.33
|
No
|
70
|
21.67
|
3.3.2 Descriptive Statistics and Correlations among variables
Table 2 presents the descriptive statistics and correlations among variables. It shows that self-control negatively correlates with procrastination at a significant level (r = -.53, p < .01), and positively correlates with future positive time attitude (r = .21, p < .05), present positive time attitude (r = .22, p < .05), and past positive time attitude (r = .27, p < .05) at a significant level. This is in line with previous findings that stronger self-control decreases the risk of procrastination (Kim et al., 2017; Tuckman, 1998) and that higher scores on self-control correlate with more optimal emotional responses (Tangney, Baumeister & Boone, 2004). However, no significant correlation was detected between academic procrastination and all six dimensions of time attitude. This partially contradicts the existing finding that a positive future time attitude is negatively correlated with procrastination (Kim et al., 2017; McKay et al., 2016; Worrell et al., 2013).
Table 2 Correlations among variables (CI=95%)
|
M
|
SD
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
1 self-control
|
3.01
|
0.49
|
1
|
|
|
|
|
|
|
|
2 procrastination
|
2.60
|
0.43
|
-.53**
|
1
|
|
|
|
|
|
|
3 future positive
|
2.16
|
0.77
|
.21*
|
.19
|
1
|
|
|
|
|
|
4 future negative
|
3.54
|
0.84
|
.16
|
.03
|
-.29*
|
1
|
|
|
|
|
5 present positive
|
2.53
|
0.70
|
.22*
|
.18
|
.75**
|
-.11
|
1
|
|
|
|
6 present negative
|
3.13
|
0.70
|
.22
|
.17
|
-.20
|
.75*
|
-.18
|
1
|
|
|
7 past positive
|
2.42
|
0.67
|
.27*
|
.14
|
.65**
|
-.16
|
.60**
|
-.07
|
1
|
|
8 past negative
|
3.25
|
0.87
|
.85
|
-.05
|
-.02
|
.57**
|
-.03
|
.50**
|
-.25*
|
1
|
(** means p < .01, * means p < .05)
3.3.3 The Mediating Effect
SPSS macro PROCESS (Model 4) developed by Hayes (2013) was used to check the mediating role of self-control in the relationship between academic procrastination and time attitude (based on a 5000 bootstrap). The results are presented in Table 3. It indicates that self-control significantly mediates the relationship between future positive time attitude and academic procrastination, 95% CI = [0.2914, 0.6225] (p < 0.05), and past positive time attitude and academic procrastination, 95% CI = [0.3019, 0.6370] (p < 0.05), but marginally mediates the relationship between present positive time attitude and academic procrastination, 95% CI = [-0.0050, 0.2195] (p = 0.06). There is no mediating effect of self-control between all the negative time attitudes and academic procrastination. This partially aligns with our expectation that self-control mediates between time attitude and academic procrastination. Nevertheless, the results primarily rely on self-reported measures. To increase the validity of our findings, we used a behaviour measure to obtain data on students’ procrastination in real settings. The details are reported in Section 4.
Table 3 The Mediating Effect
|
β
|
t
|
R2
|
95% CI
|
FP-SC-Pro
|
0.07
|
2.00
|
0.03
|
0.2914, 0.6225
|
FN-SC-Pro
|
0.04
|
1.42
|
-0.00
|
-0.0635, 0.0361
|
PP-SC-Pro
|
0.07
|
1.87
|
0.03
|
-0.0050, 0.2195
|
PN-SC-Pro
|
0.07
|
1.88
|
0.03
|
-0.0102, 0.1817
|
PAP-SC-Pro
|
0.09
|
2.27
|
0.03
|
0.3019, 0.6370
|
PAN-SC-Pro
|
0.01
|
0.19
|
-0.00
|
-0.0656, 0.0245
|
(FP=future positive, SC=self-control, Pro=procrastination, FN=future negative, PP=present positive, PN=present negative, PAP=past positive, PAN=past negative)