Participants, procedure, and ethical concerns
The study was part of an ongoing longitudinal project assessing problematic internet-related behaviors among primary school children. This research was approved by the ethics committee of the Hong Kong Polytechnic University (IRB ref: HSEARS20190718001). The longitudinal project routinely assesses primary school children’s characteristics, problematic internet-related behaviors (smartphone applications, social media, and gaming), perceived weight stigma, and psychological distress across a one-year period. During the period of the longitudinal project, the COVID-19 outbreak occurred in mainland China and the primary schoolchildren were instructed to stay at home for online learning. Consequently, an item on fear of COVID-19 infection was incorporated into the longitudinal project (see Instruments section for details) to assess the extent of children’s fear related to COVID-19. The present study was cross-sectional, with questionnaire data from the same wave that included the COVID-19 question analyzed.
The survey was conducted online with the distribution of the survey facilitated by teachers from three primary schools in Sichuan, China. The online survey was generated by the research team and checked by the teachers to ensure that the survey hyperlink worked. Schoolteachers then sent the hyperlink to their students for participation. The first page of the online survey stated the objectives and participants’ rights, and sought consent from the students and one parent. Following the provision of participation consent from students and one of their parents, access to the survey proper was opened. Eligibility of the primary schoolchildren was defined the following inclusion criteria (i) they could read and understand the survey, which was written in Chinese and (ii) they owned and used at least one smartphone with internet access. The participants were excluded if they misperceived their weight status; that is, their perceived weight status did not fit with their body mass index (BMI) defined weight status. The reason for the exclusion criterion is because prior research shows that misperception of weight status is a strong predictor of children’s psychological distress, and we did not wish for this association to confound the present study.12-14
Measures
Fear of COVID-19 infection. Using a visual analogue scale (from 0 [not at all afraid] to 10 [completely afraid]), a question “Are you afraid of being infected by COVID-19?” was used to understand to what extent participants fear the COVID-19 infection.
Depression, Anxiety, Stress Scale-21 (DASS-21). Using 21 items rated on a 4-point Likert scale (ranging from 0 [did not apply to me at all] to 3 [applied to me very much or most of the time]), the DASS-21 assesses three types of psychological distress: stress (7 items), anxiety (7 items), and depression (7 items). Example items for the DASS-21 are “I found it hard to wind down” (for stress), “I was aware of dryness of my mouth” (for anxiety), and “I could not seem to experience any positive feeling at all” (for depression). The item scores are summated in each subscale to indicate the level of psychological distress, where higher scores indicate a higher level of depression, anxiety, or stress. The psychometric properties of the DASS-21 and the Chinese DASS-21 have been found to be good.15,16 The present study found that the Chinese DASS-21 had good internal consistency (α = 0.82 for stress subscale; 0.79 for anxiety subscale; and 0.84 for depression subscale).
Perceived weight stigma. A 10-item measure was used to assess perceived weight stigma. Participants responded to items such as “people act as if you are inferior because of your weight” using a dichotomous scale (0 = No and 1 = Yes). Item scores were summated to indicate the level of perceived weight stigma (scores ranging from 0-10), with higher scores indicating a higher level of perceived weight stigma. The linguistic validity and internal consistency of the Chinese perceived weight stigma items have been found to be satisfactory.17 The present study also showed that the Chinese perceived weight stigma items had good internal consistency (α = 0.83).
Smartphone Application-Based Addiction Scale (SABAS). The six-item SABAS was used to assess level of problematic smartphone application use. The SABAS was designed based on the addiction component model criteria (i.e., salience, mood modification, tolerance, withdrawal conflict and relapse) proposed by Griffiths.18,19 Participants responded to items such as “During the past week, my smartphone is the most important thing in my life” using a Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree). The item scores are summed to indicate the level of problematic smartphone application use, where a higher score indicates a higher level of problematic use. The psychometric properties of the SABAS and the Chinese SABAS have been found to be satisfactory.20-24 The present study also showed that the Chinese SABAS had good internal consistency (α = 0.88).
Bergen Social Media Addiction Scale (BSMAS). The BSMAS assesses the level of problematic social media use with six items rated on a 5-point Likert scale ranging from 1 (very rarely) to 5 (very often). The scale was developed based on the addiction component model criteria proposed by Griffiths.18,19 The following is an example item from the BSMAS “How often during the last week have you spent a lot of time thinking about social media or planned use of social media?”. Item scores are summated to indicate the level of problematic social media use, where a higher score indicate a higher level of problematic use. The psychometric properties of the BSMAS and Chinese BSMAS have been found to be satisfactory.25-28 The present study also showed that the Chinese BSMAS had good internal consistency (α = 0.88).
Internet Gaming Disorder Scale-Short Form (IGDS9-SF). The nine-item IGDS9-SF assesses the level of disordered internet gaming behavior. The scale items were designed based on the nine criteria indicating internet gaming disorder [IGD] in the Diagnostic and statistical manual of mental disorders, fifth edition (DSM-5).29 Items such as “During last week, do you feel more irritability, anxiety or even sadness when you try to either reduce or stop your gaming activity?” were presented to participants who responded using a 5-point Likert scale ranging from 1 (never) to 5 (very often). The item scores are summed to indicate the level of problematic gaming, where higher scores indicating higher levels of problematic gaming. The psychometric properties of the IGDS9-SF have been found to be good.30-36 The present study also showed that the Chinese IGDS9-SF had good internal consistency (α = 0.926).
Time spent on internet-related behaviors. Time spent on internet-related behaviors was assessed with the question: “How much time did you spend on each of the following internet-related behaviors daily?”. Participants were asked to indicate time spent on each of the following internet-related behaviors in the past week: smartphone, social media, and gaming. The time spent on each internet-related behavior was then converted into hours per day in use.
Weight status. The schoolchildren self-reported their height in cm and weight in kg. BMI was then calculated to determine whether a schoolchild belongs to a group with overweight or a group without overweight.37 In addition to reporting height and weight, each schoolchild was asked to report their self-perceived weight status using the question: “What do you think your weight status is?” Answer choices included “Very thin”, “Thin”, “Normal weight”, “Overweight” , or “Obese”. Then, the self-perceived weight status was reclassified into two categories of “overweight” or “nonoverweight”.
Data analysis
Independent t-tests were used to detect the significant differences between the group with overweight and that without overweight in their psychological distress, perceived weight stigma, problematic internet-related behaviors, and time spent on internet-related behaviors. In addition, multivariate linear regression models were used to examine the associations between psychological distress (i.e., fear of COVID-19 infection, stress, anxiety, and depression), perceived weight stigma, and problematic internet-related behaviors (including problematic smartphone application use, problematic social media use, and problematic gaming). We divided the participants into two groups (participants with overweight and without overweight) to conduct the regression models for each group. Age and gender were adjusted in all the regression models. Moreover, a regression model using all participants (i.e., including those with and without overweight) was used to examine the associations between weight status, psychological distress, perceived weight stigma, and problematic internet-related behaviors.