Media multitasking, negative mood, and avoidance coping

ABSTRACT

Media multitasking is a prevalent phenomenon especially among adolescents and young adults. This study explored the possibility that media multitasking is used as an avoidance coping strategy against stress. If so, media multitasking behaviour could be monitored to detect symptoms of anxiety and depression. Across three experiments, participants completed measures of media multitasking, anxiety, depression, and cognitive behavioural avoidance. In each of the three experiments, participants also completed an attentional bias task (a dot probe task using emotionally negative and neutral stimuli). Media multitasking was associated with negative emotions, such as (social/trait) anxiety, depression, and cognitive behavioural avoidance. However, attentional avoidance was not linked to media multitasking, negative mood, or behavioural avoidance. Taken together, the results provide preliminary evidence that media multitasking is associated with negative emotions and behavioural avoidance, but not with an attentional avoidance of emotionally negative stimuli. The finding suggests that media multitasking behaviour may be used to help detect anxiety and depression, and treating these mental health disorders could include exploring the relationships between media multitasking, negative emotions, and avoidance coping.

KEYWORDS:

• Media multitasking
• anxiety
• depression
• attentional bias
• avoidance
• coping

1. Introduction

With an increased accessibility to portable devices, media consumption is ubiquitous. Frequent multitasking with media (known as media multitasking, e.g. constantly checking updates on social media while working or studying) is prevalent in everyday life, especially among adolescents and young adults. Eleven-to-fourteen year-olds spend about 9 h each day consuming media and about 30% of that time is spent on media multitasking (Rideout, Foehr, and Roberts 2010). However, frequent media multitasking has been linked to anxiety and depression (Becker, Alzahabi, and Hopwood 2013).

The Interaction of Person-Affect-Cognition-Execution (I-PACE) model (Brand et al. 2016) suggests that high levels of negative mood such as stress or anxiety may motivate individuals to pursue immediate relief/rewards and engage in reactive decision-making (e.g. checking social media while studying or working), to cope with the negative emotion. Thus, media multitasking may be used as a coping strategy to temporarily alleviate negative emotions. Nevertheless, this type of avoidance or distraction coping is often maladaptive as it prevents individuals from taking the necessary action to produce a positive outcome and further increases negative emotions (Lazarus 1998). If media multitasking is indeed used as an avoidance coping strategy, efforts need to be put into breaking the vicious cycle in which avoidance coping further increases negative emotions.

Selectively directing attention toward or away from threat-related stimuli (i.e. attentional bias) can serve a self-regulatory function by increasing or minimising the impact of negative information (Hock 1993). Individuals who experience anxiety exhibit an attentional bias toward negative information (MacLeod, Mathews, and Tata 1986) and this hypervigilance toward negative stimuli could exacerbate anxiety symptoms (Mogg et al. 1993). However, Matthews and Wells (2000) suggest that selective attention can be used as an avoidance coping strategy to manage the experience of negative stimuli. For example, an individual may choose to keep their attention away from negative stimuli to disrupt the processing of these stimuli and lower negative affect (Mogg et al. 2004). Alternatively, attention may initially be directed toward negative stimuli, and then diverted away from these stimuli to inhibit their further processing (Luecken, Tartaro, and Appelhans 2004). This link between avoidance coping and attentional avoidance of negative stimuli is particularly interesting because the motivation to keep attention away from negative stimuli (i.e. attentional avoidance) may be part of the avoidance coping that accompanies media multitasking behaviour during feelings of anxiety and depression.

The present study examined whether media multitasking is linked to an avoidance coping strategy to deal with negative emotions. In three experiments, participants were asked about their media multitasking use, feelings of anxiety and depression, and general tendency to avoid emotionally stressful events. In addition, to examine attentional avoidance of emotionally negative stimuli, participants completed a dot probe task in each of the three experiments. Across the three experiments, we systematically varied the presentation duration of emotionally negative stimuli from 150 ms to 1250 ms (Koster et al. 2006; Mogg et al. 2004) to detect an attentional avoidance of the negative stimuli (see Table 1 for an overview of the measures used in the three experiments).

Table 1. Overview of the Measures Used in Experiments 1–3.

Variable	Experiment 1	Experiment 2	Experiment 3
Media multitasking	Media use questionnaire	Media use questionnaire	Media use questionnaire
Mental health	State-Trait Anxiety Inventory	State-Trait Anxiety Inventory	Mini-SPIN, Patient Health Questionnaire-9
Avoidance	Miller Behavioural Style Scale	Cognitive Behavioural Avoidance Scale
Attentional avoidance	Dot probe task (negative and neutral words)	Dot probe task (negative and neutral words)	Dot probe task (negative and neutral faces)

2. Experiment 1

2.1. Method

2.1.1. Participants

One hundred and thirty-eight volunteers (105 females) aged 18–54 years (M = 28.33, SD = 9.62) took part in the study. The sample size was determined using G*Power to detect an effect size (Cohen’s f) of 0.25 at a 5% significance level with 80% power. Participants were recruited using a study advertisement on social media (N = 58) and the undergraduate research participation system (N = 80) at Charles Sturt University between May and July, 2019. Participants completed the study online at a time that was convenient for them via a web link embedded in the study advertisement. Undergraduate students received course credit for participating. Participants recruited via social media did not receive any reimbursement. All procedures were approved by the Charles Sturt University ethics committee.

2.1.2. Materials

Media use questionnaire. A variation of the media use questionnaire (Ophir, Nass, and Wagner 2009) modified by Ralph et al. (2018) was used in this study. The questionnaire surveys a range of media multitasking scenarios consisting of face-to-face interaction, print media, instant messaging/emailing/texting, social media sites, non-social text-orientated sites, telephone/video chatting, music, television/movies/YouTube, video games/online games, homework/studying/writing papers, and face-to-face interaction with a second individual. Participants indicated their average use of each media form and what percentage of that time (if any) was spent using a different media form at the same time. A media multitasking index (MMI) score was calculated using the formula of Ophir, Nass, and Wagner (2009). The mean MMI score was 1.76, with a standard deviation of 1.10.

State-Trait Anxiety Inventory (STAI). The State-Trait Anxiety Inventory (Spielberger et al. 1983) is a self-report measure of trait and state anxiety. The current study used only the trait inventory as media multitasking is associated with anxiety that is constant in daily life (Becker, Alzahabi, and Hopwood 2013). The trait inventory consists of 20 items assessing trait anxiety. The items include ‘I worry too much over something that really doesn’t matter’ and reverse scored items such as ‘I am content’ and ‘I am a steady person’. All items are rated on a 4-point scale ranging from 1 = Almost Never to 4 = Almost Always. Possible scores range from 20 to 80, with a higher score indicating greater anxiety. Cronbach’s alpha of the current sample was .94. The mean trait anxiety score was 43.7, with a standard deviation of 11.3. Of the 138 participants, 69% reported moderate to high anxiety (38–80).

Miller Behavioural Style Scale (MBSS). The Miller Behavioural Style Scale (Miller 1987) assesses an individual’s tendency to either seek out or avoid information regarding a threatening event. The MBSS consists of four scenarios: dental work, a terrorist hostage situation, unemployment, and a plane failure mid-air. Each scenario is followed by eight potential responses: four describe attention seeking or monitoring behaviour (e.g. ‘I would talk to my fellow workers to see if they knew anything about the supervisor’s evaluation of me’); the other four are blunting or avoidant responses (e.g. ‘I would push all thoughts of being laid off out of my mind’). A final score is calculated by subtracting the number of blunting responses from the monitoring responses. This questionnaire has been used extensively in the coping literature to investigate responses to experiences of real-life negative events, such as chronic pain (Litt, Shafer, and Kreutzer 2010), dental fear (Muris et al. 1996), and cancer (Rees and Bath 2000). The mean monitoring, blunting, and overall monitor-blunting scores were 9.1 (SD = 3.3), 3.2 (SD = 2.0), and 5.9 (SD = 3.7), respectively.

Dot probe task. The dot probe task is a well-known paradigm used to evaluate attentional biases (MacLeod, Mathews, and Tata 1986). The task was presented using Inquisit Web by Millisecond (millisecond.com). Participants were presented with a pair of words (taken from MacLeod et al. 2002), one negative and the other neutral, with one word displayed above the other (see Figure 1). The presentation duration of the words was either 250 ms or 1000 ms. The words were then replaced by a dot. Participants were asked to press the ‘k’ key if the dot appeared above the fixation cross and the ‘m’ key if it appeared below the fixation cross. There were 10 practice trials followed by 96 task trials, 48 trials where the dot followed the anxiety words and 48 trials where the dot followed the neutral words. The location of the words (anxiety, neutral), dots (top, bottom), and presentation duration of the words (250 , 1000 ms) were counterbalanced across trials. Intertrial intervals varied randomly between 500 and 1000 ms. An attentional bias score was calculated as the dependent variable by subtracting mean reaction times for responses to dots that replaced negative words from responses to dots that replaced neutral words (e.g. neutral word reaction times – negative word reaction times).

Figure 1. An example of a trial from the dot probe task. At the beginning of each trial, participants were presented with a fixation for 500 ms, followed by a negative word and a neutral word for either 250 ms or 1000 ms. The words were then replaced by a dot. If the dot appeared above the fixation, the participants responded by pressing the ‘k’ key. If the dot appeared below the fixation, they responded by pressing the ‘m’ key.

Procedure. After giving informed consent, all participants completed demographic questions (i.e. age and gender), the media use questionnaire, the State-Trait Anxiety Inventory, the MBSS, and the dot probe task. The entire experiment took no more than 40 min.

Data analysis. Pearson correlations were performed to investigate the relationships between media multitasking, anxiety, avoidance coping, and attentional bias. To test whether the I-PACE model (Brand et al. 2016) applies to media multitasking, we conducted moderated regression analyses to examine whether avoidance coping style moderates the relationship between media multitasking and anxiety, and the relationship between attentional bias and anxiety.

2.2. Results

2.2.1. Data preparation

Participants with an average accuracy level lower than 70% on the dot probe task were removed (17.9%; Mogg et al. 1997). In addition, reaction times greater than 1000 ms were removed (2.0%, approximately 2SD above the sample mean; Mogg et al. 2004).

2.2.2. Sample characteristics

Media multitasking was significantly correlated with trait anxiety, r(136) =  .225, p =  .008. Trait anxiety was also significantly correlated with monitoring, r(136) =  .323, p< .001, and the overall the monitoring-blunting score, r(136) =  .307, p< .001, but not with blunting, r(136) =  -.032, p =  .261. Unexpectedly, media multitasking did not correlate with any of the monitoring-blunting measures: monitoring, r(136) =  .123, p =  .151, blunting, r(136) =  .025, p =  .773, or the overall monitoring-blunting score, r(136) =  .096, p =  .261. Media multitasking was significantly correlated with age, r(136) = -.415, p<.001.

2.2.3. Attentional bias

Attentional bias scores at 250 and 1000 ms are shown in Table 2. There were no significant correlations between media multitasking and attentional bias at either stimulus presentation durations: 250 ms, r(136) =  -.081, p =  .347; 1000 ms, r(136) =  -.064, p =  .455. Nor were there significant correlations between trait anxiety and attentional bias, all ps> .322. Attentional bias at 250 ms correlated with the overall monitor-blunting score, r(136) =  .170, p =  .046, and the monitoring score, r(136) =  .179, p =  .035, but not with the blunting score, r(136) =  -.018, p =  .835. Attentional bias at 1000 ms did not correlate with any of the monitoring-blunting measures, all ps> .545.

Table 2. Attentional Bias at Stimulus Presentation Durations of 250 ms and 1000ms.

	250ms		1000ms
	Negative	Neutral	Negative	Neutral
Reaction times (ms)	510.4 (81.6)	513.9 (84.4)	512.2 (79.0)	512.7 (44.8)
Attentional bias (ms)	3.5 (44.8)		0.5 (34.3)

2.2.4. Moderating role of monitoring-blunting coping style

A series of moderated regression analyses examined whether a monitoring-blunting coping style moderated the relationship between media multitasking and trait anxiety, and the relationship between attentional bias and trait anxiety. Media multitasking and attentional bias scores at 250 and 1000 ms were, in turn, entered as the dependent variable. Trait anxiety and monitoring-blunting coping score were entered in Step 1. The interaction term between trait anxiety and monitoring-blunting coping score was added in Step 2. The model with media multitasking as the dependent variable was significant, R²=  .037, F(3,134) =  2.7, p =  .046, but only trait anxiety significantly predicted the dependent variable, B =  .024, p =  .013. In contrast, the moderation models with attentional bias scores at 250 and 1000 ms as dependent variables were not significant, all ps> .133.

2.3. Discussion

Overall, heavier media multitasking was associated with greater trait anxiety, consistent with previous studies (Becker, Alzahabi, and Hopwood 2013; Shin and Kemps 2020). Trait anxiety was also linked to monitoring coping responses but not to blunting responses. Unexpectedly, we observed that media multitasking was not associated with either monitoring or blunting (or avoidant) coping responses. This lack of association between media multitasking and monitoring/blunting may be because participants could not relate to the scenario in the MBSS (e.g. a terrorist hostage situation, a plane failure mid-air) or felt that the scenarios were too far removed from their own experiences. Thus, in Experiment 2, we used the Cognitive Behavioural Avoidance Scale (Ottenbreit and Dobson 2004), which gauges participants’ tendency to avoid common, everyday stressful situations.

Contrary to expectations, media multitasking was not associated with attentional bias toward or away from negative words at either shorter (250 ms) or longer (1000 ms) stimulus presentation durations, despite the significant relationship between media multitasking and anxiety. Previous research on the timing of attentional avoidance of anxiety stimuli has produced mixed results. Some studies have shown that among anxious individuals, avoidance of anxiety provoking stimuli can occur as early as 200 ms (Koster et al. 2006), whereas others found avoidance only from 1000 ms (Mogg et al. 2004). It is possible that the stimulus presentation durations of 250 and 1000 ms (and that of 500 ms; Shin and Kemps 2020) did not coincide with the shifting of attention of media multitaskers in the dot probe task. Including a broader range of stimulus presentation durations may better capture the time course of attention shifting. Experiment 2, therefore, included four stimulus presentation durations in the dot probe task: 150 , 250 , 500 , and 1000 ms.

3. Experiment 2

3.1. Method

3.1.1. Participants

One hundred and forty-five volunteers (115 females) aged 18–51 years (M = 30.6 years, SD = 9.47) were recruited through a study advertisement on social media (N = 5) and the undergraduate student research participation system (N = 140) at Charles Sturt University. The sample size was determined using G*Power to detect an effect size (Cohen’s f) of 0.25 at a 5% significance level with 80% power. Data collection occurred between May and August, 2021. As in Experiment 1, all participants completed the study online at a time that was convenient for them via a web link embedded in the study advertisement. Undergraduate students again received course credit for participating; participants recruited via social media did not receive any reimbursement.

3.1.2. Materials and procedure

Materials and procedure were the same as in Experiment 1, except that the stimulus presentation durations used in the dot probe task were 150 , 250 , 500 , and 1000 ms (24 trials for each, 96 trials in total), and the Cognitive Behavioural Avoidance Scale (CBAS; Ottenbreit and Dobson 2004) was used to assess the tendency to avoid difficult situations or problems in life. This measure includes four subscales: behavioural social (e.g. I tend to make up excuses to get out of social activities), behavioural non-social (e.g. Rather than getting out and doing things, I just sit at home and watch TV), cognitive social (e.g. When I experience confusion in my relationships, I do not try to figure things out), and cognitive non-social (e.g. I distract myself when I start to think about my work/school performance). Cronbach’s alpha of the sample was .96. All items are rated on a 5-point scale ranging from 1 = Not at all to 5 =  Extremely. The mean scores for the behavioural social, behavioural non-social, cognitive social, and cognitive non-social subscales were 18.1 (SD = 7.4), 13.7 (SD = 5.0), 14.2 (SD = 5.4), and 20.1 (SD = 7.6), respectively. The mean overall CBAS score was 66.1, with a standard deviation of 22.3.

The mean MMI score derived from the media use questionnaire was 3.06 with a standard deviation of 1.30, and the mean trait anxiety score from State-Trait Anxiety Inventory was 45.4, with a standard deviation of 11.0. Of the 145 participants, 75% reported moderate to high anxiety.

3.2. Results

3.2.1. Data preparation

Participants with average levels of accuracy lower than 70% on the dot probe task were again removed (7.6%), as were reaction times longer than 1000 ms (3.1%).

3.2.2. Sample characteristics

Media multitasking was significantly correlated with trait anxiety, r(143) =  .195, p =  .019. Further, trait anxiety was significantly correlated with the overall CBAS score, r(143) =  .693, p< .001. The correlation between media multitasking and the overall CBAS score was also significant, r(143) =  .189, p =  .023. More specifically, media multitasking correlated with the behavioural social subscale, r(143) =  .168, p =  .043, the behavioural non-social subscale, r(143) =  .189, p =  .023, and the cognitive non-social subscale, r(143) =  .188, p =  .024. Media multitasking was significantly correlated with age, r(143) =  -.265, p =  .001.

3.2.3. Attentional bias

Attentional bias at each stimulus presentation duration is shown in Table 3. Media multitasking and attentional bias were not significantly correlated at stimulus presentation durations of 150 ms, r(143) =  .055, p =  .509, or 250 ms, r(143) =  .037, p =  .658. However, the correlations fell just short of significance at presentation durations of 500 ms, r(143) =  -.151, p =  .071, and 1000 ms, r(143) =  .155, p =  .063, suggesting that media multitasking was marginally correlated with attentional bias away from negative words at 500 ms and attentional bias toward negative words at 1000 ms. Similarly, cognitive behavioural avoidance was marginally correlated with attentional bias away from negative words at 500 ms, r(143) =  -.155, p =  .062, and was significantly correlated with attentional bias toward negative words at 1000 ms, r(143) =  .191, p =  .021. In addition, trait anxiety and attentional bias away from negative words were significantly correlated, but only at a presentation duration of 500 ms, r(143) =  -.211, p =  .011.

Table 3. Attentional Bias at Stimulus Presentation Durations of 150 ms, 250 ms, 500 ms, and 1000ms.

	150ms		250ms		500ms		1000ms
	Negative	Neutral	Negative	Neutral	Negative	Neutral	Negative	Neutral
Reaction times (ms)	505.3 (76.6)	502.1 (64.2)	501.8 (78.9)	501.9 (80.3)	515.2 (77.4)	523.6 (78.6)	511.4 (81.9)	507.5 (77.0)
Attentional bias (ms)	−3.2		0.1		8.4		−3.9

3.2.4. Moderating role of cognitive behavioural avoidance

A series of moderated regression analyses examined whether cognitive behavioural avoidance moderated the relationship between media multitasking and trait anxiety, and the relationship between attentional bias and trait anxiety. Media multitasking and attentional bias scores at 150 , 250 , 500 , and 1000 ms were, in turn, entered as the dependent variable. Trait anxiety and the overall cognitive behavioural avoidance score were entered in Step 1. The interaction term between trait anxiety and the overall cognitive behavioural avoidance score was added in Step 2. None of the moderation models showed significant results, all ps> .054.

3.3. Discussion

Consistent with Experiment 1, heavier media multitasking was again associated with higher trait anxiety in Experiment 2. However, unlike Experiment 1, in which trait anxiety was linked only to monitoring and not blunting responses, we observed a strong relationship between trait anxiety and cognitive behavioural avoidance. More importantly, the association between heavier media multitasking and greater cognitive behavioural avoidance was significant in Experiment 2. This supports the idea that media multitasking, trait anxiety, and avoidance coping are closely related constructs.

Based on the propositions of the I-PACE model (Brand et al. 2016), we examined the moderating role of avoidance coping in the relationship between media multitasking and trait anxiety. Despite bivariate associations between media multitasking, trait anxiety, and avoidance coping, the moderation models were not significant, suggesting that the underlying mechanism in frequent media multitasking may differ from that of frequent online media consumption.

Experiment 2 included a wider range of stimulus presentation durations in the dot probe task (150 , 250 , 500 , and 1000 ms). The results showed trend associations between heavier media multitasking and an attentional bias away from negative words at 500 ms, but toward negative stimuli at 1000 ms. Similar trends were observed between trait anxiety and attentional bias, and cognitive behavioural avoidance and attentional bias. The trend association between heavier media multitasking and an attentional bias away from negative words at 500 ms may indicate that heavier media multitaskers who also tend to be anxious tried to avoid negative words, consistent with Onnis, Dadds, and Bryant (2011). However, media multitasking is also linked to attention lapses (Madore et al. 2020) and difficulty suppressing distractors (Cain and Mitroff 2011), which may explain the marginal association between media multitasking and the attentional bias away from negative stimuli at 500 ms followed by an attentional bias toward those stimuli at 1000 ms.

As the associations between media multitasking and attentional bias at presentation durations of 500 and 1000 ms in Experiment 2 were marginal, we used stimuli that elicit stronger negative emotions to try to observe a more robust attentional bias (Sutton and Lutz 2019) in Experiment 3. Previous studies have shown that emotional images, such as faces, elicit a stronger attentional bias than emotional words (Lees, Mogg, and Bradley 2005; Pool et al. 2016). Thus, in Experiment 3, angry and neutral faces were presented for 100 , 500 ms, or 1250 ms in the dot probe task. We again included a stimulus presentation duration of 500 ms as previous studies have shown an attentional bias for emotionally negative faces in socially anxious individuals at 500 ms (Pishyar, Harris, and Menzies 2004). We further included presentation durations of 100 ms and 1250 ms to detect an initial attentional bias toward emotionally negative face stimuli and a late shift in attention away from these stimuli (Koster et al. 2005). We also administered measures of social phobia and depression, as these have been closely linked to attentional bias for negative emotional faces (Pishyar, Harris, and Menzies 2004; Trapp et al. 2018).

4. Experiment 3

4.1. Method

4.1.1. Participants

One hundred and thirty-eight volunteers (104 females) aged 17–56 years (M = 30.5 years, SD = 9.1) were recruited through a study advertisement on social media (N = 47) and the undergraduate student research participation system (N = 91) at Charles Sturt University. Data collection took place between May and July, 2021. All participants completed the study online at a time that was convenient for them via a web link embedded in the study advertisement. Undergraduate students again received course credit for participating; participants recruited via social media did not receive any reimbursement. The sample size was determined using G*Power to detect an effect size (Cohen’s f) of 0.25 at a 5% significance level with 80% power.

4.1.2. Materials and procedure

Materials and procedure were the same as in Experiments 1 and 2, except that we used faces instead of words as stimuli in the dot probe task. These were taken from the Radboud faces database (Langner et al. 2010) and were frontal faces of 6 males and 6 females that showed either angry or neutral emotions (i.e. 24 faces in total). The stimulus presentation durations were 100 , 500 ms, and 1250 ms (96 trials each, 288 trials in total). The number of trials was increased from 24 (in Experiment 2) to 96 to ensure enough trials per stimulus presentation duration. Furthermore, we administered the Mini-SPIN (Connor et al. 2001) and the Patient health questionnaire-9 (Kroenke, Spitzer, and Williams 2001) to measure social anxiety and depression, respectively.

The Mini-SPIN is a short form of the social phobia inventory, a screening instrument for social phobia or social anxiety. The Mini-SPIN consists of 3 items, including ‘Fear of embarrassment causes me to avoid doing things or speaking to people’ and ‘I avoid activities in which I am the center of attention’. All items are rated on a 5-point scale ranging from 0 = not at all to 4 = extremely. Possible scores range from 0 to 12, with a higher score indicating greater social anxiety. Cronbach’s alpha of the current sample was .77. The mean Mini-SPIN score was 4.1, with a standard deviation of 3.0.

The Patient health questionnaire-9 is designed to screen for depression in medical settings. The scale consists of 9 items, including ‘little interest or pleasure in doing things’ and ‘feeling tired or having little energy’. All items are rated on a 4-point scale ranging from 0 = not at all to 3 = nearly every day. Scores range from 0 to 27, with a higher score indicating greater depression. Cronbach’s alpha of the current sample was .89. The mean Patient health questionnaire-9 score was 7.4, with a standard deviation of 5.8.

The mean MMI score derived from the media use questionnaire was 2.9, with a standard deviation of 1.2.

4.2. Results

4.2.1. Data preparation

Participants with average levels of accuracy lower than 70% on the dot probe task were again removed (2.8%), as were reaction times longer than 1000 ms (3.0%).

4.2.2. Sample characteristics

Media multitasking was significantly correlated with social anxiety, r(136) =  .177, p =  .038, and depression, r(136) =  .187, p =  .028. Media multitasking did not correlate with age, r(136) = -.136, p = .111.

4.2.3. Attentional bias

Attentional bias at each stimulus presentation duration time is shown in Table 4. Media multitasking and attentional bias for negative emotional faces were not significantly correlated at any of the presentation durations (100 ms, r(136) = -.027, p = .750; 500 ms, r(136) = -.108, p = .209; 1250 ms, r(136) = .104, p = .227). There was no significant correlation between social anxiety and attentional bias, or between depression and attentional bias across presentation durations, all ps>.209.

Table 4. Attentional Bias at Stimulus Presentation Durations of 100 , 500 ms, and 1250ms.

	100ms		500ms		1250ms
	Negative	Neutral	Negative	Neutral	Negative	Neutral
Reaction times (ms)	496.2 (62.9)	494.6 (62.4)	506.3 (64.8)	506.4 (60.8)	490.5 (64.8)	492.9 (69.1)
Attentional bias (ms)	−1.6		0.1		2.4

4.3. Discussion

Heavier media multitasking was significantly associated with greater social anxiety and depression. However, media multitasking was not associated with attentional bias at any of the presentation durations (100 , 500 ms, or 1250 ms), nor were social anxiety or depression.

Both social anxiety and depression have been associated with attentional bias for negative facial stimuli (Mansell et al. 1999; Pishyar, Harris, and Menzies 2004; Trapp et al. 2018). As media multitasking has also been linked to both social anxiety and depression (Becker, Alzahabi, and Hopwood 2013), we expected that media multitasking would be linked to attentional bias for negative facial stimuli. Furthermore, as negative facial stimuli are more biologically relevant than negative words, we expected these to elicit greater arousal, which would be reflected in a stronger attentional bias. The results are consistent with Becker, Alzahabi, and Hopwood (2013) in that media multitasking was associated with social anxiety and depression, but at odds with Pishyar, Harris, and Menzies (2004) in that heavier media multitaskers who tend to be socially anxious did not show an attentional bias for negative facial stimuli. This suggests that there is no significant difference in attentional processing of negative facial stimuli between individuals who frequently engage in media multitasking and those who do not.

5. General discussion

5.1. Media multitasking, anxiety, depression, and avoidance coping

Across three experiments, we investigated the relationships between media multitasking, negative mood, and attentional avoidance of negative stimuli. An overview of the results from the three experiments is shown in Table 5. Media multitasking was associated with trait anxiety, social anxiety, and depression. Although media multitasking was not associated with either monitoring or blunting coping, both media multitasking and trait anxiety were linked to cognitive behavioural avoidance, supporting the idea that media multitasking may be used as an avoidance coping strategy to cope with anxiety and depression.

Table 5. Overview of the Results from the Three Experiments.

	Experiment 1	Experiment 2	Experiment 3
Mental health	Correlation between media multitasking and trait anxiety	Correlation between media multitasking and trait anxiety	Correlation between media multitasking and social anxiety Correlation between media multitasking and depression
Cognitive behavioural avoidance	No association between media multitasking, monitoring or blunting coping	Correlation between media multitasking and cognitive behavioural avoidance
Attentional avoidance	No association between media multitasking and attentional bias for emotionally negative stimuli	No association between media multitasking and attentional bias for emotionally negative stimuli	No association between media multitasking and attentional bias for emotionally negative stimuli

The observed relationships between frequent media multitasking, trait anxiety, social anxiety, and depression replicate the findings of Becker, Alzahabi, and Hopwood (2013) and Shin and Kemps (2020), suggesting a close link between media multitasking and negative mood. Further, the current study showed an association between media multitasking and cognitive behavioural avoidance, which supports and extends the findings of Shin and Kemps (2020), who showed that media multitasking was linked to difficulties in accepting emotional responses. The relationships between media multitasking, poor mental health indicators, and avoidance coping support Wang and Tchernev’s (2012) suggestion that heavier media multitaskers are more likely to deviate from the task at hand to attend to emotional needs. However, this avoidance coping may reflect a reactive decision-making style to pursue current desires (e.g. to distance themselves away from negative stimuli) at the expense of future rewards (e.g. an eventual resolution of the problem itself) (Schutten, Stokes, and Arnell 2017).

5.2. Media multitasking and selective attention for emotionally negative stimuli

The current results showed that media multitasking was not associated with attentional bias for emotionally negative words (Experiments 1 and 2) or faces (Experiment 3) across a range of stimulus presentation durations (100 ms to 1250 ms). We did observe trend associations that linked attentional bias away from negative stimuli at 500 ms, and toward negative stimuli at 1000 ms, to media multitasking as well as trait anxiety and avoidance coping (Experiment 2). These trend associations led to using stimuli that elicit stronger negative emotions, such as face stimuli (Experiment 3). However, the results showed no association between attentional bias and negative emotions (social anxiety, depression), nor between attentional bias and media multitasking.

The discrepancy between the self-report measures of avoidance and the attentional bias scores in their relationship to media multitasking indicates that attentional avoidance may not always coincide with overall behavioural avoidance. This may be because attentional bias measured in the dot probe task and avoidance strategies measured by self-report measures pertain to behaviours at different time points. The dot probe task assesses attentional bias toward or away from threat over a very short timeframe (< 2 s). In contrast, cognitive or behavioural avoidance as measured by self-report measures pertain to behavioural tendencies and decisions that may be made over a relatively longer period (e.g. ‘I do not go out to events when I know there will be a lot of people I do not know’).

5.3. Media multitasking, age, and avoidance coping

Frequent media multitasking has been associated with a younger age (e.g. Carrier et al. 2009; Voorveld and van der Goot 2013). In support, we found a negative linear relationship between media multitasking and age in two of the three experiments (Experiments 1 and 2). As young people grew up using portable devices (Rideout, Foehr, and Roberts 2010), they would be more likely to use such devices as a coping strategy. When problem orientated coping strategies cannot be easily applied (e.g. to chronic life stressors), the ability to easily access media to take one’s mind off emotionally negative stimuli and engage in activities that induce positive emotion could be beneficial and promote well-being (Waugh, Shing, and Furr 2020). However, when one is required to confront the problem (e.g. preparing for a final exam), this type of avoidance or distraction coping may be maladaptive as it prevents individuals from taking the necessary action to produce a positive outcome (Lazarus 1998).

5.4. Implications for digital approaches to mental health

The current findings of the relationships between media multitasking, anxiety, and depression, and the relationship between media multitasking and avoidance coping suggest that media multitasking may be used as an avoidance coping strategy to alleviate feelings of anxiety and depression. Thus, observing media multitasking behaviour may aid mental health practitioners in the early detection of symptoms of anxiety and depression, especially in young people who spend much of their time consuming media (Matthews, Mattingley, and Dux 2022). The link between media multitasking, negative emotions and avoidance coping may also aid mental health practitioners with their treatment plans, in which clients become aware of their media multitasking behaviour and explore other more adaptive ways of coping with stress.

5.5. Limitations

Although the current study found relationships between media multitasking, negative emotions, and behavioural avoidance, it did not show a link between media multitasking and attentional avoidance (i.e. attentional bias toward or away from emotionally negative stimuli). This may be because the contribution of attentional bias for negative stimuli was obscured by other individual differences associated with media multitasking, such as impulsivity (Minear et al. 2013; Sanbonmatsu et al. 2013; Schutten, Stokes, and Arnell 2017; Shin, Webb, and Kemps 2019) or proneness to boredom (Shin, Taseski, and Murphy 2023). Future research could explore the relationships between media multitasking, negative emotions, and avoidance coping, controlling for these individual differences.

Based on the I-PACE model (Brand et al. 2016), we examined whether the relationship between media multitasking and trait anxiety was strengthened by cognitive behavioural avoidance coping, similar to problematic online media use and anxiety. However, the moderation model was not significant. Avoidance coping may have been a significant moderator if it were measured across multiple time points using a longitudinal design rather than only once in the current cross-sectional design, which is more vulnerable to recall bias (i.e. inability to accurately remember past experiences). Future media multitasking studies could use longitudinal designs to more comprehensively measure avoidance coping.

Lastly, the participants in the study were mostly female university undergraduate students. As the target population was adults aged 18+ years who use digital media, the sample may not be representative of that population. To our knowledge, no studies have identified differences in gender or sex when investigating media multitasking, negative mood and avoidance. However, older adults may show different patterns of results as older age has been associated with less media multitasking and less avoidance coping (e.g. Amirkhan & Auyeung, 2007). Thus, future studies could investigate the role of age in the relationships between media multitasking, negative mood and avoidance, as well as gender and other demographic variables not measured here (e.g. education, income, place of residence).

6. Summary

This study examined the relationships between media multitasking, negative emotions, and avoidance coping. We observed that media multitasking is associated with greater trait anxiety, social anxiety, depression, and an overall avoidance coping tendency. However, behavioural avoidance was not associated with attentional avoidance (neither were media multitasking and negative emotions), indicating that overall behavioural avoidance may not necessarily coincide with attentional avoidance. Overall, the findings suggest that media multitasking behaviour may be used to help detect anxiety and depression. Treating these mental health disorders could focus on exploring the relationships between media multitasking, negative emotions, and avoidance coping.

Disclosure statement

No potential conflict of interest was reported by the author(s).