Coping styles among Chinese adolescents: The development and validation of a smartphone coping style scale

ABSTRACT

Because of their entertainment functions and easy access, smartphones have become a popular means to help people cope with stress. However, there is not currently a validated set of measures for smartphone coping that captures the specific strategies people use when facing stress or difficulties, especially adolescents who suffer from psychological stress. This study aimed to develop a smartphone coping scale that includes specific strategies for adolescents. Using qualitative and quantitative methods, we first implemented focus groups and in-depth interviews to collect qualitative materials on smartphone coping. Then we constructed the initial items for the Smartphone Coping Style Scale. We next conducted exploratory and confirmatory factor analyses in one sample and assessed the reliability, stability, construct validity, criterion validity (anxiety/depression), and convergent validity (the Ways of Coping Questionnaire) in another sample. Three independent sub-components of smartphone coping were extracted: solving daily problems, distracting negative emotions, and seeking social support. The developed scale showed favorable levels of reliability, stability, and validity. The developed scale with three different subscales is a validated tool for capturing adolescents’ different smartphone coping styles and the scores of the three subscales should not be combined in practice.

IMPACT SUMMARY

Prior State of Knowledge: Previous literature advocated the importance of digital coping or regulation. Adolescence is a period of vulnerability to stress. Properly managing stress by using technology (e.g., smartphones) benefits adolescents’ health. However, it is unclear which smartphone coping styles adolescents use.

Novel Contributions: This study first revealed the structure of adolescents’ specific smartphone coping styles, which include solving daily problems, seeking social support, and distracting negative emotion. The first two coping styles are more adaptive, whereas the latter is more less adaptive.

Practical Implications: This study offers a reliable tool for researchers who are interested in exploring the impact of digital coping on adolescents’ development. Moreover, it informs policymakers and parents about adaptive types of smartphone coping, which should be encouraged to enhance the well-being of adolescents.

KEYWORDS:

• smartphone coping style
• problem-focused coping, emotion-focused coping
• solving daily problems
• distracting negative emotion
• seeking social support

Introduction

During the past 20 years, smartphones have attracted an increasing number of users, and that number is predicted to reach 4.5 billion in 2023 (Statista, 2021); 99.8% of people access the Internet through their smartphones. The global popularity of smartphones may be because they facilitate people’s daily lives and online communication. Among digital devices (e.g., smartphones, computers, laptops), the highest technology usage rate among Chinese adolescents is smartphones (93.9%). In 2020, the usage rates of computers, laptops, and tablets among Chinese minors were 45%, 31.5%, and 28.9%, respectively (CNNIC, 2020). In 2019, 84% of American adolescents owned a smartphone, and in 2021, 88% of American adolescents owned a smartphone (Rideout et al., 2022). In recent years, researchers have shown increasing interest in the benefits of smartphones in terms of regulating emotions (Wadley et al., 2020; Wolfers & Schneider, 2020) and coping with daily stress (Carolus et al., 2019; Chiu, 2014; Chung et al., 2014; Snodgrass et al., 2014; Wang et al., 2015; Wolfers & Schneider, 2020; Wolfers et al., 2020). For example, Wolfers et al. (2020) reported that smartphones can serve as an effective coping medium because of their flexibility and portability. Wadley et al. (2020) proposed the concept of digital emotion regulation, which argues that people use digital media, including smartphones, to regulate their emotions. According to previous research (Wadley et al., 2020; Wolfers et al., 2020) and coping theories (Lazarus & Folkman, 1984; Lazarus & Lazarus, 2006), smartphone coping refers to the use of various smartphone functions to manage one’s sense of inner balance when facing stressful situations.

In this paper, we review empirical research and theories that discuss the natural aspects of using smartphones for coping with stress. Then we summarize the existing gaps in capturing smartphone coping styles. Finally, we use a mixed method to develop the Smartphone Coping Style Scale among adolescents.

Smartphone coping: Theoretical basis and empirical evidence

To date, evidence suggests several theories about why people tend to use smartphones to cope. One is the coping theory, which suggests that individuals adopt many coping strategies to manage their stress or emotions to balance their psychological state (Lazarus & Folkman, 1984). The coping theory divides coping into problem-focused coping and emotional-focused coping. The former refers to the use of strategies to change environmental demands and solve problems (e.g., altering environmental pressures or developing a new behavior), which is an adaptive and the most effective coping strategy for handling stress and difficulty (Duan et al., 2020; Lazarus & Folkman, 1984; van Ingen et al., 2016). The latter proposes altering how individuals interpret a situation and regulate negative emotions (e.g., avoidance, selective attention), which is maladaptive and associated with low mental health (Duan et al., 2020; Lazarus & Folkman, 1984; van Ingen et al., 2016).

In the framework of problem-focused coping and emotion-focused coping, some theories related to media use provide further theoretical evidence. Rains (2018) proposed a digital coping model to illustrate how people use media to cope with a problem of illness (e.g., acquiring and sharing information). Compensatory use theory (Kardefelt-Winther, 2014) points out that negative life situations or stressors increase individuals’ motivation to find compensation in online space, which could help them deal with life issues (e.g., find a solution via media uses and gratifications theory. Blumler (1979) also highlights that individuals actively use media to solve their problems to satisfy their needs (e.g., learning new skills to solve problems) (Larose et al., 2001). Self-medication theory notes that children and adolescents use smartphones to “medicate” stress or emotional problems (Sun et al., 2019), emphasizing emotion-focused coping via media. The compensatory-use theory and gratification theory also illustrate the emotion-focused coping of media use. For example, individuals compensate for the negative emotions experienced in their offline life by distracting themselves by focusing on media (Kardefelt-Winther, 2014). They also use media to avoid negative moods to satisfy their need to regulate negative emotions (Larose et al., 2001). Using smartphones for coping has theoretical bases. Some theories highlight the use of smartphones to avoid life stresses or relieve negative emotions; other theories emphasize using smartphones to solve life issues. Based on various aims, needs, and motivations, individuals can develop different types of smartphone coping (e.g., adaptive coping or maladaptive coping).

There is a growing literature about smartphone coping. In 2021, 69% of adolescents used mobile apps (e.g., apps for sleep) to cope with health problems (Rideout et al., 2021). Two recent review studies revealed a negatively moderate correlation between smartphone use and stress (Elhai et al., 2017; Samaha & Hawi, 2016). Stressful life events are related to increased Internet or smartphone use. For example, college students’ stress is directly and indirectly related to their problematic smartphone use (Chiu, 2014). Some researchers have found that perceived stress is indirectly related to problematic smartphone use through the mediation of self-control (Cho et al., 2017; Q. Q. Liu et al., 2018). Other researchers proposed a mediation model that adopts a smartphone coping perspective, suggesting that psychological distress is indirectly related to problematic smartphone use through the mediation of emotion dysregulation (Squires et al., 2020).

Adolescents encounter many stressors, such as major life events and common daily challenges, most of which are related to school performance (e.g., academic problems), interpersonal relationships (e.g., conflicts with peers or parents), and uncertainty about the future (Byrne & Mazanov, 2002; Zimmer-Gembeck et al., 2008). Some researchers have argued that adolescents’ coping strategies during the phase of adolescence when their brains change (Crone & Konijn, 2018), are critical for reducing psychopathological risk and developing resilience (Compas et al., 2017). However, it is unclear what strategies adolescents adopt in the face of stress or difficulty, especially when they spend so much time on their smartphones (J. Liu et al., 2019).

Smartphone coping: Research gaps

Previous studies have focused primarily on the possibility of smartphones serving as a coping medium (Rideout et al., 2021; Wadley et al., 2020). Although several studies have measured smartphone coping and used scales revised from previous online coping scales (Carolus et al., 2019; Khoo & Yang, 2021; van Ingen et al., 2016), they do not capture the specific functions, features, and use patterns of smartphones. Researchers argue that such measurements are too vague and that more concrete measures for smartphone coping are necessary (Wolfers & Schneider, 2020). For example, such scales measure only whether smartphones are used as a tool for coping with stress (e.g., “My mobile phone helps me cope with stress.”) rather than the specific coping behaviors or strategies adopted (e.g., which specific smartphone function is used to cope) (Carolus et al., 2019; Khoo & Yang, 2021). By specifically clarifying different smartphone coping strategies, researchers can investigate which kinds of specific coping strategies are beneficial for adaption by adolescents. This could help adolescents to use adaptive smartphone coping strategies and avoid negative coping strategies.

Research on media coping has focused predominately on emotion-focused strategies and neglected problem-focused coping strategies (Wolfers & Schneider, 2020). For example, components of Internet coping include mental disengagement (distract attention via the Internet), emotional support (obtain emotional support through the Internet), instrumental support (obtain instrumental support through the Internet), venting emotions (express negative feelings on the Internet), positive reinterpretation (see the bright aspects of things via the Internet), and active coping (take actions to make situations better through the Internet) (van Ingen et al., 2016). Most of these strategies are emotion-focused coping strategies (Wolfers & Schneider, 2020). This indicates that smartphone coping measurement should balance emotion-focused and problem-focused coping.

Third, there is no scale to measure adolescents’ smartphone coping strategies, because different populations may use smartphones in different ways, and previous researchers have focused primarily on adult or older populations (Carolus et al., 2019; Khoo & Yang, 2021; van Ingen et al., 2016). Therefore, a Smartphone Coping Style Scale with specific strategies is needed before researchers can explore smartphone coping behavior and its related factors among adolescents.

The present study

This study aims to explore adolescents’ smartphone coping styles and develop a scale to evaluate them. Three steps were implemented in this study. In the first step, focus groups and in-depth interviews were conducted to obtain qualitative materials to generate potential items for the Smartphone Coping Style Scale (Kidd, 2002). In the second step, a quantitative method that combined exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was used to develop the Smartphone Coping Style Scale in an adolescent sample. In the final step, the reliability and validity of the Smartphone Coping Style Scale were examined in an additional adolescent sample. According to coping theory, maladaptive coping focuses on the suppression of negative emotions or changing how the situation is interpreted (e.g., avoidance, selective attention), whereas adaptive coping focuses on direct problem solving or changing the situation. Thus, maladaptive smartphone coping would be the use of smartphones to avoid situations or relieve negative emotions. Adaptive smartphone coping would be the use of smartphones as a tool to solve problems directly or develop new skills.

Methods

Qualitative data collection

Participants

Six middle school students (male = 3) and six high school students (male = 3) participated in the focus group interview. Seventeen middle school students (male = 9) and twelve high school students (male = 6) (M_age = 13.93) participated in the in-depth interviews. All the students were recruited with the help of teachers, and all students all have much experience with smartphone use. This study was approved by the Institutional Review Board (IRB) of the State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University. All participants provided informed consent.

Settings and materials

The outline and procedures of the focus group followed the rules proposed by Krueger and Casey (2000). We conducted two focus groups: one for middle school students and one for high school students. Each focus group met in a quiet room under the guidance of two researchers. Students were told that the focus group would be recorded and that no one except the researchers could access these materials. Students were asked two questions: “Usually when you encounter difficulties or feel stressed in life, do you use your mobile phone to help you?” “If so, what do you usually do with your mobile phone?” The in-depth interview also took place in a quiet room, and each researcher interviewed one student at a time. Students were asked the same two questions as in the focus group.

Analytic procedure

Focus groups are pre-interviews, and in-depth interviews are formal interviews. Focus group interviews can be helpful when researchers want to pretest ideas, materials, or plans (Krueger & Casey, 2000). Their aim for our study was to understand the characteristics of adolescents’ smartphone coping, to provide information for later, formal, in-depth interviews, and to improve the quality of the in-depth interviews. The in-depth interview aimed to obtain detailed qualitative information for later item generation. To ensure that the interview questions were easy to understand and reasonable, we tested them in two focus groups. The results indicated that adolescents could easily answer these questions; therefore, no revisions were made to the questions before using them in the in-depth interviews. The qualitative materials for the in-depth interviews were coded by two researchers, who had spent three hours building the coding norms. Using the qualitative research software program NVivo 11, they coded the coping strategies according to the functions of smartphones and categorized the strategies into different themes. Following the convention of data analysis using NVivo (Langbecker et al., 2016), the quality of the coding was assessed using the agreement rate and Kappa coefficient. Across all codes (nodes in NVivo), the average percentage agreement was 99.78% (range 94.83% ~ 100%), and the average Kappa coefficient was .77 (range 0 ~ 1). Kappa values above .80 are considered good (Landis & Koch, 1977). The coders discussed the discrepancies and recoded the nodes with Kappa values below .80. They finally obtained agreement and an acceptable average Kappa coefficient across codes (Kappa = .93). The materials from the in-depth interviews were then analyzed using the NVivo 11 (AlYahmady & Al Abri, 2013). The qualitative research of this study was pre-registered, and outlines of the interviews can be found at the following pre-registration link (https://osf.io/k37cr).

Survey questionnaire

Participants

In this study, three surveys were administered using a convenience sampling method in which teachers helped the researchers recruit participants. First, an online survey was sent to 1,156 adolescents (1,088 valid participants, M_age = 14.89 ± 1.40, male = 554) to collect data for EFA and CFA. A paper-and-pencil survey was then sent to a different sample of 897 adolescents (868 valid participants, M_age = 14.03 ± 1.36, male = 456) to test the reliability and validity of the newly developed scale. School teachers instructed students to complete the paper-and-pencil questionnaire independently. One week later, an online survey was sent to 176 adolescents from the second sample to examine the test-retest reliability of the Smartphone Coping Style Scale. The students received the online questionnaire from their teachers and completed it independently. Sixty-eight participants involved in the first (online) investigation were excluded (no age difference between participating and excluded adolescents (t = 1.266, p > .05), and, although differences in the geographic area were shown (χ² = 10.14, df = 2, p < .05), the effect size was too small (η² = .009) to be meaningful. This is because their average response time for each item was less than two seconds. Research suggested that it is unlikely that response time is faster than two seconds per item (Huang et al., 2012). Eleven participants from the second sample were excluded due to missing values, and no participants from the third online sample were excluded. The total number of adolescents investigated were from the eastern (7.6%), northern (47.71%), and southwestern (44.69%) areas of China; 51.2% of the adolescents were from urban areas. Informed consent was obtained from all participants.

Measurements

Smartphone coping style scale

According to the materials in the in-depth interview (see following section, Qualitative analysis), we formed at least one item for each specific strategy. For the most used strategies (n > 10), three items were generated for each strategy (e.g., for playing games, the example item is “I play mobile games when I am under pressure or in trouble”). Because the strategy “finding solutions to problems” contains five different aspects in the qualitative materials, five items were generated (e.g., “I use my smartphone to search for solutions to problems or difficulties”), and, for the remaining less used strategies (n < 3), one item was generated for each strategy. Four experts who were familiar with adolescents’ media use, evaluated the appropriateness of each item. A 4-point Likert scale was used (1=strongly disagree, 4=strongly agree). Finally, 20 items were selected to evaluate adolescents’ smartphone coping styles. The instructions were: “When faced with difficulties or stress, people use their smartphones to help them cope. The following statements list some ways in which individuals cope with stress through smartphone use. Please evaluate how much you agree with the statements according to your actual behavior over the past month. When answering, please do not think too much and base your response on your most immediate feelings.”

Criterion validity

Anxiety and depression were regarded as criteria, because the literature indicates that problem-focused coping style is negatively related to anxiety and depression, and emotion-focused coping style is positively related to anxiety and depression (Duan et al., 2020). Anxiety and depression were measured in the second and third surveys of the study. The Generalized Anxiety Disorder-7 scale (GAD-7) (Spitzer et al., 2006) and the Center for Epidemiologic Studies Depression Scale (CES-D-10) (Andresen et al., 1994) were used to measure the anxiety and depression of adolescents, respectively. The GAD-7 includes seven items (e.g., “I was not able to stop or control worrying”) and uses a 5-point Likert scale to rate these items (α = .963). The CES-D-10 includes ten items (e.g., “I felt everything was an effort”) and uses a 4-point Likert scale to rate these items (α = .843). We assumed that adaptive smartphone coping is negatively related to anxiety and depression, whereas maladaptive smartphone coping is positively related to anxiety and depression.

Convergent validity

The shortened Ways of Coping Questionnaire (Piko, 2001) was used to measure adolescents’ general coping styles. Three subscales were used: (1) “problem-analysing” coping (e.g., “I made a plan of action and followed it”); (2) “risky coping” (e.g., “Tried to make myself feel better by eating, drinking, or smoking”); and (3) “support-seeking coping”(e.g., “I asked a relative or friend I respected for advice”). All items are rated on a 4-point Likert scale. A higher total score on a dimension means a higher likelihood of using the given coping style. The Cronbach’s α values for the subscales are .81, .58, and .59, respectively. Because “problem-analysing coping” and “support-seeking coping” are more adaptive than “risky coping,” we assumed that adaptive smartphone coping is positively related to “problem-analysing coping” and “support-seeking coping” and negatively related to “risky coping”, whereas maladaptive smartphone coping is negatively related to “problem-analysing coping” and “support-seeking coping” and positively related to “risky coping”.

Analytic procedure

The Smartphone Coping Style Scale was used in the first survey, and EFA and CFA were conducted to analyze these items. The qualitative approach and EFA both aimed to find out the structure of smartphone coping style by analyzing detailed qualitative materials or extracting common factors from items, which is a bottom-to-top process. CFA tried to further confirm whether the factors extracted from the EFA were appropriate, which is a top-to-bottom process.

According to the rules of factor analysis, to ensure the stability of a factor solution, researchers should have at least a 4:1 ratio of subjects to variables (MacCallum et al., 2010). A sample size larger than 500 is optimal for factor analysis (Comrey & Lee, 1992). Therefore, 600 participants from the first survey were randomly selected to conduct the EFA. (The remaining participants and these 600 participants were used later to perform the CFA.) The EFA procedure follows the steps proposed by Suhr (2006), including initial extraction (e.g., variance each factor explains) and determination of the number of factors to retain (e.g., scree test, the proportion of variance), rotation. Parallel analysis was performed to test the robustness of the extracted factors (O’Connor, 2000). In the initial extraction, principal axis factoring was used, because it considers measurement errors and accounts for co-variation (Ngure et al., 2015). A total of 1,088 participants were involved in the CFA. CFI, TLI, and RMSEA were used to evaluate the fit of the CFA model. CFI and TLI > .90 and RMSEA < .08 indicate acceptable model fit, and CFI and TLI > .95 and RMSEA < .06 indicate good model fit (Hu & Bentler, 1998). We also considered the modification indices and correlated the residuals of items that were similarly worded and within the same dimension (Khoo & Yang, 2021). Finally, data from the second and third surveys were used to evaluate the reliability and validity of the scale. The second survey could be used to modify the scale, if the scale formed in the first survey was not satisfactory (e.g., sometimes the number of the developed items is few or redundant, and additional or fewer items are needed). Modification of the scale should capture and conform to the theoretical meaning. All analyses were conducted with SPSS 25.0 and Mplus 7.0 software. The development of the Smartphone Coping Style Scale was pre-registered at https://osf.io/ctvez.

Results

Qualitative analysis

Table 1 shows the coding results of the qualitative materials analyzed in NVivo 11. Adolescents’ coping strategies were coded into 10 themes. The themes included playing games, watching anime or variety shows, reading online novels, keeping a diary on one’s smartphone, browsing short video clips, listening to music, using social media, spending money online, finding solutions to problems, and taking selfies. The most used smartphone coping strategies were listening to music (n = 22), using social media (n = 22), browsing short video clips (n = 13), and playing games (n = 10). Using smartphones to take selfies (n = 1) was the least commonly used coping strategy. In general, the qualitative analysis revealed that adolescents not only use smartphones to relieve negative emotions (“… when I feel stressed, I listen to music on my smartphone to relieve tension or anxious emotions … ”), but also to seek emotional support (“It is very useful to talk with my friends on my smartphone; they comfort me and relieve my stress”) and solutions to problems (“… when I experience problems or difficulties, I usually use search engines through my smartphone to find proper solutions …”).

Table 1. Coding results of qualitative materials in NVivo 11.

Coping strategies	Examples taken from interview materials	Nodes	References
Playing games	“… I play games on my smartphone when I’m in bad mood …;” “… sometimes I play games on my smartphone to cope with difficulties I am facing.”	10	16
Watching anime or variety shows	“… When I have negative emotions, I sometimes watch variety shows, but not very frequently ….”	3	3
Reading online novels	“… I read interesting online novels when I feel stressed once a while.”	3	3
Keeping a diary on one’s smartphone	“… I write about stressful events or troublesome things in my smartphone memo, which feels like keeping a diary and venting.”	3	3
Browsing short video clips (e.g., TikTok)	“… I usually watch funny short clips on TikTok to make me feel better.”	13	13
Listening to music	“… when I feel stressed, I listen to music on my smartphone to relieve tension or anxious emotions … .”	22	24
Using social media	Posting or sharing. (e.g., “… when I experience stressful events or irritation, I post or share on my WeChat account …, which can help me vent my negative emotions.”)	3	3
	Seeking emotional support or solutions to problems from others. (e.g., “it is very useful to talk with my friends on my smartphone; they comfort me and relieve my stress.”)	19	19
Spending money online	“… online shopping on my smartphone sometimes helps me reduce my negative feelings or stress.”	2	2
Finding solutions to problems	“… when I experience problems or difficulties, I usually use search engines through my smartphone to find proper solutions ….”	5	6
Taking selfies	“… I take beautiful photos of myself to regulate my mood or get rid of bad feelings ….”	1	1

Notes. A node denotes one interview material or a participant; for a total of 29 nodes, we have 29 interviews. References denote how many times the interview transcripts refer to coping strategies used.

EFA and CFA

EFA was conducted to analyze the 20 items, and the results showed that the KMO (KMO = .918) and Bartlett (p < .001) tests were acceptable for EFA. Three eigenvalues greater than 1 were extracted. The scree plot also indicated three factors of smartphone coping; factors below the “elbow” of the scree plot were rejected. Because of the presence of cross-loadings between the factors, factor rotation was performed, and items with loadings below .30 and cross-loadings were dropped (Suhr, 2006). Then fourteen items were retained, and three factors were extracted. Parallel analysis shows that all three eigenvalues of the actual data were larger than those of the random data, indicating the robustness and appropriateness of the three factors extracted. The extracted factors (see Table 2) were solving daily problems (F1, explaining 46.26% of the variance), distracting negative emotion (F2, explaining 11.53% of the variance), and seeking social support (F3, explaining 8.12% of the variance). Solving daily problems emphasizes the use of various smartphone functions as tools to solve problems encountered in one’s daily life. Unlike F1, distracting negative emotion involves relieving stress or negative emotions by using various smartphone functions when facing difficulties. Seeking social support instead emphasizes adolescents’ use of smartphones as a medium to seek help from others but with the purpose of solving problems. Therefore, factors 1 and 3 can be regarded as means of problem-focused coping, whereas factor 2 represents emotion-focused coping, indicating three different smartphone coping styles.

Table 2. Factor loadings from EFA.

Items	F1	F2	F3
I1. I use utilities (e.g., an alarm clock, a calendar, a calculator, etc.) on my phone to help me solve problems in my life.	.831
I2. I use my smartphone to search for solutions to problems or difficulties.	.796
I3. I use my smartphone to look for solutions to problems when I encounter them.	.771
I4. I use smartphone functions such as maps, weather forecasts, etc. to solve problems in my life.	.760
I5. I use my smartphone to look up information that can help me solve problems with my studies.	.734
I6. I use my smartphone to listen to music when I am stressed or in trouble.	.613
I7. I share and vent my frustrations on social media (e.g., Weibo, QQ zone, and WeChat).		.872
I8. I spend money or shop on my smartphone when I experience something annoying.		.868
I9. I watch short videos (e.g., “TikTok” or “Kuaishou”) on my smartphone when I am upset.		.800
I10. I play mobile games when I am under pressure or in trouble.		.640
I11. I read online novels on my phone when I get into trouble.		.566
I12. When I am upset, I find someone to talk to on my phone.		.518
I13. I seek help from teachers by contacting them on my smartphone to solve problems or overcome difficulties.			.865
I14. I seek help from my family members by contacting them on my smartphone to solve problems or overcome difficulties.			.790
I15. I seek help from my parents by contacting them on my smartphone to solve problems or overcome difficulties.†			—
I16. I seek help from my elders by contacting them on my smartphone to solve problems or overcome difficulties.†			—
I17. When I face something annoying, I seek help from my family members by contacting them on my smartphone to solve problems or overcome difficulties.†			—
I18. I seek help from friends and family I know by contacting them on my smartphone to solve problems or overcome difficulties.†			—

Note. † denotes items added to factor 3 of the revised developed scale during the second investigation. These items were not measured in the first investigation, so they have no loadings on factor 3. F1= solving daily problems, F2 = distracting negative emotion, F3 = seeking social support.

The CFA results (Table 3) showed that the developed Smartphone Coping Style Scale has good construct validity (χ² = 433.879, df = 73, CFI = .959, TLI = .948, RMSEA = .067). Because only two items were found in factor 3 (see Table 2), the 14-item Smartphone Coping Style Scale was revised in the second survey by adding four new items to factor 3. There are two reasons for doing so. The first is that the eigenvalue and scree plot showed that three factors are the best. Factor 3 explained 8.12% of the variance and should be retained. The second reason is that seeking social support has its theoretical background because it emphasizes solving problems by seeking others’ help via smartphones, which is consistent with the problem-focused coping we mentioned previously. The four items added to factor 3 were created based on the theoretical significance of the factor. The revised Smartphone Coping Style Scale showed acceptable construct validity (χ² = 528.231, df = 125, CFI = .935, TLI = .920, RMSEA = .061). The revised CFA model is presented in Figure 1 (tested on sample 2). The added items can be found in Table 2.

Figure 1. CFA model of smartphone coping.

Note. SolveProb=solving daily problems, DistEmot=distracting negative emotion, SeekSupp= seeking social support.

Table 3. Reliability and construct validity of the smartphone coping style scale across samples.

	Items	αF1	αF2	αF3	αTotal	χ^2	df	CFI	TLI	RSMEA
Sample 1 (n = 1088)	14	.897	.875	.835	.915	433.879	73	.959	.948	.067
Sample 2 (n = 868)	18	.799	.747	.889	.883	528.231	125	.935	.920	.061
Sample 3 (n = 176)	18	.817	.718	.896	.882	—	—	—	—	—

Note. The items tested in sample 1 and samples 2 and 3 differ because the developed scale includes 4 additional items for factor 3.

Reliability and validity

The reliability of the Smartphone Coping Style Scale is presented in Table 3. For the three samples, Cronbach’s α values ranged from .882 to .915 for the full scale and from .718 to .897 for each subscale. In addition, the retest reliability of the scale was stable, with test-retest reliability values of .601 (p < .001), .675 (p < .001), and .556 (p < .001) for factors 1, 2 and 3, respectively.

Validity results are presented in Table 4. Solving daily problems (factor 1) is positively correlated with anxiety (r = .136, p < .001), depression (r = .071, p < .05), problem-analysing coping (r = .245, p < .001), risky coping (r = .111, p < .001), and support-seeking coping (r = .224, p < .001). Distracting negative emotion is positively related to anxiety (r = .202, p < .001), depression (r = .209, p < .001), risky coping (r = .294, p < .001), and support-seeking coping (r = .088, p < .05) but unrelated to problem-analysing coping (r = −.012, p > .05). Seeking social support is unrelated to anxiety (r = −.053, p > .05) and risky coping (r = .052, p > .05) and is negatively related to depression (r = −.095, p < .05). Seeking social support is positively related to problem-analysing coping (r = .218, p < .001) and support-seeking coping (r = .297, p < .001). The Chinese version and the translated English version of the Smartphone Coping Style Scale with items in random order are presented in the Supplemental Material.

Table 4. Partial correlations between the smartphone coping style scale and other related validity measures.

	Solving daily problems	Distracting negative emotion	Seeking social support
Anxiety	.136**	.202**	−.053
Depression	.071*	.209**	−.095*
Problem-analyzing coping	.245**	−.012	.218**
Risky coping	.111**	.294**	.052
Support-seeking coping	.224**	.088*	.297**

Note. ** p < .001, * p < .05. Covariates include age and gender.

Discussion

This study used a mixed method and explored specific smartphone coping strategies among adolescents. By using the qualitative method, we revealed 10 themes for adolescents’ smartphone coping strategies. Based on the qualitative materials and quantitative methods, we developed the Smartphone Coping Style Scale and determined three smartphone coping styles among adolescents: solving daily problems, distracting negative emotion, and seeking social support.

The developed Smartphone Coping Style Scale supports the coping theory, empirically, which classifies coping into emotion-focused coping and problem-focused coping (Lazarus & Folkman, 1984). Solving daily problems and seeking social support are forms of problem-focused coping, whereas distracting negative emotion is a form of emotion-focused coping. The distracting negative emotion style examined in this study echoes factors, such as socio-emotional coping or social support, proposed by other researchers, who examined general online and smartphone coping (Khoo & Yang, 2021; van Ingen et al., 2016). However, this newly developed component extends the scope of the previous smartphone or online emotional coping by revealing the multifunctional nature of smartphones, i.e., by responding to previous claims that media coping lacks a fine-grained level of measurement (Wolfers & Schneider, 2020). For example, although the previous online coping scale constructs socioemotional coping as involving expressing emotions online or soliciting comfort from others, the distracting negative emotion we proposed went beyond these. We argued that various functions of smartphones could serve as specific ways for emotional relief (e.g., I10. “I play mobile games when I am under pressure or in trouble”).

The newly developed scale extended the traditional problem-focused coping style to a solving-daily-problems style and a seeking-social-support style. For the former problem-focused coping via smartphone or the Internet, researchers have constructed it as making plans or solving problems with the help of the Internet or smartphones (Khoo & Yang, 2021; van Ingen et al., 2016). However, this study shows that seeking social support is also a subcomponent of problem-focused coping, which is different from solving daily problems. This is because the former emphasizes solving problems by using smartphones to seek help from others, whereas the latter emphasizes solving problems by using various features or functions of the smartphone.

Our results are partially consistent with previous studies in terms of the relationship between technology coping and psychological well-being. Previous research on Internet coping has revealed that both problem-focused coping and socioemotional-focused coping through Internet use are negatively related to mental health (van Ingen et al., 2016). This study found that distracting negative emotion is positively related to depression and anxiety. Although they are correlated, it is unclear whether the coping style affects adolescents’ depression and anxiety or, instead, alerts us to the potential risks of using technology to cope, as researchers have argued (Balk & Corr, 2009; Wadley et al., 2020). Seeking social support is negatively related to depression and anxiety, whereas solving daily problems is positively related to anxiety or depression. The former finding is inconsistent with previous research on Internet coping, but the latter is consistent with previous research on the negative association between problem-focused coping and well-being (van Ingen et al., 2016). It may be that seeking social support and solving daily problems advocate different perspectives, although they both emphasize using smartphones to solve problems. The former emphasizes seeking help to solve problems through social connection with the smartphone serving only as a bridge, whereas the latter emphasizes solving problems using smartphone functions.

Meanwhile, the negative correlations between solving daily problems and mental health and the low correlation between seeking social support and mental health may also be that the correlations did not control for confounders such as problematic smartphone use (PSU). The use of smartphones has potential risks of developing PSU, which contributes negatively to mental health (Busch & Mccarthy, 2021). Indeed, the behaviors of using smartphones for coping may mix with the propensity of PSU, because both involve smartphone use. To separate the effect of the confounder, we controlled for PSU in the regression analysis (see Table S1 in supplemental materials). When controlling for PSU, the relationship between solving daily problems on anxiety (β = .051, p > .05) and depression (β = −.027, p > .05) was insignificant, the relationship between seeking social support for anxiety (β = .121, p < .001) and depression (β = .384, p > .001) was very strong. This indicates that solving daily problems is at least a neutral coping style, but more research is needed to confirm this, because the result is based on cross-sectional data.

Furthermore, item 6 (“I use my smartphone to listen to music when I am stressed or in trouble”) was classified as solving daily problems, but item 12 (“When I am upset, I find someone to talk to on my phone”) was considered a distracting negative emotion. However, items 6 and 12 seem to be maladaptive coping styles, because they do not seem to solve the problem or change the current situation. There are many differences between the two items. Listening to music to relieve one’s negative emotions or stress has been widely illustrated in the literature (Witte et al., 2022; Yehuda, 2011). It facilitates mood relief, reduces stress and anxiety, and promotes mental health (Yehuda, 2011). Moreover, there are different types of music available on smartphones from which people can choose to relieve their emotions; this indicates stability and flexibility in dealing with stress by listening to music. However, dealing with negative emotions through interpersonal expression (as indicated by seeking social support) is more likely to be an emotional outpouring and is often fraught with uncertainty. Specifically, interpersonal feedback may be positive, negative, or confusing (see Interpersonal Regulation Interaction Scale, Swerdlow & Johnson, 2022), which is not necessarily conducive to emotion relief and may reduce the adaptability of interpersonal coping in relieving emotions. Thus, listening to music provides individuals with a relatively stable way to relieve stress and prepare for future coping, so that in the EFA result, item 6 is allocated to solving daily problems, and item 12 is allocated to distracting negative emotion.

Implications and limitations

This study implemented both qualitative and quantitative methods to develop a Smartphone Coping Style Scale. First, this scale describes the specific features of smartphone coping among adolescents. Second, this study extends the previous technology-coping framework by dividing problem-focused coping into solving daily problems and seeking social support via smartphones. Seeking social support may serve as an adaptive means to cope with negative emotions or stress. Third, this Smartphone Coping Style Scale shows how to critically understand the advantages and disadvantages of smartphone use among adolescents. Adolescents use both maladaptive and adaptive smartphone coping styles to relieve their negative emotions, seek solutions to problems, and seek social support. Parents and policymakers should encourage adolescents to use adaptive smartphone coping styles to cope with life’s stresses, which may benefit their health. However, this study also presents some limitations. First, the Smartphone Coping Style Scale was developed based on adolescents. More evidence is needed to apply it to other populations, because different populations may prefer to use different functions or features of smartphones to cope with stress. Future studies could focus on different coping aspects among different populations (e.g., adolescents, adults, and an older population). Second, this scale was developed using a Chinese population, so that cultural or regional differences should be considered in future research. The scale could be confirmed using different cultural backgrounds in future studies. Third, the relationship between smartphone coping and anxiety/depression is cross-sectional, and causal inferences should be made based on further longitudinal designs. Future studies might conduct longitudinal designs to reveal the causal relationship between different coping styles and mental health. Fourth, the reliability of how the coping scale is used for testing convergent validity is relatively low; future research may improve this. Finally, listening to music (i.e., item 6) is statistically classified as a coping mechanism for solving problems in this study, which also needs more future examination and confirmation.

Conclusion

The Smartphone Coping Style Scale shows favorable levels of reliability, stability, and validity. The scale measures three dimensions of smartphone coping: solving daily problems, distracting negative emotion, and seeking social support. The scale is reliable for measuring adolescents’ smartphone coping styles. Future research could use the Smartphone Coping Style Scale as three different subscales corresponding to the three dimensions of smartphone coping. When the scale is used in a different country or culture, researchers should translate it appropriately and further confirm its reliability and validity.

Acknowledgments

We thank the anonymous reviewers for constructive comments and suggestions, which have greatly improved the manuscript.

Disclosure statement

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

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/17482798.2023.2239951.

Additional information

Funding

This work was supported by the Major Program of the National Social Science Fund of China under Grant 20&ZD153.

Notes on contributors

Shunsen Huang

Shunsen Huang is currently a doctoral candidate at Beijing Normal University’s State Key Laboratory of Cognitive Neuroscience and Learning. His research utilizes mixed methods to explore various aspects related to technology use. They include problematic smartphone use, digital stress, media content, smartphone coping, and the use of artificial intelligence, specifically focusing on their impact on adolescents’ social development, including mental health, adjustment, and behaviors.

Xiaoxiong Lai

Xiaoxiong Lai, a doctoral candidate at Beijing Normal University’s State Key Laboratory of Cognitive Neuroscience and Learning, focuses on studying the relationship between media use and interpersonal relationships among children and adolescents. His research delves into potential mechanisms and the development of addictive media use behavior. He also explores adolescents’ mental health, growth mindset, and digital literacy.

Li Ke

Li Ke holds the position of Lecturer at the State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University. His research interests lie in child movement development and early screening and intervention for children with neurodevelopmental disorders and specific learning disabilities.

Xubao Qin

Xubao Qin works as a teacher at the High School Affiliated to Southwest University in Chongqing, China. His primary research interests are career development and social media use among adolescents.

Jia Julia Yan

Jia Julia Yan is an Assistant Professor in Child and Family Studies at the University of Tennessee in Knoxville. Her research focuses on two aspects: understanding the behavior and characteristics of fathers and mothers, and the broader contexts that nurture adaptive emotional skills and protect against biological vulnerabilities. She also investigates the factors that collectively and interactively shape parenting behavior and adjustment during the transition to parenthood.

Yumei Xie

Yumei Xie is a teacher at Chongqing Chaoyang Middle School in Chongqing, China. Her research interests encompass technology and education, media use, and adolescents’ development.

Xinran Dai

Xinran Dai is currently pursuing a master’s degree at Beijing Normal University’s State Key Laboratory of Cognitive Neuroscience and Learning. Her research concerns materialism, online interpersonal relationships, and digital media use.

Yun Wang

Yun Wang is a Professor at the State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University. She focuses on various aspects of children’s and adolescents’ mental health and environment. Her research includes examining internal and external behavior, problematic smartphone use, environmental factors influencing child and adolescent development, and school assessments of student learning and development.