Abstract
Background and aims
Problematic smartphone use (PSU) has become an important public health issue in adolescence, and it is imperative to innovate treatments to improve and prolong the effectiveness of interventions. Considering that positive psychology interventions (PPIs) are highly effective in reducing addictive behaviors in adolescents, this study aims to develop and evaluate the effectiveness of an intervention program (PREIP, 8 weeks, 1 h/week) on adolescent PSU within a positive psychology framework.
Methods
Adolescents from China were randomly assigned to the personal resources energized intervention program (PREIP) intervention group (N = 30), the CBT control group (N = 30), and the waitlist (N = 28), which were measured at baseline, post-intervention, and 2-month follow-up.
Results
Participants in the PREIP intervention group had significantly lower levels of PSU, and loneliness, and significantly higher levels of perceived social support and well-being compared to the two control groups (CBT control and waitlist). Furthermore, although participants in the CBT control group were able to significantly reduce PSU symptoms, the improvements in the PREIP group were more sustained over the follow-up period.
Discussion and conclusions
In conclusion, this study supports the positive effects of PREIP on adolescent PSU and explained the underlying mechanisms for improving positive mood, reducing loneliness, and promoting perceived social support.
Introduction
Smartphones have been pervasively used globally, with up to 92.2% reporting daily usage among adolescents in China (CNNIC, 2023). Although smartphone brings substantial convenience, the excessive use or addiction on it, which refers to the problematic smartphone use (PSU), has emerged as a new challenge to population health (Billieux, Maurage, Lopez-Fernandez, Kuss, & Griffiths, 2015; Busch & McCarthy, 2020; Horwood & Anglim, 2018). PSU refers to the uncontrolled/excessive use of smartphones that interferes with individuals' daily life functioning, which could result in negative consequences for health, emotional well-being or job performance (Billieux, 2012; Rumpf, Effertz, & Montag, 2022). Notably, evidence suggested a clear upward trend of PSU trajectory in adolescents aged 10–18 years (Lai et al., 2022). This is closely related to the critical period of adolescence for rapid physiological and psychological development, during which there is a lagging development of cognitive control regions such as the prefrontal cortex compared to socio-emotional regions such as the amygdala (Steinberg, 2008), with consequent the high incidence of emotional as well as interpersonal problems (Elhai, Levine, & Hall, 2019; Monk et al., 2003). Indeed, emotional problems, especially loneliness peak in adolescence (Pinquart & Sorensen, 2001), and these symptoms are particularly manifested in adolescents with immature self-control and poor perception and utilization of social resources, which is consistent with the upward trend of highly indulging in smartphones trajectory in adolescents (Kardefelt-Winther, 2014; Park, 2005). During COVID-19, the social distancing and disease control measures have affected the social connectedness perceptions of adolescents, leading to a gradual worsening of loneliness as the epidemic progressed (Li & Wang, 2020; Tull et al., 2020). A meta-analysis has shown an increase in the prevalence of loneliness during COVID-19, and almost 8.5% adolescents showed extreme loneliness (Ernst et al., 2022; Farrell, Vitoroulis, Eriksson, & Vaillancourt, 2023). The loneliness may induce adolescents to escape reality and turn to smartphones or virtual networks to relieve distress and maintain interpersonal existing relationships (Kardefelt-Winther, 2014; Li, Zhan, Zhou, & Gao, 2021). Given that, enhancing our understanding of adolescent emotional and interpersonal problems after the COVID-19 epidemic and, in particular, how to accessibly and efficiently intervene to attenuate PSU from the process-oriented emotional perspective has become a high priority. At present, as Billieux, Maurage, et al. (2015) suggested, problematic use is distinguished by uncontrolled behaviors leading to adverse outcomes in daily life. Studies available argued that problematic mobile phone use may not be qualified as a true addiction due to the lack of clear diagnostic criteria, insufficient neurobiological evidence supporting key features of addiction, and a scarcity of longitudinal studies and relevant case analyses (Billieux, Maurage, et al., 2015; Panova & Carbonell, 2018). Also, it is essential to note that researchers should be aware not to over-pathologize daily life behaviors (Billieux, Schimmenti, Khazaal, Maurage, & Heeren, 2015). In this study, we used the term “PSU” to describe behaviors that may not reach the same level of impairment as addiction, but involve excessive use, which provides a more flexible framework for discussing related issues.
Although encouraging supports were found in PSU interventions available (Han, Seo, Hwang, Kim, & Han, 2020; Yeun & Han, 2016), the strength of the effects tends to be small to moderate and limited in feasibility. Traditional interventions in treating PSU typically involve a substantial focus on negative aspects and how to reduce them in daily life with an outcome-oriented attitude (Wood & Tarrier, 2010). Specifically, more work is needed to accelerate the process-oriented and explore how mediating emotions and other covert psychological experiences influence behaviors, which could help generalize ameliorating problematic behaviors from in-session to out-of-session contexts and keep long-term effects (Corey, 2021; Vowles & McCracken, 2008). Currently, one approach to optimize treatments available is to focus on the positive strengths of individuals in positive psychological interventions (Heintzelman, Kushlev, & Diener, 2023). Emerging findings highlight that positive factors could not only prevent distress but also buffer the effects of negative life events on distress (Wood & Tarrier, 2010). It is conspicuously manifested in the treatment of addictive behaviors. In this context, by enhancing resilience factors to reshape the meaning of environmental situations, the motivation for addiction can be effectively mitigated (Li, Niu, & Mei, 2017; Wang, Zhang, & Kang, 2018). With specific regard to adolescents, the high incidence of behavioral addictions might be ascribed to the significant chasm between their social relationship fabric and their elevated anticipations (Zhuang, Liu, & Liu, 2017). Namely, the ineptitude to perceive adequate social support and the unmet relationship needs precipitate PSU. Moreover, positive psychology interventions can fully engage with the potential and autonomy of adolescents, while simultaneously promoting positive affective, cognitive, and behavioral dimensions (Schueller & Parks, 2014). These interventions have exhibited high levels of client contentment and have maximized the prospects for both accessibility and sustainable follow-up results (Bolier et al., 2013; Kahler et al., 2014; Meyer, Johnson, Parks, Iwanski, & Penn, 2012). In contrast, current psychological treatment practices rely on external guidance to moderate adolescent cognition and behaviors (Han et al., 2020; Yeun & Han, 2016), emphasizing the guiding role of the intervention implementer while neglecting basic psychological needs satisfaction, which is prone to high dropout as well as relapse rates (Chaves, Lopez-Gomez, Hervas, & Vazquez, 2019; Heyne, 2022). Recognizing the possible limitations, this study highlighted the significance of advantages and growth concepts of positive psychology and comprehensively considered the emotional and interpersonal in the prevention and treatment of PSU. Based on this, the Personal Resources Energized Intervention Program (PREIP) was built to dilute loneliness, facilitate perceived social support, and reduce PSU through using positive interventions to influence the emotion regulation process and expand the cognitive scope to reevaluate interpersonal events. Further, we fully tap into supportive resources with optimism and positivity, and activate enduring positive personal resources in the process of accumulating meaningful and positive experiences, with the ultimate goal of reducing PSU and enhancing overall positive functioning (Allen, Romate, & Rajkumar, 2021; Schueller & Parks, 2014; Stone & Schmidt, 2021).
Theoretical framework
In recent years, positive psychological interventions (PPIs) have been proposed to target strengthening individual positive resources and promoting positive emotions (Bolier et al., 2013; Hendriks, Schotanus-Dijkstra, Hassankhan, de Jong, & Bohlmeijer, 2020; Parks & Biswas-Diener, 2013; Sin & Lyubomirsky, 2009). The broaden-and-build model of positive emotions embodies the mechanism of positive emotions, such as contentment, happiness, and hope, which may not only broaden people's momentary thought-action repertoires but also build their enduring personal resources (e.g., social support), from which, in turn, broaden habitual modes of thinking or acting and facilitate psychological well-being (Boehm & Lyubomirsky, 2009; Fredrickson, 1998; Lyubomirsky, King, & Diener, 2005). In addition, a meta-analysis has indicated that positive emotions could create recurring cycles of urges to play with, explore, and savor our loved ones, feeling care and support and creating the urge to explore, take in new information and experiences, and expand the self in the process (Quoidbach, Mikolajczak, & Gross, 2015). The reason may be that positive emotions could serve as opportunities to satisfy basic psychological needs for autonomy, relatedness, and competence, moderating the adverse effects of negative emotions, which, in turn, broaden cognition flexibility and facilitate psychological well-being (Amonoo et al., 2021; Fredrickson, 2001). Given that, the PREIP proposed that positive emotions might represent a useful tool to reduce loneliness and improve their perceived social support, and have the potential to stimulate their durable positive personal resources to drive individuals to adopt more appropriate alternative activities to replace PSU.
Moreover, guided by the broaden-and-build model of positive emotions theory, enhancing positive emotions could help individuals effectively dilute their negative emotions, such as loneliness, and further radiate to their cognitive (e.g., perceiving social support) and behavioral (e.g., PSU) aspects. A meta-analysis that elucidated the effective mechanism of PPIs found evidence for the process model of emotion regulation in maximizing positive emotions with various emotion regulation strategies during positive emotion enhancement (i.e., situation selection, situation modification, attentional deployment, cognitive change, and response modification) (Quoidbach et al., 2015). Thus, based on the broaden-and-build model of positive emotions and the process model of emotion regulation, the PREIP intervention aimed to alleviate negative emotions by incorporating multiple skills, such as savoring (Straszewski & Siegel, 2018) to motivate adolescents to share positive experiences with others actively and positively, and to benefit from the interpersonal interaction to improve PSU and psychological well-being.
The emotional and interpersonal targets of the PREIP
Psychological treatments may not only need to consider adequate theoretical foundations but also the adaptative population and mechanisms in treatment operations (Dunn et al., 2015; Kraemer, Wilson, Fairburn, & Agras, 2002), which could facilitate a longer-lasting effect and enhance treatment structure (Green, 2015). With the transition to the critical period of physiological and psychological development (Schulenberg, Maggs, & Hurrelmann, 1997), the amygdala of adolescents becomes highly activated towards significant emotional stimulation, and they show increased sensitivity to negative emotional cues (Nelson, Jarcho, & Guyer, 2016), in which loneliness peaks during adolescence (Pinquart & Sorensen, 2001; Twenge, 2021). Prior work has emphasized that during adolescence loneliness is an important precipitant of PSU development (Prinstein, Guerry, Browne, & Rancourt, 2009). Adolescents with a high level of loneliness lack social interaction experiences and skills (Jones, 1981), and may be at increased risk for using anonymous tools (e.g., mobile phones, Kardefelt-Winther, 2014) to escape from irritability (Tokunaga & Rains, 2010). The compensatory internet use theory posits that PSU function as coping mechanisms to escape negative feelings (i.e., loneliness) (Kardefelt-Winther, 2014). Also, based on the social compensation hypothesis, smartphones provide individuals who experience loneliness or discomfort with an alternative. Loneliness could drive adolescents towards excessive smartphone use as a way to increase social interaction, fulfill need for belonging and temporarily mitigate feelings of social isolation (O’ Day & Heimberg, 2021; Schneider & Amichai-Hamburger, 2010). The Interaction of Person-Affect-Cognition-Execution model (I-PACE) also provides a robust framework for understanding the impact of loneliness on the development of PSU (Brand et al., 2016, 2019). The model suggests that individuals' loneliness may be alleviated through smartphone use, which in turn influences their appraisal of the outcomes of smartphone use and further decision processes, and perceived need fulfillment leads to the establishment and intensification of PSU (Li et al., 2021). As regards the opposite direction of influence, also plausible is that PSU may further exacerbate loneliness in adolescents (Atroszko et al., 2018; Williams, Lewin, & Meshi, 2024). Excessive use of smartphone may further impair the psychosocial functioning of adolescents, making them more avoidant of real-life interpersonal interactions and supplanting beneficial social activities. Although PSU may provide temporary solace in the short term, it diminishes the sense of belonging of adolescents in the long run, which leads to increased loneliness in real life. Thus, an interaction cycle of mutual reinforcement forms between loneliness and PSU, which intensifies their negative impact over time (Andreassen & Pallesen, 2014; Koo & Kwon, 2014). In light of this, focusing on loneliness may be a practical and process-oriented treatment alternative for adolescent PSU. The PREIP was proposed to dilute loneliness through enhancing positive emotions and to target positive emotions and cognitions, which in turn provide a mild emotional atmosphere and increase well-being.
Apart from emotional factors, the PREIP was also proposed to target interpersonal factors. On the one hand, in the Chinese filial piety context, the typical parenting strategies such as parental psychological control are often used to make children more dutiful, however, the guilt induction, love withdrawal and authoritative arbitrariness included in it may reflect child obedience and sacrifices autonomy to do as parents' desire (Barber, 1996; Chao, 2000; Rao, McHale, & Pearson, 2003; Soenens & Vansteenkiste, 2010). When stepping into the formative period of increasing autonomy and parent-child detachment, adolescents could experience intensified internal conflicts of self-development beyond the family and obedience to their parents, predisposing them to develop internalizing and externalizing problems, and escape maladjusted psychological feelings through PSU behaviors (McElhaney, Allen, Stephenson, & Hare, 2009; Pettit, Laird, Dodge, Bates, & Criss, 2001). Indeed, however, previous typical interventions such as cognitive-behavior therapy (CBT) often ignored the autonomy needs of adolescents, which may make them resist therapists same as the role of their parents and teachers, and increase interventions difficulties and burdens (Heyne, 2022; Malinauskas & Malinauskiene, 2019). In contrast, PREIP provided empirically based guidelines for addressing the autonomy development of adolescents by building adaptative resources and promoting positive emotions. In addition, based on the self-determination theory, adolescents have need to develop autonomy and self-regulate their experiences and actions. And the excessive engaging behaviors of adolescents on smartphone arises from unmet needs for autonomy, competence and relatedness (Kardefelt-Winther, 2014; Su, Larsen, Cousijn, Wiers, & Van Den Eijnden, 2022). These self-defeating emotional and cognitive patterns are associated with problematic psychosocial outcomes, and adolescents are at high risk to engage in PSU behaviors to alleviate feelings of anxiety, negative emotions, and a lack of control (Horwood & Anglim, 2019). In view of this, through making adolescents experience high levels of autonomy need satisfaction, the PREIP could provide encouraging and comprehensive support for adolescent PSU treatment.
On the other hand, seeking support from parents and peers can cushion the negative impact of risk factors (Qualter, Brown, Munn, & Rotenberg, 2010; Sheng, Wang, Zhou, Peng, & Xin, 2022) and can also effectively relieve negative emotions such as loneliness (Asher & Paquette, 2003). The expectations and evaluations of adolescents about adequate support from family, peers, and others in times of need refer to perceived social support (Barrera, 1986; Zimet, Dahlem, Zimet, & Farley, 1988), which represents the positive personal resources as well as resilient protective factors. Perceived social support is beneficial for adolescents to buffer from the negative effects of risk factors, which may be conducive to stimulating the intrinsic potential of adolescents to contribute to longer maintenance outcomes (Quaglieri et al., 2021; Sheng et al., 2022). In light of this, the PREIP could help adolescents activate and develop personal resources and actively perceive more supportive resources to alleviate PSU and maintain long-term well-being outcomes (Harp & Neta, 2023; Lakey & Orehek, 2011).
The current study
This study aimed to test the effects of PREIP on enhancing positive emotion, diluting loneliness, and improving social support perception among adolescents with PSU, and to assess the effects of PREIP on PSU and psychological well-being compared with control groups (CBT control and waitlist). The central hypothesis of the current set of studies was that adolescents in the PREIP group would report less PSU and loneliness, and more social support perception and psychological well-being. Also, we hypothesize that the improvements in the PREIP may be more valuable with a follow-up period than control groups.
Methods
Trial registration
The randomized controlled trial in this study was pre-registered on the Chinese Clinical Trial Registry (ChiCTR2200066329).
Participants and procedures
A randomized controlled trial (RCT) that explored the effects of PREIP on adolescent PSU was conducted in this study. The data was collected from May 2023 to August 2023. The assessment was self-reported by participants completing questionnaires before the intervention, at the end of the intervention (week 8), and at a 2-month follow-up after the intervention (week 16).
Online advertising was used to recruit primary and secondary school students interested in the project, and adolescents who expressed interest in participating in the trial completed an online screening survey. All participants were screened for consultation, which was conducted by clinical psychologists who had received professional training with DSM-5. Inclusion criteria were as follows: (1) adolescents aged 10–16 years, (2) having a mobile phone addiction index of more than 40 points, (3) being willing to provide written consent, and (4) obtaining a guardian's written informed consent. Participants were excluded from the intervention if: (1) were in counseling or psychotherapy, (2) had a structured clinical interview for DSM-5 confirmed mental disorders diagnosis, such as major depression disorder and generalized anxiety disorder, (3) taking psychotropic drugs, (4) having serious and unstable physical illness, and (5) reporting suicidal thoughts, including suicide plans or attempts. These exclusion criteria were selected because they indicated the need for a higher level of care.
The prior power analysis with G*Power 3.1 (Faul, Erdfelder, Buchner, & Lang, 2009) was used to assess the sample size needed for detecting a medium effect size of a 3 (group: PREIP vs. CBT-control vs. Waitlist) × 3 (time: pre vs. post vs. 2-month follow-up) mixed design and at least 54 participants were required (d = 0.25, α = 0.05, and power set at 0.95). The participants number in this study met the standard. 457 adolescents were recruited from primary and secondary schools in Shandong, China through online advertising in the baseline measurement. Written informed consent was provided in this study for the 114 adolescents who participated in the screening and met the criteria. A total of 86.8% (N = 99) of participants agreed to participate in the 8-week intervention voluntarily. And 11 participants dropped out during the intervention. Finally, there were 88 participants included for analysis. Per-protocol analysis was used in this study.
First, adolescents interested in this study completed an MPAI questionnaire, and those with scores above 40 were invited to take a baseline measurement. Participants would not only be explicitly informed of the purpose and process of this study but also be informed that the study is anonymous and they could withdraw at any time. The trial coordinators randomly assigned participants to the PREIP-intervention group (PREIP-IG, n = 33, 16 females), the CBT-control group (CBT-CG, n = 33, 16 females), and waitlist (W-CG, n = 33, 15 females) in a ratio of 1:1:1 using Excel random number table generation. Then, after the intervention began, participants in the PREIP-IG received one-on-one personal resources energized interventions once a week for about 60 min. Participants in the CBT-CG received a weekly CBT intervention about 60 min in one-on-one format. The W-CG was selected to establish whether the PREIP was more beneficial than no intervention. Specific participation in the intervention process is shown in Fig. 1. All measurements were done by independent evaluators who were not aware of the intervention. The final sample included 88 adolescents aged 10–16 years (M = 12.86 years, SD = 2.07), with 50% female. The sample consisted of 44.3% only child. For a detailed characteristic of randomized groups, see Table 1.
Participant flow from enrollment to analysis
Citation: Journal of Behavioral Addictions 2025; 10.1556/2006.2025.00016
Baseline characteristics of the participants (N = 88)
| Participants' characteristics | PREIP-IGa (n = 30) | CBT-CGb (n = 28) | W-CGc (n = 30) | Test statistics |
| Age (years), M (SD) | 12.80 (1.84) | 12.50 (1.99) | 13.27 (2.16) | F(2, 85) = 1.08, p = 0.346 |
| Gender, n (%) | χ2(2, N = 88) = 0.28, p = 0.871 | |||
| Male | 15 (50.0%) | 13 (46.4%) | 16 (53.3%) | |
| Female | 15 (50.0%) | 15 (53.6%) | 14 (46.7%) | |
| School stage, n (%) | χ2(2, N = 88) = 3.48, p = 0.176 | |||
| Primary school | 18 (60.0%) | 15 (53.6%) | 11 (36.7%) | |
| Junior middle school | 12 (40.0%) | 13 (46.4%) | 19 (63.3%) | |
| Only child or not, n (%) | χ2(2, N = 88) = 0.61, p = 0.739 | |||
| Only child | 13 (43.3%) | 14 (50.0%) | 12 (40.0%) | |
| Non-only children | 17 (56.7%) | 14 (50.0%) | 18 (60.0%) | |
| Residence, n (%) | χ2(2, N = 88) = 2.74, p = 0.254 | |||
| Country | 14 (46.7%) | 19 (67.9%) | 16 (53.3%) | |
| Town or City | 16 (53.3%) | 9 (32.1%) | 14 (46.7%) |
aPREIP-IG = PREIP Intervention Group.
bCBT-CG = CBT Control Group.
cW-CG = Waitlist Control Group.
***p < 0.001 (F test and chi-square test).
Intervention protocol
The PREIP was 8-week, 1-hour, once-weekly, one-to-one intervention developed by the study authors, who are researchers trained in counseling and therapy, mental health promotion, and statistical data analysis. Therapists were psychological professionals that had been well trained in the PREIP project. Firstly, PREIP helped adolescents improve their abilities to understand emotional states, identify and name different emotional response forms. Secondly, adolescents were encouraged to experience diverse emotions by using various methods that could enhance positive emotions (Jacobson, Martell, & Dimidjian, 2001), while understanding and accepting negative emotions such as loneliness (Humphrey, Szoka, & Bastian, 2021). Thirdly, combined with empathy and cognitive adjustment skills (Rigby & Huebner, 2005; Sanjuán, Pérez, Rueda, & Ruiz, 2008), adolescents could realize the power of social support in their environment, feel that their views of emotions and smartphone use were biased, and enhance the courage to change. Finally, through diary exercises, behavioral activation and promotion, adolescents were helped to choose positive events that could make them feel pleasure and happy, and were encouraged to try these activities instead of using smartphones. PREIP specifically focused on the following topics, sequentially, titled as (1) establishing counseling relationship and introducing PREIP; (2) understanding and distinguishing emotions; (3) experiencing positive emotions; (4) enhancing positive emotions; (5) maintaining positive emotions; (6) cognitive adjustment; (7) positive expression; (8) reviewing and future planning. A brief description of the intervention process is given in Table 2.
Session-by-session Description of the PREIP for early adolescents
| Session | Topic | Brief description of activities |
| 1 | establishing counseling relationship and introducing PREIP | (1) establishing contracts and obtain informed consent; (2) collecting information of participants and introducing the contents and goals of PREIP; (3) discussing the causes of PSU and the emotions associated with it. |
| 2 | understanding and distinguishing emotions | (1) reviewing the causes of PSU and the emotions associated with it; (2) understanding, distinguishing and naming complex emotions; (3) exploring the plasticity of emotion. |
| 3 | experiencing positive emotions | (1) reviewing the identification and classification emotions associated PSU; (2) recalling experiences in the past that trigger positive emotions; (3) keeping detailed records of each happiness experience in a journal and rate them on a 1–10 number scale based on the positive emotions experienced. |
| 4 | enhancing positive emotions | (1) reviewing diary and discussing the activities that made them happy; (2) recounting positive events that they recorded in diary and thinking about how the duration of the positive events affects their mood; (3) breaking down positive events into smaller units and extending the duration of positive event components. |
| 5 | maintaining positive emotions | (1) reviewing diary and feelings of more prolonged positive events; (2) recalling and sharing positive experiences as detailed as possible and perceiving the support and encouragement from the counselor and trying to share positive experiences with others; (3) taking a few minutes to focus entirely on enjoyable activities that they would normally rush through. |
| 6 | cognitive adjustment | (1) reviewing how it feels to share positive experiences and fully focusing on enjoyable activities; (2) experiencing its role in positive events and changing its attribution to internal, stable, and global factors; (3) feeling empathy and rethinking the surrounding supportive resources. |
| 7 | positive expression | (1) reviewing new ways of attributing to positivity and discussing the supportive resources they perceive; (2) sharing positive events about themselves with those who make them feel supported; (3) being encouraging to replacing the urge to use your phone with the things that bring them a high level of happiness that are flagged in their experiential happiness journal. |
| 8 | reviewing and future planning. | (1) reviewing how it feels to share positive events with those who support them and how it feels to replace PSU with activities that bring happiness; (2) reviewing the highlights of the process; (3) choosing their favorite activity according to the diary, extending the experience time by enlarging the details, then devoting themselves entirely to this activity, and actively experience their role in it, and sharing it with supportive friends. |
Control protocol
In this study, the CBT-CG and W-CG were set to compare the intervention effect with the PREIP-IG. Among them, CBT-CG was set in consideration of the fact that CBT, a structured, fast-acting treatment approach, has more empirical support and high acceptance in behavioral addiction intervention, and it has shown advantage in the intervention of information technology-based addiction (Han et al., 2020; Stevens, King, Dorstyn, & Delfabbro, 2019; Xu et al., 2021; Yeun & Han, 2016). In the CBT-CG, firstly, PSU was introduced to participants and its adverse consequences on physical and psychological aspects were discussed. Secondly, the motivation of participants' frequent use of smartphones and their related unreasonable belief systems were explored. Thirdly, alternative reasonable beliefs were developed by challenging unreasonable beliefs, psychological education and assigning homework to help them carry out cognitive reconstruction. Finally, behavioral activation helped participants find alternative behaviors to replace smartphone use, thereby reducing PSU. During the intervention, participants in the CBT-CG were asked to monitor their thoughts, feelings, and behaviors to prevent PSU to relapse and to acquire new coping skills. Participants in the W-CG completed surveys at parallel time points and were offered the PREIP after the follow-up assessment.
Measures
All self-reported measures were based on published guidelines and measures from previous studies. The main outcome indicators in this study were PSU, loneliness and PSS, while the secondary outcome measures were emotion regulation ability, positive affect, negative affect and life satisfaction. The questionnaires used in this study were the same for the three evaluation indicators.
Primary outcome measures
Mobile Phone Problem Usage Scale-10 (MPPUS-10)
MMPUS-10 was proposed by Bianchi and Phillips (2005) and adapted by Foerster, Roser, Schoeni, and Röösli (2015) and Zhuang et al. (2017), which included 10 items (e.g., my friends and family have complained about my smartphone use). All items were rated on a 5-point Likert scale from 1 (not true at all) to 5 (extremely true). Higher scores indicated higher levels of PSU. The Cronbach's α coefficient in this study was 0.86. The results of the confirmatory factor analysis showed that the one-factor model fitted well (χ2/df = 4.43, CFI = 0.95, TLI = 0.92, SRMR = 0.04).
Mobile Phone Addiction Index (MPAI)
MPAI was proposed by Leung (2008), which included 17-items (e.g., your friends and family complained about your use of the mobile phone). All items were rated on a 5-point Likert scale (1 = not at all, 5 = always). Higher scores indicated higher levels of PSU. The Cronbach's α coefficient in this study was 0.90. The results of the confirmatory factor analysis showed that the four-factor model fitted well (χ2/df = 3.53, CFI = 0.93, TLI = 0.91, SRMR = 0.05).
Children's Loneliness Scale (CLS)
CLS was proposed by Asher, Hymel, and Renshaw (1984), which included 16 items measured loneliness and 8 items about personal interests. All items were rated on a 5-point Likert scale (1 = not true at all, 5 = always true). Higher scores indicated higher levels of loneliness. The Cronbach's α coefficient in this study was 0.93. The results of the confirmatory factor analysis showed that the one-factor model fitted well (χ2/df = 2.62, CFI = 0.97, TLI = 0.94, SRMR = 0.04).
Perceived Social Support Scale (PSSS)
PSSS was proposed by Zimet et al. (1988), which included 12 items (e.g., I can talk about my problems with my friends). All items were rated on a 7-point Likert scale (1 = very strongly disagree, 7 = very strongly agree). Higher scores indicated higher levels of perceived social support. The Cronbach's α coefficient in this study was 0.93. The results of the confirmatory factor analysis showed that the three-factor model fitted well (χ2/df = 2.95, CFI = 0.95, TLI = 0.94, SRMR = 0.04).
Secondary outcome measures
Adolescents' Emotion Regulation Questionnaire (AERQ)
The AERQ was proposed by Gross and Levenson (1993), which included 10 items. All items were rated on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Higher scores indicated higher levels of emotion regulation. The Cronbach's α coefficient in this study was 0.85. The results of the confirmatory factor analysis showed that the two-factor model fitted well (χ2/df = 2.86, CFI = 0.96, TLI = 0.95, SRMR = 0.05).
Positive Affect and Negative Affect Scale (PANAS)
The PANAS was proposed by Watson (1988), which included 20 items (e.g., interested). All items were rated on a 5-point Likert scale (1 = very slightly/not at all, 5 = extremely). The former 10 items refer to positive emotions and the latter 10 items refer to negative emotions. The Cronbach's α coefficient in this study was 0.79. The results of the confirmatory factor analysis showed that the two-factor model fitted well (χ2/df = 2.24, CFI = 0.93, TLI = 0.91, SRMR = 0.06).
Satisfaction with Life Scale (SWLS)
SWLS was proposed by Diener, Emmons, Larsen, and Griffin (1985), which included 5 items (e.g., In most ways my life is close to my ideal). All items were rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Higher scores indicated higher levels of satisfaction with life. The Cronbach's α coefficient in this study was 0.90. The results of the confirmatory factor analysis showed that the one-factor model fitted well (χ2/df = 9.05, CFI = 0.96, TLI = 0.92, SRMR = 0.03).
Data analyses
All analyses were performed with SPSS 26.0. All the significance tests were conducted by bilateral test, and the significance level was α = 0.05. Descriptive statistics were first conducted to examine demographic characteristics. Secondly, repeated measurement ANOVA and Bonferroni correction were performed for primary and secondary outcome measures. Univariate ANOVA and Chi-square tests were used to ensure that there were no significant differences of demographic variables and primary and secondary outcome measures. Only adolescents with completing information from three measurements were included in analyses, that is to say, analyses were not intention-to-treat.
Ethics
Procedures of the randomized trial in this study involving human participants comply with the ethical standards of the Shandong Normal University Academic Committee, as well as the 1964 Helsinki Declaration and its subsequent amendments. Informed consent was obtained for this study from all adolescents participating in the study.
Results
Preliminary analysis
Prior to the main analysis, a series of variance analysis and Chi-square test were conducted to test whether participants in the PREIP-IG, CBT-CG and W-CG differ regarding demographic characteristics (see Table 1).
Intervention effects on primary outcomes (see Table 3)
Descriptive statistics for primary and secondary outcome indicators as a function of condition and time
| Time point | M (SD) | Time | Group | Time × Group | |||
| PREIP-IG (n = 30) | CBT-CG (n = 28) | W-CG (n = 30) | |||||
| MPPUS-10 | aT1 | 34.30 (9.08) | 32.86 (6.86) | 33.60 (5.58) | F(2, 85) = 41.17, p < 0.001***, ηp2 = 0.33 | F(2, 85) = 9.58, p < 0.001***, ηp2 = 0.18 | F(2, 85) = 11.31, p < 0.001***, ηp2 = 0.21 |
| bT2 | 26.07 (9.98) | 23.50 (6.16) | 33.77 (4.64) | ||||
| cT3 | 22.30 (9.61) | 24.25 (10.52) | 33.23 (5.52) | ||||
| MPAI | T1 | 53.57 (11.33) | 53.68 (10.10) | 54.77 (10.28) | F(2, 85) = 48.27, p < 0.001***, ηp2 = 0.36 | F(2, 85) = 19.12, p < 0.001***, ηp2 = 0.31 | F(2, 85) = 15.07, p < 0.001***, ηp2 = 0.26 |
| T2 | 39.23 (14.66) | 34.25 (10.01) | 55.90 (10.18) | ||||
| T3 | 35.13 (13.87) | 36.18 (15.47) | 55.40 (10.72) | ||||
| Loneliness | T1 | 40.27 (12.66) | 41.21 (9.82) | 38.97 (10.00) | F(2, 85) = 13.26, p < 0.001***, ηp2 = 0.14 | F(2, 85) = 6.86, p = 0.002**, ηp2 = 0.14 | F(2, 85) = 9.45, p < 0.001***, ηp2 = 0.18 |
| T2 | 30.10 (10.74) | 36.82 (12.34) | 41.83 (7.76) | ||||
| T3 | 27.20 (8.01) | 36.68 (11.97) | 40.37 (8.45) | ||||
| Perceived social support | T1 | 60.03 (14.08) | 60.14 (9.68) | 59.73 (9.55) | F(2, 85) = 9.85, p = 0.001**, ηp2 = 0.10 | F(2, 85) = 3.35, p = 0.040*, ηp2 = 0.07 | F(2, 85) = 3.73, p = 0.018*, ηp2 = 0.08 |
| T2 | 68.10 (14.08) | 62.04 (10.98) | 59.57 (7.96) | ||||
| T3 | 68.73 (8.82) | 62.75 (11.02) | 61.30 (9.27) | ||||
| Emotion regulation ability | T1 | 62.50 (11.40) | 61.57 (10.64) | 60.23 (9.04) | F(2, 85) = 1.07, p = 0.330, ηp2 = 0.01 | F(2, 85) = 5.47, p = 0.006**, ηp2 = 0.11 | F(2, 85) = 2.04, p = 0.112, ηp2 = 0.05 |
| T2 | 66.73 (9.96) | 64.29 (11.94) | 57.73 (9.38) | ||||
| T3 | 67.23 (10.68) | 62.36 (7.55) | 59.10 (7.20) | ||||
| Positive affect | T1 | 31.77 (6.76) | 34.11 (6.60) | 31.07 (5.75) | F(2, 85) = 0.20, p = 0.777, ηp2 = 0.00 | F(2, 85) = 4.63, p = 0.012*, ηp2 = 0.10 | F(2, 85) = 5.74, p = 0.001**, ηp2 = 0.12 |
| T2 | 34.40 (5.65) | 32.18 (5.65) | 29.43 (5.62) | ||||
| T3 | 35.97 (6.96) | 30.89 (5.58) | 30.37 (5.14) | ||||
| Negative affect | T1 | 23.00 (6.36) | 24.64 (6.88) | 23.23 (7.41) | F(2, 85) = 14.46, p < 0.001***, ηp2 = 0.15 | F(2, 85) = 3.29, p = 0.042*, ηp2 = 0.07 | F(2, 85) = 4.07, p = 0.005**, ηp2 = 0.09 |
| T2 | 18.33 (6.45) | 21.50 (5.77) | 24.07 (6.82) | ||||
| T3 | 17.93 (6.95) | 20.39 (5.74) | 22.70 (5.57) | ||||
| Life satisfaction | T1 | 24.23 (7.40) | 23.32 (5.68) | 21.93 (5.40) | F(2, 85) = 8.89, p < 0.001***, ηp2 = 0.10 | F(2, 85) = 6.96, p = 0.002**, ηp2 = 0.14 | F(2, 85) = 4.02, p = 0.005**, ηp2 = 0.09 |
| T2 | 28.20 (4.94) | 24.21 (6.53) | 20.73 (5.65) | ||||
| T3 | 27.87 (4.74) | 25.61 (7.37) | 22.80 (4.79) | ||||
aT1 = pre-intervention.
bT2 = post-intervention (8 week).
cT3 = 2-month follow-up.
*p < 0.05.
**p < 0.01.
***p < 0.001.
For MPPUS-10, there was a significant main effect in time, F (2, 84) = 41.17, p < 0.001, ηp2 = 0.33. There was a significant main effect in group, F (2, 85) = 9.58, p < 0.001, ηp2 = 0.18. The interaction of time × group was significant, F (4, 170) = 11.31, p < 0.001, ηp2 = 0.21. After intervention, the differences between the three groups were significant (p < 0.001). MPPUS-10 scores of the PREIP-IG and the CBT-CG were significantly lower than those of W-CG (p < 0.001). At 2-month follow-up, the differences between the three groups were significant (p < 0.001). MPPUS-10 scores of the PREIP-IG were lower than those of the CBT-CG (p > 0.05), with a continuing downward trend.
For MPAI, there was a significant main effect in time, F (2, 84) = 48.28, p < 0.001, ηp2 = 0.36. There was a significant main effect in group, F (2, 85) = 19.12, p < 0.001, ηp2 = 0.31. The interaction of time × group was significant, F (4, 170) = 15.07, p < 0.001, ηp2 = 0.26. At post-intervention, the differences between the three groups were significant (p < 0.001). MPAI scores of the PREIP-IG and the CBT-CG were significantly lower than those of W-CG (p < 0.001). At 2-month follow-up, the differences between the three groups were significant (p < 0.001). MPAI scores of the PREIP-IG were lower than those of the CBT-CG (p > 0.05), and showed a continuing downward trend.
For loneliness, there was a significant main effect in time, F (2, 84) = 13.26, p < 0.001, ηp2 = 0.14. There was a significant main effect in group, F (2, 85) = 6.86, p < 0.01, ηp2 = 0.14. The interaction of time × group was significant, F (4, 170) = 9.45, p < 0.001, ηp2 = 0.18. At post-intervention, the differences between the three groups were significant (p < 0.001). Loneliness scores of the PREIP-IG were significantly lower than those of the CBT-CG (p < 0.05) and the W-CG (p < 0.001). At 2-month follow-up, the differences between the three groups were significant (p < 0.001). Loneliness scores of the PREIP-IG were significantly lower than those of the CBT-CG (p < 0.01) and the W-CG (p < 0.001).
For perceived social support, there was a significant main effect in time, F (2, 84) = 9.85, p < 0.001, ηp2 = 0.10. There was a significant main effect in group, F (2, 85) = 3.35, p < 0.05, ηp2 = 0.07. The interaction of time × group was significant, F (4, 170) = 3.73, p < 0.05, ηp2 = 0.08. At post-intervention, the differences between the three groups were significant (p < 0.001). PSS scores of the PREIP-IG were significantly higher than those of the CBT-CG (p < 0.05), and significantly higher than those of W-CG (p < 0.001). At 2-month follow-up intervention, the differences between the three groups were significant (p < 0.05). PSS scores of the PREIP-IG were higher than those of the CBT-CG (p > 0.05), and significantly higher than those of W-CG (p < 0.05).
Intervention effects on secondary outcomes
For emotion regulation ability, there was a significant effect of group, F (4, 170) = 5.47, p < 0.01, ηp2 = 0.11. Bonferroni post hoc analyses showed that AERQ scores of the PREIP-IG were higher than those of the CBT-CG (p > 0.05), and significantly higher than those of W-CG (p < 0.05). The differences between the CBT-CG and W-CG were not significant (p > 0.05).
For positive affect, there was a significant effect of the group main effect, F (2, 85) = 4.63, p < 0.05, ηp2 = 0.10 and the time × group interaction, F (4, 170) = 5.74, p < 0.01, ηp2 = 0.12. At post-intervention, the differences between the three groups were significant (p < 0.01). PA scores of the PREIP-IG were higher than those of the CBT-CG (p > 0.05), and significantly higher than those of W-CG (p < 0.01). The differences between the CBT-CG and W-CG were not significant (p > 0.05). At 2-month follow-up intervention, the differences between the three groups were significant (p < 0.01). PA scores of the PREIP-IG were significantly higher than those of the CBT-CG (p < 0.01), and significantly higher than those of W-CG (p < 0.01). The differences between the CBT-CG and W-CG were not significant (p > 0.05).
For negative affect, there was a significant main effect in time, F (2, 84) = 14.46, p < 0.001, ηp2 = 0.15. There was a significant main effect in group, F (2, 85) = 3.29, p < 0.05, ηp2 = 0.07. The interaction of time × group was significant, F (4, 170) = 4.07, p < 0.01, ηp2 = 0.09. At post-intervention, the differences between the three groups were significant (p < 0.01). NA scores of the PREIP-IG were lower than those of the CBT-CG (p > 0.05), and significantly lower than those of W-CG (p < 0.01). At 2-month follow-up, the differences between the three groups were significant (p < 0.05). NA scores of the PREIP-IG were lower than those of the CBT-CG (p > 0.05), and significantly lower than those of W-CG (p < 0.05).
For life satisfaction, there was a significant main effect in time, F (2, 84) = 8.89, p < 0.001, ηp2 = 0.10. There was a significant main effect in group, F (2, 85) = 6.96, p < 0.01, ηp2 = 0.14. The interaction of time × group was significant, F (4, 170) = 4.02, p < 0.01, ηp2 = 0.09. At post-intervention, the differences between the three groups were significant (p < 0.001). SWLS scores of the PREIP-IG were significantly higher than those of the CBT-CG (p < 0.05), and significantly higher than those of W-CG (p < 0.001). At 2-month follow-up intervention, the differences between the three groups were significant (p < 0.01). SWLS scores of the PREIP-IG were higher than those of the CBT-CG (p > 0.05), and significantly higher than those of W-CG (p < 0.01).
Discussion and conclusions
Recently, a growing amount of research has indicated that PSU has repeatedly been linked to depressive symptoms, sleep problems, and poor academic performances in Chinese adolescents (Karabey, Palanci, & Turan, 2023), from which treatments are urgently needed. However, substantial concerns have been raised about the effectiveness of the interventions available. This trial was designed to provide the first evaluation of the effectiveness of a brief positive psychological intervention, known as PREIP, in improving psychological well-being and autonomy development outcomes among adolescents. Improvements in all outcome measures were sustained throughout the treatment period, which highlighted the durability of intervention effects.
The results of this study indicated positive effects of the 8-week intervention on PSU, and the effect also appeared surprising at 2-month follow-up. However, there were no significant differences of MPAI scores between the CBT-CG and PREIP-IG after intervention. The reason may be that the PREIP intervention is process-oriented, which aims at improving multiple aspects of PSU behaviors and related core resilient factors, attending to, amplifying, and extending the duration of positive feelings rather than only directly focusing on symptoms (Bryant & Smith, 2015), and therefore do not show significant differences with the CBT intervention in a short term. However, combined with the results during the follow-up period, there was a consistent downward trend of MPAI scores in the PREIP-IG and a recurrence in the CBT-CG, which demonstrated the advantages of process-oriented interventions. In line with the broaden-and-build model of positive emotions (Fredrickson & Branigan, 2005; Fredrickson & Losada, 2005), the PREIP provides novel findings to help adolescents elicit and elevate positive emotions through flexible cognition and further enhances motivation to prepare for a change in PSU. In contrast, CBT was conducted to reduce maladaptive behaviors through reconstructing irrational beliefs about PSU. Earlier notions pointed that adolescents showed low willingness and even resisted to participate in CBT treatment (Andrade, Felipe, Carvalho, & dos Santos, 2014; Raviv, Vago-Gefen, & Fink, 2009), and meta-analyses further indicated the long-term follow-up effects still need to be validated (Kim & Noh, 2019; Stevens et al., 2019), which was consistent with this study. Overall, PREIP proposed a progressive positive psychology intervention program and spirally provided a “building strengths” attempt for adolescents with PSU.
Based on the three distinct developmental pathways to PSU, the development and maintenance of PSU could be associated with excessive reassurance, impulsiveness, and extraversion (Billieux, 2012; Billieux, Maurage, et al., 2015). The excessive reassurance pathway comprises individuals whose PSU is mainly driven by the necessity to maintain relationships and obtain reassurance from others (Ha, Chin, Park, Ryu, & Yu, 2008; Lu, Katoh, Chen, Nagata, & Kitamura, 2014). As hypothesized, PREIP was effective in reducing loneliness and elevating perceived social support among PSU adolescents, and the effects persisted over time, which indicated that the PREIP intervention was suitable for adolescents whose PSU were mainly driven by excessive reassurance (Folkman & Moskowitz, 2000; Tugade & Fredrickson, 2004, 2007). In addition, positive emotions showed enhancements of social connectedness in this study (Isen, 1990), and adolescents high in positive experiences tend to actively socialize by, for example, sharing pleasant events with others, thereby building strong social relationships with others (Lakey & Orehek, 2011), and alleviating loneliness (Asher & Paquette, 2003). Notably, active listening, empathy, and unconditional positive regard as counseling professionalism as well as key factors in interpersonal relationships (Değerli & Odacı, 2023) are urgently needed for PSU adolescents (Yusni et al., 2020), which could not only contribute to the formation of good therapeutic alliances but also benefit clients by providing them with a healthy model for exploring relationships in the here and now (Stevens, Muran, Safran, Gorman, & Winston, 2007). Clients in PREIP perceive social support from therapists in a safe and comfortable environment, and they can apply this interpersonal model in their daily lives, through which they can further improve their self-concept, and facilitate the development of positive personal resources.
Also, compared with the CBT condition, the PREIP intervention generated significant improvements in secondary outcome measures including positive emotion and life satisfaction, which exerted long-term beneficial effects in adolescent psychological well-being and emotions. This finding supported the growing consensus in psychotherapy that treatment should be more process-oriented, focusing on how emotions and other underlying psychological experiences influence behaviors, which could improve problems more effectively and provide long-term improvements (Corey, 2021; Vowles & McCracken, 2008). Along with caring for the traditional “deficits and problems” model, PREIP also aimed at constructing the “strengths and growth” framework (Lerner, 2015; Wood & Tarrier, 2010), proposing to help adolescents improve problem behaviors such as PSU and further experience increased well-being and meaningful satisfaction. Building on advances in previous research, multi-component positive psychological interventions could provide better benefits in well-being improvement compared with interventions that focused on a single element (Parks, Della Porta, Pierce, Zilca, & Lyubomirsky, 2012; Schueller & Parks, 2016; Sin & Lyubomirsky, 2009). Based on this, PREIP potentially integrated a variety of effective strategies in enhancing positive emotions and a counseling atmosphere. It is also worth noting that participants in this study were recruited through online advertisements, as a systematic review has indicated the effectiveness of online advertising on recruitment rate and cost-effectiveness (Brøgger-Mikkelsen, Ali, Zibert, Andersen, & Thomsen, 2020). The reason for this may be that participants were more willing to change and more motivated to participate than the general population, from which showed reduced attrition from the intervention.
Despite these findings, it is important to acknowledge several key limitations of this study. First, the self-reports used to limit our results, and the social expectations in the measurements could not be ignored. Although compelling evidence has suggested the subjective indicators we used are meaningful, future studies should collect more objective metrics (e.g., real-time measures) and with multiple subjects (e.g., peers or parents). Second, considering that continuous practice seems to be essential for positive psychological intervention programs to build positive habits (Lyubomirsky, Sheldon, & Schkade, 2005), future research could consider appropriately extending the duration of the application of relevant interventions to enhance positive emotions, which may help to further enhance adolescent psychological well-being. Another limitation is that the 2-month follow-up period is relatively short, and do not support the long-term effect of the PREIP intervention on PSU. A longer follow-up at multiple time points seems to be necessary in the future, which could provide vital support for the effectiveness of the PREIP treatment for PSU behaviors. Lastly, the one-on-one intervention is time-consuming and belongs to consumable treatment, especially when implemented in school settings. We could consider group counseling or further design the PREIP as non-consumable intervention, such as digital intervention to transcend the limitations of space and time and reduce related costs (Pineda et al., 2023).
In conclusion, the findings in this study supported the positive impact of PREIP on adolescent PSU and explained the potential mechanism of improving positive emotions: loneliness dilution and perceived social support enhancement. Ultimately, it is hoped that PREIP in the future could be replicated and further developed in the worldwide battle against PSU and enhance adolescent well-being.
Funding sources
This work was supported by General Project of Education in 2022 for the 13th Five-Year Plan of the National Social Science Fund of China: The development, influencing factors and intervention system of middle school students' moral shading: Based on decision-making process theory (grant no. BEA210108).
Authors' contribution
YH and MP involved in study design. YH, MP, DW, and XW involved in data preparation, statistical analysis, and wrote the manuscript. DW involved in study supervision and edited the manuscript. All authors had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Conflict of interest
The authors declare no conflict of interest.
Data availability
De-identified data of the results of this study can be obtained from the corresponding authors at the reasonable request of potential collaborators. Due to privacy and/or ethical restrictions, the raw data are not publicly available.
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