The Role of Psychological Flexibility and Emotion Regulation in the Relationship Between Smartphone Addiction and Psychological Wellbeing in Adolescents: Three-Wave Longitudinal Serial Mediation Study

The Role of Psychological Flexibility and Emotion Regulation in the Relationship Between Smartphone Addiction and Psychological Wellbeing in Adolescents: Three-Wave Longitudinal Serial Mediation Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Role of Psychological Flexibility and Emotion Regulation in the Relationship Between Smartphone Addiction and Psychological Wellbeing in Adolescents: Three-Wave Longitudinal Serial Mediation Study Ahmet ALKAL This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6530346/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Health and Quality of Life Outcomes → Version 1 posted 8 You are reading this latest preprint version Abstract Background When the increasing prevalence of Smartphone Addiction (SA) and its potential negative effects on mental health among adolescents are taken into consideration, an in-depth investigation of the relationship between SA and Psychological Well-being (PW) is of critical importance. Therefore, using a three-wave longitudinal research design, this study aimed to examine the serial mediation role of Psychological Flexibility (PF) and Emotion Regulation (ER) in the relationship between SA and PW. To our knowledge, this is the first study to examine SA, PF, ER, and PW relationships and mediating mechanisms in an adolescent sample using a longitudinal design. Methods The study included 448 adolescents (49.8% female and 50.2% male; Range age =15–19, M age =16.76, SD age =1.12) who responded to the questionnaires in three waves. Participating adolescents responded to a 50-item questionnaire consisting of the Smartphone Addiction Scale-Short Version (SAS-SV), the Five-Dimensional Well-Being Scale for Adolescents (EPOCH), the Multidimensional Psychological Flexibility Inventory Short Form (MPFI-SF), and the Regulation of Emotions Questionnaire (REQ). The questionnaires were filled in using pen and paper in a classroom environment under the supervision of the teacher and the researcher. Results Compared to those who used their smartphones for 0–2 hours and 2–4 hours, adolescents who reported to use their smartphones for more than four hours daily were found to have higher SA scores and lower PW, ER, and PF scores across all three time points (T1, T2, and T3). The findings indicated that SA at T1 negatively predicted PW at T3 (β= -0.34, p < .001), PF at T2 (β= -0.39, p < .001), and ER at T2 (β= -0.23, p < .001). On the other hand, PF at T2 positively predicted ER at T2 (β = 0.17, p < .001) and PW at T3 (β = 0.40, p < .001), and ER at T2 positively predicted PW at T3 (β = 0.73, p < .001). Besides, PF at T2 (β= -0.15, SE = 0.03, 95% CI = [-0.2036, -0.1053]) and ER at T2 (β= -0.17, SE = 0.03, 95% CI = [-0.2288, -0.1054]) were found to fully mediate the longitudinal relationship between SA at T1 and PW at T3. The longitudinal serial mediation model accounted for 32% of the variance in PW (R² = .32). Conclusions This study shows that SA leads to a decrease in adolescents' PF skills and their capacity to effectively manage their emotional reactions over time, which in turn leads to lower PW levels. The findings emphasize the potential of interventions to improve PF and ER skills in alleviating SA-related mental health problems in adolescents. The findings also suggest that both strengthening PF and ER skills separately and addressing them simultaneously could significantly increase the effectiveness of treatment approaches. Smartphone Addiction Psychological Flexibility Emotion Regulation Psychological Well-being Figures Figure 1 Figure 2 1. Introduction With the spread of mobile internet technology, smartphones have become an integral part of modern life. The multipurpose functions offered by these devices in the fields of communication, social interaction, access to information, entertainment, etc. capture users’ attention [ 1 ] and lead to an increase in the frequency and duration of smartphone use [ 2 , 3 ]. However, excessive and uncontrolled use of smartphones brings along an important problem, such as the risk of smartphone addiction (SA) [ 4 , 5 ]. The constant accessibility and various functionalities provided by smartphones increase individuals' addiction to these devices. Especially user-friendly interfaces, customizable notification settings, and automation features of mobile devices increase the risk of SA by creating a continuous usage cycle [ 6 , 7 ]. Moreover, personalized content and rewarding feedback mechanisms offered by mobile devices reinforce the SA cycle by triggering dopamine release [ 8 ]. Although not specifically included in diagnostic guidelines such as DSM-5 and ICD-11, SA is defined as an uncontrolled behavioral pattern in which an individual's physiological, psychological, and social functions are impaired due to excessive use of these devices [ 9 ]. Globally, the increasing rate of smartphone use [ 10 ] raises concerns about the risk of SA [ 11 , 12 , 13 ]. Particularly adolescents are reported to be more vulnerable to the risk of SA compared to adults [ 14 ]. (Cha & Seo, 2018). The relative weakness in adolescents' impulse control mechanisms and their intensive use of smartphones as a means of meeting their social and emotional needs make them a more vulnerable group in terms of SA [ 15 , 16 ]. Hence, numerous studies conducted with samples from different cultures reported a high prevalence of SA among adolescents. For example, a cross-sectional study conducted with 1447 Philippine adolescents reported the prevalence of SA as 66.2% [ 17 ]. SA prevalence was reported as 37% in Malaysia [ 18 ] and 64.6% among Indian adolescents [ 19 ]. A study conducted by Lopez-Hernandez et al. [ 15 ] on British adolescents aged 11–18 years reported the prevalence of SA as 10%. It was reported that 30.9% of South Korean adolescents were in the risk group for SA [ 14 ]. A meta-analysis including 67 studies conducted in adolescent samples showed that the prevalence of SA among adolescents ranged between 4.3% and 70% [ 20 ]. Studies conducted in Turkey also show similar results. For instance, Daysal Güler et al. [ 21 ] reported that 41.8% of adolescents were at risk of SA. Besides, studies conducted in a sample of university students in Turkey reported that the prevalence of SA ranged between 33.7% and 48.6% [ 22 , 23 ]. These results indicate that SA is an important problem among adolescents in Turkey and the world. The increasing prevalence of SA among adolescents indicates its potential to have negative effects on physical and mental health [ 12 , 24 ]. Various studies provide strong evidence of the negative effects of SA on adolescents’ biopsychosocial development. For instance, prolonged screen time has been reported to reduce individuals’ quality of life by causing various physical health problems such as musculoskeletal disorders, postural abnormalities, and respiratory problems [ 25 , 26 , 27 ]. SA was detected to have a significant positive relationship with depression [ 28 ], anxiety [ 29 ], stress [ 30 ], loneliness [ 31 ], and poor sleep quality [ 32 ]. It was reported that SA could lead to problems such as poorer sleep quality and interpersonal relationships, lower academic achievement, and a higher risk of depression [ 33 , 34 , 35 ]. SA was also reported to weaken social skills [ 36 , 37 ] and lead to more loneliness [ 38 ]. Longitudinal studies showed that SA in adolescents predicted loneliness and depressive symptoms over time [ 6 ]. Systematic reviews and meta-analyses also supported significant associations between SA and physical and mental health problems such as depression, anxiety, musculoskeletal problems, poor sleep quality, and difficulty falling and staying asleep [ 39 , 40 , 41 ]. While the existing literature focuses on the effect of SA on mental health problems, research on its effects on psychological well-being (PW) remains relatively limited. Although increasing evidence indicates that SA increases mental health problems, there is a relatively insufficient number of studies that examined the direct and indirect effects of SA on PW. Considering the increasing prevalence of SA and its potential negative effects on mental health in the adolescent population, an in-depth examination of the relationship between SA and PW is of critical importance. Therefore, the current study aims to examine the relationship between SA and PW and the mediating roles of personal resources such as psychological flexibility (PF) and emotion regulation (ER) in this relationship using a longitudinal design. A longitudinal design is believed to contribute to the understanding of the causal patterns between these variables by revealing the changes in the relationships between these variables over time. In particular, examining the mediating mechanisms in the relationship between SA and PW is considered to provide important insights into the dynamic and sequential processes of interactions between the research variables. In addition, it is also predicted to contribute both to the expansion of theoretical knowledge and to the development of intervention programs aimed at protecting adolescents’ mental health. 2. Literature review and hypotheses 2.1. The relationship between smartphone addiction and psychological wellbeing The literature refers to reaching pathological levels of smartphone use using various concepts. SA, which is the most frequently used one among these concepts, refers to a psychological addiction to the device itself or the digital elements it contains, which occurs as a result of excessive, compulsive, and uncontrolled use of mobile devices [ 42 ]. Research shows that SA has similarities with symptoms observed in substance addictions such as loss of control, development of tolerance, withdrawal, and functional impairment [ 1 , 43 ] and is characterized by symptoms such as inability to tolerate harmful consequences, preoccupation, inability to control cravings, loss of productivity, and anxiety [ 44 ]. On the other hand, psychological well-being (PW) is defined as a multidimensional structure that includes individuals’ efforts towards life goals, the processes of realizing their potential, the ability to establish deep and meaningful social relationships, harmonious interactions with their environment, and the ability to continuously support personal development [ 45 ]. PW reflects the eudaimonic perspective of well-being and represents the basic aspects of optimal human functioning. In this regard, it emphasizes aspects of psychological functioning such as self-acceptance, social contribution, positive relationships with others, personal growth, and purpose in life [ 46 ]. In particular, PW plays a critical role in adolescence for the healthy progression of processes such as identity formation, social relationships, and planning for the future [ 47 ]. Therefore, it is considered an important indicator of adolescents' mental health. SA is reported to be an important risk factor with potentially devastating effects on individuals' well-being [ 48 , 49 ]. Various theoretical and empirical explanations indicate the potential negative effects of SA on well-being. The empowerment-enslavement paradox indicates that although the features of mobile devices providing 24/7 access to wireless networks include many advantages, individuals may become dependent on the functionality of these devices and become their ‘slaves’ [ 50 ]. Problematic or pathological smartphone use may have negative consequences on individuals' social relationships [ 51 ]. In addition, with the increase in the time spent online, it is reported to cause disruptions in users' time management skills and neglect of other important areas of daily life. In particular, it is reported to shorten the time to be allocated to activities that are considered important for individuals’ well-being and healthy lifestyles [ 52 ], which weakens positive mental health indicators [ 53 ]. In line with this theoretical framework, previous research reveals important findings indicating that SA has a negative effect on adolescents' PW. For instance, SA was consistently reported to be associated with lower PW in adolescents [ 51 , 54 , 55 ]. SA was reported to have a significant negative relationship with positive psychological constructs such as resilience [ 56 ] and life satisfaction [ 57 ] and negatively predicts happiness [ 58 ]. SA was reported to have a negative effect on PW both directly and indirectly through loneliness [ 59 ]. In addition, preliminary findings of the first-year data of the three-year longitudinal study conducted by Alkorta [ 60 ] showed that smartphone usage time had a significant negative relationship with well-being and life satisfaction in adolescents. Based on the above theoretical explanations and previous research results, the current study proposes hypothesis H1. H1. SA at T1 significantly and negatively affects PW at T3 among adolescents. 2.2. Mediating role of psychological flexibility Psychological flexibility (PF) is defined as the capacity of an individual to approach his/her inner experiences (thoughts, emotions, physical sensations) with a non-judgmental awareness, to evaluate the current context and to regulate his/her behaviors in line with his/her values [ 61 ]. PF, which is accepted as an important determinant of mental health, consists of six interrelated components. Acceptance, the first component, refers to the individual's experiencing painful thoughts, feelings and sensations as they are and having an open attitude towards these experiences instead of struggling with them. Cognitive defusion involves realizing that thoughts are only mental events, separate from reality, and not becoming overly attached to them. Being in touch with the present moment emphasizes focusing attention and awareness on the present moment rather than on past or future concerns. Self-as-context refers to perceiving oneself as a constantly observing self, separate from changing experiences. Values encourage the individual to identify the basic principles and goals that guide his/her life and to live a life in accordance with these values. Committed action involves taking consistent and decisive steps toward goals compatible with values [ 61 , 62 ]. These six integrated components provide a significant contribution to establishing a healthier relationship with one's inner experiences and leading a life in harmony with one's values. Theoretical suggestions propose that behavioral addictions have a negative effect on PF [ 63 ]. According o this perspective, compulsive tendencies towards addictive behaviors and difficulty controlling these behaviors may undermine an individual's ability to stay connected to their immediate experiences, take value-driven actions, and effectively cope with challenging thoughts and emotions. Moreover, high levels of digital addiction may increase individuals' tendency to avoid or suppress negative internal experiences by weakening their ability to resist impulsive behaviors that are incompatible with their desired long-term goals [ 64 ], which may lead to the perpetuation of the addiction cycle and lower levels of PF. Hence, various types of digital addiction were consistently shown to be linked to PF in several studies. For instance, increased SA [ 65 ] and social media addiction [ 66 ] were found to reduce individuals' PF. In addition, social media addiction was detected to be a negative predictor of PF [ 67 ]. SA was reported to have an indirect effect on procrastination behaviors through low PF [ 68 ]. Decreased PF was found to have a negative effect on individuals' PW [ 69 ]. On the other hand, some findings showed that internet addiction was positively related to psychological inflexibility [ 64 , 70 ]. A prospective study conducted by Peltz et al. [ 71 ] determined that the increase in university students' problematic mobile phone use predicted the increase in their psychological inflexibility levels. These results support the view that SA may reduce adolescents' PF levels over time and thus lead to lower levels of PW. Therefore, the current study proposes hypothesis H2 based on this empirical evidence from the literature. H2. PF at T2 will play a mediating role in the longitudinal relationship between SA at T1 and PW at T3. 2.3. Mediating role of emotion regulation Emotion regulation (ER) is generally defined as the capacity to manage emotional reactions. More specifically, it refers to the individual's ability to change the frequency, intensity, or duration of emotional experiences [ 72 , 73 ]. ER consists of intrinsic and extrinsic processes used in achieving personal goals and regulating emotional responses [ 74 ]. Researchers identified various cognitive and behavioral strategies for adaptive and maladaptive ER processes [ 75 , 76 ]. Adaptive ER strategies such as acceptance, reappraisal, and problem-solving are reported to be effective in reducing the impact of negative emotional experiences [ 77 , 78 ]. Using adaptive ER strategies more was reported to contribute to positive mental health [ 79 ] and support physical and mental health [ 80 ]. On the other hand, maladaptive ER strategies such as suppression, avoidance, and rumination have the potential to increase the persistence and severity of negative emotional states [ 75 , 76 ]. It is emphasized that suppression or maintenance of negative emotions through maladaptive ER strategies may increase the likelihood of psychopathological conditions [ 81 , 82 ]. In particular, more frequent use of maladaptive ER strategies is reported to be associated with increased psychological symptoms, poor mental health, and low well-being [ 77 ]. Adolescence represents a significant transitional phase in an individual's emotional development and identity formation. In this critical period, mobile devices could become not only an important source of social interaction and information but also a tool for coping with emotional difficulties for adolescents. However, the literature provides evidence indicating that adolescents affected by various forms of digital addiction exhibit notable deficiencies in their ER skills [ 83 ]. SA, in particular, is known to potentially increase impulsivity levels, shorten attention spans, and lead to problems in social relationships among adolescents. These factors could have negative effects on adolescents' capacity to recognize, understand, and effectively manage their negative emotions. Hence, adolescents who have SA may feel angry or frustrated more easily, or have difficulty controlling their emotional reactions when faced with stressful situations. This condition could lead them to resort to maladaptive ER strategies and, consequently, harm their PW. Existing literature suggests that an increased risk of digital addiction is linked to low ER and decreased well-being. For instance, different types of digital addiction such as internet addiction [ 84 ], problematic internet use and video game addiction [ 85 ] and social media addiction [ 86 ] have been reported to be inversely correlated with ER. Adolescents with internet addiction were reported to have more difficulties with ER [ 83 ]. On the other hand, ER difficulties were found to have a significant positive relationship with SA [ 87 ] and social media addiction [ 88 , 89 ] and predicted problematic smartphone use [ 90 ]. Longitudinal studies showed that maladaptive ER strategies were associated with problematic internet use [ 91 ] and ER difficulties predicted internet addiction over time [ 92 ]. Moreover, several studies reported that lower ER in adolescents was associated with lower well-being [ 80 , 93 ]. These results suggest that ER may play a role as an important mediating variable in the longitudinal relationship between SA and PW. Therefore, the present study proposes hypothesis H3 in light of this empirical evidence. H3. ER at T2 will play a mediating role in the longitudinal relationship between SA at T1 and PW at T3. 2.4. Series mediating role of emotion regulation and psychological flexibility SA poses an important risk factor that can potentially lead to negative effects on mental health. Research conducted in recent years consistently demonstrates the negative effects of SA on important mental health indicators such as PF and ER [ 65 , 90 ]. SA is reported to weaken particularly PF components and narrow the behavioral repertoire [ 63 ], which weakens the capacity of adolescents to recognize and understand their negative emotional experiences and to develop behaviors in line with their values. Therefore, individuals with low PF levels are reported to experience higher rates of mental health problems [ 94 ]. Low PF is also reported to negatively affect emotional regulation processes and trigger the use of maladaptive emotion regulation strategies [ 95 ]. When adolescents with lower levels of PF encounter stressful or challenging life events, they may experience difficulties in regulating their emotional reactions and demonstrate intense emotional states such as increased anger or frustration. Instead of expressing their feelings constructively after a negative emotional experience, they may use maladaptive ER strategies such as withdrawal or avoidance. While these maladaptive ER strategies may provide temporary relief in the short term, they may lead to chronic emotional problems in the long term. Previous research has shown that low PF [ 69 ] and maladaptive ER [ 80 ] are also associated with decreases in adolescents' well-being. This mutually reinforcing negative interaction of SA on PF and ER may lead to a decrease in adolescents' PW. Therefore, in light of the relevant literature, the present study proposes hypothesis H4. H4. PF and ER at T2 will have a serial mediating role in the relationship between SA at T1 and PW at T3. 2.5. The present study The widespread use of smartphones in adolescents [ 96 , 97 ] has made the potential effects of overuse of these devices on mental health an important area of research. Especially the unique dynamics of adolescence and the risk of addiction development of excessive use of smartphones [ 4 , 5 ] require a more detailed examination of the effects of digital technologies on mental health. In this regard, understanding the psychological consequences of adolescents’ interactions with the digital world is critical for efforts to protect and promote adolescents' mental health. The literature consistently reveals that SA increases negative mental health outcomes [ 29 ] and is associated with decreased well-being [ 98 ]. However, relatively limited research examined the impact of SA on PW using a longitudinal design. Furthermore, the mediating mechanisms involved in the effect of SA on PW and how they interact have not yet been fully elucidated. Therefore, to fill these gaps, the present study focuses on the role of PF and ER as potential mediating mechanisms in the longitudinal relationship between SA and PW. More specifically, this study proposes a longitudinal serial mediation model that aims to examine whether PF and ER mediate the effect of SA on PW in both an independent and serial manner. 3. Method 3.1. Participants and procedure The participants of the study consisted of 10th, 11th, and 12th graders from two different high schools in a provincial center in the Eastern Anatolia Region of Turkey who used smartphones within the last six months. Data were collected in 3 waves in March, June, and September 2024. The first wave (T1) included 482 students (47.9% female and 52.1% male). The second wave (T2) included 465 students (49% female and 51% male). The third wave (T3) included 454 students (50.2% female and 49.8% male). Matching was performed according to student numbers, and 448 students (49.8% female and 50.2% male) who answered the questionnaires in all three waves constituted the final sample of the study (Range age =15–19, M age =16.76, SD age =1.12). Socio-economic status was reported as low by 62 (13.8%), moderate by 256 (57.1%), good by 93 (20.8%), and very good by 37 (8.3%). This study was approved by the Social and Human Sciences Scientific Research and Publication Ethics Committee of the university where the researcher was affiliated (ethics committee decision dated 21.02.2024 and numbered E.139903). The participants were informed about the purpose and procedures of the study. Participation in the study was on a voluntary basis and written informed consent was obtained from the students and their parents. Four different questionnaires were developed to control the sequential effect. The questionnaires were administered to the students in the classroom under the supervision of the researcher and the relevant course teacher. The students completed the questionnaires using paper and pencil in a session lasting 30–35 minutes on average. The participating students were offered no financial incentives. 3.2. Measures 3.2.1. Smartphone Addiction Scale-Short Version (SAS-SV) SAS-SV, which was developed by Kwon et al. [ 99 ] and adapted into Turkish by Şata and Karip [ 100 ], was used to determine the adolescents’ SA levels. The Turkish version of the scale consists of 10 items and one factor. The scale is responded on a Likert-type scale ranging from 1 (strongly disagree) to 6 (strongly agree). Higher scores indicate adolescents’ higher SA levels. The Turkish version of the scale showed excellent construct validity (GFI = .93; AGFI = .88; CFI = .99; NNF = .98; RMSEA = .064; SRMR = .046) and internal consistency (α = .90) [ 100 ]. 3.2.2. Five-Dimensional Well-Being Scale for Adolescents (EPOCH) The EPOCH scale, which was developed by Kern et al. [ 101 ] and adapted into Turkish by Demirci and Ekşi [ 102 ], was used to determine the adolescents’ PW levels. The scale consists of five dimensions and 20 items and is scored by responding to Likert scale ratings from 1 (never) to 5 (always). A higher total score obtained from the scale indicates higher psychological well-being levels. The Turkish version of the scale was reported to show excellent construct validity (x²/df = 2,383; RMSEA = 0.074, NFI = .96; NNFI = .98; CFI = .98; IFI = .98; RFI = .96; SRMR = .052) and internal consistency (α = .95 for total score) [ 102 ]. 3.3.3. Multidimensional Psychological Flexibility Inventory Short Form (MPFI-SF) MPFI-SF, which was developed by Rolffs et al. [ 103 ] and adapted into Turkish by Alkal and Çam [ 104 ], was used to determine the adolescents’ PF levels. The inventory consists of 24 items and two dimensions (psychological flexibility and psychological inflexibility). It is scored by responding to the Likert scale ratings from 1 (never relevant) to 6 (always relevant) considering the last two weeks. In this study, 12 items in the PF subscale of the MPFI-SF were used to calculate the adolescents’ PF scores. Higher scores in the PF subscale indicate adolescents’ higher PF levels. The Turkish version of the MPFI-SF was reported to show excellent internal consistency (α = .97, .96 for sub-dimensions) and construct validity (χ²/sd = 2.197; CFI = .97; NFI = .92; IFI = .96; TLI = .95; RMSEA = .072; SRMR = .032) [ 104 ]. 3.3.4. Regulation of Emotions Questionnaire (REQ) The adolescents’ ER scores were determined using the REQ developed by Phillips and Power [ 105 ] and adapted into Turkish by Duy and Yıldız [ 106 ]. The REQ consists of 18 items and four dimensions (internal-functional, internal-dysfunctional, external-functional, and external-dysfunctional emotion regulation). The scale is scored by responding to Likert-type ratings from 1 (never) to 6 (always). In this study, 8 items in the internal-functional and external-functional emotion regulation subscales of the REQ were used to calculate adolescents' ER scores. Higher scores in the functional emotion regulation sub-dimensions indicate adolescents' higher ER levels. The construct validity of the 4-dimensional Turkish version of the REQ was confirmed (χ2/df = 4.01, RMSEA = .06, RMR = .09, SRMR = .06, GFI = .94, AGFI = .92, CFI = .93, NFI = .91, NNFI = .92) and Cronbach’s alpha for the internal-functional and external-functional emotion regulation sub-dimensions was found to be .74 and .59, respectively [ 106 ]. 3.3. Data analysis Firstly, descriptive statistics (mean, SD, skewness and kurtosis) and correlation coefficients between variables in T1, T2 and T3 were calculated. Secondly, Harman's one-factor test was analyzed to test the possibility of common method bias. Then, serial mediation analysis (Model 6) was performed using Hayes' PROCESS macro v3.4 to test the research model (Fig. 1). In these analyses, we entered SA at T1 as the independent variable, PW at T3 as the dependent variable, and PF and ER at T2 as mediating variables. In addition, demographic variables (gender, age and socio-economic status) were included in the analysis as control variables. The statistical significance of mediation effects was assessed using 95% confidence intervals calculated by bootstrapping based on 5000 resampling. The statistical significance level was accepted as p < 0.05. All analyses were performed using SPSS 25 software. Serial mediation analysis includes methods such as structural equation modeling (SEM) and PROCESS macro. Studies comparing SEM and PROCESS showed that the mediation model results obtained with both were largely similar [ 107 ]. Its user-friendliness and the provision of results compatible with SEM have made the PROCESS macro increasingly popular. Therefore, the present study utilized the PROCESS macro to perform the longitudinal serial mediation analysis. 4. Results 4.1. Preliminary Findings Figure 1 demonstrates the change in the SA, PF, ER, and PW mean scores over time according to the participating students’ daily phone usage time. An analysis of Fig. 1 shows that the SA mean scores increased and the PF, ER, and PW mean scores decreased over time (T1, T2, and T3) in the students who reported using smartphones for more than four hours per day. This result shows that the increase in the duration of daily smartphone use increases the risk of SA in adolescents over time and affects their mental health negatively. 4.2. Descriptive statistics and correlation analysis The skewness (range = − .58 and 1.11) and kurtosis (range = − .96 and 1.30) values presented in Table 1 support the normal distribution of the data. In addition, Cronbach's alpha (α) reliability coefficients of SA, PF, ER, and PW were highly reliable in all three waves. Correlation analysis results showed that there were significant relationships between all variables both within and between waves in the expected direction. SA was found to have a significant negative correlation with PF, ER, and PW. In addition, there was a significant positive relationship between PF, ER, and PW. Table 1 Descriptive statistics, reliabilities and correlation analysis Variables 1 2 3 4 5 6 7 8 9 10 11 12 1. SA(T1) - 2. SA(T2) .60 ** - 3. SA(T3) .62 ** .63 ** - 4. PF(T1) − .37 ** − .15 ** − .18 ** - 5. PF(T2) − .42 ** − .56 ** − .38 ** .67 ** - 6. PF(T3) − .38 ** − .26 ** − .42 ** .66 ** .53 ** - 7. ER(T1) − .39 ** − .20 ** − .24 ** .25 ** .15 ** .22 ** - 8. ER(T2) − .54 ** − .28 ** − .37 ** .47 ** .47 ** .37** .54 ** - 9. ER(T3) − .45 ** − .19 ** − .27 ** .36 ** .22 ** .34 ** .62 ** .65 ** - 10. PW(T1) − .33 ** − .16 ** − .10 ** .42 ** .28 ** .31 ** .50 ** .59 ** .66 ** - 11. PW(T2) − .34 ** − .35 ** − .38 ** .33 ** .30 ** .33 ** .47 ** .53 ** .63 ** .68 ** - 12. PW(T3) − .30 ** − .37 ** − .41 ** .40 ** .47 ** .37 ** .28 ** .49 ** .44 ** .58 ** .58 ** - Mean 25.81 34.77 29.61 3.40 2.90 3.43 25.36 24.16 25.52 60.34 57.70 56.71 SD 9.11 10.27 11.39 .65 .70 .87 5.34 4.92 5.21 10.63 11.32 10.37 Skewness 1.11 − .30 .75 − .07 .34 − .18 − .42 − .22 − .49 − .58 − .54 − .40 Kurtosis 1.30 − .96 − .52 − .15 − .42 − .55 .31 .42 .49 1.09 .10 .12 α .96 .94 .95 .96 .95 .94 .82 .85 .87 .84 .83 .85 *p < 0.05, **p < 0.01, ***p < 0.001; SA (Smartphone Addiction), PF (Psychological Flexibility), ER (Emotion Regulation), PW (Psychological Wellbeing), T1 (Time 1), T2 (Time 2), T3 (Time 3). 4.3. Test of common method bias This study used Harman's one-factor test to examine whether there was a common method bias since data were collected through a self-report questionnaire. Factor analysis without rotations was performed on 50 items used to measure SA, PF, ER, and PW variables at three different time points (T1-T2-T3). Analysis results indicated 11 factors with eigenvalues greater than 1 at T1, and nine factors at T2 and T3. The total variance explained by the first factor was 28.73% at T1, 28.14% at T2, and 28.88% at T3. The first factor explains less than 40% of the total variance at all three time points [ 108 ], which indicates that there is no significant common method bias in this longitudinal study. 4.4. Serial Mediation Analysis The serial mediation effect of PF and ER at T2 on the longitudinal effect of SA at T1 on PW at T3 was analyzed using PROCESS Macro Model 6. Demographic variables (gender, age, and socio-economic status) were controlled in the mediation analysis. The significance of the indirect effect of SA on PW mediated by PF and ER was determined according to the 95% confidence interval (CI) obtained by the bootstrapping method (5000 bootstrap samples). CIs values were in the same direction; namely, they did not contain zero, which indicates that the indirect effect is significant. Table 2 and Fig. 2 demonstrate the results of the longitudinal serial mediation analysis. The findings in Table 2 show that SA at T1 negatively predicts PW at T3 (β= -0.34, p < .001), PF at T2 (β= -0.39, p < .001) and ER (β= -0.23, p < .001). PF at T2 positively predicts ER at T2 (β = 0.17, p < .001) and PW at T3 (β = 0.40, p < .001). ER at T2 also positively predicts PW at T3 (β = 0.73, p < .001). While the direct effect of SA at T1 on PW at T3 was significant in the first model, the effect was not statistically significant when the mediating variables (PF and ER in T2) were included in the analysis (Model 4). This finding suggests that PF and ER at T2 play a fully mediating role in the longitudinal relationship between SA at T1 and PW at T3. These findings suggest that adolescents' SA levels at T1 indirectly reduce PW at T3 by reducing PF and ER levels at T2. Bootstrapping analysis was performed to confirm the significance of PF and ER at T2 on the relationship between SA at T1 and PW at T3, and the results are presented in Table 3 . The findings in Table 3 show that PF (β= -0.15, SE = 0.03, 95% CI = [-0.2036, -0.1053]) and ER (β= -0.17, SE = 0.03, 95% CI = [-0.2288, -0.1054]) at T2 mediate the longitudinal relationship between SA at T1 and PW at T3. In addition, PF and ER at T2 seem to have a fully serial mediation role in the longitudinal relationship between SA at T1 and PW at T3 (β= -0.05, SE = 0.01, 95% CI = [-0.0733, -0.0268]). The longitudinal serial mediation model explained 32% (R 2 = .32) of the dependent variable (PW). 5. Discussion Research to date has demonstrated the impact of SA on negative mental health outcomes in adolescents, yet longitudinal research that examines the direct and indirect effects of SA on PW is limited. To our knowledge, this is the first study to examine the mediating effects of PF and ER on the relationship between SA and PW in adolescents using a longitudinal design. Our study provides an important foundation for a more detailed understanding of the relationship between SA and PW and provides strong evidence for the relationships among SA, PW, PF, and ER in an adolescent sample. Our preliminary findings showed that adolescents who used smartphones more than four hours a day had higher SA scores at all three time points (T1-T2-T3) than those who used smartphones between 0–2 hours and 2–4 hours. On the other hand, PW, ER and PF scores were found to be lower. These findings suggest that the increase in adolescents' daily smartphone usage time increases the risk of SA over time and negatively affects positive mental health outcomes. This suggests that mobile device technology is an important factor to be considered in the psychosocial development of adolescents. It particularly emphasizes the importance of regulating adolescents' smartphone usage habits. In addition, it once again reveals the necessity of developing comprehensive mental health strategies to prevent the negative effects of increased screen time with the widespread use of smartphones on adolescents' mental health. In our first hypothesis (H1), we proposed that SA at T1 would significantly and negatively affect PW at T3 in adolescents. The findings of this study show that higher SA in adolescents leads to lower PW over time, which furthers previous research results [ 51 , 98 ]. Several possible explanations could be put forward for this finding: First, the compelling features of mobile device use, such as the search for uninterrupted connectivity and reassurance, may negatively affect the frequency and quality of individuals' face-to-face social interactions [ 109 ]. When this finding is evaluated within the framework of the displacement hypothesis, the increase in the time spent on mobile devices may lead to a decrease in the time allocated for offline communication and a weakening of social relationships [ 110 ]. In this regard, digital communication methods could be considered to reduce relationship satisfaction [ 111 ] and thus lead to lower PW levels. Secondly, excessive and unconscious use of smartphones could cause distraction, difficulty focusing, and increased stress levels [ 112 ]. It may also increase anxiety levels by encouraging individuals to constantly check their smartphones and stay active in the virtual environment [ 113 ]. Increased stress [ 114 ] and anxiety [ 115 ] resulting from SA may have a negative effect on adolescents' PW. Thirdly, it can be argued that SA causes a decrease in adolescents' PW levels by increasing negative emotional states [ 6 ]. In conclusion, the current study reveals the urgency of developing and implementing evidence-based preventive programs to reduce the potential harms of SA. Another important finding of the study reveals that PF at T2 mediates the longitudinal relationship between SA at T1 and PW at T3. More specifically, it shows that SA reduces adolescents' PF levels over time, which is associated with lower PW. This result supports the H2 hypothesis proposed in our study and advances the cross-sectional findings in the existing literature [ 65 ] with a longitudinal perspective. Digital addictions are reported to trigger dysfunctional processes such as coping with or trying to reduce unwanted thoughts, feelings, or experiences [ 116 ]. In this regard, SA could be considered to cause lower PF levels by negatively affecting adolescents’ PF components over time, such as adapting to changing conditions, behaving toward personal values, and being open to instant experiences [ 63 ]. In particular, it can be argued that SA narrows individuals’ behavioral repertoire by strengthening the tendency to avoid disturbing internal experiences and thus negatively affects PF over time [ 117 ]. In the literature, it is emphasized that individuals who tend to avoid negative thoughts and emotions rigidly increase their psychological distress levels and impair their functionality [ 118 , 119 ]. It is stated that this avoidance pattern negatively affects adolescents' PW levels and their ability to cope with the difficulties of daily life in a harmonious way [ 120 ]. Based on this theoretical framework, it can be argued that low PF in adolescents leads to lower PW levels over time. Our findings support previous research results showing the negative impact of low PF on PW [ 69 ] and provide important evidence for this relationship. It also suggests that interventions aimed at increasing PF may have a potential role in reducing the negative effects of SA on adolescent mental health. Another noteworthy finding of the study is that ER at T2 is an important mediating variable in the longitudinal relationship between SA at T1 and PW at T3, which supports hypothesis H3. In other words, SA seems to weaken adolescents' ER skills over time, which leads to lower PW levels. This finding can be explained from the perspective of the Theory of Compensatory Use of the Internet [ 121 ], which initially refers to Internet use and then covers various digital addictions, including SA. This theory posits that individuals may turn to mobile devices more as a coping strategy for the negative emotional states they experience [ 122 ]. Excessive mobile device use may trigger individuals' motivation to avoid facing negative emotional experiences and resort to virtual environments, which leads them to maladaptive ER strategies instead of using healthy ways of managing them. Such a condition could lead to the learning and reinforcement of dysfunctional ER strategies such as suppressing emotional reactions, distraction, or providing a temporary escape through virtual interactions [ 123 ]. Hence, research has shown that adolescents who have internet addiction have significant difficulties with ER skills [ 124 ]. In this context, it can be argued that individuals' inability to effectively regulate their emotional experiences significantly reduces their ability to maintain positive emotional states [ 124 , 125 ], which leads to lower PW levels. In conclusion, in line with the theoretical framework and previous research results, the findings of this study support that ER is an important mediating variable in the longitudinal effect of SA on adolescents' PW. Interventions aiming to increase ER skills may make a significant contribution to reducing the negative impact of SA on PW. The last noteworthy finding of the current study reveals that PF and ER at T2 play a serial mediating role in the longitudinal relationship between SA at T1 and PW at T3, which supports hypothesis H4. More specifically, it can be argued that SA leads to a decrease in adolescents' PF levels over time, which in turn leads to lower ER levels, negatively affecting PW levels. Digital addictions may reduce PF levels by weakening adolescents' awareness of being in the moment, their ability to accept their negative thoughts and emotions, and their capacity to exhibit behaviors in line with their personal values [ 64 ]. Decreased PF may lead to the development of more rigid thought patterns and the narrowing of the behavioral repertoire. This may increase adolescents' tendency to engage in maladaptive ER strategies [ 126 ]. It can be argued that this chain effect ultimately leads to a decrease in adolescents' PW levels. In conclusion, the current study advances previous research findings by revealing the causal relationships among SA, PF, ER and PW. It also supports the potential benefits of addressing PF and ER within an integrated treatment approach in reducing mental health problems associated with SA. In this context, it is thought that targeting PF and ER skills simultaneously in the design of future intervention programs may increase the effectiveness of the treatment., 5.1. İmplications and Limitations revealing the longitudinal relationships among SA, PF, ER and PW. By elucidating the potential causal relationships between these variables, our research fills an important gap in the literature and contributes significantly to the understanding of the conceptual framework. Especially the longitudinal serial mediation model proposed and tested in the study provides a holistic perspective on how the relationship between SA and PW is mediated through sequential psychological processes. The findings show that PF and ER have significant mediating roles both separately and serially in the relationship between SA and PW. This provides important insights that SA indirectly leads to lower levels of PW by reducing adolescents' PF and ER levels over time. It also suggests that SA is a potential risk factor for positive mental health indicators. The longitudinal evidence provides an important foundation for future theoretical models and intervention strategies. It emphasizes that especially PF and ER play a central role in understanding the negative effects of SA on psychological health, which has become a common phenomenon of modern life. An analysis of the findings in the context of the buffering hypothesis [ 127 ] shows that PF and ER reduce the direct effect of SA on PW over time. It emphasizes the protective role of high PF and ER, especially in the effect of SA on mental health problems. High levels of PF and ER may mitigate psychological difficulties resulting from excessive use of mobile devices and thus reduce the risk of developing negative mental health outcomes. In this regard, intervention programs that aim to increase PF and ER skills both separately and simultaneously may reduce the negative effects of SA on mental health. In today's digitalized world, the prevalence and accessibility of mobile devices have become an integral part of adolescents' lives, which reveals a reality where it is becoming increasingly difficult to completely restrict the use of mobile devices. Therefore, parents, mental health professionals and school administrations have important responsibilities in the process of reducing the potential negative effects of SA on mental health and protecting adolescent mental health. Parents should have an open and honest dialogue with their children, be informed about their mobile device usage purposes and online experiences, set appropriate boundaries, and take a supportive role when necessary. Mental health professionals could develop and implement evidence-based intervention programs for adolescents who are victims of SA or demonstrate SA behaviors. School administrations should focus on developing strategies to strengthen adolescents' digital literacy skills. In this regard, digital literacy training is believed to enable adolescents to recognize the potential risks associated with the use of mobile devices and to be aware of the potential negative effects of these devices on physical (e.g. sleep disorders, eye health problems, postural disorders) and mental health (e.g. cyberbullying, addiction). The findings of the present longitudinal study should be interpreted within the framework of several limitations that should be taken into consideration. Firstly, the instruments used in the data collection process were based on the participants’ self-report, which is a potential limitation. Although three different questionnaires were administered to control for the sequential effect and no significant common method bias was detected through statistical analyses, self-report data may be susceptible to subjective interactions such as social desirability or recall issues. This may not fully reflect the true strength and nature of the relationships between the variables analyzed. Future research could enhance the validity and reliability of the findings by enriching self-report data with different data sources (e.g. behavioral observations and parental assessments). This diversified methodological approach is believed to allow for a more comprehensive and objective understanding of the relationship between the research variables. Secondly, limiting the data collection intervals to three-month periods may limit the exploration of the long-term development and possible lagged effects of the dynamic relationships between the variables under study. Future research could more comprehensively examine the complex and time-spanning effects of SA on adolescents' mental health by using longitudinal designs covering wider time intervals. Finally, the study sample was limited to adolescents who received education in a provincial center in the Eastern Anatolia Region of Turkey. This demographic and geographical specificity may limit the generalizability of the findings to larger adolescent populations and different socio-cultural contexts. Conducting future research in more comprehensive samples could provide more precise conclusions about the universality and contextual differences of the impact of SA on mental health. 6. Conclusions This longitudinal study aimed to examine the relationships among SA, PF, ER, and PW in an adolescent sample using a three-wave longitudinal design. Through a novel longitudinal serial mediation model supported by data collected at three different time points, it empirically tested the serial mediation role of PF and ER in the longitudinal relationship between SA and PW. The findings showed that PF and ER mediated both separately and serially the negative effect of SA on PW over time in adolescents. More specifically, it can be argued that SA causes a decrease in adolescents' PF skills and their capacity to effectively manage their emotional reactions over time, which leads to lower PW levels. These findings emphasize the potential of interventions to improve PF and ER skills in alleviating SA-related mental health problems in adolescents. They also suggest that both strengthening PF and ER skills separately and addressing them simultaneously may significantly increase the effectiveness of treatment approaches. Future research could contribute to the body of knowledge in this area by examining how this longitudinal serial mediation model varies across different cultural contexts and how the dynamic relationships between these variables are affected by cultural differences. Declarations Ethics approval and consent to participate This research was conducted in accordance with the principles of the Declaration of Helsinki and ethics committee approval was obtained from Bingöl University Social and Human Sciences Scientific Research and Publication Ethics Committee (protocol numbered 21.02.2024-E.139903). Consent for publication Not applicable Availability of data and materials The data for this study are available from the corresponding author upon reasonable request. Competing interests The author declares that he has no competing interest. Funding This study did not receive any financial support. Authors' contributions All chapters of this study were prepared by a single author. Acknowledgements We are grateful to the adolescents and their parents who participated in this study, the teachers at the high school who supported our data collection, and the school counselors who assisted in data collection. References Billieux J. 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Meng SQ, Cheng JL, Li YY, Yang XQ, Zheng JW, Chang XW, et al. Global prevalence of digital addiction in general population: A systematic review and meta-analysis. Clin Psychol Rev. 2022;92:102128. Olson JA, Sandra DA, Colucci ÉS, Al Bikaii A, Chmoulevitch D, Nahas J, et al. Smartphone addiction is increasing across the world: A meta-analysis of 24 countries. Comput Hum Behav. 2022;129:107138. Ding Y, Huang H, Zhang Y, Peng Q, Yu J, Lu G, et al. Correlations between smartphone addiction and alexithymia, attachment style, and subjective well-being: A meta-analysis. Front Psychol. 2022;13:971735. Kwon M, Lee JY, Won WY, Park JW, Min JA, Hahn C, et al. Development and validation of a smartphone addiction scale (SAS). PLoS ONE. 2013;8(2):e56936. Şata M, Karip F. Turkish culture adaptation of smartphone addiction scale-short version for adolescents. Cumhuriyet Int J Educ. 2017;6(4):426–40. Kern ML, Benson L, Steinberg EA, Steinberg L. The EPOCH measure of adolescent well-being. Psychol Assess. 2016;28(5):586. Demirci İ, Ekşi F. Ergenler için beş boyutlu iyi oluş modeli: EPOCH ölçeği’nin Türkçe formunun geçerliği ve güvenirliği. Gençlik Araştırmaları Dergisi. 2015;3(3):9–30. Rolffs JL, Rogge RD, Wilson KG. Disentangling components of flexibility via the Hexaflex model: Development and validation of the multidimensional psychological flexibility inventory (MPFI). Assessment. 2018;25(4):458–82. Alkal A, Çam S. Multidimensional psychological flexibility ınventory short form (MPFISF) for adolescents: Adaptation to Turkish, validity and reliability study. Anadolu J Educ Sci Int. 2024;14(1):386–412. Phillips KFV, Power MJ. A new selfreport measure of emotion regulation in adolescents: The regulation of emotions questionnaire. Clin Psychol Psychother. 2007;14:145–56. Yıldız MA, Duy B. Adaptation of the Regulation of Emotions Questionnaire (REQ) for Adolescents. Turk Psychol Couns Guid J. 2014;5(41):23–35. Hayes AF, Montoya AK, Rockwood NJ. The Analysis of Mechanisms and Their Contingencies: PROCESS versus Structural Equation Modeling. Aust Mark J. 2017;25(1):76–81. Jakobsen M, Jensen R. Common method bias in public management studies. Int Public Manag J. 2015;18(1):3–30. Shang Z, Wang D, Liu Z, Zhang X. Exploring the impact of smartphone addiction on mental health among college students during the COVID-19 pandemic: The role of resilience and parental attachment. J Affect Disord. 2024;367:756–67. Kraut R, Patterson M, Lundmark V, Kiesler S, Mukopadhyay T, Scherlis W. Internet paradox: a social technology that reduces social involvement and psychological well-being? Am Psychol. 1998;53(9):1017–31. Goodman-Deane J, Mieczakowski A, Johnson D, Goldhaber T, Clarkson PJ. The impact of communication technologies on life and relationship satisfaction. Comput Hum Behav. 2016;57:219–29. Alter AL. Irresistible: The rise of addictive technology and the business of keeping us hooked. Penguin; 2017. Przybylski AK, Murayama K, DeHaan JW, Gladwell M. Motivational, emotional, and behavioral consequences of fear of missing out. Comput Hum Behav. 2013;29(4):1841–8. Samaha M, Hawi NS. Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Comput Hum Behav. 2016;57:321–5. Hawi NS, Samaha M. Relationships among smartphone addiction, anxiety, and family relations. Behav Inf Technol. 2017;36(10):1046–52. Wilson KG, Hayes SC, Byrd MR. Exploring compatibilities between acceptance and commitment therapy and 12-step treatment for substance abuse. J Ration-Emotive Cogn Behav Ther. 2000;18(4):209–34. Twohig MP. Acceptance and Commitment Therapy: Introduction. Cogn Behav Pract. 2012;19:499–507. Chawla N, Ostafin B. Experiential avoidance as a functional dimensional approach to psychopathology: An empirical review. J Clin Psychol. 2007;63(9):871–90. Chou WP, Yen CF, Liu TL. Predicting effects of psychological inflexibility/experiential avoidance and stress coping strategies for internet addiction, significant depression, and suicidality in college students: a prospective study. Int J Environ Res Public Health. 2018;15(4):788. Ong CW, Barthel AL, Hofmann SG. The relationship between psychological inflexibility and well-being in adults: a meta-analysis of the Acceptance and Action Questionnaire. Behav Ther. 2024;55(1):26–41. Elhai JD, Levine JC, Hall BJ. The relationship between anxiety symptom severity and problematic smartphone use: A review of the literature and conceptual frameworks. J Anxiety Disord. 2019;62:45–52. Kardefelt-Winther D. A critical account of DSM-5 criteria for internet gaming disorder. Addict Res Theory. 2015;23(2):93–8. Fortes AB, Broilo PL, Lisboa CSM. Smartphone use and psychological well-being: the moderating role of emotion regulation. Trends Psychol. 2021;29:189–203. Satıcı B, Deniz M. Modeling emotion regulation and subjective happiness: smartphone addiction as a mediator. ADDICTA Turk J Addict. 2020;7(3). Williams AD, Grisham JR. Impulsivity, emotion regulation, and mindful attentional focus in compulsive buying. Cogn Ther Res. 2012;36:451–7. Faustino B. Transdiagnostic perspective on psychological inflexibility and emotional dysregulation. Behav Cogn Psychother. 2021;49(2):233–46. Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull. 1985;98(2):310. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Sep, 2025 Read the published version in Health and Quality of Life Outcomes → Version 1 posted Editorial decision: Revision requested 01 Jul, 2025 Reviews received at journal 10 May, 2025 Reviewers agreed at journal 07 May, 2025 Reviewers agreed at journal 05 May, 2025 Reviewers invited by journal 05 May, 2025 Editor assigned by journal 29 Apr, 2025 Submission checks completed at journal 29 Apr, 2025 First submitted to journal 25 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6530346","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":453139612,"identity":"b86360f6-0af1-4518-9e04-10d0746f8872","order_by":0,"name":"Ahmet ALKAL","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIie3RvQrCMBDA8ZNAXYquFb9e4aSr+CwJhXYpInRxVAK6iLO+hY8QKdSlWNwElxZXB0cHQaMiOqUdBfNfkiE/7iAAOt1PRjjAoEuNxz0FKI3ySUkSdF+EPgkpREIKhUl1uuZ4waRfqU93KYVucyWq0VlFrJhxNsNDYDTiACm49koQslCOEYwLEw9sYvmuRSFkD6IU7STj6ytu3+SWT3DPuGOikMSLJBH5pLPPuN1AJzAsnyBFx16GxFaSVuKEtdOw128vvCw9D3vN+WZ8VJKvTJR7yjP3Jz+V0+JvdTqd7q+6A6dCStZgG/nCAAAAAElFTkSuQmCC","orcid":"","institution":"Bingöl University","correspondingAuthor":true,"prefix":"","firstName":"Ahmet","middleName":"","lastName":"ALKAL","suffix":""}],"badges":[],"createdAt":"2025-04-25 15:53:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6530346/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6530346/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12955-025-02405-8","type":"published","date":"2025-09-26T15:56:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82393662,"identity":"e232136a-1072-4732-81cf-02d3ddbd625c","added_by":"auto","created_at":"2025-05-09 19:23:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118823,"visible":true,"origin":"","legend":"\u003cp\u003eThe change in the mean scores of SA, PF, ER and PW over time according to students' duration of smartphone use. SA (Smartphone Addiction), PF (Psychological Flexibility), ER (Emotion Regulation), PW (Psychological Wellbeing), T1 (Time 1), T2 (Time 2), T3 (Time 3).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6530346/v1/a7f435f790d616c99224f193.jpg"},{"id":82394044,"identity":"70280c20-68a6-44b0-b968-45c6b365ca2b","added_by":"auto","created_at":"2025-05-09 19:31:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":141992,"visible":true,"origin":"","legend":"\u003cp\u003eLongitudinal serial mediation model. ***p\u0026lt;0.001, T1 (Time 1), T2 (Time 2), T3 (Time 3).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6530346/v1/0ba238395035d266bd8aa564.jpg"},{"id":92430640,"identity":"6e4584ad-0b9a-4720-9794-80ad0f70657c","added_by":"auto","created_at":"2025-09-29 16:07:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1499736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6530346/v1/c2aeb551-c065-4c60-a168-07ee2da0433b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of Psychological Flexibility and Emotion Regulation in the Relationship Between Smartphone Addiction and Psychological Wellbeing in Adolescents: Three-Wave Longitudinal Serial Mediation Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWith the spread of mobile internet technology, smartphones have become an integral part of modern life. The multipurpose functions offered by these devices in the fields of communication, social interaction, access to information, entertainment, etc. capture users\u0026rsquo; attention [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and lead to an increase in the frequency and duration of smartphone use [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, excessive and uncontrolled use of smartphones brings along an important problem, such as the risk of smartphone addiction (SA) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The constant accessibility and various functionalities provided by smartphones increase individuals' addiction to these devices. Especially user-friendly interfaces, customizable notification settings, and automation features of mobile devices increase the risk of SA by creating a continuous usage cycle [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Moreover, personalized content and rewarding feedback mechanisms offered by mobile devices reinforce the SA cycle by triggering dopamine release [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough not specifically included in diagnostic guidelines such as DSM-5 and ICD-11, SA is defined as an uncontrolled behavioral pattern in which an individual's physiological, psychological, and social functions are impaired due to excessive use of these devices [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Globally, the increasing rate of smartphone use [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] raises concerns about the risk of SA [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Particularly adolescents are reported to be more vulnerable to the risk of SA compared to adults [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. (Cha \u0026amp; Seo, 2018). The relative weakness in adolescents' impulse control mechanisms and their intensive use of smartphones as a means of meeting their social and emotional needs make them a more vulnerable group in terms of SA [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Hence, numerous studies conducted with samples from different cultures reported a high prevalence of SA among adolescents. For example, a cross-sectional study conducted with 1447 Philippine adolescents reported the prevalence of SA as 66.2% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. SA prevalence was reported as 37% in Malaysia [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and 64.6% among Indian adolescents [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A study conducted by Lopez-Hernandez et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] on British adolescents aged 11\u0026ndash;18 years reported the prevalence of SA as 10%. It was reported that 30.9% of South Korean adolescents were in the risk group for SA [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A meta-analysis including 67 studies conducted in adolescent samples showed that the prevalence of SA among adolescents ranged between 4.3% and 70% [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Studies conducted in Turkey also show similar results. For instance, Daysal G\u0026uuml;ler et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported that 41.8% of adolescents were at risk of SA. Besides, studies conducted in a sample of university students in Turkey reported that the prevalence of SA ranged between 33.7% and 48.6% [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These results indicate that SA is an important problem among adolescents in Turkey and the world.\u003c/p\u003e \u003cp\u003eThe increasing prevalence of SA among adolescents indicates its potential to have negative effects on physical and mental health [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Various studies provide strong evidence of the negative effects of SA on adolescents\u0026rsquo; biopsychosocial development. For instance, prolonged screen time has been reported to reduce individuals\u0026rsquo; quality of life by causing various physical health problems such as musculoskeletal disorders, postural abnormalities, and respiratory problems [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. SA was detected to have a significant positive relationship with depression [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], anxiety [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], stress [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], loneliness [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and poor sleep quality [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. It was reported that SA could lead to problems such as poorer sleep quality and interpersonal relationships, lower academic achievement, and a higher risk of depression [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. SA was also reported to weaken social skills [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and lead to more loneliness [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Longitudinal studies showed that SA in adolescents predicted loneliness and depressive symptoms over time [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Systematic reviews and meta-analyses also supported significant associations between SA and physical and mental health problems such as depression, anxiety, musculoskeletal problems, poor sleep quality, and difficulty falling and staying asleep [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile the existing literature focuses on the effect of SA on mental health problems, research on its effects on psychological well-being (PW) remains relatively limited. Although increasing evidence indicates that SA increases mental health problems, there is a relatively insufficient number of studies that examined the direct and indirect effects of SA on PW. Considering the increasing prevalence of SA and its potential negative effects on mental health in the adolescent population, an in-depth examination of the relationship between SA and PW is of critical importance. Therefore, the current study aims to examine the relationship between SA and PW and the mediating roles of personal resources such as psychological flexibility (PF) and emotion regulation (ER) in this relationship using a longitudinal design. A longitudinal design is believed to contribute to the understanding of the causal patterns between these variables by revealing the changes in the relationships between these variables over time. In particular, examining the mediating mechanisms in the relationship between SA and PW is considered to provide important insights into the dynamic and sequential processes of interactions between the research variables. In addition, it is also predicted to contribute both to the expansion of theoretical knowledge and to the development of intervention programs aimed at protecting adolescents\u0026rsquo; mental health.\u003c/p\u003e"},{"header":"2. Literature review and hypotheses","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. The relationship between smartphone addiction and psychological wellbeing\u003c/h2\u003e \u003cp\u003eThe literature refers to reaching pathological levels of smartphone use using various concepts. SA, which is the most frequently used one among these concepts, refers to a psychological addiction to the device itself or the digital elements it contains, which occurs as a result of excessive, compulsive, and uncontrolled use of mobile devices [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Research shows that SA has similarities with symptoms observed in substance addictions such as loss of control, development of tolerance, withdrawal, and functional impairment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] and is characterized by symptoms such as inability to tolerate harmful consequences, preoccupation, inability to control cravings, loss of productivity, and anxiety [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, psychological well-being (PW) is defined as a multidimensional structure that includes individuals\u0026rsquo; efforts towards life goals, the processes of realizing their potential, the ability to establish deep and meaningful social relationships, harmonious interactions with their environment, and the ability to continuously support personal development [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. PW reflects the eudaimonic perspective of well-being and represents the basic aspects of optimal human functioning. In this regard, it emphasizes aspects of psychological functioning such as self-acceptance, social contribution, positive relationships with others, personal growth, and purpose in life [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In particular, PW plays a critical role in adolescence for the healthy progression of processes such as identity formation, social relationships, and planning for the future [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Therefore, it is considered an important indicator of adolescents' mental health.\u003c/p\u003e \u003cp\u003eSA is reported to be an important risk factor with potentially devastating effects on individuals' well-being [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Various theoretical and empirical explanations indicate the potential negative effects of SA on well-being. The empowerment-enslavement paradox indicates that although the features of mobile devices providing 24/7 access to wireless networks include many advantages, individuals may become dependent on the functionality of these devices and become their \u0026lsquo;slaves\u0026rsquo; [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Problematic or pathological smartphone use may have negative consequences on individuals' social relationships [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. In addition, with the increase in the time spent online, it is reported to cause disruptions in users' time management skills and neglect of other important areas of daily life. In particular, it is reported to shorten the time to be allocated to activities that are considered important for individuals\u0026rsquo; well-being and healthy lifestyles [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], which weakens positive mental health indicators [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In line with this theoretical framework, previous research reveals important findings indicating that SA has a negative effect on adolescents' PW. For instance, SA was consistently reported to be associated with lower PW in adolescents [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. SA was reported to have a significant negative relationship with positive psychological constructs such as resilience [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and life satisfaction [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and negatively predicts happiness [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. SA was reported to have a negative effect on PW both directly and indirectly through loneliness [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. In addition, preliminary findings of the first-year data of the three-year longitudinal study conducted by Alkorta [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] showed that smartphone usage time had a significant negative relationship with well-being and life satisfaction in adolescents. Based on the above theoretical explanations and previous research results, the current study proposes hypothesis H1.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH1.\u003c/b\u003e SA at T1 significantly and negatively affects PW at T3 among adolescents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Mediating role of psychological flexibility\u003c/h2\u003e \u003cp\u003ePsychological flexibility (PF) is defined as the capacity of an individual to approach his/her inner experiences (thoughts, emotions, physical sensations) with a non-judgmental awareness, to evaluate the current context and to regulate his/her behaviors in line with his/her values [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. PF, which is accepted as an important determinant of mental health, consists of six interrelated components. Acceptance, the first component, refers to the individual's experiencing painful thoughts, feelings and sensations as they are and having an open attitude towards these experiences instead of struggling with them. Cognitive defusion involves realizing that thoughts are only mental events, separate from reality, and not becoming overly attached to them. Being in touch with the present moment emphasizes focusing attention and awareness on the present moment rather than on past or future concerns. Self-as-context refers to perceiving oneself as a constantly observing self, separate from changing experiences. Values encourage the individual to identify the basic principles and goals that guide his/her life and to live a life in accordance with these values. Committed action involves taking consistent and decisive steps toward goals compatible with values [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. These six integrated components provide a significant contribution to establishing a healthier relationship with one's inner experiences and leading a life in harmony with one's values.\u003c/p\u003e \u003cp\u003eTheoretical suggestions propose that behavioral addictions have a negative effect on PF [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. According o this perspective, compulsive tendencies towards addictive behaviors and difficulty controlling these behaviors may undermine an individual's ability to stay connected to their immediate experiences, take value-driven actions, and effectively cope with challenging thoughts and emotions. Moreover, high levels of digital addiction may increase individuals' tendency to avoid or suppress negative internal experiences by weakening their ability to resist impulsive behaviors that are incompatible with their desired long-term goals [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], which may lead to the perpetuation of the addiction cycle and lower levels of PF. Hence, various types of digital addiction were consistently shown to be linked to PF in several studies. For instance, increased SA [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] and social media addiction [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] were found to reduce individuals' PF. In addition, social media addiction was detected to be a negative predictor of PF [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. SA was reported to have an indirect effect on procrastination behaviors through low PF [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Decreased PF was found to have a negative effect on individuals' PW [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. On the other hand, some findings showed that internet addiction was positively related to psychological inflexibility [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. A prospective study conducted by Peltz et al. [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e] determined that the increase in university students' problematic mobile phone use predicted the increase in their psychological inflexibility levels. These results support the view that SA may reduce adolescents' PF levels over time and thus lead to lower levels of PW. Therefore, the current study proposes hypothesis H2 based on this empirical evidence from the literature.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2.\u003c/b\u003e PF at T2 will play a mediating role in the longitudinal relationship between SA at T1 and PW at T3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Mediating role of emotion regulation\u003c/h2\u003e \u003cp\u003eEmotion regulation (ER) is generally defined as the capacity to manage emotional reactions. More specifically, it refers to the individual's ability to change the frequency, intensity, or duration of emotional experiences [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. ER consists of intrinsic and extrinsic processes used in achieving personal goals and regulating emotional responses [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Researchers identified various cognitive and behavioral strategies for adaptive and maladaptive ER processes [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Adaptive ER strategies such as acceptance, reappraisal, and problem-solving are reported to be effective in reducing the impact of negative emotional experiences [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. Using adaptive ER strategies more was reported to contribute to positive mental health [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e] and support physical and mental health [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. On the other hand, maladaptive ER strategies such as suppression, avoidance, and rumination have the potential to increase the persistence and severity of negative emotional states [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. It is emphasized that suppression or maintenance of negative emotions through maladaptive ER strategies may increase the likelihood of psychopathological conditions [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. In particular, more frequent use of maladaptive ER strategies is reported to be associated with increased psychological symptoms, poor mental health, and low well-being [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdolescence represents a significant transitional phase in an individual's emotional development and identity formation. In this critical period, mobile devices could become not only an important source of social interaction and information but also a tool for coping with emotional difficulties for adolescents. However, the literature provides evidence indicating that adolescents affected by various forms of digital addiction exhibit notable deficiencies in their ER skills [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. SA, in particular, is known to potentially increase impulsivity levels, shorten attention spans, and lead to problems in social relationships among adolescents. These factors could have negative effects on adolescents' capacity to recognize, understand, and effectively manage their negative emotions. Hence, adolescents who have SA may feel angry or frustrated more easily, or have difficulty controlling their emotional reactions when faced with stressful situations. This condition could lead them to resort to maladaptive ER strategies and, consequently, harm their PW.\u003c/p\u003e \u003cp\u003eExisting literature suggests that an increased risk of digital addiction is linked to low ER and decreased well-being. For instance, different types of digital addiction such as internet addiction [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e], problematic internet use and video game addiction [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e] and social media addiction [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e] have been reported to be inversely correlated with ER. Adolescents with internet addiction were reported to have more difficulties with ER [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. On the other hand, ER difficulties were found to have a significant positive relationship with SA [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e] and social media addiction [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e] and predicted problematic smartphone use [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. Longitudinal studies showed that maladaptive ER strategies were associated with problematic internet use [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e] and ER difficulties predicted internet addiction over time [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. Moreover, several studies reported that lower ER in adolescents was associated with lower well-being [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. These results suggest that ER may play a role as an important mediating variable in the longitudinal relationship between SA and PW. Therefore, the present study proposes hypothesis H3 in light of this empirical evidence.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3.\u003c/b\u003e ER at T2 will play a mediating role in the longitudinal relationship between SA at T1 and PW at T3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Series mediating role of emotion regulation and psychological flexibility\u003c/h2\u003e \u003cp\u003eSA poses an important risk factor that can potentially lead to negative effects on mental health. Research conducted in recent years consistently demonstrates the negative effects of SA on important mental health indicators such as PF and ER [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. SA is reported to weaken particularly PF components and narrow the behavioral repertoire [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], which weakens the capacity of adolescents to recognize and understand their negative emotional experiences and to develop behaviors in line with their values. Therefore, individuals with low PF levels are reported to experience higher rates of mental health problems [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. Low PF is also reported to negatively affect emotional regulation processes and trigger the use of maladaptive emotion regulation strategies [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. When adolescents with lower levels of PF encounter stressful or challenging life events, they may experience difficulties in regulating their emotional reactions and demonstrate intense emotional states such as increased anger or frustration. Instead of expressing their feelings constructively after a negative emotional experience, they may use maladaptive ER strategies such as withdrawal or avoidance. While these maladaptive ER strategies may provide temporary relief in the short term, they may lead to chronic emotional problems in the long term. Previous research has shown that low PF [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] and maladaptive ER [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e] are also associated with decreases in adolescents' well-being. This mutually reinforcing negative interaction of SA on PF and ER may lead to a decrease in adolescents' PW. Therefore, in light of the relevant literature, the present study proposes hypothesis H4.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH4.\u003c/b\u003e PF and ER at T2 will have a serial mediating role in the relationship between SA at T1 and PW at T3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. The present study\u003c/h2\u003e \u003cp\u003eThe widespread use of smartphones in adolescents [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e] has made the potential effects of overuse of these devices on mental health an important area of research. Especially the unique dynamics of adolescence and the risk of addiction development of excessive use of smartphones [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] require a more detailed examination of the effects of digital technologies on mental health. In this regard, understanding the psychological consequences of adolescents\u0026rsquo; interactions with the digital world is critical for efforts to protect and promote adolescents' mental health.\u003c/p\u003e \u003cp\u003eThe literature consistently reveals that SA increases negative mental health outcomes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and is associated with decreased well-being [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. However, relatively limited research examined the impact of SA on PW using a longitudinal design. Furthermore, the mediating mechanisms involved in the effect of SA on PW and how they interact have not yet been fully elucidated. Therefore, to fill these gaps, the present study focuses on the role of PF and ER as potential mediating mechanisms in the longitudinal relationship between SA and PW. More specifically, this study proposes a longitudinal serial mediation model that aims to examine whether PF and ER mediate the effect of SA on PW in both an independent and serial manner.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Method","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Participants and procedure\u003c/h2\u003e \u003cp\u003eThe participants of the study consisted of 10th, 11th, and 12th graders from two different high schools in a provincial center in the Eastern Anatolia Region of Turkey who used smartphones within the last six months. Data were collected in 3 waves in March, June, and September 2024. The first wave (T1) included 482 students (47.9% female and 52.1% male). The second wave (T2) included 465 students (49% female and 51% male). The third wave (T3) included 454 students (50.2% female and 49.8% male). Matching was performed according to student numbers, and 448 students (49.8% female and 50.2% male) who answered the questionnaires in all three waves constituted the final sample of the study (Range\u003csub\u003eage\u003c/sub\u003e=15\u0026ndash;19, M\u003csub\u003eage\u003c/sub\u003e=16.76, SD\u003csub\u003eage\u003c/sub\u003e=1.12). Socio-economic status was reported as low by 62 (13.8%), moderate by 256 (57.1%), good by 93 (20.8%), and very good by 37 (8.3%).\u003c/p\u003e \u003cp\u003e This study was approved by the Social and Human Sciences Scientific Research and Publication Ethics Committee of the university where the researcher was affiliated (ethics committee decision dated 21.02.2024 and numbered E.139903). The participants were informed about the purpose and procedures of the study. Participation in the study was on a voluntary basis and written informed consent was obtained from the students and their parents. Four different questionnaires were developed to control the sequential effect. The questionnaires were administered to the students in the classroom under the supervision of the researcher and the relevant course teacher. The students completed the questionnaires using paper and pencil in a session lasting 30\u0026ndash;35 minutes on average. The participating students were offered no financial incentives.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Measures\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Smartphone Addiction Scale-Short Version (SAS-SV)\u003c/h2\u003e \u003cp\u003eSAS-SV, which was developed by Kwon et al. [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e] and adapted into Turkish by Şata and Karip [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e], was used to determine the adolescents\u0026rsquo; SA levels. The Turkish version of the scale consists of 10 items and one factor. The scale is responded on a Likert-type scale ranging from 1 (strongly disagree) to 6 (strongly agree). Higher scores indicate adolescents\u0026rsquo; higher SA levels. The Turkish version of the scale showed excellent construct validity (GFI\u0026thinsp;=\u0026thinsp;.93; AGFI\u0026thinsp;=\u0026thinsp;.88; CFI\u0026thinsp;=\u0026thinsp;.99; NNF\u0026thinsp;=\u0026thinsp;.98; RMSEA\u0026thinsp;=\u0026thinsp;.064; SRMR\u0026thinsp;=\u0026thinsp;.046) and internal consistency (α\u0026thinsp;=\u0026thinsp;.90) [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Five-Dimensional Well-Being Scale for Adolescents (EPOCH)\u003c/h2\u003e \u003cp\u003eThe EPOCH scale, which was developed by Kern et al. [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e] and adapted into Turkish by Demirci and Ekşi [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e], was used to determine the adolescents\u0026rsquo; PW levels. The scale consists of five dimensions and 20 items and is scored by responding to Likert scale ratings from 1 (never) to 5 (always). A higher total score obtained from the scale indicates higher psychological well-being levels. The Turkish version of the scale was reported to show excellent construct validity (x\u0026sup2;/df\u0026thinsp;=\u0026thinsp;2,383; RMSEA\u0026thinsp;=\u0026thinsp;0.074, NFI\u0026thinsp;=\u0026thinsp;.96; NNFI\u0026thinsp;=\u0026thinsp;.98; CFI\u0026thinsp;=\u0026thinsp;.98; IFI\u0026thinsp;=\u0026thinsp;.98; RFI\u0026thinsp;=\u0026thinsp;.96; SRMR\u0026thinsp;=\u0026thinsp;.052) and internal consistency (α\u0026thinsp;=\u0026thinsp;.95 for total score) [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3. Multidimensional Psychological Flexibility Inventory Short Form (MPFI-SF)\u003c/h2\u003e \u003cp\u003eMPFI-SF, which was developed by Rolffs et al. [\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e] and adapted into Turkish by Alkal and \u0026Ccedil;am [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e], was used to determine the adolescents\u0026rsquo; PF levels. The inventory consists of 24 items and two dimensions (psychological flexibility and psychological inflexibility). It is scored by responding to the Likert scale ratings from 1 (never relevant) to 6 (always relevant) considering the last two weeks. In this study, 12 items in the PF subscale of the MPFI-SF were used to calculate the adolescents\u0026rsquo; PF scores. Higher scores in the PF subscale indicate adolescents\u0026rsquo; higher PF levels. The Turkish version of the MPFI-SF was reported to show excellent internal consistency (α\u0026thinsp;=\u0026thinsp;.97, .96 for sub-dimensions) and construct validity (χ\u0026sup2;/sd\u0026thinsp;=\u0026thinsp;2.197; CFI\u0026thinsp;=\u0026thinsp;.97; NFI\u0026thinsp;=\u0026thinsp;.92; IFI\u0026thinsp;=\u0026thinsp;.96; TLI\u0026thinsp;=\u0026thinsp;.95; RMSEA\u0026thinsp;=\u0026thinsp;.072; SRMR\u0026thinsp;=\u0026thinsp;.032) [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4. Regulation of Emotions Questionnaire (REQ)\u003c/h2\u003e \u003cp\u003eThe adolescents\u0026rsquo; ER scores were determined using the REQ developed by Phillips and Power [\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e] and adapted into Turkish by Duy and Yıldız [\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. The REQ consists of 18 items and four dimensions (internal-functional, internal-dysfunctional, external-functional, and external-dysfunctional emotion regulation). The scale is scored by responding to Likert-type ratings from 1 (never) to 6 (always). In this study, 8 items in the internal-functional and external-functional emotion regulation subscales of the REQ were used to calculate adolescents' ER scores. Higher scores in the functional emotion regulation sub-dimensions indicate adolescents' higher ER levels. The construct validity of the 4-dimensional Turkish version of the REQ was confirmed (χ2/df\u0026thinsp;=\u0026thinsp;4.01, RMSEA\u0026thinsp;=\u0026thinsp;.06, RMR\u0026thinsp;=\u0026thinsp;.09, SRMR\u0026thinsp;=\u0026thinsp;.06, GFI\u0026thinsp;=\u0026thinsp;.94, AGFI\u0026thinsp;=\u0026thinsp;.92, CFI\u0026thinsp;=\u0026thinsp;.93, NFI\u0026thinsp;=\u0026thinsp;.91, NNFI\u0026thinsp;=\u0026thinsp;.92) and Cronbach\u0026rsquo;s alpha for the internal-functional and external-functional emotion regulation sub-dimensions was found to be .74 and .59, respectively [\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Data analysis\u003c/h2\u003e \u003cp\u003eFirstly, descriptive statistics (mean, SD, skewness and kurtosis) and correlation coefficients between variables in T1, T2 and T3 were calculated. Secondly, Harman's one-factor test was analyzed to test the possibility of common method bias. Then, serial mediation analysis (Model 6) was performed using Hayes' PROCESS macro v3.4 to test the research model (Fig.\u0026nbsp;1). In these analyses, we entered SA at T1 as the independent variable, PW at T3 as the dependent variable, and PF and ER at T2 as mediating variables. In addition, demographic variables (gender, age and socio-economic status) were included in the analysis as control variables. The statistical significance of mediation effects was assessed using 95% confidence intervals calculated by bootstrapping based on 5000 resampling. The statistical significance level was accepted as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were performed using SPSS 25 software.\u003c/p\u003e \u003cp\u003eSerial mediation analysis includes methods such as structural equation modeling (SEM) and PROCESS macro. Studies comparing SEM and PROCESS showed that the mediation model results obtained with both were largely similar [\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e]. Its user-friendliness and the provision of results compatible with SEM have made the PROCESS macro increasingly popular. Therefore, the present study utilized the PROCESS macro to perform the longitudinal serial mediation analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Preliminary Findings\u003c/h2\u003e\n \u003cp\u003eFigure 1 demonstrates the change in the SA, PF, ER, and PW mean scores over time according to the participating students\u0026rsquo; daily phone usage time. An analysis of Fig. 1 shows that the SA mean scores increased and the PF, ER, and PW mean scores decreased over time (T1, T2, and T3) in the students who reported using smartphones for more than four hours per day. This result shows that the increase in the duration of daily smartphone use increases the risk of SA in adolescents over time and affects their mental health negatively.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Descriptive statistics and correlation analysis\u003c/h2\u003e\n \u003cp\u003eThe skewness (range\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.58 and 1.11) and kurtosis (range\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.96 and 1.30) values presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003esupport the normal distribution of the data. In addition, Cronbach\u0026apos;s alpha (\u0026alpha;) reliability coefficients of SA, PF, ER, and PW were highly reliable in all three waves. Correlation analysis results showed that there were significant relationships between all variables both within and between waves in the expected direction. SA was found to have a significant negative correlation with PF, ER, and PW. In addition, there was a significant positive relationship between PF, ER, and PW.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDescriptive statistics, reliabilities and correlation analysis\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.\u003c/strong\u003e SA(T1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.\u003c/strong\u003e SA(T2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.60\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.\u003c/strong\u003e SA(T3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.62\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.63\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.\u003c/strong\u003e PF(T1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.37\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.15\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.18\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.\u003c/strong\u003e PF(T2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.42\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.56\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.38\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.67\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.\u003c/strong\u003e PF(T3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.38\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.26\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.42\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.66\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.\u003c/strong\u003e ER(T1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.39\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.20\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.24\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.25\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.15\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.22\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.\u003c/strong\u003e ER(T2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.54\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.28\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.37\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.54\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.\u003c/strong\u003e ER(T3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.45\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.19\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.27\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.22\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.34\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.62\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.65\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.\u003c/strong\u003e PW(T1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.33\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.16\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.10\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.42\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.28\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.31\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.50\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.59\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.66\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.\u003c/strong\u003e PW(T2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.34\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.35\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.38\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.33\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.33\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.63\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.68\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.\u003c/strong\u003e PW(T3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.37\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.41\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.40\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.28\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.49\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.44\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkewness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKurtosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; SA (Smartphone Addiction), PF (Psychological Flexibility), ER (Emotion Regulation), PW (Psychological Wellbeing), T1 (Time 1), T2 (Time 2), T3 (Time 3).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3. Test of common method bias\u003c/h2\u003e\n \u003cp\u003eThis study used Harman\u0026apos;s one-factor test to examine whether there was a common method bias since data were collected through a self-report questionnaire. Factor analysis without rotations was performed on 50 items used to measure SA, PF, ER, and PW variables at three different time points (T1-T2-T3). Analysis results indicated 11 factors with eigenvalues greater than 1 at T1, and nine factors at T2 and T3. The total variance explained by the first factor was 28.73% at T1, 28.14% at T2, and 28.88% at T3. The first factor explains less than 40% of the total variance at all three time points [\u003cspan class=\"CitationRef\"\u003e108\u003c/span\u003e], which indicates that there is no significant common method bias in this longitudinal study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003e4.4. Serial Mediation Analysis\u003c/h2\u003e\n \u003cp\u003eThe serial mediation effect of PF and ER at T2 on the longitudinal effect of SA at T1 on PW at T3 was analyzed using PROCESS Macro Model 6. Demographic variables (gender, age, and socio-economic status) were controlled in the mediation analysis. The significance of the indirect effect of SA on PW mediated by PF and ER was determined according to the 95% confidence interval (CI) obtained by the bootstrapping method (5000 bootstrap samples). CIs values were in the same direction; namely, they did not contain zero, which indicates that the indirect effect is significant. Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrate the results of the longitudinal serial mediation analysis.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img1746818486.png\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cp\u003eThe findings in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e show that SA at T1 negatively predicts PW at T3 (\u0026beta;= -0.34, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), PF at T2 (\u0026beta;= -0.39, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and ER (\u0026beta;= -0.23, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). PF at T2 positively predicts ER at T2 (\u0026beta;\u0026thinsp;=\u0026thinsp;0.17, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and PW at T3 (\u0026beta;\u0026thinsp;=\u0026thinsp;0.40, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). ER at T2 also positively predicts PW at T3 (\u0026beta;\u0026thinsp;=\u0026thinsp;0.73, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). While the direct effect of SA at T1 on PW at T3 was significant in the first model, the effect was not statistically significant when the mediating variables (PF and ER in T2) were included in the analysis (Model 4). This finding suggests that PF and ER at T2 play a fully mediating role in the longitudinal relationship between SA at T1 and PW at T3. These findings suggest that adolescents\u0026apos; SA levels at T1 indirectly reduce PW at T3 by reducing PF and ER levels at T2. Bootstrapping analysis was performed to confirm the significance of PF and ER at T2 on the relationship between SA at T1 and PW at T3, and the results are presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img1746818485.png\"\u003e\u003c/div\u003e\n \u003cp\u003eThe findings in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e show that PF (\u0026beta;= -0.15, SE\u0026thinsp;=\u0026thinsp;0.03, 95% CI = [-0.2036, -0.1053]) and ER (\u0026beta;= -0.17, SE\u0026thinsp;=\u0026thinsp;0.03, 95% CI = [-0.2288, -0.1054]) at T2 mediate the longitudinal relationship between SA at T1 and PW at T3. In addition, PF and ER at T2 seem to have a fully serial mediation role in the longitudinal relationship between SA at T1 and PW at T3 (\u0026beta;= -0.05, SE\u0026thinsp;=\u0026thinsp;0.01, 95% CI = [-0.0733, -0.0268]). The longitudinal serial mediation model explained 32% (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.32) of the dependent variable (PW).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eResearch to date has demonstrated the impact of SA on negative mental health outcomes in adolescents, yet longitudinal research that examines the direct and indirect effects of SA on PW is limited. To our knowledge, this is the first study to examine the mediating effects of PF and ER on the relationship between SA and PW in adolescents using a longitudinal design. Our study provides an important foundation for a more detailed understanding of the relationship between SA and PW and provides strong evidence for the relationships among SA, PW, PF, and ER in an adolescent sample. Our preliminary findings showed that adolescents who used smartphones more than four hours a day had higher SA scores at all three time points (T1-T2-T3) than those who used smartphones between 0\u0026ndash;2 hours and 2\u0026ndash;4 hours. On the other hand, PW, ER and PF scores were found to be lower. These findings suggest that the increase in adolescents' daily smartphone usage time increases the risk of SA over time and negatively affects positive mental health outcomes. This suggests that mobile device technology is an important factor to be considered in the psychosocial development of adolescents. It particularly emphasizes the importance of regulating adolescents' smartphone usage habits. In addition, it once again reveals the necessity of developing comprehensive mental health strategies to prevent the negative effects of increased screen time with the widespread use of smartphones on adolescents' mental health.\u003c/p\u003e \u003cp\u003eIn our first hypothesis (H1), we proposed that SA at T1 would significantly and negatively affect PW at T3 in adolescents. The findings of this study show that higher SA in adolescents leads to lower PW over time, which furthers previous research results [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. Several possible explanations could be put forward for this finding: First, the compelling features of mobile device use, such as the search for uninterrupted connectivity and reassurance, may negatively affect the frequency and quality of individuals' face-to-face social interactions [\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e]. When this finding is evaluated within the framework of the displacement hypothesis, the increase in the time spent on mobile devices may lead to a decrease in the time allocated for offline communication and a weakening of social relationships [\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e]. In this regard, digital communication methods could be considered to reduce relationship satisfaction [\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e] and thus lead to lower PW levels. Secondly, excessive and unconscious use of smartphones could cause distraction, difficulty focusing, and increased stress levels [\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e]. It may also increase anxiety levels by encouraging individuals to constantly check their smartphones and stay active in the virtual environment [\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e]. Increased stress [\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e] and anxiety [\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e] resulting from SA may have a negative effect on adolescents' PW. Thirdly, it can be argued that SA causes a decrease in adolescents' PW levels by increasing negative emotional states [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In conclusion, the current study reveals the urgency of developing and implementing evidence-based preventive programs to reduce the potential harms of SA.\u003c/p\u003e \u003cp\u003eAnother important finding of the study reveals that PF at T2 mediates the longitudinal relationship between SA at T1 and PW at T3. More specifically, it shows that SA reduces adolescents' PF levels over time, which is associated with lower PW. This result supports the H2 hypothesis proposed in our study and advances the cross-sectional findings in the existing literature [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] with a longitudinal perspective. Digital addictions are reported to trigger dysfunctional processes such as coping with or trying to reduce unwanted thoughts, feelings, or experiences [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e]. In this regard, SA could be considered to cause lower PF levels by negatively affecting adolescents\u0026rsquo; PF components over time, such as adapting to changing conditions, behaving toward personal values, and being open to instant experiences [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In particular, it can be argued that SA narrows individuals\u0026rsquo; behavioral repertoire by strengthening the tendency to avoid disturbing internal experiences and thus negatively affects PF over time [\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e]. In the literature, it is emphasized that individuals who tend to avoid negative thoughts and emotions rigidly increase their psychological distress levels and impair their functionality [\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e]. It is stated that this avoidance pattern negatively affects adolescents' PW levels and their ability to cope with the difficulties of daily life in a harmonious way [\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e]. Based on this theoretical framework, it can be argued that low PF in adolescents leads to lower PW levels over time. Our findings support previous research results showing the negative impact of low PF on PW [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] and provide important evidence for this relationship. It also suggests that interventions aimed at increasing PF may have a potential role in reducing the negative effects of SA on adolescent mental health.\u003c/p\u003e \u003cp\u003eAnother noteworthy finding of the study is that ER at T2 is an important mediating variable in the longitudinal relationship between SA at T1 and PW at T3, which supports hypothesis H3. In other words, SA seems to weaken adolescents' ER skills over time, which leads to lower PW levels. This finding can be explained from the perspective of the Theory of Compensatory Use of the Internet [\u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e], which initially refers to Internet use and then covers various digital addictions, including SA. This theory posits that individuals may turn to mobile devices more as a coping strategy for the negative emotional states they experience [\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e]. Excessive mobile device use may trigger individuals' motivation to avoid facing negative emotional experiences and resort to virtual environments, which leads them to maladaptive ER strategies instead of using healthy ways of managing them. Such a condition could lead to the learning and reinforcement of dysfunctional ER strategies such as suppressing emotional reactions, distraction, or providing a temporary escape through virtual interactions [\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e]. Hence, research has shown that adolescents who have internet addiction have significant difficulties with ER skills [\u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e]. In this context, it can be argued that individuals' inability to effectively regulate their emotional experiences significantly reduces their ability to maintain positive emotional states [\u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e, \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e], which leads to lower PW levels. In conclusion, in line with the theoretical framework and previous research results, the findings of this study support that ER is an important mediating variable in the longitudinal effect of SA on adolescents' PW. Interventions aiming to increase ER skills may make a significant contribution to reducing the negative impact of SA on PW.\u003c/p\u003e \u003cp\u003eThe last noteworthy finding of the current study reveals that PF and ER at T2 play a serial mediating role in the longitudinal relationship between SA at T1 and PW at T3, which supports hypothesis H4. More specifically, it can be argued that SA leads to a decrease in adolescents' PF levels over time, which in turn leads to lower ER levels, negatively affecting PW levels. Digital addictions may reduce PF levels by weakening adolescents' awareness of being in the moment, their ability to accept their negative thoughts and emotions, and their capacity to exhibit behaviors in line with their personal values [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Decreased PF may lead to the development of more rigid thought patterns and the narrowing of the behavioral repertoire. This may increase adolescents' tendency to engage in maladaptive ER strategies [\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e]. It can be argued that this chain effect ultimately leads to a decrease in adolescents' PW levels. In conclusion, the current study advances previous research findings by revealing the causal relationships among SA, PF, ER and PW. It also supports the potential benefits of addressing PF and ER within an integrated treatment approach in reducing mental health problems associated with SA. In this context, it is thought that targeting PF and ER skills simultaneously in the design of future intervention programs may increase the effectiveness of the treatment.,\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.1. İmplications and Limitations\u003c/h2\u003e \u003cp\u003erevealing the longitudinal relationships among SA, PF, ER and PW. By elucidating the potential causal relationships between these variables, our research fills an important gap in the literature and contributes significantly to the understanding of the conceptual framework. Especially the longitudinal serial mediation model proposed and tested in the study provides a holistic perspective on how the relationship between SA and PW is mediated through sequential psychological processes. The findings show that PF and ER have significant mediating roles both separately and serially in the relationship between SA and PW. This provides important insights that SA indirectly leads to lower levels of PW by reducing adolescents' PF and ER levels over time. It also suggests that SA is a potential risk factor for positive mental health indicators.\u003c/p\u003e \u003cp\u003eThe longitudinal evidence provides an important foundation for future theoretical models and intervention strategies. It emphasizes that especially PF and ER play a central role in understanding the negative effects of SA on psychological health, which has become a common phenomenon of modern life. An analysis of the findings in the context of the buffering hypothesis [\u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e127\u003c/span\u003e] shows that PF and ER reduce the direct effect of SA on PW over time. It emphasizes the protective role of high PF and ER, especially in the effect of SA on mental health problems. High levels of PF and ER may mitigate psychological difficulties resulting from excessive use of mobile devices and thus reduce the risk of developing negative mental health outcomes. In this regard, intervention programs that aim to increase PF and ER skills both separately and simultaneously may reduce the negative effects of SA on mental health.\u003c/p\u003e \u003cp\u003eIn today's digitalized world, the prevalence and accessibility of mobile devices have become an integral part of adolescents' lives, which reveals a reality where it is becoming increasingly difficult to completely restrict the use of mobile devices. Therefore, parents, mental health professionals and school administrations have important responsibilities in the process of reducing the potential negative effects of SA on mental health and protecting adolescent mental health. Parents should have an open and honest dialogue with their children, be informed about their mobile device usage purposes and online experiences, set appropriate boundaries, and take a supportive role when necessary. Mental health professionals could develop and implement evidence-based intervention programs for adolescents who are victims of SA or demonstrate SA behaviors. School administrations should focus on developing strategies to strengthen adolescents' digital literacy skills. In this regard, digital literacy training is believed to enable adolescents to recognize the potential risks associated with the use of mobile devices and to be aware of the potential negative effects of these devices on physical (e.g. sleep disorders, eye health problems, postural disorders) and mental health (e.g. cyberbullying, addiction).\u003c/p\u003e \u003cp\u003eThe findings of the present longitudinal study should be interpreted within the framework of several limitations that should be taken into consideration. Firstly, the instruments used in the data collection process were based on the participants\u0026rsquo; self-report, which is a potential limitation. Although three different questionnaires were administered to control for the sequential effect and no significant common method bias was detected through statistical analyses, self-report data may be susceptible to subjective interactions such as social desirability or recall issues. This may not fully reflect the true strength and nature of the relationships between the variables analyzed. Future research could enhance the validity and reliability of the findings by enriching self-report data with different data sources (e.g. behavioral observations and parental assessments).\u003c/p\u003e \u003cp\u003eThis diversified methodological approach is believed to allow for a more comprehensive and objective understanding of the relationship between the research variables. Secondly, limiting the data collection intervals to three-month periods may limit the exploration of the long-term development and possible lagged effects of the dynamic relationships between the variables under study. Future research could more comprehensively examine the complex and time-spanning effects of SA on adolescents' mental health by using longitudinal designs covering wider time intervals. Finally, the study sample was limited to adolescents who received education in a provincial center in the Eastern Anatolia Region of Turkey. This demographic and geographical specificity may limit the generalizability of the findings to larger adolescent populations and different socio-cultural contexts. Conducting future research in more comprehensive samples could provide more precise conclusions about the universality and contextual differences of the impact of SA on mental health.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003eThis longitudinal study aimed to examine the relationships among SA, PF, ER, and PW in an adolescent sample using a three-wave longitudinal design. Through a novel longitudinal serial mediation model supported by data collected at three different time points, it empirically tested the serial mediation role of PF and ER in the longitudinal relationship between SA and PW. The findings showed that PF and ER mediated both separately and serially the negative effect of SA on PW over time in adolescents. More specifically, it can be argued that SA causes a decrease in adolescents' PF skills and their capacity to effectively manage their emotional reactions over time, which leads to lower PW levels. These findings emphasize the potential of interventions to improve PF and ER skills in alleviating SA-related mental health problems in adolescents. They also suggest that both strengthening PF and ER skills separately and addressing them simultaneously may significantly increase the effectiveness of treatment approaches. Future research could contribute to the body of knowledge in this area by examining how this longitudinal serial mediation model varies across different cultural contexts and how the dynamic relationships between these variables are affected by cultural differences.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted in accordance with the principles of the Declaration of Helsinki and ethics committee approval was obtained from Bingöl University Social and Human Sciences Scientific Research and Publication Ethics Committee (protocol numbered 21.02.2024-E.139903).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data for this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares that he has no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any financial support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll chapters of this study were prepared by a single author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the adolescents and their parents who participated in this study, the teachers at the high school who supported our data collection, and the school counselors who assisted in data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBillieux J. 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The relationship between psychological inflexibility and well-being in adults: a meta-analysis of the Acceptance and Action Questionnaire. Behav Ther. 2024;55(1):26\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElhai JD, Levine JC, Hall BJ. The relationship between anxiety symptom severity and problematic smartphone use: A review of the literature and conceptual frameworks. J Anxiety Disord. 2019;62:45\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKardefelt-Winther D. A critical account of DSM-5 criteria for internet gaming disorder. Addict Res Theory. 2015;23(2):93\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFortes AB, Broilo PL, Lisboa CSM. Smartphone use and psychological well-being: the moderating role of emotion regulation. Trends Psychol. 2021;29:189\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSatıcı B, Deniz M. Modeling emotion regulation and subjective happiness: smartphone addiction as a mediator. ADDICTA Turk J Addict. 2020;7(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams AD, Grisham JR. Impulsivity, emotion regulation, and mindful attentional focus in compulsive buying. Cogn Ther Res. 2012;36:451\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFaustino B. Transdiagnostic perspective on psychological inflexibility and emotional dysregulation. Behav Cogn Psychother. 2021;49(2):233\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull. 1985;98(2):310.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Smartphone Addiction, Psychological Flexibility, Emotion Regulation, Psychological Well-being","lastPublishedDoi":"10.21203/rs.3.rs-6530346/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6530346/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWhen the increasing prevalence of Smartphone Addiction (SA) and its potential negative effects on mental health among adolescents are taken into consideration, an in-depth investigation of the relationship between SA and Psychological Well-being (PW) is of critical importance. Therefore, using a three-wave longitudinal research design, this study aimed to examine the serial mediation role of Psychological Flexibility (PF) and Emotion Regulation (ER) in the relationship between SA and PW. To our knowledge, this is the first study to examine SA, PF, ER, and PW relationships and mediating mechanisms in an adolescent sample using a longitudinal design.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study included 448 adolescents (49.8% female and 50.2% male; Range\u003csub\u003eage\u003c/sub\u003e=15\u0026ndash;19, M\u003csub\u003eage\u003c/sub\u003e=16.76, SD\u003csub\u003eage\u003c/sub\u003e=1.12) who responded to the questionnaires in three waves. Participating adolescents responded to a 50-item questionnaire consisting of the Smartphone Addiction Scale-Short Version (SAS-SV), the Five-Dimensional Well-Being Scale for Adolescents (EPOCH), the Multidimensional Psychological Flexibility Inventory Short Form (MPFI-SF), and the Regulation of Emotions Questionnaire (REQ). The questionnaires were filled in using pen and paper in a classroom environment under the supervision of the teacher and the researcher.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared to those who used their smartphones for 0\u0026ndash;2 hours and 2\u0026ndash;4 hours, adolescents who reported to use their smartphones for more than four hours daily were found to have higher SA scores and lower PW, ER, and PF scores across all three time points (T1, T2, and T3). The findings indicated that SA at T1 negatively predicted PW at T3 (β= -0.34, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), PF at T2 (β= -0.39, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), and ER at T2 (β= -0.23, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). On the other hand, PF at T2 positively predicted ER at T2 (β\u0026thinsp;=\u0026thinsp;0.17, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and PW at T3 (β\u0026thinsp;=\u0026thinsp;0.40, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), and ER at T2 positively predicted PW at T3 (β\u0026thinsp;=\u0026thinsp;0.73, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Besides, PF at T2 (β= -0.15, SE\u0026thinsp;=\u0026thinsp;0.03, 95% CI = [-0.2036, -0.1053]) and ER at T2 (β= -0.17, SE\u0026thinsp;=\u0026thinsp;0.03, 95% CI = [-0.2288, -0.1054]) were found to fully mediate the longitudinal relationship between SA at T1 and PW at T3. The longitudinal serial mediation model accounted for 32% of the variance in PW (R\u0026sup2; = .32).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study shows that SA leads to a decrease in adolescents' PF skills and their capacity to effectively manage their emotional reactions over time, which in turn leads to lower PW levels. The findings emphasize the potential of interventions to improve PF and ER skills in alleviating SA-related mental health problems in adolescents. The findings also suggest that both strengthening PF and ER skills separately and addressing them simultaneously could significantly increase the effectiveness of treatment approaches.\u003c/p\u003e","manuscriptTitle":"The Role of Psychological Flexibility and Emotion Regulation in the Relationship Between Smartphone Addiction and Psychological Wellbeing in Adolescents: Three-Wave Longitudinal Serial Mediation Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 19:23:47","doi":"10.21203/rs.3.rs-6530346/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-01T15:07:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-10T16:17:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295373319457998316189309433829208175185","date":"2025-05-07T08:56:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333083684102762597590395976965760956850","date":"2025-05-05T13:45:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-05T07:44:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-29T09:25:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-29T09:18:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Health and Quality of Life Outcomes","date":"2025-04-25T15:38:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2359d1df-f465-4392-abc4-fd6c082800d8","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T16:04:18+00:00","versionOfRecord":{"articleIdentity":"rs-6530346","link":"https://doi.org/10.1186/s12955-025-02405-8","journal":{"identity":"health-and-quality-of-life-outcomes","isVorOnly":false,"title":"Health and Quality of Life Outcomes"},"publishedOn":"2025-09-26 15:56:59","publishedOnDateReadable":"September 26th, 2025"},"versionCreatedAt":"2025-05-09 19:23:47","video":"","vorDoi":"10.1186/s12955-025-02405-8","vorDoiUrl":"https://doi.org/10.1186/s12955-025-02405-8","workflowStages":[]},"version":"v1","identity":"rs-6530346","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6530346","identity":"rs-6530346","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}