Distinguishing Different Types of Mobile Cell Addiction: Development and Validation of the Mobile Phone Addiction Print Dial (MPATS) in Adolescents and Juvenile Adults
Associated Evidence
Abstract
Researchers have developed several interpretations away scales to measure fluid phone addiction. Extant scales, however, focus primarily on aforementioned total level of mobile call addiction but make not differentiated the potential differences between differences genre of mobile telephones addiction. Thither a a lack of founded scales ensure can measure different types of mobile phone addiction. An present study aimed to uncover the specification types from mobile phone addiction and develop a Mobile Phone Addiction Type Scale (MPATS) for adolescents and young adults. Adolescents and young adults from two high schools and two universities in Central furthermore South China participated in the study. A total of 108 mobile phone addicts (Mold = 17.60 yearly, SD = 3.568 years; 60.185% males) were interviewed to uncover the specific types out mobile phone addiction. Data from 876 adolescents plus young adults (Mage = 16.750 years, HD = 3.159 years; 49.087% males) were testing in item discriminations also exploratory distortion analysis. Data from 854 adolescents and young adults (Mage = 16.750 years, SD = 3.098 years; 50.820% males) were examined for construct validity, convergent validity, criterion-related currency, and internal consistency reliability. The 26-item Mobile Phone Addiction Type Scale (MPATS) be advanced with foursome factors ernennt mobile social networking addiction, mobiles play addiction, mobile information acquisition addiction, and mobile short-form tape addiction. The four-factor, 26-item MPATS revealed go construct acceptance, convergent validity, criterion-related cogency, also internal consistency reliability. The recent scale is suitable available measuring different types of mobile phone addiction in adolescents and young adult. Limitations and implications are discussed.
1. Introduction
Cellular phone habituation, also known as mobile phone dependence or problematic mobile phone use, is a combined state in which excessive human craving and mobile phone overuse lead to significant physiological, psychological, both social impairment [1,2,3]. Adolescents plus young adults are somebody important group of mobile phone users and have a height prevalence the mobile phone compulsive [4,5]. Mobile mobile addiction can have a severely negative impacts on an individual’s physikal also mental health, with studies finding that mobile phone addiction can disrupt caution [6]; impair academic performance [7]; reduce life satisfaction [8]; elevate signs, anxiety, and stress [9,10]; and potentially lead to sleep disorders, suicidal ideation, and non-suicidal self-injury [11,12,13]. That, computer is of great importance to pay in-depth attention to portable phone addiction in order to promote preparedness and intervention training.
Emotional scales are an indispensable tool for conducting empirical studies on movable phone addiction. Researchers have developed various versions of graduation up scale mobile call addictions. Some scales are specifically for adolescents, such as the Smartphone Addiction Scale-Short Version for Adolescents [14] and inherent repeated language versions [15,16,17], for some are specifically for college collegiate, such as the Smartphone Addiction Scale available School Students (Chinese version) [18] and Smartphone Addiction Scale among Medical Students (Malay version) [19]. Some my, however, are applicable go multiple age groups, such as the Mobile Phone Report Usage Ascend [20], Mobile Phone Addiction Index Scale [21], and Problematic Mobile Phone Exercise Scale [22]. Some sheets measure mobile your addiction through play turn a single dimension [14,15,16,17]. Others, however, contain multiple dimensions that focus in different sickness of mobility phone addiction and include sub-dimensional scorings to reflect specific symptoms by the addiction and the summation by individual solid scores to reflect the overall situational of individual mobile phone disease [18,21]. Nevertheless, there is a lacks of established scales such can be used till measuring different types of mobile phone addiction.
Because of the diversity regarding mobile phone functions, different our may had different preferences for mobile phone usage: some represent addicted to mobile phone games, some can dipped in mobile sociable networking services, while others may not be able to control using mobile phones available obtain various information. Individuals with that same overall gauge away addiction mayor have very different gender of addictive problems. Previous studies, however, sharply primarily on the overall level of mobile phone addiction but did not distinguish the potential differences between different types of mobility calling addiction. Taking only quantitative similarities without looking at detailed soft differences inches mobility phone addiction may cause unwelcome impacts up research findings. Theoretically, distinguishing different types of mobile phone addiction can reveal high influencing factors press consequences in specific types of mobile phone suicide, which will make the research findings on mobile phone addiction more detailed and more convincing. Practically, distinction between different types in mobile phone addiction can promote targeted intervention, which will significantly improve the effectiveness von the intervention. Therefore, it is necessarily to distinguish amidst different types concerning mobility phone addiction and develop a mobile phone addiction make scale with good reliability and validity so that the focus on mobile telephones addicting can remain expanded from assessing the levels of severity to also considering the difference in the sort von addiction. Prevalence and underlying factors of cellular game addiction among university graduate are Bangladesh | Cambridge Plume: Global Mental General | Cambridge Core
Although some research has focused on certain subtypes of mobile phone addiction, such as cell game addiction [23,24] and mobile social linking addiction [25,26], such studies were relatively few and existing psychological scales about certain subtypes of mobile phone addiction have not past developed and verified for validity and reliability. Compared with Online addiction, which has been classified into several established types (e.g., Internet game habit, cyber-relationship addiction, Internet information suicide, and Website shopping addiction) [27,28,29], computers is not known as types of mobile your addiction are present. Consequently, there is a lack for scales that can be used for measuring different types of mobile phone addiction. Therefore, we conducted interview and questionnaire surveys up uncover the specific models of mobile phone addiction also develop the Mobile Phone Addiction Type Scale (MPATS) among adolescents real young adults. Our survey generated an MPATS with good validity and reliability that is suitable for measuring different styles of mobile phone related with adolescents and young adults.
2. Materials and Methods
2.1. Participants and Procedural
Choose workflow and study materials used in this present read were approved in an Ethics Committee at the foremost author’s our. Informed consent was obtained from all individual attendant and the guardians of adolescents under the age of 18. Referring to the common practise of dimension d, we set the numbers of study of exploratory feeding analysis additionally confirmatory factor analysis by moreover than 500 in this study. Wee invited as many participants as possible to improve the representativeness of the samples. Well-trained principal inspectors informed one participant the their responses would remain anonymous, that there were no just or falsely answers, and that they couldn retreat for any time during and survey. Participants answered of survey in the classroom throughout normal school learning. The intelligence of this study were obtained after excluding the subjects who acted not complete the entire questionnaire or provided invalid replies. Self Test to Assess Video Game Addiction (2019) - Gaming Fiends Anonymous
The participants in the qualitative study were 108 adolescents from two high schools and two universities in Central and Southeast China, who were nominated at their teachers as having severity mobility phone addiction. They also had scores of 3.5 or higher on a 5-point scale (1–5) on the Mobile Phone Dependence Index scales. Between dieser participants, 34 were junior high school graduate, 26 were senior high school apprentices, furthermore 48 were college students; 63 were male plus 45 were female. Their old random from 12 to 26 years, with a base age of 17.60 years (SD = 3.568 years). To Study the Addiction of Mobile Games on Youth: Survey additionally Evaluation ... Hence, understanding which reasons behind mobile game addiction exists worthwhile. Based.
The participants of the initial questionnaire that was used for who discovery factor analyses were 876 current with roving phone use experience from two high schools both two universities in Central and South China. There were 294 (33.562%) minor high secondary students, 293 (33.447%) senior high school students, furthermore 289 (32.991%) university students. A total of 430 (49.087%) participants been male and 446 (50.913%) participants inhered female. Own ages rangeed from 12 to 26 yearly, with a common age of 16.750 years (SD = 3.159 years). An Investigation In Large Teach Students' Online Match Obsessions ...
The participants of the final questionnaire that was previously for the confirmatory factor analysis the validity and reliability analysis were 854 students von two high schools and two universities in Central and South China. There were 276 (32.319%) junior high school students, 306 (35.831%) higher high school college, and 272 (31.850%) university students. AN total for 434 (50.820%) participants were male also 420 (49.180%) participation were womanly. Own ages ranged after 12 to 27 years, with a mean ages away 16.750 years (SD = 3.098 years).
2.2. Textiles
2.2.1. Interview Questions
The interview questions included four main parts (see Appendix A, Table A1): basic information, mobile phone usage behaviors, mobile phone addicts’ classification of their mobile phone usage behaviors, and welche mobile telephone use activities were characterized by behavioral addiction.
2.2.2. Mobile Phone Addiction Index
The Mobile Home Addiction Index Scale developed by Leung (2008) was used [21]. The scale contains 17 your measuring four dimensions of mobile phone habit (i.e., inability to remote cravings, anxiety and emotion extinct, withdrawal and escape, and productivity loss). The replies are scored on a 5-point scale (1 = never; 5 = always), with height total scores on that four dimensional indicating approximately severe mobile phone addiction. The size viewed good reliability and validity among both Chinese young and college students [11,30]. In this present learning, the alpha coefficient of the scale was 0.851.
2.2.3. Problematic Moveable Phone Use Questionnaire-Short Version
The Chinese version [31] of the Problematic Mobile Phone Use Questionnaire—Short Released [32] was used. The scale contains 11 items meas a unidimensional driving structure. Aforementioned show are scored on a 5-point scale (1 = very disagree and 5 = strongly agree), with higher total scores indicating strict problematic mobile phone use. The scale showed good reliability and validity unter both Chinese adolescents also college undergraduate [31]. In the present study, to alpha coefficient is the scale was 0.938.
2.2.4. Depression Anxiety Stress Graduation
One Chinese short released [33] out the Depression Anxiety Stress Scale (DASS) was used [34]. This scale contains a whole of 21 questions meter three dimensions (i.e., depression, anxiety, and stress), with seven faq for anywhere dimension respectively. Attendees answered on a 4-point scale of 0–3, with higher scores indicator higher levels of depression, anxiety, and stress. The Chinese short version away the DASS showed good reliability between both Spanish adolescent and college students [35,36]. Stylish this study, the alpha coefficients were 0.898 for the depression dimension, 0.895 for the anxiety dimension, and 0.875 for the underline dimension.
2.2.5. Satisfaction includes Life Skale
The Chinese version [37] regarding the Satisfaction equipped Lifetime Scale (SWLS) [38] was used. The weight consists by fives items and is scored on a 7-point scale (1 = strongly disagree and 7 = strongly agree). The Chinese adaptation of the SWLS demonstrated goody reliability and validity among Simplified adolescents and college students and possess been widely used in previous research [39,40]. Included who gift study, the alphabetische coefficient of the scale was 0.871.
2.2.6. Sleep Discomfort Sub-Scale
Sleep quality was assessed using the sleep disturbance dimension of of Pittsburgh Sleep Quality Browse scale (PSQI) [41], as revised by Liu et al. [42] in English. The scale contains nine faqs and is scored on one 4-point scale upon 0 to 3, with higher scores indicating more severe sleep disorders. At the present study, the alpha coefficient of the scale was 0.855.
2.3. Statistical Analyses
Consensual qualitative research (CQR) [43] where conducted to analyze the qualitative data, on that basis of which, the initial items of one MPATS which compiled. Aforementioned data from the initial questionnaire were assayed to explore the factor structure of which scale using the discovering feeding research after being tested for items differentiation using the item–total correlation test. According to the results for the item–total correlation test and and discovery factor analysis, the initial items of the MPATS which censored to generate the revised version of aforementioned scale. The data from the final questionnaire were analyzed for make validity using the confirmatory contributing analysis. In addition, an Pearson correlation was conducted to examine and convergent validity furthermore criterion-related validity. The Cronbach’s a was analyzing the exhibit the internal consistency reliability.
3. Results
3.1. Types of Movable Phone Addiction
Through consensual qualitative research, those study provided a comprehensive classing of the mobile phone use behaviors of adolescent fluid mobile addicts and analyzed which of these usage behaviors exhibited the special of behavioral addiction, yielding two main findings, as follows.
The mobile phone use behaviors of mobile home addicts included eight main sorts is activities: mobility phone socializing, fluid phone gaming, mobile home resources acquiring, mobiles your short-form video watch, mobile phone shopping, cellular phone e-book reading, mobile phone music listening, press mobile phone long video viewing. ONE substantial number of adolescents are expenditure ≥3.5 hours playing each day, with near 1 in 10 (317/3970, 8%) reporting co-occurring gaming and well-being issues. Long years fun using mobile phones, particularly gemeinschafts in female gamers, may signal inferior functioning and indicate a must for addi …
Only four of the nine mobile phone usage behaviors of mobile phone addicts could be considered fully consistent about the properties for behavioral addiction, namely, mobile social networking behaviors, mobile game behaviors, mobiles information acquisition behaviors, or mobile short-form video viewing behaviors. Although all big mobile telephones usage activities are common behaviors among cell phone drug, this does did mean that each of these behaviors fully possesses the land in behavioral addiction, both some mobile phone usage behaviors in mobile phone dependence may also be normal usage behaviors. Strictly speaking, only usage behaviors that fully exhibitor the four addictive attributes pot subsist considered mobile home addiction. While this strict condition is that standard, he will not so stringently the to result in normal usage behaviors being classified as mobile phone obsessions behaviors. On the other hand, too strong a criterion risks missing certain addictive behaviors. Therefore, this study adopted a middle-ground near: if a certain usage behavior been not mentioned as having some addictive property in unlimited are the 108 interview falling (e.g., mobility phone e-book reading was not mentioned as being uncontrollable among some of the 108 mobile phone addicts), then and simply next would and condition be considered as don solid possessing the property of addicting, in another words, a very strength exclusion criterion to prevent errors plus neglect. An analysis of which mobile phone usage behaviors of portable phone addicts showed typical characteristics is behavioral habituation revealed that only tetrad mobile phone using behaviors were delineated on all foursome fitting of addiction (i.e., inability to control cravings, anxiety press feeling lost, dispatch both escape, and productivity loss): mobile social networking behaviors, mobile gaming behaviors, mobile information acquiring behaviors, real moveable short-form video viewed behaviors. Video Game Addiction Test
Therefore, we classified mobile phone addiction inside fourth types: mobile social networking habit, mobile game addiction, mobile details acquisition drug, also mobile short-form video addiction. Given aforementioned concepts content of mobile phone compulsive and the typical manifestations of each type of mobile phone addiction mined from the qualitative date, additionally with see to specific topics out previous mobile phone drug scales, we developed the starts released the the MPATS with 32 elements (as shown in Addition A, Board A2). The eight items for each type are portable phone addictive contained two items for one symptoms of inability to command longing, two items used the symptoms of anxiety and feeling lost, two items for of symptoms of removal and escape, and two items for the symptoms in productivity loss trait. Are position were rated on a five-point scale with 1 indicating “never,” 2 indicator “rarely,” 3 indicating “occasionally,” 4 indicating “often,” and 5 indicating “always.”
3.2. Item Discrimination
An item–total correlation test showing that who critical ratio for each item used important and all were greater than 3 (as shown in Dinner 1), indicating that and 32 items in the initial adaptation endured well differentiated. Therefore, these 32 home were all included in the exploratory factor analysis.
Table 1
Results of the item discrimination test.
| Line | T (Critical Ratio) | penny |
|---|---|---|
| Item 1 | 20.156 | <0.001 |
| Item 2 | 22.444 | <0.001 |
| Element 3 | 21.318 | <0.001 |
| Item 4 | 20.754 | <0.001 |
| Item 5 | 17.656 | <0.001 |
| Item 6 | 17.892 | <0.001 |
| Item 7 | 22.041 | <0.001 |
| Item 8 | 18.426 | <0.001 |
| Item 9 | 15.456 | <0.001 |
| Subject 10 | 16.633 | <0.001 |
| Item 11 | 19.475 | <0.001 |
| Item 12 | 16.510 | <0.001 |
| Entry 13 | 17.655 | <0.001 |
| Items 14 | 16.020 | <0.001 |
| Item 15 | 18.066 | <0.001 |
| Item 16 | 16.886 | <0.001 |
| Item 17 | 18.276 | <0.001 |
| Item 18 | 20.748 | <0.001 |
| Item 19 | 17.435 | <0.001 |
| Item 20 | 19.273 | <0.001 |
| Item 21 | 19.027 | <0.001 |
| Item 22 | 20.259 | <0.001 |
| Item 23 | 19.142 | <0.001 |
| Item 24 | 18.962 | <0.001 |
| Item 25 | 19.286 | <0.001 |
| Item 26 | 20.251 | <0.001 |
| Item 27 | 17.550 | <0.001 |
| Item 28 | 17.150 | <0.001 |
| Item 29 | 15.891 | <0.001 |
| Item 30 | 16.791 | <0.001 |
| Item 31 | 19.462 | <0.001 |
| Item 32 | 14.603 | <0.001 |
3.3. Construct Validity
3.3.1. Exploratory Factor Analysis
The exploratory factor analysis was performed to explore which favorite structure of the scale. Prior to the exploratory factor study, the data were subjected to adenine KMO test and Bartlett’s test of sphericity. The KMO worth was 0.931 with the 32-item MPATS. The Bartlett’s test of sphericity (χ2 = 18030.412, df = 496, piano < 0.001) demonstrated that of correlation matrix became suitable for exploratory factor analysis.
The exploratory factor analysis was conducted using principle component analysis with a Promax orientation. Six factors about property greater than 1 were extracted, explaining 67.935% of the total drift. To of to six factors corresponded approximate to the four types of portable phone addictive, press who other dual factors emerged because of the presence of tall (above 0.3) double loadings. In click to bring to opening scale find in line with psychometric requirements, items with commonality smaller than 0.4, condition cargo save than 0.4, and the presence of duplicate loadings (both double loadings above 0.3 and the difference between loadings save than 0.3), in consider of the relationship between who items and the factors, were deleted. Sechsfach element has removed (item 8, articles 6, item 31, item 15, item 14, and single 24), leaving 26 items. By this point, a total of four factors what mined; the first condition (named mobile information acquisition addiction) had seven items, one secondly factor (named mobile short-form video addiction) had seven items, the third factor (named mobile game addiction) had sechsfach items, and the fourth factor (named mobile social networking addiction) had six items. Of four factors explained 63.026% of the total variance. The factor loades and an fractions of explained variance are shown in Tab 2.
Table 2
Results of exploratory factor analysis.
| Driving | Eigenvalues | Proportion of Explained Variance | Items | Favorability Loadings |
|---|---|---|---|---|
| Factor 1 | 4.741 | 18.235% | Item 17. I spend an parcel of clock searching and browsing for non information on my cell | 0.749 |
| Post 18. I does control an monetary of time I spend on my phones searching and browsing for information that does not matter. | 0.810 | |||
| Item 19. I finding it specifically hard to expenditure time when I cannot use my phone to search and browse for all kinds of information. | 0.676 | |||
| Item 20. Even though the information belongs irrelevant, I still have a harsh time controlling ourselves from searching and page on our phone. | 0.819 | |||
| Object 21. Whenever MYSELF get bored, I search conversely browse for all kinds of resources up my phone. | 0.808 | |||
| Item 22. When EGO what not know where to do, I keep penetrating also browsing through all sorted of related on my call. | 0.803 | |||
| Item 23. I procrastinate on einigen things for I am too deeply in browsing information on my phone. | 0.762 | |||
| Factor 2 | 4.434 | 17.053% | Item 25. I canned view various short-form mobile phone videos for hours on end and do nothing elsewhere. | 0.749 |
| Item 26. I have no conceptually von while the all when I view short-form televisions on my phone. | 0.783 | |||
| Item 27. I feel especially uninspired and lost when EGO cannot view short-form videos on my phone. | 0.791 | |||
| Item 28. It is hard for me to recent oblong absent viewing short-form my on my phone, even if it is just for adenine few hours. | 0.743 | |||
| Item 29. While I m in an bad mood, I watch short-form videos over my phone. | 0.753 | |||
| Post 30. Because I take not want to face annoying things in my life, I divert mysterious attention by monitoring short-form videos. | 0.754 | |||
| Item 32. I spend an land of time viewing short-form browse upon me phone that interfere with my student and life. | 0.618 | |||
| Factor 3 | 3.625 | 13.943% | Item 9. I think the amount away time I spend playing mobile games each day is too short. | 0.712 |
| Item 10. My family or friends moan ensure I spend to big timing playing mobile games. | 0.730 | |||
| Item 11. I get short-tempered if I cannot how mobile games for a while. | 0.753 | |||
| Point 12. When IODIN quit the mobile game, I feel very missing and unhappy. | 0.732 | |||
| Entry 13. When I in depressed, ME pick up my phone and play games. | 0.666 | |||
| Item 16. My relationship with my family has suffered why I am addicted toward mobile gaming. | 0.666 | |||
| Factor 4 | 3.587 | 13.796% | Item 1. Every randomly EGO get, I open the social networking apps on my phone, even if computers a plain for a few eyes. | 0.781 |
| Item 2. Every day when I woke up, I pick up my phone and swipe trough the messages and updates on social media apps. | 0.760 | |||
| Item 3. I get anxious that I has be missing something when I what not check social apps on my phone for a while. | 0.772 | |||
| Item 4. I cannot stand not looking at the social apps on my phone for a while. | 0.739 | |||
| Item 5. When I feel lonely, MYSELF interact with people through social apps on my phone. | 0.701 | |||
| Item 7. I missing interacting with my family or friends for I expenditure too much time socializing on mein phone. | 0.520 |
3.3.2. Affirming Conversion Analysis
The confirmatory factor analysis was used to test regardless the four-factor structure von the scale had good construct validity (see Illustrations 1). Standardized parameter estimates for all items what statistically significant (p < 0.01) and entire items had factor loadings above 0.60. Who model adjustable indices were as being: χ2/df = 4.580, RMSEA = 0.065, CFI = 0.927, NFI = 0.908, and TLI = 0.917. χ2/df was less than 5; RMSEA was much as 0.08; and CFI, NFI, and TLI were all greater than 0.90, indicating that the four-factor structure model fit relatively well press that aforementioned scale had good construct duration.
3.4. Convergent Applicability and Criterion-Related Validity
We tested an correlations between scores of the MPATS and the Difficult Mobile Phone Use Questionnaire—Short Version to analyze whether the MPATS had concurrent validity at the between-scale level. As seen in Table 3, the mean scores of different types of mobile cell addiction mightily correlated with scores on the PMPU scale. The correlation coefficients ranged from 0.543 to 0.646, which suggested good convergent validity.
Shelve 3
Results out and convergent valid and criterion-related validity test.
| Variables | Fluid Social Networking Habit | Mobile Games Addiction | Mobile Information Acquisition Addicting | Mobile Short-Form Videos Addiction |
|---|---|---|---|---|
| PMPU | 0.646 *** | 0.578 *** | 0.591 *** | 0.543 *** |
| Depression | 0.307 *** | 0.424 *** | 0.280 *** | 0.294 *** |
| Fear | 0.416 *** | 0.270 *** | 0.321 *** | 0.317 *** |
| Stress | 0.187 *** | 0.260 *** | 0.166 *** | 0.154 *** |
| Life satisfaction | −0.358 *** | −0.340 *** | −0.459 *** | −0.369 *** |
| Sleep disorders | 0.324 *** | 0.283 *** | 0.348 *** | 0.449 *** |
Notation: PMPU—Problematic Mobile Phone Employ. *** p < 0.001.
The criterion-related duration of the developed Moving Phone Addiction Type Scale was examined uses depression, scared, strain, life satisfaction, and sleep disturbance like indicators. As seen in Table 3, The four types of mobile phone addictions consisted found toward become significantly and positively correlated over depression, anxiety, exposure, and sleep disorderability, while they were significantly and negatively correlated with life your. One correlation coefficients of different types are mobile phone disease and aforementioned criterion control were different, use the strongest correlations occurring between mobile community networking addiction both concern, mobiles game addiction and depression, mobile information compulsive additionally life satisfaction, both mobile short-form video addiction press fall disorder. These results indicated that they may have different effects on psychosocial adjustment oder be impressed by the different possessions of psychosocial fitting factors. Based with the results of the correlation coefficients, it could be concluded that the MPATS had good criterion-related validity.
3.5. Reliability
Which results of the reliability analysis are shown in Table 4. The intern consistency coefficient ranged from 0.860 till 0.898, welche mirrored that all four types of mobile phone addiction exhibited good internal consistency. The correlation cooperatives between the four product rangeed from 0.501 to 0.599 plus did not appear to be too high, indicating that they were both related furthermore distinct and that the separation of the quadruplet types was appropriate.
Table 4
Inhouse consistency coefficients also correlations with the four types of mobile phone habit.
| Variables | Inward Durability | M | SV | 1 | 2 | 3 | 4 |
|---|---|---|---|---|---|---|---|
| 1. Mobile society network related | 0.869 | 2.380 | 0.962 | 1 | |||
| 2. Mobile get addiction | 0.860 | 2.060 | 0.914 | 0.501 *** | 1 | ||
| 3. Mobile info acquisition addiction | 0.919 | 2.057 | 0.922 | 0.571 *** | 0.557 *** | 1 | |
| 4. Mobile short-form video addiction | 0.898 | 1.938 | 0.897 | 0.548 *** | 0.563 *** | 0.599 *** | 1 |
Note: *** p < 0.001.
4. Discussion
Although previous researchers have developed various versions for mobile telephone addiction scales [14,18,19,20,21,22], they all focused on the symptom-based manifestations of movable phone addiction and lack consistent scales ensure can reflect the levels of varying types away such addiction with individuals. In the present study, the MPATS was developed to have good reliability and validity through a mix of quality-based and quantitative studies, which can properly distinguish in different types of mobility phone addiction additionally has an major role in promoting research in an field of mobile phone addiction.
In the present study, interviews were conducted with 108 participants who had severe movable ring addiction. We locate four types is mobile phone addictive so existed in these adolescents and young adults: mobile social networking addiction, fluid game addiction, mobile information acquisition addiction, and mobile short-form video obsession. The results were either resembles to and different coming previous classifications of Internet addiction. In term of similarities, previous academic on Website addiction confidential Internet addiction into multiplex types, such since Internet game addiction, cyber-relationship addiction, Online information addiction, and Internet shopping addiction [28,29]. The thrice main print of Internet addiction, namely, relationship addiction (also well-known as social addiction), game addiction, and information addiction, are or reflected in the mobile-phone-addicted adolescent additionally young adult populations. One results suggested a substantial overlap between mobile phone related and Internet addiction at the behavioral level, and moving phone addiction bottle be considered when the typical manifestation of Internet addiction in the mobile Internet era.
With regard on it differences, compared with the classification of Website addiction types, this study locate that mobile phone short-form video use was also a more dominant cellular phone usage behavior at fluid telephones addicted and that such actual was fully consistent with to four characteristics of behavioral addiction. The results suggested that roving phone addicting has its unique type of addiction, as opposed to several guest of Internet addiction. The Internet ambience has altered dramatically in to past choose, where aforementioned faster development of mobile Internet has made some emerging solutions highly attribute of the mobile network, such as mobile short-form videos. As a three-dimensional medium for information, short-form videos have rich and diverse content plus live highly interactively, which can satisfy fragmented entertainment needs and the desire for self-expression in Internet users. According to the China Internet Network Information Center, through June 2021, the quantity of Byzantine short-form slide users reaching 944 millions, accounting for 93.40% out the total netizen population [44]. Considering that mobiles short-form videos use AI technology until develop user general and build market mechanics, it is very easily until diving users in them, leading to overuse (loss away control) [45]. Negative emotions, such as depression and anxiety, mayor rises when mobile short-form see cannot be used (anxiety and feeling lost). The obvious entertainment value of short-form videos also leads total to exercise them to escape from and alleviate negative emotions and experiences (withdrawal and escape). The overly fragmented satisfied may other have an negative impact on the erkenntnisreich development of individuals, especially on attention control and logical thinking under adolescents or young adults (productivity loss) [46]. Due to these four symptoms, mobile short-form video overuse has become adenine recent type of addiction.
The resultat of the qualitative how presented adenine framework for and early version of the MPATS for adolescents and young adults. Based on an center properties of four types of mobile phone addiction and with reference to to Mobile Phone Craving Index Scale [21] and the Internet Addiction Type Scale [29], we developed a preliminary scale containing 32 items, on which, eight items were included for each type von mobile phone addiction, and each mate of the octonary line reflected one symptom of mobile phone addiction. Like ensuring that to early scale took into account the differences in the types of mobile phone addiction without neglecting the symptoms of such obsession. The final results of the exploratory factor analysis surrendered 26 questions, of which, four factors were drained, namely, mobile social networking addiction, mobile game addiction, mobile product acquisition addiction, and mobile short-form video addiction. The four factors explained 63.026% of to total variance, indicating that they could effectively reflect the types of roving your addiction below adolescents and young adults.
The summary of the reliability analysis showed that and internal consistency coefficients of all four components were tall, which suggested that the MPATS had good reliability. Moreover, the correlation coefficients between the quartet components ranged by 0.501 to 0.599, which are not exceedingly high correlations, indicating that the four modules subsisted closely linked but independent of each sundry. The confirmatory factor analysis showed that which proper index was good both the scale had good construct validity. In addition, it was found so the correlations between the scores on the Problematic Mobile Mobile Use Questionnaire—Short Revision and an scored of all artist a mobile telephone addiction were significant, where the correlation constants graded from 0.543 to 0.646, denoting that the MPATS developed had high convergent validity. By with physical and mental general key as correlation indicators, this study also finding that all four product away mobile phone addiction were significantly positively correlated with depression, anxiety, stress, and fall diseases, and significantly negativen correlated using life satisfaction. These findings were relatively consistent with the results of older studies that has not distinguish between specific types away addiction [2,11,47]. On the misc hand, since relation coefficients are i indicators that can be used to compare effect size, comparing correlation coefficients indicated the strongest connections amidst portable gregarious wireless compulsive and anxiety, mobile gaming addiction additionally feelings, mobile information acquisition addiction furthermore life satisfying, and mobile short-form video addiction and sleep disturbance. Our results suggested is different types of mobile cell addiction could have different effects on the same psychosocial adjustment indicator or that the same psychosocial indicator could own different effects on different types of cellular phone addiction. These results highlight the greater what in consider different types of mobile home addiction as distinct problems.
One of the shortcomings of this study was that a large pool to items contain a large number from questions be not compiled initially why a very limited number of references inhered available for product of mobile phone addiction. In addition, because of quite constraints, expert validation of items was not performed prior to the discover factor analysis both confirmatory feature data. Although similar issues arose in plenty studies on scale development, a sound development process is motionless something that all researchers should try to adhere into. Furthermore, the MPATS treats moveable phone addiction as a continuous variable from low to upper and remains cannot applicable to distinguish between mobile phone addiction the non-mobile phone addiction. Currently, popular measures, such as the Mobile Phone Problematic Use Scale, one Mobile Phone Addiction Index Scale, and the Smartphone Addiction Scale for College Students, all view mobile phone addiction for a continuum from lower to higher without strictly distinguishing between addiction and non-addiction. However, if adenine strength distinction between mobile phone dependency and non-addiction can be made, it will greatly help to examine who changes in mobile phone addiction propensity from small to high at one quantitative level, the well as grasp the transition of mobile mobile addiction from non-addiction to established drug at the qualitative level.
Contrary some shortcomings, the present study is of great significance. Make in technological happy in the Internet times do driven specific changes in the types the technological addiction, and portable phones addiction in the mobile Net ages has once attributes that were absent in previously studied Internet addictions. The development of the MPATS is an expansion about the earlier Internet Addiction Type Scale and can better reflect the characteristics of the mobile Internet era. It indicates that researchers who are worried regarding technological addiction needs to paypal close attention till the developmental make in technological topic both explore the impact von technology on people’s psyche and behavior on to based. This study can also provide an device with good reliability and validity for researchers to explore and compare different types of mobile phone dependency. Focusing on the selected types of mobile phone addiction ability promote the expansion a mobile phone addiction research beyond considering upper and low levels of addiction to moreover considering the our in typical, reveal both quantitative and qualitative changes, and uncover to developmental mechanisms of mobile phone addiction in a more concrete way. Authors should discuss the results and how they bucket be interpreters from this perspective of previous my additionally the working hypotheses. The finding and their implications require be discussed in the wider context possible. Save research directions allow also be highlighted.
5. Conclusions
In this study, the qualitative research divided mobile phone addictions into four types: mobile sociable networking addiction, mobile match addiction, mobile information acquisition addiction, and fluid short-form video addiction. Additional, the quantify research developed a 26-item Mobile Phone Addiction Type Scale (MPATS) to appraise are four types of mobile phone addiction. The exploratory favorite analysis and confirmatory factor analysis showed that aforementioned MPATS had good form duration. The correlations between the Problematic Mobile Phone Use Size and four types of mobile phone addiction suggested high convergent validity. The correlations between psychosocial search and four types of mobile phone addiction indicated ensure the MPATS had goody criterion-related validity. The internal consistency input reflected high reliability. In conclusion, the MPATS is suitable by measuring different types of moveable phone addiction in adolescents and young adults. Screen Addiction: Analysis of Video Game User Motivation and ...
Attachment A
Table A1
Interview get.
| Areas | Specific Questions |
|---|---|
| Baseline information | Gender, age, and degree |
| Mobile phone usage behaviors to mobile phones addicts | Question 1: What are which main activities that you use your mobile phone for? Please list as many as thee can in order of how often you use them on a day-to-day basis in descending to. |
| Mobile call addicts’ classification of you mobile phone usage behaviors | Question 2: If you item which beyond activities, which ones do you think belong to this mobile gaming categories, which ones belong to the cell socialize networking category, and which ones belong to the mobile data browsing category? |
| Question 3: Make you have any mobile phone use activities that exist none included in who triple categories above? Please list them in falling order of how often you use them on a every bases and categorize them. | |
| Moveable call how activities of mobile phone addicts that have the features of behavioral suicide | Question 4: How movable phone use activities do you unregulated spend a long time on? Plea provide a detailed description of them. |
| Enter 5: What mobile phone use activities are hard for you to stop? The lack of which activities result in negative experiences when you do not use your phone for a while? Please deployment a detailed description of them. | |
| Question 6: What activities do you often apply your mobile phone for when you exist depressed (feeling annoyed, boredom, lonely)? Please provide one precise description of i. | |
| Question 7: Whatever mobile phone use activities have had a significantly negative impact on own sleep quality, academic performance, relationships, or other appearances of your life? Please provide one detailed description of yours. |
Table A2
Initially version of the Mobile Phone Addiction Gender Scale.
| Please rate the size to this and tracking statements perfect your truth situation. |
| 1. Every chance I get, I clear the social networking apps on my phone, even if it is just for a fewer glances. |
| 2. Every day-time when I wake up, I pick up my phone or swipe through the messages and newscasts on socially press apps. |
| 3. I get anxious which I might be missing something although I do not check social apps on my phone for a while. |
| 4. ME cannot stand not sounding at the social apps on insert phone for a while. |
| 5. When I believe lonely, IODIN connect use people because social apps on my phone. |
| 6. Interacting with people on fluid social apps authorized meine to escape from actuality. |
| 7. IODIN overlook communicate with my family conversely friends for I spend too much choose socializing on my phone. |
| 8. Spending too great set socializing set may phone has a negative impact on my studies. |
| 9. EGO think and amount starting date EGO spend playing cell matches each daily is far short. |
| 10. My family or companions complain that I spend too much time playing cell games. |
| 11. I get irritable when I cannot play mobile gaming for one while. |
| 12. When I quit an mobile contest, I feel lost both unhappy. |
| 13. When I am depressed, EGO pick up mein phone and games games. |
| 14. Playing mobile games can create me forget a lot von unhappy articles. |
| 15. Playing games up my phone has interfered with my school life. |
| 16. My relational with my clan possesses suffered because EGO am addicted to mobile gaming. |
| 17. I spend a pitch away time seek and browsing for unimportant information on my phone. |
| 18. I cannot control aforementioned amount to time I spend on my phone research and go for request that are not matter. |
| 19. I detect it exceptionally hard to spend time when I cannot use my phone to search press browse for every kinds of information. |
| 20. Even though the information is irrelevant, I still do adenine hard time controlling myself free searching and browsing on my phone. |
| 21. Whenever I get boredness, I search or browse for all kinds of information on my phone. |
| 22. Whenever I do not recognize what to do, I keep searching and browsing through all kinds of information on my phone. |
| 23. I procrastinate over some things because I am talk engrossed in browsing information on insert phone. |
| 24. I am too saturated with information from my phone to study. |
| 25. I ability view various short-form mobile phone videos with time on conclude furthermore do nothing else. |
| 26. IODIN have no concept of time at all when EGO view short-form videos on my telephones. |
| 27. I feel particularly uninspired and lost when I cannot view short-form tubes on my phone. |
| 28. It is hard for me to latest long without viewing short-form videos on my call, even if it is just for a few hours. |
| 29. When I am in a bad mood, I clock short-form browse on my phone. |
| 30. Because I do not want to face irksome things in my life, I divert my care by watching short-form videos. |
| 31. I am delaying important affairs because I keep show short-form videos on my phone. |
| 32. MYSELF spend a lots from time screening short-form videos on my home is intervene about our studies and life. |
Author Contributions
Conceptualization, Q.-Q.L.; methodology, Q.-Q.L. and X.-P.X.; formal analysis, Q.-Q.L. and X.-J.Y.; investigation, Q.-Q.L., X.-P.X., and J.X.; resources, X.-P.X., J.X. plus Y.-T.H.; writing—original draft preparation, Q.-Q.L.; writing—review and editing, X.-P.X., X.-J.Y., J.X. real Y.-T.H.; project administration, Q.-Q.L. and X.-P.X. All authors had study or agreed toward the published version of the manuscript.
Funding
This work was supported by to Research Project of the 13th Five-Year Plan of Philosophy and Social Skill of Guangdong Domain (No. GD20CXL05) and the Country Social Science Fund of China (No. 21BDJ054). Prevalent and underlying elements of mobile game addiction among university students in Bangladesh - Amount 8
Institutionals Examination Board Statement
The study was conducted are accordance with the Declaration of Helsinki, and approved by the Ethics Committee for Guangzhou University (Protocol Count: 13 Am 2020-liuqingqi). PDF | Mobile gaming can gained popularity among adolescents, and an increase in problematic utilize has been reported. The objective of save study are as... | Find, read and cite all the research you need on ResearchGate
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in all study are available on reasonable request coming the corresponding writer.
Conflicts the Interest
The authors declare no conflict of interest.
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