Occurence of Internet addiction in a general population sample: A Latent Class Analysis
Abstract
Background: Prevalence studies of Internet addiction in the general population are rare. In addition, a lack of approved criteria hampers estimation of its occurrence. Aims: This study conducted a latent class analysis (LCA) in a large general population sample to estimate prevalence. Methods: A telephone survey was conducted based on a random digit dialling procedure including landline telephone (n = 14,022) and cell phone numbers (n = 1,001) in participants aged 14-64. The Compulsive Internet Use Scale (CIUS) served as the basis for a LCA used to look for subgroups representing participants with Internet addiction or at-risk use. CIUS was given to participants reporting to use the Internet for private purposes at least 1 h on a typical weekday or at least 1 h on a day at the weekend (n = 8,130). Results: A 6-class model showed best model fit and included two groups likely to represent Internet addiction and at-risk Internet use. Both groups showed less social participation and the Internet addiction group less general trust in other people. Proportions of probable Internet addiction were 1.0% (CI 0.9-1.2) among the entire sample, 2.4% (CI 1.9-3.1) in the age group 14-24, and 4.0% (CI 2.7-5.7) in the age group 14-16. No difference in estimated proportions between males and females was found. Unemployment (OR 3.13; CI 1.74-5.65) and migration background (OR 3.04; CI 2.12-4.36) were related to Internet addiction. Conclusions: This LCA-based study differentiated groups likely to have Internet addiction and at-risk use in the general population and provides characteristics to further define this rather new disorder.
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- Findingown data§ Results · p. 5
The six classes differed significantly on all examined variables.
“In all variables, classes differed significantly”
Quote in the paperSubstantial claim - Findingown data§ Occurrence of Latent Classes · p. 6
The proportion of probable Internet addiction was higher among mobile-only recruits (1.95%) than landline recruits (0.86%).
“The proportion for probable Internet addiction was markedly higher in subjects recruited through mobileonly (1.95%) compared to landline numbers (0.86%; χ 2 = 55.74; d.f. = 1; design d.f. = 48; p < 0.001).”
Quote in the paperNot a substantial claim - Findingown data§ Abstract · p. 1
Migration background was related to Internet addiction, with an odds ratio of 3.04 (CI 2.12-4.36).
“migration background (OR 3.04; CI 2.12-4.36) were related to Internet addiction.”
Quote in the paperNot a substantial claim - Findingown data§ Results · p. 6
Participants with probable Internet addiction spent 4.2 hours per day online for private purposes.
“Participants with probable Internet addiction spent 4.2 h/day in the Internet for private purposes”
Quote in the paperNot a substantial claim - Findingown data§ Results · p. 4
In the 5-class and 6-class models, the same extreme group with a high CIUS score emerged, with n = 162.
“In the 5-class model and the 6-class model, the same extreme group with high CIUS score emerges (n = 162) speaking in favour of these models.”
Quote in the paperSubstantial claim
- Findingown data§ Occurrence of Latent Classes · p. 6
The odds ratio for migration background with Internet addiction was 3.04 (95% CI 2.12-4.36).
“migration background 3.04 (2.12-4.36)”
Quote in the paperNot a substantial claim - Findingown data§ Abstract · p. 1
The estimated proportion of probable Internet addiction was 1.0% (CI 0.9-1.2) in the entire sample.
“Proportions of probable Internet addiction were 1.0% (CI 0.9-1.2) among the entire sample”
Quote in the paperSubstantial claim - Findingown data§ Abstract · p. 1
The estimated proportion of probable Internet addiction was 4.0% (CI 2.7-5.7) in the 14-16 age group.
“4.0% (CI 2.7-5.7) in the age group 14-16”
Quote in the paperSubstantial claim - Findingown data§ Occurrence of Latent Classes · p. 6
No significant gender differences were found in probable Internet addiction across age groups 18-64, 14-24, and 14-16.
“Looking at probable Internet addiction in the entire sample and in subgroups according to age, no significant differences between males and females can be found”
Quote in the paperNot a substantial claim - Findingown data§ Abstract · p. 1
Unemployment was related to Internet addiction, with an odds ratio of 3.13 (CI 1.74-5.65).
“Unemployment (OR 3.13; CI 1.74-5.65)”
Quote in the paperNot a substantial claim - Findingown data§ Results · p. 4
From the 4-class model onward, each solution contained two groups with distinctly higher CIUS scores than the other classes.
“From the 4-class model onwards, in each solution, two groups have distinctively higher CIUS scores than the other classes as hypothesized (supposed to represent the at-risk group and the addiction group).”
Quote in the paperSubstantial claim - Findingown data§ Results · p. 5
The latent class analysis produced six mutually exclusive classes based on CIUS mean scores.
“The LCA resulted in 6 mutual exclusive classes with respect to CIUS mean scores.”
Quote in the paperSubstantial claim - Findingown data§ Occurrence of Latent Classes · p. 6
The odds ratio for unemployment with Internet addiction was 3.13 (95% CI 1.74-5.65).
“unemployment 3.13 (1.74-5.65)”
Quote in the paperNot a substantial claim - Findingown data§ Abstract · p. 1
A 6-class model showed the best model fit.
“A 6-class model showed best model fit”
Quote in the paperSubstantial claim - Findingown data§ Abstract · p. 1
The estimated proportion of probable Internet addiction was 2.4% (CI 1.9-3.1) in the 14-24 age group.
“2.4% (CI 1.9-3.1) in the age group 14-24”
Quote in the paperSubstantial claim - Findingown data§ Abstract · p. 1
No difference in estimated proportions of Internet addiction was found between males and females.
“No difference in estimated proportions between males and females was found.”
Quote in the paperNot a substantial claim - Findingnone given§ Occurrence of Latent Classes · p. 6
The addicted group differed significantly from the other groups in all CIUS items.
“The addicted group differed significantly from the others in all CIUS items.”
Quote in the paperNot a substantial claim - Findingown data§ Abstract · p. 1
Both groups likely to represent Internet addiction and at-risk use showed less social participation.
“Both groups showed less social participation”
Quote in the paperNot a substantial claim - Findingreasoning§ Results · p. 4
The 6-class model was selected and explored further.
“Taking all the information into account, the 6-class model was chosen and explored further because the same number (n = 162)”
Quote in the paperSubstantial claim - Findingown data§ Results · p. 5
BIC and entropy support a six-class solution over a five-class solution.
“of extreme cases occurs as in the foregoing model and BIC and entropy speak in favour of the 6 classes compared to the 5 classes.”
Quote in the paperSubstantial claim - Findingown data§ Results · p. 5
Differences between classes were more pronounced for class 6 across variables.
“Differences are more pronounced for class 6 throughout.”
Quote in the paperNot a substantial claim - Findingown data§ Occurrence of Latent Classes · p. 6
4.6% of the total sample belonged to class 5 (probable at-risk Internet use).
“4.6% to class 5 (probable at-risk Internet use).”
Quote in the paperNot a substantial claim- Rests on an assumption: Participants who used the Internet for private purposes less than 1 hour on a typical weekday or weekend day do not have problematic Internet use or Internet addiction.
- Findingown data§ Results · p. 6
Participants with at-risk Internet use spent 3.1 hours per day online for private purposes.
“those with at-risk use spent 3.1 h/day.”
Quote in the paperNot a substantial claim - Findingown data§ Results · p. 5
Class 5 was the youngest group.
“Regarding age, class 5 is the youngest group.”
Quote in the paperNot a substantial claim - Findingown data§ Results · p. 5
Only class 6 had lower generalized trust scores than other classes.
“With respect to generalized trust, only class 6 shows lower scores.”
Quote in the paperNot a substantial claim - Findingown data§ Abstract · p. 1
The Internet addiction group showed less general trust in other people.
“the Internet addiction group less general trust in other people.”
Quote in the paperNot a substantial claim - Findingown data§ Occurrence of Latent Classes · p. 6
The odds ratio for age with Internet addiction was 0.95 (95% CI 0.94-0.97).
“odds ratios (95% CI) were for age 0.95 (0.94-0.97)”
Quote in the paperNot a substantial claim - Findingown data§ Occurrence of Latent Classes · p. 6
No significant gender differences were found in probable problematic Internet use across age groups.
“Looking at probable problematic Internet use in the entire sample and in different age groups, proportions again do not differ significantly according to gender”
Quote in the paperNot a substantial claim - Findingown data§ Occurrence of Latent Classes · p. 6
1.0% of the total sample belonged to class 6 (probable Internet addiction).
“1.0% of the total sample belongs to class 6 (probable Internet addiction)”
Quote in the paperNot a substantial claim- Rests on an assumption: Participants who used the Internet for private purposes less than 1 hour on a typical weekday or weekend day do not have problematic Internet use or Internet addiction.
- Findingown data§ Discussion · p. 7
This group was the only one that differed in social trust compared to all other groups.
“This was the only group differing in social trust compared to all other groups”
Quote in the paperNot a substantial claim - Findingown data§ Discussion · p. 7
In this study, no statistical difference in Internet addiction prevalence by gender was found in all age groups examined.
“In all age groups looked at, no statistical difference could be found according to gender.”
Quote in the paperNot a substantial claim - Findingown data§ Discussion · p. 7
The proportion of probable Internet addiction in the mobile-only sample doubles that of the landline sample.
“Findings show that the proportion of probable Internet addiction in the mobile-only sample doubles that of the landline sample.”
Quote in the paperSubstantial claim - Findingown data§ Discussion · p. 7
Using the class found as an estimator, the total proportion of Internet addiction for participants aged 14-64 is 1%.
“Using the class found as an estimator for the occurrence of Internet addiction results in a total proportion of 1% for all participants aged 14-64.”
Quote in the paperSubstantial claim- Rests on an assumption: Participants who used the Internet for private purposes less than 1 hour on a typical weekday or weekend day do not have problematic Internet use or Internet addiction.
- Findingown data§ Discussion · p. 7
If the 4-class model had been chosen, the rate of Internet addiction would have been nearly threefold.
“if the decision had been that the 4-class model would fit data best, the rate of Internet addiction would have been nearly threefold.”
Quote in the paperNot a substantial claim - Premisecitation§ Abstract · p. 1
The absence of approved diagnostic criteria makes it difficult to estimate how often Internet addiction occurs.
“In addition, a lack of approved criteria hampers estimation of its occurrence.”
- Also stated in: § Introduction · p. 1 · plain
“Although generally accepted that formal diagnostic criteria are missing, the existence of compulsive Internet use or Internet addiction is widely claimed and included as a condition for further research in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) [1, 2]”
Quote in the paperSubstantial claim0 of 2 sources checked - Also stated in: § Introduction · p. 1 · plain
- Premisecitation§ Abstract · p. 1
Studies estimating the prevalence of Internet addiction in the general population are uncommon.
“Prevalence studies of Internet addiction in the general population are rare.”
- Also stated in: § Introduction · p. 3 · plain
“studies on the occurrence of Internet addiction in the general population are rare and suffer from methodological shortcomings.”
Quote in the paperSubstantial claim0 of 2 sources checked - Also stated in: § Introduction · p. 3 · plain
- Premisereasoning§ Introduction · p. 2
Sample selection bias is very likely a major reason for divergent prevalence estimates.
“Sample selection bias is very likely to be a major cause of divergent prevalence estimates.”
Quote in the paperSubstantial claim - Interpretationown data§ Abstract · p. 1
The latent class analysis differentiated groups likely to have Internet addiction and at-risk use in the general population.
“This LCA-based study differentiated groups likely to have Internet addiction and at-risk use in the general population”
Quote in the paperSubstantial claim - Premisecitation§ Discussion · p. 7
Only two studies on prevalence estimates have used a general population approach.
“Only two studies on prevalence estimates have used a general population approach.”
Quote in the paperNot a substantial claim0 of 2 sources checked - Premisecitation§ Discussion · p. 7
There are no generally accepted diagnostic criteria for defining Internet addiction.
“In face of lacking generally accepted diagnostic criteria to define Internet addiction”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationown data§ Abstract · p. 1
The 6-class model included two groups likely to represent Internet addiction and at-risk Internet use.
“included two groups likely to represent Internet addiction and at-risk Internet use.”
Quote in the paperSubstantial claim - Premisecitation§ Introduction · p. 2
Only two studies have used general population samples to estimate Internet addiction.
“Only two studies used general population samples.”
Quote in the paperNot a substantial claim0 of 2 sources checked - Study design and conductnone given§ Discussion · p. 7
The identification of the respective groups depends on the latent class model that was considered to fit the data best.
“the identification of the respective groups depends on the latent class model that was considered to fit data best.”
Quote in the paperSubstantial claim - Interpretationown data§ Discussion · p. 7
The differences in social participation suggest that extensive Internet use may have led to withdrawal from life in society.
“The differences with respect to social participation are an important finding showing that the extensive use of the Internet may have led to withdrawal from life in society.”
Quote in the paperSubstantial claim - Interpretationown data§ Discussion · p. 7
This second class was considered to probably have at-risk Internet use.
“This class was considered as probably having at-risk Internet use.”
Quote in the paperSubstantial claim - Study design and conductnone given§ Discussion · p. 7
Including mobile-only participants reduces a possible sample selection bias.
“including mobile-only participants reduces a possible sample selection bias.”
Quote in the paperSubstantial claim - Interpretationown data§ Discussion · p. 7
According to the study's data, a 6-hour threshold for Internet addiction is too high.
“According to our data, 6 h as a threshold are too high.”
Quote in the paperSubstantial claim - Interpretationreasoning§ Discussion · p. 7
This group was considered to represent the subgroup likely to have Internet addiction.
“was considered as representing the subgroup of those likely to have Internet addiction.”
Quote in the paperSubstantial claim - Interpretationown data§ Discussion · p. 8
The data presented give a reliable basis to estimate the magnitude of problems following excessive Internet use.
“We conclude that data presented here give a reliable basis to estimate the magnitude of problems following excessive Internet use.”
Quote in the paperNot a substantial claim - Study design and conductown data§ Discussion · p. 7
Finding an identical number of cases (n = 162) in the 5- and 6-class models gives strong evidence for the estimates based on the chosen model.
“finding an identical number of cases (n = 162) in the 5- and 6-class-model gives strong evidence for the estimates based on the model we chose.”
Quote in the paperSubstantial claim
- May combine two claims. 32
- Classified as probably not a substantial claim. 41
May combine two claims.
Findingown data§ Occurrence of Latent Classes · p. 7Based on participants aged 14-24, the cut-off of 28 estimated Internet addiction prevalence at 3.8% (95% CI 3.0-4.6) overall, 4.5% (95% CI 3.3-6.0) in females, and 3.0% (95% CI 2.2-4.3) in males.
“Based on participants aged 14-24, Internet addiction occurred in 3.8% (CI 3.0-4.6) in total, 4.5% (CI 3.36.0) in females, and 3.0% (CI 2.2-4.3) in males.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Occurrence of Latent Classes · p. 7Using the recommended CIUS cut-off of 28, estimated Internet addiction prevalence was 1.5% (95% CI 1.3-1.7) for the entire sample, 1.3% (95% CI 1.0-1.7) for females, and 1.7% (95% CI 1.3-2.1) for males.
“the recommended cut-off (28) for the CIUS was used to estimate occurrence of Internet addiction resulting in 1.5% (CI 1.3-1.7) for the entire sample, 1.3% (CI 1.0-1.7) for females, and 1.7% (CI 1.3-2.1) for males.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Method · p. 3In the current sample, the CIUS had a Cronbach's alpha of 0.87, indicating good internal consistency.
“In the current sample, α was 0.87 which approves the good internal consistency of this instrument.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Occurrence of Latent Classes · p. 6Age, migration background, and unemployment were significantly related to Internet addiction in a logistic regression.
“Age, migration background and unemployment were significantly related with Internet addiction”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Occurrence of Latent Classes · p. 7Based on participants aged 14-16, the cut-off of 28 estimated Internet addiction prevalence at 6.3% (95% CI 4.6-8.4) overall, 8.6% (95% CI 5.5-13.0) in females, and 4.1% (95% CI 2.6-6.3) in males.
“Based on participants aged 14-16, Internet addiction occurred in 6.3% (CI 4.6-8.4) in total, 8.6% (CI 5.5-13.0) among females, and 4.1% (CI 2.6-6.3) among males.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Occurrence of Latent Classes · p. 6More males than females were in class 6, but this was not statistically significant in the regression model (OR 1.53; 95% CI 0.99-2.35).
“More males than females were in class 6, however this was not statistically significant in the regression model (OR 1.53; 0.99-2.35).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Results · p. 5Classes 5 and 6 had higher CIUS scores, more online time, and less social participation.
“class 5 and 6 showing higher CIUS scores, more time spent in the Internet and less social participation.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Findingown data§ Results · p. 4An 8-class solution was not considered because a group of n = 8 emerged as part of the n = 118 group from the 7-class solution.
“An 8-class solution was not considered because a group of n = 8 emerged as a part of the group of n = 118 from the 7-class solution.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Occurrence of Latent Classes · p. 6In younger age groups, the proportions of both class 5 and class 6 were higher.
“In younger age groups, proportions of both groups are higher.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ Method · p. 3Of the total sample of 15,023 participants, 8,132 reported using the Internet for private purposes for at least 1 hour on a typical weekday or at least 1 hour on a weekend day.
“Of the total sample of 15,023 participants, 8,132 reported using the Internet for private purposes at least 1 h on a typical weekday or at least 1 h on a day at the weekend.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Occurrence of Latent Classes · p. 6Female class-6 members used online games less often as their main Internet activity, but this difference was not statistically significant (7.2% vs. 33.6%, p = 0.057).
“female class-6 members used online games less often, however this was only a tendency and not statistically significant (7.2 vs. 33.6%; χ 2 = 3.79; d.f. = 1; design d.f. = 48; p = 0.057).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Results · p. 4Lower BIC values and higher entropy measures were observed as the number of classes increased.
“Lower BIC values and higher entropy measures (both as desired) can be found with the increasing number of classes.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Discussion · p. 7In the youngest group (14-16), proportions were highest for females, although not statistically significant.
“in the youngest group (14-16) of our study, proportions were highest for females, although not statistically significant.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Discussion · p. 7In younger age groups, proportions are higher, with up to 4% for Internet addiction in 14- to 16-year-olds.
“In younger age groups, proportions are - as expected - higher with up to 4% for Internet addiction in the 14- to 16-year-old participants.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Discussion · p. 7This withdrawal effect was observed in both groups but was strongest in class 6.
“This could be observed in both groups but was strongest in class 6 representing Internet addiction.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Discussion · p. 7A 6-class solution showed the best fit and included two classes that differed in variables related to problematic and addictive Internet use compared to the other groups.
“A 6-class solution showed the best fit and included 2 classes that differed in variables that are related to problematic and addictive Internet use compared to the other groups.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Discussion · p. 7A second group showed the second highest CIUS scores and time spent online, the second lowest social participation, and the lowest mean age.
“A second group shows the second highest values in CIUS scores and time spent in the Internet, the second lowest scores in social participation and the lowest mean age.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ Discussion · p. 7One group showed the highest CIUS scores and time spent online, and the lowest social participation.
“One group showed highest rates in CIUS scores and time spent in the Internet, whereas social participation was lowest.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ Discussion · p. 7Female participants showed a tendency to use online games less often as their main Internet activity.
“female participants showed a tendency to use less often online games as their main activity on the Internet.”
Quote in the paperNot a substantial claimMay combine two claims.
Premisereasoning§ Introduction · p. 2Most studies used convenience samples, and in those studies the chance of being included was likely confounded with the problem behaviour being measured.
“The majority of studies have used convenience samples consisting of non-representative subgroups such as can be found in online surveys. In these studies, probability of study inclusion was obviously likely to be confounded with the problem behaviour to be measured.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisereasoning§ Introduction · p. 2Regional variation cannot explain the very large differences in prevalence estimates across studies.
“regional differences cannot account for the immense difference in prevalence rates that have been found.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Introduction · p. 2The DSM-5 proposed criteria for Internet addiction are limited to Internet gaming.
“However, in DSM-5, the proposed criteria are restricted to Internet gaming.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [2] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Introduction · p. 2Reported prevalence rates of Internet addiction across studies range from 1% to 14%.
“Rates range from 1 to 14% [7]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [7] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation§ Introduction · p. 1Compulsive Internet use or Internet addiction is widely asserted to exist and is listed in DSM-5 as a condition needing further study.
“the existence of compulsive Internet use or Internet addiction is widely claimed and included as a condition for further research in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) [1, 2]”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
Interpretationreasoning§ Results · p. 5Class 5 represents at-risk Internet use and class 6 represents Internet addiction.
“Data can be interpreted as class 5 representing at-risk use and class 6 Internet addiction.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation§ Method · p. 3The CIUS has 14 items and was developed to assess five core criteria for Internet addiction: salience, withdrawal, loss of control, conflict, and coping with unpleasant mood.
“It consists of 14 items and was developed to assess the following 5 core criteria for Internet addiction: salience, withdrawal, loss of control, conflict and coping with unpleasant mood.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [19] source
Not checked in the free run.
Classified as probably not a substantial claim.
Study design and conductown data§ Introduction · p. 3The present study conducted a latent class analysis in a large representative general population sample.
“the present study performed a LCA in a large representative general population sample”
Quote in the paperSubstantial claimMay combine two claims.
Premisecitation§ Method · p. 3The CIUS has shown good validity and Cronbach's alpha reliability between 0.88 and 0.90.
“The questionnaire showed good validity and a Cronbach's α as measure of reliability ranging from 0.88 to 0.90 [18, 19]”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Introduction · p. 2A previous latent class analysis in two large Dutch school-based samples found that a 6-class model had the best fit.
“In two large school-based samples, respondents filled out the Compulsive Internet Use Scale (CIUS) [19] , a 14-item questionnaire covering core criteria of problematic Internet use. A LCA revealed a 6-class model to have the best fit.”
Quote in the paperNot a substantial claim0 of 2 sources checkedClassified as probably not a substantial claim. May combine two claims.
Premiseown data§ Introduction · p. 2The previous latent class analysis results are limited to adolescents and to online gaming.
“However, results are restricted to adolescents and to online gaming.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Method · p. 3The CIUS was selected because psychometric data for it are available from representative samples.
“This instrument was chosen because data on its psychometric performance in representative samples are available [19]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [19] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone given§ Introduction · p. 2Both general population studies of Internet addiction used diagnostic measures that have not been sufficiently validated.
“Both general population studies suffer from diagnostic measures that have not been sufficiently validated.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisereasoning§ Introduction · p. 2Data used to define Internet addiction come from clinical settings and may not cover the full range of characteristics present in the general population.
“Data to define Internet addiction are derived from clinical settings but may not cover the whole spectrum of characteristics found in the general population.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoning§ Method · p. 3The landline sample was drawn as a clustered and stratified sample with probability proportional to size and implicit stratification to support representativeness.
“For the landline telephone survey a clustered and stratified sample was drawn. At the first sampling stage, 53 sample points (52 municipalities, Berlin was represented by two sample points) were selected based on a 'probability proportional to size' procedure. Implicit stratification ensures a representative selection of German federal states, administrative districts and counties.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown data§ Method · p. 3The mobile-only sample participation rate was 56.6%, yielding 1,001 respondents.
“56.6% (1,001 respondents) participated in the interview.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown data§ Method · p. 3Among participants assessed with the CIUS, 3.2% did not answer all items, and missing values were replaced by mean values when at least 8 items had been answered.
“Of those, 3.2% did not answer to all CIUS items. In the majority of these cases the participants had only one (2.5%) or two (0.4%) missing values. Further, 0.3% did not answer between 3 and 10 CIUS items. A minimum number of 8 items answered was defined and missing values were replaced by mean values.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Introduction · p. 2In that previous latent class analysis, two classes had characteristics making it very likely that participants were heavy users or had problems with online gaming.
“According to the data, 2 of these classes showed characteristics that made it very likely that participants were experiencing heavy use or problems with online gaming”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [18] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ Method · p. 3The CIUS items were translated into German using translation and back-translation.
“The CIUS items were transformed into German by procedures of translation and back-translation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Introduction · p. 2The 20-item Internet Addiction Test is the most widely used questionnaire for Internet addiction.
“The most widely used questionnaire is the 20-item Internet Addiction Test (IAT) [14]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [14] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown data§ Method · p. 3The mobile-only sample used random selection of nationwide cell phone numbers and screened in only those not reachable by landline.
“In the mobile-only sample, a random selection of nationwide cell phone numbers was used and a screening to include only those who could not be reached via landline telephone was performed.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Introduction · p. 2Tao and colleagues define a minimum of 6 hours per day of Internet use as required for a diagnosis of Internet addiction.
“Tao et al. [7] define a minimum amount of 6 h/day spent in the Internet to fulfil the diagnosis of Internet addiction.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [7] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown data§ Method · p. 3The landline sample participation rate was 52.4%, yielding 14,022 respondents.
“52.4% (14,022 respondents) participated in the interview.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoning§ Method · p. 3The telephone survey used a German landline sample plus an additional mobile-only sample to cover people reachable only by cellular phone.
“The survey was based on a German landline telephone sample and an additional mobile-only sample to cover the growing percentage of individuals that are only accessible via cellular phone numbers.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Premisenone given§ Introduction · p. 2The Internet Addiction Test was developed in clinical settings, and its psychometric properties in general population samples are unclear.
“This scale has been developed in clinical settings and psychometric properties for general population samples are unclear.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Social Participation and Trust · p. 4The social participation instrument had good test-retest reliability with a kappa of 0.70 based on dichotomous results.
“Good test-retest reliability was found with a κ of 0.70 based on dichotomous results [22]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [22] source
Not checked in the free run.
Classified as probably not a substantial claim.
Interpretationown data§ Abstract · p. 1The study provides characteristics that can help further define Internet addiction as a relatively new disorder.
“provides characteristics to further define this rather new disorder.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitation§ Social Participation and Trust · p. 4Social participation was assessed with a standardized instrument asking about participation in 13 activity domains during the previous 12 months.
“It was assessed with a standardized instrument by asking if respondents had taken part in activities in 13 domains during the last 12 months [22]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [22] source
Not checked in the free run.
May combine two claims.
Interpretationreasoning§ Discussion · p. 7The authors state their study is the largest representative general-population study so far to estimate how common Internet addiction is and to describe associated features.
“This is the largest representative general population study that aimed to quantify the occurrence of Internet addiction and describe related characteristics so far.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitation§ Social Participation and Trust · p. 4Generalized trust was assessed with the item 'Generally, you can trust other people' using four answer options.
“Generalized trust to other people was assessed with the following item: 'Generally, you can trust other people' with the answer formats 'Do not agree at all' , 'Do not agree' , ' Agree' , and 'Completely agree' [21]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [21] source
Not checked in the free run.
Classified as probably not a substantial claim.
Premisecitation§ Method · p. 3The CIUS has shown a stable one-factor solution across time and different samples.
“A stable one-factor solution was found across time and different samples [19]”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [19] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation§ Introduction · p. 2In that previous study, the dependent-user group made up 3% of the sample and about 1.5% of all children aged 13-16 in the Netherlands.
“This latter group constituted 3% of the sample and about 1.5% of all children aged 13-16 years in the Netherlands.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [18] source
Not checked in the free run.
Classified as probably not a substantial claim.
Premisecitation§ Method · p. 3A CIUS cut-off score of 28 was suggested by the instrument's developers.
“a cut-off score of 28 was suggested from the developers of this instrument [19]”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [19] source
Not checked in the free run.
Classified as probably not a substantial claim.
Premisecitation§ Discussion · p. 7The CIUS is a questionnaire that covers well-accepted signs of problematic Internet use.
“These classes were based on the CIUS, a questionnaire which covers well-accepted signs of problematic Internet use.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [19] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ Discussion · p. 7A clear advantage of this study is its large and representative sample size.
“A clear advantage of this study is the large and representative sample size.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Interpretationown data§ Discussion · p. 7The inclusion of mobile-only participants is of special importance.
“Therefore, the inclusion of mobile-only participants is of special importance.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Study design and conductnone given§ Discussion · p. 7It is not very likely that the inclusion filter resulted in biased findings, but it cannot be fully ruled out.
“It is not very likely that this filter resulted in biased findings, however it cannot be fully ruled out.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisecitation§ Discussion · p. 7Proposed criteria for Internet addiction by Tao et al. include a course criterion requiring at least 3 months of duration and 6 hours of Internet non-business usage per day.
“Proposed criteria for Internet addiction by Tao et al. [7] include a course criterion requiring at least 3 months of duration and 6 h of Internet non-business usage per day.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [7] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ Discussion · p. 7The CIUS might not cover all relevant aspects to specify Internet addiction.
“Another possible shortcoming might be that the CIUS which served as the basis for the LCA might not cover all relevant aspects to specify Internet addiction.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Discussion · p. 7The CIUS includes salience, withdrawal, loss of control, conflict, and coping with unpleasant mood, which resemble current suggestions for classifying Internet use disorders.
“salience, withdrawal, loss of control, conflict and coping with unpleasant mood are included and resemble current suggestions for classifying Internet use disorders.”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone given§ Discussion · p. 7The LCA approach is currently a viable method given that no consensus on criteria to define Internet addiction or problematic Internet use is available.
“the LCA approach is currently a viable method considering that no consensus on criteria to define Internet addiction or problematic Internet use is available.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Discussion · p. 8Use and misuse of mobile phones is prevalent in adolescents.
“use and misuse of mobile phones is prevalent in adolescents [28]”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [28]
Not checked in the free run.
May combine two claims.
Study design and conductown data§ Discussion · p. 7Using the suggested cut-off of 28 results in a rate of 1.5% positive cases and strengthens the solution.
“using the suggested cut-off of 28 for CIUS might serve as another indicator. This results in a rate of 1.5% positive cases and strengthens our solution.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Participants who did not report private Internet use for at least 1 hour on a typical weekday or at least 1 hour on a weekend day were treated as not having Internet addiction or problematic Internet use.
“When calculating the occurrence of Internet use disorders, all participants who did not report Internet use for private purposes at least 1 h on a typical weekday or at least 1 h on a day at the weekend were considered as not having Internet addiction or problematic Internet use.”
The authors state this as an assumption.
A mobile phone number generally represents one person rather than a household.
“Because we assumed that, in general, a mobile phone number represented one person rather than a household”
The paper relies on this without support.
Participants who used the Internet for private purposes less than 1 hour on a typical weekday or weekend day do not have problematic Internet use or Internet addiction.
“All participants with less time spent in the Internet were considered as not having problematic use or Internet addiction.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the age group of 14-16 years, girls show a higher prevalence of addictions to the Internet and SNSs in a representative German sample.
“First, in the age group of 14–16 years, girls appear to show a higher prevalence of addictions to the Internet and SNSs, as found in a representative German sample [88]”
From Social networking sites and addiction: Ten lessons learned (2017) · cites this paper as [88]
There are sociodemographic differences among those addicted to social networking.
“Research suggests there are sociodemographic differences among those addicted to social networking.”
From Social networking sites and addiction: Ten lessons learned (2017) · cites this paper as [88]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
The whole-sample age range changes in the gender comparisons
MinorThe gender-comparison text calls its first group the entire sample but labels it ages 18-64. Table 3 identifies the entire sample of 15,023 as ages 14-64.
“Looking at probable Internet addiction in the entire sample and in subgroups according to age, no significant differences between males and females can be found: age 18-64”
“| 14-64 (n = 15,023) | 1.0 (0.9-1.2) | 0.8 (0.6-1.1) | 1.2 (1.0-1.6)”
The one-class BIC does not follow the stated trend
MinorThe paper says BIC decreases as the number of classes increases, but the printed one-class BIC is 23.560 and the two-class BIC is 220.945. The latter is higher, not lower.
“Lower BIC values and higher entropy measures (both as desired) can be found with the increasing number of classes.”
“| Class = 1 BIC = 23.560 | 1 | 0.03 | 8,130 | 1,000 | | | | Classes = 2 | 1 | -0.53 | 5,564 | 0.910 | 0.000 | 0.000 | | BIC = 220.945 Entropy = 0.658 | 2 | 1.13 | 2,566 | 0.875 | | |”
Mobile-only eligibility uses a different upper age limit
MinorThe mobile-only screening description gives an eligible age range ending at 46, while the study describes its target population, including mobile-only respondents, as aged 14-64.
“11,506 did not fulfil the inclusion criteria (age group 14-46)”
“The combined design weights for the mobile-only and landline sample were computed by assuming an estimated proportion of 14% of German residents are exclusively accessible via mobile phone in the 14- to 64-year-old age group.”
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- Authors
- Rumpf, H.-J., Vermulst, A. A., Bischof, A., Kastirke, N., Gürtler, D., Bischof, G., Meerkerk, G.-J., John, U., & Meyer, C.
- Affiliations
- Radboud University Nijmegen (NL)
- ORCID
- Venue
- European Addiction Research
- Publisher
- S. Karger AG
- Published
- 2013-12-24
- Volume
- 20
- Issue
- 4
- Pages
- 159-166
- ISSN
- 1022-6877 (ISSN-L)
- 1421-9891
- OpenAlex
- W1972051428
- Semantic Scholar
- f809291ce77f56fdc74b4695200bac014f657731
- Cited by
- 199
- References
- 27
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 13 · 2023: 20 · 2022: 17 · 2021: 26 · 2020: 22 · 2019: 18 · 2018: 20 · 2017: 17 · 2016: 12 · 2015: 10 · 2014: 10 · 2013: 1
- FWCI
- 33.95
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Addiction Research (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Clinical Psychology › Sexuality, Behavior, and Technology
- Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
- Keywords
- internet addiction, prevalence, Compulsive Internet Use Scale, latent class analysis, social participation (health and rehabilitation), interpersonal trust, unemployment, migration background, adolescents, general population
- MeSH terms
- Adolescent, Adult, Emigration and Immigration, Female, Humans, Male, Middle Aged, Risk Factors, Unemployment, Models, Statistical, Prevalence, Behavior, Addictive, Internet, Young Adult
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