The role of metacognitions in problematic Internet use
David Cohen, M.D.·Published 13 May 2008·22 min read
Key points
Research has suggested that negative emotions are associated with problematic Internet use.
The last decade has seen a world-wide surge in Internet use.
Participants and procedure Convenience sampling was used for selecting participants, who consisted of university students residing in the United Kingdom.
Hospital Anxiety and Depression Scale (HADS; Zigmond & Snaith, 1983).
Research has suggested that negative emotions are associated with problematic Internet use. This study investigated the role of metacognitions as a mediator of the relationship between negative emotions and problematic Internet use. A sample of 97 university students completed the following questionnaires: Hospital Anxiety and Depression Scale, Boredom Proneness Scale, Metacognitions Questionnaire 30, and Internet Addiction Test. All dimensions of metacognition were found to be positively and significantly correlated with problematic Internet use. Positive and significant correlations were also observed between problematic Internet use and negative emotions (anxiety, depression and boredom). Structural equation modeling was used to test a mediation model in which negative emotions predicted metacognitions which in turn predicted problematic Internet use. The results supported the hypothesis that the relationship between negative emotions and problematic Internet use is fully mediated by metacognitions, suggesting that metacognitive theory may be relevant to understanding problematic Internet use. The implications of these findings are discussed.
Keywords: Anxiety; Boredom; Depression; Metacognitions; Negative emotions, problematic Internet use
Introduction
The last decade has seen a world-wide surge in Internet use. This has been accompanied by a growing concern over what researchers have variously termed problematic, pathological or addictive Internet use (e.g. [Beard and Wolf, 2001], [Scherer, 1997], [Wallace, 1999] and [Young, 1998a]). Problematic Internet use (PIU) can be defined as "use of the Internet that creates psychological, social, school and/or work difficulties in a person's life" (Beard & Wolf, 2001, p. 378).
Anecdotal and research evidence suggests that PIU affects a significant number of people with incidence rates (determined by frequent or daily Internet usage meeting varying criteria for pathological use) ranging between 4.6% and 18.3% ([Kaltiala-Heino et al., 2004], [Morahan-Martin & Schumacher, 2000] and [Niems et al., 2005]). These figures exceed the estimated incidence rates for other impulse control disorders, the category of disorders which PIU has most often been compared to ([LaRose et al., 2003] and [Shapira et al., 2003]). Pathological gambling, for example, is estimated to affect 1–3% of the US population and other impulse control disorders have even lower incidence rates (American Psychiatric Association, 2000).
A variety of studies have investigated the relationship between PIU and psychological dysfunction, revealing that anxiety and mood problems are common among problematic Internet users ([Kim et al., 2006], [Morgan and Cotten, 2003], [Sanders et al., 2000], [Whang et al., 2003] and [Young and Rogers, 1998]). Additionally, negative emotions appear to differentiate problematic from non-problematic Internet use with a reduction of negative emotions driving problematic use, and an enhancement of positive emotions driving non-problematic use (Wan & Chiou, 2006). As such, using the Internet may represent a way of coping with real life problems that takes the form of problem solving, entertainment and challenge in non-problematic use, and of reassurance and avoidance in problematic use. If this were the case then PIU could be conceptualized as a specific form of maladaptive self-regulatory strategy (LaRose et al., 2003).
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David Cohen, M.D.
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The emergence of cognitive theories of psychological dysfunction (e.g., Beck, 1976) has led to a growing interest in the characteristics of cognition and its regulation. Recent work by Davis (2001), applying Beck's (1976) cognitive therapy paradigm, has highlighted the potential role of cognitions in the development and maintenance of PIU. More recently, a particular line of theoretical work has begun emphasizing the role of metacognitions as central to the development and persistence of psychological dysfunction ([Wells, 2000], [Wells and Matthews, 1994] and [Wells and Matthews, 1996]).
Metacognitions refer to the information individuals hold about their own cognition and internal states, and about coping strategies that impact on both ([Flavell, 1979], [Wells, 2000], [Wells and Matthews, 1994] and [Wells and Matthews, 1996]). Examples of information individuals hold about their own cognition and internal states may include beliefs concerning the significance of particular types of thoughts, e.g. "It is bad to think thought X" or "I need to control thought X". Examples of information individuals hold about coping strategies that impact on cognition and internal states may include beliefs such as "Smoking will help me get things sorted out in my mind" or "Drinking will help me solve the problem". According to the metacognitive theoretical tenet ([Wells, 2000], [Wells and Matthews, 1994] and [Wells and Matthews, 1996]) metacognitions are fundamental in predisposing individuals to develop response patterns to thoughts and internal events that are characterised by heightened self-focused attention, recyclic thinking patterns, avoidance and thought suppression, and maladaptive behaviors. One such maladaptive behavior may be indeed PIU.
The role of metacognitions has been explored using the Metacognitions Questionnaire ([Cartwright-Hatton and Wells, 1997] and [Wells and Cartwright-Hatton, 2004]), which was developed to assess metacognitions related to psychopathology. The questionnaire consists of five distinct sub-scales: (1) positive beliefs about worry, measuring the extent to which a person believes that perseverative thinking is useful; (2) negative beliefs about worry concerning uncontrollability and danger, which assesses the extent to which a person thinks that perseverative thinking is overwhelming and dangerous; (3) cognitive confidence, which assesses confidence in attention and memory; (4) beliefs about the need to control thoughts; and finally (5) cognitive self-consciousness, measuring the tendency to monitor one's own thoughts and focus attention inwards.
Support for the link between individual dimensions of metacognition and psychological dysfunction has come from a wide range of studies that show cross-sectional and directional relationships between dimensions of metacognition and psychological disturbance including, depression (Papageorgiou & Wells, 2003), generalised anxiety disorder ([Wells, 2000] and [Wells and Matthews, 1994]), hypochondriasis (Bouman & Meijer, 1999), obsessive–compulsive symptoms ([Emmelkamp and Aardema, 1999], [Hermans et al., 2003], [Myers and Wells, 2005] and [Wells and Papageorgiou, 1998]), pathological procrastination (Spada, Hiou, & Nikcevic, 2006), pathological worry (Wells & Papageorgiou, 1998), post-traumatic stress disorder (Roussis & Wells, 2006), predisposition to auditory hallucinations ([Baker and Morrison, 1998] and [Morrison et al., 2000]), problem drinking ([Spada et al., 2007], [Spada and Wells, 2005], [Spada and Wells, 2006] and [Spada et al., 2007]), psychosis (Morrison, French, & Wells, 2007), smoking dependence ([Spada et al., 2007], [Spada et al., 2007] and Spada et al., 2007 M.M. Spada, M. Zandvoort and A. Wells, Metacognitions in problem drinkers, Cognitive Therapy and Research 31 (2007), pp. 709–716. Full Text via CrossRef[Spada et al., 2007]), and test-anxiety ([Matthews et al., 1999] and [Spada et al., 2006]).
To date, no attempt has been made to investigate the possible links between PIU, metacognitions and negative emotions. Two lines of reasoning suggest that metacognitions should be associated with PIU. Firstly, PIU has been conceptualized as a means for regulating negative cognition and affect, and as such it represents, at least in part, a strategy that should be driven by metacognitions. Secondly, negative emotions are associated with PIU, and according to metacognitive conceptualizations of psychological dysfunction, emotional disturbance should be linked to maladaption in metacognitions.
In this study, we tested a mediation model in which negative emotions predict metacognitions which in turn predict PIU. Because all the variables in the model were expected to be highly correlated and measured with large errors, the test was performed using structural equation modeling.
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Method
2.1. Participants and procedure Convenience sampling was used for selecting participants, who consisted of university students residing in the United Kingdom. Ninety-seven individuals (41 females, 56 males) completed the study. For purposes of inclusion in the study participants were required to speak English, be at least 18 years of age, and have used the Internet over the previous week. The mean age of the sample was 23.3 years (SD = 3.0 years) and the age range was 18–30 years. The sample was 78.4% Caucasian, 10.3% African–British, 5.2% Asian and 6.2% other. Participants were approached and asked if they were willing to take part in a research project "investigating the role of thoughts and emotions in Internet use". Participation in the research project was entirely voluntary. Participants who agreed to take part in the study were seated at a desk and asked (verbally and in writing) to provide demographic details and complete the batch of questionnaires (HADS, BPS, MCQ-30 and IAT) on one occasion. The questionnaires were administered in pencil-and-paper format and presented randomly. Participants were informed that they had 20 min available to complete the batch of questionnaires. At the end of the task participants were asked to return the batch of questionnaires and were debriefed about the research project. No opportunity was given for response correction.
2.2. Measures
The following scales were used:
Hospital Anxiety and Depression Scale (HADS; Zigmond & Snaith, 1983). This scale consists of 14 items, 7 assessing anxiety and 7 assessing depression. The anxiety sub-scale includes items such as: "I get a sort of frightened feeling as if something horrible is about to happen". The depression sub-scale includes items such as: "I feel as if I am slowed down". Higher scores represent higher levels of anxiety and depression. Overall, the scale possesses good validity and reliability ([Herrmann, 1997], [Mykletun et al., 2001] and [Zigmond and Snaith, 1983]). HADS was chosen as a measure of negative emotions because it is widely used in both clinical and non-clinical research samples across a variety of domains in psychological dysfunction (e.g. [Alati et al., 2004] and [Wagena et al., 2005]).
The Boredom Proneness Scale (BPS; Farmer & Sundberg, 1986). This scale consists of 28 items assessing levels of boredom. Examples of items include: "It is easy for me to concentrate on my activities"; "Time always seems to be passing slowly". Higher scores represent higher levels of generally experienced boredom. The scale possesses good psychometric properties ([Ahmed, 1990] and [Farmer and Sundberg, 1986]).
Metacognitions Questionnaire 30 (MCQ-30; Wells & Cartwright-Hatton, 2004). This measure assesses individual differences in metacognitive beliefs, judgments and monitoring tendencies. It consists of five replicable sub-scales assessed by 30 items in total. The five sub-scales measure the following dimensions of metacognition: (1) positive beliefs about worry (e.g. "worrying helps me cope"); (2) negative beliefs about worry concerning uncontrollability and danger (e.g. "when I start worrying I cannot stop"); (3) cognitive confidence (e.g. "my memory can mislead me at times"); (4) beliefs about the need to control thoughts (e.g. "not being able to control my thoughts is a sign of weakness"); and (5) cognitive self-consciousness (e.g. "I pay close attention to the way my mind works").
Higher scores represent higher levels of metacognitive maladaption. The MCQ-30 possesses good internal consistency and convergent validity, as well as acceptable test–retest reliability (Wells & Cartwright-Hatton, 2004).
The Internet Addiction Test (IAT; Young, 1998b). This measure consists of 20 items assessing the degree of problematic Internet use. Examples of items include: "How often do you choose to spend more time on-line over going out with others?"; "How often do you lose sleep due to late-night log-ins?". Higher scores represent higher levels of problematic Internet use. The scale has been found to posses good psychometric properties (Widyanto & McMurran, 2004).
{pagebreak}2.3. Statistical analysis
The hypothesised mediation model was tested using structural equation modeling (e.g., Kline, 1998) as implemented in LISREL 8.8 (Jo"reskog & So"rbom, 1996). Simpler statistical techniques for the test of mediation, such as Baron and Kenny (1986) four-step regression procedure, assume that the mediator is measured with no error, and tend to produce unstable estimates when the sample is small and the variables are strongly intercorrelated. Structural equation modeling allows for controlling the measurement error of the mediator and of other study variables thus coping more efficiently with small sample size and multicollinearity.
Structural equation modeling requires defining a measurement model and a structural model. The measurement model is a confirmatory factor model in which each of the study variables is defined as a latent variable imperfectly measured by a set of directly measurable indicator variables. The relationships between a latent variable and its indicators are graphically represented as arrows heading from the latent variable to its indicators, meaning that the latent construct "produces" the indicators as its manifestations; the coefficients of these paths are equivalent to factor loadings. The structural model is a path model that specifies the relationships between latent variables. A relationship between two latent variables is graphically represented as an arrow heading from one latent variable to the other latent variables, meaning that the first variable "causes" or "predicts" the second one; the coefficients of these paths are equivalent to regression coefficients. Although the language of structural equation modeling is causal, when a model is fitted to cross-sectional (not-experimental and not-longitudinal) data, the structural paths should be prudently interpreted as indicative of causal relationships.
The three study variables (negative emotions, metacognitions, and PIU) were defined as latent variables. The two sub-scale scores of the HADS and the scale scores of the BPS were defined as the indicators of the latent variable negative emotions. The five sub-scale scores of the MCQ-30 were defined as the indicators of the latent variable metacognitions. Indicators for the latent variable PIU were created using parcelling as follows. We first fitted a single-factor Principal Components model to the item score of the IAT. The scree-plot indicated that a single-factor was sufficient, confirming that the scale is unidimensional. The item factor pattern coefficients were all positive. We then created parcels using the item factor pattern coefficients as a guide, following the "item-to-construct balance" method (e.g., Little et al., 2002 T.D. Little, W.A. Cunningham, G. Shahar and K.F. Widaman, To parcel or not to parcel?: Exploring the question, weighing the merits, Structural Equation Modeling 9 (2002), pp. 151–173. Full Text via CrossRefLittle, Cunningham, Shahar, & Widaman, 2002). We created two parcels of seven items and one of six items.
The indicators of the latent variables MCQ-30 and HADS are specific constructs, that is, facets of the underlying latent construct that are measured as sub-scales of an overall scale. Instead, the indicators of the latent variable PIU are unspecific constructs, that is, aggregate parcels of items that are designed to measure the same underlying construct, not different facets of the underlying construct. Three parcels were used instead of two because three indicators allow a considerably more efficient estimation of the PIU error variance, which is what the model is primarily intended to explain. Three parcels were used instead of four or more because, due to the small sample size, the addition of parameters would result in overall less stable estimation of the model.
Lisrel 8.8 employs a range of goodness-of-fit indices to estimate the adequacy of the proposed model under investigation. The most common statistic test for the assessment of the model fit is the Chi-square goodness of fit test (?2). This test estimates the discrepancies between the observed covariance matrices and those implied by the model. A non-significant Chi-square value indicates adequacy of a model. The Chi-square statistic assesses the absolute fit of the model to the data however it is sensitive to sample size and often inflates Type 1 error ([Bollen, 1989] and [Cohen, 1988]). Therefore it is necessary to use additional indices to evaluate the model fit. We have chosen the Root Mean Square Error of Approximation (RMSEA) which indicates the closeness of fit and is sensitive to the mis-specification of the measurement model (the factor loadings). Cut-off values close to .08 demonstrate adequate fit of the model, whereas between 0 and .05 indicate a good fit ([Browne and Cudeck, 1993] and [Hu and Bentler, 1999]). The relative Comparative Fit Index (CFI) was selected as an incremental fit index. The minimally acceptable fit is indicated by threshold values of .90 with values close to or above .95 indicating a good model fit (Hu & Bentler, 1999).
The analysis was conducted in two steps. In the first step, we defined three structural paths: (a) a path from negative emotions to PIU, (b) a path from negative emotions to metacognitions, and (c) a path from metacognitions to PIU. These paths represent the correlated antecedents of PIU which are consistent with a partial mediation process, in which negative emotions has both a direct effect on PIU and an indirect effect through the mediation of metacognitions.
In the second step of the analysis, we tested the model of the previous step but without the path (a) from negative emotions to PIU. The remaining two paths (b) and (c) represent the correlated antecedents of PIU which are consistent with a complete mediation process, in which negative emotions only has an indirect effect on PIU through the mediation of metacognitions. The comparison in goodness of fit between the models of the first and second step provided useful information on the nature and strength of the hypothesised mediation process.
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Discussion
The goal of this study was to determine whether metacognitions mediated the relationship between negative emotions and PIU. The results of the correlation analyses indicated positive and significant correlations between all dimensions of metacognition and PIU. In accord with research evidence positive and significant correlations were identified between PIU, anxiety, depression and boredom. The results of structural equation modeling supported the mediation hypothesis, suggesting that mediation is complete. These findings, taken together suggest that the basic premise of the (Wells and Matthews, 1994) and Wells and Matthews, 1996) metacognitive model of psychological disorder may be extended to PIU.
Why should the metacognitive dimensions identified be relevant? Two of the domains (positive beliefs about worry, and cognitive confidence) represent metacognitive knowledge about the usefulness of perseverative thinking as a coping strategy, and the ineffectiveness of memory and judgment. Overall these variables may reflect diminished confidence in coping and a need to anticipate problems (through worry and rumination) in order to function. If we are correct in assuming that these are a marker for low metacognitive confidence, then they would contribute to PIU because the Internet can provide information to reduce metacognitive discomfort. Examples may include searching for information on the specific symptoms of a disease because one believes that worrying is a helpful strategy to cope with intrusive thoughts (e.g. about disease), or searching for information regarding train times because of one's lack of trust in his or her own mnemonic capabilities. In addition, it is possible to postulate that negative beliefs about worry concerning uncontrollability, beliefs about the need to control thoughts, and high self-consciousness taken together are a marker for the tendency to monitor and control intrusive thoughts. In turn, the strategies that are employed to control intrusive thoughts, if maladaptive (e.g. perseverative thinking and thought suppression), will lead to an increase in the accessibility of negative information about the self and a greater likelihood of utilizing the Internet to regulate one's emotional state.
The MCQ-30 was not intended to specifically capture metacognitions in PIU, and only preliminary inferences about the nature of their statistical contribution can be made at the present time. However, the data do support the potentially ubiquitous contribution of metacognition to perseverative and unhealthy forms of cognition and behavior, by demonstrating relationships with PIU. The finding that metacognitions fully mediate the relationship between negative emotions and PIU extends conceptualizations of the problem that are based on a direct link between negative emotions and PIU.
The results of this study must be considered with regard to design limitations. Firstly a cross-sectional design was adopted and this does not allow causal inferences. Secondly social desirability, self-report biases, context effects, and poor recall may have contributed to errors in self-report measurements. Finally the sample consisted only of university students and potential confounders such as socio-economic status and education were not controlled for. Thus, whilst the present findings can be generalised to PIU they will need to be verified by examining individuals from a wider age range and controlling for background variables. Future research will have to ascertain the role of metacognitions in the predisposition towards, and maintenance of, PIU through longitudinal designs. Finally, efforts will have to be directed towards investigating the influence of PIU on metacognitions. This could be accomplished, for example, by ascertaining whether metacognitions differ between problem and non-problem Internet users.
Despite the above limitations, we believe the present findings provide the basis for developing a metacognitive understanding of PIU.
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Marcantonio M. Spada, Benjamin Langston, Ana V. Nikcevic and Giovanni B. Moneta
School of Human and Life Sciences, Roehampton University, Whitelands College, Holybourne Avenue, London SW15 4JD, United Kingdom Unit of Psychology, Kingston University, Kingston – Upon - Thames, UK Department of Psychology, London Metropolitan University, London, UK
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