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Person-centred interventions for problem gaming: a stepped care approach

BMC Public Health volume 21, Article number: 872 (2021) Cite this article

Abstract

Background

Problem gaming is reported by approximately 1–3% of the population and is associated with decreased health and wellbeing. Research on optimal health responses to problem gaming remains limited. This study aimed to identify and describe the key components of a person-centred approach to interventions for problem gaming for individuals who voluntary seek assistance.

Methods

Online interviews were conducted with 20 adults (90% male; Mage = 23y) currently seeking help for problem gaming. The interview protocol was guided by a health care access framework which investigated participants’ experiences and needs related to accessing professional support. Transcripts were analysed in NVivo using qualitative content analysis to systematically classify participant data into the themes informed by this framework.

Results

Participants had mixed views on how the negative consequences of problem gaming could be best addressed. Some indicated problems could be addressed through self-help resources whereas others suggested in-person treatment with a health professional who had expertise in gaming. Participants described the essential components of an effective health service for problem gaming as including: valid and reliable screening tools; practitioners with specialist knowledge of gaming; and access to a multimodal system of intervention, including self-help, internet and in-person options that allow gamers to easily transition between types and intensity of support.

Conclusion

A comprehensive health care approach for interventions for problem gaming is in its infancy, with numerous service access and delivery issues still to be resolved. This study highlights the importance of involving individuals with gaming-related problems in developing solutions that are fit for purpose and address the spectrum of individual preferences and needs. These findings recommend a stepped healthcare system that adheres to evidence-based practice tailored to each individual and the implementation of standard assessment and routine outcome monitoring.

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Background

Problem gaming is reported by approximately 1–3% of people internationally [1,2,3,4]. People with gaming problems report issues including reduced quality of physical health (e.g., sleep disruption), psychological well-being (e.g., anxiety and depression), social life (e.g., impaired quality of relationships) and legacy problems such as reduced employment or educational attainment [5,6,7]. People with gaming problems also report other mental health conditions including anxiety, depression, ADHD, social phobia, and anxiety. Problem gaming appears to be more prevalent in male gamers [8, 9]. Following a provisional status for ‘internet gaming disorder’ in the DSM-5 (American Psychiatric Association, 2013), “Gaming Disorder” was officially adopted at the World Health Assembly in May 2019 as a diagnosis in the eleventh edition of the International Classification of Diseases (ICD-11) [10]. Gaming disorder within the ICD-11 is characterized by increasing priority given to gaming over other activities, impaired control over gaming, and functional impairment due to gaming for a period of at least 12 months in most instances. Recognition in the ICD-11 is an important step toward advancing knowledge and standardising approaches to the condition. However, the concept of problem gaming as an addictive disorder is the topic of extensive debate [2, 11,12,13,14,15,16,17,18,19]. For instance, measurement inconsistencies add to problems identified with specific criteria listed in the IGD classification, particularly the relatively low specificity of the tolerance and mood modification criteria [20]. In the current paper we refer to gaming problems as inclusive of Gaming Disorder.

Recent systematic reviews and meta-analyses have examined the quality and effectiveness of prevention of gaming problems [21,22,23,24] and treatment [25,26,27,28]. To date, research on prevention has tended to focus on school-based prevention programs. Much of the work in this area has been conducted in Asian settings [29, 30], including South Korea and China, where there have been parallel developments in trialling targeted technology-restriction measures including content filters and gaming time limits aimed particularly at younger users [31,32,33,34]. In terms of treatment, the most common approach has been cognitive-behavioural therapy (CBT), usually delivered in brief individual and group-based formats, and other non-CBT psychotherapeutic interventions [25,26,27, 35, 36]. CBT for gaming problems may be an effective short-term approach for reducing gaming problems and depressive symptoms, but more studies with follow-up are needed to assess longer-term gains [35, 37]. Pharmacological interventions have predominantly employed antidepressants (i.e., bupropion and escitalopram), but their effectiveness is currently unclear due to lack of controlled trials [14]. Some treatment centres provide brief voluntary retreats from digital technologies, group therapy and social activities, but these options may be financially burdensome and have limited evidence for their long-term efficacy.

The growing body of literature examining early intervention and treatment for gaming problems highlights several important gaps [25, 26, 30, 36]. Zajac et al.’s [26] review of 15 studies reported that the majority had targeted school age samples with just six studies involving adults. The majority of participants were male and almost all were conducted in university settings, however there was some heterogeneity in terms of problem severity (mild, moderate and severe problems) and time spent gaming (ranging daily to weekly sessions, and very low to high levels of gaming time). Treatment was often delivered over 4 to 8 weeks, and almost all were delivered via in-person consultation. Other reviews [25, 36] have reported most studies have been conducted in East Asian settings, indicating a need for cross-cultural perspectives. There are well-documented problems of validity across a wide range of assessment tools, including those employed in intervention studies [38, 39]. A related problem is that many intervention studies, particularly those in Asia, have relied on problematic internet use measures to evaluate gaming. Together, these reviews suggest that interventions may be enhanced by a range of improvements and wider consideration of alternative treatment approaches and delivery methods.

Very few people experiencing gaming-related problems will access the healthcare system [24, 40]. A longitudinal study involving over 4000 adults in Canada reported just 4.5% of people with gaming problems (n = 69) had sought professional help [41]. The type of help surveyed included a family physician, psychologist, psychiatrist, counseling service or telephone helpline. Rates of professional treatment-seeking for other addictive behaviours is approximately 10% [42], much higher than is reported for gaming problems. The reason for the low rate of treatment seeking may be due to structural issues such as the homogeneity of available treatments and lack of available options. Most research has investigated intensive and in-person treatments which may not be the right kind of support for people without other complex or co-occurring issues. For those that could benefit from in-person treatment, it may be that individual barriers such as procrastination, impulsivity, shyness or introversion impede help-seeking [43,44,45,46]. Another possibility is that some individuals with gaming-related problems seek out information, social support and assistance from less formal, convenient sources (e.g., online support groups), and this is sufficient to address the problem [47].

People with gaming problems report co-occurring mental health issues which may be a precursor or concurrent to gaming problems [48]. High rates of depression, anxiety, substance use and gambling disorder may mean people with gaming problems attend other services for more acute issues and therefore do not report seeking help for gaming [46]. Lau et al. [49] for example, examined the records of 5820 clinically referred youth in the Canadian mental health system and reported that moderate to severe problematic gaming was reported by 13% of the sample; however, most of the sample had been referred for issues including threat or danger to self or others, or other psychiatric symptoms. This suggests a need to explore how early intervention and treatment for gaming problems can be provided by a range of different health care providers.

Taken together, the evidence suggests a need to broaden the scope of research into interventions so as to provide a stepped care approach to early intervention and treatment. The current study interviewed people experiencing gaming problems to gather their views of the components of an effective integrated health care approach. Although the prevalence of gaming problems in New Zealand (NZ) is currently unclear, there is evidence of problematic gamers in this region [50] and surveys of psychiatrists and mental health professionals that suggest NZ gamers and their support networks may seek help via addiction and related services [51, 52]. The aims of this study were to: (i) describe the experiences and needs of people seeking help for gaming problems; and (ii) identify the optimal components of a health care system to support early intervention and treatment of gaming problems.

Methods

Participants

Participants were drawn from a larger study examining the impact of a brief online intervention for gaming problems [53]. The larger study involved 50 gamers who reported an intention to limit or reduce their gaming in the next 30 days. Participants were also required to be aged 18 years or older and not currently seeking in-person treatment. The current study involved sequential recruitment of the first 20 participants willing to engage in a semi-structured online interview examining the needs, experiences, and preferences for treatment-seeking in New Zealand. Recruitment occurred over a one-month period between April and May 2019 through social media advertising, posters in the Auckland community (university, schools, supermarkets) and word of mouth. While there was no specific remuneration for the current study, all participants received a NZD$50 shopping voucher for completing follow-up evaluation as part of the main study. The research was approved by the University of Auckland Human Participants Ethics Committee (022614).

Table 1 presents a summary of participant information. The majority of participants were male (n = 18, 90%) and the average age of participants was 23 years (range: 20 to 35 years). The sample primarily identified as New Zealand European (n = 10, 50%) and as Asian (n = 7, 35%). Using the Gaming Addiction Scale-21 [54] to screen for problematic gaming, 16 participants were classified as problematic gamers (endorsed four or more of seven item areas). Four participants indicated concerns about their gaming but did not meet the GAS cut-off score. The average hours spent online per week was 29 (SD = 23) with an average frequency of 9 sessions per week (SD = 4.7).

Table 1 Participant characteristics at baseline
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Procedure

All participants completed a participant information sheet and informed consent form in Qualtrics survey software. This included completion of demographic (age, sex, employment, ethnicity) and gaming-related measures. The survey included the 21-item Game Addiction Scale [54] which measures seven dimensions of problem gaming (i.e., salience, tolerance, mood modification, relapse, withdrawal, conflict and problems). Participants also completed the Time Line Follow Back [55, 56] to determine the duration and frequency of gaming, and the Kessler 6 measure of non-specific psychological distress [57].

A semi-structured interview schedule was developed based on the components of the person-centred model for accessing health care by Levesque (2013) and colleagues [58]. As indicated in Fig. 1, this access framework highlights the important relationship between the design of health services and the capabilities of those who seek help to facilitate access to appropriate health care and improved health.

Fig. 1
figure 1

Conceptual framework of access to health care based on Levesque et al. [58] 

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The purpose of semi-structured interviews was to identify needs and preferences for support and treatment, specific to gaming problems. The first part of the interview schedule focused on the capabilities of gamers, and the individual barriers and facilitators to help seeking. This included the questions: “I understand that you are interested in doing something about your gaming. What made you make this decision?” and “What might stop you from getting help? What could help address these barriers?” Additional prompts were included in the semi-structured interview schedule to continue the conversation if it became stalled (i.e., the participant needed more context on the nature of the questions). These included: reasons for wanting to change gaming and reasons for seeking help; barriers and facilitators to help seeking; and knowledge of services. The second part of the interview schedule focused on support and service needs. Specifically, participants were asked: “We are looking at services that could be developed for people wanting help for gaming. Let’s say you decide you want to seek help in the future. What would be important to you in a service?” Prompts included accessibility (cost, waiting times, travel, location, type of support), quality (treatment types, qualifications, relationships, desired resources) and equity (considerations for culture, age, sex and social disadvantage).

Interviews were conducted by a postgraduate population health student under supervision. The interviewer was trained in motivational interviewing and the administration of a semi-structured interview schedule. Interviews were by appointment and delivered via the participants’ preferred instant messaging platform (Facebook Messenger, Skype, WhatsApp). Instant messaging was used instead of recording video call to provide greater participant anonymity, increase personal disclosure, and provide more coherent verbal expression for qualitative analysis. Transcripts were created by copying and pasting the online conversation into a word document. The average time per interview was 90 min (range 40 to 180 min) and the average word count was 839 (range 377 to 1988).

Data analysis and application of framework

We applied the conceptual framework of person-centred access to health care to understand how services can meet the needs of people with gaming problems [58]. This framework systematically describes the client and provider factors necessary to facilitate the entire client experience from the point of identifying a health care need to the ultimate achievement of improved health outcomes (see Fig. 1). From the client perspective, the framework outlines five processes that influence access to support and treatment. These include the ability to perceive a need for treatment (including health literacy, health beliefs and knowledge of services); ability to seek, reach and pay for treatment as well as an ability to engage (facilitating minimal attrition and maximum adherence). From the treatment provider perspective, client access to health care is influenced by their approachability (service information, screening tools), acceptability (values and culture of the organisation and support for client autonomy), availability (physical location, mode of delivery, qualifications of provider and flexible opening hours), affordability (time and resource costs) and appropriateness (delivery of evidence-based treatment tailored to client need). A qualitative content analysis [59] was used to group our data into this framework. This method was selected because we wanted to systematically classify participant data into themes guided by an established framework [59].

NVivo software was used to assist the qualitative content analysis. Transcripts were read twice for familiarity with the data and initial codes developed. Two complete transcripts were coded by two researchers (JP and SR). The codes were discussed and disagreements were resolved through consensus. Common codes were grouped by the first author into themes that were adjusted to accommodate additional data. As outlined by Hsieh and Shannon [59], this data was then grouped into broad categories which reflected the selected framework. Data that could not be coded into one of the broad categories were re-examined to describe different manifestations of treatment needs and these were merged into the framework and noted accordingly. The findings were structured according to: (1) participant ability to perceive, seek, reach, pay and engage with health care, which is supported with illustrative quotes, and (2) the proposed components of a health care system response specific to gaming problems. We reported the proportion of participant statements (n = 568 statements that were coded) that align with each of the five components of the framework. All 20 participants provided at least one statement that was relevant to the framework. Where quotes were used, these were de-identified to ensure participant anonymity. Quotes were also cleaned to improve readability (i.e., spelling and punctuation) as well as clarity (i.e., grammar corrected).

Results

Treatment needs and preferences

Table 2 presents a summary of the five components of the framework from the client perspective. The most frequently discussed participant experiences related to ability to seek help with relatively less discussion on ability to pay for services. The ability to perceive a need for help was focused on health beliefs and health literacy (10% of statements from the 20 participants). Health beliefs focused on the seriousness of gaming problems in relation to the amount of harm. Participants indicated they had a reasonable understanding of the characteristics of gaming problems including its nature, prevalence, and resultant harms. As indicated in Table 1, participant experiences ranged from gaming being a problem that could be managed, through to a range of negative consequences including reduced quality of health, work, sleep and social life. Participants reported that family and friends were a barrier to perceiving a problem in that gaming problems were not real, trivial, or a “soft” addiction. Participants stated this increased their feeling of being stigmatised and a key reason to delayed help-seeking. There were many different reported reasons for deciding to change as indicated by the cons of gaming starting to outweigh the pros. For some participants, there were co-occurring issues such as alcohol, cannabis or mental health issues that were more acute and/or deserving of attention.

Table 2 Mapping participant experiences against the five constructs
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The ability to seek support was informed predominantly by beliefs that in-person treatment-seeking for problem gaming was inappropriate. There was low knowledge of service options and a perception that if help was sought, then services would not be willing or able to respond (33% of statements). Some participants perceived that the individual should be able to solve the problem themselves and that the issue was not as serious as other conditions (i.e., illicit drug use). Informing this view was social group responsivity that either minimised the problem or suggested the solution was simple (‘just stop’). Participants reported feeling embarrassed at having to seek help. They were also embarrassed to tell friends they needed to cut back on gaming for a while. There was also a perception that health resources would be made available according to the burden of disease, where gaming was less of a priority concern (due to it not being associated with serious harm). Some participants who had previous experience with addiction or health care services reported concerns on the appropriateness of service models that were either adolescent-centric (thereby being more family-centred in their approach) or focused on a disease model of addiction (abstinence over harm minimisation).

The ability to reach services referred to the ease of access and being located where they were most needed (22% of statements). The absence of a service system for gaming problems was highlighted in this theme, whereby participants who had sought treatment from addiction or private providers had to travel long distances to seek help or instead sought help online from international sources. They thought help should be in a convenient physical location such as co-located with university or other health care services such as those that address substance use problems (e.g., alcohol, cannabis). There was a preference for a range of different modalities for treatment which included online and in-person, as well as individual and group options. Online treatment was especially attractive for its convenience, time efficiency (access or engagement), and that as it allowed participants to type instead or talk (which was preferable initially for introverted help-seekers). There was also a view that some service options should be local, immediate, and available 24/7, which would help to address urgent issues before they became more desperate, such as the need to decrease gaming time during exams.

The ability to pay related to the direct costs of in-person treatment as well as other facilitating factors (10% of statements). There was a preference for direct costs to be assessed according to employment status and income. For those with low income there was an expectation of paying around NZD$20p/h for the service and upwards of NZD$100p/h for those that were employed. Factors impacting on ability to pay included recent transitions from home to independent living arrangements. Other factors included over-spending on gaming such as the frequent purchase of loot boxes, new games and other products such as cards and tokens.

The ability to engage with a service related to the fit between client need and the content, quality, and delivery modality of treatment (26% of statements). There was a view that services should be tailored according to the amount of treatment needed and the presenting problem. The range of treatment needs was extensive and included gaming-focused needs such as enhancing self-efficacy, competency and skill development in limiting or reducing gaming. Treatment needs also included co-morbidities such as addiction (cannabis and alcohol) as well as depression and anxiety. Other areas requiring assistance included sleep and stress management, social skills, and time management. The perceived quality of the treatment and relationship with the provider was perceived as important. This focused on the development of rapport through unconditional positive regard with a general empathic and non-judgemental approach. Participants also preferred treatment providers to understand gaming as well as the wider context of gaming culture (e.g., social norms).

Service system components

Figure 2 depicts the five components of an accessible health care system response. The approachability of services related to the importance of information on gaming problems, screening tools and the provision of service information. There was a need for evidence-based information on the nature and risk of gaming problems. This information would be ideally supported by valid and reliable screening tools that can be self-administered or integrated into various early intervention and treatment phases. Participants expressed confusion and uncertainty as to whether they really had a problem, indicating a need for clear feedback on problem severity and prognosis, especially for those experiencing lower levels of severity. While there are currently few community-based treatment options, participants indicated a need for clear service information that could guide decisions about service options based on level of severity (mild to severe problems) as well as modality of delivery (e.g., online, self-help, in-person).

Fig. 2
figure 2

Key components of a person-centred approach to early intervention, and treatment of gaming problems

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Acceptability of services involved themes of responsivity and specificity, and values of partnership and mutual respect. Participants expressed a need for high quality specialist gaming services that have in-depth knowledge of gaming and its prevention and treatment. Responsive services would value taking preventive action or treatment-seeking and promote this as a normal and reasonable response to gaming issues. Gaming support, resources and services should be established for adolescent and adult gamers and avoid a ‘one-size-fits-most/all’ approach. Clinical staff should be experienced in working with young people and have relevant gaming knowledge.

The availability of services related to flexible access and location of the provider. Participants expressed a need for a multi-modal system that supported online, text messaging, smartphone, and in-person treatment accessible through self-help, individual and group-based formats. Participants said services should be available after-hours including evenings and weekends as well as located in or near health care centres or universities. Where travel was required, services should be able to be accessed via public transport and ideally located in each major centre. The affordability of in-person services was proposed to be income-based and should represent value for money. Service costs were proposed as ranging from $20 upwards depending on private or public funding.

Services should be appropriate to meet the needs of a potentially heterogeneous group of gamers and their family. To be appropriate, a person-centred approach should include valid and reliable screening tools that can inform early intervention and treatment plans and the selection of modality and intensity of treatment. This means supporting a transition between service types and intensity whereby individuals are able to alter care plans and arrangements as required (akin to a stepped care approach). Co-locating treatment within mental health services would ensure that co-morbidities are addressed, however there should also be an option whereby the treatment is primarily focused on gaming-specific issues. The workforce should have an in-depth knowledge of gaming and addictions including gaming culture (e.g., not letting your friends down) and potential comorbidities (e.g., anxiety). Participants were positive towards talking with other people with lived experience in terms of understanding how they regained control over their gaming. Identified clinical approaches included the delivery of urge management, relapse prevention and psychosocial rehabilitation via replacement activities. Services should be routinely assessed for quality and compliance with standards with these evaluations available to all clients.

Discussion

The aim of this study was to understand the health care needs of individuals with gaming problems. We applied a person-centred framework for conceptualising the components of a support system for the identification, early intervention and treatment of gaming problems. Gamers’ perceptions and experiences reflected the components of the framework in terms of facilitators and barriers to the ability to perceive, seek, reach, pay and engage with treatment. This approach identified critical issues in healthcare for gaming problems that also arise across the spectrum of addictive disorders (e.g., barriers to help seeking such as shame, stigma and health beliefs around the seriousness and susceptibility of having a problem) as well as use of health care more broadly (being able to navigate, locate and reach the right type of support at the right time). The second aim was to identify the components of a healthcare system informed by the framework while accounting for participant expectations and needs. Critical discussion of this system included the need for multi-modal options that catered for mild to severe gaming problems. It also flagged the usefulness of transdiagnostic treatments that could address a range of comorbidities including mood disorders, substance use, relationship difficulties, social skills and adaptive functioning.

Gaps in health care identified in this study related to the adequacy of screening and assessment, access to evidence-based treatment and routine outcome monitoring. Screening and assessment has been identified as a major problem in gaming research that has a direct impact on service ability to provide valid and reliable feedback to gamers [24, 60]. Inconsistencies in definitions and screening are a barrier to offering the right treatment that matches client need and preferences. In terms of access to evidence-based treatment, there are very few options for those with less severe problems. Promising work is being conducted in the area of structured cognitive behavioural therapy programs [37, 61]. However, there are currently few RCTs for gaming problems suggesting that the development of an evidence-based treatment model is some way in the future [37, 61].

Some participants expressed uncertainty about the legitimacy of in-person help for gaming problems. Sixteen of twenty participants in our study met the cut-off for gaming problems inclusive of five who reported more serious problems. This meant the majority of our help-seeking participants who accessed a brief self-help intervention [53] were not experiencing severe problems which required in-person treatment. These finding are in part consistent with the broader issue of the concept of problem gaming and that few people with these issues seek in-person help [2, 11,12,13,14,15,16,17,18,19]. It highlights the need to develop a diverse range of early intervention and support options. Studies also indicate gamers engage with a broad range of self-managed cognitive and behavioural strategies to limit their gaming [62] and are able to adhere to personal change goals [63]. The current study highlights the need to consider a stepped care service system that is inclusive of low-severity (e.g., brief interventions such as personalised normative feedback) and low-intensity service options (e.g., self-directed treatments) as well as options that are more intensive (e.g., in-person and group treatment).

A limitation of the field is the absence of quality information on people across the continuum of severity, including case reports and clinical data. To address this problem, early intervention and treatment should include routine outcome monitoring which tracks the scope of the problem, patterns of use, and responsivity to different approaches to reducing gaming problems [64]. Ideally, routine outcome monitoring is informed by international consensus on a minimum dataset with a set of recommendations for clinical outcomes (for early intervention and treatment) and process measures. In particular, there is a need to better understand how problematic gaming may intersect with issues of comorbidity, such as mood disorders, and how such considerations may influence case formulation and treatment planning. Less is known about the efficacy of structured treatments for gaming problems, including psychological and pharmacological treatment, in the context of other mental disorders, because such issues are often excluded from trials and other intervention studies.

This is the first study to consider the optimal components of a service system for gaming problems from a holistic perspective but this work had several limitations. First, the study involved a self-selected sample of help-seeking adults who provided qualitative data. Qualitative studies are not intended to be generalisable and in the current study data were analysed to identify patterns in help-seeking preferences and experiences. These patterns were mapped onto an established model outlining the potential components of a comprehensive health care system. Future research should identify the relevance, applicability and generalisability of these findings using quantitative methodologies as well as consensus-based approaches to responding to gaming problems. Second, we believe that the model reflects the wide range of issues that need to be considered when establishing a co-ordinated clinical response to gaming problems. However, the nature of the sample means there would be additional country specific needs that should be incorporated (e.g., cultural considerations). Finally, participants in this study were motivated to change their gaming behaviour and were in the process of seeking help. Future research should examine the perspective of gamers across the continuum including those that have a problem but do not want to change as well as those who have lived experience of a range of different treatment services.

Conclusions

A comprehensive health care approach for gaming problems is currently in its infancy and there are numerous access and delivery issues for support and access that are still to be resolved. A challenge that has received relatively less attention has been the issue of treating gaming problems and its comorbid disorders. Our findings are consistent with lessons from the gambling field that suggest treatment approaches need to be tailored according to readiness to change [65] and specific needs such as co-occurring issues. The pathways model of problem gambling outlines three different profiles of gamblers: (i) behaviourally conditioned, (ii) emotionally vulnerable, (iii) impulsive/anti-social [66]. The model recommends treatment is matched accordingly whereby those who are behaviourally conditioned may benefit from less intensive brief interventions. In comparison, those who present with comorbidities such as mood disorders would likely benefit from more intensive treatment that covers a range of different presenting issues. The proposed model in the current study is consistent with this approach in terms of recommending a range of different service options that are tailored to the needs of individuals. Currently, health care systems for gaming problems lack a stepped care approach whereby a gamer can transition between levels of treatment as needed [24].

The current study has identified issues associated with the establishment of a service system for gaming problems. A key issue with establishing a service system is the identification of an appropriate workforce who has the skills and expertise to administer the range of different service responses. Future research might identify existing capacity and how it aligns with the expertise identified in the current study.

Availability of data and materials

The datasets and materials used and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

ICD-11:

International Classification of Diseases

CBT:

Cognitive and Behavioural Therapy

GAS:

Gaming Addiction Scale

References

  1. Ferguson CJ, Coulson M, Barnett J. A meta-analysis of pathological gaming prevalence and comorbidity with mental health, academic and social problems. J Psychiatr Res. 2011;45(12):1573–8. https://doi.org/10.1016/j.jpsychires.2011.09.005.

    Article  PubMed  Google Scholar 

  2. Przybylski AK, Weinstein N, Murayama K. Internet gaming disorder: investigating the clinical relevance of a new phenomenon. Am J Psychiatr. 2017;174(3):230–6. https://doi.org/10.1176/appi.ajp.2016.16020224.

    Article  PubMed  Google Scholar 

  3. Mihara S, Higuchi S. Cross-sectional and longitudinal epidemiological studies of I nternet gaming disorder: a systematic review of the literature. Psychiatry Clin Neurosci. 2017;71(7):425–44. https://doi.org/10.1111/pcn.12532.

    Article  PubMed  Google Scholar 

  4. Stevens MW, Dorstyn D, Delfabbro PH, King DL. Global prevalence of gaming disorder: a systematic review and meta-analysis. Aust N Z J Psychiatry. 2020. https://doi.org/10.1177/0004867420962851.

  5. Saunders JB, Hao W, Long J, King DL, Mann K, Fauth-Bühler M, et al. Gaming disorder: its delineation as an important condition for diagnosis, management, and prevention. J Behav Addict. 2017;6(3):271–9. https://doi.org/10.1556/2006.6.2017.039.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Petry NM, Rehbein F, Gentile DA, Lemmens JS, Rumpf HJ, Mößle T, et al. An international consensus for assessing internet gaming disorder using the new DSM-5 approach. Addiction. 2014;109(9):1399–406. https://doi.org/10.1111/add.12457.

    Article  PubMed  Google Scholar 

  7. Long J, Liu T, Liu Y, Hao W, Maurage P, Billieux J. Prevalence and correlates of problematic online gaming: a systematic review of the evidence published in Chinese. Curr Addict Rep. 2018;5(3):359–71. https://doi.org/10.1007/s40429-018-0219-6.

    Article  Google Scholar 

  8. Andreassen CS, Billieux J, Griffiths MD, Kuss DJ, Demetrovics Z, Mazzoni E, et al. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychol Addict Behav. 2016;30(2):252–62. https://doi.org/10.1037/adb0000160.

    Article  Google Scholar 

  9. Wang HR, Cho H, Kim D-J. Prevalence and correlates of comorbid depression in a nonclinical online sample with DSM-5 internet gaming disorder. J Affect Disord. 2018;226:1–5. https://doi.org/10.1016/j.jad.2017.08.005.

    Article  CAS  PubMed  Google Scholar 

  10. World Health Organisation. 6C51 Gaming Disorder. Retrieved online: https://icd.who.int/browse11/l-m/en#/http://id.who.int/icd/entity/1448597234.2019.

  11. Aarseth E, Bean AM, Boonen H, Colder Carras M, Coulson M, Das D, et al. Scholars’ open debate paper on the World Health Organization ICD-11 gaming disorder proposal. J Behav Addict. 2017;6(3):267–70. https://doi.org/10.1556/2006.5.2016.088.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Billieux J, Flayelle M, Rumpf H-J, Stein DJ. High involvement versus pathological involvement in video games: a crucial distinction for ensuring the validity and utility of gaming disorder. Curr Addict Rep. 2019;6(3):323–30. https://doi.org/10.1007/s40429-019-00259-x.

    Article  Google Scholar 

  13. Dullur P, Starcevic V. Internet gaming disorder does not qualify as a mental disorder. Aust N Z J Psychiatry. 2018;52(2):110–1. https://doi.org/10.1177/0004867417741554.

    Article  PubMed  Google Scholar 

  14. Higuchi S, Nakayama H, Mihara S, Maezono M, Kitayuguchi T, Hashimoto T. Inclusion of gaming disorder criteria in ICD-11: a clinical perspective in favor: commentary on: scholars’ open debate paper on the World Health Organization ICD-11 gaming disorder proposal (Aarseth et al.). J Behav Addict. 2017;6(3):293–5. https://doi.org/10.1556/2006.6.2017.049.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kardefelt-Winther D. A critical account of DSM-5 criteria for internet gaming disorder. Addict Res Theory. 2015;23(2):93–8. https://doi.org/10.3109/16066359.2014.935350.

    Article  Google Scholar 

  16. Kardefelt-Winther D. Conceptualizing I nternet use disorders: A ddiction or coping process? Psychiatry Clin Neurosci. 2017;71(7):459–66. https://doi.org/10.1111/pcn.12413.

    Article  PubMed  Google Scholar 

  17. King DL, Delfabbro PH, Potenza MN, Demetrovics Z, Billieux J, Brand M. Internet gaming disorder should qualify as a mental disorder. Aust N Z J Psychiatry. 2018;52(7):615–7. https://doi.org/10.1177/0004867418771189.

    Article  PubMed  Google Scholar 

  18. Rumpf H-J, Achab S, Billieux J, Bowden-Jones H, Carragher N, Demetrovics Z, et al. Including gaming disorder in the ICD-11: the need to do so from a clinical and public health perspective: commentary on: a weak scientific basis for gaming disorder: let us err on the side of caution (van Rooij et al., 2018). J Behav Addict. 2018;7(3):556–61. https://doi.org/10.1556/2006.7.2018.59.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Van Rooij AJ, Ferguson CJ, Colder Carras M, Kardefelt-Winther D, Shi J, Aarseth E, Bean AM, Bergmark KH, Brus A, Coulson M, Deleuze J. A weak scientific basis for gaming disorder: Let us err on the side of caution. J Behav Addict. 2018;7(1):1–9.

  20. Muller KW, Beutel ME, Wolfling K. Decreased occupational functioning and increased physical health complaints in treatment seekers with internet-related disorders: compared to patients with gambling disorder. Eur Addict Res. 2019;25(5):229–37. https://doi.org/10.1159/000500543.

    Article  PubMed  Google Scholar 

  21. King DL, Delfabbro PH. Prevention and policy related to internet gaming disorder. Curr Addict Rep. 2017;4(3):284–92. https://doi.org/10.1007/s40429-017-0157-8.

    Article  Google Scholar 

  22. Vondráčková P, Gabrhelik R. Prevention of internet addiction: a systematic review. J Behav Addict. 2016;5(4):568–79. https://doi.org/10.1556/2006.5.2016.085.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Xiang YT, Jin Y, Zhang L, Li L, Ungvari GS, Ng CH, Zhao M, Hao W. An overview of the expert consensus on the prevention and treatment of gaming disorder in China (2019 Edition). Neurosci Bull. 2020;36(7):825–8.

  24. Rumpf H-J, Bischof A, Bischof G, Besser B, Brand D, Rehbein F. Early intervention in gaming disorder: what can we learn from findings in the substance abuse field? Curr Addict Rep. 2018;5(4):511–6. https://doi.org/10.1007/s40429-018-0229-4.

    Article  Google Scholar 

  25. King DL, Delfabbro PH, Wu AM, Doh YY, Kuss DJ, Pallesen S, et al. Treatment of internet gaming disorder: an international systematic review and CONSORT evaluation. Clin Psychol Rev. 2017;54:123–33. https://doi.org/10.1016/j.cpr.2017.04.002.

    Article  PubMed  Google Scholar 

  26. Zajac K, Ginley MK, Chang R. Treatments of internet gaming disorder: a systematic review of the evidence. Expert Rev Neurother. 2020;20(1):85–93. https://doi.org/10.1080/14737175.2020.1671824.

    Article  CAS  PubMed  Google Scholar 

  27. Zajac K, Ginley MK, Chang R, Petry NM. Treatments for internet gaming disorder and internet addiction: a systematic review. Psychol Addict Behav. 2017;31(8):979–94. https://doi.org/10.1037/adb0000315.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kuss DJ, Lopez-Fernandez O. Internet addiction and problematic internet use: a systematic review of clinical research. World J Psychiatry. 2016;6(1):143–76. https://doi.org/10.5498/wjp.v6.i1.143.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Shek DT, Yu L. Longitudinal impact of the project PATHS on adolescent risk behavior: what happened after five years? Sci World J. 2012;2012:316029.

    Google Scholar 

  30. Yeun YR, Han SJ. Effects of psychosocial interventions for school-aged children's internet addiction, self-control and self-esteem: meta-analysis. Healthc Inform Res. 2016;22(3):217–30. https://doi.org/10.4258/hir.2016.22.3.217.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Wang Q, Ren H, Long J, Liu Y, Liu T. Research progress and debates on gaming disorder. Gen Psychiatry. 2019;32(3):1–6.

  32. King DL, Delfabbro PH, Doh YY, Wu AM, Kuss DJ, Pallesen S, et al. Policy and prevention approaches for disordered and hazardous gaming and internet use: an international perspective. Prev Sci. 2018;19(2):233–49. https://doi.org/10.1007/s11121-017-0813-1.

    Article  PubMed  Google Scholar 

  33. Davies B, Blake E. Evaluating existing strategies to limit video game playing time. IEEE Comput Graph Appl. 2016;36(2):47–57. https://doi.org/10.1109/MCG.2016.25.

    Article  PubMed  Google Scholar 

  34. Király O, Griffiths MD, King DL, Lee H-K, Lee S-Y, Banyai F, et al. Policy responses to problematic video game use: a systematic review of current measures and future possibilities. J Behav Addict. 2018;7(3):503–17. https://doi.org/10.1556/2006.6.2017.050.

    Article  PubMed  Google Scholar 

  35. Stevens MW, King DL, Dorstyn D, Delfabbro PH. Cognitive–behavioral therapy for internet gaming disorder: a systematic review and meta-analysis. Clin Psychol Psychother. 2019;26(2):191–203. https://doi.org/10.1002/cpp.2341.

    Article  PubMed  Google Scholar 

  36. Costa S, Kuss D. Clinical practices for gaming disorders: a systematic review. Front Psychol. 2019;10:578. https://doi.org/10.3389/fpsyg.2019.00578.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Wölfling K, Müller KW, Dreier M, Ruckes C, Deuster O, Batra A, et al. Efficacy of short-term treatment of internet and computer game addiction: a randomized clinical trial. JAMA Psychiatry. 2019;76(10):1018–25. https://doi.org/10.1001/jamapsychiatry.2019.1676.

    Article  PubMed  PubMed Central  Google Scholar 

  38. King DL, Billieux J, Carragher N, Delfabbro PH. Face validity evaluation of screening tools for gaming disorder: scope, language, and overpathologizing issues. J Behav Addict. 2020;9(1):1–13. https://doi.org/10.1556/2006.2020.00001.

    Article  PubMed  Google Scholar 

  39. King DL, Chamberlain SR, Carragher N, Billieux J, Stein D, Mueller K, et al. Screening and assessment tools for gaming disorder: a comprehensive systematic review. Clin Psychol Rev. 2020;77:101831. https://doi.org/10.1016/j.cpr.2020.101831.

    Article  PubMed  Google Scholar 

  40. Feng W, Ramo D, Chan S, Bourgeois J. Internet gaming disorder: trends in prevalence 1998–2016. Addict Behav. 2017;75:17–24. https://doi.org/10.1016/j.addbeh.2017.06.010.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Thege BK, Woodin EM, Hodgins DC, Williams RJ. Natural course of behavioral addictions: a 5-year longitudinal study. BMC Psychiatry. 2015;15(1):4. https://doi.org/10.1186/s12888-015-0383-3.

    Article  Google Scholar 

  42. Grant BF, Goldstein RB, Saha TD, Chou SP, Jung J, Zhang H, et al. Epidemiology of DSM-5 alcohol use disorder: results from the National Epidemiologic Survey on alcohol and related conditions III. JAMA Psychiatry. 2015;72(8):757–66. https://doi.org/10.1001/jamapsychiatry.2015.0584.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Yeh Y-C, Wang P-W, Huang M-F, Lin P-C, Chen C-S, Ko C-H. The procrastination of internet gaming disorder in young adults: the clinical severity. Psychiatry Res. 2017;254:258–62. https://doi.org/10.1016/j.psychres.2017.04.055.

    Article  PubMed  Google Scholar 

  44. Müller KW, Beutel M, Egloff B, Wölfling K. Investigating risk factors for internet gaming disorder: a comparison of patients with addictive gaming, pathological gamblers and healthy controls regarding the big five personality traits. Eur Addict Res. 2014;20(3):129–36. https://doi.org/10.1159/000355832.

    Article  PubMed  Google Scholar 

  45. Lee YS, Son JH, Park JH, Kim SM, Kee BS, Han DH. The comparison of temperament and character between patients with internet gaming disorder and those with alcohol dependence. J Ment Health. 2017;26(3):242–7. https://doi.org/10.1080/09638237.2016.1276530.

    Article  PubMed  Google Scholar 

  46. Burleigh TL, Griffiths MD, Sumich A, Stavropoulos V, Kuss DJ. A systematic review of the co-occurrence of gaming disorder and other potentially addictive behaviors. Curr Addict Rep. 2019;6(4):383–401. https://doi.org/10.1007/s40429-019-00279-7.

    Article  Google Scholar 

  47. King DL, Adair C, Saunders JB, Delfabbro PH. Clinical predictors of gaming abstinence in help-seeking adult problematic gamers. Psychiatry Res. 2018;261:581–8. https://doi.org/10.1016/j.psychres.2018.01.008.

    Article  PubMed  Google Scholar 

  48. Lemmens JS, Valkenburg PM, Peter J. Psychosocial causes and consequences of pathological gaming. Comput Hum Behav. 2011;27(1):144–52. https://doi.org/10.1016/j.chb.2010.07.015.

    Article  Google Scholar 

  49. Lau C, Stewart SL, Sarmiento C, Saklofske DH, Tremblay PF. Who is at risk for problematic video gaming? Risk factors in problematic video gaming in clinically referred Canadian children and adolescents. Multimodal Technol Interact. 2018;2(2):19. https://doi.org/10.3390/mti2020019.

    Article  Google Scholar 

  50. Drummond A, Sauer JD, Ferguson CJ, Hall LC. The relationship between problem gambling, excessive gaming, psychological distress and spending on loot boxes in Aotearoa New Zealand, Australia, and the United States—a cross-national survey. PLoS One. 2020;15(3):e0230378. https://doi.org/10.1371/journal.pone.0230378.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Keough B. Video game addicts seek help from gambling foundation as most health board don’t provide treatment. 2018. Available from: https://www.stuff.co.nz/national/health/109179959/video-game-addicts-seek-help-from-gambling-foundation-as-most-health-boards-dont-provide-treatment.

    Google Scholar 

  52. Dullur P, Hay P. Problem internet use and internet gaming disorder: a survey of health literacy among psychiatrists from Australia and New Zealand. Australas Psychiatry. 2017;25(2):140–5. https://doi.org/10.1177/1039856216684714.

    Article  PubMed  Google Scholar 

  53. Park JJ, Booth N, Bagot KL, Rodda SN. A brief internet-delivered intervention for the reduction of gaming-related harm: a feasibility study. Comput Hum Behav Rep. 2020;2:100027. https://doi.org/10.1016/j.chbr.2020.100027.

    Article  Google Scholar 

  54. Lemmens JS, Valkenburg PM, Peter J. Development and validation of a game addiction scale for adolescents. Media Psychol. 2009;12(1):77–95. https://doi.org/10.1080/15213260802669458.

    Article  Google Scholar 

  55. Weinstock J, Whelan JP, Meyers AW. Behavioral assessment of gambling: an application of the timeline followback method. Psychol Assess. 2004;16(1):72–80. https://doi.org/10.1037/1040-3590.16.1.72.

    Article  PubMed  Google Scholar 

  56. Sobell LC, Sobell MB. Timeline follow-Back. In: Litten R, Allen J, editors. Measuring alcohol consumption: psychosocial and biochemical methods. 1st ed. New Jersey: Humana Press; 1992. p. 41–72.

  57. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand S-L, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32(6):959–76. https://doi.org/10.1017/S0033291702006074.

    Article  CAS  PubMed  Google Scholar 

  58. Levesque J-F, Harris MF, Russell G. Patient-centred access to health care: conceptualising access at the interface of health systems and populations. Int J Equity Health. 2013;12(1):18.

    Article  Google Scholar 

  59. Hsieh H-F, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88. https://doi.org/10.1177/1049732305276687.

    Article  PubMed  Google Scholar 

  60. King DL, Haagsma MC, Delfabbro PH, Gradisar M, Griffiths MD. Toward a consensus definition of pathological video-gaming: a systematic review of psychometric assessment tools. Clin Psychol Rev. 2013;33(3):331–42. https://doi.org/10.1016/j.cpr.2013.01.002.

    Article  PubMed  Google Scholar 

  61. Kim SM, Han DH, Lee YS, Renshaw PF. Combined cognitive behavioral therapy and bupropion for the treatment of problematic on-line game play in adolescents with major depressive disorder. Comput Hum Behav. 2012;28(5):1954–9.

    Article  Google Scholar 

  62. Rodda SN, Booth N, Vacaru M, Knaebe B, Hodgins DC. Behaviour change strategies for internet, pornography and gaming addiction: a taxonomy and content analysis of professional and consumer websites. Comput Hum Behav. 2018;84:467–76. https://doi.org/10.1016/j.chb.2018.03.021.

    Article  Google Scholar 

  63. King DL, Kaptsis D, Delfabbro PH, Gradisar M. Craving for internet games? Withdrawal symptoms from an 84-h abstinence from massively multiplayer online gaming. Comput Hum Behav. 2016;62:488–94. https://doi.org/10.1016/j.chb.2016.04.020.

    Article  Google Scholar 

  64. King DL, Delfabbro PH. Internet gaming disorder treatment: a review of definitions of diagnosis and treatment outcome. J Clin Psychol. 2014;70(10):942–55. https://doi.org/10.1002/jclp.22097.

    Article  PubMed  Google Scholar 

  65. Rodda SN, Lubman DI, Iyer R, Gao CX, Dowling NA. Subtyping based on readiness and confidence: the identification of help-seeking profiles for gamblers accessing web-based counselling. Addiction. 2015;110(3):494–501.

    Article  CAS  Google Scholar 

  66. Blaszczynski A, Nower L. A pathways model of problem and pathological gambling. Addiction. 2002;97(5):487–99. https://doi.org/10.1046/j.1360-0443.2002.00015.x.

    Article  PubMed  Google Scholar 

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Acknowledgements

We would like to thank the Change Strategies Project team for their assistance with the recruitment of participants.

Funding

This research was undertaken as part of a Health Research Council early career grant awarded to the senior author (17/548). Additional funding for participant recruitment and remuneration was provided by Internet NZ. The funders had no role in the design or conduct of the study or decision to publish the findings.

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Authors and Affiliations

  1. School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand

    Jennifer J. Park, Laura Wilkinson-Meyers & Simone N. Rodda

  2. College of Education, Psychology, & Social Work, Flinders University, GPO Box 2100, Adelaide, South Australia, 5001, Australia

    Daniel L. King

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Contributions

Author SR designed the study and sought the funding. Author JP conducted literature searches and prepared the first draft of the manuscript. Author JP and SR conducted the initial analysis with LW and DK advising on the interpretation of data. DK made substantial contribution to draft revisions. JP, LW, DK and SR contributed to and have approved the final manuscript.

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Correspondence to Simone N. Rodda.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The research was approved by the University of Auckland Human Participants Ethics Committee (022614). Online informed consent was obtained from all participants after reviewing the study purpose and aims.

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Park, J.J., Wilkinson-Meyers, L., King, D.L. et al. Person-centred interventions for problem gaming: a stepped care approach. BMC Public Health 21, 872 (2021). https://doi.org/10.1186/s12889-021-10749-1

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