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Language of change in online narratives of recovery from disordered gaming

Scientific Reports, 2026

Spyridon Kavvadias, Bruno Schivinski, Nalin Arachchilage, Taylor Brown, Vasileios Stavropoulos

Scientific Reports, volume 16, article 3936, 14 January 2026

  • Open access
  • 22,459 Reddit posts and comments
  • r/StopGaming
  • Topic modelling (LDA)
  • Transtheoretical model of change
  • Netnography
Read the article
Keywords
  • gaming disorder
  • Reddit
  • transtheoretical model of change
  • topic modeling
  • netnography
  • disordered gaming
  • recovery
  • stages of change
  • relapse
  • online peer support
  • online self-help community
  • r/StopGaming
  • latent Dirichlet allocation
  • natural language processing
  • sentiment analysis
  • VADER
  • NRC Emotion Lexicon
  • reflexive thematic analysis
  • gamification
  • motivational interviewing
  • digital mental health

People trying to quit problem gaming do not move neatly from one stage of change to the next. In 22,459 posts and comments from Reddit’s r/StopGaming community, their stories mixed ambivalence, relapse and renewed effort, with a mostly hopeful tone, and many members filled the gap left by gaming with exercise, hobbies and game-like goal tracking.

Key findings

  1. Seven themes run through recovery stories. A seven-topic model fitted the posts best (perplexity 945; coherence 0.298), and the qualitative analysis found seven recurring themes: escapism, guilt and regret over lost time, relationship strain, identity and self-worth, health deterioration, a desire for moderation, and replacement activities (Kavvadias et al., 2026).
  2. Recovery is fluid and cyclical, not a straight line. The topics did not lock onto single stages of the transtheoretical model of change: each spanned several stages, and users who posted over several years moved through action, relapse and renewed effort before sustained maintenance (Kavvadias et al., 2026).
  3. The community’s tone is mostly hopeful. Average sentiment was moderately positive (VADER mean 0.35), positive words outnumbered negative ones (0.41 vs 0.32), and anticipation (0.22) and trust (0.21) were the most frequent emotions, ahead of fear and sadness (0.13 each) (Kavvadias et al., 2026).
  4. Filling the void after quitting is central. Members replaced gaming with physical activity, creative hobbies, learning, social connection, daily routines, mindfulness and value-driven work, and many turned game mechanics such as quests and experience points into tools for structuring change (Kavvadias et al., 2026).

At a glance

Design
Netnography of Reddit’s r/StopGaming self-help community: computational topic modelling combined with reflexive thematic analysis, checked against sentiment, emotion and engagement metrics
Data
28,409 posts and comments collected through the Reddit API (24 November 2013 to 31 July 2025); after removing 688 duplicate posts and 5,262 entries from deleted accounts, 22,459 texts (1,963 posts and 20,496 comments) by 7,135 users
Topics (RQ1)
Latent Dirichlet allocation (Python, Gensim) on 1,587 posts after preprocessing; 42 models compared; best model: seven topics
Stages of change (RQ2)
70 posts (the 10 most representative of each topic, May 2020 to July 2025) coded by two researchers and mapped to the stages of the transtheoretical model of change
Validation
VADER sentiment, NRC Emotion Lexicon, NRC valence–arousal–dominance lexicon, and engagement (post scores, comments per post)
Ethics
Approved by the RMIT University Human Research Ethics Committee (2025-28502-27067); public data only, de-identified before analysis

Figure 1. Emotional tone of r/StopGaming posts

Emotions (NRC Emotion Lexicon)Word polarity (NRC)00.10.2AnticipationAnticipation: 0.220.22TrustTrust: 0.210.21JoyJoy: 0.170.17FearFear: 0.130.13SadnessSadness: 0.130.13AngerAnger: 0.110.11DisgustDisgust: 0.090.09SurpriseSurprise: 0.060.0600.20.4Positive wordsPositive words: 0.410.41Negative wordsNegative words: 0.320.32Positive emotion or polarityNegative emotion or polaritySurprise (neither)Overall sentiment (VADER, −1 to +1):mean 0.35, median 0.60Valence 0.20, arousal −0.03,dominance 0.06 (NRC VAD lexicon)Average proportion of emotion words per post across all topics, as printed in Figures 4 and 5 and the Results of the article.Posts from Reddit's r/StopGaming community; the lexicons count emotion-related words, not the writers' clinical state.
Redrawn from the averages printed in Figures 4 and 5 and the Results of the article.

Share of posts by topic (seven-topic model)

Replacement activities (6)43.7%Guilt and lost time (1)17.0%Relationship strain (2)11.3%Escapism and stress coping (0)10.1%Desire for moderation (5)8.6%Health deterioration (4)4.8%Identity and self-worth (3)4.5%
Prevalence of each topic in the refined corpus of 1,587 posts, from Table 5 of the article; topic labels from Table 9.

Tables

Table 4. LDA models compared by topic count and fit indices

Model Topics α β Perplexity Coherence
1 7 Symmetric Auto 945 0.2980
2 10 Symmetric Auto 1032 0.2839
3 12 Symmetric Auto 1149 0.2868
4 15 Symmetric Auto 1254 0.2748
5 20 Symmetric Auto 1467 0.2753

α = document–topic prior; β = topic–word prior (“eta” in Gensim); “auto” = learned during training. Lower perplexity and higher coherence are better; Model 1 was selected.

Table 5. Topic prevalence, engagement and key terms (optimum model)

Topic Prevalence (%) Mean score Mean comments per post Key terms
0 10.08 81.05 15.89 year, life, hour, play, would, job, never, played, playing, day, anything, back, addicted, cant, could
1 16.95 59.34 13.87 play, playing, life, hour, thing, year, every, without, really, real, make, stop, day, quit, going
2 11.34 81.81 18.52 playing, play, better, life, thing, back, year, hour, would, world, maybe, cant, well, way, point
3 4.54 69.40 11.67 quit, never, year, back, league, friend, keep, addiction, life, sure, playing, sell, console, hour, stopped
4 4.79 78.54 19.25 friend, he, mother, hour, year, thing, really, doesnt, life, stop, would, play, money, back, long
5 8.57 44.79 10.90 really, quit, since, day, would, month, bad, craving, hour, play, playing, steam, today, shit, may
6 43.73 66.03 16.57 life, addiction, would, got, school, started, year, play, friend, way, went, new, first, fun, week

Prevalence = share of the refined corpus of posts; mean score = upvotes minus downvotes. Key terms as printed. The article’s exemplar posts are not reproduced here.

Table 6. Themes, definitions and links to the stages of change

Theme Short definition Posts (N) Topic with most posts Stages of change
1. Escapism through gaming Using games to avoid real-life stress or anxiety 48 Topic 0 Maintenance/relapse
2. Guilt and regret over lost time Feeling remorse for hours or years wasted gaming 42 Topic 1 Action/early maintenance
3. Impact on relationships Gaming harmed friendships, dating, marriage 32 Topic 2 Precontemplation/contemplation
4. Identity and self-worth problems Tying self-esteem or identity to gaming performance 29 Topic 6 Action/maintenance
5. Health and lifestyle deterioration Poor sleep, nutrition, hygiene or exercise habits 27 Topic 0 Preparation/action
6. Desire for moderation Wanting to play “sometimes” without relapse (self-control) 18 Topic 5 Maintenance (with relapse risk)
7. Replacement activities and “filling the void” Seeking new hobbies to replace gaming time 24 Topic 5 Action/maintenance

Values as printed. Topic numbers follow the article’s Table 6, which differs from the topic labels in its Table 9 (identity = Topic 3, health = Topic 4, replacement activities = Topic 6). The illustrative comments are not reproduced here.

Table 7. Key gaming-replacement activities

Category Specific activities and approaches
Physical activity Gym, running, calisthenics, yoga, martial arts, daily walks, cycling
Creative hobbies Drawing, painting, music (instruments, singing), writing, coding (non-gaming), cooking, crafting, sewing
Learning and education Studying (formal or informal), languages, instrument practice, reading books, podcasts, Rubik’s cube solving
Social connection Spending more time with family and friends, volunteering, joining clubs, support groups (in person or virtual)
Daily structure and chores Journaling, daily scheduling (Google Calendar, Coach.me, whiteboard), chores, cooking, housework, errands
Mindfulness and well-being Meditation, therapy, self-reflection, mindfulness exercises, walks in nature
Activism and value-driven work Environmental activism, political engagement, volunteering, meaningful work

Example quotes from the article’s table are not reproduced here.

Table 8. Thematic and linguistic markers by stage of change
Stage Interpretative commentary
Precontemplation Marked by a lack of awareness or denial of the problem. Narratives often reflect concerns raised by others, like family or partners, rather than the users themselves.
Contemplation Users acknowledge the problem and express significant internal conflict. Narratives often show an ambivalence between recognizing the harm caused by gaming and feeling uncertain about changing.
Preparation Characterized by active planning and readiness to change. Posts often share intentions to quit or moderate, alongside requests for strategies and support from the community.
Action Deliberate efforts to change behavior, such as reducing or ceasing gaming. These narratives may also describe the struggles and emotional challenges accompanying these changes.
Maintenance Users strive to sustain their behavioral changes and avoid relapse. Narratives often discuss ongoing challenges like cravings and social pressures, but are grounded in a commitment to long-term change.
Relapse Setbacks and a return to gaming. These narratives are often marked by feelings of guilt, frustration, and a desire to recommit to recovery.
Termination Full disengagement from problematic gaming. Posts often reflect the development of a new identity and a sense of liberation from the old habit.

Commentary from the article’s Table 8; the example quotes are not reproduced here.

Table 9. Per-topic sentiment, emotion and engagement
Topic Primary stage Mean score Mean comments VADER NRC+ NRC− Anger Anticipation Disgust Fear Joy Sadness Surprise Trust Valence Arousal Dominance
0 Escapism/stress coping Maintenance/relapse 81.05 15.89 0.23 0.37 0.31 0.10 0.21 0.10 0.11 0.17 0.13 0.07 0.16 0.16 −0.03 −0.01
1 Guilt and lost time Contemplation/relapse 59.34 13.87 0.32 0.37 0.34 0.13 0.24 0.10 0.14 0.15 0.15 0.04 0.23 0.19 −0.01 0.03
2 Relationship strain Precontemplation/contemplation 81.81 18.52 0.28 0.40 0.34 0.12 0.24 0.09 0.14 0.17 0.15 0.06 0.21 0.19 −0.02 0.04
3 Identity and self-worth Action/maintenance 69.40 11.67 0.28 0.40 0.38 0.07 0.21 0.08 0.09 0.17 0.13 0.07 0.22 0.14 −0.03 −0.03
4 Health deterioration Contemplation/preparation 78.54 19.25 0.23 0.41 0.32 0.11 0.20 0.08 0.12 0.19 0.14 0.06 0.24 0.15 −0.04 −0.01
5 Desire for moderation Maintenance/action 44.79 10.90 0.25 0.36 0.35 0.11 0.31 0.10 0.13 0.18 0.13 0.08 0.21 0.20 −0.04 0.01
6 Replacement activities Contemplation/action/maintenance 66.03 16.57 0.47 0.46 0.32 0.11 0.28 0.09 0.15 0.20 0.15 0.08 0.26 0.20 −0.02 0.05

VADER = compound sentiment (−1 to +1); NRC+ and NRC− = shares of positive and negative words; emotions = proportions (NRC Emotion Lexicon); valence, arousal and dominance from the NRC VAD lexicon. Values as printed.

The question

Most research on disordered gaming relies on surveys and interviews, which rarely capture how people describe their own recovery in their own words. We asked which themes people raise in r/StopGaming, a Reddit community for quitting problem gaming, and how those themes line up with the stages of the transtheoretical model of change.

Implications

Practical implications

Readiness assessments should not rely on rigid stage labels; language-based tools could show where someone is in their change journey in real time. Prevention can promote healthy alternatives such as physical activity, creative hobbies, learning and volunteering; interventions can draw on motivational interviewing and on the goal tracking and self-reward systems that users already adopt; and online peer-support communities could be supported as scalable, low-barrier help.

Theoretical implications

Topics bridged the stages of the transtheoretical model rather than mapping onto single stages, supporting a fluid, cyclical view of change while reinforcing the model’s relevance to disordered gaming. Combining topic modelling with netnography and lexicon-based checks offers a way to read stages of change from naturalistic language at scale.

Limitations and future research

  • No demographic or psychometric information on the Reddit users, which limits subgroup analysis and generalisation.
  • Self-reported narratives may involve selective disclosure, exaggeration or recall bias.
  • One platform and one community (r/StopGaming), so the findings may not transfer to other online groups or offline populations.
  • Future work: richer data with demographic, psychometric and longitudinal measures; more advanced language models (e.g., BERT or fine-tuned large language models); and links between digital traces and clinical outcomes.

Questions this paper answers

What do people talk about when they try to quit gaming?

In r/StopGaming, seven themes recur: escapism, guilt and regret over lost time, strain on relationships, identity and self-worth, health problems, a wish to play in moderation, and finding activities to replace gaming (Kavvadias et al., 2026).

Is recovery from disordered gaming a linear process?

No. Posts mixed stages such as contemplation and relapse, and people who posted over several years cycled through action, relapse and renewed effort before sustained maintenance (Kavvadias et al., 2026).

What do people do instead of gaming when they quit?

Physical activity, creative hobbies, learning, time with family and friends, daily routines and chores, mindfulness and therapy, and value-driven work such as volunteering or activism (Kavvadias et al., 2026).

Can online communities help people quit gaming?

The r/StopGaming community’s language was mostly hopeful and supportive, and members described it as a source of support; the authors see such peer-support communities as scalable, low-barrier help (Kavvadias et al., 2026).

Key concepts

Transtheoretical model of change
A model of intentional behaviour change in stages: precontemplation, contemplation, preparation, action, maintenance, relapse and termination (Prochaska & DiClemente).
Latent Dirichlet allocation (LDA)
An unsupervised topic model that finds groups of words that tend to occur together across documents and gives each document a mix of topics.
Netnography
A qualitative approach to studying online communities through their naturally occurring posts and interactions (Kozinets).
Disordered gaming
A pattern of gaming that causes significant harm to a person’s daily life, such as study or work, relationships and health.

Open science and materials

How to cite

Kavvadias, S., Schivinski, B., Arachchilage, N., Brown, T., & Stavropoulos, V. (2026). Language of change in online narratives of recovery from disordered gaming. Scientific Reports, 16, Article 3936. https://doi.org/10.1038/s41598-025-33991-8

Open access under a Creative Commons CC BY-NC-ND 4.0 licence.

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