As I learn more about AI and it’s functionalities, I’ve come to realize that there’s something even more important than it’s functions or engagement, it’s also about responsibility. A recent tutorial where we talked about how some of my target audience may be vulnerable people really made me pause and thank about how Jeff could potentially impact users, both positively and negatively. The last thing I want is for my tool to unintentionally cause harm. Jeff is a reflective tool and not a therapeutic tool, and I need to make that distinction clear.
Being Transparent About What Jeff Is (and Isn’t)
One of the steps I’ve taken is making it clear what Jeff is supposed to do. It’s a reflective tool, not therapy, and I’ve added disclaimers to make sure users understand that. It’s there to guide and support, but it’s not a replacement for professional help. This transparency feels really important as people need to know exactly what they’re engaging with.
Safeguards
I’ve also put specific guardrails in place to make sure that Jeff doesn’t bring up emotionally charged or sensitive topics like self-harm, and if a user mentions them, Jeff will redirect them to mental health resources.
Another consideration is preventing users from becoming overly reliant on Jeff. While Jeff’s aim is to support reflection and encourage confidence-building, there is a risk of users seeing it as a crutch rather than a stepping stone. To address this, I’m working to implement features that nudge users towards real-life actions and balance.
For example, during each session, Jeff will keep reminding users that true progress happens offline, and encouraging them to step into the real-world situations to apply what they have rehearsed.
Acknowledgement
I fully acknowledge the ethical considerations inherent in developing a tool like Jeff, which walks a fine line between being a therapeutic tool and not. While my current focus has been on enhancing Jeff’s engagement and functionality, I do recognize that ethical responsibility must also be an important aspect to this development. Moving forward, I intend to dedicate more time and research into AI ethics, including consulting with experts to make sure that I have not made any oversights, and if any, are to be identified and addressed.
This past week, I set out to try and gather feedback from gaming groups I’ve been active in to see how well Jeff resonates with my target audience. Initially, I asked around in my online gaming friend groups and identified two individuals who have ChatGPT Plus access, hoping they would be able to help me give Jeff a spin. Unfortunately, both declined, explaining that they didn’t feel it was relevant to them as they don’t experience difficulties in social interactions offline. This experience highlighted a key limitation of basing Jeff on the GPT platform, as it requires a paid subscription to be able to use my CustomGPT, limiting access to a smaller group of users, and limiting the diversity of feedback I can gather and refining it for a wider audience.
Unplanned Testing Session in Class
To my surprise, I observed an unplanned testing session during a break in one of Richard’s lectures. Two classmates, Iggy (who identifies with the struggle on bridging his online and offline social behaviors) and Ziyi (who plays online games but without the same online-offline persona gap), started playing around with the visualization feature. They seemed to be really entertained, generating multiple visualizations of their archetypes without moving forward to the mental rehearsal phase. I followed up with them afterwards to understand their experience.
Iggy explained that he found the visualization component to be very engaging and “fun,” he kept generating new images to see the different variations Jeff can come up with. He mentioned that even those who don’t face the challenge of struggling with social confidence offline, like Ziyi, might find this feature fun too. I appreciated this piece of feedback, it showed me Jeff’s potential to appeal beyond it’s original purpose. The visualization tool itself seemed to have a strong hook, drawing users in and keeping them engaged.
Some visualizations of Iggy & Ziyi’s archetypes
The Potential Issue of “Stalling” at Visualization
However, this raised a potential issue: while the visualization feature hooks and engages users, it might also stall their progress through the Jeff’s intended purpose. By repeatedly generating new visualizations, users might be less inclined to move on to the more reflective and growth oriented stage of mental rehearsal. This made me realize the importance of structuring Jeff to maintain engagement while still encouraging users to continue past visualization.
Visualization Accuracy Concerns
Ziyi’s feedback also provided some insights, while she thought it was a fun experience, there were some problems that stood out. Since her online and offline archetypes were very similar, as expected, she received identical visualizations for Jeff. However, she felt that the visualizations didn’t fully capture the nuances in how she saw herself and her personality, which is why she went on to generate multiple more images to look for one that felt accurate. Iggy then also pointed out the need for more customization in the visualization phase, such as options for gender, style, or other personal attributes, which could make the archetypes feel more nuanced, accurate, and relatable.
Reflections and Next Steps
One of the main limitations I’m facing is the accessibility barrier due to the reliance on the ChatGPT platform, which requires users to have a ChatGPT Plus subscription. This creates a bottleneck, as it restricts the pool of potential testers to those who have subscribed to the service and identity with the issues Jeff aims to address. So far, finding individuals who meet both criteria has been challenging. To work around this, I’m considering a more localized approach for testing. Rather than just trying to find people who meet the criteria in my networks online, I’ll also try to find people in my local network nearby who resonate with the issue Jeff addresses, such as social anxiety or identity gaps. I can then have them test Jeff directly on my laptop, so to circumvent the need for a subscription. While this is not ideal for scalability, it’s more practical in the short term. The reason why I’m confining this initial testing phase in my network is because it aligns with the observation in my previous testings, where many individuals in my target audience tend to be uncomfortable interacting with complete strangers, so focusing people within my own online and offline network or friends of friends will likely create a more comfortable testing environment. This should allow for more authentic engagement and feedback without any added social pressure that might come from interacting with unfamiliar people.
Another challenge that came up this week was around the engagement structure itself, specifically, that suers could potentially get stuck in the visualization phase, generating new images over and over instead of moving on the core mental rehearsal exercises. While the visuals add an engaging element, there’s a risk of them unintentionally becoming the main attraction, diverting users from the primary goal of the tool. To address this, I’m considering ways of subtly prompting users to move forward after a few visualizations, keeping them engaged without letting them linger too long on the visualization feature.
Lastly, I’ve received feedback suggesting that the visualizations themselves could benefit from more nuance, such as options for specifying gender or other basic traits. While I agree this could increase relatability, I’m cautious about making the visualization process too detailed, as it could shift the tool’s focus away from behavioral reflection and into something more like an avatar generator. Instead, I might add a couple of simple prompts at the beginning to capture key traits that users feel are most relevant to their identity, keeping it personal without over-complicating the setup.
As it stands, Jeff is hosted on the ChatGPT platform as a CustomGPT, which provides a convenient setup but comes with significant limitations. I quickly realized that my control over the user interface and branding is minimal, meaning that I can’t fully shape the experience. Creating a standalone platform for Jeff could open up more branding and marketing opportunities. I could tailor Jeff’s branding to specific user personas, especially my main target audience who are gamers. Currently, I feel limited by the generic ChatGPT environment, which makes it hard to create a memorable and standout experience.
Additionally, using Jeff on this platform requires a ChatGPT Plus subscription, which, while accessible to 10 million subscribers (Backlinko, 2024), restricts the tool’s availability to a broader audience. I want to make Jeff more accessible and versatile, and this platform constraint has pushed me to consider alternative hosting solutions.
Evaluating API Integration and Frontend Options
To build a more accessible and branded interface, my initial thoughts were to link the ChatGPT API to a custom frontend on platforms like Wix or WordPress, which offer more user friendly design tools without needing extensive coding knowledge. However, after doing some research, I found out that integrating ChatGPT’s API with these platforms is more complex than I initially anticipated. Neither Wix nor WordPress supports direct server-side scripting, which is essential for managing API requests. Setting up my own server to handle these requests is an option, but with my limited hardware and experience, it’s not feasible in the short term.
I then looked into third-party tools like Zapier and Make, which are able to facilitate API integrations without the need for coding. Unfortunately, these tools are enterprise level, with pricing that far exceeds this project’s current scale. While they could potentially streamline the integration, they aren’t practical for now due to the cost.
Alternatives
In my search for alternatives, I discovered the AI Engine plugin for WordPress, which simplifies the API integration process considerably. However, a critical limitation of this plugin is its inability to store and remember past conversations. This limitation disrupts Jeff’s core functionality, which relies on a continuous rehearsal and reflection loop. Without memory retention, Jeff cannot support users in revisiting and reflecting on past interactions, which is essential for sustained behavioral change.
Another platform I considered is SamurAI, which allows customization and already has server-side capabilities. However, like many other third-party solutions, it also cannot retain conversations across session, this prevents me from creating a long-term interaction flow for users.
Next Steps: Testing and Iterative Improvement
Throughout this exploration, I’ve realized how vital conversation memory is to Jeff’s purpose. The retention of user data across sessions is essential for a sense of continuity, which is central to Jeff’s rehearsal, action, and reflection loop. While I continue learning about potential integration solutions, I recognize the limitations in my technical knowledge and the complexity of achieving my ideal setup. The learning curve is quite steep, and the task of building a fully customized, memory-retaining chatbot is proving to be challenging.
Given these constraints, I’ve decided to refocus my immediate efforts on testing the concept with my target audience. By gathering direct feedback on Jeff’s current functionality, I want to refine the tool’s approach and ensure that, regardless of platform, it meets user needs effectively. This phase of testing will inform how I can structure Jeff to maximize its impact and what adjustments may be necessary as I continue exploring more customizable solutions.
In my last tutorial, I presented Jeff to class and also had Iggy test it out, who’s part of my target audience, and received some feedback that made me reevaluate the user experience, especially in the mental rehearsal component. Iggy suggested that the mental rehearsal part could be more immersive if I make it more personalized and interactive, potentially similar to the choice-based gameplay of “Detroit: Become Human.” This feedback really made me consider the importance of engagement through interactivity, especially in a tool like Jeff, which aims to support behavioral reflection and growth.
Snapshot of the mental rehearsal component in the initial testing with Iggy
As we watched Iggy go through the interview with Jeff, it looked like it was too long and it was boring for us onlookers, there were worries that it was too long and could get boring. However, Iggy himself said the interview length was fine, it’s just that it took awhile for him to go through the questions as English is not his native language. Gab also pointed out that people love answering questions about themselves, which helps keep them engaged.
Initial Self-Testing
During further self-testing, I noticed something that disrupted the flow and engagement of the experience. The issue comes after Jeff generates the two social archetypes. At this point, Jeff would ask the user to see if they wanted a comparison between their online and offline personas. For me personally, this comparison felt like a natural endpoint to the conversation, like providing a sense of closure which actually made me inclined to end the session right there. It was as if I had already reached a satisfying conclusion, this could risk prematurely ending engagement just as users are starting to get into it.
Tweaks
In response to these insights, I made several tweaks to Jeff. First, I removed the comparison prompt entirely after the archetypes are generated, opting instead to transition directly into the mental rehearsal component. It felt like a smoother experience for me now. This change will prevent users from feeling as though they’ve reached the end of the session prematurely, keeping users engaged as they move into the next stage.
For the mental rehearsal component, I implemented a more personalized approach. Instead of providing generic scenarios, Jeff will now ask users to describe an upcoming social situation that might be challenging. This adjustment made the rehearsal feel more relevant and impactful in my own self-testing, as it allowed to me mentally envision a specific real life scenario that I will find myself in rather than imagining a broad hypothetical situation. This shift should align more with McGlade’s (2021) research on mental rehearsal, which highlights the benefits of scenario-specific visualization for confidence and behavior change.
Snapshot of the new, more personalized mental rehearsal approach
Finally, I added a follow-up component at the end of the rehearsal. Now, Jeff encourages users to return after they’ve lived through the practiced scenario in real life, creating a cycle of action and reflection. This loop mirrors Jung’s (2020) concept of identity negotiation, where behavior is continuously adjusted to align more closely with their ideal self. It turns Jeff into a tool for ongoing growth rather than a single-use exercise, allowing users to build a habit of reflection and gradual social adaptation.
Snapshot of the follow-up from Jeff
Visualization Update
To better enhance the impact of the visualization component, I tweaked the archetype generation by adding color distinctions and more dynamic motion elements to make the generated archetype stand out more vividly. For example, I introduced cooler colors, like blues and greens, for shyer archetypes to convey a more reserved energy, while using warmer tones, such as reds and oranges, for more extroverted and confident archetypes.
I also tested using a background style inspired by trading cards, almost like tarot cards, to give each generation a distinct frame and aesthetic. This card-like design makes the visualization feel collectible and intentional, adding an extra layer of personalization that makes users feel as though they’re viewing a unique, tangible representation of their social personas. These tweaks should make the visualizations more memorable.
Left Side: Before Update, Right Side: After Update
Reflections and Future Considerations
With these changes, I feel Jeff is moving closer to becoming a meaningful tool for bridging the online and offline identity gap. The rehearsal feels more personal and focused now, though I’m still considering the ideal balance between depth and length. I plan to start gathering user feedback to see how I can improve it’s functions more. I’m looking forward to see how these adjustments resonate with others.
References
Jung, E., (2020) Identity gap: A concept for theorizing communicative aspects of identity. In Proceedings of the Annual Convention of National Communication Association, University of Southern Mississippi
McGlade, A.L., (2021) Optimizing exposure: Between-session mental rehearsal as an augmentation strategy. PhD. University of California, Los Angeles
In my recent Dragon’s Den presentation, I got some feedback that really got me thinking about the bigger picture for my project. One of the dragons mentioned that she loved the concept, especially because she does a similar mental rehearsal exercise with her daughter, who sometimes feels anxious before social gatherings. She said she could actually see my project helping a much wider audience, not just gamers. At the same time, she appreciated that I was starting with a specific focus, targeting socially anxious gamers first to really refine the tool.
This feedback really stuck with me. Hearing that someone uses mental rehearsal in their own life made me realize the potential impact my project could have outside of gaming. It’s encouraging to know the idea resonates with others and has relevance beyond the niche I’d originally planned for. I’m starting to think about how, further down the road, I could adapt this to support anyone who struggles with social anxiety in different situations, and not just the gaming community.
This Dragon’s feedback was a great reminder that sometimes a project’s potential goes beyond what you first imagine. I will definitely keep this broader application in mind as I continue to develop and test the tool.
The initial setup for the CustomGPT showed some promise, I was really excited to test it out once I had the general setup done, but as predicted, my first round of testing revealed several areas that needs refinement, as it is just a concept build, to make sure it can actually work, now that I know it can run theoratically, I need to refine it.
Challenges with Archetype Generation
The archetypes generated by the GPT felt very vague and impersonal. The GPT struggled to capture the nuances of a user’s social behavior, making the results feel more like generic labels than personal insights.
I quickly realized that this was largely due to the absence of a structured framework to guide the GPT’s decision making process. Without a framework to follow, the GPT was left to making random decisions and asking random questions, which impacted the quality of the archetypes.
To address this, I plan to implement the below frameworks and see how it runs and tune it from there:
-Social Interaction Style (Based on the Extraversion Scale from Big Five): -Social Role (Based of Leadership & Group Dynamics from Social Identity Theory) -Conflict Handling Style (Based on Thomas-Kilmann Conflict Mode Instrument) -Social Network & Engagement Context (Based on Social Circles & Network Theories) -Emotional Intelligence (Based on Mayer-Salovey Emotion Intelligence Model)
Issues with Visualization:
Another issue that showed was with the visualization process of the archetypes. In some instances, the visualization process will not even trigger, and sometimes and generated images would contain game logos or elements that shouldn’t be in there, like random texts. Additionally, the visualizations themselves were somewhat generic, lacking strong contrasts between different personality types. For example, whether the archetype was a leader or a follower, the visuals don’t vary much.
Tuning Mental Rehearsal for Personalization:
The mental rehearsal component of the GPT is one of the most important aspects of this intervention. During my first test, the GPT guided me through a scenario that was highly personal, asking me to describe a real life situation in which I could apply my social strengths. That felt incredibly engaging for me as I could very vividly imagine myself in that scenario, walking around and interacting. However, in my later tests, the GPT defaulted to generic scenarios that felt much less personal, I feel like this diminished the impact of the exercise, as it no longer felt personal and is not tailored to my experiences.
I will need to tune the mental rehearsal section so that it is able to consistently replicate the personalized experience I had in the first test. This means ensuring that the GPT always asks the user to provide a scenario from their real life, rather than defaulting to a pre-scripted situation. This will involve asking the user about recent or upcoming social situations or challenges they have or might face and then guiding them through a mental walkthrough of that experience.
I want it to feel as personal and realistic as possible, to allow users to be able to genuinely mentally picture applying their online strengths in offline situations. If the users can fully picture themselves in these rehearsals, the chances or them successfully using these skills in real life will likely increase.
Next Steps
Moving forward, my primary focus will be on refining the archetypes and mental rehearsal sections, as these are the most important parts of the project. Both areas needs deeper personalization.
Oh and about the name of the CustomGPT, I originally named it the “Persona Explorer.” But let’s be honest, it’s a very generic name. I’ve taken to liberty to rename it “Jeff,” until it is polished enough to deserve another name. So for now, I will be working with Jeff.
My goal is to help my audience reflect on the gap between their online and offline social behaviors and guide them toward reducing this gap through a series of reflective and rehearsal steps. There are three key stages with this tool I’m envisioning: reflection through social archetypes, mental rehearsal of real life scenarios, and social sharing for peer feedback. This method helps users acknowledge their strengths in online environments and practice applying these skills in real-world interactions.
AI Chatbot and the Big Five Personality Framework
The tool begins with a personalized interview conducted through a customized AI chatbot (ChatGPT as foundation) based on the Big Five personality framework, with a particular focus on the extraversion scale. Extraversion is key because it determines how users engage socially, whether they are more outgoing or reserved in different environments.
-Interview Process: The AI asks users questions about their social behaviors in online gaming contexts and offline settings. The interview gathers insights into how users communicate, lead, collaborate, and handle conflict in each environment.
The AI then analyzes the responses to pinpoint the user’s social archetype in both contexts, how they behave in online gaming and how they interact in offline situations.
2. Reflection Through Social Archetype Visualizations
Once the user’s online and offline social archetypes are identified, the next step is reflection. This is an important part of the process, where users are given the opportunity to see the gap between how they behave in online and offline settings.
Visualization: The archetypes are visualized using generative AI built into the chatbot, providing a graphic representation of their online and offline personas. The online archetype might depict the user as a leader or team collaborator, whereas the offline archetype might show a more reserved or passive role in offline interactions.
Purpose of Reflection: This stage is inspired by Jung’s Identity Gap Theory, which explores the discrepancy between personal and enacted identities. More often than not, the online persona (in this case, often more confident or outgoing) reflects an individual’s ideal self, while the offline persona (in this case, often more reserved) may reflect their actual self.
By reflecting on these two archetypes side by side, users can start to acknowledge the gap between their idealized self in the online world and their real-life behavior. This reflection serves as the first step in identity negotiation, helping users recognize that the strengths they display online.
3. Mental Rehearsal for Offline Social Skills
After the visualization and reflection process, the next stage will focus on mental rehearsal, where users are guided through real life social scenarios. This is designed to help them practice applying their online social strengths to real world interactions.
Scenario Design: The AI presents the user with parallel scenarios:
-Online Scenario: “You’re leading a group in an online multiplayer game, organizing the team to achieve a shared objective. How do you communicate with your teammates? How do you lead and resolve conflicts?” -Offline Scenario: “Now imagine you’re in a face-to-face group setting at work. You need to take charge and coordinate the group to complete a task. How do you apply the same leadership skills here?”
Role of Mental Rehearsal: This step is inspired by McGlade’s (2021) research, which demonstrates the effectiveness of mental rehearsal in reducing anxiety and improving behavioral outcomes. McGlade found that individuals who mentally rehearsed scenarios related to their fears showed significantly greater improvement compared to control groups, particularly in confidence and approach behaviors (McGlade, 2021, p.42).
4. Social Sharing for Peer Feedback and Reinforcement
The final step is social sharing, where users are encouraged to share their archetype results with their social circle. By sharing the visualized archetypes through social media, users can receive feedback and encouragement from friends and peer, and also hopefully generate some buzz and discussion around their archetypes and this tool I’m trying to create.
Social sharing can also serve as a motivator, as users might feel more accountable for applying their online strengths in real life after receiving encouragement from their friends. But I also understand that this places some responsibility on the user’s social circle and results could vary widely depending on the circle. I hope this peer support can help reinforce the work they have done in reflecting and mentally rehearsing offline scenarios and help them feel more confident in their real-world interactions.
Conclusion
My intervention method combines reflection, mental rehearsal, and optional social sharing to provide a comprehensive approach to bridging the identity gap.
Currently, I am in the process of brining this tool to life through a Custom GPT model as foundation. As this project evolves, things may change during development, and the impact of this intervention is still to be determined. However, I am quite excited about what I am currently doing!
References
McGlade, A.L. (2021). Optimizing Exposure: Between-Session Mental Rehearsal as an Augmentation Strategy. University of California, Los Angeles.
As my project continues to evolve, I’ve been exploring the ways in which gamers navigate the gap between their online and offline personas. Revisiting some literature, I have come to realize that Jung’s Identity Gap Theory offers a meaningful framework for understanding this phenomenon. Jung’s theory introduces the concept of the personal-enacted identity gap, which refers to the discrepancy between how individuals views themselves internally (their personal identity) and how they present themselves in communication (their enacted identity) (p. 6).
I think this concept applies well to the audience I’m targeting, as they often create avatars or online personas that allow them to express parts of their identity that they may not feel comfortable sharing in real life. In online environments, where stakes are lower and anonymity is possible, people can communicate with confidence and display social skills that seem to be inconsistent with their offline behavior. In these contexts, they enact an identity that is closer to their ideal self, a version of themselves that is confident, socially capable, and in control. However, offline, their behavior may reflect their actual self, which could be more influenced by social anxiety, self-consciousness, or a lack or confidence in face-to-face interactions.
The Role of Context in Identity Gaps
One of the key insights in Jung’s theory is that identity gaps are often context-dependent. I feel like this is highly relevant in the case of my audience, as the online environment provides a safe space where they can experiment with different social roles and identities, free from the pressures of real-world consequences or social judgements. They may experience a smaller gap between their personal and enacted identities online, as the digital space allows them to express parts of themselves that they would normally not show in offline situations.
When they transition to offline environments, the gap widens. Social pressures, heightened self-awareness, or anxiety may prevent gamers from enacting the same confident identity they express online. As a result, they might revert to more introverted or reserved behaviors, leading to a larger gap between their internal self-concept and how they interact with others in face-to-face situations. This could explain why some gamers may feel socially adept in online environments but withdrawn or anxious in offline settings, as their enacted identity does not fully align with their personal identity.
The Consequences of Identity Gaps
The consequences of this gap can be significant. Jung (2020) notes that a large gap between one’s personal and enacted identities can lead to negative outcomes, such as feeling misunderstood or experiencing communication dissatisfaction (p.9). For some gamers, this might explain why they might feel disconnected and/or frustrated when interacting offline, as their offline persona doesn’t fully represent who they are or what they are capable of.
Moreover, this identity gap can contribute to feelings of inauthenticity. Some might struggle with the fact that the confident, socially capable version of themselves that they project online seems inaccessible in offline situations. This disconnect can make worse issues like low self-esteem or even social anxiety, as they are unable to bring their online strengths into real-world interactions.
Identity Negotiation
According to Jung, reducing the identity gap requires a process known as identity negotiation. It involves actively finding ways to align one’s enacted identity more closely with their personal self-concept. Jung describes this process as dialectical because it is continuous, individuals will constantly work through the tension between how they see themselves and how they express themselves. Through repeated adjustments the aim is to reach a synthesis where their personal and enacted identities are more in harmony, and this process is always ongoing and always evolving.
For my audience, gamers who often feel more confident and socially adept online, the identity negotiation process would involve recognizing the strengths they display in online environments and learning how to apply those same strengths in offline situations. By being conscious of their online and offline differences, and adapting their online behaviors into offline settings, it should help to reduce the gap between their two identities.
However, through my research and initial testing, I discovered that many in my audience are reluctant with immediately practicing in offline environments, especially when it involves interacting with strangers. This presents a challenge that I will have to navigate.
I have been exploring the potential of using mental rehearsal as a way to guide my audience towards practicing their social skills in a more accessible way. It could be a way to visualize and mentally prepare for social interactions without immediately putting them into those situations, but I’m not sure how feasible this is yet, I need to look more into this.
References
Jung, E., 2020. Identity Gap: A Concept for Theorizing Communicative Aspects of Identity. Presented at the Annual Convention of National Communication Association. University of Southern Mississippi.
As I continue developing my project, I’ve found a need to revisit literature that initially guided me, to both straighten out my flow of thinking and explore new potential avenue for testing.
Revisiting the Problem
One of the first areas I explored in understanding this subject was in social anxiety, particularly how online games can be temporary measures for alleviating social anxiety. Cole and Griffiths (2007) described MMORPGs as “highly socially interactive environments” where players can express themselves in ways they might shy away from in real life, often due to social anxiety or concerns about their physical appearance or social standing (p.575).
While the escape to an online world is liberating, it also comes with a downside. The comfort of online spaces often reinforces avoidance behavior in offline environments. As Gioia et al. (2022) highlighted, socially anxious individuals frequently turn to online gaming to escape the stress of face-to-face interactions. This provides temporary relief from social anxiety, but it can also lead to problematic gaming behavior, where individuals become overly dependent on virtual worlds for social interaction, further alienating themselves from real-world experiences (p.33).
The Need for Reflection
Initially I considered guiding people towards therapeutic methods, like Cognitive-Behavioral Therapy (CBT) wrapped up in the skin of tabletop roleplaying games, which provide the opportunities of exposure therapy, behavioral experiments, and social skills training. However, from my previous testing, I understood that not everyone needs or wants to follow this path. Instead, more informal practices could provide a meaningful way to help individuals bridge the gap between their online and offline selves.
As I revisited literature, I became interested in how reflective practices can potentially help individuals bridge their online and offline gap. For instance, Carlson (2013) discusses how blind spots in self-knowledge can occur when individuals are unable to accurately assess their own behaviors and nonverbal cues. It was explained that people often lack “the visual perspective necessary to detect their own nonverbal behavior,” leading to over or underestimations of what their inner states are to others. Carlson also argued that self-knowledge involves the understanding of one’s pattern of thinking, feeling, and behaving, as well as knowing how others perceive those patterns (p.174). For gamers, this could mean reflecting on how they communicate effectively and build relationships in online games, compared to how they approach these same activities in real life. By putting these two behaviors side by side, individuals should be able to gain insight into their strengths and weaknesses across contexts.
References
Carlson, E. N. (2013). Overcoming the barriers to self-knowledge: Mindfulness as a path to seeing yourself as you really are. Perspectives on Psychological Science, 8(2), pp. 173-186.
Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer online role-playing gamers. CyberPsychology & Behavior, 10(4), pp. 575-583.
Gioia, F., Colella, G. M., & Boursier, V. (2022). Evidence on problematic online gaming and social anxiety over the past ten years: A systematic literature review. Current Addiction Reports, 9(1), pp. 32-47.
After my tutorial where I was encouraged to get the game night idea out of my head and test it, I invited two individuals to participate. Both are longtime gamers with distinct personalities when interacting online versus offline.
The first person I invited was Ting, a 23 year old Chinese student living in London. I approached him casually, under the pretense that we would be meeting new friends during the game night next week. Ting, however, declined the invitation due to his busy schedule. While I can’t be certain if his reason was only about availability, it does align with a broader hesitation that socially anxious gamers have towards stepping into unfamiliar face-to-face situations.
My second person was Jimi, a 27 year old male living in Taiwan, whom I had interviewed at the beginning of my Unit 3 independent study. Jimi had previously voiced interest in participating, but only if a friend invited him. I told him my idea of organizing such a game workshop in Taiwan remotely, with someone else helping on the ground, but Jimi also declined. His reason was he didn’t want to play with strangers. Additionally, a fellow member of my tutorial group, who falls into my target audience, also shared this same sentiment, expressing his disinterest because he doesn’t want to play with people he doesn’t know.
This experience confirmed the bias I had since my last tutorial: many socially anxious gamers are hesitant, some even resistant, to engage in face-to-face interactions with strangers. This reluctance raises the difficulty in making social interventions like game nights effective for this particular audience.
With this, I’m shifting my focus and changing my question to: How can we help socially shy young gamers recognize and encourage the transfer of their online social skills to face-to-face interactions? This reframed question will allow me to explore interventions that emphasize self-reflection and recognition of existing social abilities, rather than trying to force face-to-face situations that these gamers are uncomfortable with.
