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Why Did You Leave? A Content Analysis of Comments to Former Teacher Posts on TikTok

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Title: Why Did You Leave? A Content Analysis of Comments to Former Teacher Posts on TikTok
Language: English
Authors: Forrest Kaiser (ORCID 0000-0002-5261-9169), Jennifer Lane
Source: SAGE Open. 2025 15(3).
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 16
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Social Media, Video Technology, Faculty Mobility, Career Change, Teacher Persistence, Teachers, Self Disclosure (Individuals), Social Support Groups, Content Analysis, Algorithms, Feedback (Response)
DOI: 10.1177/21582440251379513
ISSN: 2158-2440
Abstract: Motivations for commenting on social media vary greatly and are driven by multiple factors including personal interests, political leaning, and algorithmic influence. This study used a thematic content analysis of comments on the TikTok platform to explore how users respond to videos created by former teachers sharing their stories of leaving the profession. Comment data were collected from a sample of posts explicitly sharing narratives of leaving and analyzed through a four-step mixed methods process. The researchers noted that words of affirmation had the highest representation in all comments, and included thoughts of encouragement, solidarity, acknowledgment, confirmation, and support. Users seeking connections had the next highest representation and involved user responses to extend the post to different situations, build on the ideas conveyed, or share personal feelings. Finally, discussions on self-care were the third highest and represented comments that focused on taking care of personal needs and thinking of self apart from a profession. By analyzing comments and engagement metrics, the study revealed key patterns on how users connect with others, express support, share personal experiences, and engage in discussions. The findings may offer insights into how social media platforms like TikTok may serve as spaces for emotional support, critical discourse, and the amplification of systemic issues within the education sector. These findings contribute to the growing body of literature on digital engagement and its implications for understanding educational challenges like teacher turnover.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1487275
Database: ERIC
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  Value: <anid>AN0188424241;[kbz6]01jul.25;2025Oct07.03:06;v2.2.500</anid> <title id="AN0188424241-1">Why Did You Leave? A Content Analysis of Comments to Former Teacher Posts on TikTok </title> <p>Motivations for commenting on social media vary greatly and are driven by multiple factors including personal interests, political leaning, and algorithmic influence. This study used a thematic content analysis of comments on the TikTok platform to explore how users respond to videos created by former teachers sharing their stories of leaving the profession. Comment data were collected from a sample of posts explicitly sharing narratives of leaving and analyzed through a four-step mixed methods process. The researchers noted that words of affirmation had the highest representation in all comments, and included thoughts of encouragement, solidarity, acknowledgment, confirmation, and support. Users seeking connections had the next highest representation and involved user responses to extend the post to different situations, build on the ideas conveyed, or share personal feelings. Finally, discussions on self-care were the third highest and represented comments that focused on taking care of personal needs and thinking of self apart from a profession. By analyzing comments and engagement metrics, the study revealed key patterns on how users connect with others, express support, share personal experiences, and engage in discussions. The findings may offer insights into how social media platforms like TikTok may serve as spaces for emotional support, critical discourse, and the amplification of systemic issues within the education sector. These findings contribute to the growing body of literature on digital engagement and its implications for understanding educational challenges like teacher turnover.</p> <p>Plain language summary: Why Did You Leave? An Analysis of Comments to Former Teacher Posts on TikTok More teachers are leaving the classroom prior to retirement than ever before. This has created a challenge for schools trying to hire and retain excellent teachers. This study analyzed comments left to former teachers sharing their stories of leaving the profession on the TikTok platform. Comments fell within eight primary groups, with Affirmation showing the highest across all posts. Affirmation included thoughts of encouragement, solidarity, acknowledgment, confirmation, and support. Connections had the second highest representation and involved user responses to extend the post to different situations, build on the ideas conveyed, or share personal feelings. Self-Care was the third highest and represented comments that focused on taking care of personal needs and thinking of self apart from a profession. By analyzing comments, likes, and shares, the study revealed key patterns that reflect the junction between personal and emotional connections and the influence of social media algorithms on user experiences. This study may offer insights into how social media platforms like TikTok serve as spaces for emotional support, critical discourse, and the amplification of systemic issues in education. These findings contribute to the growing body of literature on digital engagement and its implications for understanding educational challenges like teacher turnover.</p> <p>Keywords: content analysis; filter bubbles; teacher attrition; TikTok algorithm</p> <hd id="AN0188424241-2">Introduction</hd> <p>Understanding why teachers leave the classroom prior to retirement is an important issue for school leaders as they work to ensure every student has access to effective instruction. With fewer new candidates entering the field, retaining quality teachers has become a central concern in maintaining a full teacher workforce into the future ([<reflink idref="bib17" id="ref1">17</reflink>]). Teacher attrition has only increased in the past decade as mental health and personal care have come to the forefront in teacher's decisions to stay or go ([<reflink idref="bib16" id="ref2">16</reflink>]; [<reflink idref="bib22" id="ref3">22</reflink>]). Unfortunately, formal exit surveys distributed by schools only tell part of the story.</p> <p>Mobile short video apps such as TikTok have emerged as powerful spaces where current and former teachers share why they are leaving or have left the profession and where thousands of others respond, relate, and reflect on those narratives. Understanding these digital interactions can expand the contextual understanding of why teachers leave or stay. This work draws on the Uses and Gratifications Theory (UGT) to understand how users interact with and derive meaning from content shared by former teachers on TikTok. This theory is frequently used in studies examining why users seek particular platforms and how the usage of those platforms fulfills emotional, informational, and social needs ([<reflink idref="bib35" id="ref4">35</reflink>]). Additionally, this study incorporates emotional attachment theory ([<reflink idref="bib9" id="ref5">9</reflink>]) extended to digital contexts ([<reflink idref="bib8" id="ref6">8</reflink>]) in relation to how user responses may reflect identity and support for the content creators, as well as social cognitive theory ([<reflink idref="bib6" id="ref7">6</reflink>]) to help frame how online responses are shaped by users' experiences, perceived norms, and emotional states in digital communities.</p> <p>By applying these theoretical perspectives to content analysis of TikTok comments, this study aims to explore how users react to stories of attrition and what those reactions suggest about public perceptions of teaching and teacher burnout in the post-pandemic social media era. The purpose of this study is to use thematic content analysis to examine comments from users on the TikTok platform as they interact with video posts by former teachers. Following the COVID-19 pandemic, social media has become a considerable means for teachers to connect and share outside the school context as they seek authentic and varied connections to others ([<reflink idref="bib2" id="ref8">2</reflink>]). The study was guided by the following questions: (<reflink idref="bib1" id="ref9">1</reflink>) How do outsiders respond to teachers' stories of quitting on TikTok? (<reflink idref="bib2" id="ref10">2</reflink>) How do these types of responses reflect the current literature on teacher attrition? (<reflink idref="bib3" id="ref11">3</reflink>) How common are these various types of responses?</p> <p>The exploration of user comments on video posts by former teachers on TikTok may allow for an understanding of how others outside the classroom view the issue of teacher attrition and interact with the stories shared by those who have left the field. This insight could inform school leaders and policy makers as they work to implement strategies to support hiring and retaining quality teachers.</p> <hd id="AN0188424241-3">Review of the Literature</hd> <p>Accelerated by the pandemic, teacher attrition has become a significant issue for schools wanting to ensure every classroom is staffed by an effective teacher ([<reflink idref="bib16" id="ref12">16</reflink>]). The reasons teachers leave may be highly personal and specific to individual context, yet a heightened focus on self-care and individual wellness has emerged as a frequent justification among leavers ([<reflink idref="bib22" id="ref13">22</reflink>]; [<reflink idref="bib26" id="ref14">26</reflink>]). Safety concerns, political tensions, and mental health needs stemming from post-pandemic practices have placed additional strains on an already fragile system ([<reflink idref="bib51" id="ref15">51</reflink>]). Traditionally, literature on teacher attrition has focused on these institutional and psychological issues with discussions and studies on burnout, lack of administrative support, and dissatisfaction with working conditions ([<reflink idref="bib18" id="ref16">18</reflink>]; Ingersoll, 2001). However, as the landscape of educational practitioners evolves, particularly in digital spaces, it is crucial to broaden discussion to include the role of community engagement, emotional validation, and online social connectivity might influence teachers' decisions to leave or stay.</p> <p>According to the [<reflink idref="bib33" id="ref17">33</reflink>], 44% of public schools responded as having problems with ongoing teacher vacancies. Of these schools, 50% claimed that that current vacancies were the result of teacher resignations rather than retirement or new positions. The issue of attrition is not new, with teachers leaving prior to retirement accounting for close to 90% of open positions even before the pandemic ([<reflink idref="bib13" id="ref18">13</reflink>]). Combined with lower numbers of new candidates entering formal teacher preparation programs and the high cost of replacing current faculty, keeping veteran teachers in the classroom has become a key concern for school administrators and policymakers ([<reflink idref="bib12" id="ref19">12</reflink>]; [<reflink idref="bib17" id="ref20">17</reflink>]).</p> <hd id="AN0188424241-4">Burnout versus Demoralization</hd> <p>The concept of burnout is often defined as a syndrome characterized by emotional exhaustion, depersonalization, and reduced personal accomplishment ([<reflink idref="bib31" id="ref21">31</reflink>]). In contrast, demoralization refers to a state of disillusionment and a loss of morale, stemming from a perceived discrepancy between one's professional values and the realities of teaching ([<reflink idref="bib45" id="ref22">45</reflink>]). Essentially, burnout happens primarily within self-efficacy constructs while demoralization is dissonance caused by external and environmental factors. This can be referred to as the difference between emotional exhaustion and moral disillusionment, as burnout primarily involves emotional exhaustion and detachment from work tasks whereas demoralization centers on feelings of moral disillusionment, incompetence, and a loss of confidence in the teaching profession due to external impacts ([<reflink idref="bib41" id="ref23">41</reflink>]).</p> <p>Causes of burnout are often associated with excessive workload, job stress, and organizational factors. Causes of demoralization tend to be linked to perceived professional ineffectiveness, moral conflicts, and dissonance with educational policies. According to [<reflink idref="bib50" id="ref24">50</reflink>], both phenomena have negative implications for teacher well-being, job satisfaction, and professional efficacy. However, burnout may lead to emotional detachment and cynicism, whereas demoralization may result in a loss of faith in the teaching profession and a sense of moral distress. This is illustrated in the exploration of the justification educators provide for leaving and whether they leave behind one school for another or leave the profession entirely. Although burnout and demoralization can be defined and illustrated as separate constructs, they often coexist and mutually influence each other. For example, teachers experiencing burnout may also feel demoralized due to a sense of professional inadequacy, while demoralization can exacerbate feelings of exhaustion and detachment associated with burnout. This is illustrated through the study of how teachers' emotional experiences, both positive and negative, influence their ability to engage in reflective thinking about their teaching practices and the underlying connection between teacher emotional perceptions and their actions and behavior.</p> <p>To combat both teacher burnout and demoralization, improvement efforts must be focused on organizational support, professional development relevance and opportunities, positive school culture, and promotion of self-care and resilience ([<reflink idref="bib23" id="ref25">23</reflink>]). The intricate and complex challenges faced by teachers in today's educational landscape require investigation into the multifaceted dimensions of teacher morale, exploring systemic pressures, and seeking to understand ethical dilemmas that contribute to teachers' professional experiences ([<reflink idref="bib42" id="ref26">42</reflink>]). In examining the underlying causes and consequences in teacher turnover, research shows that while increasing student enrollments and teacher retirements contribute to staffing challenges, turnover driven by factors such as job dissatisfaction and career changes plays the most critical role ([<reflink idref="bib20" id="ref27">20</reflink>]). Factors such as rigid accountability measures, diminished autonomy, and conflicting expectations are also credited for the expansion of burnout into demoralization ([<reflink idref="bib19" id="ref28">19</reflink>]).</p> <hd id="AN0188424241-5">Teacher Self-Efficacy and Well-Being</hd> <p>Self-efficacy is defined by [<reflink idref="bib4" id="ref29">4</reflink>] as an individual's belief in their capacity to accomplish specific tasks or achieve goals. Mastery experiences, physiological and emotional states, vicarious experiences, and social persuasion all play a critical role in influencing self-efficacy and these beliefs are not synonymous with beliefs regarding whether those actions affect outcomes ([<reflink idref="bib5" id="ref30">5</reflink>]). Additionally, [<reflink idref="bib40" id="ref31">40</reflink>] scheme of inter-external locus of control explored the lack of its connection to personal efficacy. Expanding on these concepts, [<reflink idref="bib49" id="ref32">49</reflink>] added specificity of context for teacher efficacy particularly as "the extent to which teachers believe that they can control the reinforcement of their actions and whether control of reinforcement lay within themselves or the environment" (p. 202).</p> <p>Early investigations into self-efficacy primarily occurred within clinical therapeutic realms but have since extended across diverse domains such as education and occupation on a global scale ([<reflink idref="bib44" id="ref33">44</reflink>]). Research consistently acknowledges the role of self-efficacy in shaping motivation and performance and despite its recognized strength as a behavioral predictor, it is imperative to recognize that self-efficacy operates within a nuanced interplay of contextual factors ([<reflink idref="bib4" id="ref34">4</reflink>]; [<reflink idref="bib43" id="ref35">43</reflink>]; [<reflink idref="bib49" id="ref36">49</reflink>]). Cultural and situational differences notably influence self-efficacy beliefs, with distinct cultural emphases and environmental contexts impacting individual confidence levels.</p> <hd id="AN0188424241-6">Online Interactions – Social Media Influences and Motivations</hd> <p>With the rise of social media influence, research has explored the motivations of both social media producers and consumers, its impact on attitudes, perceptions, and self-efficacy, and the role algorithms play in curated media.</p> <p>Online interactions, especially those involving social media platforms have been investigated for their impact and influence on both attitudes and identity. There is much discussion over the authenticity of online personas and how they present differently than interactions from real-life identities. Specifically, shaping of the online persona is influenced by social networks, which act as electronic mirrors, and by extension then impact real lives, psychological well-being, and interpersonal interactions ([<reflink idref="bib53" id="ref37">53</reflink>]). This conformity often manifests itself in groups to enhance feelings of connection and purpose ([<reflink idref="bib29" id="ref38">29</reflink>]) and is demonstrated in both original posting and the motivation behind post interaction, commenting, and sharing.</p> <p>As a result of these influential and motivating factors, individuals posting media on social media platforms often leverage them to tailor their posts, interactions, and sensory language to yield maximum engagement and interaction. For example, choosing a simple and quick interaction platform such as Twitter and Instagram may not be as effective for complex social issue influence and discussion whereas platforms such as Facebook and TikTok may allow for deeper emotional content and response through video output ([<reflink idref="bib34" id="ref39">34</reflink>]). The intentional curation of words and visuals to elicit maximum number of likes, comments, and follows raises some concerns of authenticity and truth, as these messages sometimes compound to influence social movement and popular culture ([<reflink idref="bib53" id="ref40">53</reflink>]).</p> <p>Motivations for commenting on social media posts are varied and encompass social, psychological, and situational factors that drive user engagement and motivation to comment. Perhaps the biggest factor is the need to connect with others, express support, share personal experiences, and engage in discussions ([<reflink idref="bib2" id="ref41">2</reflink>]; [<reflink idref="bib29" id="ref42">29</reflink>]). Commenting allows users to express themselves, share their opinions, showcase their expertise, and shape their online identities ([<reflink idref="bib15" id="ref43">15</reflink>]). Researchers have also noted the impact of the nature of the original post with users reporting an increased likelihood of commenting if they felt the posts were personally relevant, interesting, entertaining, or reflective of their personal preferences and individual tastes, or if they provoked extensive emotional arousal such as joy, surprise, or anger ([<reflink idref="bib52" id="ref44">52</reflink>]). Specifically, if posts included small shifts in intentional sensory language used by influencers, it led to a substantial increase in likes, comments, and shares ([<reflink idref="bib14" id="ref45">14</reflink>]).</p> <p>Additionally, studies have shown that social influence and norms play a crucial role in the threshold between viewing and commenting as individuals may feel compelled to participate in discussions to conform to group expectations or to gain social validation as an extension of social desirability bias ([<reflink idref="bib32" id="ref46">32</reflink>]; [<reflink idref="bib47" id="ref47">47</reflink>]). The concept of audience salience indicates that knowing that a comment will be seen by friends, family, or followers means the author of the comment may curate a more socially desirable response ([<reflink idref="bib34" id="ref48">34</reflink>]). Users may also feel compelled to comment to provide assistance, offer advice, support others, or to shape opinions and contribute to collective decision-making processes with online communities ([<reflink idref="bib15" id="ref49">15</reflink>]).</p> <p>The popularity of mobile short video applications such as TikTok offer an additional lens for examining and understanding teacher attrition specifically. These social media platforms have risen to become premier digital forums where current and former educators share their experiences and where the public is able to engage with those narratives. [<reflink idref="bib35" id="ref50">35</reflink>] examined how users' social and system interactivity on mobile video platforms influence their perceived benefits which in turn shape their continuance intentions. The findings of the study indicated that digital interaction not only entertains, but also fulfills psychological needs such as empathy, validation, and connection.</p> <p>Similarly, [<reflink idref="bib36" id="ref51">36</reflink>]) conducted research that explored how service quality on mobile platforms directly impacts users' identity, social belonging, and emotional attachment. When examined in the educational context, these findings reflect the importance of teacher's emotional connections to their professional identity and institutional culture. This suggests that digital spaces like those explored on TikTok may become alternate spaces for those individuals to rebuild a sense of identity and community.</p> <p>Studies have further explored how multidimensional perceived benefits, including functional, psychosocial, and hedonic, contribute to satisfaction and electronic word-of-mouth (eWOM) behavior ([<reflink idref="bib37" id="ref52">37</reflink>]). The positive engagement users experience when their narratives are validated provides emotional closure or affirmation they may have been missing in their professional setting. Conversely, [<reflink idref="bib38" id="ref53">38</reflink>] studied the darker side of these social media experiences by finding that cyberbullying and communication overload on these platforms can lead to app switching behavior, mediated by depressive mood and platform fatigue. Essentially, users can be driven to switch platforms if they are not getting the validation they seek. In the educational space, teachers may seek to abandon the profession just as users abandon one app for another.</p> <p>Together, this literature expands the conceptual framework for teacher attrition beyond the traditional and into the digital realm. They reveal how online social dynamics reflect broader psychological and relational processes that influence both identity reconstruction and disengagement. This offers new insight on both why teachers ultimately choose to leave the profession and how their stories resonate with others.</p> <hd id="AN0188424241-7">The Role of Algorithms</hd> <p>The influence of computer algorithms present in many social media platforms may impact the specific audience or reach of any given post or content produced on social media platforms. The depth and span of a social media post's visibility is significantly shaped by recommendation algorithms. These algorithms are designed to increase user engagement by grouping recommended content that is in alignment with individual users' preferences ([<reflink idref="bib24" id="ref54">24</reflink>]). This largely controls what content is promoted and to whom the content is shown resulting in viral success for certain posts. It also raises some concerns over the potential spread of misinformation and the reinforcement of existing biases ([<reflink idref="bib46" id="ref55">46</reflink>]).</p> <p>The concept of intentionally recommended, or conversely, absent content based on user algorithm is often referred to as a filter bubble. The phenomenon of filter bubbles can be compared to the Ladder of Inference ([<reflink idref="bib1" id="ref56">1</reflink>]) as it relates to data presentation and consumption. The Ladder of Inference illustrates that as humans, we are innately acute to scanning our environment for the data that supports, defends, or aligns to what we already believe to be true, rather than data that refutes it. As a result, we see and collect only what bolsters our belief system and not what challenges it. This is the concept behind filter bubbles, which can be thought of as the automated and technological version of this phenomenon by only showing users what their usage data shows they are interested in or interact with most, while withholding the content that does not ([<reflink idref="bib3" id="ref57">3</reflink>]). This is of interest to social media studies, as the data collected can potentially be affected by filter bubbles and algorithms and should be considered in analysis.</p> <hd id="AN0188424241-8">Theoretical Framework</hd> <p>This work draws on the Uses and Gratifications Theory (UGT), emotional attachment theory, and social cognitive theory to help make sense of how users respond to former teachers' stories on TikTok. Together, these frameworks provide a lens for understanding not just why people engage with this content, but also what that engagement reveals about broader beliefs, emotions, and experiences connected to the teaching profession.</p> <p>UGT helps explain how and why users are drawn to this type of content initially. The theory suggests that users actively seek out media that fulfills a need—whether that need is for emotional support, entertainment, community, or information ([<reflink idref="bib25" id="ref58">25</reflink>]; [<reflink idref="bib35" id="ref59">35</reflink>]). On TikTok, users are not passively scrolling but are rather watching stories that resonate, commenting to connect, and engaging because it serves a personal or social purpose. In this study, UGT helped the authors explore the different motivations behind user comments and how those motivations might reflect deeper reactions to teacher attrition.</p> <p>The second framework, emotional attachment theory, was originally developed to explain human bonding ([<reflink idref="bib9" id="ref60">9</reflink>]) but has since been adapted to explain how people connect with media and digital spaces ([<reflink idref="bib8" id="ref61">8</reflink>]). On platforms like TikTok, emotional attachment is illustrated in how users respond with empathy, share similar experiences, or offer words of affirmation. These comments often reflect an emotional investment in the creators and the content rather than a surface-level reaction. Users signal alignment, solidarity, and even a shared identity, particularly when the stories touch on burnout, systemic injustice, or personal well-being ([<reflink idref="bib38" id="ref62">38</reflink>]).</p> <p>Finally, social cognitive theory helps explain how users learn from and model one another's responses. According to [<reflink idref="bib6" id="ref63">6</reflink>], people observe others, see how they are rewarded or supported, and then adjust their own behavior accordingly. This kind of observational learning is especially powerful in digital communities, where the visibility of others' reactions is immediate and public. In this study, social cognitive theory helps frame the way comment sections can influence not just individual responses, but also how people make sense of teaching as a profession. Whether it's affirmation, critique, or advice, users are participating in a shared conversation shaped by the stories they watch and the community responses they see around them ([<reflink idref="bib38" id="ref64">38</reflink>]). Together, these theories offer a more nuanced way of understanding how public discussion and perception about teaching is being shaped by those who tell their stories, as well as by those who listen and respond.</p> <hd id="AN0188424241-9">Methods</hd> <p>The present study utilized a thematic content analysis to explore meaning within text-based comments in response to video posts on the Tik-Tok platform and was guided by the following questions: (<reflink idref="bib1" id="ref65">1</reflink>) How do outsiders respond to teachers' stories of quitting on TikTok? (<reflink idref="bib2" id="ref66">2</reflink>) How do these types of responses reflect the current literature on teacher attrition? (<reflink idref="bib3" id="ref67">3</reflink>) How common are these various types of responses?</p> <p>Using the model outlined by [<reflink idref="bib11" id="ref68">11</reflink>] the thematic content analysis was an inductive process where the researchers began by reviewing the data to become familiar with the video posts and associated comments. Each researcher then independently developed initial codes and considered potential themes. The initial codes and themes were then discussed collaboratively to review and refine into a final set that could be clearly defined and shared through narratives and examples. A more in depth-discussion of the analysis can be found below.</p> <p>This study is an extension on findings from prior research that explored narratives on TikTok from current and former teachers discussing the issue of teacher attrition ([<reflink idref="bib22" id="ref69">22</reflink>]). While the initial study centered on how current and former teachers used social media to share their thoughts and beliefs about the issue through short video posts, this research intended to understand how others social media respond and interact with these posts.</p> <p>Post creators on social media may share their stories as a means to engage in a topic or elicit responses from other users on the platform ([<reflink idref="bib21" id="ref70">21</reflink>]). While the specific algorithm used by TikTok to highlight videos for users is not open to researchers, the platform itself explains that videos are shared based on interactions and engagement with presented content ([<reflink idref="bib48" id="ref71">48</reflink>]). For the purpose of this research, there are no assumptions made as to how directly the commentors are connected to field of teaching or the issue of teacher attrition beyond being presented with the video posts on TikTok.</p> <hd id="AN0188424241-10">Sample</hd> <p>The comments that were reviewed for this study were derived from a prior dataset of 100 English-language videos created by distinct users found using the keyword "teacher resignation." Videos considered for inclusion explicitly demonstrated being posted by a current or former teacher and discussed in some form the concept of teacher attrition. Keyword identification and initial codebook development was conducted through a pilot run where multiple possible keywords were identified. The final combination of "teacher resignation" was selected as it had the highest engagement with 41.4 billion views at the time of data collection.</p> <p>To achieve a sample of 100 videos by individual users, a total of 174 videos were reviewed on the platform with only the first presented post by an individual user included. As the TikTok algorithm uses user viewing and engagement metrics to shape presented content, a new user account was created for both the pilot run and main study, and each video was viewed in a fresh incognito browser window.</p> <p>To explore how outside users respond to teachers' stories of quitting on TikTok, the base sample of 100 videos was narrowed to 66 posts that explicitly shared stories of quitting. From this, 10 videos were randomly selected to bring the total number of comments to an accessible number for manual review by the research team.</p> <hd id="AN0188424241-11">Data Collection</hd> <p>Data collection began with a review and download of top-level comments for each video within the sample. Top-level comments include only those made by an individual user responding to the original video post author. Top-level comments were selected as the primary form of data for this study as they represent a user's personal thoughts on the content of the initial video post. Comments made in response to top-level comments were not included as the researchers wanted to isolate and examine initial reactions to the video posts rather than responses or discussion stemming from other users' comments.</p> <p>In the instance where the number of overall comments was too excessive for manual review and analysis, a random sample of 100 comments were used. This sampling choice impacted two posts as can be noted in Table 1 below. From the included videos, a total of 438 individual top-level comments were collected for review. Identifiable demographic information such as username, nickname, and profile link were removed from the comments prior to analysis. Each comment was then provided with an identifier for reference between researchers and analysis phases.</p> <p>Table 1. Video Post Engagement by Type and Theme.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /><col align="left" /></colgroup><thead><tr><th /><th /><th /><th align="center" colspan="2">Comments</th><th align="center" colspan="2">Likes</th><th align="center" colspan="2">Shares</th><th align="center">Total Eng</th></tr><tr><th align="left">Post</th><th align="center">Theme</th><th align="center">Views</th><th align="center">%</th><th align="center">n</th><th align="center">%</th><th align="center">n</th><th align="center">%</th><th align="center">n</th><th align="center">%</th></tr></thead><tbody><tr><td>1</td><td>PHW</td><td>2,826</td><td>1.4</td><td>40</td><td>8.2</td><td>233</td><td>0.1</td><td>2</td><td>9.7</td></tr><tr><td>2</td><td>WC</td><td>795</td><td>1.1</td><td>9</td><td>9.8</td><td>78</td><td>0.8</td><td>6</td><td>11.7</td></tr><tr><td>3</td><td>PHW</td><td>10,700</td><td>0.4</td><td>45</td><td>8.5</td><td>912</td><td>0.2</td><td>25</td><td>9.2</td></tr><tr><td>4</td><td>PHW</td><td>46,900</td><td>0.1</td><td>64</td><td>5.2</td><td>2,433</td><td>0.0</td><td>8</td><td>5.3</td></tr><tr><td>5</td><td>RS</td><td>27,500</td><td>0.1</td><td>32</td><td>3.6</td><td>983</td><td>0.0</td><td>4</td><td>3.7</td></tr><tr><td>6</td><td>RS</td><td>4,600,000</td><td>0.0</td><td>1,609</td><td>16.5</td><td>760,400</td><td>0.0</td><td>1,852</td><td>16.6</td></tr><tr><td>7</td><td>SE</td><td>6,419</td><td>3.2</td><td>204</td><td>11.3</td><td>723</td><td>3.6</td><td>229</td><td>18.0</td></tr><tr><td>8</td><td>SE</td><td>1,257</td><td>2.2</td><td>28</td><td>14.0</td><td>176</td><td>0.0</td><td>0</td><td>16.2</td></tr><tr><td>9</td><td>PHW</td><td>5,132</td><td>1.0</td><td>49</td><td>4.6</td><td>235</td><td>0.4</td><td>21</td><td>5.9</td></tr><tr><td>10</td><td>PHW</td><td>9,884</td><td>0.6</td><td>55</td><td>3.8</td><td>373</td><td>0.1</td><td>10</td><td>4.4</td></tr><tr><td>Mean</td><td /><td /><td>1.0</td><td /><td>8.5</td><td /><td>0.5</td><td /><td>10.1</td></tr></tbody></table> </ephtml> </p> <hd id="AN0188424241-12">Data Analysis</hd> <p>Analysis for this study included four phases: (<reflink idref="bib1" id="ref72">1</reflink>) codebook development, (<reflink idref="bib2" id="ref73">2</reflink>) qualitative language analysis, (<reflink idref="bib3" id="ref74">3</reflink>) quantitative language analysis, and (<reflink idref="bib4" id="ref75">4</reflink>) a final reflexive thematic analysis. In the first phase of codebook development, the researchers independently reviewed each video post, examined the associated comments, and assigned up to three initial codes to describe each associated top-level comment. From this independent review, a set of 134 initial codes were identified for all 10 videos. The researchers then shared and discussed these codes into a combined document, compared them to the literature, and refined the set into a working codebook of 24 code categories. Codebook development was an iterative process to combine synonyms, highlight discrepancies, and identify patterns between researchers. Each code category was provided with a definition and a representative sample of comments illustrating each in use. The refined codebook was then applied to the entire dataset.</p> <p>In the second phase, a qualitative language analysis was conducted by the researchers to further refine codes and identify emergent themes. Comments for each video were considered independently based on themes presented in the videos identified from the prior study. The researchers further reviewed patterns within code categories and identified emergent themes that encompassed connections found in the literature. These themes operated as baskets for subcategories observed within the comments.</p> <p>For the third phase, a quantitative language analysis was conducted using the LIWC-22 application to explore user sentiment, word frequencies, and emotional language. LIWC-22 uses an internal dictionary that includes words, stems, phrases and emoticons to connect text to categories ([<reflink idref="bib10" id="ref76">10</reflink>]). Each comment was reviewed individually as a full text segment. Output from the analysis was placed into a spreadsheet by video and comment identifier. In addition to providing insight into sentiment and tone, the LIWC-22 analysis was used to check and revise emergent themes from the prior phase. Finally, for the fourth phase, counts were recorded for each theme and a reflexive thematic analysis was used to examine connections between qualitative and quantitative data and compare relationships among themes.</p> <p>Throughout the data collection and analysis process, the researchers created process memos and engaged in internal audits on research decisions. The audits consisted of discussions between researchers on coding rigor and emerging results, and the retention of raw data for reference throughout analysis.</p> <hd id="AN0188424241-13">Results</hd> <p>This research sought to explore how outside users responded to video posts by former teachers on the TikTok platform. To provide a visual representation of the data, a word cloud was developed highlighting the most frequently occurring words in the entire data set (see Figure 1).</p> <p>Graph: Figure 1. Word cloud of most frequently used words and emojis.</p> <p>Eight primary themes were identified from the analysis. These included Affirmation, Making Connections, Self-care, Social Structures, Surface Level, Trend, Stakeholders, and Advice. To understand the context behind word frequencies and user engagement in each post, counts were taken of views, comments, likes, and shares along with the primary theme for the video (see Table 1). In the random sample of 10 videos, 5 discussed Personal Health and Wellness (PHW). This theme includes physical or emotional health, well-being, job efficacy, and work/life balance. Two videos discussed Relationships and Support (RS) including student, parent, or administrator relationships along with administrator support and communication. Another two videos focused on the Social Environment (SE). This theme includes discussions of the social and political environment, equity/inclusion/diversity, professional respect, teacher attrition as a trend, and hope for change. One video in the sample spoke directly to Working Conditions (WC) including job demands or workload, local/state/federal policies, school culture, and safety.</p> <p>It should be noted that even when a video post received a high number of views, the relative percentage of engagement by users to comment was low. Users were more prone to like a video than to comment or share.</p> <hd id="AN0188424241-14">Language Analysis</hd> <p>LIWC-22 is a text processing software tool that takes language from a source text and compares it to a set of dictionaries delineated by various psychosocial constructs. Depending on the parameters set, the output may highlight the sentiment, thoughts, and emotions behind the text ([<reflink idref="bib10" id="ref77">10</reflink>]). While the complexity of language makes a full and clear analysis difficult, the results of a LIWC-22 analysis may provide further insight and clarity to support a manually completed qualitative analysis.</p> <p>The output from LIWC-22 reports on a variety of dimensions. For the purpose of this research, only the four summary language measures of Analytical Thinking (Analytic), Clout, Authenticity (Authentic), and Emotional Tone (Tone) were used. These measures are standardized composite variables reported on a scale of 1 to 100 ([<reflink idref="bib10" id="ref78">10</reflink>]). Average word count for each post was included for reference. Results from the analysis can be found in Table 2 below.</p> <p>Table 2. LIWC-22 Summary Measures by Post and Theme.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Post</th><th align="center">Theme</th><th align="center">Word count</th><th align="center">Analytic</th><th align="center">Clout</th><th align="center">Authentic</th><th align="center">Tone</th></tr></thead><tbody><tr><td>1</td><td>PHW</td><td>16.6</td><td>26.2</td><td>38.3</td><td>86.2</td><td>32.3</td></tr><tr><td>2</td><td>WC</td><td>13.7</td><td>25.2</td><td>65.9</td><td>70.5</td><td>40.1</td></tr><tr><td>3</td><td>PHW</td><td>15.8</td><td>26.0</td><td>64.4</td><td>67.9</td><td>90.7</td></tr><tr><td>4</td><td>PHW</td><td>12.9</td><td>27.8</td><td>75.8</td><td>70.5</td><td>75.3</td></tr><tr><td>5</td><td>RS</td><td>8.7</td><td>43.2</td><td>56.8</td><td>58.7</td><td>55.4</td></tr><tr><td>6</td><td>RS</td><td>12.4</td><td>21.7</td><td>52.3</td><td>65.7</td><td>42.4</td></tr><tr><td>7</td><td>SE</td><td>17.7</td><td>34.0</td><td>83.5</td><td>40.1</td><td>70.7</td></tr><tr><td>8</td><td>SE</td><td>17.7</td><td>41.0</td><td>62.2</td><td>75.2</td><td>51.5</td></tr><tr><td>9</td><td>PHW</td><td>13.3</td><td>27.8</td><td>46.8</td><td>85.1</td><td>57.1</td></tr><tr><td>10</td><td>PHW</td><td>15.4</td><td>18.1</td><td>46.4</td><td>74.5</td><td>56.9</td></tr><tr><td>Mean</td><td /><td>14.7</td><td>27.2</td><td>61.6</td><td>64.5</td><td>59.5</td></tr></tbody></table> </ephtml> </p> <p>Considering the average word count of comments for each theme, the two posts discussing the Social Environment had the highest count with 17.7 average words each, while the two posts speaking to Relationships and Support had the lowest count with 8.7 and 12.4 average words respectively compared to the overall mean of 14.7.</p> <p>The Analytical Thinking measure considers the level in which individuals use logical or hierarchical thinking in their comments. The highest levels of analytical thinking were found in the comments of post 5 (43.2) which discussed Relationships and Support and post 8 (41.0) which discussed the Social Environment. The lowest level was found in post 10 (18.1) which discussed personal health and wellness. Clout speaks to how individuals project leadership and self-confidence in the language they choose. The highest level of clout was reported for post 7 (83.5) which discussed the Social Environment. The lowest level was noted in post 1 (38.3) which discussed personal health and wellness. The Authenticity measure represents language that is more spontaneous, impulsive, or natural, lacking self-regulation or formality. The highest levels of authenticity were found in post 1 (86.2) and post 9 (85.1) both of which discussed personal health and wellness. The lowest level was reported in post 7 (40.1) which discussed the social environment. Finally, the measure of Emotional Tone describes the overall positive or negative sentiment expressed within the text. A number above 50 represents a positive remark while numbers below 50 represent a negative emotional tone. The closer the score moves to 100 or 0 delineates the degree of positivity or negativity. The highest level of positive sentiment was observed in post 3 (90.7) and the lowest was noted in post 1 (32.3), both of which discussed personal health and wellness.</p> <hd id="AN0188424241-15">Primary Themes</hd> <p>Eight primary themes emerged from the comment analysis and included Affirmation (Aff), Connections (Con), Self-care (SC), Social Structures (SS), Surface Level (Sur), Trend (Tre), Stakeholders (Sta), and Advice (Adv). Comment theme counts by post can be found in Table 3 below.</p> <p>Table 3. Theme Counts as Percent of Top-Level Comments.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Post</th><th align="center">TL com</th><th align="center">Aff</th><th align="center">Con</th><th align="center">SC</th><th align="center">SS</th><th align="center">Sur</th><th align="center">Tre</th><th align="center">Sta</th><th align="center">Adv</th></tr></thead><tbody><tr><td>1</td><td>25</td><td>60.0</td><td>48.0</td><td>52.0</td><td>16.0</td><td>16.0</td><td>16.0</td><td>8.0</td><td>20.0</td></tr><tr><td>2</td><td>6</td><td>66.7</td><td>50.0</td><td>33.3</td><td>50.0</td><td>0.0</td><td>0.0</td><td>16.7</td><td>33.3</td></tr><tr><td>3</td><td>24</td><td>87.5</td><td>50.0</td><td>41.7</td><td>8.3</td><td>8.3</td><td>20.8</td><td>0.0</td><td>8.3</td></tr><tr><td>4</td><td>46</td><td>76.1</td><td>39.1</td><td>17.4</td><td>4.3</td><td>0.0</td><td>4.3</td><td>28.3</td><td>2.2</td></tr><tr><td>5</td><td>20</td><td>80.0</td><td>20.0</td><td>40.0</td><td>35.0</td><td>20.0</td><td>0.0</td><td>30.0</td><td>10.0</td></tr><tr><td>6</td><td>100</td><td>52.0</td><td>79.0</td><td>22.0</td><td>16.0</td><td>23.0</td><td>11.0</td><td>2.0</td><td>0.0</td></tr><tr><td>7</td><td>100</td><td>71.0</td><td>27.0</td><td>13.0</td><td>48.0</td><td>27.0</td><td>2.0</td><td>12.0</td><td>3.0</td></tr><tr><td>8</td><td>18</td><td>77.8</td><td>83.3</td><td>11.1</td><td>27.8</td><td>16.7</td><td>33.3</td><td>0.0</td><td>0.0</td></tr><tr><td>9</td><td>21</td><td>76.2</td><td>90.5</td><td>47.6</td><td>4.8</td><td>0.0</td><td>14.3</td><td>14.3</td><td>14.3</td></tr><tr><td>10</td><td>78</td><td>80.8</td><td>62.8</td><td>33.3</td><td>10.3</td><td>5.1</td><td>9.0</td><td>0.0</td><td>20.5</td></tr><tr><td>Mean</td><td>30</td><td>72.8</td><td>55.0</td><td>31.1</td><td>22.0</td><td>11.6</td><td>11.1</td><td>11.1</td><td>11.2</td></tr></tbody></table> </ephtml> </p> <hd id="AN0188424241-16">Affirmation</hd> <p>The theme of Affirmation centers on thoughts of encouragement, solidarity, acknowledgment, confirmation, and support. These comments relate to the human quality of work, assurance that appropriate choices were made, empathy for circumstances, and commendation for taking risks where needed. As one commenter expressed: "Good for you taking care of yourself. You'll figure out your next move." Some comments focused on assuring the poster of the quality of their choice, such as "Thank you for standing up for what's right!!!" or "I super respect that." Others just sent positive statements of affirmation: "Sending you so much love." Affirmation had the highest representation in all comments, with an average of 72.8% observed among all posts. The highest level of affirmation was noted in post 10 (PHW), where 80.8% of the comments fit within the theme. The lowest level was found in post 6 (RS) where only 52.0% of the comments aligned with the theme.</p> <hd id="AN0188424241-17">Connections</hd> <p>Comments within the theme of Connections used the response to extend the post to different situations, build on the ideas conveyed, or share emojis to represent feelings. Users expressed commonality with the post, made personal connections to outside experiences, described thoughts of professional expectations, or simply left an emotional tag in response. One commenter shared a similar story in their response: "I just submitted my resignation today and I feel exactly how you were feeling. I have no idea what's next and I am so sad about this!" Another shared about taking the same path: "I had this talk with my students back in Sept. Leaving the classroom was absolutely the right decision for me but that conversation is so difficult." One commenter provided the poster with a student perspective: "when I was in third grade my teacher had to leave early too, we were sad but we made it through. they will be okay." Connections had the second highest representation in the comments, with an average of 55.0% observed among all posts. Post 9 (PHW) had the highest representation with 90.5% while post 5 (RS) had the lowest with 20.0%.</p> <hd id="AN0188424241-18">Self-care</hd> <p>The theme of Self-Care encompasses an individual's focus on taking care of personal needs and thinking of self apart from a profession. Self-Care includes the need for physical or emotional health, balancing time between work and life, negative personal transformations due to job expectations, and feelings of demoralization, uncertainty, fear, anxiety, or guilt. As one commenter shared: "I've literally been broken down by teaching. I have run out of patience and I feel bad everyday because I know I'm not my best self." Another echoed this concern: "I relate so much! I'm only going on to teaching for a year now, my mental health is in shambles & I'm not as happy as I was when I started." The theme of Self-Care was noted in 31.1% of the comments. Post 1 (PHW) had the highest representation with 52.0% and post 8 (SE) had the lowest with 11.1%.</p> <hd id="AN0188424241-19">Social Structures</hd> <p>Comments within the theme of Social Structures included statements representing, defending, or speaking to political, social or cultural perspectives. This could be discussion of school systems, the political environment, religion, inclusivity, and morality. Opposing viewpoints and contrasting arguments were also housed within this theme. For example, one commenter spoke to one perspective on teaching as a job: "No offense..but. You get weekends off, holidays off, and summers off. Yes, you work a lot during the week. BUT." Another shared a similar concern connected to teacher performance: "What was your schools drop out rate proficiency Rating that's what teachers need to worry about not this Distraction." In contrast, one commenter focused more on the current state of education: "As a retired teacher, I think it is a very different education system. I would find it very challenging today." The theme of Social Structures was noted in 22.0% of the comments. Post 2 (WC) had the highest representation with 50.0% and post 4 (PHW) had the lowest with 4.3%.</p> <hd id="AN0188424241-20">Surface Level</hd> <p>The theme of Surface Level involved comments that were off topic, light commentary without substance, general humor, self-promotion, or sarcasm. These comments did not add to the discussion but instead offered services, asked broad questions, or made disconnected statements. One example disregarded the post altogether to ask a request of the original poster: "Hey I am a future teacher doing a research project on why teachers leave and was wondering if you will be willing to take a survey for me?" Similarly, some commenters within this theme asked questions that could be considered somewhat tangent to the original post, such as: "What grades were you teaching?" Others added comments that would be considered advertisements for services. One example connected the teacher narrative from the post to sell a service: "I can help you work from home. I taught for over 30 years. It can be extra $ or full time $, your choice. I wouldn't go back for s million $!" The theme of Surface Level was noted in 11.6% of the comments. Post 7 (SE) had the highest representation with 27.0%. This theme was absent from posts 2 (WC), 4 (PHW), and 9 (PHW).</p> <hd id="AN0188424241-21">Trend</hd> <p>The theme of Trend spoke to leaving the classroom as ongoing movement, including statements of doing the same in the future. This theme also included discussion of school change, loss of efficacy, and transformation of the profession. Many discussed the present environment in contrast to the past, such as: "The drastically lower number of new, first-year teachers is also considerable. College teaching programs are way down." And another similar perspective: "I'm wondering how many positions are just being dissolved because they can't get them filled. Those who remain are taking on extra duties." Other commenters simply responded how the original post encouraged them to follow a similar path: "This just solidified me quitting. I feel the exact same way." The theme of Trend was noted in 11.1% of the comments. Post 8 (SE) had the highest representation with 33.3%. This theme was absent from posts 2 (WC) and 5 (RS).</p> <hd id="AN0188424241-22">Stakeholders</hd> <p>The theme of Stakeholders spoke to student populations and non-teacher stakeholders. While this theme housed all comments explicitly noted from non-teacher stakeholders, primary discussions included statements of positive or negative student behaviors or influence on decisions to leave, student blame, and student affirmation. Some commenters homed in on the student perspective. For example: "By far the best teacher I've ever had all your students will miss you even though I was one of your troubled students your we always awesome." Others shared from a related field or service, such as: "As a school social worker, thank you for your advocacy!" The theme of Stakeholders was noted in 11.1% of the comments. Post 5 (RS) had the highest representation with 30.0%. This theme was absent from posts 3 (PHW), 8 (SE), and 10 (PHW).</p> <hd id="AN0188424241-23">Advice</hd> <p>The final theme of Advice included calls for help, questions about current or former teaching contexts, suggestions, or calls for connection. Examples from the comments include: "I'm in Texas and I'm in college for elementary education do you think that it's a good decision or should I try to move somewhere else." Other questions focused on the issues involved with leaving, for example: "What jobs can we get when we leave? #helpmeplease!" Some simply were reaching out for more help: "Could someone please message me with some advice about this because I am struggling and considering this and don't know what to do." The theme of Advice was present in 11.2% of the comments. Post 2 (WC) had the highest representation with 33.3%. This theme was absent from posts 6 (RS) and 8 (SE).</p> <hd id="AN0188424241-24">Discussion</hd> <p>This study explored how TikTok users respond to video posts created by former teachers sharing their stories of leaving the profession, with a particular focus on the themes, levels of engagement, and motivations driving user interactions. By analyzing comments and engagement metrics, the study revealed key patterns that reflect the convergence of personal connection, emotional resonance, and algorithmic influence. The findings are situated within the broader context of teacher attrition, offering insights into how social media platforms like TikTok serve as spaces for emotional support, critical discourse, and the amplification of systemic issues within the education sector. These findings contribute to the growing body of literature on digital engagement in social platforms and the implications for understanding educational challenges like teacher turnover.</p> <hd id="AN0188424241-25">How Do Outsiders Respond to Teachers' Stories of Quitting on TikTok?</hd> <p></p> <hd id="AN0188424241-26">Levels of Engagement</hd> <p>Findings indicated that there can be a discernable scale of patterned interactions ranging from shallow to deep. The study found that, despite high view counts, the percentage of users who "liked" posts was considerably larger than those who commented. General engagement for users as commentors was low, representing only 1.0% of the sample. Of note is Post 6 discussing relationships and support. While this post had the largest viewership of the sample with 4,600,000 views, it only received 1,609 comments which represents less than 0.1% of the overall views. In contrast, user likes for this post were much higher, with 16.5% of viewers responding positively. This suggests that interacting via "likes" can serve as a quick, shallow, low-effort way for consumers of the posts to express approval without need for deeper connection. This is supported by existing research, which has noted that social media consumers utilize likes as a common form of simple engagement ([<reflink idref="bib28" id="ref79">28</reflink>]).</p> <p>Conversely, findings also indicated that response through commenting on posts could represent a deeper level of engagement. Commenting requires more effort, with users needing to articulate their thoughts, share personal experiences, or provide support which reflects a higher, or deeper, emotional investment. Across the video posts and comments analyzed in the study, the themes of "Affirmation" and "Connections" made up the overwhelming majority, suggesting that users were motivated to engage more deeply when they felt a personal connection to the content. This aligns with the literature in that commenting allows user to engage in social connection and communal support to enhance their sense of belonging ([<reflink idref="bib29" id="ref80">29</reflink>]).</p> <hd id="AN0188424241-27">Motivation</hd> <p>Along the spectrum of shallow to deep interaction, lies various motivations that cause users to interact within those ranges. Several key elements were both illustrated in the findings of this study and in alignment with the literature. The need for connection as motivation to comment was prevalent in findings again with many comments falling under the themes of "Affirmation" and "Connections" where users expressed support and shared experiences. This aligns with the idea that commenting allows users to curate interpersonal connections and gives them a platform to articulate their individual thoughts while seeking validation ([<reflink idref="bib27" id="ref81">27</reflink>]). Additionally, the study found that emotionally charged video posts, especially those coded as Personal Health and Wellness (PHW) contained elements of pathos and strong diction, received more comments. This is supported in the literature as users often comment to share their own emotional experiences and are motivated to comment when they feel an emotional connection to the content ([<reflink idref="bib15" id="ref82">15</reflink>]). Posts that are perceived as personally relevant or emotionally engaging prompt more user interaction. The study's findings support this by showing that most comments were directed at video posts discussing personal health and wellness, indicating that such content motivates deeper engagement. This also aligns with [<reflink idref="bib52" id="ref83">52</reflink>], who found that emotionally evocative content increases the likelihood of user comments.</p> <hd id="AN0188424241-28">Social Commentary</hd> <p>The findings related to sentiment and tone analysis indicated a discernable shift as it related to video themes. This shift occurred most notably around personal health and wellness with topics related to working conditions, professional comparisons, and relationships containing contrasting analyses. The study found that video posts discussing personal health and wellness elicited a strong emotional response from viewers, while video posts focused on working conditions and professional comparisons yielded a more analytical and critical tone from commenters. This may be representative of the desire to focus on supporting others where they have the agency to do so ([<reflink idref="bib29" id="ref84">29</reflink>]). For example, comments on personal health emphasized emotional support, affirmations, shared experiences, and overall positive messages while those addressing working conditions often received more contrasting commentary on systemic issues, jobs stress, and overall professional dissatisfaction. This may also be indicative of a willingness or comfort within the TikTok userbase to discuss matters of mental health and personal well-being ([<reflink idref="bib7" id="ref85">7</reflink>]).</p> <p>This contrasting shift aligns with broader social commentary about social and emotional health prevalent both in education and general professional spaces. These types of discussions are on the rise online, with many content creators on social media speaking specifically to mental health needs ([<reflink idref="bib39" id="ref86">39</reflink>]). Similarly, the results of this study reflect the idea that educators are seeking discourse and spaces where they can share and reflect on their personal emotional health and experience and the importance of self-care and mental well-being in the teaching profession.</p> <hd id="AN0188424241-29">Algorithm and Filter Bubbles</hd> <p>Results of the data analysis also indicate a need to address the role of algorithms and filter bubbles on both levels of engagement as it relates to the study's findings. Users were more likely to engage with content that resonated with their personal experiences, reinforcing the notion that algorithmic curation affects both the reach and depth of user engagement ([<reflink idref="bib3" id="ref87">3</reflink>]). The TikTok algorithm curates content based on users' previous interactions and continuously promotes videos that align with those users' interests. As a result, video posts analyzed in the study may have been shared with an audience that was already predisposed to engage in topics of education and teacher attrition ([<reflink idref="bib32" id="ref88">32</reflink>]). Additionally, the algorithm prefers media that generates the highest levels of engagement, so videos that resonate more emotionally with viewers, such as the PHW video posts, may get more visibility on the platform, which could explain the higher percentage of likes, comments, and shares. This aligns with the work of [<reflink idref="bib24" id="ref89">24</reflink>], who discusses the implications of recommendation algorithms in shaping user behavior on social media. This could reflect both the content's relevance and the algorithm's role in amplifying some content versus filter bubbling others.</p> <p>Echo chambers were also reflected in the themes of "Affirmation" and "Connections" as algorithmic manipulation may narrow the audience of visibility. If the sample of commenters and users that engaged in the set of video posts analyzed in the study was comprised primarily of educators who share similar experiences and sentiments, this could lead to narrow viewpoints and less diversity in data perspectives which fails to represent a wide range of opinions and engagement.</p> <hd id="AN0188424241-30">How Do These Types of Responses Reflect the Current Literature on Teacher Attrition?</hd> <p>The responses observed in this study align closely with existing literature on teacher attrition. A prominent theme in the comments was Affirmation as discussed, which often expressed encouragement, solidarity, and validation for the teachers' choices. This reflects findings in the literature that emphasize the importance of emotional support and self-care as protective factors against burnout and demoralization ([<reflink idref="bib50" id="ref90">50</reflink>]). Teacher burnout, characterized by emotional exhaustion, is a prevalent issue, and support systems are critical for mitigating its effects ([<reflink idref="bib30" id="ref91">30</reflink>]). Similarly, the focus on Personal Health and Wellness (PHW) in the responses addresses how narratives of self-care resonate with audiences, aligning with research that emphasizes the growing importance of prioritizing mental health and work-life balance in high-stress professions like teaching ([<reflink idref="bib42" id="ref92">42</reflink>]; [<reflink idref="bib51" id="ref93">51</reflink>]).</p> <p>Responses discussing Relationships and Support (RS) and Social Environment (SE) often included more analytical and critical commentary, reflecting systemic dissatisfaction. Research supports this, identifying organizational factors such as lack of professional respect, excessive workload, and rigid accountability measures as significant contributors to teacher attrition ([<reflink idref="bib13" id="ref94">13</reflink>]; [<reflink idref="bib20" id="ref95">20</reflink>]). Comments critiquing working conditions and policies mirror studies that link these systemic issues to teacher turnover and highlight the need for structural changes within educational environments ([<reflink idref="bib16" id="ref96">16</reflink>]; [<reflink idref="bib17" id="ref97">17</reflink>]). The engagement patterns also echo findings that show how demoralization—resulting from a disconnect between professional values and institutional realities—can compound feelings of dissatisfaction and drive attrition ([<reflink idref="bib42" id="ref98">42</reflink>]).</p> <p>Additionally, the study revealed that emotionally engaging and personally relevant content, particularly posts addressing PHW, elicited deeper levels of interaction, including comments sharing personal experiences and emotional support. This aligns with research by [<reflink idref="bib52" id="ref99">52</reflink>] and [<reflink idref="bib15" id="ref100">15</reflink>], which found that emotionally evocative content is more likely to prompt user engagement. The focus on sharing and connecting in these responses reflects a need for social validation and community, as noted by [<reflink idref="bib29" id="ref101">29</reflink>]. The algorithmic promotion of such content on TikTok likely amplifies its visibility, further reinforcing the literature's findings on how curated media can shape engagement patterns ([<reflink idref="bib24" id="ref102">24</reflink>]; [<reflink idref="bib46" id="ref103">46</reflink>]). Responses also illustrated contrasting tones between personal and systemic themes. Comments on PHW posts were predominantly supportive and empathetic, while those addressing systemic issues like working conditions often adopted a more critical perspective. This reflects a broader trend in teacher attrition literature, which acknowledges the interplay of individual well-being and structural challenges as dual contributors to teachers leaving the profession ([<reflink idref="bib26" id="ref104">26</reflink>]; [<reflink idref="bib45" id="ref105">45</reflink>]). The engagement data further aligns with the idea that addressing systemic issues requires framing them in a way that connects with audiences' values and lived experiences, as seen in the high engagement and share rates for SE video posts.</p> <p>Overall, the responses in this study support and extend the existing literature on teacher attrition by illustrating how personal and systemic factors are experienced and discussed in digital spaces. They highlight the critical role of emotional support, self-care, and structural reforms in addressing the ongoing issue of teacher turnover.</p> <hd id="AN0188424241-31">How Common Are These Various Types of Responses?</hd> <p>Frequency and commonality of different types of responses seemed to vary depending on a myriad of factors. PHW video posts attracted the most affirming comments (72.8% on average), while RS and SE posts prompted more analytical and critical feedback. Notably, post 7, discussing Social Environment, had the highest engagement rate (3.2% of comments and 3.6% of shares), suggesting that posts addressing systemic issues resonate broadly but require a specific framing to encourage interaction. This post also received the highest share rate among the sample at 3.6% which was significantly higher than the mean of 0.5%.</p> <p>One overarching pattern is the way the content is framed seems to influence how users respond. Video posts about Personal Health and Wellness (PHW) received the most affirming comments, suggesting that topics focused on well-being and self-care connect with users on a personal and emotional level, encouraging supportive responses. In comparison, videos about Relationships and Support (RS) and Social Environment (SE) led to more analytical and critical comments, showing that users are more likely to discuss systemic or broader issues when the content goes beyond individual experiences. Post 7, which focused on the Social Environment, stood out with the highest engagement and share rates, indicating that content addressing larger societal or systemic challenges can resonate with a wide audience when presented effectively. The high share rate (3.6%) suggests users not only engaged with the content but also felt motivated to spread it to others, highlighting the potential for systemic discussions to inspire broader conversations and advocacy. This demonstrates that the themes of the video posts play a significant role in shaping both the type and level of user interaction.</p> <hd id="AN0188424241-32">Limitations and Future Research</hd> <p>This study has possible limitations that are important to discuss. First, the impact of social media algorithms cannot be understated. The algorithm used by TikTok to present users with content is not open or transparent. Instead, the platform simply describes the process as based on user interactions with prior content ([<reflink idref="bib48" id="ref106">48</reflink>]). Although this study used a new account in an incognito browser, it is impossible to identify how content was served beyond the selected keyword search. A second limitation is from the random sample of 10 video posts. While this number was chosen to allow for a reasonable analysis of the comments, an extended sample of posts may provide greater nuance in the results. Finally, this study represented a sample of comments from videos taken during a single snapshot of time. It is possible that some of the posts would have greater numbers of comments or vary in theme with more exposure to users over time.</p> <p>Future research should prioritize expanding the sample size to include a broader range of posts and user comments. This would increase the generalizability of findings and capture a wider variety of responses. Additionally, research would benefit from cross-platform analyses to compare engagement patterns on TikTok with other social media platforms, such as Instagram, Facebook, Twitter, etc. This would enhance understanding of platform-specific dynamics in responses to teacher attrition narratives.</p> <p>Disaggregating data by identifying markers such as commenter demographics, geographic location, professional background, age, etc. could enhance this study, as well as allow for more specific and detailed insights into how different groups engage with this content. Furthermore, expanding on the definition and descriptions of the levels of engagement observed and discussed within this study would contribute exponentially to the literature on social media engagement and motivation in the field of education and beyond. Investigating this continuum of shallow to deep responsive interactions could shed light on the psychological and social drivers of social media interactions, which could in turn yield more public discourse on the role of social media in teacher attrition.</p> <hd id="AN0188424241-33">Conclusions</hd> <p>This study explored how TikTok users respond to teachers' stories about leaving the profession, showing clear patterns in how people engage with this content. Posts focused on personal health and wellness received the most affirming and supportive responses, while those addressing systemic issues prompted more critical and analytical feedback. These findings align with existing research, specifically the importance of emotional support, self-care, and addressing larger systemic challenges in reducing teacher attrition. The findings also suggest that social media platforms, particularly those that prioritize short-form video content and community engagement, can serve as public spheres for processing and amplifying the complexities of teacher attrition. Additionally, the role of TikTok's algorithm emerged as an impactful factor, with its ability to personalize content amplifying engagement with specific themes while potentially narrowing the range of perspectives. This raises questions about how social media platforms influence public discussions on both professional and societal issues.</p> <p>This research offers a unique perspective on the issue of teacher attrition and shows how social media can act as both a space for emotional connection and a forum for critical conversations about systemic problems in education. Even considering the influence of social media algorithms on content exposure, the patterns found in the comments should not be discounted. In agreement or not, users felt compelled to connect, share stories, and continue a discussion beyond the initial post. While prior studies have documented why teachers leave, this analysis uncovers how those stories are received by the public and how that reception reflects broader attitudes toward the teaching profession, burnout, and self-preservation.</p> <p>The study also contributes to literature of the utilized theories by demonstrating the applicability of Uses and Gratifications Theory, emotional attachment theory, and social cognitive theory in understanding user behavior in educational discussions online. User responses on TikTok align with these frameworks by showing how emotional resonance, identity affirmation, and normative social behaviors shape digital engagement. These theoretical insights offer an updated and focused way to understand how cultural narratives around teaching are constructed and sustained in digital spaces.</p> <p>Teacher attrition is a complex and continuing issue that still requires a solution. While social media may not provide the answer, it may provide a wider view of the intricate factors that play into why teachers leave and how society will choose to respond. By better understanding how users engage with teacher narratives, we can create strategies that address the personal and professional challenges teachers face. These findings offer a starting point for more research into the role of digital platforms in shaping conversations around important social and professional issues.</p> <ref id="AN0188424241-34"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref9" type="bt">1</bibl> <bibtext> Forrest Kaiser</bibtext> </blist> <blist> <bibtext>Graph https://orcid.org/0000-0002-5261-9169</bibtext> </blist> <blist> <bibl id="bib2" idref="ref8" type="bt">2</bibl> <bibtext> The Institutional Review Board at The University of Texas at Tyler has determined that this study is not research involving human subjects as defined by DHHS and FDA regulations. Therefore, this project does not require further IRB oversight. Protocol number: 2023-137-UT. Institutional Review Board Office 1100 East Lake Street, Suite 330 Phone: 903-877-7632 Email: irb@uthct.edu</bibtext> </blist> <blist> <bibl id="bib3" idref="ref11" type="bt">3</bibl> <bibtext> Informed consent for information published in this article was not obtained because data came from publicly available social media sources.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref29" type="bt">4</bibl> <bibtext> The authors received no financial support for the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref30" type="bt">5</bibl> <bibtext> The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref7" type="bt">6</bibl> <bibtext> The data that support the findings of this study are available from the corresponding author (FK), upon reasonable request.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref85" type="bt">7</bibl> <bibtext> Data Availability Statement included at the end of the article</bibtext> </blist> </ref> <ref id="AN0188424241-35"> <title> References </title> <blist> <bibtext> Aguilar E. 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Philosophy, 112(4), 233–238. https://doi.org/10.31489/2023ph4/233-238</bibtext> </blist> </ref> <aug> <p>By Forrest Kaiser and Jennifer Lane</p> <p>Reported by Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib17" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib16" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib22" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib35" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib26" firstref="ref14"></nolink> <nolink nlid="nl6" bibid="bib51" firstref="ref15"></nolink> <nolink nlid="nl7" bibid="bib18" firstref="ref16"></nolink> <nolink nlid="nl8" bibid="bib33" firstref="ref17"></nolink> <nolink nlid="nl9" bibid="bib13" firstref="ref18"></nolink> <nolink nlid="nl10" bibid="bib12" firstref="ref19"></nolink> <nolink nlid="nl11" bibid="bib31" firstref="ref21"></nolink> <nolink nlid="nl12" bibid="bib45" firstref="ref22"></nolink> <nolink nlid="nl13" bibid="bib41" firstref="ref23"></nolink> <nolink nlid="nl14" bibid="bib50" firstref="ref24"></nolink> <nolink nlid="nl15" bibid="bib23" firstref="ref25"></nolink> <nolink nlid="nl16" bibid="bib42" firstref="ref26"></nolink> <nolink nlid="nl17" bibid="bib20" firstref="ref27"></nolink> <nolink nlid="nl18" bibid="bib19" firstref="ref28"></nolink> <nolink nlid="nl19" bibid="bib40" firstref="ref31"></nolink> <nolink nlid="nl20" bibid="bib49" firstref="ref32"></nolink> <nolink nlid="nl21" bibid="bib44" firstref="ref33"></nolink> <nolink nlid="nl22" bibid="bib43" firstref="ref35"></nolink> <nolink nlid="nl23" bibid="bib53" firstref="ref37"></nolink> <nolink nlid="nl24" bibid="bib29" firstref="ref38"></nolink> <nolink nlid="nl25" bibid="bib34" firstref="ref39"></nolink> <nolink nlid="nl26" bibid="bib15" firstref="ref43"></nolink> <nolink nlid="nl27" bibid="bib52" firstref="ref44"></nolink> <nolink nlid="nl28" bibid="bib14" firstref="ref45"></nolink> <nolink nlid="nl29" bibid="bib32" firstref="ref46"></nolink> <nolink nlid="nl30" bibid="bib47" firstref="ref47"></nolink> <nolink nlid="nl31" bibid="bib36" firstref="ref51"></nolink> <nolink nlid="nl32" bibid="bib37" firstref="ref52"></nolink> <nolink nlid="nl33" bibid="bib38" firstref="ref53"></nolink> <nolink nlid="nl34" bibid="bib24" firstref="ref54"></nolink> <nolink nlid="nl35" bibid="bib46" firstref="ref55"></nolink> <nolink nlid="nl36" bibid="bib25" firstref="ref58"></nolink> <nolink nlid="nl37" bibid="bib11" firstref="ref68"></nolink> <nolink nlid="nl38" bibid="bib21" firstref="ref70"></nolink> <nolink nlid="nl39" bibid="bib48" firstref="ref71"></nolink> <nolink nlid="nl40" bibid="bib10" firstref="ref76"></nolink> <nolink nlid="nl41" bibid="bib28" firstref="ref79"></nolink> <nolink nlid="nl42" bibid="bib27" firstref="ref81"></nolink> <nolink nlid="nl43" bibid="bib39" firstref="ref86"></nolink> <nolink nlid="nl44" bibid="bib30" firstref="ref91"></nolink>
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Why Did You Leave? A Content Analysis of Comments to Former Teacher Posts on TikTok
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Forrest+Kaiser%22">Forrest Kaiser</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5261-9169">0000-0002-5261-9169</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jennifer+Lane%22">Jennifer Lane</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22SAGE+Open%22"><i>SAGE Open</i></searchLink>. 2025 15(3).
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 16
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Social+Media%22">Social Media</searchLink><br /><searchLink fieldCode="DE" term="%22Video+Technology%22">Video Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Faculty+Mobility%22">Faculty Mobility</searchLink><br /><searchLink fieldCode="DE" term="%22Career+Change%22">Career Change</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Persistence%22">Teacher Persistence</searchLink><br /><searchLink fieldCode="DE" term="%22Teachers%22">Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Disclosure+%28Individuals%29%22">Self Disclosure (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Social+Support+Groups%22">Social Support Groups</searchLink><br /><searchLink fieldCode="DE" term="%22Content+Analysis%22">Content Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1177/21582440251379513
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 2158-2440
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Motivations for commenting on social media vary greatly and are driven by multiple factors including personal interests, political leaning, and algorithmic influence. This study used a thematic content analysis of comments on the TikTok platform to explore how users respond to videos created by former teachers sharing their stories of leaving the profession. Comment data were collected from a sample of posts explicitly sharing narratives of leaving and analyzed through a four-step mixed methods process. The researchers noted that words of affirmation had the highest representation in all comments, and included thoughts of encouragement, solidarity, acknowledgment, confirmation, and support. Users seeking connections had the next highest representation and involved user responses to extend the post to different situations, build on the ideas conveyed, or share personal feelings. Finally, discussions on self-care were the third highest and represented comments that focused on taking care of personal needs and thinking of self apart from a profession. By analyzing comments and engagement metrics, the study revealed key patterns on how users connect with others, express support, share personal experiences, and engage in discussions. The findings may offer insights into how social media platforms like TikTok may serve as spaces for emotional support, critical discourse, and the amplification of systemic issues within the education sector. These findings contribute to the growing body of literature on digital engagement and its implications for understanding educational challenges like teacher turnover.
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  Data: 2025
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  Data: EJ1487275
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      – Type: doi
        Value: 10.1177/21582440251379513
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
    Subjects:
      – SubjectFull: Social Media
        Type: general
      – SubjectFull: Video Technology
        Type: general
      – SubjectFull: Faculty Mobility
        Type: general
      – SubjectFull: Career Change
        Type: general
      – SubjectFull: Teacher Persistence
        Type: general
      – SubjectFull: Teachers
        Type: general
      – SubjectFull: Self Disclosure (Individuals)
        Type: general
      – SubjectFull: Social Support Groups
        Type: general
      – SubjectFull: Content Analysis
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      – SubjectFull: Algorithms
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      – SubjectFull: Feedback (Response)
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    Titles:
      – TitleFull: Why Did You Leave? A Content Analysis of Comments to Former Teacher Posts on TikTok
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            NameFull: Forrest Kaiser
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            NameFull: Jennifer Lane
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            – D: 01
              M: 07
              Type: published
              Y: 2025
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              Value: 3
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