Original Paper
Abstract
Background: Early maladaptive schemas (EMSs) are pervasive, self-defeating patterns of thoughts and emotions underlying most mental health problems and are central in schema therapy. However, the characteristics of EMSs vary across demographics, and despite the growing use of online mental health communities (OMHCs), how EMSs manifest in these online support-seeking environments remains unclear. Understanding these characteristics could inform the design of more effective interventions powered by artificial intelligence to address online support seekers’ unique therapeutic needs.
Objective: We aimed to uncover associations between EMSs and mental health problems within OMHCs and examine features of EMSs as they are reflected in OMHCs.
Methods: We curated a dataset of 29,329 posts from widely accessed OMHCs, labeling each with relevant schemas and mental health problems. To identify associations, we conducted chi-square tests of independence and calculated odds ratios (ORs) with the dataset. In addition, we developed a novel group-level case conceptualization technique, leveraging GPT-4 to extract features of EMSs from OMHC texts across key schema therapy dimensions, such as schema triggers and coping responses.
Results: Several associations were identified between EMSs and mental health problems, reflecting how EMSs manifest in online support-seeking contexts. Anxiety-related problems typically highlighted vulnerability to harm or illness (OR 5.64, 95% CI 5.34-5.96; P<.001), while depression-related problems emphasized unmet interpersonal needs, such as social isolation (OR 3.18, 95% CI 3.02-3.34; P<.001). Conversely, problems with eating disorders mostly exemplified negative self-perception and emotional inhibition (OR 1.89, 95% CI 1.45-2.46; P<.001). Personality disorders reflected themes of subjugation (OR 2.51, 95% CI 1.86-3.39; P<.001), while posttraumatic stress disorder problems involved distressing experiences and mistrust (OR 5.04, 95% CI 4.49-5.66; P<.001). Substance use disorder problems reflected negative self-perception of failure to achieve (OR 1.83, 95% CI 1.35-2.49; P<.001). Depression, personality disorders, and posttraumatic stress disorder were also associated with 12, 9, and 7 EMSs, respectively, emphasizing their complexities and the need for more comprehensive interventions. In contrast, anxiety, eating disorder, and substance use disorder were related to only 2 to 3 EMSs, suggesting that these problems are better addressed through targeted interventions. In addition, the EMS features extracted from our dataset averaged 13.27 (SD 3.05) negative features per schema, with 2.65 (SD 1.07) features per dimension, as supported by existing literature.
Conclusions: We uncovered various associations between EMSs and mental health problems among online support seekers, highlighting the prominence of specific EMSs in each problem and the unique complexities of each problem in terms of EMSs. We also identified EMS features as expressed by support seekers in OMHCs, reinforcing the relevance of EMSs in these online support-seeking contexts. These insights are valuable for understanding how EMS are characterized in OMHCs and can inform the development of more effective artificial intelligence–powered tools to enhance support on these platforms.
doi:10.2196/59524
Keywords
Introduction
Background
Over recent years, mental health problems have become increasingly prevalent worldwide [-]. However, access to professional therapy remains limited for many individuals due to high treatment costs and a shortage of trained mental health professionals [-]. As a result, a growing number of individuals are seeking support for their problems through online mental health communities (OMHCs) [-]. These communities provide a more accessible alternative to professional therapy [,], allowing individuals to share their distressing experiences and receive peer support to help them cope [,]. These problems, typically shared through posts within OMHCs, not only reveal support seekers’ struggles but also reflect the underlying dysfunctional beliefs contributing to their distress. These insights are crucial in shaping more personalized and effective online interventions for support seekers [,].
A set of dysfunctional beliefs commonly present in OMHC posts is early maladaptive schemas (EMSs) [,]. Central to schema therapy (ST), EMSs are pervasive, self-defeating beliefs formed in childhood and often persist into adulthood. Young et al [] identified 18 distinct types of EMSs (
Table 1) that distort worldviews and are typically associated with mental health problems, such as anxiety [-]. Understanding these associations provides a more reliable method for anticipating potential schemas based on a mental health diagnosis, enabling proactive and targeted therapeutic interventions [,,]. Similarly, recognizing the unique features of each schema (eg, “I’m incompetent when it comes to achievement,” corresponding to the failure to achieve schema) helps inform targeted interventions (eg, setting small, realistic goals to foster a sense of accomplishment). By addressing these schemas, these interventions can enhance therapy effectiveness and improve treatment outcomes.
However, the characteristics of these EMSs can vary across demographic groups. For example, Cámara and Calvete [] identified a strong association between the failure schema and depression in Spanish university students. However, Wright et al [] did not report such an association in their study of a US cohort. Similarly, Balsamo et al [] did not observe a relationship between the failure schema and depression among young adults in Italy. Likewise, OMHCs likely present a demographically distinct population of online support seekers reflecting unique EMS characteristics [,-]. Gaining a clearer understanding of these characteristics could provide valuable insights for policy making and the design of more effective digital therapeutic tools for this online support-seeking population. However, how EMSs are reflected in these communities remains largely unexplored, despite their growing importance in mental health support.
This research gap largely stems from the lack of tools for accurately identifying EMSs in the asynchronous, text-based environments of OMHCs. In professional practice, therapists use the Young Schema Questionnaire (YSQ) [] to assess patients’ EMSs through clinically validated statements of dysfunctional beliefs, which patients rate on a scale from 1 (“completely untrue of me”) to 6 (“describes me perfectly”). Replicating this structured assessment in OMHCs is challenging due to the unstructured nature of online support-seeking interactions [,,]. Overcoming this challenge requires interpreting EMSs directly from the text, which necessitates specialized natural language processing techniques to identify EMSs in OMHC posts. Recent advancements in large language models (LLMs) have demonstrated remarkable performance in complex language tasks, such as text classification, retrieval, and generation, which require nuanced interpretation of unstructured texts [-]. These models can capture subtle meanings in textual discourse, such as recognizing that the phrase “dark tunnel” in “I just feel like I’m stuck in a dark tunnel, and there’s no way out” metaphorically conveys despair, isolation, and hopelessness []. LLMs have also been used to predict mental health problems, such as depression, from online conversations [-] and have recently been applied to predict EMSs in OMHC posts [].
| EMS | Description | Examples from YSQ |
| Abandonment/instability | The perception that others will not be reliable enough to provide emotional support or connection, leading to a sense of instability and insecurity | “I worry that people I feel close to will leave me or abandon me.” |
| Approval seeking/recognition-seeking | A constant desire for approval, recognition, or acceptance from others to the extent that one compromises their authentic self | “Unless I get a lot of attention from others, I feel less important.” |
| Defectiveness/shame | A deep-seated belief that one is flawed, unlovable, or inferior, leading to feelings of shame and inadequacy | “I cannot understand how anyone could love me.” |
| Dependence/incompetence | A belief in one’s inability to handle daily responsibilities or make appropriate decisions independently | “I feel that I need someone I can rely on to give me advice about practical issues.” |
| Emotional deprivation | The belief that one’s emotional needs will not be adequately met by others | “For much of my life, I haven’t felt that I am special to someone.” |
| Emotional inhibition | The suppression or inhibition of emotions, often due to a fear of losing control or being overwhelmed by intense feelings | “People see me as uptight emotionally.” |
| Enmeshment/undeveloped self | An overly intense emotional attachment and proximity to one or more important individuals (typically parents), which hinders the process of becoming an independent individual and impedes normal social development | “I often found myself constantly turning to my parents for approval in every decision I made.” |
| Entitlement/grandiosity | An exaggerated sense of self-importance and a belief that one deserves special treatment | “I get very irritated when people won’t do what I ask of them.” |
| Failure to achieve | The belief that one has failed or will inevitably fail in achieving personal and practitioner goals, leading to a sense of underachievement | “I am humiliated by my failures and inadequacies in the work (or school) sphere.” |
| Insufficient self-control/self-discipline | An inability to control impulses, leading to difficulty in achieving long-term goals. | “I often do things impulsively that I later regret.” |
| Mistrust/abuse | A belief that others are likely to deceive, take advantage of, or harm the person emotionally or physically | “I have been physically, emotionally, or sexually abused by important people in my life.” |
| Negativity/pessimism | A pervasive focus on the negative aspects of life while neglecting the positive aspects | “People close to me consider me a worrier.” |
| Punitiveness | The belief that harsh punishment is deserved for perceived mistakes or failures | “I am a bad person who deserves to be punished.” |
| Self-sacrifice | The belief that one must meet the needs of others at the expense of one’s own needs and desires | “No matter how much I give, I feel it is never enough.” |
| Social isolation/alienation | The belief that one is different from others, leading to a sense of isolation and difficulty connecting with others | “I always feel on the outside of groups.” |
| Subjugation | A tendency to prioritize others’ needs and desires over one’s own because one feels coerced | “I let other people have their way, because I fear the consequences.” |
| Unrelenting standards/hypercriticalness | The belief that one must meet high standards of performance, usually to avoid criticism | “I can’t let myself off the hook easily or make excuses for my mistakes.” |
| Vulnerability to harm or illness | The belief that catastrophic events are imminent, leading to excessive worry and anxiety about potential harm or illness | “I feel that the world is a dangerous place.” |
Objectives
Using the EMS classifiers from the recent study on EMS prediction [] and leveraging recent LLMs, we can identify EMS labels within large volumes of unstructured OMHC texts. This enables us to (1) uncover associations between EMSs and mental health problems within OMHCs and (2) examine how features of EMSs are reflected in online support-seeking populations. These insights will guide the development of online interventions powered by artificial intelligence (AI) and grounded in ST, tailored to meet the unique therapeutic needs of online support seekers [].
Methods
Curating the Dataset and Identifying EMSs
We curated posts shared by support seekers in 3 highly frequented OMHCs, namely 7-Cups [], Beyond-Blue [], and Patient [], from 2013 to November 2023. Using a custom Python-based web crawler developed for this study, we collected posts from subcommunities focusing on anxiety, depression, posttraumatic stress disorder (PTSD), personality disorders (PDs), eating disorders (EDs), and substance use disorders (SUDs). These mental health problems are prevalent among adults [,] and are often treated with ST [].
To identify EMSs in OMHC posts, we used the entailment-based prediction model (EPM) from a recent study []. EPM predicts EMSs from a post by leveraging textual entailment, a sentence-level inference technique from natural language processing []. In textual entailment, a statement entails a hypothesis h if a human reader would infer that h is likely true based on t []. EPM computes the entailment between sentences in a post and statements from the YSQ. When a sentence entails a YSQ statement, the latter serves as an “explanation” for assigning the corresponding EMS label. For instance, the sentence “Since then I either try to find excuses not to ride or when I do try to ride, I have to push myself and have massive panic attacks.” entails the YSQ statement “I often feel that I’m going to have an anxiety attack.” This YSQ statement corresponds to the vulnerability to harm or illness schema, and the EPM labels the post with this schema. We used the Text-To-Text Transfer Transformer (Google; T5-LLM []) in EPM to compute entailment and assign EMS labels to each post.
The 18 EMSs in Table 1 are each represented as a binary categorical variable, where a value 1 indicates the relevance of a schema to an OMHC post, and 0 indicates nonrelevance. In a similar way, we labeled each post with 6 binary categorical variables, each corresponding to one of the mental health problems examined in this study.
Uncovering Associations Between EMSs and Mental Health Problems
Using these categorical variables, we constructed 2×2 contingency tables (Table S1 in ) and calculated the expected frequency, Eij (equation S1 in ), and the χ2 statistic (equation S2 in ) for each pair of schema and mental health problem []. Each χ2 value was compared to the critical value from the χ2 distribution table with 1 df and a significance level of 0.05. For each χ2 value that exceeded the critical value, we rejected the null hypothesis to indicate a statistically significant association between a schema and mental health problem. To quantify the strength of association for each statistically significant pair, we calculated the odds ratio (OR), ORems_mhp (equation S3 in ), and its 95% CI, ORems_mhp_95%CI (equation S4 in ) [,]. Following established guidelines for interpreting ORs [], we considered an association inconclusive if the 95% CI of the OR included the null value of 1.
Examining Features of EMSs With Group-Level Case Conceptualization
We further examined how online support seekers express their schemas by analyzing specific features reflected in their online posts. For this purpose, we used the case conceptualization technique, which is commonly used by therapists to identify key features related to patients’ beliefs and mental health problems, thus facilitating personalized therapeutic interventions. In ST, case conceptualization focuses on several dimensions, including schema triggers (situations that activate the schema), emotions (associated feelings), negative thoughts (irrational beliefs), coping responses (behaviors and reactions), and bodily sensations (physical and physiological experiences) [].
We adapted this case conceptualization to our dataset using a data-driven AI approach, which we refer to as group-level case conceptualization. First, we prepared the data by using the EPM to identify sentences from OMHC posts that entailed specific YSQ statements, as outlined in the Curating the Dataset and Identifying EMSs section. These sentences reflected the dysfunctional beliefs and respective schemas established in the YSQ. We grouped these sentences according to their schema, resulting in a distribution of sentence counts by EMSs, which ranged from 8494 for social isolation to 98 for subjugation. To derive group-level features for each schema, we randomly sampled 10% of the sentences (in , we demonstrate that the similarity scores between features extracted from different groups of randomly sampled sentences consistently average 0.79 (SD 0.09), which indicates substantial overlap in the features generated across groups. This validates the approach of conducting in-depth analysis on a single group of randomly sampled sentences for each schema and instructed GPT-4 (OpenAI; we used the model gpt-4-1106-preview for GPT-4) [] through a custom prompt (
Textbox 1) to extract common features among the sentences and categorize them along the dimensions of case conceptualization.
Identify every common features exhibited from the given sentences. The features should belong to one of the following dimension (a) Schema Triggers (What are the situations that trigger the emotions, negative thoughts, coping responses, and bodily sensations?) (feature should start with: Situation where...), (b) Emotions (What are the feelings involved?) (feature should start with: Feeling...), (c) Negative thoughts (What irrational thoughts are going through the mind?) (feature should start with: Thinking that...), (d) Coping Responses (What are the behaviors and reactions?) (feature should start with: Responding by...), (e) Bodily Sensations (What are the physical and physiological experiences with the body?) (feature should start with: Experiencing...). Provide more than 1 relevant samples from the given sentences for each feature.
If a dimension has feature(s), the output should be in the format as this example:
(d) Coping Responses:
** Destructive or impulsive actions when upset.
• “When I’m angry or frustrated, I sometimes lose control of my emotions and destroy things.”
• “Im 22, and I have this problem when I get angry I can't control myself I yell hit stuff around me and often I hurt myself.”
If a dimension does not have any feature, the output should be in the format as this example:
(d) Coping Responses:
**NO_FEATURES.
Given sentences:
Ethical Considerations
This study aligns with NUS-IRB Review Not Required guidelines by analyzing nonindividually identifiable data from OMHCs to explore the characteristics of EMSs. Specifically, we used textual content that was already anonymized through usernames and we further decoupled these pseudonyms and other identifying information from the data. In addition, the analysis focused exclusively on examining publicly available data, with no interactions with support seekers. This approach minimized the risks of introducing harmful or unsupportive content while also adhering to ethical guidelines and the responsible use of these online platforms [,].
Results
Dataset Statistics
Our dataset comprised 29,329 online posts in which support seekers shared their experiences with various mental health problems. Anxiety was the most frequently mentioned problem, appearing in 51.56% (15,149/20,329) of the posts, followed by depression, which appeared in 33.98% (9966/20,329) of the posts. PTSD, SUDs, PDs, and EDs correspondingly represented 8.75% (2565/20,329), 1.96% (576/20,329), 1.87% (548/20,329), and 1.79% (525/20,329) of the dataset. This distribution aligned with general sociodemographic trends in the prevalence of mental health problems. For example, anxiety is typically more prevalent than depression, while both are more common than PTSD, PDs, and EDs [,]. This suggests that the mental health problems discussed in OMHCs may reflect their real-world prevalence, suggesting that policies based on these trends could be effectively applied to online settings.
Regarding post length, the median sentence count was 10 (IQR 5-16). Word count showed similar variability, with a median of 214 words (IQR 124-356). This variability likely reflected the open nature of online support forums, where individuals can express themselves freely, unconstrained by the structured environments of in-person therapy. Unlike therapy sessions, where therapists guide conversations and encourage concise, focused responses, OMHCs allow support seekers to share their experiences through detailed, unfiltered narratives. Consequently, the dataset included both succinct and elaborate descriptions of mental distress.
As illustrated in Table 2, the distribution of EMSs, as predicted by EPM [], was nonuniform across the dataset. Posts more frequently involved schemas related to social isolation and vulnerability to harm or illness than schemas such as approval seeking and subjugation. We hypothesize that this skewed distribution resulted from a combination of societal, environmental, biological, and psychological factors. For instance, modern societal pressures, pervasive social media use, and global crises, such as the COVID-19 pandemic, may amplify feelings of isolation and vulnerability [,]. In contrast, schemas such as approval seeking and subjugation may be less common due to cultural factors, including the emphasis on individualism and self-reliance in many societies [].
| EMSs | Posts with EMSs, n (%) |
| Social isolation/alienation | 12820 (43.71) |
| Vulnerability to harm or illness | 10191 (34.75) |
| Dependence/incompetence | 5414 (18.46) |
| Abandonment/instability | 3736 (12.74) |
| Enmeshment/undeveloped self | 2942 (10.03) |
| Negativity/pessimism | 2777 (9.47) |
| Defectiveness/shame | 2451 (8.36) |
| Emotional inhibition | 2006 (6.84) |
| Emotional deprivation | 1916 (6.53) |
| Mistrust/abuse | 1641 (5.6) |
| Insufficient self-control/self-discipline | 1578 (5.38) |
| Self-sacrifice | 1530 (5.22) |
| Failure to achieve | 1316 (4.49) |
| Unrelenting standards/hypercriticalness | 1301 (4.44) |
| Punitiveness | 839 (2.86) |
| Entitlement/grandiosity | 487 (1.66) |
| Approval seeking/recognition seeking | 475 (1.62) |
| Subjugation | 276 (0.94) |
Associations Between EMSs and Mental Health Problems
Among all mental health problems, depression had the highest number of statistically significant associations with 12 out of the 18 EMSs (refer to Table S1 in for specific P values, ORs, and 95% CI of these associations). This was followed by PDs and PTSD, which had 9 and 7 associations, respectively. In contrast, anxiety, EDs, and SUDs showed fewer associations, with only 2 to 3 EMSs associated with these problems.
In Table S1 in , we present the strength of the association between specific schemas and particular mental health problems using ORs. Consistent with previous works [,], we used OR<1.5 to indicate small effect sizes (weak associations), OR<2.5 to indicate moderate effect sizes (moderate associations), OR<4.0 to indicate large effect sizes (strong associations), and OR>4.0 to indicate very large effect sizes (very strong associations). Higher ORs suggest stronger associations, indicating that certain EMSs are relatively more likely to be present in specific mental health problems observed in OMHCs compared to others.
For anxiety, the strongest association was observed with the vulnerability to harm or illness schema, reflecting a very large effect size. In contrast, insufficient self-control and emotional inhibition schemas exhibited weak associations with anxiety.
In the case of depression, schemas with strong associations included social isolation, approval-seeking, and emotional deprivation. Moderate associations were observed for abandonment, defectiveness, dependence, failure to achieve, and negativity. Meanwhile, unrelenting standards, entitlement, punitiveness, and self-sacrifice schemas showed weak associations.
For EDs, moderate associations were observed with the emotional inhibition, defectiveness, and self-sacrifice schemas.
In PDs, the subjugation schema exhibited a very strong association, followed by moderate associations for the abandonment, entitlement, enmeshment, defectiveness, punitiveness, and mistrust schemas. Weak associations were observed for emotional deprivation and social isolation.
PTSD showed a very strong association with the mistrust schema and strong associations with punitiveness and subjugation. The emotional deprivation schema demonstrated a moderate association with PTSD, while weak associations were observed for enmeshment, self-sacrifice, and abandonment.
For SUDs, a moderate association was observed with the failure to achieve schema, while the dependence schema exhibited a weak association.
Features of EMSs Extracted From Group-Level Case Conceptualization
Features of each schema were identified using GPT-4, as detailed in . On average, our group-level case conceptualization approach identified approximately 13 features per schema across the 5 dimensions of case conceptualization. Schema triggers, emotions, and negative thoughts each comprised approximately 3 features, followed by coping responses with about 2 features, and bodily sensations with 1 feature. Most features conveyed negative connotations. For instance, individuals with the abandonment schema often perceived themselves as burdens to others and frequently reported feelings of loneliness, anxiety, and emptiness.
These features also highlighted the unique characteristics of each schema. For instance, the punitiveness schema, which centers on self-blame, involved features, such as “situations where there is a fear of repeating past mistakes or events,” “feelings of guilt or shame over past actions or events,” “thinking that one cannot forgive oneself or others for past wrongdoings,” and “responding with self-harm or destructive behavior.” These features are elaborated on in the Discussion section.
Discussion
Principal Findings
Associations With EMSs Reflect Varying Complexities Among Mental Health Problems
The associations identified in this study highlight the varying complexities of mental health problems among online support-seeking populations. Depression exhibited numerous associations with EMSs, suggesting a considerable overlap with depression symptomatology. This indicates that EMSs may provide a valuable framework for understanding the diverse factors influencing the experience of depression, underscoring its multifaceted nature [-]. Similarly, the large number of associations between EMSs and either PDs or PTSD highlight the heterogeneous and complex nature of these mental health problems, emphasizing the need for personalized and comprehensive therapeutic approaches.
In contrast, fewer associations were observed between EMS and anxiety, EDs, and SUDs, respectively. This suggests more uniform schema-related underpinnings for these problems, suggesting that individuals with anxiety, EDs, or SUDs may present a more consistent and predictable symptomatology. Consequently, treatment strategies for these conditions could focus on targeting specific schema patterns rather than adopting broader, more comprehensive approaches.
The Prominence of “Vulnerability to Harm or Illness” in Anxiety Problems
The association observed between anxiety and vulnerability to harm or illness schema aligns with findings from previous studies, which have identified this schema in groups with higher anxiety levels, such as individuals affected by COVID-19 and college students [,,,,]. The very strong association found in this study suggests that individuals seeking support for anxiety in OMHCs are very likely to experience and express heightened feelings of vulnerability. This observation aligns with the core purpose of OMHCs: creating a supportive safe space for individuals to share their challenges and vulnerabilities.
In contrast, associations between anxiety and the insufficient self-control and emotional inhibition schemas, though consistent with previous offline studies [-], were weak in OMHCs. One possible explanation is that individuals participating in OMHCs may exhibit greater self-discipline, as their active participation reflects motivation for change and growth []. In addition, the anonymity of OMHCs likely encourages more open disclosure, mitigating tendencies for emotional inhibition [].
Overall, these findings suggest that anxiety-related problems discussed in OMHCs are prominently characterized by perceptions of vulnerability to harm and danger rather than deficits in self-control or emotional inhibition. This highlights the central role of vulnerability in the experiences of online support seekers with anxiety and underscores the importance of addressing these feelings in the development of online peer support interventions.
The Prominence of “Prolonged Unmet Interpersonal Needs” in Depression Problems
The associations between depression and schemas of social isolation, approval seeking, and emotional deprivation are consistent with previous research, suggesting that individuals with depression often experience social exclusion, seek external validation, and report unmet emotional needs [-]. These schemas showed strong associations in OMHCs, suggesting these schemas are more likely to appear and are central concerns for individuals seeking support for depression-related problems.
In contrast, schemas such as abandonment, defectiveness, dependence, failure to achieve, and negativity exhibited moderate associations, consistent with studies relating depression to struggles with fears of abandonment, low self-worth, reliance on others for emotional support, and pervasive pessimism [,-]. These schemas are likely to appear in OMHC discussions on depression but may not dominate the discourse to the same extent as those with strong associations.
In contrast, schemas such as unrelenting standards, entitlement, punitiveness, and self-sacrifice demonstrated weak associations. These schemas are less likely to emerge in OMHC discourse on depression, although these schemas have been identified as relevant to depression in previous studies [,,].
The varying strengths of association between these schemas indicate a focus on prolonged unmet interpersonal needs in depression-related discourse. Strongly associated schemas, such as social isolation, approval seeking, and emotional deprivation, highlight long-term difficulties in forming social and emotional connections. In addition, the abandonment, defectiveness, dependence, failure to achieve, and negativity schemas reflect interpersonal aspects, although seemingly primarily on the implications of unmet interpersonal needs. Indeed, depression is known to exacerbate interpersonal challenges, further intensifying fears of rejection, lowered self-esteem, interpersonal dependency, and dissatisfaction with both self and life [-]. In contrast, weakly associated schemas, such as unrelenting standards and entitlement, are less focused on unmet interpersonal needs and seem more related to self-directed or situational aspects of depression.
The Prominence of “Self-Neglect and Negative Self-Perception” in ED Problems
The association between the emotional inhibition schema and EDs aligns with previous research suggesting that individuals with disordered eating behaviors often use these behaviors to avoid confronting distressing emotions [-]. This avoidance hinders healthy emotional processing and could contribute to neglecting psychological well-being.
The defectiveness schema reflects deep-seated feelings of inadequacy and self-criticism, which are particularly prevalent in individuals with binge eating behaviors. These individuals often resort to binge eating as a coping mechanism to manage pervasive feelings of shame, self-criticism, and low self-worth [-].
The self-sacrifice schema reflects a tendency to prioritize others’ needs over one’s own well-being. This behavior is closely related to pathological altruism, which involves irrational behaviors aimed at promoting the welfare of others but with negative consequences for the individual []. In the context of EDs, previous studies have found that individuals engage in self-sacrifice driven by pathological altruism to cope with negative self-perception of inadequacy and defectiveness, often stemming from their maladaptive eating behaviors [-].
These schemas demonstrated moderate associations with EDs in OMHCs, suggesting that themes of self-neglect and negative self-perception are likely to emerge from the distress experienced by individuals seeking support for their EDs within these communities.
The Prominence of “Subjugation” in PD Problems
The strong association between the subjugation schema and PDs observed in this study aligns with findings from previous research on avoidant PD and borderline PD (BPD) [,,]. This association suggests that individuals discussing PD-related challenges in OMHCs are more likely to articulate struggles related to feeling oppressed by others. These struggles are often accompanied by fears of retaliation, humiliation, or rejection when expressing their true feelings and needs []. These fears can hinder their ability to assert themselves, establish boundaries, and manage conflicts effectively.
Moderate associations were uncovered between PDs and schemas such as abandonment, entitlement, defectiveness, mistrust, enmeshment, and punitiveness. While these schemas likely appear in discussions about PDs, they are less prominent compared to the subjugation schema. The abandonment, mistrust, defectiveness, and enmeshment schemas are frequently observed in individuals with BPD [,-], whereas entitlement is more frequently seen in individuals with narcissistic PD [], and punitiveness is associated with both BPD and avoidant PD [,].
This study also found weak associations between PDs and schemas such as emotional deprivation and social isolation. While consistent with earlier studies on BPD [,,], these findings suggest that these schemas are less emphasized in discussions about PDs within OMHCs.
Overall, themes of subjugation emerge as a central focus in PD problems discussed in OMHCs. These themes highlight patterns rooted in power dynamics, emotional oppression, and interpersonal dependency. They appear to overlap with other schemas, such as abandonment, defectiveness, entitlement, mistrust, enmeshment, and punitiveness. For instance, individuals who feel subjugated may develop a fear of abandonment if they challenge others’ expectations []. In contrast, schemas such as emotional deprivation and social isolation might be less prominent because they focus more on internal emotional states (eg, feelings of neglect or alienation) and less on the relational and power dynamics that are central to subjugation.
The Prominence of “Traumatizing Experiences” in PTSD Problems
The association between PTSD and the mistrust schema in OMHCs is consistent with research showing that individuals typically develop chronic mistrust following traumatic experiences involving betrayal, attachment disruptions, or abuse [-]. The very strong association suggests that mistrust is very likely to emerge from OMHC discussions on PTSD.
Similarly, the association between PTSD and the punitiveness schema highlights the prominent role of self-blame, which is frequently observed in individuals with PTSD [,-]. The association with the subjugation schema indicates that individuals may express feelings of being controlled or oppressed, with the anonymity afforded by these online platforms likely encouraging the disclosure of such sensitive experiences [,,,]. These strong associations suggest that these schemas are more likely to appear in OMHC posts about PTSD.
The association between PTSD and the emotional deprivation schema aligns with findings from previous research on traumatized populations, such as veterans and survivors of interpersonal trauma [,]. The moderate association observed in this study suggests that emotional neglect is likely to be reflected in OMHC discussions on PTSD.
Consistent with previous studies that identified relationships between PTSD and schemas such as enmeshment, self-sacrifice, and abandonment [,], this study identified similar associations. However, the associations observed in OMHCs are comparatively weak, suggesting that these schemas are less central to PTSD experiences shared within these online platforms.
Overall, the findings suggest that individuals seeking PTSD support in OMHCs are more likely to describe acute traumatizing experiences, reflecting schemas such as mistrust, punitiveness, subjugation, and emotional deprivation. In contrast, schemas such as enmeshment, self-sacrifice, and abandonment play a lesser role in these discussions.
The Prominence of “Perceived Failure” in SUD Problems
The association between SUDs and the failure to achieve schema is consistent with previous research, suggesting that individuals who perceive themselves as underachievers are more susceptible to substance misuse, and vice versa [,-]. The moderate association observed in OMHCs indicates that themes of inadequacy and failure are likely to emerge in posts related to SUDs.
In contrast, the weak association between the dependence schema and SUDs in OMHCs challenges the traditional understanding of the disorder, which often emphasizes a high degree of helplessness and complete reliance on others for daily functioning [-]. The weak association suggests that individuals with SUD seeking support in OMHCs may still retain some autonomy and self-sufficiency despite their struggles.
Extracted Features Reflect Known Characteristics of EMSs
The EMS features (features extracted by GPT-4 for each schema are as listed in ; the features referenced in this section are enclosed in quotes.) identified in OMHCs reflect the core characteristics of each schema and align with previous research. Notable examples are presented subsequently.
Several features of the vulnerability to harm or illness schema suggest that it is triggered when an individual “anticipates or experiences a panic attack,” “fears a negative health outcome,” “encounters social interactions or public places,” and “perceives everything is falling apart.” These are consistent with the findings of Young et al [], who noted that this schema is often activated by fears of uncontrollable external events. Similarly, McGinn et al [] found that heightened anxiety about bodily symptoms and low perceived control significantly increase vulnerability to panic. The looming vulnerability model by Riskind [] provides additional support for this, proposing that perceived vulnerability amplifies anxiety, manifesting in hypervigilance and beliefs such as “something bad is going to happen” and “one’s health is in serious danger.” In addition, Faustino et al [] related this schema to COVID-19–related anxiety, emphasizing how individuals with heightened vulnerability often interpret health concerns as severe. Dean et al [] observed that social exclusion intensifies vulnerability, perceived harm, and avoidant behaviors, aligning with the feature of “avoiding situations or places.” In addition, features related to somatic symptoms, such as “physical discomfort or pain related to anxiety” and “heavy breathing or heart palpitations,” were identified, consistent with the findings of McGinn et al [] on somatic responses to low perceived control and vulnerability. Another notable feature of this schema is “seeking reassurance or help.” Groves et al [] found that patients awaiting medical diagnoses often sought reassurance from nurses, alleviating feelings of vulnerability and fostering greater optimism about medical outcomes.
Features of the social isolation schema indicate an increased sensitivity to “potential rejection,” often leading individuals to “self-isolate” and “avoid social interactions or places.” This behavior aligns with the findings of Watson and Nesdale [] on how social rejection exacerbates isolation tendencies. Individuals with this schema often view themselves as “unworthy or unlovable,” believe “others are better off without them,” and believe they are “fundamentally different and unable to connect with others.” These beliefs mirror the low self-esteem associated with social isolation and exclusion, as highlighted by Stanley and Arora [] and Verkuyten and Thijs []. Emotional struggles, such as feelings of “hopelessness or helplessness,” and at times, “fear or anxiety,” are also prevalent. Johari et al [] reported similar themes among homeless youth in Iran, who frequently experienced loneliness, abandonment, and fears of social harassment. Despite these challenges, some individuals with this schema expressed a “desire for connection,” which is consistent with the observation by Cacioppo and Cacioppo [] that loneliness, while heightening sensitivity to social threats, can also drive efforts to seek and rebuild social bonds.
The emotional inhibition schema is characterized by a persistent fear of having “personal issues or emotions disclosed,” particularly in “social interaction” settings. This is consistent with findings by Young et al [] and Coggins and Fox [], who noted that individuals with this schema often suppress emotions out of concern that “others will judge or misunderstand them.” As a result, they frequently experience feelings of being “overwhelmed by anxiety and worry,” “scared or fearful,” and at times, “helpless or hopeless.” This schema is commonly triggered in situations where “negative outcomes are anticipated,” as observed by Iwamitsu et al [], who found that patients with breast tumor reported higher emotional distress when suppressing emotions after receiving their diagnosis. In addition, individuals with this schema often “avoid discussing personal issues” and “internalize feelings without seeking help.” These tendencies mirror the inhibition and withdrawal behaviors observed by Denollet and Duijndam [] in adults who had been socially inhibited, highlighting an aversion to open emotional expression and a reluctance to seek support from others.
Individuals with the mistrust schema often exhibit behaviors such as being “untrusting or suspicious” and perceiving others as “deceitful or have malicious intent,” particularly when their “personal safety or well-being feels threatened.” This aligns with the findings by Young et al [], who observed that individuals with this schema commonly view others as potential threats, making them feel vulnerable if they lower their guard. Similarly, LaMotte et al [] found that mistrust plays a role in the relationship between betrayal in romantic relationships and subsequent experiences of intimate partner violence. Individuals with this schema often believe they “will always be a targeted or wronged,” aligning with the concept of victim sensitivity [-], which involves a heightened expectation of untrustworthy motives in others and intense reactions to perceived injustices. Pilkington et al [] further highlighted the link between “mistrust” and accounts of violence, particularly in cases of domestic violence. Furthermore, those with this schema often “push others away” and prefer being “isolated or alone.” Smith and Rosen [] observed similar patterns among older clients receiving methadone treatment, who tended to self-isolate because of their mistrust. This self-isolation undermines the development of healthy relationships that are essential for recovery.
The failure to achieve schema reflects a persistent belief that one is “not good enough” and has “ruined everything,” leading to cycles of “self-criticism.” Young et al [] similarly noted that individuals with this schema often feel doomed to failure in both present and future endeavors. Wood et al [] found that such individuals frequently engage in social comparison, seeking reassurance by comparing themselves to others they perceive as less successful. This aligns with the observation that individuals often “compare themselves to peers or societal standards.” However, comparisons with those perceived as more successful can often intensify feelings of “jealousy,” “disappointment in themselves,” and “helplessness,” sometimes causing them to “give up trying” to improve their circumstances. Leahy [] observed that unfavorable comparisons in competitive environments can lead to envy, humiliation, helplessness, and withdrawal. This withdrawal reinforces feelings of failure, perpetuating the belief in one’s inability to succeed and deepening cycles of self-criticism.
Limitations
This study focused exclusively on 3 widely accessed OMHCs that use English as the primary mode of communication. To broaden the cultural and linguistic diversity of the sample, future research could explore OMHCs that use other languages and compare the findings of this study with subsequent research to verify whether our results extend to OMHCs in different sociolinguistic and cultural contexts, where schema expression may vary. In addition, while the anonymity of these platforms encourages openness, it limits access to sociodemographic data (eg, age, gender, and socioeconomic status), which might be important in shaping mental health perspectives and schema characteristics. Future studies could explore methods that allow for the ethical anonymous collection of demographic data or use validated techniques to infer demographic characteristics while maintaining user privacy, which is of utmost importance. These suggestions are essential for assessing the generalizability of the EMS characteristics uncovered in this study. Expanding the demographic and cultural scope in future research would help validate and deepen these findings, contributing to a more comprehensive understanding of EMSs in online support-seeking environments.
Conclusions
In this study, we examined the characteristics of EMSs within OMHCs, situating our findings within the existing literature. By analyzing a large dataset of posts from widely accessed OMHCs, annotated with EMS labels using a state-of-the-art EMS classifier, we identified key EMS features and various associations between EMSs and mental health problems. Notably, we found that depression, PDs, and PTSD were associated with a wide range of EMSs, highlighting the complexity of these multifaceted problems. These findings suggest that interventions for these problems could benefit from addressing multiple EMSs simultaneously. In contrast, mental health problems with fewer EMS associations, such as anxiety, may respond more effectively to more targeted interventions focused on specific schemas. In addition, we identified EMSs as more prominently associated with certain mental health problems in OMHCs. For example, anxiety-related posts typically center around vulnerability to harm, while depression-related posts reflect prolonged unmet interpersonal needs. Negative self-perception and self-neglect are prevalent in posts about EDs, while posts about PDs involve themes of subjugation. Posts about PTSD often describe traumatic experiences, and those concerning SUD are marked by themes of personal failure. A key contribution of this study is the novel group-level case conceptualization technique, which uses recent advanced LLMs and prompt engineering techniques to extract EMS features from OMHC posts. This approach provides valuable insights into how EMSs are expressed in online support-seeking environments and has the potential to inform personalized, ST-focused interventions. Overall, this study provides a foundational understanding of EMS characteristics in online support-seeking contexts and their role in shaping mental health experiences. Our findings highlight the potential for tailored, ST-based interventions in online peer support settings, which could enhance therapeutic outcomes and promote the mental well-being of individuals seeking support in these online communities.
Acknowledgments
This research and project is supported by the National Research Foundation, Singapore under its AI Singapore Programme (AISG-GC-2019-001-2B).
Data Availability
The datasets generated and analyzed during this study are available from the corresponding author on reasonable request.
Conflicts of Interest
None declared.
Multimedia Appendix 3
Associations between early maladaptive schemas and mental health problems.
DOC File , 64 KBReferences
- Mauz E, Walther L, Junker S, Kersjes C, Damerow S, Eicher S, et al. Time trends in mental health indicators in Germany's adult population before and during the COVID-19 pandemic. Front Public Health. Feb 23, 2023;11:1065938. [FREE Full text] [CrossRef] [Medline]
- Deng J, Zhou F, Hou W, Heybati K, Lohit S, Abbas U, et al. Prevalence of mental health symptoms in children and adolescents during the COVID-19 pandemic: a meta-analysis. Ann N Y Acad Sci. Feb 2023;1520(1):53-73. [FREE Full text] [CrossRef] [Medline]
- COVID-19 pandemic triggers 25% increase in prevalence of anxiety and depression worldwide. World Health Organization. Mar 2, 2022. URL: https://tinyurl.com/bdcykcjv [accessed 2024-01-03]
- Kantor V, Knefel M, Lueger-Schuster B. Perceived barriers and facilitators of mental health service utilization in adult trauma survivors: a systematic review. Clin Psychol Rev. Mar 2017;52:52-68. [FREE Full text] [CrossRef] [Medline]
- Kazdin AE, Blase SL. Rebooting psychotherapy research and practice to reduce the burden of mental illness. Perspect Psychol Sci. Jan 03, 2011;6(1):21-37. [CrossRef] [Medline]
- Mojtabai R, Olfson M, Sampson NA, Jin R, Druss B, Wang PS, et al. Barriers to mental health treatment: results from the National Comorbidity Survey Replication. Psychol Med. Dec 07, 2010;41(8):1751-1761. [CrossRef]
- Houston TK, Cooper LA, Ford DE. Internet support groups for depression: a 1-year prospective cohort study. Am J Psychiatry. Dec 01, 2002;159(12):2062-2068. [CrossRef] [Medline]
- Melling B, Houguet-Pincham T. Online peer support for individuals with depression: a summary of current research and future considerations. Psychiatr Rehabil J. 2011;34(3):252-254. [CrossRef] [Medline]
- Powell J, Clarke A. Investigating internet use by mental health service users: interview study. Stud Health Technol Inform. 2007;129(Pt 2):1112-1116. [Medline]
- Liu J, Kong J. Why do users of online mental health communities get likes and reposts: a combination of text mining and empirical analysis. Healthcare (Basel). Aug 31, 2021;9(9):1133. [FREE Full text] [CrossRef] [Medline]
- Strand M, Eng LS, Gammon D. Combining online and offline peer support groups in community mental health care settings: a qualitative study of service users' experiences. Int J Ment Health Syst. May 29, 2020;14(1):39. [FREE Full text] [CrossRef] [Medline]
- Suler J. The online disinhibition effect. Appl Psychoanal Stud. Jan 06, 2006;2(2):184-188. [CrossRef]
- Wongkoblap A, Vadillo MA, Curcin V. Researching mental health disorders in the era of social media: systematic review. J Med Internet Res. Jun 29, 2017;19(6):e228. [FREE Full text] [CrossRef] [Medline]
- Yazdavar AH, Mahdavinejad MS, Bajaj G, Thirunarayan K, Pathak J, Sheth A. Mental health analysis via social media data. In: Proceedings of the IEEE International Conference on Healthcare Informatics. 2018. Presented at: ICHI 2018; June 4-7, 2018; New York, NY. [CrossRef]
- Young JE, Klosko JS, Weishaar ME. Schema Therapy: A Practitioner's Guide. New York, NY. Guilford Publications; 2003.
- Gollapalli S, Ang B, Ng SK. Identifying early maladaptive schemas from mental health question texts. In: Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023. 2023. Presented at: EMNLP 2023; December 6-10, 2023; Singapore, Singapore. [CrossRef]
- Faustino B, Vasco AB, Delgado J, Farinha-Fernandes A, Guerreiro JC. Early maladaptive schemas and COVID-19 anxiety: the mediational role of mistrustfulness and vulnerability to harm and illness. Clin Psychol Psychother. Jul 17, 2022;29(4):1297-1308. [FREE Full text] [CrossRef] [Medline]
- Cámara M, Calvete E. Early maladaptive schemas as moderators of the impact of stressful events on anxiety and depression in university students. J Psychopathol Behav Assess. Oct 9, 2011;34(1):58-68. [CrossRef]
- Kunst H, Lobbestael J, Candel I, Batink T. Early maladaptive schemas and their relation to personality disorders: a correlational examination in a clinical population. Clin Psychol Psychother. Nov 17, 2020;27(6):837-846. [FREE Full text] [CrossRef] [Medline]
- Janson DL. Early maladaptive schemas in an Australian adult alcohol dependent clinical sample: differences between men and women. Edith Cowan University. 2015. URL: https://ro.ecu.edu.au/theses_hons/1463/ [accessed 2025-01-27]
- Barazandeh H, Kissane DW, Saeedi N, Gordon M. A systematic review of the relationship between early maladaptive schemas and borderline personality disorder/traits. Pers Individ Differ. May 2016;94:130-139. [CrossRef]
- Bishop A, Younan R, Low J, Pilkington PD. Early maladaptive schemas and depression in adulthood: a systematic review and meta-analysis. Clin Psychol Psychother. Jan 16, 2022;29(1):111-130. [CrossRef] [Medline]
- Halvorsen M, Wang CE, Richter J, Myrland I, Pedersen SK, Eisemann M, et al. Early maladaptive schemas, temperament and character traits in clinically depressed and previously depressed subjects. Clin Psychol Psychother. 2009;16(5):394-407. [CrossRef] [Medline]
- Wright MO, Crawford E, Del Castillo D. Childhood emotional maltreatment and later psychological distress among college students: the mediating role of maladaptive schemas. Child Abuse Negl. Jan 2009;33(1):59-68. [CrossRef] [Medline]
- Balsamo M, Carlucci L, Sergi MR, Klein Murdock K, Saggino A. The mediating role of early maladaptive schemas in the relation between co-rumination and depression in young adults. PLoS One. Oct 21, 2015;10(10):e0140177. [FREE Full text] [CrossRef] [Medline]
- Messman-Moore TL, Coates AA. The impact of childhood psychological abuse on adult interpersonal conflict. J Emot Abuse. 2007;7(2):75-92. [CrossRef]
- Young J, Brown G. YSQ-L3. Schema Therapy Institute. 2017. URL: https://psychology-training.com.au/wp-content/uploads/2017/04/Young-Schema-Questionnaire-L3.pdf [accessed 2024-01-04]
- Dean J, Potts HW, Barker C. Direction to an internet support group compared with online expressive writing for people with depression and anxiety: a randomized trial. JMIR Ment Health. May 17, 2016;3(2):e12. [FREE Full text] [CrossRef] [Medline]
- Gliddon E, Lauder S, Berk L, Cosgrove V, Grimm D, Dodd S, et al. Evaluating discussion board engagement in the MoodSwings online self-help program for bipolar disorder: protocol for an observational prospective cohort study. BMC Psychiatry. Oct 14, 2015;15:243. [FREE Full text] [CrossRef] [Medline]
- Chung HW, Hou L, Longpre S, Zoph B, Tay Y, Fedus W, et al. Scaling instruction-finetuned language models. arXiv. Preprint posted online on October 20, 2022. [CrossRef]
- Ouyang L, Wu J, Jiang X, Almeida D, Wainwright C, Mishkin P, et al. Training language models to follow instructions with human feedback. arXiv. Preprint posted online on March 4, 2022. [CrossRef]
- OpenAI. GPT-4 technical report. arXiv. Preprint posted online on March 15, 2023
- Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, et al. Attention is all you need. arXiv. Preprint posted online on June 12, 2017. [CrossRef]
- Kjell ON, Sikström S, Kjell K, Schwartz HA. Natural language analyzed with AI-based transformers predict traditional subjective well-being measures approaching the theoretical upper limits in accuracy. Sci Rep. Mar 10, 2022;12(1):3918. [FREE Full text] [CrossRef] [Medline]
- Teferra BG, Rose J. Predicting generalized anxiety disorder from impromptu speech transcripts using context-aware transformer-based neural networks: model evaluation study. JMIR Ment Health. Mar 28, 2023;10:e44325. [FREE Full text] [CrossRef] [Medline]
- Malgaroli M, Hull TD, Zech JM, Althoff T. Natural language processing for mental health interventions: a systematic review and research framework. Transl Psychiatry. Oct 06, 2023;13(1):309. [FREE Full text] [CrossRef] [Medline]
- Gkotsis G, Oellrich A, Velupillai S, Liakata M, Hubbard TJ, Dobson RJ, et al. Characterisation of mental health conditions in social media using informed deep learning. Sci Rep. Mar 22, 2017;7:45141. [FREE Full text] [CrossRef] [Medline]
- Xu X, Yao B, Dong Y, Gabriel S, Yu H, Hendler J, et al. Mental-LLM: leveraging large language models for mental health prediction via online text data. Proc ACM Interact Mob Wearable Ubiquitous Technol. Mar 06, 2024;8(1):1-32. [CrossRef]
- Community support forum. 7Cups. URL: https://www.7cups.com/community/ [accessed 2023-11-21]
- Beyond Blue homepage. Beyond Blue. URL: https://forums.beyondblue.org.au/ [accessed 2023-11-21]
- Patient homepage. Patient. URL: https://patient.info/forums [accessed 2023-11-21]
- National alliance on mental illness homepage. National Alliance on Mental Illness. URL: https://tinyurl.com/ynb9b3u7 [accessed 2024-01-12]
- Castaldelli-Maia JM, Bhugra D. Analysis of global prevalence of mental and substance use disorders within countries: focus on sociodemographic characteristics and income levels. Int Rev Psychiatry. Feb 2022;34(1):6-15. [CrossRef] [Medline]
- Poliak A. A survey on recognizing textual entailment as an NLP evaluation. In: Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems. 2020. Presented at: Eval4NLP 2020; November 8-12, 2020; Punta Cana, Dominican Republic. [CrossRef]
- Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, et al. Exploring the limits of transfer learning with a unified text-to-text transformer. J Mach Learn Res. Jan 01, 2020;21(1):5485-5551. [FREE Full text]
- McHugh ML. The chi-square test of independence. Biochem Med (Zagreb). 2013;23(2):143-149. [FREE Full text] [CrossRef] [Medline]
- Lantz B. The large sample size fallacy. Scand J Caring Sci. Jun 2013;27(2):487-492. [CrossRef] [Medline]
- Szumilas M. Explaining odds ratios. J Can Acad Child Adolesc Psychiatry. Aug 2010;19(3):227-229. [FREE Full text] [Medline]
- Roberts LD. Ethical issues in conducting qualitative research in online communities. Qual Res Psychol. Apr 20, 2015;12(3):314-325. [CrossRef]
- Smedley RM, Coulson NS. A practical guide to analysing online support forums. Qual Res Psychol. May 30, 2018;18(1):76-103. [CrossRef]
- Mental disorders. World Health Organization. Jun 08, 2022. URL: https://www.who.int/news-room/fact-sheets/detail/mental-disorders [accessed 2024-01-12]
- Hwang TJ, Rabheru K, Peisah C, Reichman W, Ikeda M. Loneliness and social isolation during the COVID-19 pandemic. Int Psychogeriatr. Oct 2020;32(10):1217-1220. [CrossRef]
- Boyraz G, Legros DN, Tigershtrom A. COVID-19 and traumatic stress: the role of perceived vulnerability, COVID-19-related worries, and social isolation. J Anxiety Disord. Dec 2020;76:102307. [FREE Full text] [CrossRef] [Medline]
- Li JB, T Vazsonyi A, Dou K. Is individualism-collectivism associated with self-control? Evidence from Chinese and U.S. samples. PLoS One. Dec 19, 2018;13(12):e0208541. [FREE Full text] [CrossRef] [Medline]
- Agopian AJ, Eastcott LM, Mitchell LE. Age of onset and effect size in genome-wide association studies. Birth Defects Res A Clin Mol Teratol. Nov 2012;94(11):908-911. [FREE Full text] [CrossRef] [Medline]
- Rosenthal JA. Qualitative descriptors of strength of association and effect size. J Soc Serv Res. 1996;21(4):37-59. [CrossRef]
- Knaster P, Estlander AM, Karlsson H, Kaprio J, Kalso E. Diagnosing depression in chronic pain patients: DSM-IV major depressive disorder vs. Beck Depression Inventory (BDI). PLoS One. Mar 23, 2016;11(3):e0151982. [FREE Full text] [CrossRef] [Medline]
- Wiechman SA, Ptacek JT, Patterson DR, Gibran NS, Engrav LE, Heimbach DM. Rates, trends, and severity of depression after burn injuries. J Burn Care Rehabil. 2001;22(6):417-424. [CrossRef] [Medline]
- O'Neil MF, Moore NA. Animal models of depression: are there any? Hum Psychopharmacol. Jun 2003;18(4):239-254. [CrossRef] [Medline]
- Karmen C, Hsiung RC, Wetter T. Screening Internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods. Comput Methods Programs Biomed. Jun 2015;120(1):27-36. [CrossRef] [Medline]
- Cui L, Lin W, Oei TP. Factor structure and psychometric properties of the Young Schema Questionnaire (short form) in Chinese undergraduate students. Int J Ment Health Addiction. Sep 15, 2010;9(6):645-655. [CrossRef]
- Bär A, Bär HE, Rijkeboer MM, Lobbestael J. Early maladaptive schemas and schema modes in clinical disorders: a systematic review. Psychol Psychother. Sep 2023;96(3):716-747. [CrossRef] [Medline]
- Powers JP, Moshontz H, Hoyle RH. Self-control and affect regulation styles predict anxiety longitudinally in university students. Collabra Psychol. Feb 10, 2020;6(1):11. [CrossRef]
- Zhang C, Meng D, Zhu L, Ma X, Guo J, Fu Y, et al. The effect of trait anxiety on bedtime procrastination: the mediating role of self-control. Int J Behav Med. Apr 2023;30(2):260-267. [CrossRef] [Medline]
- Bertrams A, Baumeister RF, Englert C. Higher self-control capacity predicts lower anxiety-impaired cognition during math examinations. Front Psychol. Mar 31, 2016;7:485. [FREE Full text] [CrossRef] [Medline]
- He M, Zhan X, Liu C, Li L, Zhao X, Ren L, et al. The relationship between self-control and mental health problems among Chinese university students. Front Public Health. Oct 31, 2023;11:1224427. [FREE Full text] [CrossRef] [Medline]
- Krause ED, Mendelson T, Lynch TR. Childhood emotional invalidation and adult psychological distress: the mediating role of emotional inhibition. Child Abuse Negl. Feb 2003;27(2):199-213. [CrossRef] [Medline]
- Coggins J, Fox JR. A qualitative exploration of emotional inhibition: a basic emotions and developmental perspective. Clin Psychol Psychother. 2009;16(1):55-76. [CrossRef] [Medline]
- Roemer L, Salters K, Raffa SD, Orsillo SM. Fear and avoidance of internal experiences in GAD: preliminary tests of a conceptual model. Cogn Ther Res. Feb 2005;29:71-88. [CrossRef]
- Tao S, Jing Y. More sense of self-discipline, less procrastination: the mediation of autonomous motivation. Front Psychol. Nov 23, 2023;14:1268614. [FREE Full text] [CrossRef] [Medline]
- Ahmadpanah M, Astinsadaf S, Akhondi A, Haghighi M, Sadeghi Bahmani D, Nazaribadie M, et al. Early maladaptive schemas of emotional deprivation, social isolation, shame and abandonment are related to a history of suicide attempts among patients with major depressive disorders. Compr Psychiatry. Aug 2017;77:71-79. [CrossRef] [Medline]
- Ge L, Yap CW, Ong R, Heng BH. Social isolation, loneliness and their relationships with depressive symptoms: a population-based study. PLoS One. Aug 23, 2017;12(8):e0182145. [FREE Full text] [CrossRef] [Medline]
- Canlı D, Karaşar B. Predictors of major depressive disorder: the need for social approval and self-esteem. Alpha Psychiatry. Jan 19, 2021;22(1):38-42. [FREE Full text] [CrossRef] [Medline]
- Karagöl A, Törenli Kaya Z. Evaluating early maladaptive schemas and depression levels in living kidney and liver donors. Psychol Health Med. Dec 2022;27(10):2161-2170. [CrossRef] [Medline]
- Davoodi E, Wen A, Dobson KS, Noorbala AA, Mohammadi A, Farahmand Z. Early maladaptive schemas in depression and somatization disorder. J Affect Disord. Aug 01, 2018;235:82-89. [CrossRef] [Medline]
- Matos M, Pinto-Gouveia J, Duarte C. Internalizing early memories of shame and lack of safeness and warmth: the mediating role of shame on depression. Behav Cogn Psychother. Mar 25, 2013;41(4):479-493. [CrossRef]
- darvishi F, rahmani MA, Akbari B, Rahbar M. A comparison of relationship between early maladaptive schemas with depression severity in suicidal group and non-clinical sample. Procedia Soc Behav Sci. Jul 09, 2013;84:1072-1077. [CrossRef]
- Blatt SJ. Experiences of Depression: Theoretical, Clinical, and Research Perspectives. Washington, DC. American Psychological Association; 2004.
- Cohen RE, Tennen H. Self-punishment in learned helplessness and depression. J Soc Clin Psychol. Mar 1985;3(1):82-96. [CrossRef]
- Segrin C. Interpersonal communication problems associated with depression and loneliness. In: Handbook of Communication and Emotion: Research, Theory, Applications, and Contexts. Cambridge, MA. Academic Press; 1996.
- Hames JL, Hagan CR, Joiner TE. Interpersonal processes in depression. Annu Rev Clin Psychol. 2013;9:355-377. [CrossRef] [Medline]
- Marcus DK, Nardone ME. Depression and interpersonal rejection. Clin Psychol Rev. 1992;12(4):433-449. [CrossRef]
- Forbush K, Watson D. Emotional inhibition and personality traits: a comparison of women with anorexia, bulimia, and normal controls. Ann Clin Psychiatry. 2006;18(2):115-121. [CrossRef] [Medline]
- Bekker MH, Spoor ST. Emotional inhibition, health, gender, and eating disorders: the role of (over) sensitivity to others. In: Vingerhoets AJ, Nyklíček I, Denollet J, editors. Emotion Regulation. Boston, MA. Springer; 2008.
- Espeset EM, Gulliksen KS, Nordbø RH, Skårderud F, Holte A. The link between negative emotions and eating disorder behaviour in patients with anorexia nervosa. Eur Eat Disord Rev. Nov 2012;20(6):451-460. [CrossRef] [Medline]
- Aloi M, Rania M, Caroleo M, Carbone EA, Fazia G, Calabrò G, et al. How are early maladaptive schemas and DSM-5 personality traits associated with the severity of binge eating? J Clin Psychol. Mar 2020;76(3):539-548. [CrossRef] [Medline]
- Sanftner JL, Barlow DH, Marschall DE, Tangney JP. The relation of shame and guilt to eating disorder symptomatology. J Soc Clin Psychol. Dec 1995;14(4):315-324. [CrossRef]
- Kelly AC, Carter JC. Why self-critical patients present with more severe eating disorder pathology: the mediating role of shame. Br J Clin Psychol. Jun 2013;52(2):148-161. [CrossRef] [Medline]
- Oakley B, Knafo A, Madhavan G, Wilson DS. Pathological Altruism. Oxford, UK. Oxford University Press; Dec 09, 2011.
- Bachner-Melman R, Zohar AH, Ebstein RP, Bachar E. The relationship between selflessness levels and the severity of anorexia nervosa symptomatology. Eur Eat Disord Rev. May 2007;15(3):213-220. [CrossRef] [Medline]
- Buchholz A, Henderson KA, Hounsell A, Wagner A, Norris M, Spettigue W. Self-silencing in a clinical sample of female adolescents with eating disorders. J Can Acad Child Adolesc Psychiatry. Nov 2007;16(4):158-163. [FREE Full text] [Medline]
- Bachner-Melman R, Oakley B. Giving ‘til it hurts’: eating disorders and pathological altruism. In: Latzer Y, Stein D, editors. Bio-Psycho-Social Contributions to Understanding Eating Disorders. Cham, Switzerland. Springer; 2016.
- Bachner-Melman R. The relevance of pathological altruism to eating disorders. In: Oakley B, Knafo A, Madhavan G, Wilson DS, editors. Pathological Altruism. Oxford, UK. Oxford University Press; 2012.
- van der Linde RP, Huntjens RJ, Bachrach N, Rijkeboer MM. Personality disorder traits, maladaptive schemas, modes and coping styles in participants with complex dissociative disorders, borderline personality disorder and avoidant personality disorder. Clin Psychol Psychother. Aug 10, 2023;30(6):1234-1245. [CrossRef] [Medline]
- Carr SN, Francis AJ. Do early maladaptive schemas mediate the relationship between childhood experiences and avoidant personality disorder features? A preliminary investigation in a non-clinical sample. Cogn Ther Res. May 2, 2009;34(4):343-358. [CrossRef]
- Bach B, Farrell JM. Schemas and modes in borderline personality disorder: the mistrustful, shameful, angry, impulsive, and unhappy child. Psychiatry Res. Jan 2018;259:323-329. [CrossRef] [Medline]
- Palihawadana V, Broadbear JH, Rao S. Reviewing the clinical significance of 'fear of abandonment' in borderline personality disorder. Australas Psychiatry. Feb 07, 2019;27(1):60-63. [CrossRef] [Medline]
- Vanwoerden S, Kalpakci A, Sharp C. The relations between inadequate parent-child boundaries and borderline personality disorder in adolescence. Psychiatry Res. Nov 2017;257:462-471. [CrossRef] [Medline]
- Yakeley J. Current understanding of narcissism and narcissistic personality disorder. BJPsych Adv. Jul 05, 2018;24(5):305-315. [CrossRef]
- Esmaeilian N, Dehghani M, Koster EH, Hoorelbeke K. Early maladaptive schemas and borderline personality disorder features in a nonclinical sample: a network analysis. Clin Psychol Psychother. May 05, 2019;26(3):388-398. [CrossRef] [Medline]
- Beaton J, Thielking M. Chronic mistrust and complex trauma: Australian psychologists' perspectives on the treatment of young women with a history of childhood maltreatment. Aus Psychol. Nov 12, 2020;55(3):230-243. [CrossRef]
- Lian AE, Chooi WT, Bono SA. A systematic review investigating the early maladaptive schemas (EMS) in individuals with trauma experiences and PTSD. Eur J Trauma Dissoc. Mar 2023;7(1):100315. [CrossRef]
- Ahmadian A, Mirzaee J, Omidbeygi M, Holsboer-Trachsler E, Brand S. Differences in maladaptive schemas between patients suffering from chronic and acute posttraumatic stress disorder and healthy controls. Neuropsychiatr Dis Treat. Jul 2015;11:1677-1684. [FREE Full text] [CrossRef] [Medline]
- LaMotte AD, Taft CT, Weatherill RP. Mistrust of others as a mediator of the relationship between trauma exposure and use of partner aggression. Psychol Trauma. Jul 2016;8(4):535-540. [FREE Full text] [CrossRef] [Medline]
- Cockram DM, Drummond PD, Lee CW. Role and treatment of early maladaptive schemas in Vietnam Veterans with PTSD. Clin Psychol Psychother. Mar 29, 2010;17(3):165-182. [FREE Full text] [CrossRef] [Medline]
- Greenblatt-Kimron L, Karatzias T, Yonatan M, Shoham A, Hyland P, Ben-Ezra M, et al. Early maladaptive schemas and ICD-11 CPTSD symptoms: treatment considerations. Psychol Psychother. Mar 17, 2023;96(1):117-128. [CrossRef] [Medline]
- Ullman SE, Townsend SM, Filipas HH, Starzynski LL. Structural models of the relations of assault severity, social support, avoidance coping, self-blame, and PTSD among sexual assault survivors. Psychol Women Q. Mar 01, 2007;31(1):23-37. [CrossRef]
- Kline NK, Berke DS, Rhodes CA, Steenkamp MM, Litz BT. Self-blame and PTSD following sexual assault: a longitudinal analysis. J Interpers Violence. Mar 21, 2021;36(5-6):NP3153-NP3168. [CrossRef] [Medline]
- Raz A, Rubinstein R, Shadach E, Chaikin G, Ben Yehuda A, Tatsa-Laur L, et al. Behavioral self-blame in PTSD-etiology, risk factors, and proposed interventions. Int J Environ Res Public Health. Aug 05, 2023;20(15):6530. [FREE Full text] [CrossRef] [Medline]
- Harding HG, Burns EE, Jackson JL. Identification of child sexual abuse survivor subgroups based on early maladaptive schemas: implications for understanding differences in posttraumatic stress disorder symptom severity. Cogn Ther Res. Aug 10, 2011;36(5):560-575. [CrossRef]
- Holmes SC, Facemire VC, DaFonseca AM. Expanding criterion a for posttraumatic stress disorder: considering the deleterious impact of oppression. Traumatology. 2016;22(4):314-321. [CrossRef]
- Karatzias T, Jowett S, Begley A, Deas S. Early maladaptive schemas in adult survivors of interpersonal trauma: foundations for a cognitive theory of psychopathology. Eur J Psychotraumatol. Sep 16, 2016;7(1):30713. [FREE Full text] [CrossRef] [Medline]
- Fothergill KE, Ensminger ME, Green KM, Crum RM, Robertson J, Juon HS. The impact of early school behavior and educational achievement on adult drug use disorders: a prospective study. Drug Alcohol Depend. Jan 01, 2008;92(1-3):191-199. [FREE Full text] [CrossRef] [Medline]
- Henry KL. Academic achievement and adolescent drug use: an examination of reciprocal effects and correlated growth trajectories. J Sch Health. Jan 2010;80(1):38-43. [CrossRef] [Medline]
- Goslin JC. Underachieves: a curriculum design. Prev Sch Fail. Oct 1989;34(1):22-28. [CrossRef]
- Adeoye OE, Fasanmi SS, Igo J. Self-concept clarity, learned helplessness and fatigue severity as predictors of psychoactive drug use and abuse among undergraduates. Int J Sci Basic Appl Res. 2020;53(2):198-210. [FREE Full text]
- Bakhshi Bojed F, Nikmanesh Z. Role of early maladaptive schemas on addiction potential in youth. Int J High Risk Behav Addict. Sep 25, 2013;2(2):72-76. [FREE Full text] [CrossRef] [Medline]
- Sterling RC, Gottheil E, Weinstein SP, Lundy A, Serota RD. Learned helplessness and cocaine dependence: an investigation. J Addict Dis. Mar 14, 1996;15(2):13-24. [CrossRef]
- Shaghaghy F, Saffarinia M, Iranpoor M, Soltanynejad A. The relationship of early maladaptive schemas, attributional styles and learned helplessness among addicted and non-addicted men. Addict Health. 2011;3(1-2):45-52. [FREE Full text] [Medline]
- Koob GF, Powell P, White A. Addiction as a coping response: hyperkatifeia, deaths of despair, and COVID-19. Am J Psychiatry. Nov 01, 2020;177(11):1031-1037. [CrossRef] [Medline]
- Romano I, Patte KA, de Groh M, Jiang Y, Wade TJ, Bélanger RE, et al. Substance-related coping behaviours among youth during the early months of the COVID-19 pandemic. Addict Behav Rep. Dec 2021;14:100392. [FREE Full text] [CrossRef] [Medline]
- Wardell JD, Kempe T, Rapinda KK, Single A, Bilevicius E, Frohlich JR, et al. Drinking to cope during COVID-19 pandemic: the role of external and internal factors in coping motive pathways to alcohol use, solitary drinking, and alcohol problems. Alcohol Clin Exp Res. Oct 2020;44(10):2073-2083. [CrossRef] [Medline]
- McGinn LK, Nooner KB, Cohen J, Leaberry KD. The role of early experience and cognitive vulnerability: presenting a unified model of the etiology of panic. Cogn Ther Res. Apr 2, 2015;39(4):508-519. [CrossRef]
- Riskind JH. Looming vulnerability to threat: a cognitive paradigm for anxiety. Behav Res Ther. Aug 1997;35(8):685-702. [CrossRef] [Medline]
- Dean KK, Wentworth G, LeCompte N. Social exclusion and perceived vulnerability to physical harm. Self Identity. Jan 08, 2019;18(1):87-102. [CrossRef]
- Groves PS, Bunch JL, Kuehnle F. Increasing a patient's sense of security in the hospital: a theory of trust and nursing action. Nursing Inquiry. Oct 2023;30(4):e12569. [CrossRef]
- Watson J, Nesdale D. Rejection sensitivity, social withdrawal, and loneliness in young adults. J Appl Soc Psychol. Jun 14, 2012;42(8):1984-2005. [CrossRef]
- Stanley L, Arora T. Social exclusion amongst adolescent girls their self‐esteem and coping strategies. Educ Psychol Pract. Oct 19, 2007;14(2):94-100. [CrossRef]
- Verkuyten M, Thijs J. Ethnic discrimination and global self-worth in early adolescents: the mediating role of ethnic self-esteem. Int J Behav Dev. Mar 01, 2006;30(2):107-116. [CrossRef]
- Johari F, Iranpour A, Dehghan M, Alizadeh S, Safizadeh M, Sharifi H. Lonely, harassed and abandoned in society: the lived experiences of Iranian homeless youth. BMC Psychol. Mar 20, 2022;10(1):75. [FREE Full text] [CrossRef] [Medline]
- Cacioppo JT, Cacioppo S. Social relationships and health: the toxic effects of perceived social isolation. Soc Personal Psychol Compass. Feb 01, 2014;8(2):58-72. [FREE Full text] [CrossRef] [Medline]
- Iwamitsu Y, Shimoda K, Abe H, Tani T, Kodama M, Okawa M. Differences in emotional distress between breast tumor patients with emotional inhibition and those with emotional expression. Psychiatry Clin Neurosci. Jun 02, 2003;57(3):289-294. [FREE Full text] [CrossRef] [Medline]
- Denollet J, Duijndam S. The multidimensional nature of adult social inhibition: inhibition, sensitivity and withdrawal facets of the SIQ15. J Affect Disord. Feb 15, 2019;245:569-579. [CrossRef] [Medline]
- Gollwitzer M, Rothmund T, Süssenbach P. The sensitivity to mean intentions (SeMI) model: basic assumptions, recent findings, and potential avenues for future research. Soc Pers Psychol Compass. Jul 08, 2013;7(7):415-426. [CrossRef]
- Gollwitzer M, Rothmund T, Pfeiffer A, Ensenbach C. Why and when justice sensitivity leads to pro- and antisocial behavior. J Res Pers. Dec 2009;43(6):999-1005. [CrossRef]
- Gollwitzer M, Süssenbach P, Hannuschke M. Victimization experiences and the stabilization of victim sensitivity. Front Psychol. Apr 14, 2015;6:439. [FREE Full text] [CrossRef] [Medline]
- Pilkington PD, Noonan C, May T, Younan R, Holt RA. Early maladaptive schemas and intimate partner violence victimization and perpetration: a systematic review and meta-analysis. Clin Psychol Psychother. Sep 05, 2021;28(5):1030-1042. [CrossRef] [Medline]
- Smith ML, Rosen D. Mistrust and self-isolation: barriers to social support for older adult methadone clients. J Gerontol Soc Work. Oct 24, 2009;52(7):653-667. [CrossRef] [Medline]
- Wood JV, Giordano-Beech M, Ducharme MJ. Compensating for failure through social comparison. Pers Soc Psychol Bull. Nov 01, 1999;25(11):1370-1386. [CrossRef]
- Leahy RL. Cognitive-behavioral therapy for envy. Cogn Ther Res. Jul 29, 2020;45(3):418-427. [CrossRef]
Abbreviations
| AI: artificial intelligence |
| BPD: borderline personality disorder |
| ED: eating disorder |
| EMS: early maladaptive schema |
| EPM: entailment-based prediction model |
| LLM: large language model |
| OMHC: online mental health community |
| OR: odds ratio |
| PD: personality disorder |
| PTSD: posttraumatic stress disorder |
| ST: schema therapy |
| SUD: substance use disorder |
| YSQ: Young Schema Questionnaire |
Edited by A Mavragani; submitted 19.04.24; peer-reviewed by A AL-Asadi, F Franza; comments to author 29.08.24; revised version received 08.12.24; accepted 06.01.25; published 07.02.25.
Copyright©Beng Heng Ang, Sujatha Das Gollapalli, Mingzhe Du, See-Kiong Ng. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 07.02.2025.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.