1202 Reconstructing the PAP Therapy Journey Using Reddit: Stage-Specific Topics and Emotional Patterns

Abstract Introduction Online forums like Reddit are popular among people seeking information and support for chronic health conditions, including obstructive sleep apnea (OSA). Experiences with Positive Airway Pressure (PAP) - the first-line therapy for OSA - vary greatly and are often influenced by clinical, behavioral and emotional factors. This study explored distinct topics and emotions emerging across the PAP therapy journey, including pre-therapy, therapy initiation, and therapy persistence. Methods Text data were collected weekly from r/SleepApnea and r/CPAP from March to August 2025. De-identified data were analyzed using three components: therapy stage classification, topic modeling, and emotion classification. Traditional machine learning models and a transformer-based DistilRoBERTa model were trained or fine-tuned to classify therapy stages. Topic modeling using BERTopic to group semantically similar content, extract keywords and representative texts, with OpenAI GPT-4.0-mini generating human-interpretable labels. Emotions were identified by a transformer model pre-trained on the GoEmotions dataset. Human review refined the initial labeling used for model training and the validation of topic labels and representative examples. Results We examined 9,623 unique discussions, divided into 13,975 segments that combined same-stage sentences for more precise topic modeling. Of these segments, 4,560 (32.6%) were classified as pre-therapy, 4,062 (29.1%) as therapy initiation, 3,151 (22.5%) as therapy persistence, and 2,202 (15.8%) as unknown. Distinct topics emerged at each stage, while emotional tone remained relatively consistent. Pre-therapy posts focused on symptom burden, challenges navigating diagnostic and sleep study processes, uncertainty and conflicting readings from home monitoring technologies, health insurance issues, and alternative treatments. Therapy-initiation discussions emphasized mask fit, technical troubleshooting, therapy adjustment, and device comparisons. Therapy-sustained-use focused on equipment replacement and maintenance timelines, long-term mask fit, ongoing symptoms, pressure optimization, and interpreting CPAP or wearable data. Across stages, discussions were most often classified as neutral, curiosity, and realization, reflecting a focus on information exchange and problem-solving. Confusion appeared as the main negative emotion, and gratitude was the most consistent positive tone. Conclusion Stage-specific insights and emotions revealed how needs, concerns, and behaviors shifted through the PAP therapy journey. This work highlights opportunities for personalized, stage-specific support to improve therapy experiences and promote long-term adoption and use. Support (if any) Resmed

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Publication Details

Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.1201
Primary Topic
Mental Health via Writing
Type
article
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0.00
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article

1202 Reconstructing the PAP Therapy Journey Using Reddit: Stage-Specific Topics and Emotional Patterns

Leanne Kaye, Kimberly Sterling, Vy Vuong, Caleb Woodford
SLEEP
Mental Health via Writing
article

1202 Reconstructing the PAP Therapy Journey Using Reddit: Stage-Specific Topics and Emotional Patterns

Leanne Kaye, Kimberly Sterling, Vy Vuong, Caleb Woodford
article en

Abstract

Abstract Introduction Online forums like Reddit are popular among people seeking information and support for chronic health conditions, including obstructive sleep apnea (OSA). Experiences with Positive Airway Pressure (PAP) - the first-line therapy for OSA - vary greatly and are often influenced by clinical, behavioral and emotional factors. This study explored distinct topics and emotions emerging across the PAP therapy journey, including pre-therapy, therapy initiation, and therapy persistence. Methods Text data were collected weekly from r/SleepApnea and r/CPAP from March to August 2025. De-identified data were analyzed using three components: therapy stage classification, topic modeling, and emotion classification. Traditional machine learning models and a transformer-based DistilRoBERTa model were trained or fine-tuned to classify therapy stages. Topic modeling using BERTopic to group semantically similar content, extract keywords and representative texts, with OpenAI GPT-4.0-mini generating human-interpretable labels. Emotions were identified by a transformer model pre-trained on the GoEmotions dataset. Human review refined the initial labeling used for model training and the validation of topic labels and representative examples. Results We examined 9,623 unique discussions, divided into 13,975 segments that combined same-stage sentences for more precise topic modeling. Of these segments, 4,560 (32.6%) were classified as pre-therapy, 4,062 (29.1%) as therapy initiation, 3,151 (22.5%) as therapy persistence, and 2,202 (15.8%) as unknown. Distinct topics emerged at each stage, while emotional tone remained relatively consistent. Pre-therapy posts focused on symptom burden, challenges navigating diagnostic and sleep study processes, uncertainty and conflicting readings from home monitoring technologies, health insurance issues, and alternative treatments. Therapy-initiation discussions emphasized mask fit, technical troubleshooting, therapy adjustment, and device comparisons. Therapy-sustained-use focused on equipment replacement and maintenance timelines, long-term mask fit, ongoing symptoms, pressure optimization, and interpreting CPAP or wearable data. Across stages, discussions were most often classified as neutral, curiosity, and realization, reflecting a focus on information exchange and problem-solving. Confusion appeared as the main negative emotion, and gratitude was the most consistent positive tone. Conclusion Stage-specific insights and emotions revealed how needs, concerns, and behaviors shifted through the PAP therapy journey. This work highlights opportunities for personalized, stage-specific support to improve therapy experiences and promote long-term adoption and use. Support (if any) Resmed

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Quality Education
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Mental Health via Writing
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