[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-426100-105":59,"doc-detail-426100-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","linguistic-features-of-older-adults-daily-self-talk-a-naturalistic-observational-approach","Linguistic Features of Older Adults’ Daily Self-Talk: A Naturalistic Observational Approach","","Research supporting socioemotional selectivity theory links late-life emotion regulation to older adults’ greater ability to manage negative emotion. This study characterizes linguistic features of verbalized self-talk (audible speech when alone) and compares them with conversations with social partners. Older adults reported partner presence across days while electronically activated recorders sampled frequent sound snippets. Linguistic analyses examined pronouns, structured language, and emotional tone, finding limited within-person associations for second-person pronouns but differences when alone.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/linguistic-features-of-older-adults-daily-self-talk-a-naturalistic-observational-approach/426100/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/linguistic-features-of-older-adults-daily-self-talk-a-naturalistic-observational-approach/426100.png","ImageObject",300,407,{"name":92,"@type":93},"Nguyễn Văn Học","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-15","2026-09-28",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the study investigate about older adults’ self-talk?","Question",{"text":112,"@type":113},"It characterizes the linguistic features of verbalized self-talk when participants are alone and compares them with conversations with social partners.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were self-talk samples collected in this research?",{"text":117,"@type":113},"Electronically Activated Recorders captured short, repeated sound snippets from participants, which coders transcribed and identified when verbal utterances occurred during alone periods.",{"name":119,"@type":110,"acceptedAnswer":120},"Which linguistic features were examined?",{"text":121,"@type":113},"The study extracted features including second-person pronouns, formal/structured language, and emotional tone using the Linguistic Inquiry and Word Count approach.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},426100,1791143107,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":8,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":81},1374402739827,"https://ap-avatar.wpscdn.com/avatar/14000c97e7351f1a627?x-image-process=image/resize,m_fixed,w_180,h_180&k=1787885694763230660","1134 Innovation in Aging, 2025, Vol. 9, No. S2  \nstructured language and expressed more negative emotion compared with language when with social partners. This study makes an important contribution by capturing naturalistic self-talk as it occurs in daily life and suggests self-talk may help older adults regulate negative emotions. Future research using wearable sensors might capture arousal or allow self-reported experience sampling of unspoken self-talk to tease out when and who uses self-talk to regulate emotions.  \nAbstract citation ID: igaf122.3804  \nLINGUISTIC FEATURES OF OLDER ADULTS’ DAILY  \nSELF-TALK: A NATURALISTIC OBSERVATIONAL  \nAPPROACH  \nSibo Gao1, and Karen Fingerman2, 1. University of Texas at Austin, Austin, Texas, United States, 2. The University of Texas  \nat Austin, Austin, Texas, United States  \nResearch supporting socioemotional selectivity theory finds that older adults tend to have better emotion regulation than younger adults, particularly with regard to negative emotion.  \nVerbalized self-talk (i.e., audible speech when alone) may be an important but understudied emotion regulation strategy in late life, promoting psychological distance through second-person pronouns and structured speech, and providing an opportunity to express negative emotions. The current study sought to characterize linguistic features of verbalized self-talk descriptively and in comparison to conversations with social partners. Older adults (N = 333; Mage=73.9) reported whether they had been with social partners every three hours across 5–6 days.  \nElectronically Activated Recorders captured 30-second sound snippets every 7 minutes. Coders transcribed 109,609 snippets;  \n918 snippets contained verbal utterances when participants were alone (self-talk). Using the Linguistic Inquiry and Word Count, we extracted linguistic features including second-person pronouns, formal and structured language, and emotional tone.  \nMultilevel models revealed no significant within-person association between being alone and second-person pronoun use.  \nHowever, when participants were alone, they used more","cbCaiux6KavgBcpX","https://ap.wps.com/l/cbCaiux6KavgBcpX","pdf",999450,"English","# Background\n## Emotion regulation and verbalized self-talk\n# Methods\n## Participants and reporting\n## Audio recording and transcription\n## Linguistic feature extraction\n# Results\n## Within-person association findings\n# Implications and Future Work\n## Wearable sensors and experience sampling","[{\"question\":\"What does the study investigate about older adults’ self-talk?\",\"answer\":\"It characterizes the linguistic features of verbalized self-talk when participants are alone and compares them with conversations with social partners.\"},{\"question\":\"How were self-talk samples collected in this research?\",\"answer\":\"Electronically Activated Recorders captured short, repeated sound snippets from participants, which coders transcribed and identified when verbal utterances occurred during alone periods.\"},{\"question\":\"Which linguistic features were examined?\",\"answer\":\"The study extracted features including second-person pronouns, formal/structured language, and emotional tone using the Linguistic Inquiry and Word Count approach.\"}]","Linguistic Features of Older Adults’ Daily Self-Talk: A Naturalistic Observational Approach | PDF",1790639355]