Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach
<h3>Background</h3><p dir="ltr">Natural language understanding (NLU), a subfield of artificial intelligence, focuses on the computational understanding of human language. This technology offers an objective and quantitative approach to analysing interviews in qualitative...
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| مؤلفون آخرون: | , , , , |
| منشور في: |
2025
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| _version_ | 1864513533493903360 |
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| author | Lamyia Anweigi (14778760) |
| author2 | Iheb Ben Naceur (22504409) Jomana Awad (22504412) Mohamed Ahmeda (22504415) Noha Barhom (14150748) Faleh Tamimi (2867255) |
| author2_role | author author author author author |
| author_facet | Lamyia Anweigi (14778760) Iheb Ben Naceur (22504409) Jomana Awad (22504412) Mohamed Ahmeda (22504415) Noha Barhom (14150748) Faleh Tamimi (2867255) |
| author_role | author |
| dc.creator.none.fl_str_mv | Lamyia Anweigi (14778760) Iheb Ben Naceur (22504409) Jomana Awad (22504412) Mohamed Ahmeda (22504415) Noha Barhom (14150748) Faleh Tamimi (2867255) |
| dc.date.none.fl_str_mv | 2025-05-09T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1111/joor.13986 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Natural_Language_Understanding_to_Assess_Oral_Health_Related_Quality_of_Life_A_Cross_Sectional_Study_Incorporating_a_Mixed_Methods_Approach/30455978 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Dentistry Health sciences Health services and systems Artificial intelligence artificial intelligence hypodontia natural language processing patient outcomes quality of life tooth development |
| dc.title.none.fl_str_mv | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <h3>Background</h3><p dir="ltr">Natural language understanding (NLU), a subfield of artificial intelligence, focuses on the computational understanding of human language. This technology offers an objective and quantitative approach to analysing interviews in qualitative research. This study hypothesises that NLU can assess the impact of oral health on quality of life by analysing semi‐structured interviews.</p><h3>Objective</h3><p dir="ltr">This study aimed to assess the utility of NLU in evaluating oral health‐related quality of life by analysing semi‐structured interviews with individuals diagnosed with hypodontia.</p><h3>Methods</h3><p dir="ltr">A cross‐sectional qualitative study was conducted on 10 participants (aged 16–25 years) suffering from hypodontia. Semi‐structured interviews were transcribed and analysed using IBM Watson NLU text analysis. The analysis identified entities, keywords, sentiments (positive and negative) and emotions (joy, sadness, anger, fear and disgust) expressed in the interviews.</p><h3>Results</h3><p dir="ltr">NLU analysis revealed a predominantly negative sentiment towards hypodontia and its management, with 93.2% of identified entities presenting a negative sentiment and only 6.8% showing a positive sentiment. Patient sentiment correlated inversely with age (<i>R</i> = −0.49), treatment waiting time (<i>R</i> = −0.22) and OHIP score (<i>R</i> = −20). Negative sentiments and sadness were most prominent when discussing the history of dental problems and feelings about their teeth, whereas joy and positive sentiments were expressed regarding successful dental work. Keywords associated with negative sentiment were primarily related to treatment length and delays.</p><h3>Conclusion</h3><p dir="ltr">NLU effectively identified patients' negative sentiments and emotional responses to oral health conditions, demonstrating its potential as a valuable tool in qualitative dental research.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Oral Rehabilitation<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1111/joor.13986" target="_blank">https://dx.doi.org/10.1111/joor.13986</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_baa9cfc86698fc6c8ac78b888ea93d9b |
| identifier_str_mv | 10.1111/joor.13986 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30455978 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods ApproachLamyia Anweigi (14778760)Iheb Ben Naceur (22504409)Jomana Awad (22504412)Mohamed Ahmeda (22504415)Noha Barhom (14150748)Faleh Tamimi (2867255)Biomedical and clinical sciencesDentistryHealth sciencesHealth services and systemsArtificial intelligenceartificial intelligencehypodontianatural language processingpatient outcomesquality of lifetooth development<h3>Background</h3><p dir="ltr">Natural language understanding (NLU), a subfield of artificial intelligence, focuses on the computational understanding of human language. This technology offers an objective and quantitative approach to analysing interviews in qualitative research. This study hypothesises that NLU can assess the impact of oral health on quality of life by analysing semi‐structured interviews.</p><h3>Objective</h3><p dir="ltr">This study aimed to assess the utility of NLU in evaluating oral health‐related quality of life by analysing semi‐structured interviews with individuals diagnosed with hypodontia.</p><h3>Methods</h3><p dir="ltr">A cross‐sectional qualitative study was conducted on 10 participants (aged 16–25 years) suffering from hypodontia. Semi‐structured interviews were transcribed and analysed using IBM Watson NLU text analysis. The analysis identified entities, keywords, sentiments (positive and negative) and emotions (joy, sadness, anger, fear and disgust) expressed in the interviews.</p><h3>Results</h3><p dir="ltr">NLU analysis revealed a predominantly negative sentiment towards hypodontia and its management, with 93.2% of identified entities presenting a negative sentiment and only 6.8% showing a positive sentiment. Patient sentiment correlated inversely with age (<i>R</i> = −0.49), treatment waiting time (<i>R</i> = −0.22) and OHIP score (<i>R</i> = −20). Negative sentiments and sadness were most prominent when discussing the history of dental problems and feelings about their teeth, whereas joy and positive sentiments were expressed regarding successful dental work. Keywords associated with negative sentiment were primarily related to treatment length and delays.</p><h3>Conclusion</h3><p dir="ltr">NLU effectively identified patients' negative sentiments and emotional responses to oral health conditions, demonstrating its potential as a valuable tool in qualitative dental research.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Oral Rehabilitation<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1111/joor.13986" target="_blank">https://dx.doi.org/10.1111/joor.13986</a></p>2025-05-09T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1111/joor.13986https://figshare.com/articles/journal_contribution/Natural_Language_Understanding_to_Assess_Oral_Health_Related_Quality_of_Life_A_Cross_Sectional_Study_Incorporating_a_Mixed_Methods_Approach/30455978CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/304559782025-05-09T03:00:00Z |
| spellingShingle | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach Lamyia Anweigi (14778760) Biomedical and clinical sciences Dentistry Health sciences Health services and systems Artificial intelligence artificial intelligence hypodontia natural language processing patient outcomes quality of life tooth development |
| status_str | publishedVersion |
| title | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach |
| title_full | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach |
| title_fullStr | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach |
| title_full_unstemmed | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach |
| title_short | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach |
| title_sort | Natural Language Understanding to Assess Oral Health‐Related Quality of Life: A Cross‐Sectional Study Incorporating a Mixed Methods Approach |
| topic | Biomedical and clinical sciences Dentistry Health sciences Health services and systems Artificial intelligence artificial intelligence hypodontia natural language processing patient outcomes quality of life tooth development |