Academic Journal
Προβολή σε EDS

Improving Evidence-Based Practice Through the Development and Validation of Key Words to Identify Intervention Articles in Communication Disorders.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Improving Evidence-Based Practice Through the Development and Validation of Key Words to Identify Intervention Articles in Communication Disorders.
Συγγραφείς: Nisha, Sonia Islam1, Wang, Qingyun2, Yu, Charles2, Ji, Heng2, Hendricks, Alison Eisel1 ahendric@buffalo.edu
Πηγή: Language, Speech & Hearing Services in Schools. Apr2026, Vol. 57 Issue 2, p525-540. 16p.
Θεματικοί όροι: *Treatment of communicative disorders, *Subject headings, *Database searching, *Data analysis, *Research funding, *Artificial intelligence, *Statistical sampling, *Data curation, *Speech-language pathology, *Natural language processing, *Experimental design, *Statistics, *Acquisition of data, *Medical research, *Evidence-based medicine, *Sensitivity & specificity (Statistics), *Inter-observer reliability, *Abstracting & indexing services, Research evaluation
Εταιρία/Οντότητα: American Speech-Language-Hearing Association
Περίληψη: Purpose: Although evidence-based practice (EBP) promotes better clinical practice, implementing it in speech-language pathology is challenging. A limited number of intervention studies and inconsistent use of key words in abstracts complicates the implementation of EBP. Given time constraints in clinical practice, identifying relevant research from study abstracts would provide an efficient method for identifying intervention studies. In this project, we compare the classification accuracy of an artificial intelligence (AI)-created set of key words and a set of evidencebased key words that were developed through an analysis of commonly used words in intervention abstracts from American Speech-Language-Hearing Association (ASHA) journals. Method: Abstracts from three major ASHA journals were crawled using Selenium and WebDriver Manager, creating a large database of abstracts for analysis. In Study 1, a random sample of 180 abstracts was annotated as reporting on intervention or nonintervention studies to develop a set of evidence-based key words. In Study 2, classification accuracy was calculated to validate these key words by comparing them with a set of AI-generated (ChatGPT-4.0) key words. Results: The results suggested that 12%-15% of studies report on an intervention study. Evidence-based key words had higher sensitivity (85%) and a higher positive predictive value (27%) but a lower specificity rate (67%). Also, the likelihood ratio suggested that evidence-based key words had a moderate capacity to identify nonintervention studies (true negatives) accurately. Conclusions: Evidence-based key words have the potential to accurately classify intervention studies, addressing a key barrier to EBP implementation in clinical practice. Future research should focus on refining key words by integrating AI and promoting standardized journal reporting by incorporating uniform key words in abstracts. [ABSTRACT FROM AUTHOR]
Βάση Δεδομένων: Academic Search Index
FullText Text:
  Availability: 0
Header DbId: asx
DbLabel: Academic Search Index
An: 192859142
RelevancyScore: 1491
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1491.07458496094
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Improving Evidence-Based Practice Through the Development and Validation of Key Words to Identify Intervention Articles in Communication Disorders.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Nisha%2C+Sonia+Islam%22">Nisha, Sonia Islam</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Wang%2C+Qingyun%22">Wang, Qingyun</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Yu%2C+Charles%22">Yu, Charles</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Ji%2C+Heng%22">Ji, Heng</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Hendricks%2C+Alison+Eisel%22">Hendricks, Alison Eisel</searchLink><relatesTo>1</relatesTo><i> ahendric@buffalo.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Language%2C+Speech+%26+Hearing+Services+in+Schools%22">Language, Speech & Hearing Services in Schools</searchLink>. Apr2026, Vol. 57 Issue 2, p525-540. 16p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Treatment+of+communicative+disorders%22">Treatment of communicative disorders</searchLink><br />*<searchLink fieldCode="DE" term="%22Subject+headings%22">Subject headings</searchLink><br />*<searchLink fieldCode="DE" term="%22Database+searching%22">Database searching</searchLink><br />*<searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Statistical+sampling%22">Statistical sampling</searchLink><br />*<searchLink fieldCode="DE" term="%22Data+curation%22">Data curation</searchLink><br />*<searchLink fieldCode="DE" term="%22Speech-language+pathology%22">Speech-language pathology</searchLink><br />*<searchLink fieldCode="DE" term="%22Natural+language+processing%22">Natural language processing</searchLink><br />*<searchLink fieldCode="DE" term="%22Experimental+design%22">Experimental design</searchLink><br />*<searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br />*<searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink><br />*<searchLink fieldCode="DE" term="%22Medical+research%22">Medical research</searchLink><br />*<searchLink fieldCode="DE" term="%22Evidence-based+medicine%22">Evidence-based medicine</searchLink><br />*<searchLink fieldCode="DE" term="%22Sensitivity+%26+specificity+%28Statistics%29%22">Sensitivity & specificity (Statistics)</searchLink><br />*<searchLink fieldCode="DE" term="%22Inter-observer+reliability%22">Inter-observer reliability</searchLink><br />*<searchLink fieldCode="DE" term="%22Abstracting+%26+indexing+services%22">Abstracting & indexing services</searchLink><br /><searchLink fieldCode="DE" term="%22Research+evaluation%22">Research evaluation</searchLink>
– Name: SubjectCompany
  Label: Company/Entity
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22American+Speech-Language-Hearing+Association%22">American Speech-Language-Hearing Association</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: Although evidence-based practice (EBP) promotes better clinical practice, implementing it in speech-language pathology is challenging. A limited number of intervention studies and inconsistent use of key words in abstracts complicates the implementation of EBP. Given time constraints in clinical practice, identifying relevant research from study abstracts would provide an efficient method for identifying intervention studies. In this project, we compare the classification accuracy of an artificial intelligence (AI)-created set of key words and a set of evidencebased key words that were developed through an analysis of commonly used words in intervention abstracts from American Speech-Language-Hearing Association (ASHA) journals. Method: Abstracts from three major ASHA journals were crawled using Selenium and WebDriver Manager, creating a large database of abstracts for analysis. In Study 1, a random sample of 180 abstracts was annotated as reporting on intervention or nonintervention studies to develop a set of evidence-based key words. In Study 2, classification accuracy was calculated to validate these key words by comparing them with a set of AI-generated (ChatGPT-4.0) key words. Results: The results suggested that 12%-15% of studies report on an intervention study. Evidence-based key words had higher sensitivity (85%) and a higher positive predictive value (27%) but a lower specificity rate (67%). Also, the likelihood ratio suggested that evidence-based key words had a moderate capacity to identify nonintervention studies (true negatives) accurately. Conclusions: Evidence-based key words have the potential to accurately classify intervention studies, addressing a key barrier to EBP implementation in clinical practice. Future research should focus on refining key words by integrating AI and promoting standardized journal reporting by incorporating uniform key words in abstracts. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asx&AN=192859142
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1044/2025_LSHSS-25-00144
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 525
    Subjects:
      – SubjectFull: American Speech-Language-Hearing Association
        Type: general
      – SubjectFull: Treatment of communicative disorders
        Type: general
      – SubjectFull: Subject headings
        Type: general
      – SubjectFull: Database searching
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Statistical sampling
        Type: general
      – SubjectFull: Data curation
        Type: general
      – SubjectFull: Speech-language pathology
        Type: general
      – SubjectFull: Natural language processing
        Type: general
      – SubjectFull: Experimental design
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Acquisition of data
        Type: general
      – SubjectFull: Medical research
        Type: general
      – SubjectFull: Evidence-based medicine
        Type: general
      – SubjectFull: Sensitivity & specificity (Statistics)
        Type: general
      – SubjectFull: Inter-observer reliability
        Type: general
      – SubjectFull: Abstracting & indexing services
        Type: general
      – SubjectFull: Research evaluation
        Type: general
    Titles:
      – TitleFull: Improving Evidence-Based Practice Through the Development and Validation of Key Words to Identify Intervention Articles in Communication Disorders.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Nisha, Sonia Islam
      – PersonEntity:
          Name:
            NameFull: Wang, Qingyun
      – PersonEntity:
          Name:
            NameFull: Yu, Charles
      – PersonEntity:
          Name:
            NameFull: Ji, Heng
      – PersonEntity:
          Name:
            NameFull: Hendricks, Alison Eisel
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 01611461
          Numbering:
            – Type: volume
              Value: 57
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Language, Speech & Hearing Services in Schools
              Type: main
ResultId 1