| Literature DB >> 36010092 |
Ahmed Alduais1, Abdullah Alduais2, Hind Alfadda3, Silvia Allegretta4.
Abstract
Across the world, many infants, children, adults, and elderly people are reported with many types of disorders and disabilities that damage, delay, or impede typical language development and/or use. Speech-language pathologists and other relevant clinicians are responsible for diagnosing, assessing, and rehabilitating these conditions. In nearly all types of disorders or disabilities that affect language, clinical linguistics plays a significant role in their study, diagnosis, and evaluation. This study provides a thorough analysis of the field of clinical linguistics. Data from Scopus, WOS, and Lens were used between 1981 and 2022. The documents included in the analysis were 1685, 1628, and 2677 articles published between 1981 and 2022 in clinical linguistics in Scopus, WOS, and Lens, respectively. For the purpose of assessing the development and impacts of the field of clinical linguistics, we used eight bibliometric and eight scientometric indicators. As part of the study, the results summarized the top contributors to clinical linguistics in terms of production size by year, country, university/research centre, journal, publisher, and author. The impact of the examined evidence on clinical linguistics was visualized and tabulated in the form of visual networks, citation counts, burst, cooccurrence, centrality, and sigma factors that are helpful in identifying the main influencers in clinical linguistics. A few examples of clinical linguistics patterns that are being explored extensively by researchers include cleft palate speech with model theories, visual feedback, motor speech disorders with instrumental analysis, acoustic analysis to understand conversational breakdown, nonlinear phonological theory, aphasic conversation in atypical interaction, and diagnostic markers in functional segments. There are also phonological disorders, William Syndrome, and the use of ultrasound, which may be considered potential clusters of clinical linguistics. A key contribution of this paper is highlighting the importance of clinical linguistics as well as its integration with linguistics, speech-language pathology, neurolinguistics, psycholinguistics, neuroscience, cognitive sciences, psychology, and psychometrics.Entities:
Keywords: acquired aphasia; clinical linguistics; developmental dysphasia; language disorders; scientometric review; speech disorders; speech–language pathology
Year: 2022 PMID: 36010092 PMCID: PMC9406678 DOI: 10.3390/children9081202
Source DB: PubMed Journal: Children (Basel) ISSN: 2227-9067
Bibliometric and Scientometric Indicators to Map Knowledge Domains of Clinical Linguistics.
| Element | Definition/Specification/Retrieved Data | Database/Software | |||
|---|---|---|---|---|---|
| Indicator | Scopus | WOS | Lens | ||
| Bibliometric | |||||
| Year | Production size by year | √ | √ | √ | |
| Country | Top countries publishing in the field | √ | √ | √ | |
| University | Top universities, research centres, etc. | √ | √ | √ | |
| Source | Top journals, book series, etc. | √ | √ | √ | |
| Publisher | Top publishers | ✕ | √ | √ | |
| Subject area | Top fields associated with the field | √ | √ | √ | |
| Author | Top authors publishing in the field | √ | √ | √ | |
| Citation | Top cited documents | √ | √ | √ | |
| Scientometric | CiteSpace | VOSviewer | |||
| Betweenness centrality | A path between nodes and is achieved when located between two nodes [ | √ | ✕ | ||
| Burst detection | Determines the frequency of a certain event in certain period (e.g., the frequent citation of a certain reference during a period of time) [ | √ | ✕ | ||
| Co-citation | When two references are cited by a third reference [ | √ | √ | ||
| Silhouette | Used in cluster analysis to measure consistency of each cluster with its related nodes [ | √ | ✕ | ||
| Sigma | To measure strength of a node in terms of betweenness centrality citation burst [ | √ | ✕ | ||
| Clusters | “We can probably eyeball the visualized network and identify some prominent groupings” [ | √ | √ | ||
| Citation | “The relatedness of items is determined based on the number of times they cite each other” [ | √ | √ | ||
| Keywords | CiteSpace provides co-occurring author keywords and keywords plus. | √ | √ | ||
Search Strings for Retrieving Data in Clinical Linguistics from Scopus, WOS, and Lens.
| Scopus |
| WOS |
| Lens |
Figure 1Knowledge Production Size of Clinical Linguistics by Year.
Figure 2Knowledge Production Size of Clinical Linguistics by Country.
Figure 3Knowledge Production Size of Clinical Linguistics by University/Research Centre.
Figure 4Knowledge Production Size of Clinical Linguistics by Journal.
Figure 5Knowledge Production Size of Clinical Linguistics by Publisher.
Figure 6Knowledge Production Size of Clinical Linguistics by Research Area.
Figure 7Knowledge Production Size of Clinical Linguistics by Author.
Figure 8Top 10 Keywords with the Strongest Citation Bursts.
Figure 9Top Keywords, Cited Authors, and Clusters.
Figure 10Cooccurrence by Author Keywords Network Visualisation.
Figure 11Co-citation by Cited Author Density Visualisation.
Figure 12Co-citation by Source Network Visualisation.
Top-Cited Documents of Clinical Linguistics Based on Citation Reports from Scopus, WOS, and Lens.
| No. | Source Title | Citation | Citations by Database | ||
|---|---|---|---|---|---|
| Scopus | WOS | Lens | |||
| 1 | A guide to analysing tongue motion from ultrasound images | [ | 223 | 172 | 261 |
| 2 | Assessing intonation and prosody in children with atypical language development: The PEPS-C test and the revised version | [ | 124 | ✕ | ✕ |
| 3 | Assessing vocal development in infants and toddlers | [ | 130 | 116 | ✕ |
| 4 | Automatic contour tracking in ultrasound images | [ | 141 | 119 | ✕ |
| 5 | Differentiating Phonotactic Probability and Neighbourhood Density in Adult Word Learning | [ | ✕ | ✕ | 239 |
| 6 | Estimating dysphonia severity in continuous speech: Application of a multi-parameter spectral/cepstral model | [ | 127 | 103 | ✕ |
| 7 | Estimation of Glottal Closure Instants in Voiced Speech Using the DYPSA Algorithm | [ | ✕ | ✕ | 271 |
| 8 | Extensions to the Speech Disorders Classification System (SDCS) | [ | ✕ | 105 | ✕ |
| 9 | Heritage languages and their speakers: Opportunities and challenges for linguistics | [ | ✕ | ✕ | 375 |
| 10 | New developments in electropalatographic: A state-of-the-art report | [ | 119 | 124 | ✕ |
| 11 | Non-specific nature of specific language impairment: a review of the literature with regard to concomitant motor impairments | [ | ✕ | ✕ | 464 |
| 12 | Phonological development: a normative study of British English-speaking children | [ | 237 | 226 | 275 |
| 13 | Quantifying dysphonia severity using a spectral/cepstral-based acoustic index: Comparisons with auditory-perceptual judgements from the CAPE-V | [ | 173 | 146 | 188 |
| 14 | Reliability studies in broad and narrow phonetic transcription | [ | 187 | 177 | 225 |
| 15 | The Handbook of Conversation Analysis | [ | ✕ | ✕ | 235 |
| 16 | The index of narrative microstructure: a clinical tool for analysing school-age children’s narrative performances. | [ | ✕ | ✕ | 200 |
| 17 | Toward an acoustic typology of motor speech disorders | [ | 132 | 107 | ✕ |
Summary of the Largest Clusters in Clinical Linguistics in Scopus and WOS.
| Cluster ID | Size | Silhouette | Label (LSI) | Label (LLR) | Label (MI) | Average Year |
|---|---|---|---|---|---|---|
| Scopus | ||||||
| 0 | 104 | 0.88 | cleft palate speech | cleft palate speech (317.57, 1.0 × 10−4) | models theories (1.07) | 1989 |
| 1 | 89 | 0.77 | visual feedback | visual feedback (349.49) | Finnish-speaking children (1.57) | 2013 |
| 2 | 86 | 0.814 | motor speech disorder | motor speech disorder (563.43) | instrumental analysis (1.26) | 2007 |
| 3 | 84 | 0.885 | acoustic analysis | acoustic analysis (239.4) | understanding conversational breakdown (0.29) | 1997 |
| 4 | 76 | 0.85 | nonlinear phonological theory | nonlinear phonological theory (286.28) | aspirated target (0.41) | 1993 |
| 5 | 75 | 0.903 | aphasic conversation | intensive language-action therapy (166.27) | atypical interaction (0.33) | 2002 |
| 6 | 55 | 0.904 | diagnostic marker | foreign accent syndrome (176.54) | functional segment (0.32) | 2001 |
| WOS | ||||||
| 0 | 187 | 0.686 | phonological disorder | phonological acquisition (1269.51) | Arabic-speaking children (2.38) | 1997 |
| 1 | 171 | 0.778 | Williams syndrome | Williams syndrome (1774.89) | Arabic-speaking children (2.59) | 2005 |
| 2 | 140 | 0.916 | emergent phenomena | emergent phenomena (574.54) | monitoring change (0.37) | 2006 |
| 3 | 121 | 0.842 | acoustic analysis | Parkinson’s disease (2124.6) | Arabic-speaking children (1.12) | 2001 |
| 4 | 96 | 0.872 | using ultrasound | covert contrast (616.82) | Arabic-speaking children (0.67) | 2006 |
Impact of Research on Clinical Linguistics by Citation Counts.
| WOS | Scopus | ||||
|---|---|---|---|---|---|
| Citation | Reference | Cluster ID | Citation | Reference | Cluster ID |
| 266 | Shriberg [ | 0 | 78 | Boersma [ | 1 |
| 199 | Kent [ | 3 | 65 | Shriberg [ | 2 |
| 169 | Leonard [ | 1 | 53 | McLeod [ | 2 |
| 140 | Grunwell [ | 0 | 50 | [Anonymous], 1991 | 8 |
| 140 | Ingram [ | 0 | 36 | Ball [ | 0 |
| 121 | Bishop [ | 1 | 33 | Leonard [ | 14 |
| 105 | Dodd [ | 0 | 33 | Bishop [ | 6 |
| 99 | Boersma [ | 6 | 30 | Kent [ | 6 |
| 92 | Crystal [ | 0 | 28 | Gibbon [ | 0 |
| 89 | Stoel-Gammon [ | 0 | 27 | Stoel-Gammon [ | 0 |
Impact of Research on Clinical Linguistics by Bursts.
| WOS | Scopus | ||||
|---|---|---|---|---|---|
| Burst | Reference | Cluster ID | Burst | Reference | Cluster ID |
| 17.82 | Crystal [ | 0 | 14.46 | Boersma [ | 1 |
| 16.05 | Grunwell [ | 0 | 11.28 | Byun [ | 1 |
| 13.02 | McLeod [ | 6 | 9.76 | Kent [ | 6 |
| 12.69 | Ingram [ | 0 | 8.84 | Grunwell [ | 0 |
| 11.74 | Boersma [ | 6 | 8.26 | Shriberg [ | 2 |
| 11.73 | Preston [ | 4 | 7.68 | Preston [ | 1 |
| 11.24 | Munson [ | 4 | 6.84 | Zharkova [ | 1 |
| 10.92 | Byun [ | 4 | 6.82 | Bernhardt [ | 4 |
| 10.31 | Fletcher [ | 1 | 6.55 | Hewlett [ | 0 |
| 10.25 | [Anonymous], 2007 | 1 | 6.49 | Crystal [ | 0 |
Figure 13Top 10 Cited Authors and References with the Strongest Citation Bursts.
Impact of Research on Clinical Linguistics by Centrality.
| WOS | Scopus | ||||
|---|---|---|---|---|---|
| Centrality | Reference | Cluster ID | Centrality | Reference | Cluster ID |
| 143 | Grunwell [ | 0 | 142 | Shriberg [ | 2 |
| 143 | Shriberg [ | 0 | 88 | McLeod [ | 2 |
| 125 | Ingram [ | 0 | 85 | [Anonymous] | 8 |
| 113 | Kent [ | 3 | 78 | Boersma [ | 1 |
| 104 | Leonard [ | 1 | 69 | Kent [ | 6 |
| 102 | Gierut [ | 0 | 66 | Ball [ | 0 |
| 86 | Ladefoged [ | 0 | 56 | Bernhardt [ | 4 |
| 82 | Bernhardt [ | 0 | 56 | Stoel-Gammon [ | 0 |
| 82 | Gibbon [ | 4 | 53 | Bishop [ | 6 |
| 81 | Stoel-Gammon [ | 0 | 47 | Gibbon [ | 0 |
Impact of Research on Clinical Linguistics by Sigma.
| WOS | Scopus | ||||
|---|---|---|---|---|---|
| Sigma | Reference | Cluster ID | Sigma | Reference | Cluster ID |
| 0 | Grunwell [ | 0 | 0 | Shriberg [ | 2 |
| 0 | Shriberg [ | 0 | 0 | McLeod [ | 2 |
| 0 | Ingram [ | 0 | 0 | [Anonymous] | 8 |
| 0 | Kent [ | 3 | 0 | Boersma [ | 1 |
| 0 | Leonard [ | 1 | 0 | Kent [ | 6 |
| 0 | Gierut [ | 0 | 0 | Ball [ | 0 |
| 0 | Ladefoged [ | 0 | 0 | Bernhardt [ | 4 |
| 0 | Bernhardt [ | 0 | 0 | Stoel-Gammon [ | 0 |
| 0 | Gibbon [ | 4 | 0 | Bishop [ | 6 |
| 0 | Stoel-Gammon [ | 0 | 0 | Gibbon [ | 0 |