Juxtaposing Medical Centers Using Different Questionnaires Through Score Predictors

  • Clara Puga*
  • , Miro Schleicher
  • , Uli Niemann
  • , Vishnu Unnikrishnan
  • , Benjamin Boecking
  • , Petra Brueggemann
  • , Jorge Simoes
  • , Berthold Langguth
  • , Winfried Schlee
  • , Birgit Mazurek
  • , Myra Spiliopoulou
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
15 Downloads (Pure)

Abstract

Background: Chronic tinnitus is a clinically multidimensional phenomenon that entails audiological, psychological and somatosensory components. Previous research has demonstrated age and female gender as potential risk factors, although studies to this regard are heterogeneous. Moreover, whilst recent research has begun to identify clinical “phenotypes,” little is known about differences in patient population profiles at geographically separated and specialized treatment centers. Identifying such differences might prevent potential biases in joint randomized controlled trials (RCTs) and allow for population-specific treatment adaptations.

Method: Two German tinnitus treatment centers were compared regarding pre-treatment data distributions of their patient population bases. To identify overlapping as well as center-specific factors, juxtaposition-, similarity-, and meta-data-based methods were applied.

Results: Between centers, significant differences emerged. One center demonstrated some predictive power of the patients of the other center with regard to questionnaire score after treatment, indicating similarities in treatment response across center populations. Furthermore, adherence to the completion of the questionnaires was found to be an important factor in predicting post-treatment data.

Discussion: Differential age and gender distributions per center should be considered as regards RCT design and individualized treatment planning.

Original languageEnglish
Article number818686
JournalFrontiers in Neuroscience
Volume16
DOIs
Publication statusPublished - 23 Mar 2022
Externally publishedYes

Keywords

  • Adherence
  • Networks
  • Predictive modeling
  • Similarity
  • Socio-demographics
  • Tinnitus

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