title: Algorithm-Driven Dosage Decisions (AD3): Optimizing Treatment for Children With Language Impairment.
abstract: BACKGROUND
  This study was designed to provide recommended amounts of treatment to achieve the optimal amount of language gain for children with language impairment.
  
  
  METHODS
  The authors retrospectively analyzed treatment outcomes for 233 children for delivered dose, intensity, and cumulative intensity of therapy. The steps of the analytical process they applied to arrive at algorithms for recommended amounts of treatment were (1) multilevel modeling to predict children's language gains from the 3 intensity parameters and (2) extraction of regression weights to create a recommended amount of treatment.
  
  
  RESULTS
  Optimal outcomes can be identified using an equation specifying Ŷ = desired points of change (e.g., 0.6 SD units), V = child's baseline language skills, D = average number of minutes spent targeting language in a session, F = total number of sessions conducted across the year, and D × F = product of planned dose and frequency (cumulative intensity). Input of the values for Ŷ and V provides recommended amount of treatment.
  
  
  CONCLUSIONS
  This study constitutes the first effort to provide empirical guidance on intensity of treatment for children with language impairment. The use of algorithm-driven dosage recommendations may be more effective than clinician judgment and trial and error, although these correlational results must be confirmed with experimental methods.
authors.affiliation: The Ohio State University, Columbus.
authors.forename: Laura M
authors.initials: LM
authors.lastname: Justice
authors.affiliation: The Ohio State University, Columbus.
authors.forename: Jessica
authors.initials: J
authors.lastname: Logan
authors.affiliation: The Ohio State University, Columbus.
authors.forename: Hui
authors.initials: H
authors.lastname: Jiang
authors.affiliation: Texas Tech University Health Sciences Center, Lubbock.
authors.forename: Mary Beth
authors.initials: MB
authors.lastname: Schmitt
mesh_terms: D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D003657:Decision Making; D005260:Female; D006801:Humans; D007807:Language Tests; D007808:Language Therapy / Q000379:methods*; D008137:Longitudinal Studies; D008297:Male; D012189:Retrospective Studies; D013068:Speech Production Measurement; D013070:Speech Therapy / Q000379:methods; D013997:Time Factors