title: Confirming the theoretical structure of expert-developed text messages to improve adherence to anti-hypertensive medications.
abstract: Text messages can improve medication adherence and outcomes in several conditions. For this study, experts developed text messages addressing determinants of medication adherence: disease beliefs, medication necessity, medication concerns, and forgetfulness, as well as positive reinforcement messages for patients who were adherent.
  
  
  
  To validate expert-developed text messages to address medication non-adherence with a group of non-researchers.
  
  
  
  A two-wave, card-sorting activity was conducted with students and staff at the University of Michigan. In the first wave, 40 participants grouped 32 messages addressing barriers for medication adherence (disease beliefs, medication necessity, medication concerns, and forgetfulness) according to their perceived relationship. Messages with poor grouping agreement were deleted or modified. In the second wave, positive reinforcement messages were developed and tested along with the previous categories (36 messages) by 37 participants. Similarity and cluster analyses were used to assess agreement between experts and participants.
  
  
  
  In the first card-sorting wave, participants grouped messages into between 2 and 13 separate categories. Similarity analysis showed four groupings of messages, however, some had an agreement below 50% and clusters appeared dispersed. In the second wave, and after messages being edited, participants grouped the messages into between 4 and 9 categories. Five groups (now including positive reinforcement messages) were identified with higher agreement in the similarity and cluster analyses.
  
  
  
  The structure of expert-developed text messages to address medication adherence key barriers was confirmed. Messages will be used in future research to determine their impact on affecting medication adherence to anti-hypertensive medications using a reinforcement learning controlled text messaging service.
authors.affiliation: Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, USA. Electronic address: kfarris@umich.edu.
authors.forename: Karen B
authors.initials: KB
authors.lastname: Farris
authors.affiliation: Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, USA.
authors.forename: Teresa M
authors.initials: TM
authors.lastname: Salgado
authors.affiliation: Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: Batra
authors.affiliation: Ann Arbor Department of Veterans Affairs Center for Clinical Management Research, Ann Arbor, USA; University of Michigan School of Public Health, Ann Arbor, USA; University of Michigan School of Medicine, Ann Arbor, USA.
authors.forename: John D
authors.initials: JD
authors.lastname: Piette
authors.affiliation: Division of Computer Science and Engineering, Department of Electrical Engineering and Computer Science, University of Michigan College of Engineering, Ann Arbor, USA.
authors.forename: Satinder
authors.initials: S
authors.lastname: Singh
authors.affiliation: University of Michigan College of Pharmacy, Ann Arbor, USA.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Guhad
authors.affiliation: Division of Computer Science and Engineering, Department of Electrical Engineering and Computer Science, University of Michigan College of Engineering, Ann Arbor, USA.
authors.forename: Sean
authors.initials: S
authors.lastname: Newman
authors.affiliation: Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, USA.
authors.forename: Vincent D
authors.initials: VD
authors.lastname: Marshall
authors.affiliation: Department of Internal Medicine, University of Michigan School of Medicine, Ann Arbor, USA.
authors.forename: Larry
authors.initials: L
authors.lastname: An
mesh_terms: D000959:Antihypertensive Agents / Q000008:administration & dosage*; D016000:Cluster Analysis; D006801:Humans; D055118:Medication Adherence / Q000523:psychology*; D012054:Reinforcement, Psychology; D017010:Reminder Systems; D060145:Text Messaging
chemical_list: D000959:Antihypertensive Agents
keywords: Adherence; Card-sort technique; Mobile health; Text messaging