title: Perceptions and experiences of using automated bolus advisors amongst people with type 1 diabetes: a longitudinal qualitative investigation.
abstract: OBJECTIVE
  We explored people's reasons for, and experiences of, using bolus advisors to determine insulin doses; and, their likes/dislikes of this technology.
  
  
  METHODS
  42 people with type 1 diabetes who had received instruction in use of bolus advisors during a structured education course were interviewed post-course and 6 months later. Data were analysed thematically.
  
  
  RESULTS
  Participants who considered themselves to have poor mathematical skills highlighted a gratitude for, and heavy reliance on, advisors. Others liked and chose to use advisors because they saved time and effort calculating doses and/or had a data storage facility. Follow-up interviews highlighted that, by virtue of no longer calculating their doses, participants could become deskilled and increasingly dependent on advisors. Some forgot what their mealtime ratios were; others reported a misperception that, because they were pre-programmed during courses, these parameters never needed changing. Use of data storage facilities could hinder effective review of blood glucose data and some participants reported an adverse impact on glycaemic control.
  
  
  CONCLUSIONS
  While participants liked and perceived benefits to using advisors, there may be unintended consequences to giving people access to this technology. To promote effective use, on-going input and education from trained health professionals may be necessary.
authors.affiliation: Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK. Electronic address: j.lawton@ed.ac.uk.
authors.forename: J
authors.initials: J
authors.lastname: Lawton
authors.affiliation: Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK.
authors.forename: J
authors.initials: J
authors.lastname: Kirkham
authors.affiliation: Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK.
authors.forename: D
authors.initials: D
authors.lastname: Rankin
authors.affiliation: Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK.
authors.forename: K
authors.initials: K
authors.lastname: Barnard
authors.affiliation: Clinical Trials Research Unit, University of Sheffield, Sheffield, UK.
authors.forename: C L
authors.initials: CL
authors.lastname: Cooper
authors.affiliation: The Sheffield Diabetes and Endocrine Centre, Northern General Hospital, Sheffield, UK.
authors.forename: C
authors.initials: C
authors.lastname: Taylor
authors.affiliation: Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, UK.
authors.forename: S
authors.initials: S
authors.lastname: Heller
authors.affiliation: Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, UK.
authors.forename: J
authors.initials: J
authors.lastname: Elliott
mesh_terms: D000328:Adult; D000465:Algorithms; D001786:Blood Glucose / Q000378:metabolism; D015190:Blood Glucose Self-Monitoring / Q000379:methods*; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000188:drug therapy*; D054796:Drug Dosage Calculations; D005260:Female; D005500:Follow-Up Studies; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D006943:Hyperglycemia / Q000097:blood / Q000517:prevention & control; D007003:Hypoglycemia / Q000097:blood / Q000517:prevention & control; D007004:Hypoglycemic Agents / Q000008:administration & dosage*; D007328:Insulin / Q000008:administration & dosage; D008297:Male; D055118:Medication Adherence; D008875:Middle Aged; D017060:Patient Satisfaction; D010465:Perception; D016896:Treatment Outcome
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; D007328:Insulin; C517652:hemoglobin A1c protein, human
keywords: Automated bolus advisor; Patient experience; Qualitative methods; Technology; Type 1 diabetes