Lawrence Fisher1, Danielle Hessler2, William Polonsky3, Lisa Strycker4, Umesh Masharani5, Anne Peters6. 1. Department of Family & Community Medicine, University of California,s San Francisco, San Francisco, CA, USA. Electronic address: larry.fisher@ucsf.edu. 2. Department of Family & Community Medicine, University of California,s San Francisco, San Francisco, CA, USA. 3. Department of Psychiatry, University of California, San Diego, San Diego, CA, USA; Behavioral Diabetes Institute, San Diego, CA, USA. 4. Oregon Research Institute, Eugene, OR, USA. 5. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. 6. University of Southern California, Los Angeles, CA, USA.
Abstract
AIMS: To document the prevalence and 9-month incidence of elevated diabetes distress (DD) and the stability of DD over time using both single threshold and minimal clinically important differences (MCID) approaches. METHODS: Adults with type 1 diabetes (T1D) (N=224) completed the 28-item T1-Diabetes Distress Scale (T1-DDS) at baseline and 9months. A T1-DDS threshold was identified with spline analysis and MCID was calculated from the standard error of measurement. RESULTS: Analyses supported a cut-point of ≥2.0 for elevated DD. The prevalence and 9-month incidence of elevated DD was 42.1% and 54.4%, respectively. MCID was ±0.19 but varied by subscale (.26 to .50). Elevated DD was stable: only 20% crossed 2.0 over 9months. MCID analyses showed that change also occurred among those who remained either below or above 2.0 over time. Change varied by source of distress, with Powerlessness the most prevalent and stable. Using MCID, only participant age, gender and number of complications predicted change. CONCLUSIONS: The prevalence, 9-month incidence and stability of elevated DD are high among adults with T1D, with change based on source of DD. We propose a combined cut-point/MCID framework for measuring change in DD, since each approach reflects unique characteristics of change over time.
AIMS: To document the prevalence and 9-month incidence of elevated diabetes distress (DD) and the stability of DD over time using both single threshold and minimal clinically important differences (MCID) approaches. METHODS: Adults with type 1 diabetes (T1D) (N=224) completed the 28-item T1-Diabetes Distress Scale (T1-DDS) at baseline and 9months. A T1-DDS threshold was identified with spline analysis and MCID was calculated from the standard error of measurement. RESULTS: Analyses supported a cut-point of ≥2.0 for elevated DD. The prevalence and 9-month incidence of elevated DD was 42.1% and 54.4%, respectively. MCID was ±0.19 but varied by subscale (.26 to .50). Elevated DD was stable: only 20% crossed 2.0 over 9months. MCID analyses showed that change also occurred among those who remained either below or above 2.0 over time. Change varied by source of distress, with Powerlessness the most prevalent and stable. Using MCID, only participant age, gender and number of complications predicted change. CONCLUSIONS: The prevalence, 9-month incidence and stability of elevated DD are high among adults with T1D, with change based on source of DD. We propose a combined cut-point/MCID framework for measuring change in DD, since each approach reflects unique characteristics of change over time.
Authors: Lawrence Fisher; William H Polonsky; Danielle M Hessler; Umesh Masharani; Ian Blumer; Anne L Peters; Lisa A Strycker; Vicky Bowyer Journal: J Diabetes Complications Date: 2015-02-07 Impact factor: 2.852
Authors: Danielle Hessler; Lawrence Fisher; Russell E Glasgow; Lisa A Strycker; L Miriam Dickinson; Patricia A Arean; Umesh Masharani Journal: Diabetes Care Date: 2013-10-29 Impact factor: 19.112
Authors: Marisa E Hilliard; Jean M Lawrence; Avani C Modi; Andrea Anderson; Tessa Crume; Lawrence M Dolan; Anwar T Merchant; Joyce P Yi-Frazier; Korey K Hood Journal: Diabetes Care Date: 2013-01-22 Impact factor: 19.112
Authors: Lawrence Fisher; Danielle Hessler; Russell E Glasgow; Patricia A Arean; Umesh Masharani; Diana Naranjo; Lisa A Strycker Journal: Diabetes Care Date: 2013-06-04 Impact factor: 19.112
Authors: Marisa E Hilliard; Maartje De Wit; Rachel M Wasserman; Ashley M Butler; Meredyth Evans; Jill Weissberg-Benchell; Barbara J Anderson Journal: Pediatr Diabetes Date: 2017-09-22 Impact factor: 4.866
Authors: William H Polonsky; Jennifer E Layne; Christopher G Parkin; Coco M Kusiak; Nathan A Barleen; David P Miller; Howard Zisser; Ronald F Dixon Journal: Clin Diabetes Date: 2020-10
Authors: Lawrence Fisher; Danielle Hessler; William H Polonsky; Umesh Masharani; Susan Guzman; Vicky Bowyer; Lisa Strycker; Andrew Ahmann; Marina Basina; Ian Blumer; Charles Chloe; Sarah Kim; Anne L Peters; Martha Shumway; Karen Weihs; Patricia Wu Journal: Diabetes Care Date: 2018-07-05 Impact factor: 19.112
Authors: Cheryl L P Vigen; Kristine Carandang; Jeanine Blanchard; Paola A Sequeira; Jamie R Wood; Donna Spruijt-Metz; Robin Whittemore; Anne L Peters; Elizabeth A Pyatak Journal: Diabetes Educ Date: 2018-10-08 Impact factor: 2.140