Measuring the quality of Patients' goals and action plans: Development and validation of a novel tool

Cayla R. Teal, Paul Haidet, Ajay S. Balasubramanyam, Elisa Rodriguez, Aanand D. Naik

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Background: The purpose of this study is to develop and test reliability, validity, and utility of the Goal-Setting Evaluation Tool for Diabetes (GET-D). The effectiveness of diabetes self-management is predicated on goal-setting and action planning strategies. Evaluation of self-management interventions is hampered by the absence of tools to assess quality of goals and action plans. To address this gap, we developed the GET-D, a criteria-based, observer rating scale that measures the quality of patients' diabetes goals and action plans. Methods. We conducted 3-stage development of GET-D, including identification of criteria for observer ratings of goals and action plans, rater training and pilot testing; and then performed psychometric testing of the GET-D. Results: Trained raters could effectively rate the quality of patient-generated goals and action plans using the GET-D. Ratings performed by trained evaluators demonstrated good raw agreement (94.4%) and inter-rater reliability (Kappa = 0.66). Scores on the GET-D correlated well with measures theoretically associated with goal-setting, including patient activation (r=.252, P<.05), diabetes specific self-efficacy (r=.376, P<.001) and inverse relationship with depression (r= -.376, P<.01). Significant between group differences (P<.01) in GET-D scores between goal-setting intervention (mean = 7.33, standard deviation = 4.4) and education groups (mean = 4.93, standard deviation = 3.9) confirmed construct validity of the GET-D. Conclusions: The GET-D can reliably and validly rate the quality of goals and action plans. It holds promise as a measure of intervention fidelity for clinical interventions that promote diabetes self-management behaviors to improve clinical outcomes. Trial registration. Clinicaltrials.gov Identifier: NCT00481286.

Original languageEnglish (US)
Article number152
JournalBMC medical informatics and decision making
Volume12
Issue number1
DOIs
StatePublished - 2012

All Science Journal Classification (ASJC) codes

  • Health Policy
  • Health Informatics

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