DOI: 10.5061/dryad.x69p8czsk
title: Feasibility and acceptability of a tailored health coaching intervention to improve type 2 diabetes self-management in Saudi Arabia: A mixed-methods randomised feasibility trial

description: Background: Around a third of the population of Saudi Arabia have been
 diagnosed with Type 2 diabetes, a condition often requiring lifestyle
 changes. Personalised health coaching, a strategy developed to assist
 individuals in overcoming challenges to adopt healthy behaviours, has not
 yet been widely applied in the country. Aims: We aim to explore the
 feasibility and acceptability of tailored health coaching in Saudi Arabia,
 in order to help those with Type 2 diabetes to more effectively manage
 their condition. Methods: Using a mixed-methods approach, this research
 involved a randomised controlled trial with 30 Saudi adults who have Type
 2 diabetes. They were randomly allocated into either the intervention or
 control arm for 12 weeks. The Capability, Opportunity, Motivation, and
 Behaviour framework was used to guide the intervention implementation
 along with the Behaviour Change Techniques Taxonomy version 1. The primary
 goal was to assess the suitability and duration of the intervention,
 recruitment, retention, and completion rates. The secondary outcome
 focused on the preliminary efficacy of the health coaching measured by the
 glycaemic index, blood pressure, body mass index, waist circumference,
 weight, patient self-efficacy, and diabetes self-management. Results: The
 results showed high rates of eligibility, recruitment, and retention (a
 screening rate of 90%, a recruiting rate of 79%, and a retention rate of
 97%). Notable improvements were observed in the health coaching group
 across five outcomes: HbA1c, BMI, waist circumference, patient
 self-efficacy, and diabetes self-care. Qualitative findings highlighted
 the participants' perceived benefits from the intervention, including
 enhanced motivation, better understanding of diabetes management, and a
 supportive coaching relationship. Participants expressed high satisfaction
 with the intervention and advocated for its expansion. Conclusion: The
 findings demonstrated positive outcomes, supporting the need for a larger
 randomised controlled trial to evaluate the efficacy of health coaching in
 improving diabetes self-management among individuals with Type 2 diabetes.
description: # Feasibility and Acceptability of a Tailored Health Coaching Intervention
 to Improve Type 2 Diabetes Self-Management in Saudi Arabia: A
 Mixed-Methods Randomised Feasibility Trial
 [https://doi.org/10.5061/dryad.x69p8czsk](https://doi.org/10.5061/dryad.x69p8czsk) This dataset accompanies the manuscript titled "Feasibility and Acceptability of a Tailored Health Coaching Intervention to Improve Type 2 Diabetes Self-Management in Saudi Arabia: A Mixed-Methods Randomised Feasibility Trial". It consists of quantitative and qualitative data from a randomized controlled feasibility trial aimed at assessing the impact of health coaching on Type 2 Diabetes management in Saudi Arabia. ## Description of the data and file structure Data Files: Quantitative_Data.xlsx: Contains anonymized participant data including baseline and post-intervention measures of HbA1c levels, BMI, waist circumference, blood pressure, and diabetes self-care activities. Qualitative_Transcripts.docx: Transcripts from interviews and focus groups discussing participant experiences and perceptions of the health coaching intervention. Describe relationships between data files, missing data codes, other abbreviations used. Be as descriptive as possible. Relationships and Abbreviations: HbA1c: Hemoglobin A1c BMI: Body Mass Index COM-B: Capability, Opportunity, Motivation, and Behavior BCTTv1: Behavior Change Technique Taxonomy version 1 ## Sharing/Access information The data are stored and accessible at the following location on Dryad: [https://doi.org/10.5061/dryad.x69p8czsk](https://doi.org/10.5061/dryad.x69p8czsk). No secondary sources were used to derive this data. ## Code/Software The analysis was conducted using SPSS and Stata for quantitative data and NVivo for qualitative data analysis. The specific scripts and commands used are included in the Analysis_Scripts folder: Quantitative_Analysis.sps: SPSS script for statistical testing and regression analysis. Qualitative_Analysis.qda: NVivo project file with coding details.Please ensure that you have the appropriate versions of these software packages to run the scripts. The versions used are SPSS v25, Stata 16, and NVivo 12.