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The effect of diabetes health coaching on glycemic control and quality of life in adults living with type 2 diabetes: a community-based randomized controlled trial.
Abstract
Background
Health coaching for type 2 diabetes (T2DM) holds promise in improving clinical health outcomes and quality of life. The purpose of this study was to evaluate the effect of a 12-month telephone diabetes health coaching (DHC) intervention on glycemic control in persons living with T2DM.
Methods
In this community-based randomized controlled trial, adults with T2DM, an A1C of > 7.5% and telephone access were assigned to either usual diabetes education (DE) or DHC and access to DE. The primary outcome was change in A1C after one year; secondary outcomes included Audit of Diabetes-Dependent Quality of Life 19 (ADDQoL) and self-care behaviours. Safety was assessed in all participants. (clinicaltrials.gov, NCT02128815)
Findings
365 participants (50% female, mean age 57 years, mean A1C 8.98%) were randomized to control (DE; n=177) or intervention (DHC; n=188). The A1C level decreased by an absolute amount of 1.8% and 1.3% in the intervention and control group, respectively. DHC plus DE reduced A1C by 0.49% more than DE alone (95% CI -0.80 to -0.18; p < 0.01) and improved ADDQoL scores, with between group differences in the average weighted score of 0.28 (CI 0.04 to 0.52; p = 0.02). There were no differences in proportion of participants having an emergency department visit or hospitalization between groups.
Interpretation
Providing frequent telephone-based DHC and access to DE to adults living with T2DM for one year supports improvements in glycemic control and quality of life.
... In Type 1 and Type 2 diabetes, interventions aim to improve self-management and glycemic control. For example, Sherifali et al., (2021) demonstrated that health coaching can improve glycemic control and quality of life in Type 2 diabetes patients. Some studies also explore interventions for asthma and COPD, such as Benzo et al., (2021), who showed the effectiveness of home-based health coaching and rehabilitation for managing COPD symptoms. ...
... Digital storytelling and health coaching also improved medication adherence, as seen in Carlson et al., (2020), where digital storytelling enhanced patient engagement and adherence. Health coaching also improved glycemic control and quality of life in Type 2 diabetes patients, as shown by Sherifali et al., (2021). ...
... This approach not only enhances medication adherence and self-management but also improves quality of life and patient engagement, as observed in peer-coached storytelling programs for diabetes patients (Andreae et al., 2021). Health coaching, in particular, has been shown to improve glycemic control and quality of life for Type 2 diabetes patients (Sherifali et al., 2021). However, several research gaps need to be addressed. ...
Chronic diseases such as diabetes, hypertension, and cardiovascular conditions require ongoing and holistic management. Digital storytelling and health coaching are innovative methods that support chronic disease management. Digital storytelling enables patients to share personal experiences, enhancing their understanding and engagement. Health coaching offers personalized support to help patients achieve health goals through sustainable lifestyle changes. This scoping review aims to examine the existing literature on the use of digital storytelling and health coaching in chronic disease management. The review focuses on the potential benefits of combining these approaches and identifying research gaps. A literature search was conducted across electronic databases (PubMed, Scopus, Google Scholar) using keywords related to digital storytelling, health coaching, and chronic disease management. Studies meeting the inclusion criteria were analyzed to identify key themes and research gaps. The findings indicate that digital storytelling enhances patient understanding of their condition, promotes better communication with healthcare providers, and increases patient engagement. Health coaching effectively helps patients set and achieve health goals through a structured and personalized approach. The combination of these methods provides a more holistic approach to chronic disease management. Integrating digital storytelling and health coaching provides a personalized, empathetic, and coordinated method for addressing chronic illnesses. However, further research is required to enhance integration strategies and evaluate the sustained impact of these methods across different long-term health conditions.
... The field of lifestyle medicine aspires to move today's population from poor health (40% of adults have 2 or more chronic diseases 1 ) to good health through daily engagement in lifestyle behaviors that treat and reverse chronic diseases and deliver the vitality needed for a high quality of life. Lifestyle medicine is best practiced as a team-based endeavor where multiple roles and coordinated interventions together, including coaching, deliver clinically significant results. 2 In the health and well-being coaching literature, robust studies demonstrate coaching efficacy, [3][4][5][6][7] combining physician counseling and encouragement, lifestyle education and skills programs, and an ongoing coaching partnership. One role of a coach is to help a patient translate lifestyle medicine treatment plans, education, and skills programs into daily life, aligned with their values, priorities, and readiness to change. ...
... 17 • no. 5 American Journal of Lifestyle Medicine medicine benefits from this coaching mindset. 27 Our Mindsets are Ground Zero-Hold Space, Not Fill Space ...
... vol. 17 • no. 5 American Journal of Lifestyle Medicine A generative moment in coaching is a healthy process of integration in action. Being in touch with the uncomfortable state of feeling stuck, and through a non-linear and generative coaching conversation, inviting and taking in new and varied perspectives, a moment of integration arrives. ...
The aspiration of lifestyle medicine practitioners is a healthy population engaged daily in lifestyle behaviors that generate the vitality needed to live a good life. That said, we are aware that there is a high population prevalence of low readiness to change behavior. This article proposes that we can improve readiness to change by shifting our expert mindsets to coaching mindsets. We focus first on helping others mobilize resources that improve readiness to change, including motivation and confidence—rather than beginning with expert education and training on new skills and behaviors. We call this coaching activity tilling the (patient’s) ground, which then germinates an interest in a mindset shift from an unresolved state ( e.g., I don’t have time to exercise) to a new state ( e.g., I might feel better and be more productive, if I exercise). In a generative conversation, moving from unresolved to resolved improves confidence in behavior change. This mindset shift is called integration—connecting and integrating an unresolved state to new thoughts, ideas, or perspectives (the ah-hah experience). We use the ground zero metaphor in multiple ways, and invite readers to till their own ground, generate potential, and enable integration as role models.
... A total of 3222 participants were included in the 20 studies, of whom 1674 were randomised to receive coaching interventions and 1548 were allocated to control groups. The majority of studies (n = 10) were conducted in the US [34][35][36][37][38][39][40][41][42][43], two were conducted in Taiwan [44,45], and the rest were conducted once in different countries including Turkey [46], Canada [47], South Korea [48], Norway [49], Finland [50], Germany [51], Belgium [52], and Australia [53]. In the 17 studies that reported gender of participants, 53% of participants were female. ...
... Due to the inconsistent reporting of other demographic and socioeconomic characteristics, such as education, ethnicity and income status, across the 20 papers we were unable to report them here. The recruitment of participants was varied and drawn from different communities including ethnic community centres [36], community health centres [34,48,49], community advertisement [43,47,49,51], primary care or hospital clinics [38,41,45,46,53] and databases [40,44,50,52]. For clinical factors, including HbA1c, there were no discernible changes between the intervention and control groups at baseline. ...
... Health coaching was delivered through various methods including exclusive telephone-based [34,39,43,47,52,53], exclusive web or mobile-based remote patient monitoring/electronic assistance (ERPM/EA) systems [37] or in combinations of face-to-face and telephonebased [36,38,40,42,[44][45][46]; face-to-face and ERPM/E A [48] telephone-based and ERPM/EA [49][50][51] or face-toface, telephone-based and ERPM/EA [35,41]. The duration of studies ranged from two [37] [48] to 18 months [52] (Mdn = 6 months). ...
Background
Given the high rates globally of Type 2 Diabetes Mellitus (T2DM), there is a clear need to target health behaviours through person-centred interventions. Health coaching is one strategy that has been widely recognised as a tool to foster positive behaviour change. However, it has been used inconsistently and has produced mixed results. This systematic review sought to explore the use of behaviour change techniques (BCTs) in health coaching interventions and identify which BCTs are linked with increased effectiveness in relation to HbA1C reductions.
Methods
In line with the PICO framework, the review focused on people with T2DM, who received health coaching and were compared with a usual care or active control group on HbA1c levels. Studies were systematically identified through different databases including Medline, Web of science, and PsycINFO searches for relevant randomised controlled trials (RCTs) in papers published between January 1950 and April 2022. The Cochrane collaboration tool was used to evaluate the quality of the studies. Included papers were screened on the reported use of BCTs based on the BCT taxonomy. The effect sizes obtained in included interventions were assessed by using Cohen’s d and meta-analysis was used to estimate sample-weighted average effect sizes (Hedges’ g).
Results
Twenty RCTs with a total sample size of 3222 were identified. Random effects meta-analysis estimated a small-sized statistically significant effect of health coaching interventions on HbA1c reduction ( g + = 0.29, 95% CI: 0.18 to 0.40). A clinically significant HbA1c decrease of ≥5 mmol/mol was seen in eight studies. Twenty-three unique BCTs were identified in the reported interventions, with a mean of 4.5 (SD = 2.4) BCTs used in each study. Of these, Goal setting (behaviour) and Problem solving were the most frequently identified BCTs. The number of BCTs used was not related to intervention effectiveness. In addition, there was little evidence to link the use of specific BCTs to larger reductions in HbA1c across the studies included in the review; instead, the use of Credible source and Social reward in interventions were associated with smaller reductions in HbA1c.
Conclusion
A relatively small number of BCTs have been used in RCTs of health coaching interventions for T2DM. Inadequate, imprecise descriptions of interventions and the lack of theory were the main limitations of the studies included in this review. Moreover, other possible BCTs directly related to the theoretical underpinnings of health coaching were absent. It is recommended that key BCTs are identified at an early stage of intervention development, although further research is needed to examine the most effective BCTs to use in health coaching interventions.
Trial registration
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021228567 .
... Our search strategy yielded 3,612 citations after duplicates were removed. We assessed 137 full-text articles for eligibility and included 9 RCTs in this review ( Figure 1) (27)(28)(29)(30)(31)(32)(33)(34)(35). The studies were published from 2014 to 2021. ...
... A total of 5 studies measured outcomes beyond immediate posttreatment and 4 of these studies conducted follow-up measurements 6 months after intervention completion (29-32) while 1 study completed measurements 12 months postintervention (28). Adverse events were only reported by 2 studies (27,34). Balducci et al., 2019 reported any elective surgeries and medical conditions that occurred outside of the intervention and hypoglycemic episodes, arrythmias, and musculoskeletal injuries or discomfort that occurred during intervention visits or sessions (27). ...
... Balducci et al., 2019 reported any elective surgeries and medical conditions that occurred outside of the intervention and hypoglycemic episodes, arrythmias, and musculoskeletal injuries or discomfort that occurred during intervention visits or sessions (27). Sherifali et al., 2021 reported on hospitalizations (for any reason), emergency department visits, and hypo-and hyper-glycemic episodes requiring hospitalizations (34). There were no statistically significant differences in proportion of participants with adverse events between the 2 groups. ...
Background
As diabetes self-management necessitates life-long learning, behaviour change, support, and monitoring, health coaching is a promising intervention to assist individuals in more than just meeting glycemic goals and glycated hemoglobin (A1C) targets. Currently, studies of health coaching for type 2 diabetes (T2DM) are limited due to their emphasis on glycemic control. The goal of this systematic review and meta-analysis is to determine the effects of health coaching on adults with T2DM based on quadruple aim outcomes and to assess the implementation of these interventions.
Methods
We searched 6 databases for randomized controlled trials of health coaching interventions delivered by a health professional for adults with T2DM. Reviewers screened citations, extracted data, and assessed risk of bias and certainty of evidence (GRADE). We assessed statistical and methodological heterogeneity and performed a meta−analysis of studies.
Results
Nine studies were included in this review. Our meta-analysis showed a significant reduction of A1C [0.24 (95% CI, -0.38 to -0.09)] after exposure to diabetes health coaching, and small to trivial significant benefits for BMI, waist circumference, body weight, and depression/distress immediately post intervention based on moderate certainty of evidence. However, long term benefit of these clinical outcomes were not maintained at follow-up timepoints. There was a small significant benefit for systolic blood pressure which was maintained after the completion of health coaching exposure at follow-up, but there was no statistically significant benefit in other secondary outcomes such as diastolic blood pressure and lipid profile measures (e.g. triglycerides). Very few studies reported on other quadruple aim measures such as patient-reported outcomes, cost of care, and healthcare provider experience.
Conclusions
Our systematic review and meta-analysis shows that health coaching interventions can have short term impact beyond glucose control on cardiometabolic and mental health outcomes. Future studies should try to examine quadruple aim outcomes to better assess the benefit and impact of these interventions at longer time points and following termination of the coaching program.
Systematic Review Registration
https://www.crd.york.ac.uk/prospero, identifier (CRD42022347478).
... Of these, 5105 received telerehabilitation and 4572 received conventional face-to-face consultations; 6 studies were 3-armed randomized controlled trials [11][12][13][14][15][16], and the remaining studies were 2-armed studies. Among the 38 included studies, 9 targeted patients with cardiac disease [15][16][17][18][19][20][21][22][23], 9 targeted chronic patients with respiratory disease [24][25][26][27][28][29][30][31][32], 9 targeted patients with diabetes [11,12,[33][34][35][36][37][38][39], 4 targeted patients with hypertension [14,[40][41][42], 4 targeted patients with cancer [43][44][45][46], and 3 targeted patients with stroke [13,47,48]. ...
... A total of 32 studies conducted telerehabilitation programs through telephone (n=26) [11][12][13]15,17,[19][20][21][22][24][25][26][27][28]33,35,[37][38][39][40][41][42][43][46][47][48], videoconferencing (n=4) [21,30,32,34], SMS text messaging (n=2) [14,41], or WhatsApp (n=1) [45] (Multimedia Appendix 3). Nurse-led counseling was mostly implemented weekly (n=4), monthly (n=5), or a combination of both (n=7). ...
... For diabetes, 1 study [34] showed no significant difference, while 2 studies [38,39] reported an improvement in the quality of life of patients after receiving nurse-led telerehabilitation. ...
Background:
Chronic diseases are putting huge pressure on health care systems. Nurses are widely recognized as one of the competent health care providers who offer comprehensive care to patients during rehabilitation after hospitalization. In recent years, telerehabilitation has opened a new pathway for nurses to manage chronic diseases at a distance; however, it remains unclear which chronic disease patients benefit the most from this innovative delivery mode.
Objective:
This study aims to summarize current components of community-based, nurse-led telerehabilitation programs using the chronic care model; evaluate the effectiveness of nurse-led telerehabilitation programs compared with traditional face-to-face rehabilitation programs; and compare the effects of telerehabilitation on patients with different chronic diseases.
Methods:
A systematic review and meta-analysis were performed using 6 databases for articles published from 2015 to 2021. Studies comparing the effectiveness of telehealth rehabilitation with face-to-face rehabilitation for people with hypertension, cardiac diseases, chronic respiratory diseases, diabetes, cancer, or stroke were included. Quality of life was the primary outcome. Secondary outcomes included physical indicators, self-care, psychological impacts, and health-resource use. The revised Cochrane risk of bias tool for randomized trials was employed to assess the methodological quality of the included studies. A meta-analysis was conducted using a random-effects model and illustrated with forest plots.
Results:
A total of 26 studies were included in the meta-analysis. Telephone follow-ups were the most commonly used telerehabilitation delivery approach. Chronic care model components, such as nurses-patient communication, self-management support, and regular follow-up, were involved in all telerehabilitation programs. Compared with traditional face-to-face rehabilitation groups, statistically significant improvements in quality of life (cardiac diseases: standard mean difference [SMD] 0.45; 95% CI 0.09 to 0.81; P=.01; heterogeneity: X21=1.9; I2=48%; P=.16; chronic respiratory diseases: SMD 0.18; 95% CI 0.05 to 0.31; P=.007; heterogeneity: X22=1.7; I2=0%; P=.43) and self-care (cardiac diseases: MD 5.49; 95% CI 2.95 to 8.03; P<.001; heterogeneity: X25=6.5; I2=23%; P=.26; diabetes: SMD 1.20; 95% CI 0.55 to 1.84; P<.001; heterogeneity: X24=46.3; I2=91%; P<.001) were observed in the groups that used telerehabilitation. For patients with any of the 6 targeted chronic diseases, those with hypertension and diabetes experienced significant improvements in their blood pressure (systolic blood pressure: MD 10.48; 95% CI 2.68 to 18.28; P=.008; heterogeneity: X21=2.2; I2=54%; P=0.14; diastolic blood pressure: MD 1.52; 95% CI -10.08 to 13.11, P=.80; heterogeneity: X21=11.5; I2=91%; P<.001), and hemoglobin A1c (MD 0.19; 95% CI -0.19 to 0.57 P=.32; heterogeneity: X24=12.4; I2=68%; P=.01) levels. Despite these positive findings, telerehabilitation was found to have no statistically significant effect on improving patients' anxiety level, depression level, or hospital admission rate.
Conclusions:
This review showed that telerehabilitation programs could be beneficial to patients with chronic disease in the community. However, better designed nurse-led telerehabilitation programs are needed, such as those involving the transfer of nurse-patient clinical data. The heterogeneity between studies was moderate to high. Future research could integrate the chronic care model with telerehabilitation to maximize its benefits for community-dwelling patients with chronic diseases.
Trial registration:
International Prospective Register of Systematic Reviews CRD42022324676; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=324676.
... [42,43,44,45] Compared to educational technology and text messages, face-to-face training was more effective at educating patients. Even though Sherifali et al. [46] applied telephone instructing, they directed week after week and month-to-month calls, which might have supported a valuable underpinning of inspiration and adherence. Besides, a week-by-week contact hour was more compelling in further developing QoL, further fortifying the use of persistent checking and management during mediations. ...
... However, a few studies reported that income and education levels were factors in the dropout rate. [46] To cut down on the number of students who drop out of the study during the course of the study, future studies should use well-matched pairings of sociodemographic data between the intervention and control groups, particularly in terms of education, motivation, finances, and residence (rural or urban). This survey has two constraints. ...
... The results of the current study have exhibited an insignificant association between gender, age, time elapsed since diagnosis of DM, values of the HbA1c, and the participants' level of knowledge regarding T2DM. While some studies have found patients' age and duration of disease and HbA1c values to not be significantly associated with the patients' level of knowledge [32,34,39], other evidence has affirmed a significant association between patients' age and time elapsed from diagnosis and HbA1c value [31,33,35,40], as well as the level of patients' knowledge about T2DM [41,42]. Similarly, the results of this study have shown the educational background to have a meaningful effect on the level of knowledge regarding T2DM. ...
... These findings are similar to those found in other countries [23,32,45]. The variation in the literature regarding the assessment of the QoL among T2DM patients has also been highlighted [42,46,47]. For instance, this study was found congruent to other studies that support no significant difference between males and females with T2DM in terms of DQOL [23,48,49]. ...
Background
The assessment of the quality of life (QoL) among type 2 diabetic patients is associated with different factors. Evidence shows that these patients usually suffer from a lack of knowledge about the disease, inadequate self-care, and low QoL.
Objective
The study aimed to assess knowledge of the QoL of type 2 diabetes patients and its possible associated factors.
Methods
This cross-sectional descriptive correlational study recruited type 2 diabetic patients conveniently from out-clinics to achieve the objective of the study. The Diabetes Quality of Life Brief Clinical Inventory (DQOL) and the Diabetes Knowledge Questionnaire 18 (DKQ-18) along with a demographic questionnaire were used for patient assessment.
Results
A total of 184 patients participated in the study. Patients' knowledge of diabetes was found to be low (8.57 out of 18), with no statistical differences between male and female participants (p=0.259). The average DQOL score was 2.87 out of 5, indicating moderate satisfaction and self-care behavior. DKQ-18 and DOQL were found to be correlated (r= 0.216, p=0.003). However, the patient’s age was found to be a significant factor that influences patients’ QoL (F=4.27, p=0.040), whereas patients’ knowledge contributed weakly to the variation of QoL (F=1.70, p=0.084).
Conclusion
Irrespective of knowledge and educational background, the patient’s age is influential in enhancing better QoL among type 2 diabetic patients.
... Telemedicine with phone coaching is a way to motivate and deliver lifestyle interventions to increase positive health behaviors, facilitate preventative actions, and improve the quality of care in patients with diabetes. Throughout the literature there were strong supporting evidencebased studies, with statistically significant findings, demonstrating the effectiveness of telemedicine with phone coaching as an intervention for improving HbA1c levels and diabetes self-care practices (Sherifali et al., 2020;Su et al., 2016;Wayne et al., 2015;Wolever et al., 2010;& Zhai et al., 2014). ...
... A total of 20 studies evaluated quality of life outcomes, where majority of the studies (12/20, 60%) found no improvement in quality of life outcomes [28,30,46,48,60,72,78,97,108,109,117,119], 7 (35%) studies found significant improvements in patient quality of life [32,39,75,98,106,110,114,115], and 1 (5%) showed mixed evidence regarding the impact of health coaching with remote monitoring on patient quality of life [83]. ...
Background: Health coaching refers to the practice of health education and promotion to drive goal-directed behavioral changes and improve an individual's well-being. Remote patient monitoring systems, which employ health coaching interventions, have been gaining interest and may aid in the management of patients with type 2 diabetes mellitus (T2DM).
Objective: This scoping review aims to summarize the impact of health coaching in the remote monitoring of patients with T2DM.
Methods: A scoping review was performed in MEDLINE, Embase, CINAHL, PsychInfo, and Web of Science up to September 2024 and was reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. The initial abstract screening, full-text review, and data extraction were performed by 2 independent reviewers. Studies that evaluated the impact of health coaching on the remote management of patients with T2DM were included. Outcomes evaluated were grouped into clinical, humanistic, psychiatric, behavioral, knowledge, and economic domains. A narrative review was performed for the impact of health coaching on the remote management of patients with T2DM.
Results: Among 168,888 citations identified, 104 studies were included. Majority of the studies were conducted in North America (56/104, 53.8%) and Asia (30/104, 28.8%). Approximately half of the studies (48/104, 46.2%) were conducted in primary health care settings, and one-third of the studies (37/104, 35.6%) employed nurses as health coaches. Phone consultations were the most common modality of remote monitoring (45/104, 43.3%). The follow-up duration of most studies (64/104, 61.5%) was less than 1 year. Regarding clinical outcomes, majority of the studies (68/92, 73%) showed improvements in diabetes-related parameters, but there was no improvement in blood pressure (21/32, 66%) or hyperlipidemia control (19/32, 59%). For humanistic outcomes, health coaching was associated with higher satisfaction with diabetes-related care (10/11, 91%), but there was no improvement in quality of life (12/20, 60%). Regarding psychiatric outcomes, there was no association with improvement in depressive (8/14, 57%) or anxiety symptoms (4/5, 80%). For behavioral outcomes, most studies (12/19, 63%) showed improvement in diabetes-related self-efficacy. For knowledge outcomes, evidence was mixed, with half of the studies (5/9, 56%) showing improvement in diabetes-related knowledge. For economic outcomes, majority of the studies (8/11, 73%) did not show a reduction in health care use.
Conclusions: Health coaching was associated with improved diabetes control and self-management among patients with T2DM on remote monitoring. Its role appears limited in improving health care use, lipid parameters, and quality of life; however, this may have been confounded by the short duration of follow-up in the studies. More studies are required to identify the optimal modality and duration of digital health coaching for patients with T2DM.
... В настоящее время имеются убедительные доказательства преимуществ виртуальных, телемедицинских, телефонных или интернет-программ профилактики и лечения СД в самых разных группах населения перед «традиционными» способами ведения пациентов с этим заболеванием [10][11][12][13][14]. Для реализации DSMES также возможно использование таких технологий, как мобильные приложения, инструменты моделирования, цифровой коучинг и цифровое самоуправление [15][16][17][18][19][20]. ...
Achieving compensation of carbohydrate metabolism indicators is a priority in the treatment of patients with diabetes mellitus. However, repeated measurements of glucose levels, especially in patients with type 1 diabetes mellitus (T1D), lead to rapid burnout and increased anxiety of the patient. Digital assistants help to increase the patient's commitment to treatment, compliance with the schedule of daily measurements of blood glucose, timely correction of therapy and optimization of various types of medical care (traditional visits, telemedicine consultations, online consultations). Based on clinical research data, it is currently known that the use of digital assistants contributes to achieving a stable clinical result of treatment, reducing the number of hospitalizations for diabetes decompensation, and reducing patient anxiety about their disease. This article presents a clinical case of managing a patient with T1D who used a glucometer with the ability to maintain an electronic self-monitoring diary, followed by telemedicine consultation with an endocrinologist based on data from structured reports generated in the glucometer application. The results obtained demonstrate the advantages of using individual digital assistants in the daily life of patients with diabetes
... Systematic review and meta-analysis studies also demonstrate diabetes health coaching is an effective strategy to improve HbA1c [16,17,22,23]. In addition, evidence suggests diabetes health coaching can lead to improvements in self-efficacy [24], self-care practice [19,20], and quality of life [22,25]. Despite the above evidence, culturally appropriate and effective DSM programs are lacking in most LMICs (Iregbu & Iregbu,[26], including Ethiopia. ...
Background
Diabetes mellitus is the third most prevalent chronic metabolic disorder and a significant contributor to disability and impaired quality of life globally. Diabetes self-management coaching is an emerging empowerment strategy for individuals with type 2 diabetes, enabling them to achieve their health and wellness goals. The current study aims to determine the feasibility of a diabetes self-management coaching program and its preliminary effectiveness on the clinical and psychosocial outcomes in the Ethiopian primary healthcare context.
Methods
The study will employ a mixed-method feasibility randomized controlled trial design. Forty individuals with type 2 diabetes will be randomly allocated to treatment and control groups using block randomization. The primary feasibility outcomes include acceptability, eligibility, recruitment, and participant retention rates, which will be computed using descriptive analysis. The secondary outcomes are self-efficacy, self-care activity, quality of life, and glycated hemoglobin A1c. For normally distributed continuous variables, the mean difference within and between the groups will be determined by paired sample Student t-test and independent sample Student t-test, respectively. Non-parametric tests such as the Mann-Whitney U test, the Wilcoxon signed rank test, and the Friedman analysis of variance test will determine the median difference for variables that violated the normality assumption. A repeated measure analysis of variance will be considered to estimate the variance between the baseline, post-intervention, and post-follow-up measurements. A sample of 10 volunteers in the treatment group will participate in the qualitative interview to explore their experience with the diabetes self-management coaching program and overall feasibility. The study will follow a qualitative content analysis approach to analyze the qualitative data. Qualitative and quantitative findings will be integrated using a joint display technique.
Discussion
Evidence reveals diabetes self-management coaching programs effectively improve HbA1c, self-efficacy, self-care activity, and quality of life. This study will determine the feasibility of a future large-scale randomized controlled trial on diabetes self-management coaching. The study will also provide evidence on the preliminary outcomes and contribute to improving the diabetes self-management experience and quality of life of individuals with type 2 diabetes.
Trial registration
The trial was registered online at ClinicalTrials.gov on 12/04/2022 and received a unique registration number, NCT05336019, and the URL of the registry is https://beta.clinicaltrials.gov/study/NCT05336019.
... Health coaching was used as a core component due to its strong evidence of effectiveness compared to standard counselling on promoting treatment adherence and health behaviour change, while reducing healthcare utilization and cost [22,23,26]. Health coaching is defined as the practice of health education and promotion of behaviour change to enhance a person's well-being and facilitate the achievement of individual health-related goals [27]. ...
Introduction: Type-2 diabetes (T2D) is a complex chronic condition associated with a lower quality of life due to disease specific distress. While there is growing support for personalized diabetes programs, care for mental health challenges is often fragmented and limited by access to psychiatry, and integration of care. The use of communication technology to improve team based collaborative care to bridge these gaps is promising but untested. Methods: We conducted an explanatory sequential mixed methods study to assess the feasibility and acceptability of the co-designed Technology-Enabled Collaborative Care for Diabetes and Mental Health (TECC-D) program. Participants included adults aged ≥18 years who had a clinical diagnosis of T2D, and self-reported mental health concerns. Results: 31 participants completed the 8-week virtual TECC-D program. Findings indicate that the program is feasible and acceptable and indicate that there is a role for virtual diabetes and mental health care. Discussion: The TECC-D program, designed through an iterative co-design process and supported by innovative, responsive adaptations led to good uptake and satisfaction. Conclusion: The TECC-D model is a feasible and scalable care solution that empowers individuals living with T2D and mental health concerns to take an active role in their care.
... Additionally, this includes how many participants chose to fill out stage 2 ("optional") surveys, to further inform co-design with our participants for future studies. Lastly, the delivery of the intervention will be assessed, including the planned intervention sessions, the duration that the CDE was in each session, the mode of interaction (ie, whether the participant completed their visits via telephone, web-conferencing, or a combination of both), and strategies used by the CDE during health coaching sessions (eg, frequencies and examples of strategies and recommendations posed during visits), using a reporting template used in previous coaching trials [33,34]. ...
Background:
The COVID-19 pandemic disrupted the delivery of diabetes care and worsened mental health among many patients with type 2 diabetes (T2D). This disruption puts patients with T2D at risk for poor diabetes outcomes, especially those who experience social disadvantage due to socioeconomic class, rurality, or ethnicity. The appropriate use of communication technology could reduce these gaps in diabetes care created by the pandemic and also provide support for psychological distress.
Objective:
The purpose of this study is to test the feasibility of an innovative co-designed Technology-Enabled Collaborative Care (TECC) model for diabetes management and mental health support among adults with T2D.
Methods:
We will recruit 30 adults with T2D residing in Ontario, Canada, to participate in our sequential explanatory mixed methods study. They will participate in 8 weekly web-based health coaching sessions with a registered nurse, who is a certified diabetes educator, who will be supported by a digital care team (ie, a peer mentor, an addictions specialist, a dietitian, a psychiatrist, and a psychotherapist). Assessments will be completed at baseline, 4 weeks, and 8 weeks, with a 12-week follow-up. Our primary outcome is the feasibility and acceptability of the intervention, as evident by the participant recruitment and retention rates. Key secondary outcomes include assessment completion and delivery of the intervention. Exploratory outcomes consist of changes in mental health, substance use, and physical health behaviors. Stakeholder experience and satisfaction will be explored through a qualitative descriptive study using one-on-one interviews.
Results:
This paper describes the protocol of the study. The recruitment commenced in June 2021. This study was registered on October 29, 2020, on ClinicalTrials.gov (Registry ID: NCT04607915). As of June 2022, all participants have been recruited. It is anticipated that data analysis will be complete by the end of 2022, with study findings available by the end of 2023.
Conclusions:
The development of an innovative, technology-enabled model will provide necessary support for individuals living with T2D and mental health challenges. This TECC program will determine the feasibility of TECC for patients with T2D and mental health issues.
Trial registration:
ClinicalTrials.gov NCT04607915; https://clinicaltrials.gov/ct2/show/NCT04607915.
International registered report identifier (irrid):
DERR1-10.2196/39724.
... Diabetes health coaching has both educational and behavioral components, which include goal-setting, self-care knowledge, and frequent follow-up appointments [6]. Coaching has been shown to improve health outcomes [7][8][9] and treatment adherence [10,11]. However, the widespread adoption of diabetes health coaching may be limited by constraints on health human resources. ...
Background
Health coaching is an emerging intervention that has been shown to improve clinical and patient-relevant outcomes for type 2 diabetes. Advances in artificial intelligence may provide an avenue for developing a more personalized, adaptive, and cost-effective approach to diabetes health coaching.
Objective
We aim to apply Q-learning, a widely used reinforcement learning algorithm, to a diabetes health-coaching data set to develop a model for recommending an optimal coaching intervention at each decision point that is tailored to a patient’s accumulated history.
Methods
In this pilot study, we fit a two-stage reinforcement learning model on 177 patients from the intervention arm of a community-based randomized controlled trial conducted in Canada. The policy produced by the reinforcement learning model can recommend a coaching intervention at each decision point that is tailored to a patient’s accumulated history and is expected to maximize the composite clinical outcome of hemoglobin A1c reduction and quality of life improvement (normalized to [ 0, 1 ], with a higher score being better). Our data, models, and source code are publicly available.
ResultsAmong the 177 patients, the coaching intervention recommended by our policy mirrored the observed diabetes health coach’s interventions in 17.5% (n=31) of the patients in stage 1 and 14.1% (n=25) of the patients in stage 2. Where there was agreement in both stages, the average cumulative composite outcome (0.839, 95% CI 0.460-1.220) was better than those for whom the optimal policy agreed with the diabetes health coach in only one stage (0.791, 95% CI 0.747-0.836) or differed in both stages (0.755, 95% CI 0.728-0.781). Additionally, the average cumulative composite outcome predicted for the policy’s recommendations was significantly better than that of the observed diabetes health coach’s recommendations (tn-1=10.040; P
Introduction
Diabetes mellitus is a long-term medical condition with a high morbidity rate and numerous complications. Diabetes can impair a person’s quality of life (QoL) by having an adverse effect on their physical, psychological, social, and environmental health. This study attempts to evaluate the effectiveness of a web-based model in improving the health-related QoL among patients with type 2 diabetes mellitus (T2DM) in Southern Karnataka.
Methodology
A longitudinal study was conducted among 545 T2DM patients attending the outpatient department of a tertiary care hospital in Mysore in southern India. Diabetes Care (https://www.diabetes-care.co.in/), an online website that can predict the risk for uncontrolled diabetes and recommends lifestyle changes, was used by the patients. The WHOQOL-BREF questionnaire was used to assess the QoL at the start of the study and 3 months later.
Results
Comparing the QoL of the study participants before and after the intervention period, all four domains of QoL, i.e., the physical domain (53.10 ± 23.140–57.36 ± 17.276), the psychological domain (53.37 ± 23.200–61.32 ± 14.154), the social relationship domain (52.77 ± 25.116–58.22 ± 18.695), and the environmental domain (54.97 ± 24.665–60.12 ± 19.725) scores, improved, and this was found to be statistically significant.
Conclusion
The web-based model significantly improved the QoL in all four domains of health. Thus, more technological approaches should be implemented along with other public health measures to improve the health outcomes of patients with T2DM.
The American Diabetes Association (ADA) “Standards of Care in Diabetes” includes the ADA’s current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
In 2020, a consortium composed of three national coach credentialing organizations, four medical societies, and 72 healthcare organizations led by National Board for Health and Wellness Coaching (NBHWC) was formed to advocate for the reimbursement of Health and Wellness Coaching (HWC) services in the U.S. healthcare system. Building on that, the NBHWC and the Veterans Health Administration (VHA) initiated a pivotal collaboration in 2023, with a target audience comprised influential reimbursement policymakers, notably the American Medical Association’s Current Procedural Terminology (CPT®) Panel and the Centers for Medicare & Medicaid Services (CMS). This concerted effort led to CMS announcing the temporary inclusion of HWC services on the 2024 Medicare Telehealth list. This ongoing advocacy work is crucial while understanding its key components is imperative for wider participation. This paper aims to distill the essence of the advocacy to date into a coherent narrative. By doing so, we seek to share with stakeholders—health and wellness coaches, medical professionals, healthcare organizations, patient advocates, and policy experts—a robust framework to support advocacy for reimbursement to both government and private insurers, at local and national levels. This initiative marks a significant milestone in healthcare policy, reflecting a growing recognition and impact of HWC.
Type 2 diabetes (T2D) is a complex chronic condition that requires ongoing self‐management. Diabetes health coaching interventions provide personalized healthcare programming to address physical and psychosocial aspects of diabetes self‐management.
Aims
This scoping review aims to explore the contexts and settings of diabetes health coaching interventions for adults with T2D, using the RE‐AIM framework.
Methods
A search was completed in MEDLINE, PsycINFO, Emcare, Embase and Cochrane. Included citations described adults with exclusively T2D who had received a health coaching intervention. Citations were excluded if they focused on any other types of diabetes or diabetes prevention.
Results
A total of 3418 records were identified through database and manual searches, with 29 citations selected for data extraction. Most health coaching interventions were delivered by health professionals, many employed lay health workers and a few included peer coaches. While many health coaching interventions were delivered remotely, in‐person intervention settings were distributed among primary care, community health settings and non‐healthcare sites.
Conclusion
The findings of this review suggest that diabetes health coaching may be implemented by a variety of providers in different settings. Further research is required to standardize training and implementation of health coaching and evaluate its long‐term effectiveness.
The American Diabetes Association (ADA) “Standards of Care in Diabetes” includes the ADA’s current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
Background
Diabetes health coaching continues to emerge as an effective intervention to support diabetes self-management. While previous systematic reviews have focused on the effectiveness of diabetes health coaching programs in adults with type 2 diabetes (T2DM), limited literature is available on its implementation. This review examines what aspects of diabetes health coaching interventions for adults living with type 2 diabetes have been reported using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to optimize implementation.
Methods
We examined the included studies from our recently completed systematic review, which searched 6 databases for randomized controlled trials (RCTs) of health coaching interventions delivered by a health professional for adults with T2DM. Reviewers screened citations and extracted data for study characteristics and the 5 dimensions (62 criteria) of the RE-AIM framework.
Results
9 diabetes health coaching RCTs were included in this review. 12 criteria were reported by all the included studies and 21 criteria were not reported by any of the studies. The included studies all reported on more than 20 RE-AIM criteria, ranging from 21 to 27. While Reach was the best reported construct by the included studies, followed by Effectiveness and Implementation, the criteria within the Adoption and Maintenance constructs were rarely mentioned by these studies. In general, there was also wide variation in how each of the criteria were reported on by study authors
Conclusions
Due to the paucity of reporting of the RE-AIM components for diabetes health coaching, limited implementation and clinical practice implications can be drawn. The lack of detail regarding implementation approaches to diabetes health coaching greatly limits the interpretation and comparisons across studies to best inform the application of this intervention to support diabetes self-management.
Systematic review registration
PROSPERO identifier, CRD42022347478
The American Diabetes Association (ADA) “Standards of Care in Diabetes” includes the ADA’s current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
Introduction: Patient education is an integral component of diabetes mellitus care. The emergence of different methods and characteristics of patient education has led to varying outcomes of quality of life (QoL). Herein, we systematically searched for published studies reporting patient education and its methods and characteristics for improving the QoL of patients with type 2 diabetes mellitus (T2DM).
Methods: In this scoping review, eligible studies from six databases (PubMed, Scopus, Cochrane Library, Springer Link, Science Direct and Google Scholar) were identified. The keywords used in the search strategies were as follows: health education, health promotion, patient education, diabetes care, QoL, diabetes mellitus and type 2 diabetes mellitus. Two reviewers independently screened all references and full-text articles retrieved to identify articles eligible for inclusion.
Results: A total of 203 articles were identified in the initial search. Of them, 166 were excluded after screening the titles and abstracts. Further full-text screening led to the subsequent removal of 22 articles, leaving 15 articles eligible for data extraction.
Conclusion: There is a broad array of methods of patient education for improving the QoL of patients with T2DM. Self-management education with supplementary supervision and monitoring effectively improves QoL. Future studies must emphasise the application of holistic education covering psychological distress, diet plan, and physical health.
Background: Given the high rates globally of Type 2 Diabetes Mellitus (T2DM), there is a clear need to target health behaviours through person-centred interventions. Health coaching is one strategy that has been widely recognised as a tool to foster positive behaviour change. However, it has been used inconsistently and has produced mixed results. This systematic review sought to explore the use of behaviour change techniques (BCTs) in health coaching interventions and identify which BCTs are linked with increased effectiveness in relation to HbA1C reductions.
Methods: Studies were systematically identified through database searches for relevant randomised controlled trials (RCTs) in papers published between January 1950 and April 2020. Included papers were screened on the reported use of BCTs based on the BCT taxonomy. The effectiveness of included interventions was assessed by using Cohen’s d.
Results: Twenty-one RCTs were identified. Thirteen interventions were shown to have medium to large effects on HbA1c reduction (d=0.50 to d=1.30). Twenty-three BCTs were identified, with a mean of 5.3 (SD = 3.6) BCTs used in each study. Of these, Goal setting (behaviour) and Problem solving were the most frequently identified BCTs. The intervention with the largest effect size (d=1.30) used five different BCTs: Goal setting (behaviour), Problem Solving, Goal setting (outcome), Self-monitoring of outcome of behaviour, and framing/reframing. However, there was little evidence to link the use of specific BCTs to reductions in HbA1c across the studies included in the review
Conclusion: A relatively small number of BCTs have been used in RCTs of health coaching interventions for T2DM. Moreover, other possible BCTs directly related to the theoretical underpinnings of health coaching were absent. It is recommended that key BCTs are identified at an early stage of intervention development, although further research is needed to examine the most effective BCTs to use in health coaching interventions.
Aims
In-depth and updated systematic reviews evaluating telephone calls in type 2 diabetes (T2DM) management are missing. This study aimed to assess the effect of this intervention on glycemic control in T2DM patients when compared with usual care.
Methods
We systematically searched for randomized controlled trials (RCT) on T2DM using Medline, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and LILACS, up to March 2021. The Risk of Bias 2.0 (Rob 2.0) tool and GRADE were used for the quality evaluation. The intervention effect was estimated by the change in glycated hemoglobin (HbA1c). PROSPERO registry CRD42020204519.
Results
3545 references were reviewed and 32 were included (8598 patients). Telephone calls, all approaching education, improved HbA1c by 0.33% [95% CI, −0.48% to −0.18%; I ² = 78%; p < 0.0001] compared to usual care. A greater improvement was found when the intervention included pharmacologic modification (−0.82%, 95% CI, −1.42% to −0.22%; I ² = 92%) and when it was applied by nurses (−0.53%, 95% CI, −0.86% to −0.2%; I ² = 87%). Meta-regression showed no relationship between DM duration and HbA1c changes.
Conclusion
The telephone call intervention provided a benefit regarding T2DM glycemic control, especially if provided by nurses, or if associated with patient education and pharmacological treatment modification.
Background
A recent randomized controlled trial demonstrated that a community-based, telephone-delivered diabetes health coaching intervention was an effective intervention for improving diabetes management. The purpose of the current study was to determine whether this effective intervention is also cost-effective.
Methods
An economic evaluation, in the form of a cost-utility analysis (CUA), was used to assess the cost-effectiveness of the coaching intervention from a public payer perspective. All direct medical costs, as well as intervention implementation, were included. The outcome of the CUA was the quality adjusted life year (QALY). Uncertainty of cost-effectiveness results were estimated using non-parametric bootstraps of patient-level costs and QALYs in the coaching and control arms. A cost-effectiveness acceptability curve was used to express this uncertainty as the probability that diabetes health coaching is cost-effective across a range of values of willingness to pay (WTP) thresholds for a QALY.
Findings
The results show that subjects in the coaching arm incurred higher overall costs (Canadian dollars) compared to the control arm (1,086, respectively) and incurred 0.02 more QALYs. The incremental cost-effectiveness ratio of the diabetes health coaching intervention compared to usual care was found to be 50,000 per QALY and $100,000 per QALY, respectively.
Interpretation
A community-based, telephone-delivered diabetes health coaching intervention is cost-effective.
Funding
We acknowledge the Canadian Institutes for Health Research for funding the trial.
Objective:
To extend our understanding of self-management by using original data and a recent concept analysis to propose a unifying framework for self-management strategies.
Methods:
Longitudinal interview data with 117 people with neurological conditions were used to test a preliminary framework derived from the literature. Statements from the interviews were sorted according to the predefined categories of the preliminary framework to investigate the fit between the framework and the qualitative data. Data on frequencies of strategies complemented the qualitative analysis.
Results:
The Taxonomy of Every Day Self-management Strategies (TEDSS) Framework includes five Goal-oriented Domains (Internal, Social Interaction, Activities, Health Behaviour and Disease Controlling), and two additional Support-oriented Domains (Process and Resource). The Support-oriented Domain strategies (such as information seeking and health navigation) are not, in and of themselves, goal focused. Instead, they underlie and support the Goal-oriented Domain strategies. Together, the seven domains create a comprehensive and unified framework for understanding how people with neurological conditions self-manage all aspects of everyday life.
Conclusions:
The resulting TEDSS Framework provides a taxonomy that has potential to resolve conceptual confusion within the field of self-management science.
Practice implications:
The TEDSS Framework may help to guide health service delivery and research.
Objective
Personal health coaching (PHC) programs have become increasingly utilized as a type 2 diabetes mellitus (T2DM) self-management intervention strategy. This article evaluates the impact of PHC programs on glycemic management and related psychological outcomes.
Data Sources
Electronic databases (CINAHL, MEDLINE, PubMed, PsycINFO, and Web of Science).
Study Inclusion and Exclusion Criteria
Randomized controlled trials (RCT) published between January 1990 and September 2017 and focused on the effectiveness of PHC interventions in adults with T2DM.
Data Extraction
Using prespecified format guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework.
Data Synthesis
Quantitative synthesis for primary (ie, hemoglobin A1c [HbA1c]) and qualitative synthesis for selected psychological outcomes.
Results
Meta-analyses of 22 selected publications showed PHC interventions favorably impact HbA1c levels in studies with follow-ups at ≤3 months (−0.32% [95% confidence interval, CI = −0.55 to −0.09%]), 4 to 6 months (−0.50% [95% CI = −0.65 to −0.35%], 7 to 9 months (−0.66% [95% CI = −1.04 to −0.28%]), and 12 to 18 months (−0.24% [95% CI = −0.38 to −0.10%]). Subsequent subgroup analyses led to no conclusive patterns, except for greater magnitude of effect size in studies with conventional (2-arm) RCT design.
Conclusions
The PHC appears effective in improving glycemic control. Further research is required to assess the effectiveness of specific program components, training, and supervision approaches and to determine the cost-effectiveness of PHC interventions.
Background
The burden of chronic disease and multimorbidity is rapidly increasing. Self-management support interventions are effective in reduce cost, especially when targeted at a single disease group; however, economical evidence of such complex interventions remains scarce. The objective of this study was to evaluate a cost-effectiveness analysis of a tele-based health-coaching intervention among patients with type 2 diabetes (T2D), coronary artery disease (CAD) and congestive heart failure (CHF). MethodsA total of 1570 patients were blindly randomized to intervention (n = 970) and control (n = 470) groups. The intervention group received monthly individual health coaching by telephone from a specially trained nurse for 12-months in addition to routine social and healthcare. Patients in the control group received routine social and health care. Quality of life was assessed at the beginning of the intervention and follow-up measurements were made after 12 months health coaching. The cost included all direct health-care costs supplemented with home care and nursing home-care costs in social care. Utility was based on a Health Related Quality of Life (HRQoL) measurement (15D instrument), and cost effectiveness was assessed using incremental cost-effectiveness ratios (ICERs). ResultsThe cost-effectiveness of health coaching was highest in the T2D group (ICER €20,000 per Quality-Adjusted Life Years [QALY]). The ICER for the CAD group was more modest (€40,278 per QALY), and in the CHF group, costs increased with no marked effect on QoL. Probabilistic sensitivity analysis indicated that at the societal willingness to pay threshold of €50,000 per QALY, the probability of health coaching being cost effective was 55% in the whole study group. Conclusions
The cost effectiveness of health coaching may vary substantially across patient groups, and thus interventions should be targeted at selected subgroups of chronically ill. Based on the results of this study, health coaching improved the QoL of T2D and CAD patients with moderate costs. However, the results are grounded on a short follow-up period, and more evidence is needed to evaluate the long-term outcomes of health-coaching programs. Trial registrationNCT00552903 [Prospectively registered, registration date 1st November 2007, last updated 3rd February 2009].
Diabetes coaching is emerging as an important role in self-management and care. The conceptualization of coaching, and how to implement and evaluate coaching has not been articulated in the literature. The aim of the study was to review the literature to: (i) identify the components of coaching using a validated framework, including the description of the role of technology; (ii) describe the implementation and evaluation measures for diabetes coaching; and (iii) propose a diabetes coaching model for future implementation. The EMBASE, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO and Cochrane Central Register of Controlled Trials databases were searched from inception to January 2015. Two evaluators independently screened and extracted data from eligible studies for descriptions of coaching. Eight trials met the selection criteria, with no consistency in the core components of coaching. However, elements noted across all studies included goal setting, diabetes knowledge acquisition, individualized care, and frequent follow-up. Only two studies leveraged technology for coaching communication purposes. Diabetes coaching is an intervention that can support the ongoing and complex needs of patients; however, implementation and evaluation strategies are limited in the literature. A diabetes coaching model is presented, derived from components identified throughout the literature with direction for implementation and evaluation approaches, and optimal integration into the healthcare system.
Objectives:
Diabetes health coaching has not been adequately assessed in individuals with type 2 diabetes. The objective of this review was to synthesize the evidence of health coaching for individuals with diabetes to determine the effects of coaching on diabetes control, specifically on glycated hemoglobin (A1C) levels.
Methods:
The EMBASE, MEDLINE, CINAHL, PsychINFO and Cochrane Central Register of Controlled Trials databases were searched from inception to January 2015. Reference lists from important publications were also reviewed. At least 2 evaluators independently screened and extracted data from eligible studies.
Results:
A total of 8 trials met the selection criteria, which included 724 adult participants; 353 participants were randomized to a diabetes health coaching intervention, and 371 were randomized to usual care. The pooled effect of diabetes health coaching overall was a statistically significant reduction of A1C levels by 0.32 (95% CI, -0.50 to -0.15). Longer diabetes health coaching exposure (>6 months) resulted in a 0.57% reduction in A1C levels (95% CI, -0.76 to -0.38), compared to shorter diabetes health coaching exposure (≤6 months) (-0.23%; 95% CI, -0.37 to -0.09). Across all studies, diabetes health coaching consisted of goal setting, knowledge acquisition, individualized care and frequent follow up.
Conclusions:
Diabetes health coaching has an emerging role in healthcare that facilitates self-care, behaviour change and offers frequent follow up and support. This review finds that health coaching for those with diabetes is an effective intervention for improving glycemic control, which may be of greater benefit when offered in addition to existing diabetes care.
Though several questionnaires on self-care and regimen adherence have been introduced, the evaluations do not always report consistent and substantial correlations with measures of glycaemic control. Small ability to explain variance in HbA1c constitutes a significant limitation of an instrument's use for scientific purposes as well as clinical practice. In order to assess self-care activities which can predict glycaemic control, the Diabetes Self-Management Questionnaire (DSMQ) was designed.
A 16 item questionnaire to assess self-care activities associated with glycaemic control was developed, based on theoretical considerations and a process of empirical improvements. Four subscales, 'Glucose Management' (GM), 'Dietary Control' (DC), 'Physical Activity' (PA), and 'Health-Care Use' (HU), as well as a 'Sum Scale' (SS) as a global measure of self-care were derived. To evaluate its psychometric quality, 261 patients with type 1 or 2 diabetes were assessed with the DSMQ and an established analogous scale, the Summary of Diabetes Self-Care Activities Measure (SDSCA). The DSMQ's item and scale characteristics as well as factorial and convergent validity were analysed, and its convergence with HbA1c was compared to the SDSCA.
The items showed appropriate characteristics (mean item-total-correlation: 0.46 +/- 0.12; mean correlation with HbA1c: -0.23 +/- 0.09). Overall internal consistency (Cronbach's alpha) was good (0.84), consistencies of the subscales were acceptable (GM: 0.77; DC: 0.77; PA: 0.76; HU: 0.60). Principal component analysis indicated a four factor structure and confirmed the designed scale structure. Confirmatory factor analysis indicated appropriate fit of the four factor model. The DSMQ scales showed significant convergent correlations with their parallel SDSCA scales (GM: 0.57; DC: 0.52; PA: 0.58; HU: n/a; SS: 0.57) and HbA1c (GM: -0.39; DC: -0.30; PA: -0.15; HU: -0.22; SS: -0.40). All correlations with HbA1c were significantly stronger than those obtained with the SDSCA.
This study provides preliminary evidence that the DSMQ is a reliable and valid instrument and enables an efficient assessment of self-care behaviours associated with glycaemic control. The questionnaire should be valuable for scientific analyses as well as clinical use in both type 1 and type 2 diabetes patients.
Coaching has become acceptable to both business and individuals to help improve performance, manage stress and achieve work and personal goals. Yet very few papers have been published with a specific focus on health and coaching. This paper highlights the
possible role of coaching to facilitate the promotion of healthy behaviours and to help individuals achieve their health-related goals.
Citation: Palmer, S., Tubbs, I. and Whybrow, W. (2003). Health coaching to facilitate the promotion of healthy behaviour and achievement of health-related goals. International Journal of Health Promotion and Education, 41, 3, 91-93.
To identify and evaluate the effectiveness, clinical usefulness, sustainability, and usability of web-compatible diabetes-related tools.
Medline, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, world wide web.
Studies were included if they described an electronic audiovisual tool used as a means to educate patients, care givers, or clinicians about diabetes management and assessed a psychological, behavioral, or clinical outcome.
Study abstraction and evaluation for clinical usefulness, sustainability, and usability were performed by two independent reviewers.
Of 12,616 citations and 1541 full-text articles reviewed, 57 studies met inclusion criteria. Forty studies used experimental designs (25 randomized controlled trials, one controlled clinical trial, 14 before-after studies), and 17 used observational designs. Methodological quality and ratings for clinical usefulness and sustainability were variable, and there was a high prevalence of usability errors. Tools showed moderate but inconsistent effects on a variety of psychological and clinical outcomes including HbA1c and weight. Meta-regression of adequately reported studies (12 studies, 2731 participants) demonstrated that, although the interventions studied resulted in positive outcomes, this was not moderated by clinical usefulness nor usability.
This review is limited by the number of accessible tools, exclusion of tools for mobile devices, study quality, and the use of non-validated scales.
Few tools were identified that met our criteria for effectiveness, usefulness, sustainability, and usability. Priority areas include identifying strategies to minimize website attrition and enabling patients and clinicians to make informed decisions about website choice by encouraging reporting of website quality indicators.
The purpose of this study was to evaluate the effectiveness of integrative health (IH) coaching on psychosocial factors, behavior change, and glycemic control in patients with type 2 diabetes.
Fifty-six patients with type 2 diabetes were randomized to either 6 months of IH coaching or usual care (control group). Coaching was conducted by telephone for fourteen 30-minute sessions. Patients were guided in creating an individualized vision of health, and goals were self-chosen to align with personal values. The coaching agenda, discussion topics, and goals were those of the patient, not the provider. Preintervention and postintervention assessments measured medication adherence, exercise frequency, patient engagement, psychosocial variables, and A1C.
Perceived barriers to medication adherence decreased, while patient activation, perceived social support, and benefit finding all increased in the IH coaching group compared with those in the control group. Improvements in the coaching group alone were also observed for self-reported adherence, exercise frequency, stress, and perceived health status. Coaching participants with elevated baseline A1C (>/=7%) significantly reduced their A1C.
A coaching intervention focused on patients' values and sense of purpose may provide added benefit to traditional diabetes education programs. Fundamentals of IH coaching may be applied by diabetes educators to improve patient self-efficacy, accountability, and clinical outcomes.
Previous reviews of the effect of oral antidiabetic (OAD) agents on A1C levels summarized studies with varying designs and methodological approaches. Using predetermined methodological criteria, we evaluated the effect of OAD agents on A1C levels.
The Excerpta Medica (EMBASE), the Medical Literature Analysis and Retrieval System Online (MEDLINE), and the Cochrane Central Register of Controlled Trials databases were searched from 1980 through May 2008. Reference lists from systematic reviews, meta-analyses, and clinical practice guidelines were also reviewed. Two evaluators independently selected and reviewed eligible studies.
A total of 61 trials reporting 103 comparisons met the selection criteria, which included 26,367 study participants, 15,760 randomized to an intervention drug(s), and 10,607 randomized to placebo. Most OAD agents lowered A1C levels by 0.5-1.25%, whereas thiazolidinediones and sulfonylureas lowered A1C levels by approximately 1.0-1.25%. By meta-regression, a 1% higher baseline A1C level predicted a 0.5 (95% CI 0.1-0.9) greater reduction in A1C levels after 6 months of OAD agent therapy. No clear effect of diabetes duration on the change in A1C with therapy was noted.
The benefit of initiating an OAD agent is most apparent within the first 4 to 6 months, with A1C levels unlikely to fall more than 1.5% on average. Pretreated A1C levels have a modest effect on the fall of A1C levels in response to treatment.
We hypothesized that people with type 2 diabetes in an online diabetes self-management program, compared with usual-care control subjects, would 1) demonstrate reduced A1C at 6 and 18 months, 2) have fewer symptoms, 3) demonstrate increased exercise, and 4) have improved self-efficacy and patient activation. In addition, participants randomized to listserve reinforcement would have better 18-month outcomes than participants receiving no reinforcement.
A total of 761 participants were randomized to 1) the program, 2) the program with e-mail reinforcement, or 3) were usual-care control subjects (no treatment). This sample included 110 American Indians/Alaska Natives (AI/ANs). Analyses of covariance models were used at the 6- and 18-month follow-up to compare groups.
At 6 months, A1C, patient activation, and self-efficacy were improved for program participants compared with usual care control subjects (P < 0.05). There were no changes in other health or behavioral indicators. The AI/AN program participants demonstrated improvements in health distress and activity limitation compared with usual-care control subjects. The subgroup with initial A1C >7% demonstrated stronger improvement in A1C (P = 0.01). At 18 months, self-efficacy and patient activation were improved for program participants. A1C was not measured. Reinforcement showed no improvement.
An online diabetes self-management program is acceptable for people with type 2 diabetes. Although the results were mixed they suggest 1) that the program may have beneficial effects in reducing A1C, 2) AI/AN populations can be engaged in and benefit from online interventions, and 3) our follow-up reinforcement appeared to have no value.
This review examined the effectiveness of self-management interventions compared to usual care on mortality, all-cause hospital readmissions, chronic heart failure hospitalization rate and quality of life in patients with chronic heart failure.
A systematic review was performed. MEDLINE, EMBASE, CINAHL and the Cochrane Library were searched between 1996 and 2009. Randomized controlled trials were selected evaluating self-management interventions designed for patients with chronic heart failure. Outcomes of interest are mortality, all-cause hospital readmissions, chronic heart failure hospitalization rate and quality of life.
Nineteen randomized controlled trials were identified. The effectiveness of heart failure management programs initiating self-management interventions in patients with chronic heart failure indicate a positive effect, although not always significant, on reduction of numbers of all-cause hospital readmitted patients and due to chronic heart failure, decrease in mortality and increasing quality of life.
This systematic review found that current available published studies show methodological shortcomings impairing validation of the effectiveness of self-management interventions on mortality, all-cause hospital readmissions, chronic heart failure hospitalization rate and quality of life in patients with chronic heart failure.
Further research should determine independent effects of self-management interventions and different combinations of interventions on clinical and patient reported outcomes.
To review reliability, validity, and normative data from 7 different studies, involving a total of 1,988 people with diabetes, and provide a revised version of the Summary of Diabetes Self-Care Activities (SDSCA) measure.
The SDSCA measure is a brief self-report questionnaire of diabetes self-management that includes items assessing the following aspects of the diabetes regimen: general diet, specific diet, exercise, blood-glucose testing, foot care, and smoking. Normative data (means and SD), inter-item and test-retest reliability, correlations between the SDSCA subscales and a range of criterion measures, and sensitivity to change scores are presented for the 7 different studies (5 randomized interventions and 2 observational studies).
Participants were typically older patients, having type 2 diabetes for a number of years, with a slight preponderance of women. The average inter-item correlations within scales were high (mean = 0.47), with the exception of specific diet; test-retest correlations were moderate (mean = 0.40). Correlations with other measures of diet and exercise generally supported the validity of the SDSCA subscales (mean = 0.23).
There are numerous benefits from standardization of measures across studies. The SDSCA questionnaire is a brief yet reliable and valid self-report measure of diabetes self-management that is useful both for research and practice. The revised version and its scoring are presented, and the inclusion of this measure in studies of diabetes self-management is recommended when appropriate.
Research has addressed the problem of poor adherence for the past 4 decades. Much of the research has focused on the prevalence and predictors of adherence, research methodologies, and the development of measures of adherence. To a much lesser extent, attention has been given to intervention studies designed to evaluate strategies to improve adherence to treatment regimens. This article provides an up-to-date review of the literature on medication adherence in chronic disease.
The goal of multiple imputation is to provide valid inferences for statistical estimates from incomplete data. To achieve that goal, imputed values should preserve the structure in the data, as well as the uncertainty about this structure, and include any knowledge about the process that generated the missing data. Two approaches for imputing multivariate data exist: joint modeling (JM) and fully conditional specification (FCS). JM is based on parametric statistical theory, and leads to imputation procedures whose statistical properties are known. JM is theoretically sound, but the joint model may lack flexibility needed to represent typical data features, potentially leading to bias. FCS is a semi-parametric and flexible alternative that specifies the multivariate model by a series of conditional models, one for each incomplete variable. FCS provides tremendous flexibility and is easy to apply, but its statistical properties are difficult to establish. Simulation work shows that FCS behaves very well in the cases studied. The present paper reviews and compares the approaches. JM and FCS were applied to pubertal development data of 3801 Dutch girls that had missing data on menarche (two categories), breast development (five categories) and pubic hair development (six stages). Imputations for these data were created under two models: a multivariate normal model with rounding and a conditionally specified discrete model. The JM approach introduced biases in the reference curves, whereas FCS did not. The paper concludes that FCS is a useful and easily applied flexible alternative to JM when no convenient and realistic joint distribution can be specified.
Objectives:
The Diabetes Health Coaching Trial was a single-blind, randomized controlled trial designed to evaluate the effect of a 1-year telephone-based diabetes health-coaching intervention for community-dwelling adults living with type 2 diabetes mellitus. It concerned glycated hemoglobin levels, self-care behaviours and cost-effectiveness. The purpose of this article is to describe the rationale, design and participants' characteristics.
Methods:
The eligibility criteria were: 1) adults ≥18 years of age; 2) a diagnosis of type 2 diabetes; 3) glycated hemoglobin levels of ≥7.5% 6 months before randomization; 4) the ability to read, write and understand English; and 5) having telephone access. Participants were randomized to either usual diabetes education or diabetes education plus diabetes health coaching.
Results:
From May 2016 to December 2017, 365 participants were randomized into the trial. At baseline, the mean age was 57.9 (11.78) years, the mean duration of diabetes was 8.69 (8.54) years, the mean glycated hemoglobin level was 8.98 (1.58) %, and the mean body mass index was 35.03 (8.07) kg/m2.
Conclusions:
The baseline characteristics of the participants were equally distributed across the intervention and control groups. The Diabetes Health Coaching Trial is in a position to evaluate a potential treatment alternative and approach for type 2 diabetes and examined the effect of the intervention on clinical outcomes, self-care behaviours and cost-effectiveness.
Objective:
Evaluate a 16-week decision support and goal-setting intervention to compare diet quality, decision, and diabetes-related outcomes to a control group.
Methods:
Adults with type 2 diabetes (n=54) were randomly assigned to an intervention or control group. Intervention group participants completed one in-person motivational interviewing and decision support session followed by seven biweekly telephone coaching calls. Participants reported previous goal attempts and set diet- and/or physical activity-related goals during coaching calls. Control group participants received information about local health care resources on the same contact schedule.
Results:
There was a significant difference between groups for diabetes empowerment (p=0.045). A significant increase in diet quality, diabetes self-efficacy, and diabetes empowerment, and a significant decrease in diabetes distress and depressive symptoms (all p≤0.05) occurred in the intervention group. Decision confidence to achieve diet-related goals significantly improved from baseline to week 8 but then declined at study end (both p≤0.05).
Conclusions:
Setting specific diet-related goals may promote dietary change, and telephone coaching can improve psychosocial outcomes related to diabetes self-management.
Practice implications:
Informed shared decision making can facilitate progressively challenging yet attainable goals tailored to individuals' lifestyle. Decision coaching may empower patients to improve self-management practices and reduce distress.
This study aimed to evaluate the effectiveness of a telephone health coaching and support service provided to members of an Australian private health insurance fund-Telephonic Complex Care Program (TCCP)-on hospital use and associated costs. A case-control pre-post study design was employed using propensity score matching. Private health insurance members (n=273) who participated in TCCP between April and December 2012 (cases) were matched (1:1) to members who had not previously been enrolled in the program or any other disease management programs offered by the insurer (n=232). Eligible members were community dwelling, aged ≥65 years, and had 2 or more hospital admissions in the 12 months prior to program enrollment. Preprogram variables that estimated the propensity score included: participant demographics, diagnoses, and hospital use in the 12 months prior to program enrollment. TCCP participants received one-to-one telephone support, personalized care plan, and referral to community-based services. Control participants continued to access usual health care services. Primary outcomes were number of hospital admission claims and total benefits paid for all health care utilizations in the 12 months following program enrollment. Secondary outcomes included change in total benefits paid, hospital benefits paid, ancillary benefits paid, and total hospital bed days over the 12 months post enrollment. Compared with matched controls, TCCP did not appear to reduce health care utilization or benefits paid in the 12 months following program enrollment. However, program characteristics and implementation may have impacted its effectiveness. In addition, challenges related to evaluating complex health interventions such as TCCP are discussed.
AimThe evidence for self-management programmes in older adults varies in methodological approaches, and disease criteria. Using predetermined methodological criteria, we evaluated the effect of diabetes-specific self-management programme interventions in older adults.Methods The EMBASE, MEDLINE and Cochrane Central Register of Controlled Trials databases were searched from January 1980 to November 2013, as were reference lists from systematic reviews, meta-analyses and clinical practice guidelines. A total of 13 trials met the selection criteria, which included 4517 older adult participants; 2361 participants randomized to a diabetes self-management programme and 2156 to usual care.Results The pooled effect on HbA1c was a reduction of –2 mmol/mol (–0.2%; 95% CI –0.3 to –0.1); tailored interventions [–3 mmol/mol (–0.2%; 95% CI –0.4 to –0.1)] or programmes with a psychological emphasis [–3 mmol/mol (–0.2; 95% CI –0.4 to –0.1)] were most effective. A pooled treatment effect on total cholesterol was a 5.81 mg/dl reduction (95% CI –10.33 to –1.29) and non-significant reductions in systolic and diastolic blood pressure.Conclusions
Diabetes self-management programmes for older adults demonstrate a small reduction in HbA1c, lipids and blood pressure. These findings may be of greater clinical relevance when offered in conjunction with other therapies.This article is protected by copyright. All rights reserved.
Rationale, aims and objectivesInterventions aimed at improving chronic care typically consist of multiple interconnected parts, all of which are essential to the effect of the intervention. Limited attention has been paid to the use of routine clinical and administrative data in the evolution of these complex interventions. The purpose of this study is to examine the feasibility of routinely collected data when evaluating complex interventions and to demonstrate how a theory-based, realist approach to evaluation may increase the feasibility of routine data.Methods
We present a case study of evaluating a complex intervention, namely, the chronic care model (CCM), in Finnish primary health care. Issues typically faced when evaluating the effects of a complex intervention on health outcomes and resource use are identified by using routine data in a natural setting, and we apply context-mechanism-outcome (CMO) approach from the realist evaluation paradigm to improve the feasibility of using routine data in evaluating complex interventions.ResultsFrom an experimentalist approach that dominates the medical literature, routine data collected from a single centre offered a poor starting point for evaluating complex interventions. However, the CMO approach offered tools for identifying indicators needed to evaluate complex interventions.Conclusions
Applying the CMO approach can aid in a typical evaluation setting encountered by primary care managers: one in which the intervention is complex, the primary data source is routinely collected clinical and administrative data from a single centre, and in which randomization of patients into two research arms is too resource consuming to arrange.
Health coaching is quickly emerging as a new approach of partnering with patients to enhance self-management strategies for the purpose of preventing exacerbations of chronic illness and supporting lifestyle change. Medicare is now pilot testing this approach for patients with congestive heart failure and diabetes. With acute care hospitalization an outcome of great interest to us all, health coaching is an exciting technique worthy of consideration by home health providers.
Multiple imputation by chained equations is a flexible and practical approach to handling missing data. We describe the principles of the method and show how to impute categorical and quantitative variables, including skewed variables. We give guidance on how to specify the imputation model and how many imputations are needed. We describe the practical analysis of multiply imputed data, including model building and model checking. We stress the limitations of the method and discuss the possible pitfalls. We illustrate the ideas using a data set in mental health, giving Stata code fragments.
Multiple imputation of missing data continues to be a topic of considerable interest and importance to applied researchers. In this article, the ice package for multiple imputation by chained equations (also known as fully con- ditional specification) is further updated. Special attention is paid to categorical variables. The relationship between ice and the new multiple-imputation system in Stata 11 is clarified.
The objectives of the study were to design and develop a questionnaire to measure individuals' perceptions of the impact of diabetes on their quality of life (QoL). The design of the ADDQoL (Audit of Diabetes Dependent QoL) was influenced by patient-centred principles underlying the SEIQoL interview method. Respondents rate only personally-applicable life domains, indicating importance and impact of diabetes. Fifty-two out-patients with diabetes and 102 attending diabetes education open days provided data for psychometric analyses. Each of the 13 domain-specific ADDQoL items was relevant and important for substantial numbers of respondents. Factor analysis and Cronbach's alpha coefficient of internal consistency (0.85) supported combination of items into a scale. Insulin-treated patients reported greater impact of diabetes on QoL than table/diet-treated patients. People with microvascular complications showed, as expected, greater diabetes-related impairment of QoL than people without complications. Unlike other QoL measures, the ADDQoL is an individualized questionnaire measure of the impact of diabetes and its treatment on QoL. Preliminary evidence of reliability and validity is established for adults with diabetes. Findings suggest that the ADDQoL will be more sensitive to change and responsive to differences than generic QoL measures.
Patient self-management support programs: An evaluation. Agency for Healthcare Research and Quality. US Department of Health and Human Services
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