Self-monitoring smartphone apps and health coaching have both individually been shown to improve weight-related outcomes, but their combined effects remain unclear.
This study aims to examine the effectiveness of combining self-monitoring apps with health coaching on anthropometric, cardiometabolic, and lifestyle outcomes in people with overweight and obesity.
Relevant articles published from inception till June 9, 2022, were searched through 8 databases (Embase, CINAHL, PubMed, PsycINFO, Scopus, The Cochrane Library, and Web of Science). Effect sizes were pooled using random-effects models. Behavioral strategies used were coded using the behavior change techniques taxonomy V1.
A total of 14 articles were included, representing 2478 participants with a mean age of 39.1 years and a BMI of 31.8 kg/m2. Using combined intervention significantly improved weight loss by 2.15 kg (95% CI -3.17 kg to -1.12 kg; P<.001; I2=60.3%), waist circumference by 2.48 cm (95% CI -3.51 cm to -1.44 cm; P<.001; I2=29%), triglyceride by 0.22 mg/dL (95% CI -0.33 mg/dL to 0.11 mg/dL; P=.008; I2=0%), glycated hemoglobin by 0.12% (95% CI -0.21 to -0.02; P=.03; I2=0%), and total calorie consumption per day by 128.30 kcal (95% CI -182.67 kcal to -73.94 kcal; P=.003; I2=0%) kcal, but not BMI, blood pressure, body fat percentage, cholesterol, and physical activity. Combined interventional effectiveness was superior to receiving usual care and apps for waist circumference but only superior to usual care for weight loss.
Combined intervention could improve weight-related outcomes, but more research is needed to examine its added benefits to using an app.
PROSPERO CRD42022345133; https://tinyurl.com/2zxfdpay.

BACKGROUND: Health coaching-based interventions can support behaviour change to improve oral health. This scoping review aims to identify key characteristics of health coaching-based interventions for oral health promotion.
METHODS: The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist and the Joanna Briggs Institute manual for evidence synthesis were used in this review. A search strategy using medical subject heading terms and keywords was developed and applied to search the following databases: CINAHL, Ovid, PubMed, Cochrane Library and Scopus. Thematic analysis was used to synthesise the data.
RESULTS: Twenty-three studies met the inclusion criteria and were included in this review. These studies were predominantly based on health coaching and motivational interviewing interventions applied to oral health promotion. The following are the characteristics of health coaching-based interventions extracted from themes of the included studies: (a) Health professionals should be trained on the usage of motivational interviewing/health coaching interventions; (b) oral health professionals should acquire motivational techniques in their practice to engage patients and avoid criticisms during the behaviour change process; (c) routine brief motivational interviewing/health coaching intervention sessions should be introduced in dental clinics; (d) traditional oral health education methods should be supplemented with individually tailored communication; and (e) for cost-effectiveness purposes, motivational interviewing/health coaching strategies should be considered.
CONCLUSIONS: This scoping review reveals that health coaching-based techniques of health coaching and motivational interviewing can significantly impact oral health outcomes and behaviour change and can improve oral health professional-patient communication. This calls for the use of health coaching-based techniques by dental teams in community and clinical settings. This review highlights gaps in the literature, suggesting the need for more research on health coaching-based intervention strategies for oral health promotion.

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.
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).
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.
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.
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021228567 .

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.
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.
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.
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.
https://www.crd.york.ac.uk/prospero, identifier (CRD42022347478).

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.
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.
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.
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.
PROSPERO identifier, CRD42022347478.

To appraise and synthesize evidence on the effects of health coaching as the primary intervention on cardiometabolic health among middle-aged adults.
Six electronic databases (MEDLINE, Embase, PsycINFO, CINAHL, PubMed, and the Cochrane library) were searched from inception until July 2021.
Randomized controlled trials and controlled clinical trials published in English, reporting health coaching aimed to promote behavioral changes for improving cardiometabolic health among middle-aged adults were included. Studies on health coaching as secondary intervention were excluded.
Two reviewers selected the articles, appraised the study quality, and extracted data independently. All kinds of outcomes related to cardiometabolic health, including health behaviors, psychological and physiological outcomes, were included.
Meta-analysis was performed if three or more studies reported the same outcomes. Narrative synthesis was performed if pooling of data for meta-analysis was not feasible.
Eight studies were reviewed. Most studies involved substantial risk of bias. The majority of the participants were women (99.1%). Meta-analysis showed a small but significant effect of health coaching on increasing physical activity (SMD = .34, 95% CI = .08-.60, p = .01, I2 = 0%); however, its effect on perceived barriers to physical activity and depressive symptoms was nonsignificant. Narrative synthesis yielded inconsistent results on diet, smoking, anxiety, goal achievement and self-efficacy for behavioral change, physiological outcomes, and metabolic syndrome severity, and nonsignificant effects on alcohol consumption, sleep quality, perceived benefits of physical activities, and cardiovascular symptoms.
Health coaching has significant effects on increasing physical activity among middle-aged adults; however, its effects on health behaviors and risk factors related to cardiometabolic health are inconclusive. Further efforts are warranted to examine how health coaching can improve cardiometabolic health among middle-aged adults.

BACKGROUND: Health coaching is an intervention process for driving behavior change through goal-setting, education, encouragement, and feedback on health-related behaviors. Telehealth systems that include health coaching and remote monitoring are making inroads in managing chronic conditions and may be especially suited for older populations.
OBJECTIVE: This literature review aimed to investigate the current status of health coaching interventions incorporating telehealth technology and the associated effectiveness of this intervention to deliver health care with an emphasis on older adults (aged 65 and older).
METHODS: A literature review was conducted to identify the research conducted on health coaching combined with remote monitoring for delivering health care to older adults. The Ovid MEDLINE and CINAHL databases were queried using a combination of relevant search terms (including middle aged, aged, older adult, elderly, health coaching, and wellness coaching). The search retrieved 196 papers published from January 2010 to September 2019 in English. Following a systematic review process, the titles and abstracts of the papers retrieved were screened for applicability to health coaching for older adults to define a subset for further review. Papers were excluded if the studied population did not include older adults. The full text of the 42 papers in this subset was then reviewed, and 13 papers related to health coaching combined with remote monitoring for older adults were included in this review.
RESULTS: Of the 13 studies reviewed, 10 found coaching supported by telehealth technology to provide effective outcomes. Effectiveness outcomes assessed in the studies included hospital admissions/re-admissions, mortality, hemoglobin A1c (HbA1c) level, body weight, blood pressure, physical activity level, fatigue, quality of life, and user acceptance of the coaching program and technology.
CONCLUSIONS: Telehealth systems that include health coaching have been implemented in older populations as a viable intervention method for managing chronic conditions with mixed results. Health coaching combined with telehealth may be an effective solution for providing health care to older adults. However, health coaching is predominantly performed by human coaches with limited use of technology to augment or replace the human coach. The opportunity exists to expand health coaching to include automated coaching.

Health coaching has emerged as a potential supporting tool for health professionals to overcome behavioral barriers, but its efficacy in weight management remains unclear. We conducted a systematic review and meta-analysis to synthesize and evaluate the quality of evidence supporting the use of self-reported health coaching for weight loss. Seven electronic databases (PubMed, Web of Science, Scopus, Cochrane, Psyinfo, Virtual Health Library, and Scielo) were independently searched from inception to May 2020. This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation recommendations. Any study that investigated a self-reported health coaching intervention with the goal of inducing weight loss in individuals of any age, health, or training status was considered for inclusion. Quantitative data were analyzed using multilevel hierarchical metaregression models conducted within a Bayesian framework. A total of 653 studies were screened and 38 were selected for inclusion. The quality of evidence supporting outcomes based on the entire evidence base was very low and studies were deemed to have high risk of bias. Meta-analysis of controlled studies provided evidence of an effect favoring coaching compared with usual care but was trivial in magnitude [effect size (ES)0.5: -0.09; 95% credible interval (CrI): -0.17, -0.02]. The multilevel extension of Egger\'s regression-intercept test indicated the existence of publication bias, whereas a sensitivity analysis based only on those studies deemed to be of high quality provided no evidence of an effect of coaching on weight loss (ES0.5: -0.04; 95% CrI: -0.12, 0.09). Considered collectively, the results of this investigation indicate that the available evidence is not of sufficient quality to support the use of self-reported health coaching as a health care intervention for weight loss. This trial was registered at Prospective Register of Systematic Reviews (PROSPERO) as CRD42020159023.

In this systematic review, we focus on the clinical impact of digital tools for providing health coaching, education, and facilitating behavior in patients with prediabetes or type 2 diabetes. Our approach was designed to provide insights for clinicians and health care systems that are considering adopting such digital tools.
We searched the CINAHL, Scopus, and Ovid/MEDLINE databases using PRISMA guidelines for studies that reported digital coaching strategies for management and prevention of type 2 diabetes published from January 2014 to June 2019. Articles were reviewed by 2 independent blinded reviewers. Twenty-one articles met inclusion criteria.
We found that 20 of 21 studies in our analysis showed statistically significant improvements in at least one measure of diabetes control including HbA1c, weight loss, fasting blood glucose, and BMI. Studies that reported weight loss percentage from baseline at 1 year reported values ranging from -3.04% to -8.98%, similar to outcomes with traditional coaching in the Diabetes Prevention Program (N = 4). Additionally, all studies that included a comparison group of in-person or telephone-based coaching showed statistically better or similar outcomes in the digital coaching group (N = 5).
The evidence reported in this systematic review suggests that digital health coaching offers a promising strategy for long-term management and prevention of type 2 diabetes in diverse populations with similar benefits to in-person or telephone-based health coaching. We argue that, with the potential to treat large numbers of individuals in diverse geographic locations, digital coaching offers a promising solution to the rapid increase in diabetes prevalence.

Background: Across the globe, managing chronic diseases has been recognized as a challenge for patients and healthcare providers. The state of the art in managing chronic conditions requires not only responding to the clinical needs of the patient, but also guaranteeing a comfortable state of wellbeing for them, despite living with the disease. This demands mutual effort between the patient and the physician in constantly collecting data, monitoring, and understanding the disease. The advent of artificial intelligence has made this process easier. However, studies have rarely attempted to analyze how the different artificial intelligence based health coaching systems are used to manage different types of chronic conditions. Objective: Throughout this grounded theory literature review, we aim to provide an overview for the features that characterize artificial intelligence based health coaching systems used by patients with chronic diseases. Methods: During our search and paper selection process process, we use three bibliographic libraries (PubMed, IEEE Xplore, and ACM Digital Library). Using the grounded theory, we extract overarching themes for the artificial intelligence based health coaching systems. These systems are then classified according to their role, platform, type of interaction with the patient, as well as targeted chronic conditions. Of 869 citations retrieved, 31 unique studies are included in this review. Results: The included studies assess 14 different chronic conditions. Common roles for AI-based health coaching systems are: developing adherence, informing, motivating, reminding, preventing, building a care network, and entertaining. Health coaching systems combine the aforementioned roles to cater to the needs of the patients. The combinations of these roles differ between multilateral, unilateral, opposing bilateral, complementing bilateral, one-role-missing, and the blurred role combinations. Conclusion: Clinical solutions and research related to artificial intelligence based health coaching systems are very limited. Clear guidelines to help develop artificial intelligence-based health coaching systems are still blurred. This grounded theory literature review attempted to shed the light on the research and development requirements for an effective health coaching system intended for patients with chronic conditions. Researchers are recommended to use this review to identify the most suitable role combination for an effective health coaching system development.