Behavior change interventions in patients with type 2 diabetes: a systematic review of the effects on self-management and A1c

2021 ◽  
Author(s):  
Ana Paula Delgado Bomtempo Batalha ◽  
Isabela Coelho Ponciano ◽  
Gabriela Chaves ◽  
Diogo Carvalho Felício ◽  
Raquel Rodrigues Britto ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Behavior Change ◽  
Self Management ◽  
Behavior Change Interventions

scholarly journals Diet Behavior Change Techniques in Type 2 Diabetes: A Systematic Review and Meta-analysis

Diabetes Care ◽  
2017 ◽  
Vol 40 (12) ◽  
pp. 1800-1810 ◽  
Author(s):  
Kevin A. Cradock ◽  
Gearóid ÓLaighin ◽  
Francis M. Finucane ◽  
Rhyann McKay ◽  
Leo R. Quinlan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Behavior Change ◽  
Meta Analysis ◽  
Behavior Change Techniques ◽  
Diet Behavior

scholarly journals Impact of mobile health applications on self-management in patients with type 2 diabetes mellitus: protocol of a systematic review

BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e025714 ◽  
Author(s):  
Benard Ayaka Bene ◽  
Siobhan O’Connor ◽  
Nikolaos Mastellos ◽  
Azeem Majeed ◽  
Kayode Philip Fadahunsi ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Systematic Review ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Global Health ◽  
Mobile Health ◽  
Self Management ◽  
Cochrane Central Register ◽  
Mhealth Apps

IntroductionThe emergence of mobile health (mHealth) solutions, particularly mHealth applications (apps), has shown promise in self-management of chronic diseases including type 2 diabetes mellitus (T2DM). While majority of the previous systematic reviews have focused on the effectiveness of mHealth apps in improving treatment outcomes in patients with T2DM, there is a need to also understand how mHealth apps influence self-management of T2DM. This is crucial to ensure improvement in the design and use of mHealth apps for T2DM. This protocol describes how a systematic review will be conducted to determine in which way(s) mHealth apps might impact on self-management of T2DM.MethodsThe following electronic databases will be searched from inception to April 2019: PubMed, MEDLINE, EMBASE, Global Health, PsycINFO, CINAHL, The Cochrane Central Register of Controlled Trials, Scopus, Web of Science, ProQuest Dissertations & Theses Global, Health Management Information Consortium database, Google Scholar and ClinicalTrials.gov. The Cochrane risk of bias tool will be used to assess methodological quality. The primary outcome measures to be assessed will be ‘change in blood glucose’. The secondary outcomes measures will be ‘changes in cardiovascular risk markers’ (including blood pressure, body mass index and blood lipids), and self-management practices. Others will include: health-related quality of life, economic data, social support, harms (eg, death or complications leading to hospital admissions or emergency unit attendances), death from any cause, anxiety or depression and adverse events (eg, hypoglycaemic episodes).Ethics and disseminationThis study will not involve the collection of primary data and will not require ethical approval. The review will be published in a peer-reviewed journal and a one-page summary of the findings will be shared with relevant organisations. Presentation of findings will be made at appropriate conferences.Trial registration numberCRD42017071106.

scholarly journals Tailored mobile text messaging interventions targeting type 2 diabetes self-management: A systematic review and a meta-analysis

2019 ◽  
Vol 5 ◽  
pp. 205520761984527 ◽  
Author(s):  
Cigdem Sahin ◽  
Karen L Courtney ◽  
PJ Naylor ◽  
Ryan E Rhodes
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Text Messaging ◽  
Meta Analysis ◽  
Scientific Evidence ◽  
Self Management ◽  
Reference List ◽  
Pool Data ◽  
Message Delivery

Objectives This study aimed to identify, assess and summarize available scientific evidence on tailored text messaging interventions focused on type 2 diabetes self-management. The systematic review concentrated on message design and delivery features, and tailoring strategies. The meta-analysis assessed the moderators of the effectiveness of tailored text messaging interventions. Methods A comprehensive search strategy included major electronic databases, key journal searches and reference list searching for related studies. PRISMA and Cochrane Collaboration's guidelines and recommended tools for data extraction, quality appraisal and data analysis were followed. Data were extracted on participant characteristics (age, gender, ethnicity), and interventional and methodological characteristics (study design, study setting, study length, choice of modality, comparison group, message type, format, content, use of interactivity, message frequency, message timing, message delivery, tailoring strategies and theory use). Outcome measures included diet, physical activity, medication adherence and glycated hemoglobin data (HbA1C). Where possible, a random effects meta-analysis was performed to pool data on the effectiveness of the tailored text messaging interventions and moderator variables. Results The search returned 13 eligible trials for the systematic review and 11 eligible trials for the meta-analysis. The majority of the studies were randomized controlled trials, conducted in high-income settings, used multi-modalities, and mostly delivered informative, educational messages through an automated message delivery system. Tailored text messaging interventions produced a substantial effect ( g = 0.54, 95% CI = 0.08–0.99, p < 0.001) on HbA1C values for a total of 949 patients. Subgroup analyses revealed the importance of some moderators such as message delivery ( QB = 18.72, df = 1, p = 0.001), message direction ( QB = 5.26, df = 1, p = 0.022), message frequency ( QB = 18.72, df = 1, p = 0.000) and using multi-modalities ( QB = 6.18, df = 1, p = 0.013). Conclusions Tailored mobile text messaging interventions can improve glycemic control in type 2 diabetes patients. However, more rigorous interventions with larger samples and longer follow-ups are required to confirm these findings and explore the effects of tailored text messaging on other self-management outcomes.

scholarly journals Self-management interventions for Type 2 Diabetes: systematic review protocol focusing on patient workload and capacity support

2021 ◽  
Vol 6 ◽  
pp. 257
Author(s):  
Peter Hanlon ◽  
Iona Bryson ◽  
Holly Morrison ◽  
Qasim Rafiq ◽  
Kasey Boehmer ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Hospital Admissions ◽  
Macrovascular Disease ◽  
Self Management ◽  
Management Support ◽  
Patient Capacity ◽  
Management Interventions ◽  
The Impact

Introduction: People living with type 2 diabetes undertake a range of tasks to manage their condition, collectively referred to as self-management. Interventions designed to support self-management vary in their content, and efficacy. This systematic review will analyse self-management interventions for type 2 diabetes drawing on theoretical models of patient workload and capacity. Methods and analysis: Five electronic databases (Medline, Embase, CENTRAL, CINAHL and PsycINFO) will be searched from inception to 27th April 2021, supplemented by citation searching and hand-searching of reference lists. Two reviewers will independently review titles, abstracts and full texts. Inclusion criteria include Population: Adults with type 2 diabetes mellitus; Intervention: Randomised controlled trials of self-management support interventions; Comparison: Usual care; Outcomes: HbA1c (primary outcome) health-related quality of life (QOL), medication adherence, self-efficacy, treatment burden, healthcare utilization (e.g. number of appointment, hospital admissions), complications of type 2 diabetes (e.g. nephropathy, retinopathy, neuropathy, macrovascular disease) and mortality; Setting: Community. Study quality will be assessed using the Effective Practice and Organisation of Care (EPOC) risk of bias tool. Interventions will be classified according to the EPOC taxonomy and the PRISMS self-management taxonomy and grouped into similar interventions for analysis. Clinical and methodological heterogeneity will be assessed within subgroups, and random effects meta-analyses performed if appropriate. Otherwise, a narrative synthesis will be performed. Interventions will be graded on their likely impact on patient workload and support for patient capacity. The impact of these theoretical constructs on study outcomes will be explored using meta-regression. Conclusion This review will provide a broad overview of self-management interventions, analysed within the cumulative complexity model theoretical framework. Analyses will explore how the workload associated with self-management, and support for patient capacity, impact on outcomes of self-management interventions. Registration number: PROSPERO CRD42021236980.

Patient activation and Type 2 diabetes mellitus self-management: a systematic review and meta-analysis

2020 ◽  
Vol 26 (6) ◽  
pp. 431
Author(s):  
Hassan Hosseinzadeh ◽  
Iksheta Verma ◽  
Vinod Gopaldasani
Keyword(s):  
Diabetes Mellitus ◽  
Systematic Review ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Clinical Outcomes ◽  
Meta Analysis ◽  
Patient Activation ◽  
Self Management ◽  
Haemoglobin A1c

Patient activation has been recognised as a reliable driver of self-management decision-making. This systematic review and meta-analysis examines existing evidence on whether embedding patient activation within Type 2 diabetes mellitus (T2DM) self-management programs can improve patient outcomes. This review has included 10 randomised controlled trials (RCTs) conducted between 2004 and 2019 retrieved from well-known databases such as MEDLINE, PubMed, CINAHL Plus, Scopus, ProQuest and ScienceDirect. The eligible RCTs were excluded if they scored low according to Cochrane Collaboration’s ‘risk of bias’ criteria. Random-effects meta-analyses showed that there were no significance changes in haemoglobin A1C (HbA1c), body mass index (BMI) and patient activation measure (PAM) between intervention and control groups after the intervention; however, the systematic review findings indicated that an improved patient activation level led to significant improvements in T2DM self-management and clinical outcomes including HbA1c level. Studies with a longer follow-up period conducted in community settings and delivered by peer coaches were more likely to lead to significant improvement in both patient activation levels and T2DM self-management and clinical outcomes. This review concludes that patient activation can be used as a reliable tool for improving T2DM self-management and clinical outcomes.

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