Introduction {#Sec1} ============ Diabetes mellitus (DM) is one of the most common chronic diseases affecting the health and well-being of humans around the globe. There are two types of diabetes, type I and type II, that cause chronic hyperglycemia. The International Diabetes Federation reported that, in 2012, approximately 9% of the world's adult population have diabetes. It is anticipated that this number will increase to 10% by 2030 \[[@CR1]\]. This will pose an enormous burden on society. It is also estimated that one out of every eleven people will be diagnosed with DM in their lifetime \[[@CR2]\]. Despite being a chronic condition, DM is difficult to manage. It causes many complications in the cardiovascular, central nervous, and urinary systems. The management of DM involves an intensive self-management plan that requires ongoing health education, self-monitoring of blood glucose (SMBG) at home, and insulin therapy. Most patients with DM visit healthcare professionals such as physicians, nurses, pharmacists, and diabetes educators in the management of their disease \[[@CR3]\]. Diabetes and chronic disease self-management programmes are interventions that are designed to support and provide information, psychosocial support, health-related education and skills training, problem solving, and decision making to patients with chronic conditions such as diabetes. Self-management programmes have been shown to improve a variety of outcomes such as knowledge, self-efficacy, and health outcomes such as clinical measurements, quality of life, and patient satisfaction \[[@CR4]\]. A meta-analysis of 35 randomised controlled trials (RCT) published between 1999 and 2007 concluded that self-management interventions improved HbA1c in the range from 0.23% to 1.07% \[[@CR5]\]. Similar results were found in other systematic reviews \[[@CR6]--[@CR11]\]. In 2011, a Cochrane review reported that self-management programmes significantly reduced the risk of developing or worsening DM-related complications (pneumonia, renal complications, hypoglycemia) \[[@CR12]\]. Systematic reviews and meta-analyses for self-management programmes conducted among diabetes patients in Jordan, however, are limited. These studies found that self-management programmes had no impact on the quality of life of diabetic patients \[[@CR13]\]. Also, another study reported that there was no difference in glycemic control between intervention and control groups \[[@CR14]\]. This lack of evidence-based interventions is a major barrier to health promotion in developing countries, such as Jordan. Therefore, it is important to conduct systematic reviews on self-management programmes to support policy decision making. To the best of our knowledge, this is the first systematic review of randomised controlled trials (RCTs) among adult diabetics in Jordan. We aimed to synthesise the best available evidence on self-management education and care on HbA1c in adults with diabetes. Methods {#Sec2} ======= Our systematic review was conducted according to the Cochrane Handbook for Systematic Reviews of Interventions \[[@CR15]\]. This review is registered in the PROSPERO international prospective register of systematic reviews, registration number CRD42015025068. Data sources {#Sec3} ------------ A systematic literature search was performed in multiple electronic databases to identify relevant publications for our review: MEDLINE (accessed via PubMed, 1946 to April 1, 2015), Scopus (Elsevier, January 01, 2015), CINAHL (EBSCO, January 01, 2015), PsycINFO (EBSCO, January 01, 2015), SCOPUS (Elsevier, January 01, 2015), and the Cochrane Central Register of Controlled Trials (CENTRAL). Reference lists from included articles and relevant systematic reviews were reviewed to identify additional studies. Furthermore, the internet was searched using Google Scholar and Clinical Trials.gov. No language or date limits were applied. All searches were restricted to human studies and articles published in English. For the purposes of this systematic review, we applied the "PICO" approach (population, intervention, comparison, and outcome). Study selection {#Sec4} --------------- The primary objective of this review was to identify the effects of self-management programmes on glycaemic control among diabetic adults. RCTs were included for the purposes of this review. A self-management programme could involve educating the patient about the disease, providing skills training for diabetes self-management, encouraging regular self-monitoring of the blood glucose level, or encouraging adherence to lifestyle changes. A self-management programme could be a single, continuous, short-term, or multi-modal intervention. The interventions could involve one or more health professionals; only patients could provide self-management education and healthcare providers could prescribe medications and insulin. The control group could provide diabetes education or usual care. Interventions could take place at any time during or after the diagnosis of diabetes. Studies that were ongoing were included in our review. Articles that met the following inclusion criteria were selected for this review:Randomised controlled trials (RCTs) designed to test the effectiveness of diabetes self-management programmes on glycaemic control or other outcomes for people diagnosed with diabetes. The age of patients had to be between 18 and 85 years. Only patients with type 1 or type 2 diabetes were included.Articles published in English.RCTs reported in all languages.Peer-reviewed journal articles. Articles were excluded based on the following exclusion criteria:Articles in languages other than English.Studies that did not have an intervention or control group.Opinion articles or abstracts.Duplicate publications of RCTs.Unpublished trials.Studies involving surgical interventions.Outcome measures of interest. Two authors independently screened titles, abstracts, and articles in full against the inclusion and exclusion criteria described above to identify studies that met the review eligibility criteria. If a disagreement occurred regarding inclusion of a particular study, it was discussed, and a consensus was achieved. Data extraction {#Sec5} --------------- Data were extracted from included RCTs by using a standardised Excel template. Two authors independently extracted data from all included studies, including general information (study author, publication year, setting, journal of publication, inclusion/exclusion criteria), intervention and control group details, method of allocation, and outcomes (type of outcomes, assessment time, type of data, and data points). Risk of bias was assessed using the Cochrane Collaboration risk-of-bias tool \[[@CR16]\], by which we evaluated eight key domains: sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessors, incomplete outcome data, selective outcome reporting, and other potential sources of bias. Risk of bias was rated as low, unclear, or high, which was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) \[[@CR17]\]. Any disagreements were resolved by discussion, and a consensus was achieved. Statistical analysis {#Sec6} -------------------- All analyses were conducted using RevMan software version 5.1 \[[@CR18]\]. Data were entered and analysed in the form of Review Manager 5.1 \[[@CR18]\]. Review Manager software was used to produce forest plots and generate pooled mean difference (MD) and 95% confidence intervals (CI). A random effects model was used for all outcome measures (HbA1c level at the end of the trial). Based on the *I*^2^ statistic, which represents the variation across studies due to heterogeneity, we determined the size of the effect (the difference between the intervention and control groups) for each outcome measure. The intervention effect is represented by the MD of the outcomes. In the case of studies that report more than one outcome, only one effect size estimate was included in the review. The *I*^2^ statistic with a value of \<25% represents no evidence of heterogeneity, 25--50% indicates low heterogeneity, 50--75% indicates moderate heterogeneity, and \>75% indicates high heterogeneity \[[@CR19]\]. A fixed-effects model was used in situations when there was low heterogeneity between the studies included in the meta-analysis. Additional file {#Sec7} =============== Additional file 1:Searching PubMed (accessed April 2015). This data file shows the search strategies conducted in PubMed. (DOCX 13 kb) CI : Confidence interval HbA1c : Glycated haemoglobin MD : Mean difference RCT : Randomised controlled trial **Electronic supplementary material** The online version of this article (doi:10.1186/s13643-017-0582-6) contains supplementary material, which is available to authorized users. Not applicable. Funding {#FPar1} ======= This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Availability of data and materials {#FPar2} ================================== The datasets analysed during the current study are available from the corresponding author on reasonable request. Authors' contributions {#FPar3} ====================== RA participated in designing the systematic review, analysing and interpreting the data, and drafting the manuscript. SB participated in designing the systematic review and critically revised the manuscript. All authors read and approved the final manuscript. Competing interests {#FPar4} =================== The authors declare that they have no competing interests. Consent for publication {#FPar5} ======================= Not applicable. Ethics approval and consent to participate {#FPar6} ========================================== Not applicable. Publisher's Note {#FPar7} ================ Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.