The objective is to investigate the benefits and harms of guided self-determination and self-determination theory interventions versus usual care in people with diabetes.
This protocol has been registered in the PROSPERO database ID nr. 181144 (submitted on the 24th April 2020) and is reported according to the preferred Reporting Items for Systematic reviews and Meta-analysis Protocols (PRISMA-P) 2015 statement . (Checklist as additional file).
Criteria for considering studies for this review
Types of studies
We will include randomised clinical trials and cluster randomised trials irrespective of publication status, reported outcomes, publication date, publication type, and language conducted in any setting for assessment of benefits and harms. We will not include quasi-randomised studies or observational studies .
Types of participants
People with a diagnosis of type 1 diabetes or type 2 diabetes as defined by trialists. The participants should be described as adolescents or adults by trialists. Trials including participants described as children will be excluded.
Types of interventions
Experimental interventions theoretically based on guided self-determination or self-determination theory provided face-to-face or digitally by any health care professional in any setting. The trials must refer to either guided self-determination or self-determination theory as their primary theoretical framework. Additionally, the trials must use the reflection sheets and the communication forms that are basic to the guided self-determination method.
Control group interventions
Control interventions may be ’no intervention’, wait list, or standard care as defined by trialists (e.g. standard healthcare provision). We will also accept attention placebo control , which is a control intervention that is not related to enhancing autonomy support but include a similar number of contacts with the interventionists .
- Quality of life (continuous data) measured by either any validated diabetes-specific questionnaire such as the diabetes quality of life  or any validated generic outcome measure such as the WHO-5 questionnaire .
- All-cause mortality (dichotomous data).
- Proportion of participants with one or more serious adverse events (dichotomous data), defined as any untoward medical occurrence that resulted in death, was life-threatening, required hospitalization or prolonging of existing hospitalization and resulted in persistent or significant disability or jeopardized the patient . If the trialists do not use the ICH-GCP definition, we will include the data if the trialists use the term “serious adverse event.” If the trialists do not use the ICH-GCP definition nor use the term serious adverse event, then we will also include the data, if the event clearly fulfils the ICH-GCP definition for a serious adverse event.
- Diabetes distress (continuous data) measured with any validated instruments such as the diabetes distress scale or the problem areas in diabetes scale [61, 62].
- Depressive symptoms (continuous data) measured with any validated instruments such as the Patient Health Questionnaire (PHQ-9) or the hospital anxiety and depression scale 
- Proportion of participants with at least one adverse event (dichotomous data) not considered serious .
Assessment time points
The primary assessment time points for all outcomes will be closest to the end of intervention. We will secondly assess all outcomes at maximum follow-up.
Search methods for identification of studies
We will search Cochrane Central Register of Controlled Trials (CENTRAL), Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medical database (EMBASE), Latin American and Caribbean Health Sciences Literature (LILACS), PsycINFO, Science Citation Index Expanded (SCI-EXPANDED), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Social Sciences Citation Index (SSCI), Conference Proceedings Citation Index—Science (CPCI-S), and Conference Proceedings Citation Index—Social Science & Humanities (CPCI-SSH) to identify relevant trials. We will search all databases from their inception to the present. For a detailed search strategy for all electronic databases, see Additional file 2. The search strategy for PsycINFO will be given at the review stage.
Searching other resources
The reference lists of relevant publications will be checked for any unidentified randomised trials. We will contact the authors of included studies by email asking for unpublished randomised trials. Further, we will search for ongoing trials on the following:
- gov (www.clinicaltrials.gov)
- Google Scholar (https://scholar.google.dk/)
- The Turning Research into Practice (TRIP) Database (https://www.tripdatabase.com/)
- European Medicines Agency (EMA) (http://www.ema.europa.eu/ema/)
- US Food and Drug Administration (FDA) (www.fda.gov)
- China Food and Drug Administration (CFDA) (http://eng.cfda.gov.cn/WS03/CL0755/)
- Medicines and Healthcare Products Regulatory Agency (https://www.gov.uk/government/organisations/medicines-and-healthcare-products-regulatoryagency)
- The World Health Organization (WHO) International
- Clinical Trials Registry Platform (ICTRP) search portal (http://apps.who.int/trialsearch/)
- Cochrane Database of Systematic Reviews
Additionally, we will hand search conference abstracts from diabetes conferences for relevant trials. We will also consider relevant-for-the-review unpublished and grey literature trials if we identify these. Reference lists of reviews and meta-analyses retrieved from the searches will also be screened. The latest search will be performed in May 2020 supplemented with ongoing alerts from the databases when new studies within the search matrix are published. We will end inclusion in June 2020.
Data collection and analysis
We will conduct the review following The Cochrane Collaboration guidelines . The analyses will be performed by the use of Review manager 5.3 . The analyses will be performed using Trial Sequential Analysis  and Stata version 16 .
Selection of studies
All potentially eligible trials identified in the literature searches will be imported into the systematic review management program, Covidence  or a reference management program. Two authors (ASM) and a co-author will independently screen potentially eligible studies on title and abstract. All full text studies will be retrieved and independently assessed by the two reviewers. Reasons for exclusion will be recorded. Any disagreements will be solved by discussion or by consulting a third author. Trial selection will be displayed in a flow diagram according to the PRISMA-P .
Data extraction and management
Two authors will independently extract data from included trials. Disagreements will be solved by discussion or by consulting a third author. We will assess duplicate publications and companion papers of a trial together, to evaluate all data simultaneously (to maximize data extraction and correct bias assessment). We will contact all trial authors by email to specify any additional data, which may not be reported sufficiently or at all in the publication.
The following data will be extracted: trial design (parallel, factorial, or crossover), number of intervention groups, lengths of follow-up, risk of bias components, and inclusion and exclusion criteria.
Participants characteristics and diagnosis
We will extract the following data: number of randomised participants in each intervention group, adherence to intervention, age range (mean or median), sex ratio, type of diabetes, diabetes treatment, number of comorbidities (complications of diabetes/other comorbidities) and socioeconomic status/educational level.
We will extract the following data: type of intervention, treatment duration of intervention group, number of sessions (or dose), intensity, and treatment format provided to the intervention group.
Education and training of the interventionists
The intervention could be provided by any interventionist. Data on who is providing the intervention will be extracted. The training of the interventionists providing the method will be reported. Assessment of fidelity will be reported.
We will extract the following data: type of co-intervention, treatment duration of co-intervention, number of sessions (or dose), and treatment format.
Control group intervention
We will extract the following data: type of control group intervention, treatment duration of control group, number of sessions (or dose), intensity, and treatment format provided to the control group. Any reported beneficial and harmful effects of the control intervention will be derived and described.
For each outcome, we will extract the number of analysed participants, the number of participants lost to follow-up/withdrawals/crossover in the experimental and the control group.
Funding of the trial and notable conflicts of interest of the trial authors will be extracted, if available. Unusual reporting of outcome data will be noted in the ‘Characteristics of included studies’ table. Two reviewers (ASM and co-author) will independently extract and transfer data into Review Manager . Disagreements will be solved through discussion or by consulting a third author.
Risk of bias assessment
Risk of bias in included RCTs will be assessed based on the domains described below [44, 69-79]. This assessment will be done separately for each outcome and comparison and will then be considered in relation to overall reliability of the evidence. This will be done in pairs by two independent review authors (ASM and co-author).
Random sequence generation
- Low risk of bias: study authors performed sequence generation using computer random number generation or a random numbers table. Drawing lots, tossing a coin, shuffling cards, and throwing dice were adequate if an independent person not otherwise involved in the study performed them
- Unclear risk of bias: study authors did not specify the method of sequence generation
- High risk of bias: sequence generation method was not random or quasi-randomised. Such studies will be excluded for the assessment of benefits.
- Low risk of bias: participant allocations could not have been foreseen in advance of, or during, enrolment. A central and independent randomisation unit controlled the allocation. Investigators were unaware of the allocation sequence (e.g. if the allocation sequence was hidden in sequentially numbered, opaque, and sealed envelopes)
- Unclear risk of bias: study authors did not describe the method used to conceal the allocation, so intervention allocations may have been foreseen before, or during, enrolment
- High risk of bias: it is likely that investigators who assigned participants knew the allocation sequence
Blinding of participants and personnel
- Low risk of bias: either of the following: no blinding or incomplete blinding, but review authors judged that the outcome was unlikely to have been influenced by lack of blinding or blinding of participants and key study personnel ensured, and it was unlikely that the blinding could have been broken
- Unclear risk of bias: either of the following: insufficient information to permit judgement of 'low risk' or 'high risk'; or the trial did not address this outcome
- High risk of bias: either of the following: no blinding or incomplete blinding, and the outcome was likely to have been influenced by lack of blinding; or blinding of key study participants and personnel attempted, but likely that the blinding could have been broken, and the outcome was likely to have been influenced by lack of blinding
Blinding of outcome assessment
- Low risk of bias: either of the following: no blinding of outcome assessment, but review authors judged that the outcome measurement was not likely to be influenced by lack of blinding (we will consider self-reported questionnaires more prone to be affected by lack of blinded outcome assessor and hba1c less likely to be affected by lack of blinded outcome assessor) or blinding of outcome assessment ensured, and unlikely that the blinding could have been broken
- Unclear risk of bias: either of the following: insufficient information to permit judgement of 'low risk' or 'high risk'; or the trial did not address this outcome
- High risk of bias: either of the following: no blinding of outcome assessment, and the outcome measurement was likely to be influenced by lack of blinding; or blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome measurement was likely to be influenced by lack of blinding
Incomplete outcome data
- Low risk of bias: missing data were unlikely to make treatment effects depart from plausible values. The study used adequate methods, such as multiple imputation, to handle missing data or had <5% missing data.
- Unclear risk of bias: information was insufficient to assess whether missing data in combination with the method used to handle missing data were likely to induce bias on the results
- High risk of bias: results were likely to be biased due to missing data
Selective outcome reporting
- Low risk of bias: a protocol is published or a trial has been registered in a trial register (e.g. clinicaltrials.gov) before or at the time the trial is begun and the outcome called for in the protocol or trial registration is reported on.
- Unclear risk of bias: study authors did not report all pre‐defined outcomes fully, or it was unclear whether study authors recorded data on these outcomes
- High risk of bias: study authors did not report one or more pre‐defined outcomes
- Low risk of bias: the trial appeared free of other factors that could have put it at risk of bias
- Unclear risk of bias: the trial may or may not have been free of other factors that could have put it at risk of bias
- High risk of bias: other factors in the trial could have put it at risk of bias
We will judge a trial to be at low overall risk of bias if assessed as having low risk of bias in all of the above domains. We will judge a trial to be at high overall risk of bias if assessed as having unclear or high risk of bias in one or more of the above domains.
We will assess the domains ‘blinding of outcome assessment’, ‘incomplete outcome data’, and ‘selective outcome reporting’ for each outcome result. Thus, we can assess the bias risk for each outcome assessed in addition to each trial. Our primary conclusion will be based on the results of our primary outcome results with overall low risk of bias.
Differences between protocol and the review
Any deviations between the published protocol and the review will be reported in the ‘Differences between the protocol and the review’ section of the systematic review.
Measures of treatment effect
We will calculate risk ratios (RRs) with 95% confidence interval (CI) for dichotomous outcomes, as well as the Trial Sequential Analysis-adjusted CIs (see below).
We will calculate the mean differences (MDs) and consider calculating the standardized
mean difference (SMD) with 95% CI for continuous outcomes. We will also calculate trial sequential analysis-adjusted CIs (see below).
Dealing with missing data
We will, as the first option, contact all trial authors to obtain any relevant missing data (i.e., for data extraction and for assessment of risk of bias, as specified above). Second, we will investigate the effects of missing data in sensitivity analyses, see below.
We will not impute missing values for any outcomes in our primary analysis. In our sensitivity analyses (see paragraph below), we will impute data.
We will primarily analyse scores assessed at single time points. If only changes from baseline
scores are reported, we will analyse the results together with follow-up scores . If standard deviations (SDs) are not reported, we will calculate the SDs using trial data, if possible. We will not use intention-to-treat data if the original report did not contain such data. We will not impute missing values for any outcomes in our primary analysis. In our sensitivity analysis (see paragraph below) for continuous outcomes, we will impute data.
Assessment of heterogeneity
We will primarily investigate forest plots to visually assess any sign of heterogeneity. We will secondly assess the presence of statistical heterogeneity by chi2 test (threshold P < 0.10) and measure the quantities of heterogeneity by the I2 statistic [80, 81]. We will investigate possible heterogeneity through subgroup analyses. We may ultimately decide that a meta-analysis should be avoided .
Assessment of reporting bias
We will use a funnel plot to assess reporting bias if ten or more trials are included . We will visually inspect funnel plots to assess the risk of bias. We are aware of the limitations of a funnel plot (i.e., a funnel plot assesses bias due to small sample size). From this information, we assess possible reporting bias. For dichotomous outcomes, we will test asymmetry with the Harbord test  if I2 is less than 0.1 and with the Rücker test if I2 is more than 0.1. For continuous outcomes, we will use the regression asymmetry test  and the adjusted rank correlation .
Unit of analysis issues
We will only include randomised clinical trials. For trials using crossover design, only data from the first period will be included [44, 86]. We will include cluster-randomised trials after adjusting the original sample size of the trial to the effective sample size using the intracluster correlation coefficient from the ‘design effect’ . Therefore, there will not be any unit of analyses issues.