Interventi basati sulla teoria dell'autodeterminazione rispetto alle cure abituali nelle persone con diabete: una revisione sistematica con meta-analisi e analisi sequenziale degli studi.

Introduction

More than 425 million people are affected by diabetes worldwide, and of these, type 2 diabetes accounts for 90% [1]. People with type 1 and 2 diabetes have to manage complex and demanding self-management tasks in their everyday life. To adequately support these tasks, diabetes care management should consider the person’s age, cognitive abilities, literacy, social, cultural factors, diabetes complications and comorbidities, health priorities, and preferences of care [2]. One way to support patient engagement and long-term improvement in diabetes care may be the use of autonomy-supporting interventions facilitating shared decision-making and collaborative goal setting. Intrinsic motivation is a key element in autonomy interventions as it is associated to successfully achieving and sustaining treatment targets [3].

Existing self-management and behavioral interventions for diabetes vary in their content, and the long-term effectiveness is uncertain [4, 5]. Several interventions including educational, psychological, and health educational tools are based on different theoretical foundations, training, and clinical skills. Meta-analyses on interventions grounded in behavioral change theory have indicated that these interventions are more effective than interventions that are not theoretically grounded [6, 7].

Meta-analyses of psychological interventions addressing emotions, cognitions, and behaviors proved non-effective for reducing glycated hemoglobin (HbA1c) in people with type 1 [8] or type 2 diabetes [4]. Health educational tools targeted translation of person-centered care into practice, and enhance intrinsic motivation may lead to greater long-term behavior change than tools solely relying on external motivation [9].

The guided self-determination intervention developed by Zoffmann [10, 11] and interventions based on self-determination theory by Deci and Ryan [12] are autonomy-supportive methods. Guided self-determination is an empowerment-based method recognized as a life-skills approach [13], and empirically developed from grounded theory [10, 11, 14, 15], and formal theories including self-determination theory and life-skills theory.

The guided self-determination method is hypothesized to improve clinical outcomes through the following pathways [15, 16]: increased perceived autonomy, a higher frequency of self-monitored blood glucose, increased perceived competence in managing diabetes, decreased diabetes-related distress, and ultimately improved glycemic control [10, 11, 14, 15].

The self-determination theory is based on comprehensive empirical research. According to the self-determination theory, enhanced autonomous motivation and mental health are met when the three basic psychological needs, competence, autonomy, and relatedness, are satisfied [12, 17]. Self-determination theory proposes a continuum for the internalization of motivation, whereby people become more autonomous (or self-determined) to engage in behaviors over time. The pathways of mechanisms behind enhanced autonomy are built on a theoretical model [18], which argues that social-contextual events (e.g., feedback, communications, rewards) that conduce towards feelings of competence during action can enhance intrinsic motivation. Accordingly, tailored feedback and lack of demeaning evaluations are hypothesized to facilitate intrinsic motivation and thereby promote autonomy.

Previous reviews including randomized trials and non-randomized studies have been carried out [3, 6, 19]; however, all three reviews [19–21] included trials from diverse populations, primarily with healthy people and multiple experimental designs. Nevertheless, whether an improvement can be attributed to the intervention, it can only be established in randomized clinical trials. A detailed overview of the characteristics of the three reviews can be found on our protocol [22]. None of the reviews had a registered or published protocol, neither were they based on unrestricted searches, and bias of risk was only assessed in two reviews applying selected domains adopted from the Cochrane Handbook [23, 24]. None of the reviews controlled the risks of random errors using trial sequential analysis.

Nevertheless, the guided self-determination method (GSD) [10, 11, 14, 15] and self-determination theory (SDT) [12] aim to enhance autonomous motivation and behavior change and may thereby improve clinical outcomes. Due to the limitations of the existing reviews and the fact that guided self-determination intervention method had not yet been systematically reviewed, we find it justified to conduct a systematic review including trial sequential analysis (TSA) and Grading of Recommendations, Assessment, Development and Evaluations (GRADE) for assessing the potential of an effect, specifically targeting people with diabetes.

The objective was to investigate the benefits and harms of guided self-determination and self-determination theory interventions versus usual care in people with diabetes type 1 or type 2.

Materials and methods

We conducted this systematic review according to our protocol published prior to conducting the literature searches [22]. In short, we conducted this review following Cochrane guidelines [20] and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) 2020 statement (Supplementary file 2, PRISMA-P expanded checklist 2020) [25]. The analyses were performed using the Review Manager 5.3 [26] and the TSA 0.9.5.10 beta software [27]. Deviations from the published protocol were recorded and are elaborated in the section “Differences between the protocol and the systematic review”.

We included randomized clinical trials and cluster-randomized clinical trials (parallel, factorial, or crossover design) investigating interventions theoretically based on guided self-determination or self-determination theory conducted in any setting. Trials were defined as a guided self-determination trial if the reflection sheets specific for the method were applied. Trials were included irrespective of publication status, reported outcomes, publication date, publication type, and language [20]. Participants were adolescents (13 to 18 years) or adults with type 1 or type 2 diabetes. Control interventions were attention control [28], “no intervention”, wait list, or standard care as defined by trialists (e.g., standard healthcare provision).

We searched the 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. All databases were searched from their inception to the present. The latest literature searches were performed in April 2022 and inclusion ended in April 2022 [22]. (For a detailed search strategy for all electronic databases, see Supplementary file 1, search strategy.)

Two authors independently screened, extracted data, and performed risk-of-bias assessment of included trials using the Cochrane risk-of-bias tool. If data were missing or unclear, we contacted the trial author by email. Disagreements were solved by consulting a third author.

All potentially eligible trials identified in the literature searches were imported into the systematic review management program, Covidence [29]. Two authors (A. S. M.) and (J. L.) independently screened potentially eligible trials and subsequently extracted data from included trials. Disagreements were solved by consulting a third author (V. Z. or J. C. J.).

Trial data extracted included trial characteristics, participants characteristics, and diagnosis. Intervention group and control group characteristics, education and training of the interventionists, outcomes, funding, and conflict of interests (Table 1, characteristics of included trials). For a detailed list of trial data extracted, we refer to our protocol [22].Table 1Characteristics of included individually randomized and cluster-randomized clinical trialsAuthor (year)Clinicaltrials.gov IDDesignSetting, countryTotal (n)InterventionControl groupParticipantsType of diabetesMean ageMean duration of diabetes (years)DelivererOutcomesFollow-up time points (months)Brorson et al. (2019) [30]A cluster-randomized controlled trialOutpatient setting, Sweden71Guided self-determination (group based)Standardized pump start education, follow-up after 1 week, follow-up after 4–6 weeks and 4 months after startAdolescents (12–18 years)Type 115.1 years (12–17.99)NRa“Guided self-determination youth group leaders (educational background not described)Primary outcome: Hba1cSecondary outcomes: DISABKIDS, check your health, the Diabetes Family Conflict scale (DFCS), the Swedish Diabetes Empowerment Scale (Swe-DES 23), usage of continuous glucose monitoring system. Multiple daily injections6 and 12 monthsHusted et al. (2014) [31]A randomized clinical trialOutpatient setting, Denmark71Guided self-determination (revised for adolescents)Eight sessions scheduled equal to the intervention group across an 8- to 12-month period, with a duration of 30 to 45 min. They received HbA1c measurement, advice on glycemic control, and insulin administration. Parents participatedAdolescents (13–18 years) HbA1c > 64 mmol/molType 115 years5.7 yearsTwo pediatric physicians, five pediatric diabetes nurses, and two dieticians (HCPs) provided the GSD-Y interventionPerceived competence for diabetes management (PCD), Health Care Climate Questionnaire (HCCQ) assessing the degree to which patients believed their HCPs to be autonomy supportive versus Treatment Self-Regulation Questionnaire (TSRQ) assessing the motivation for diabetes management and the degree to which behaviors tended to be self-determined. Problem Areas in Diabetes (PAID) assessing diabetes-related distress including a wide range of feelings related to living with diabetes and the Perception of Parents Scale (POPS)Intervention group 215 ± 59 days versus control group 246 ± 83 daysMohn et al. (2017) [32]ClinicalTrials. gov NCT 01317459A randomized clinical trialOutpatient setting, Norway178 (62% women)Guided self-determination (group based)Usual careAdults (> 18 years old), HbA1c > 64 mmol/molType 118–55 years, mean age 36.7 ± 10.719 years, range (1–46)Diabetes specialist nurses trained in the guided self-determination methodHbA1cSelf-monitored blood glucose (SMBG), PAID; DDS, PCDS, Rosenberg Self-Esteem Scale (RSES), WHO-5, HCCQ, TSRQ, treatment Relative Autonomy Index (RAI)9 monthsZoffmann et al. (2006) [15]A randomized clinical trialOutpatient setting, Denmark50Guided self-determination (group based)Delayed group trainingAdults (> 18 years old), HbA1c > 64 mmol/molType 136.8 ± 1.7 (exp.)35.7 ± 2.1 (cont.)Age at onset of diabetes18.2 ± 2 (exp.)13 ± 2.2 (cont.)Nurses trained in the guided self-determination methodHealth Care Climate Questionnaire (HCCQ)Treatment Self-Regulation Questionnaire (TSRQ)Perceived Competence in Diabetes Scale (PCD)Problem Areas in Diabetes (PAID)12 monthsZoffmann et al. (2015) [16, 33]Trial registration: ISRCTN70566290A randomized clinical trialOutpatient setting, Denmark200, balanced 2:1Guided self-determination (group based or individual)18-month delayed GSD interventionDuring the control period, participants received care as usual and met for sessions with nurse, doctor, or dieticians every 3–4 monthsAdults (18 to 35 years old), HbA1c ≥ 64 mmol/molType 125.713.7Seven diabetes nurse specialists with 7–25 years of experience within the field of diabetes. They were GSD certified passing a test after 40 h of systematized training in the theoretical background and practical use of GSD, and all of them were supervised by V. Z.Primary outcome: HbA1cSecondary outcomes: PAID, WHO-5, Rosenberg SES, Perceived Competence in Diabetes (PCD, Treatment Self-regulation Questionnaire (TSRQ), SMBG, Autonomy IndexHbA1c: 3, 6, 9, 12, 15, 18 monthsSecondary outcomes 9 and 18 monthsJuul et al. (2014) [34]ClinicalTrials.gov identifier: NCT01187069A cluster-randomized trialGeneral practice, Denmark4035 (56.5% men)Self-determination theory (individual)Usual practice at their general practitionerNRType 1 (15% and type 2 85%)60.4 ± 8.6 years8 yearsA total of 34 nurses from 19 of 20 intervention practices had received the core intervention. 22 nurses from the 13 practices had completed the full coursePrimary outcomes: HbA1c, total cholesterol, PAID18 months (average)Mathiesen (2019) [35]A randomized clinical feasibility trialOutpatient clinic setting, Denmark20Guided self-determination (individual)Usual careAdults (> 18 years old), HbA1c > 53 mmol/molType 2 diabetes58 years (mean)NRThe guided self-determination intervention was provided by the PhD student certified in the methodPrimary outcomes: HbA1c, diabetes distress, depressive symptoms, physical activity, hip/waist ratio, eating habits4-month follow-upNansel et al. (2015) [36]ClinicalTrials.gov identifier: NCT00999375A randomized clinical trialOutpatient clinic setting, USA136 (48.5% male)Self-determination theory (Individual)Received an equal amount of session and frequency of contacts with research staff and an equal frequency of 3-day masked CGM. Participants in the control group received no additional dietary advice beyond that provided as part of standard type 1 diabetes care. Scales, measuring cops, and spoons were provided to both groupsAdolescents 8–16.9 years old), HbA1c ≥ 6.5%, and ≤ 10%Type 1NR6.0 yearsResearch assistants trained in pediatric T1 diabetes, intervention procedures, and motivational interviewing. Study investigators provided feedback to audiotaped role-play practice sessions prior to intervention delivery and on a random sample of audiotaped intervention sessionsPrimary outcomes: diet quality, measured by the Healthy Eating Index 2005 (HEI2005), the whole plant food density (WPFD), measure and Hba1c15 and 18 monthsVanroy et al. (2017) [23]Clinical Trials.gov NCT 02064335A randomized controlled pilot trialBelgium48(27 men and 21 women)Self-determination theory (individual)Similar intervention 6 months delayed. The participants in the control group were told that during the waiting period, their health measurements were analyzed ≥ 18 years oldType 2 diabetesExperimental group: 65 ± 8Control group: 59 ± 8NRAn intake and an outtake session with a professional PA coach, who held the degree of Master in Physical Education and Movement Sciences and who was familiarized with SDT and motivational interviewingHba1c and measurement of physical activity (armband SenseWear). A minimum of 3 weekdays and 1 weekend day was considered a valid measurement week1–5 months and 6 monthsGlasgow et al. (2005) [24]A randomized clinical trialOutpatient clinic setting, USA886Self-determination theory (individual)Participants completed a touch screen computer assessment procedure involving the Provider Recognition Program measures as well as a general health risk appraisal items (e.g., use of seatbelts, cancer screening, etc.). They had the same number of visits as intervention patients and received a printout but one that focused on general health tasks and risk reduction that did not address the DPP ≥ 25 years oldType 2 diabetesIntervention 62 ± 1.4Control 64 ± 1.3NRNRPrimary outcomes: self-management goalsetting medical nutrition therapy, dilated eye examination, foot examinationSecondary outcomes: PAID 2, PHQ-9 depression scale, lipids and HbA1c, blood pressure, microalbuminuria12 monthsYun et al. (2020) [37]ChiCTR1900024354A cluster-randomized controlled trialGeneral practitioner, China364Self-determination theory (group based or individual)2 control group interventions 1) Usual care group offering regular public health management services 2) Social support group (SSG) providing 3-month social support intervention based on problem-solving principles ≥ 18 years oldType 2 diabetes65.14 ± 7.23 years oldNRCommunity doctorsPrimary outcome: HbA1c3 and 6 monthsaNot reported

Characteristics of included individually randomized and cluster-randomized clinical trials

Secondary outcomes: DISABKIDS, check your health, the Diabetes Family Conflict scale (DFCS), the Swedish Diabetes Empowerment Scale (Swe-DES 23), usage of continuous glucose monitoring system. Multiple daily injections

Self-monitored blood glucose (SMBG), PAID; DDS, PCDS, Rosenberg Self-Esteem Scale (RSES), WHO-5, HCCQ, TSRQ, treatment Relative Autonomy Index (RAI)

Treatment Self-Regulation Questionnaire (TSRQ)

Perceived Competence in Diabetes Scale (PCD)

During the control period, participants received care as usual and met for sessions with nurse, doctor, or dieticians every 3–4 months

Secondary outcomes: PAID, WHO-5, Rosenberg SES, Perceived Competence in Diabetes (PCD, Treatment Self-regulation Questionnaire (TSRQ), SMBG, Autonomy Index

ClinicalTrials.gov identifier: NCT01187069

ClinicalTrials.gov identifier: NCT00999375

Primary outcomes: self-management goalsetting medical nutrition therapy, dilated eye examination, foot examination

Secondary outcomes: PAID 2, PHQ-9 depression scale, lipids and HbA1c, blood pressure, microalbuminuria

1) Usual care group offering regular public health management services

2) Social support group (SSG) providing 3-month social support intervention based on problem-solving principles

We assessed three primary outcomes: quality of life, all-cause mortality, and serious adverse events. Our secondary outcomes were diabetes distress, depressive symptoms, and adverse events considered non-serious. We also assessed two explorative outcomes: HbA1c and motivation (increased autonomy, decreased control, and decreased amotivation (discouraged lacking faith in own actions)). All outcomes were assessed at end of intervention (our primary follow-up time point) and at maximum follow-up. We assessed a potential effect in both random-effects and fixed-effect meta-analyses. We predefined 10 subgroup analyses for our three primary outcomes [22].

We included randomized clinical trials only [22]. For trials using crossover design, we had planned to only include data from the first period [20, 38]. Cluster-randomized trials were included after adjusting the original sample size of the trial to the effective sample size using the intracluster correlation coefficient from the “design effect” [20]. Meta-analyses including both individual and cluster-randomized trials were conducted as subgroup analyses (Supplementary file 4, results).

Risk of bias in included trials was assessed based on the domains described below [18, 20, 39–47]. These domains are as follows: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome reporting, and other bias.

All domains were considered at “low risk of bias”, “unclear risk of bias”, or “high risk of bias”. Detailed criteria for risk-of-bias assessment are outlined in our protocol [22]. This assessment was done in pairs by two independent review authors (A. S. M. and J. L.), separately for each outcome and comparison and ultimately considered in relation to overall reliability of the evidence. A trial was judged to be at low overall risk of bias if assessed as having low risk of bias in all of the above domains. A trial was judged 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 assessed the domains “blinding of outcome assessment”, “incomplete outcome data”, and “selective outcome reporting” for each outcome result. Thus, we assessed the bias risk for each outcome assessed in addition to each trial.

All meta-analyses and subgroup analyses were conducted using Review Manager 5.4 [26]. TSA was used to control random errors [48]. To control the risk of systematic errors, we assessed the risk of bias of all included trials. The thresholds for statistical significance were adjusted according to our three primary, three secondary, and two explorative outcomes as suggested by Jakobsen et al. [48]. Thus, we considered a p-value of ≤ 0.014 as the threshold for statistical significance.

For dichotomous outcomes, we calculated risk ratios (RRs) with 95% confidence interval (CI), as well as the TSA-adjusted CIs. We calculated the mean differences (MDs) with 95% CI for continuous outcomes. It was not possible to calculate the standardized mean difference (SMD) due to lack of data.

We primarily investigated forest plots to visually assess signs of heterogeneity. Secondly, we assessed the presence of statistical heterogeneity by chi-square test (threshold P < 0.10) and measured the quantities of heterogeneity by the I2 statistic [21, 49]. We investigated possible heterogeneity through subgroup analyses. We found the rationale for conducting meta-analyses was justified [20].

We used intention to treat data if such data were available. As the first option, we contacted trial authors to obtain any relevant missing data (i.e., for data extraction and for assessment of risk of bias, as specified above). Secondly, we investigated the effects of missing data in sensitivity analyses (Supplementary file 3). We did not impute missing values for any outcomes in our primary analysis.

We primarily analyzed continuous outcome scores assessed at single time points. If changes from baseline scores were reported only, we analyzed the results together with the follow-up scores [20]. If standard deviations (SDs) were not reported, we calculated the SDs using trial data, if possible.

We conducted the meta-analyses according to the recommendations stated in the Cochrane Handbook for Systematic Reviews of Interventions [20], Keus et al. [50], and the eight-step assessment suggested by Jakobsen et al. [48]. The intervention effects were assessed with both random-effects meta-analyses [51] and fixed-effect meta-analyses [52]. We primarily reported the most conservative result (highest p-value) and considered the less conservative result as a sensitivity analysis [48]. We assessed a total of three primary, three secondary outcomes, and two explorative outcomes and therefore considered a p-value of 0.014 or less as the threshold for statistical significance [48]. For further details, we refer to our protocol [22].

We also controlled the risks of type 1 errors and type 2 errors and thereby the risk of potential false-positive findings of meta-analyses [53] using TSA 0.9.5.10 beta on all outcomes. We performed trial sequential analysis on all outcomes, in order to calculate the required information size (that is, the number of participants needed in a meta-analysis to detect or reject a certain intervention effect) and the cumulative Z curve’s breach of relevant trial sequential monitoring boundaries. For dichotomous outcomes, we planned to estimate the required information size based on the observed proportion of patients with an outcome in the control group (the cumulative proportion of patients with an event in the control groups relative to all patients in the control groups), a relative risk reduction of 20%, an alpha of 1.4% for all our outcomes, a beta of 10%, and the observed diversity as suggested by the trials in the meta-analysis. For the continuous outcomes, we used the observed SD in the trial sequential analysis, a mean difference of the observed SD/2, an alpha of 1.4% for all outcomes, a beta of 10%, and the observed diversity as suggested by the trials in the meta-analysis. A more detailed description of the TSA applied in this review can be found in the protocol [22] and in the TSA manual [54] or at http://www.ctu.dk/tsa/.

The following ten exploratory subgroup analyses were planned on the primary outcomes, quality of life, mortality, and serious adverse events [22]:Type of diabetes (trials including participants with type 1 compared to trials including participants with type 2)Socioeconomic status (trials including participants with low socioeconomic status compared to trials including participants with high socioeconomic status)Number of comorbiditiesMen compared to womenAdolescent (13 to 18 years) compared to adults (> 18 years)Self-determination theory compared to trials investigating guided self-determination methodTrials with an experimental intervention above and below the mean difference in intervention lengthIndividual interventions compared to trials investigating group interventionsType of control intervention (no intervention, standard care, or placebo attention control)Trials with overall high risk of bias compared to trials with overall low risk of bias [22]

Type of diabetes (trials including participants with type 1 compared to trials including participants with type 2)

Socioeconomic status (trials including participants with low socioeconomic status compared to trials including participants with high socioeconomic status)

Adolescent (13 to 18 years) compared to adults (> 18 years)

Self-determination theory compared to trials investigating guided self-determination method

Trials with an experimental intervention above and below the mean difference in intervention length

Individual interventions compared to trials investigating group interventions

Type of control intervention (no intervention, standard care, or placebo attention control)

Trials with overall high risk of bias compared to trials with overall low risk of bias [22]

To assess the potential impact of missing data, we performed the “best-worst-case” scenario and “worst-best-case” scenario analyses on both the primary and secondary outcomes (Supplementary file 3). For further details, we refer to our protocol [22].

We were not able to assess reporting bias as planned, as none of our outcomes included more than 10 trials.

The certainty of the evidence was assessed by GRADE [20, 55, 56] using the five GRADE considerations (risk of bias, consistency, imprecision, indirectness, and publication bias) and the software GRADEpro GDT [56].

The certainty of the evidence was assessed independently by two authors (A. S. M. and J. L.) on the primary outcomes (quality of life, mortality, serious adverse events), the secondary outcomes (diabetes distress, depressive symptoms, and nonserious adverse events), and the explorative outcome (HbA1c and motivation).

Results

The initial searches yielded 5578 references of which 958 duplicates were found. Screening of title and abstracts resulted in exclusion of 4551 references. Thus, 69 references were full text screened of which 16 references representing 11 unique trials involving initial recruitment of 6059 participants were included. Trial selection and reasons for exclusion are displayed in the PRISMA flowchart (Fig. 1) [57]. Sample sizes ranged from 20 to 4034 participants [34, 35]. Five trials provided a self-determination theory-based intervention [23, 24, 34, 36, 37], and six provided a guided self-determination intervention [15, 32, 33, 35] or a GSD version revised for adolescents [30, 58] (Table 1, Characteristics of included trials). Five trials originated from Denmark [15, 33–35, 58], two originated from the USA [24, 36], and one each from Sweden [30], Norway [32], China [37], and Belgium [23]. We included four cluster-randomized trials [24, 30, 34, 37] and adjusted the original sample size of the trial to the effective sample size using the intracluster correlation coefficient from the “design effect” [20]. Brorson et al. [30] did not provide the number of clusters, which meant that we were unable to calculate the effective sample size and include data from this trial. We contacted seven trial authors by email to specify any missing data, but only one provided the requested data. We contacted three authors who had ongoing trials registered in trial registers; none of them replied.Fig. 1PRISMA flowchart

All included trials were adjudicated at high risk of bias on minimum 2 domains. For “risk of bias” for the individual outcomes, we refer to the “Primary outcomes” section below. For risk of bias on the individual trials, the risk of bias is displayed in the meta-analyses.

Three trials [33, 35, 58] including 225 participants assessed quality of life with the WHO-5 questionnaire at the end of intervention, while Brorson et al. [30] reported quality of life with the “Check your Health” questionnaire without providing data suitable for inclusion in the meta-analysis. Brorson et al. [30] did not provide the number of clusters, which meant that we were unable to calculate the effective sample size and include data from this trial. The WHO-5 ranges from 0 to 25; lower scores indicate poorer quality of life. The meta-analysis of the three trials [33, 35, 58] showed no difference between the intervention and control group on quality of life (MD 0.00 points, 95% CI −4.85, 4.86, p = 1.0, I2 = 0%; 225 participants, 3 trials, TSA-adjusted CI −11.83, 11.83). TSA showed that we had enough information to reject that self-determination theory-based intervention increased quality of life with 9 points (the diversity-adjusted required information size (DARIS) 186 participants) (Fig. 2, meta-analysis and TSA of quality of life, end of intervention). The “best-worst case” and “worst-best case” scenarios showed that missing data alone had the potential to bias the results (Supplementary material 3, sensitivity analyses). This result was at very low certainty due to serious risk of bias, serious inconsistency, and serious indirectness (Table 2, Summary of findings).Fig. 2Meta-analysis and trial sequential analysis (TSA) for quality of life, end of intervention for self-determination theory vs. control. a Meta-analysis. b TSA. The diversity-adjusted required information size (DARIS) was calculated according to a mean difference of 9 points, which is half of the observed SD of 18, alpha of 1.4%, beta of 20% (80% power), and diversity 0%. The DARIS was 186 participants. The cumulative Z-curve (blue line) breaches the boundary of futility (dotted outward sloping red lines) and the DARIS. The green dotted lines show naive conventional boundaries (alpha 5%)Table 2Summary of findings table with GRADE evaluation for self-determination interventions compared with usual care (follow-up timepoint: end of intervention)Certainty assessmentNo. of patientsEffectCertaintyImportanceNo. of studiesStudy designRisk of biasInconsistencyIndirectnessImprecisionOther considerationsSelf-determination theoryUsual careRelative (95% CI)Quality of life3RCTsSeriousaSeriousbSeriouscNot seriousNone12897MD 0 (−4.85, 4.86)⨁◯◯◯Very lowCriticalAll-course mortality1Cluster RCTsVery seriousdNot seriousSeriouseSeriousfNone20052021RR 1.13 (0.73, 1.74)⨁◯◯◯Very lowCriticalSAEs0---------CriticalDiabetes distress3RCTsSeriousgSerioushNot seriousNot seriousNone12896MD −0.10 (−6.17, 5.97)⨁⨁◯◯LowImportantDepressive symptoms2RCTsVery seriousiSeriousjNot seriousSeriouskNone1010MD −3.0 (−3.75, 9.74)⨁◯◯◯Very lowImportantAdverse events0----------ImportantRCTs randomized clinical trials, SAEs serious adverse events, CI confidence interval, MD mean differenceExplanations:aThe three trials reporting on quality of life at the end of intervention were all rated as high risk of bias on the domains: “blinded outcome assessment” and “incomplete outcome data”bInconsistency regarding the direction of effect of included trialscDowngraded due to indirectness caused by Mathiesen et al. including elderly persons with type 2 diabetes and Zoffmann et al. (2015) [16, 33] including young people with type 1 diabetes, and Husted et al. include adolescents. The three trials also apply slightly diverse versions of the guided self-determination interventiondThis outcome was rated as high risk of bias on the domain “blinded outcome assessor” as the first, and the last author analyzed the data in the trial. On the domain “incomplete outcome data,” it was unclear whether there where participants lost to follow-up on this domaineThe nurses were trained in advanced communication techniques, but the reflection sheets in the guided self-determination method were not provided to the patientsfTSA showed lack of data because only 3.99% of optimal information size had been reachedgAll trials have a minimum of three high risk-of-bias domainshDowngraded due to heterogeneity of the included populations (type 1 diabetes) in the trials of Zoffmann (2015) and Husted et al. (2014) [31] and type 2 diabetes in the trial of Mathiesen et al. (2019) [59]iDowngraded due to “high risk of bias on blinded outcome assessor,” “incomplete outcome data,” “and selective reporting” on this outcome (only data from Mathiesen (2019) [35])jDowngraded due to heterogeneity of the provided interventionskWide confidence intervals in the trial of Mathiesen et al. (2019) [59]

Meta-analysis and trial sequential analysis (TSA) for quality of life, end of intervention for self-determination theory vs. control. a Meta-analysis. b TSA. The diversity-adjusted required information size (DARIS) was calculated according to a mean difference of 9 points, which is half of the observed SD of 18, alpha of 1.4%, beta of 20% (80% power), and diversity 0%. The DARIS was 186 participants. The cumulative Z-curve (blue line) breaches the boundary of futility (dotted outward sloping red lines) and the DARIS. The green dotted lines show naive conventional boundaries (alpha 5%)

Summary of findings table with GRADE evaluation for self-determination interventions compared with usual care (follow-up timepoint: end of intervention)

RCTs randomized clinical trials, SAEs serious adverse events, CI confidence interval, MD mean difference

aThe three trials reporting on quality of life at the end of intervention were all rated as high risk of bias on the domains: “blinded outcome assessment” and “incomplete outcome data”

bInconsistency regarding the direction of effect of included trials

cDowngraded due to indirectness caused by Mathiesen et al. including elderly persons with type 2 diabetes and Zoffmann et al. (2015) [16, 33] including young people with type 1 diabetes, and Husted et al. include adolescents. The three trials also apply slightly diverse versions of the guided self-determination intervention

dThis outcome was rated as high risk of bias on the domain “blinded outcome assessor” as the first, and the last author analyzed the data in the trial. On the domain “incomplete outcome data,” it was unclear whether there where participants lost to follow-up on this domain

eThe nurses were trained in advanced communication techniques, but the reflection sheets in the guided self-determination method were not provided to the patients

fTSA showed lack of data because only 3.99% of optimal information size had been reached

gAll trials have a minimum of three high risk-of-bias domains

hDowngraded due to heterogeneity of the included populations (type 1 diabetes) in the trials of Zoffmann (2015) and Husted et al. (2014) [31] and type 2 diabetes in the trial of Mathiesen et al. (2019) [59]

iDowngraded due to “high risk of bias on blinded outcome assessor,” “incomplete outcome data,” “and selective reporting” on this outcome (only data from Mathiesen (2019) [35])

jDowngraded due to heterogeneity of the provided interventions

kWide confidence intervals in the trial of Mathiesen et al. (2019) [59]

Three trials including 335 participants assessed quality of life assessed with the WHO-5 scale at longest follow-up [32, 33, 58], while Brorson et al. [30] reported quality of life with the “Check your Health” questionnaire and did not provide data suitable for inclusion in the meta-analysis. Brorson et al. [30] did not provide the number of clusters, which meant that we were unable to calculate the effective sample size and include data from this trial. The meta-analysis of the three trials showed no difference between the intervention and the control group on quality of life (MD 2.82 points, 95% CI −2.74, 8.38, p = 0.32, I2 = 33%; 335 participants, 3 trials, TSA-adjusted CI −5.80, 11.43) (Supplementary file 4, results). TSA showed that we had enough information to reject that self-determination theory-based intervention increased quality of life with 10 points (DARIS 294 participants). The “best-worst case” and “worst-best case” scenarios showed that missing data alone had the potential to bias the results. This outcome result was overall assessed at high risk of bias as all three trials were judged to be of “high risk of bias” on the outcome domains “blinded outcome assessment”, and “incomplete outcome data” (Supplementary material 3, sensitivity analyses). The evidence was rated at very low certainty due to serious risk of bias, serious inconsistency, and serious indirectness.

One cluster-randomized trial assessed mortality at longest follow-up [34]. The trial showed no difference between the intervention and the control group on all-cause mortality (RR 1.13, 95% CI 0.73; 1.74, p = 0.59; 1529 participants (design-adjusted participant number), 1 trial). TSA could not be shown due to too little information (only 3.99% of DARIS) (Supplementary file 4, results). The result was overall assessed at high risk of bias on the domain “blinded outcome assessor” as the first and the last author analyzed the data in the trial. On the domain “incomplete outcome data”, it was unclear whether there were participants lost to follow-up. Regarding the domain “selective outcome reporting”, it was judged at low risk of bias due to the register-based design. The evidence was rated at very low certainty due to very serious risk of bias, serious indirectness, and serious imprecision (Table 2, Summary of findings).

None of the included trials reported serious adverse events as an outcome. Mohn et al. [32] reported that one participant dropped out in the intervention group due to referral to psychiatric care, and one dropped out from the control group due to “critical illness”. Brorson et al. [30] reported that one participant dropped out in the control group due to extremely high HbA1c values (113 mmol/mol) at 6-month follow-up [30]. This outcome result was overall assessed at high risk of bias as the two trials were judged to be of “high risk of bias” or “unclear” on the outcome domains “blinded outcome assessment”, and “incomplete outcome data”. Data was not suitable for meta-analysis (Supplementary file 5, serious adverse events and adverse events).

Three individually randomized trials [31, 33, 35] including 224 participants assessed diabetes distress with the PAID score at the end of the intervention. The PAID score ranges from 0 to 100; lower scores indicate less diabetes distress. The meta-analysis showed no difference between the intervention and the control group on diabetes distress (MD −2.59 points, −8.16, 2.98, p = 0.36, I2 = 0%; 224 participants, 3 trials). One cluster-randomized trial [24] reported a MD 1.82 points, 95% CI 1.69, 1.95, p < 0.00001, 467 participants (design effect-adjusted participant number), and 1 trial, favoring the control group (Supplementary file 4, results). The cluster-randomized trial of Glasgow et al. [24] contributed with more than 99% weight in the meta-analyses on diabetes distress. For this trial, we identified several methodological issues. First, the trial was not adequately registered in a trial register, nor was a protocol published. As such, it was not clear whether the outcomes were predefined. Furthermore, randomization, blinding, and attrition were inadequately described [24]. The TSA figure was not shown as number of included participants exceeded 100% of the DARIS. The “best-worst case” and “worst-best case” scenarios showed that incomplete data alone had the potential to influence the results (Supplementary file 3, sensitivity analyses). This result was rated at low certainty due to high risk of bias and serious inconsistency (Table 2, Summary of findings).

Four trials [15, 31–33] including 384 participants assessed diabetes distress at longest follow-up. The meta-analysis showed no difference between the intervention and control group (MD −5.31 points, 95% CI −11.12, 0.50, p = 0.07, I = 48%, 384 participants, four trials, TSA-adjusted CI −14.34, 3.72) (Supplementary file 4, results). The relatively large heterogeneity was explained by the trial of Husted et al. [31] reporting that the guided self-determination adjusted for adolescents and increased diabetes distress in young people (mean age 15 years, range 13–18 years) and relatively short duration of diabetes (mean 5.7 years). Removing the trial of Husted et al. from the forest plot reduced the heterogeneity to 0%. TSA showed that we had enough information to reject that self-determination theory-based intervention decreased diabetes distress with 10 points (DARIS 367 participants) (Figure 3, meta-analysis and TSA of diabetes distress, longest follow-up). The “best-worst case” and “worst-best case” scenarios showed that missing data alone had the potential to bias the results (supplementary material 3, sensitivity analyses). The outcome result was overall assessed at high risk of bias as all three trials were judged to be at “high risk of bias” on the domains “blinded outcome assessment” and “incomplete outcome data”. The evidence was rated at low certainty due to serious risk of bias and serious inconsistency.Fig. 3Meta-analysis and trial sequential analysis (TSA) for diabetes distress, longest follow-up for self-determination theory vs. control. a Meta-analysis. b TSA. The diversity-adjusted required information size (DARIS) was calculated according to a mean difference of 10 points, which is half of the observed SD of 20, alpha of 1.4%, a beta of 20% (80% power), and diversity 50%. The DARIS was 367 participants. The cumulative Z-curve (blue line) breaches the boundary of futility (dotted outward sloping red lines) and the DARIS. The green dotted lines show naive conventional boundaries (alpha 5%)

Meta-analysis and trial sequential analysis (TSA) for diabetes distress, longest follow-up for self-determination theory vs. control. a Meta-analysis. b TSA. The diversity-adjusted required information size (DARIS) was calculated according to a mean difference of 10 points, which is half of the observed SD of 20, alpha of 1.4%, a beta of 20% (80% power), and diversity 50%. The DARIS was 367 participants. The cumulative Z-curve (blue line) breaches the boundary of futility (dotted outward sloping red lines) and the DARIS. The green dotted lines show naive conventional boundaries (alpha 5%)

Two trials [24, 35] assessed depressive symptoms at the end of intervention. Glasgow et al. [24] reported depressive symptoms measured by the Patient Health Questionnaire (PHQ-9) but in percent, and the authors did not reply to our request for additional data. Mathiesen et al. (2019) measured depressive symptoms by the Hospital Anxiety and Depression Score (HADS) at the end of intervention and reported no difference between the intervention and the control group (MD −0.10 points, 95% CI −6.17, 5.97, p = 0.97) in a high risk-of-bias small feasibility trial (n = 20) [35]. This outcome result was overall assessed as a high risk of bias, and the evidence was rated at very low certainty due to very serious risk of bias, serious inconsistency, and serious imprecision (Table 2, Summary of findings). No trials reported on depressive symptoms at longest follow-up.

Mathiesen et al. (2019) reported that one participant in the intervention group experienced relapse in her paranoid schizophrenia during the intervention [35]. Data was not suitable for meta-analyses (Supplementary file 5, serious adverse events and adverse events). The outcome result was overall assessed at high risk of bias as both trials were judged to be of unclear or “high risk of bias” on the domains “blinded outcome assessment” and “incomplete outcome data” and high risk of bias on “selective reporting”. No adverse events were reported at longest follow-up.

Four trials including 401 participants assessed HbA1c at the end of the intervention [31, 33, 35, 37]. Meta-analysis of the individually randomized trials showed no difference between the intervention and the control group (MD −0.07 mmol/mol, 95% CI −3.60, 3.46, p = 0.97, I2 = 0%; 275 participants, 3 trials, TSA-adjusted CI −5.62, 1.93). One cluster-randomized trial [37] reported an effect (MD −4.63 mmol/mol, 95% CI −7.49, −1.77, p = 0.001, 126 participants (design effect-adjusted participant number), 1 trial) (Supplementary file 4, results), favoring the intervention group. TSA of the individually randomized trials and the cluster-randomized trial showed that we had enough information to reject that self-determination theory-based intervention decreased HbA1c with 7 mmol/mol (DARIS 324 participants). This outcome result was overall assessed as a high risk of bias, and the evidence was rated at low certainty due to very serious risk of bias and serious inconsistency.

Five trials [30, 32–34, 58] including 1913 participants assessed HbA1c at longest follow-up. Meta-analysis of the three individually randomized trials [32, 33, 58] showed no effect (MD −3.19 mmol/mol, 95% CI −6.22, −0.16, p = 0.04, I2 = 0%; 384 participants, 3 trials, TSA-adjusted CI −12.31, 8.90). One cluster-randomized trial reported no effect (MD −0.40 mmol/mol, 95% CI −2.20, 1.40, p = 0.66, 1529 participants (design-adjusted participant number), 1 trial) (Supplementary file 4, results) [34]. Brorson et al. [30] reported on Hba1c, but did not provide the number of clusters; thus, we were unable to adjust for the design effect. TSA of the individually randomized trials and the cluster-randomized trial showed that we had enough information to reject that self-determination theory-based intervention decreased HbA1c with 7 mmol/mol (DARIS 748 participants). This outcome result was overall assessed at high risk of bias as all three trials were judged to be at “high risk of bias” on the outcome domains “blinded outcome assessment”, and two trials [32, 58] had high risk of bias on the domain “incomplete outcome data”. The evidence was rated at low certainty due to very serious risk of bias and serious inconsistency.

Two trials including 207 participants assessed autonomy at the end of intervention [33, 58]. The meta-analysis of the two trials showed a MD 0.42 points, 95% CI 0.16, 0.67, p = 0.001, I2 = 0%; 207 participants, 2 trials, TSA-adjusted CI −0.99, 0.14 (Supplementary file 4, results) favoring the intervention group. The treatment self-regulation score (TSRS) (autonomy) ranges from 1 to 7; lower scores indicate less autonomous motivation. TSA showed that we had enough information to show that self-determination theory-based intervention increased autonomy with 0.45 points (DARIS 186 participants). This outcome result was overall assessed as a high risk of bias, and the evidence was rated at very low certainty due to very serious risk of bias.

Five trials including 1248 participants assessed autonomy at longest follow-up [15, 31–34]. The meta-analysis of the four individually randomized trials [15, 32, 33, 58] showed a difference between the intervention and the control group (MD of 0.30 points, 95% CI 0.11, 0.48, p = 0.002, I2 = 0%; 384 participants, 4 trials, TSA-adjusted CI −0.01, 0.45) (Supplementary file 4, results) favoring the intervention group. One cluster-randomized trial (design-adjusted participant number) reported no effect. TSA of the individually randomized trials and the cluster-randomized trial showed that we had enough information to reject that self-determination theory-based intervention increased autonomy with 0.45 points (DARIS 557 participants).

This outcome result was overall assessed as a high risk of bias as all four included trials were judged to be of “high risk of bias” on the outcome domains “blinded outcome assessment” and “incomplete outcome data”. The evidence was rated at low certainty due to serious risk of bias and serious indirectness.

Two trials including 207 participants [33, 58] assessed motivation (control) at the end of intervention. The meta-analyses of the two trials showed no difference between the intervention and the control group (0.06 points, 95% CI −0.26, 0.39, p = 0.71, I2 = 0%; 207 participants, 2 trials, TSA-adjusted CI −0.71, 0.83) (Supplementary file 4, results). The treatment self-regulation score (TSRS) (control) ranges from 1 to 7; lower scores indicate less controlled motivation. TSA showed that we had enough information to reject that self-determination theory-based intervention increased motivation (control) with 0.6 points (DARIS 175 participants). This outcome result was overall assessed as at high risk of bias, and the evidence was rated at low certainty due to very serious risk of bias and serious inconsistency.

Four individually randomized trials [15, 32, 33, 58] including 384 participants assessed motivation (control) at longest follow-up. Meta-analysis of the four trials showed no difference between the intervention and the control group (MD 0.05 points, 95% CI −0.19, 0.30, p = 0.67, I2 = 0%; 384 participants, 4 trials, TSA-adjusted CI −0.92, 1.07) (Supplementary file 4, results). One cluster-randomized trial (design-adjusted participant number) reported no effect. TSA showed that we had enough information to reject that self-determination theory-based intervention decreased motivation (control) with 0.6 points (DARIS 575 participants) (Supplementary file 4, results). This outcome result was overall assessed as at high risk of bias as all four included trials were judged to be of “high risk of bias” on the outcome domains “blinded outcome assessment” and “incomplete outcome data”. The evidence was rated at low certainty due to serious risk of bias and serious indirectness.

Two trials including 207 participants assessed motivation (amotivation) at the end of intervention. Meta-analysis of the two trials showed a difference between the intervention and the control group (MD −0.37 points, 95% CI −0.67, −0.07, p = 0.02, I2 = 0%; 207 participants, 2 trials, TSA-adjusted CI: −1.08, 0.34) favoring the intervention group (Supplementary file 4, results). The treatment self-regulation score (TSRS) (amotivation) ranges from 1 to 7; lower scores indicate less amotivation. TSA showed that we had enough information to reject that self-determination theory-based intervention decreased amotivation (DARIS 176 participants). This outcome result was overall assessed as at high risk of bias, and the evidence was rated at low certainty due to very serious risk of bias.

Three trials [15, 31, 33] including 258 participants assessed amotivation at longest follow-up. Meta-analysis of the three trials showed a difference between the intervention and the control group (MD −0.53 points, 95% CI −0.62, −0.45, p < 0.00001, I2 = 27%; 253 participants, 3 trials, TSA-adjusted CI: −0.73, −0.32) favoring the intervention group (Supplementary file 4, results). TSA showed that we had enough information to show that self-determination theory-based intervention decreased amotivation with 0.2 points (DARIS 207 participants). This outcome result was overall assessed at high risk of bias as all three included trials were judged to be of “high risk of bias” on the outcome domains “blinded outcome assessment” and “incomplete outcome data”. The evidence was rated as at low certainty due to serious risk of bias and serious indirectness.

We predefined ten exploratory subgroup analyses on the primary outcomes, quality of life, mortality, and serious adverse events [22]. Of these, we were only able to conduct subgroup analyses on quality of life and on diabetes distress (post hoc).

When assessing quality of life, test for subgroup difference showed no evidence of a difference when comparing type of diabetes (p = 0.17), sex (men compared to women) (p = 0.12), age (adolescents compared to adults) (p = 0.12), length of intervention (p = 0.14), type of therapy (individual compared to group) (p = 0.06), or type of control intervention (standard care compared to waitlist design compared to attention control) (p = 0.23) (Supplementary file 6, subgroup analyses quality of life).

One secondary outcome (diabetes distress) was post hoc analyzed due to clinical relevance [60]. When assessing diabetes distress, test for subgroup difference showed evidence of a difference when comparing type of diabetes (p = 0.02) with no effect of the experimental intervention in participants with type 1 diabetes and a negative effect in participants with type 2 diabetes, guided self-determination method compared to self-determination theory-based interventions (p = 0.007) showing benefits of guided self-determination and harms of self-determination theory intervention, and type of therapy (individual compared to group) (p = 0.004) showing harms of individual therapy compared to benefits of group therapy.

We found no evidence of a difference when comparing adolescents to adults (p = 0.15), length of intervention (p = 0.15), or type of control intervention (no intervention compared to standard care compared to placebo compared to attention control) (p = 0.05) (Supplementary file 7, subgroup analyses diabetes distress).

We were not able to conduct any of the remaining pre-defined subgroup analyses [22] due to lack of relevant data.

Two authors (A. S. M. and J. L.) independently assessed the certainty of the evidence using the five GRADE considerations (risk of bias, consistency, imprecision, indirectness, and publication bias) and the software GRADEpro GDT [56].

The certainty of the evidence was assessed on the primary outcomes (quality of life, mortality, serious adverse events), the secondary outcomes (diabetes distress, depressive symptoms, and non-serious adverse events), and the explorative outcome (HbA1c and motivation).

The certainty of the evidence was very low on the outcomes quality of life, mortality, serious adverse events, diabetes distress, depressive symptoms, serious adverse events, and motivation (control) (Table 2, summary of findings). On the outcomes motivation (autonomy) and motivation (amotivation), the quality of the evidence was rated as “low”.

We assessed imprecision using TSA and found that imprecision was present on the outcome “all-cause mortality” (Table 2, summary of findings). We reported all decisions to downgrade the quality of the trials by footnotes to add to the transparency of the decisions.

We were not able to report on all predefined subgroup analyses [22], as the included trials did not investigate, report, or provide the missing data on our requests. We performed post hoc subgroup analyses on our three secondary outcomes due to unexplainable heterogeneity. We needed to retrospectively report on motivation measured by the treatment self-regulation questionnaire. These changes have been submitted to PROSPERO. Basing our summary of findings table of trials assessed as low risk of bias was not an option as all included trials were at high risk of bias.

Discussion

This systematic review synthesized the evidence for beneficial and harmful effects of guided self-determination or self-determination theory interventions for people with diabetes in any healthcare setting assessed in randomized clinical trials.

We adhered to our pre-published protocol [22] and considered both risks of random errors and risks of systematic errors by applying the Cochrane methodology [20], the eight-step assessment suggested by Jakobsen et al. [48], trial sequential analysis [27], and GRADE assessments [56]. We found no effects of self-determination theory-based interventions compared with usual care on quality of life, all-course mortality, serious adverse events, diabetes distress, depressive symptoms, adverse events, HbA1c, and motivation (controlled); all results were at very low certainty, except for diabetes distress, which was at low certainty of the evidence. We found a potential effect on motivation (autonomous and amotivation) but at low certainty of the evidence.

We found no effect on the quality of life assessed with the WHO-5 index. If these interventions have any effects on quality of life, we may need a more specific instrument than the generic WHO-5 index to assess it [61]. Also, it may be so that guided self-determination or self-determination theory interventions simply do not affect quality of life. A randomized trial testing an emotional writing intervention in people with type 2 diabetes found a potentially clinically important worsening in depressive symptoms [62]. First, this emphasizes the need of assessing harms in all trials investigating psychosocial interventions. Second, in trials that reported no benefit of the guided self-determination on quality of life, the included participants were older and more likely to have well-developed writing skills [32, 33, 35].

We were not able to show any effects on the secondary outcome diabetes distress. This might mirror the pooling of the two potentially different interventions (guided self-determination and self-determination theory). The cluster-randomized trial of Glasgow et al. [24] investigating a self-determination theory intervention found harmful effect on diabetes distress. The trial contributed with more than 99% weight in the meta-analyses on diabetes distress. This trial had several methodological issues and thus high risk of bias: the trial was not registered in a trial register, nor was a protocol published; randomization, blinding, and attrition were inadequately described [24]. The guided self-determination method makes use of the reflection sheets as a pragmatic tool for internalizing the method, which might make a difference in clinical practice. This is supported by the high heterogeneity in the analysis of diabetes distress (end of intervention) and our subgroup analyses comparing the effect of guided self-determination to self-determination theory on diabetes distress. This difference should be cautiously interpreted. However, it might indicate that the guided self-determination is more useful in problem-solving of diabetes-specific challenges and potentially a more adequate tool for reducing diabetes distress, perhaps due to the reflection sheets. Moreover, the group format enables sharing of experiences between people living with diabetes which has been shown to increase normalization of emotional challenges related to diabetes and in turn reduction of diabetes distress [63, 64]. It might also be mediated by the increase of motivation (autonomy) and decrease on amotivation found in the meta-analyses solely including trials applying guided self-determination.

We found no effects on all-cause mortality, serious adverse events, and nonserious adverse events. These outcomes were seriously underreported in the included trials. Therefore, we do not know if guided self-determination or self-determination theory interventions have any effects on these important patient related outcomes.

Regarding the secondary outcome “depressive symptoms”, our results were also prone to missing data. The evidence for all primary and secondary outcomes were rated at very low certainty, and more high-quality trials are severely needed prior to implementing interventions applying guided self-determination or self-determination theory for diabetes into clinical practice.

Subgroup analyses on diabetes distress indicated differences in effects when comparing type of diabetes, favoring type 1 diabetes, and, as mentioned on guided self-determination method compared to self-determination theory-based interventions, favoring guided self-determination, and on type of therapy (individual compared to group), favoring group therapy. However, subgroup analyses are only hypotheses generating due to a high risk of type 1 error, and these subgroup effects may be investigated further in high-quality randomized trials.

It might be questioned if the half SDs derived from the meta-analyses and applied in the TSAs always reflect the minimal clinical important difference. In our currently ongoing trial investigating guided self-determination method in people with type 2 diabetes [60], we estimated a reduction of 6 points on the Problem Areas in Diabetes scale (PAID) as the minimal clinical important difference [59]. In this systematic review, we cannot reject that self-determination theory-based intervention decreases diabetes distress with less than 10.5 point as assessed in the TSA.

A preplanned outcome focusing on diabetes self-management skills, e.g., self-monitored blood glucose, would potentially have strengthened the clinical relevance of this systematic review; however, increased autonomy, alleviation of diabetes distress, and depressive symptoms have been reported to be associated with improved diabetes self-management skills [15, 33, 65].

Overall, large attrition [32] and incomplete outcome data [24, 31, 33] leading to high risk of bias rating on this domain seemed to be a general problem associated with the trials included in this systematic review which also may overestimate effect sizes [47]. Qualitative methods [66] or realist evaluation methodology [67] may be appropriate to investigate the pathways leading to the large attrition in some trials. A general upgrading of the clinical trial management skills invested in non-pharmacological trials may improve trial methodology. The trials that we included had difficulties with blinding personnel and participants and used several subjective patient-reported outcomes.

Our systematic review has some important limitations. The primary limitation was the clinical heterogeneity caused by the inclusion of both types of interventions (guided self-determination and self-determination theory), both type 1 and type 2 diabetes, and all modes of delivery and interventionists. Furthermore, flaws in trial design may overestimate effect estimates and increase between-trials heterogeneity [47], especially prone to trials with subjective outcome reporting [47]. Moreover, diabetes management always consists of multiple treatment elements [2], and it is likely that different co-interventions and spill-over effects from clinical practice may also have influenced results.

We were not able to conduct most of our planned subgroup analyses due to the fact that the trials were not reporting on the predefined characteristics. Another limitation of our review was the large number of comparisons which increases the risk of type 1 error. Likewise, our meta-analyses were compromised by missing data, despite preplanned attempt to contact all authors of included trials. A further limitation was the exclusion of quasi-randomized studies and observational studies in the assessments of adverse events. By focusing on randomized clinical trials that are unlikely to identify late and rare adverse events, we run the risks of focusing too much on benefits and too little on harms. A future systematic review focusing on the risks of harms in quasi-randomized studies and observational studies should take this into account to achieve a more balanced evaluation of benefits and harms once we have demonstrated convincing benefits of the interventions.

Conclusions

We found no effect of self-determination theory-based interventions compared with usual care on our primary outcomes: quality of life, all-cause mortality, and serious adverse events or secondary outcomes: diabetes distress, depressive symptoms, and adverse events. The evidence was of low to very low certainty.

Testo

Additional file 1. Search strategies.Additional file 2. PRISMA 2020 Checklist.Additional file 3. Sensitivity analyses best-worst and worst-best scenarios Quality of life and diabetes distress.Additional file 4. Results all outcomes.Additional file 5. Serious adverse events (SAE) and Adverse events.Additional file 6. Subgroup analyses, Quality of life.Additional file 7. Subgroup analyses, Diabetes distress.

Additional file 2. PRISMA 2020 Checklist.

Additional file 3. Sensitivity analyses best-worst and worst-best scenarios Quality of life and diabetes distress.

Additional file 5. Serious adverse events (SAE) and Adverse events.

Additional file 6. Subgroup analyses, Quality of life.

Additional file 7. Subgroup analyses, Diabetes distress.