Background

Adherence to the recommended standards in diabetes care has improved worldwide in recent decades (ADA 2020). However, such improvements have not been enough to stop the rapid spread of type 2 diabetes mellitus (T2DM), which represents a strong challenge for health systems, people, and society (Stegbauer et al. 2020). Known as a chronic disease and often poorly managed, it is considered the main cause of retinopathy and blindness, nephropathy, and micro- and macrovascular complications (Cusick et al. 2005; WHO 2016). Its action translates into a heavy burden derived from the disease, associated complications, and the acquisition and integration of new self-care. This growing trend underscores the urgency for effective management strategies in primary healthcare settings, where the frontline of T2DM management and prevention takes place. Assumed as a priority by the World Health Organization (2016), it requires articulated interventions to prevent and reduce its prevalence.

Emerging from the recognized vital contribution that communities can make to health and well-being, community support through social prescribing intervention is being explored to expand options and resources beyond those traditionally provided in primary healthcare (Munford et al. 2020a; Centre for Reviews and Dissemination 2015). Social prescribing is considered a “holistic, person-centred and community-based approach to health and well-being, bridges the gap between clinical and nonclinical support and services.” (Muhl et al. 2023). It facilitates and improves communication between primary healthcare professionals and the target community. Through community development workers or health workers, most often referred to as linked workers, professionals who support people’s access to community resources, it is possible to establish a link between the two contexts (Kimberlee 2013; Kielly et al. 2020). The linked worker establishes a relationship with the person after they have been referred by the healthcare system, exploring their needs and directing them to the resources in the community that appears to be a viable response (Connolly et al. 2024). Social prescribing intervention allows healthcare professionals to refer people to nonclinical activities aimed at preventing and promoting self-management of long-term diseases, such as T2DM2 (Bickerdike et al. 2017; Calderón Larrañaga et al. 2021).

The first intervention in the field of social prescribing dates to the United Kingdom over the past few decades and is referred to as community referrals, such as voluntary or arts activities (Lejac 2021; Morse et al. 2022). The concept emerged in 2016, with the definition by the Social Prescribing Network and the subsequent introduction of social prescribing into the national health system in England. The decade between 2012 and 2022 encompasses the formalization of the concept in 2016 and follows its quick evolution and integration into healthcare systems, both in the UK and internationally, with 20 countries currently involved (Morse et al. 2022; Muhl et al. 2023).

People’s lifestyles, such as low physical activity, smoking, and the intake of saturated fats and sugar, play a major role in the risk of and progression of T2DM and are also associated with low adherence to medication management, self-care behaviors, and recommendations made by health professionals (ADA 2020; Hamlin et al. 2016; Maddison et al. 2020). In addition, social determinants play a strong role in influencing behavioral changes in people with T2DM; when they come from disadvantaged socioeconomic backgrounds, they are more likely to have poorer self-management of the disease and an increased risk of associated complications. Social prescribing intervention, used as a stand-alone intervention or as a component of a complex intervention in a program, can reduce these deleterious effects of social determinants and encourage healthier behaviors and self-care (Calderón Larrañaga et al. 2021; Munford et al. 2020a; Wildman et al. 2019; Wildman and Wildman 2021). By bringing the person to the centre of care and acknowledging their needs, social prescribing is anchored in a multidimensional perspective (Husk et al. 2019) that enables people to change, adapt, and self-manage in the face of physical, emotional, and social challenges. Owing to its complexity (Saatci et al. 2010), it has been developed as a social prescribing program composed of a set of intervention components with structural intervention domains. Previous systematic literature reviews have been carried out more broadly to evaluate the effectiveness of social prescribing for producing outcomes related to health and well-being but not for specific diseases. In the literature, evidence analysis focusing only on T2DM, and social prescribing has been scarce; only one scoping review explored social prescribing for people with T2DM (Pilkington et al. 2017). Owing to the existence of a research gap in evaluating the effectiveness of social prescribing intervention for people with T2DM in the primary healthcare context, our focus was directed to the search for evidence. For a comprehensive understanding of the social prescribing intervention outcomes, they will also be analyzed by domains, such as a health intervention by the International Classification of Health Intervention (WHO 2021) and grounded in a conceptual framework the Fundamentals of Care (Kitson et al. 2013; Feo et al. 2018). This systematic literature review aimed to evaluate how the intervention of social prescribing can be effective on people with T2DM through the reporting of outcomes in three categories, health-related outcomes, health-related behaviors, and health-related economic evaluations.

Methods

Study design, data sources, and search strategy

A systematic literature review was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Page et al. 2021) in four electronic bibliographic databases, via EBSCO Host (CINHAL, MEDLINE and Psychology, and Behavioral Sciences Collection) and the SCOPUS database (MEDLINE). The selected search for published papers from January 2012 to December 2022 captures the field’s dynamic and transformative phase. This decade encapsulates the rapid evolution and increasing adoption of social prescribing, making it a critical phase for examining its impact on people with T2DM in primary healthcare. Boolean operators were used to link descriptors according to the PICO model (patient/population, intervention, comparison, and outcomes) to search for specific words’ synonyms or rejected results (Additional File 1). As social prescribing is a recent term and indexed descriptors are not yet available, the data search resorted to natural language. Truncation was used to integrate word variations and the singular and plural of each word. Covidence® software was used for independent analysis, and the research team was composed of three reviewers. Title and abstract analyses were carried out to exclude all duplicated papers. In the second stage, studies were identified for relevance to the theme under study through complete reading and were excluded if they met the established eligibility criteria. Subsequently, the reference lists of the selected studies were analyzed to locate new studies. The three reviewers carried out the final inclusion of the studies eligible for the systematic literature review.

Eligible and exclusion criteria

Our systematic literature review aimed to focus on the analysis, evaluation, and synthesis of the evidence produced by primary studies that seek to demonstrate the effectiveness of interventions in creating health, behavioral, and economic outcomes. Eligibility criteria included randomized controlled trials, non-randomized controlled trials, quasi-experimental trials, cohort studies, mixed methods studies, and observational studies. Owing to the recent concept of the social prescribing intervention and the fact that previous systematic reviews did not focus on the population under study, systematic literature reviews were not considered for our research. Gray literature was also excluded. Each study had to meet the following eligibility criteria: (i) person with T2DM aged 18 years or older; (ii) intervention carried out under social prescribing programs, as part of a set of interventions; (iii) social prescribing intervention carried out in the primary healthcare setting; (iv) social prescribing intervention through the referral of health professionals from the primary healthcare setting to linked worker or non-clinical activities in the community.

Intervention categorization

Interventions were categorized using three different approaches: social prescribing domains, which facilitate understanding of the intervention of social prescribing in the production of results in the context of primary healthcare (Costa et al. 2021); the International Classification of Health Intervention (ICHI), which is used as a facilitating tool in the reporting and analysis of health-related interventions from different sectors of the system, including primary care and public health (WHO 2021); and the Fundamentals of Care Framework, as a conceptual framework, which provides support to health professionals and nurses in recognizing the needs of the person and taking into account the fundamental physical, psychosocial and relational needs, contemplated in the dimension of integration of care (Kitson et al. 2013; Feo et al. 2018).

Main outcomes

This systematic literature review was intended to analyze any outcomes produced by social prescribing programs and categorize them into three categories: health-related outcomes, health-related behaviors, and health-related economic evaluation. To determine the results, the following scales were used: the EQ5D5L and WHOQOL-BREF for quality of life, the New Zealand Physical Activity Questionnaire Short Form (NEPAQ-SF), International Physical Activity Questionnaire Short Form (IPAQ-SF-), and self-exercise reported for physical activity, the Warwick-Edinburg Mental WellBeing Scale (WEMWBS) for psychological and mental well-being, the Qualify-Adjusted Life Years Scale (QUALYs) for quality of adjusted life years, the Hospital Anxiety and Depression Scale – Anxiety (HADS-A) for anxiety, the Hospital Anxiety and Depression Scale – Depression (HADS-D) for depression, the ICEop Capability Measure Adults (ICECAP-A) for capability measurement for adults, the Active Engagement in Life Score for Patient Engagement, and the Patient Activation Measure for self-management. During the follow-up period, the results of the intervention were evaluated on the basis of a temporal analysis from the beginning of implementation until the end of the study.

Data extraction

After independently reading the full texts of the eligible studies, two reviewers selected the relevant data for extraction; in the event of disagreement, a third reviewer was involved. As a resource for the extraction process, standardized tables were created, consisting of the author’s name, year of publication, country of origin, sample size, study design, provider, context, method and mode of delivery, frequency, duration, and content of the intervention, outcomes, and categorization of the social prescribing intervention (domains, ICHI categorization, and Fundamentals of Care Framework).

Data analysis

The heterogeneity of the studies in focus was calculated using the inconsistency index (I2) (Higgins and Thompson 2002). Subsequently, owing to the methodological and clinical heterogeneity presented, a meta-analysis was carried out by subgrouping, grouping, and analyzing the studies that led to the same outcome. Values of I2 < 25% were considered indicative of low heterogeneity, I2 > 50% of moderate heterogeneity, and I2 ˃ 75% of high heterogeneity (Higgins et al. 2003). When the studies that produced the same outcome were grouped, a meta-analysis by subgroup was carried out if I2 ˂ 25%. The effect sizes were analyzed according to Cohen’s d-test, assuming a small effect (d = 0.2), a moderate effect (d = 0.5), and a large effect (d = 0.8) (Lakens 2013) and considering significant statistics with a p value ˂ 0.05.

Data synthesis

A synthesis of social prescribing programs was performed under the recommendations of the Synthesis without Meta-analysis (SWiM) reporting guidelines (Champbel et al. 2020) and reporting the effect sizes of the outcome that was allowed a meta-analysis by sub-group. Overall, the population, objectives, limitations, and recommendations were stated. The interventions were related to the provider, context, delivery mode and method, duration, frequency, content, outcome, social prescribing domain, categorization of ICHI, and dimension of care integration of the Fundamentals of Care Framework.

Study quality appraisal and data analysis

A quality appraisal was independently performed by two reviewers using standardized tools to assess the risk of bias, ensuring a comprehensive evaluation of potential biases. Discrepancies were resolved using a third reviewer. The risk of bias was analyzed using the Cochrane Risk of Bias Rob 2 Assessment tool for randomized clinical trials and the ROBINS-I tool for nonrandomized intervention studies (Sterne et al. 2019); and the assessment tool developed by the NIH (National Heart Lung and Blood Institute) Study Quality Assessment Tools – NHLBI (2021) tool for mixed methods studies, cohort studies (retrospective and prospective), and observational studies (longitudinal, observational noncontrolled before and after study).

Results

The database searches identified 744 articles, of which 250 were duplicated and removed. After reading the title and abstract, 42 were selected and read in full; ten papers met the inclusion criteria. Subsequently, the bibliographical references of the ten papers were analyzed, and one article was identified and included in the review. A total of 11 papers met the inclusion criteria and were taken under the systematic review. The exclusion criteria were as follows: the wrong population, a person with another type of diabetes mellitus or of pediatric age; the wrong study design, a pilot study protocol; incorrect indication, not referring to social prescribing interventions; and incorrect setting, which took place in a hospital environment (Fig. 1).

Fig. 1
figure 1

Flow diagram of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. https://doi.org/10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/

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Study and population characteristics

The eligible studies included two randomized controlled trials (Mercer et al. 2019; Williams et al. 2017), one nonrandomized controlled trial (Kiely et al. 2021), one mixed methods study with a matched control group (Cranes et al. 2017), three cohort studies (retrospective and prospective) (Hamlin et al. 2016; Wildman and Wildman 2021) and (Munford et al. 2020b) and four observational studies (Munford et al. 2020a; Pescheny et al. 2019; Poulos et al. 2019), and (Wakefield et al. 2022) (Table 1).

Table 1 Principal characteristics of social prescribing studies
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The studies were from five different countries: England (Carnes et al. 2017; Munford et al. 2020a, 2020b; Pescheny et al. 2019; Wakefield et al. 2022; Wildman and Wildman 2021), Scotland (Mercer et al. 2019), Ireland (Kiely et al. 2021), New Zealand (Hamlin et al. 2016; Williams et al. 2017), and Australia (Poulos et al. 2019). All the studies involved n = 19,202 participants with chronic disease, defined as a long-term disease in which T2DM was present (Table 1). In the cohort study by Wildman and Wildman (2021), with 8086 participants, and in the randomized controlled trial by Williams et al. (2017), with 138 participants, the focus was the person with T2DM. The mean age (SD) of the population was ± 58.5 years, but two of the papers, Munford et al. (2020b) and Poulos et al. (2019), focused on people older than 65 years. The female population was predominant, and five social prescribing programs have been developed in socioeconomically deprived areas (Carnes et al. 2017; Hamlin et al. 2016; Kiely et al. 2021; Wakefield et al. 2022; Wildman and Wildman 2021).

Social prescribing intervention

Provider and setting

Different approaches to social prescribing programs have been identified. Six studies involved three stages in the development of the programs (Kiely et al. 2021; Mercer et al. 2019; Munford et al. 2020a, 2020b; Wildman and Wildman 2021; and Pescheny et al. 2019) (Table 2). Each had two types of settings, primary care and community, with the first stage involving the recognition of the person’s needs by healthcare professionals. The provider mainly identified in primary care was a general practitioner in ten studies (Carnes et al. 2017; Hamlin et al. 2016; Kiely et al. 2021; Munford et al. 2020a, 2020b; Pescheny et al. 2019; Poulos et al. 2019; Wakefield et al. 2022; Williams et al. 2017) and a practice nurse in five (Hamlin et al. 2016; Mercer et al. 2019; Poulos et al. 2019; Wakefield et al. 2022; Williams et al. 2017).

Table 2 Principal Characteristics and Categorization of Social Prescribing Interventions
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In the second stage, an articulation between primary healthcare and community organizations was referred to as performed by the linked worker (Kiely et al. 2021; Wakefield et al. 2022), also referred to as the social prescribing coordinator (Carnes et al. 2017), navigator (Pescheny et al. 2019), community health worker (Wildman and Wildman 2021), green prescriptor facilitator (Williams et al. 2017), or community-link practitioner (Mercer et al. 2019), which normally occurs in the community. The third stage involved the development of social prescribing interventions in the community. Despite other reported approaches, healthcare professionals can refer directly to the community, such as network support sports (Williams et al. 2017) or professional arts (Poulos et al. 2019). Different approaches involved an intermediate stage, between stage 1 and stage 2, performed by the health coach (Wakefield et al. 2022) or trained volunteers to assist in the delivery of the service in the community by providing additional support (Carnes et al. 2017).

Delivery mode and method

The delivery methods were divided into individuals and groups and differed in the purpose of the activity in the community (Table 2). The social prescribing programs analyzed combined the two types, individually in the beginning and individually or in a group, according to community activities; only in one study were all activities in groups (Poulos et al. 2019). In terms of delivery mode, four studies reported face-to-face mode and by phone (Hamlin et al. 2016; Kiely et al. 2021; Mercer et al. 2019; Williams et al. 2017), two reported home visits (Mercer et al. 2019; Wildman and Wildman 2021), and four reported accompanying patient to community activities (Carnes et al. 2017; Kiely et al. 2021; Mercer et al. 2019; Wildman and Wildman 2021). Compared with phone mode, face-to-face mode had a small effect on HbA1c and body weight, with a greater effect (Table 3).

Table 3 Health-related, behavior economics evaluation outcomes of the social prescribing intervention
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Duration and frequency

The interventions took place for a minimum of 6 weeks (Kiely et al. 2021) or for a maximum of 25 months (Wildman and Wildman 2021) (Table 2). Most of the studies did not detail the intervention duration or frequency. Only one study mentioned the number of sessions (Pescheny et al. 2019), and another study mentioned the number of courses, showing better results for participants who engaged in three or more courses (Poulos et al. 2019). Another three studies reported the appointment frequency with linked workers: six sessions (Carnes et al. 2017), one to five (Mercer et al. 2019), and one session face-to-face per month, with a duration of 15–60 min or four phone conversations per month (Williams et al. 2017). The studies revealed that there was a small to large effect of the linked worker intervention when three or more contacts were made during the program (Table 3).

Intervention content

Social prescribing intervention was developed in the community by carrying out different activities (Table 2). The most common interventions were physical activity (Carnes et al. 2017; Hamlin et al. 2016; Kiely et al. 2021; Munford et al. 2020a, 2020b; Pescheny et al. 2019; Poulos et al. 2019) (Wildman and Wildman 2021; Williams et al. 2017), involving 19 types of activities; walking was the most popular (Hamlin et al. 2016; Mercer et al. 2019; Pescheny et al. 2019; Williams et al. 2017). Social interaction activity was referred to in seven studies, with activities such as voluntary or charity (Carnes et al. 2017; Mercer et al. 2019; Munford et al. 2020a, 2020b; Poulos et al. 2019; Wakefield et al. 2022; Wildman and Wildman 2021). Personal development (Carnes et al. 2017; Hamlin et al. 2016; Mercer et al. 2019; Munford et al. 2020b; Pescheny et al. 2019; Wildman and Wildman 2021) and arts activities were developed in six programs, along with six different activities (Mercer et al. 2019; Munford et al. 2020a, 2020b; Pescheny et al. 2019; Poulos et al. 2019; Wildman and Wildman 2021). Self-management education intervention was presented in five studies (Munford et al. 2020a, 2020b; Pescheny et al. 2019; Wildman and Wildman 2021; Williams et al. 2017), and self-care management was presented in three (Carnes et al. 2017; Mercer et al. 2019; Wakefield et al. 2022). Other interventions, such as social support (Kiely et al. 2021; Wakefield et al. 2022), religious support (Carnes et al. 2017; Munford et al. 2020a; Pescheny et al. 2019), and cultural activity (Carnes et al. 2017; Munford et al. 2020a, 2020b), were also observed (Table 2).

Social prescribing intervention categorization

Heterogeneous interventions were identified and assembled in seven of the nine social prescribing domains mentioned by Costa et al. (2021). Of the seven social prescribing domains, self-care education was divided into two distinct fields—self-care management and self-management education—and a new domain—social support—was included. The nine domains assigned were physical activity, art activities, social interaction, personal development, self-management education, self-care management, social support, and cultural and religious activities (Table 2). After categorization by domain, each domain was allocated according to the ICHI into two categories: interventions on health-related behaviors, which involve interventions related to accessing, promoting, and modifying behavior associated with a particular health condition; and interventions on activities and participation domains related to learning, applying knowledge, self-care, interpersonal interactions and relationships, and community, social and civic life (WHO 2021). The social prescribing domains of social interaction, art activities, social support, and cultural and religious activities were allocated to the intervention on activities and participation domains. The physical activity, personal development, self-care management, and self-management education domains were categorized as interventions for health-related behavior. Considering that physical, psychosocial, and relational needs are fundamental pillars of T2DM, the intervention of social prescribing was categorized according to the Integration of the Care dimension of Fundamentals of Care Framework: Physical: physical activities and self-care management; Psychosocial: self-management education, social support, and arts activities; and Relational: social interaction, personal development, and cultural and religious activities.

Social prescribing intervention outcomes

The impact of the social prescribing intervention resulted in different outcomes, which were grouped into three categories: health-related outcomes, health-related behavior outcomes, and health-related economics evaluation. The outcome was evaluated using questionnaires administered at the beginning of the intervention and during the follow-up period (between 6, 8, 12, 18, 24–36, and 96 months) (Table 2). Owing to methodological and clinical heterogeneity, with I2 = 97%, it was not possible to carry out a meta-analysis. A subsequent subgroup meta-analysis was carried out for the following outcomes: anxiety, depression, HbA1c, and body weight, with an I2 = 0%.

Health-related outcomes

The health-related outcomes considered were social, psychological, and mental well-being; anxiety; quality of life; quality-adjusted life years; physical activity; HbA1c; total cholesterol; waist circumference; and weight. Regarding quality of life, quantitative and qualitative data from six social prescribing programs revealed an increase in quality of life, with a small effect size (Kiely et al. 2021; Mercer et al. 2019; Munford et al. 2020a, 2020b; Wakefield et al. 2022; Williams et al. 2017) (Table 3). An improvement in quality of life was associated with a greater number of contacts with the linked worker, three or more contacts with a very small effect (d = 0.07 [95% CI 0.02, 0.13] p ˂ 0.011), a length of the follow-up period with a small effect (d = 0.36 [95% CI 0.28, 0.44]) and an environmental domain with a small to moderate effect size (d = 0.45 [95% CI 0.39, 0.52] p ˂ 0.000).

Psychological or mental well-being was referred to in three studies in which positive feelings were reported (Poulos et al. 2019; Wakefield et al. 2022; Williams et al. 2017), with a moderate effect size (Poulos et al. 2019), and social well-being was associated with a decline in social isolation (Poulos et al. 2019). Anxiety and depression were reported in three studies (Carnes et al. 2017, Kiely et al. 2021, Mercer et al. 2019), with an I2 = 0%. On the basis of the homogeneity displayed, a subgroup meta-analysis of anxiety and depression outcomes was conducted and revealed small effect sizes (d = 0.19 [95% CI 0.0145, 0.044] p = 0.006 and d = 0.17 [95% CI 0.403, 0.057] p = 0.114) for both outcomes. When the levels of anxiety and depression were compared with the number of times (three or more times) the person consulted the linked worker, they revealed an increase in the effect on the results (Table 3).

Four studies showed that there is a growth in physical activity levels and a decrease in a sedentary lifestyle (Hamlin et al. 2016; Mercer et al. 2019; Pescheny et al. 2019; Williams et al. 2017). Age and work status were reported to have a negative effect on physical activity (Pescheny et al. 2019) and consulting a linked worker three or more times had a small effect on physical activity (d = 0.34 [95% CI 0.07, 0.61], p = 0.013) (Mercer et al. 2019).

In terms of HbA1c, there was a modest reduction, with a very small effect size reflected by the subgroup meta-analysis d = 0.07 [95% CI 0.021, 0.109], p = 0.004) (Wildman and Wildman 2021; Williams et al. 2017) (Table 4). A slight increase in the impact can be observed when analyzing the face-to-face mode, but with no statistical significance (Williams et al. 2017). The same effect can be seen in the decrease in body weight (Williams et al. 2017). Waist circumference and total cholesterol have also been reported to have a small effect, but the phone approach had a greater effect on decreasing total cholesterol (Table 3). A gain in years of life was revealed throughout a longer follow-up period, and a stop in community asset participation revealed a decrease in quality-adjusted life years with a small impact (Munford et al. 2020b).

Table 4 Effects size of health-related outcomes
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Health-related behavior outcomes

Health-related behaviors were categorized as follows: self-management (patient measure activation) and patient engagement (active engagement in life score). Self-management was reported in two studies, with suggested improvements in self-care and condition management (Kiely et al. 2021; Wildman and Wildman 2021). Related active engagement in life scores revealed better engagement through linked worker intervention, intending to facilitate the understanding of needs, and coaching lifestyle interventions that promote self-management of life skills and health conditions, with no reported statistical significance (Carnes et al. 2017) (Table 3). Other studies have shown personal growth and empowerment (Pescheny et al. 2019), with an increase in self-confidence and self-determination (Poulos et al. 2019).

Health-related economics evaluation

For health-related economics, evaluations were assigned according to capability measures for adults (ICECAP-A), number of visits to general practitioners, and healthcare costs. The adult capability measure did not show an effect size when related to the number of views of the linked worker. Healthcare costs continued to rise throughout the follow-up period. Discontinuing participation in the program was found to have a small impact on costs after 18 months of follow-up (Munford et al. 2020b) (Table 4). A decrease in the number of visits to the general practitioner was identified when comparing the data of the control group before the start and after the course of the intervention (Carnes et al. 2017).

Quality appraisal

All eligible studies were critically analyzed using methodological assessment tools. The risk of bias was determined according to the study design: randomized controlled trial (Fig. 2), nonrandomized controlled trial (Table 5), mixed methods study (Table 6), cohort study (retrospective and prospective) (Table 7), and observational study (longitudinal, observational noncontrolled before and after study) (Table 8).

Fig. 2
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Risk of bias assessment of randomized controlled trials, Cochrane Risk of Bias Assessment Tool (RoB 2)

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Table 5 Risk of bias assessment of non-randomized controlled trials, Cochrane Risk of Bias Assessment Tool (ROBINS-I)
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Table 6 Risk of bias assessment of mixed method study, (adapted from an assessment tool developed by the US National Heart, Lung, and Blood Institute)
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Table 7 Risk of bias assessment of cohort study (adapt from an assessment tool developed by the US National Heart, Lung, and Blood Institute)
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Table 8 Risk of bias assessment of observational studies (longitudinal, observational non-controlled before and after study) (adapt from an assessment tool developed by the US National Heart, Lung, and Blood Institute)
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Analysis of the included studies revealed significant concerns regarding their methodologies. A quality appraisal using a risk of bias assessment indicated a “high” level of bias in these studies. Several issues arose, including a considerable drop-out of participants from the initial phases to the follow-up periods in most of the studies (Carnes et al. 2017; Kiely et al. 2021; Hamlin et al. 2016; Munford et al. 2020a, 2020b; Pescheny et al. 2019; Wakefield et al. 2022; Wildman and Wildman 2021). Furthermore, four studies reported a reduced number of participants (Kiely et al. 2021; Munford et al. 2020a; Pescheny et al. 2019; Poulos et al. 2019), potentially compromising the representativeness of the sample and thereby affecting the generalizability of the findings.

In addition, the analysis highlighted another significant concern, missing data, which impeded the coherence of the studies. Specifically, comprehensive information related to the clear description of various interventions and outcome measures was lacking, diminishing the overall clarity and coherence of the research findings.

Discussion

The analysis of 11 papers in this systematic literature review sought to identify social prescribing interventions for people with T2DM and analyze their impact on producing health, behavioral, and economic outcomes. Nine domains of social prescribing intervention were assigned in the production of outcomes. Social prescribing intervention carried out face-to-face, over longer periods, and with regular contact with the linked worker, showed the greatest impact. The effect of the social prescribing intervention on health-related outcomes was more noticeable than on behavioral or economic outcomes, such as improved quality of life, well-being, reduced anxiety and depression, increased physical activity, reduced HbA1c levels, weight, and abdominal circumference. Similar to the difficulties mentioned in another study (Carnes et al. 2017), during the analysis and narrative synthesis of the data from the papers under review, it was observed that the qualitative data was sometimes able to better translate the impact of the social prescription intervention than the quantitative data (Carnes et al. 2017). This difficulty can be attributed to the heterogeneity of the social prescribing intervention and the instruments used to measure the results (Carnes et al. 2017; Sonke et al.2023; Thomas et al. 2021).

Main findings social sociodemographic and socioeconomic characteristics

Individual characteristics of each participant, such as problems related to mobility concerns (poor balance), fear of failure, limitations in walking distance and inability to stand for long periods, poor vision, and hearing (Poulos et al. 2019), and older age (Munford et al. 2020a, 2020b), were related to social prescribing program dropout and negative results in physical activities (Pescheny et al. 2019). The group of working people was identified as those who found it most difficult to practice physically (Munford et al. 2020b), and the time when the interventions were carried out, after or before work, or on weekends was mentioned as a facilitating factor (Munford et al. 2020b). The socioeconomic deprivation context emphasizes limited access to resources, such as appropriate diet, medication, and exercise opportunities, while reducing self-efficacy by creating barriers to self-care management (Carnes et al. 2017; Hamlin et al. 2016; Kiely et al. 2021; Wakefield et al. 2022; Wildman and Wildman 2021).

Main findings in social prescribing intervention

Different approaches were identified, beginning with primary healthcare and continuing activities in the community. Some of them revealed many clinical and nonclinical professionals involved in programs, with people reporting difficulty distinguishing the role of each (Carnes et al. 2017). As identified in five studies (Mercer et al. 2019; Hamlin et al. 2016; Poulos et al. 2019; Wakefield et al. 2022; Williams et al. 2017), nurses are recognized as health professionals who are becoming increasingly involved in social prescribing and assume an important role in social prescribing programs (McKenzie et al. 2021). They are considered health professionals with the ability to assess a person’s needs and identify psychosocial problems with an impact on self-care and diabetes mellitus control more easily (Donohue-Porter 2012; Kenkre and Howarth 2018; Nikitara et al. 2019). It plays a major role in social prescribing, supporting people in achieving desired goals (Kenkre and Howarth 2018; Nikitara et al. 2019).

The face-to-face approach had an impact on people’s knowledge of needs from the first visit, with a higher rate of adherence to the program and a greater reduction in HbA1c compared to the telephone-based approach (Williams et al. 2017). Longer programs have shown better results (Mercer et al. 2019; Kiely et al. 2021; Williams et al. 2017), and those who consulted linked workers more often had a better quality of life and improvements in anxiety, depression, and self-reported exercise (Carnes et al. 2017; Mercer et al. 2019).

Heterogeneous interventions were identified and assembled in nine social prescribing domains that can be developed in the community to support behavioral change by connecting patients with their activities and providing interpersonal support and motivation (Munford et al. 2020a). The following social prescribing program involves the three fundamental needs of the Fundamentals of Care Framework (Williams et al. 2017), and others direct their intervention to specific needs dimensions. Physical engagement can have a positive impact on self-care, condition management (Kiely et al. 2021; Wildman and Wildman 2021), and decreasing HbA1c (Wildman and Wildman 2021; Williams et al. 2017). The potential for growth and integrated physical activity in inactive persons has been demonstrated, with significant results in weight management, waist circumference reduction, and glycemic control (Pescheny et al. 2019; Williams et al. 2017). Self-care management intervention improves the patient’s condition through information and education and empowers the person to manage their illness (Bhuyan 2004). In the psychosocial dimension, art activities lead to a rise in physical levels, a sense of purpose and direction, personal growth, empowerment, and interaction, and the establishment of a relationship with others, which contributes to psychological and mental well-being (Poulos et al. 2019). Social support intervention contributes to the self-management of T2DM and clinical outcomes (Garizábalo-Dávila et al. 2021; van Dam et al. 2005). Self-management education is considered a significant contributor to new learning, knowledge, and skills that promote long-term and positive health outcomes (Haas et al. 2013). In a qualitative follow-up study, individuals reported confidence and an improved ability to self-manage their disease condition (Wildman et al. 2019). In the relational dimension, social interaction creates an opportunity to engage patients in open decision-making through community assets, which leads to a better quality of life and personal relationships that allow the person to feel more integrated into their community (Munford et al. 2020a; Wakefield et al. 2022). Personal development involves the person in a dynamic process, engaging in their own life with an increase in self-esteem and a sense of purpose (Yardley et al. 2015).

Most of the programs encompass several domains of social prescribing, with no discernible variation in the development of the intervention or the associated outcomes. The lack of an evaluation of individual results according to each intervention, and the results are seen as an outcome of the entire program, poses challenges in identifying the effectiveness of the individuality of each intervention.

Main finding outcomes

HbA1c recognized as a marker of glycemic control and as an important indicator for metabolic control and diabetes management (ADA 2020; Genis-Mendoza et al. 2022; Wildman and Wildman 2021) was reported in two studies, with a slight decrease and a small effect (Wildman and Wildman 2021; Williams et al. 2017). Obesity and the accumulation of visceral fat with increased abdominal circumference are related to increased cardiovascular risk and the development of non-communicable diseases such as T2DM (Powell-Wiley et al. 2021; Rothberg et al. 2017). Considering the predictors of worsening metabolic control in T2DM patients and/or the occurrence of associated complications. Previous studies in recent decades have shown that reducing weight and abdominal circumference is associated with improvements in T2DM control, with reductions in blood glucose, cholesterol levels, and blood pressure (Genis-Mendoza et al. 2022; Rothberg et al. 2017). The social prescribing intervention in this systematic review showed a small effect on reducing weight and abdominal circumference.

Quality of life, as a health-related outcome, was one of the outcomes that was the focus of interest in most social prescribing programs and the one that showed results in different studies (Mercer et al. 2019; Kiely et al. 2021; Munford et al. 2020a, 2020b; Wakefield et al. 2022; Williams et al. 2017). Quality of life was analyzed in four domains (Munford et al. 2020a). Environment quality of life: a person feels more physically safe and secure, has a positive perception of their physical environment, and has positive feelings. Psychological quality of life includes more self-esteem, better body image, and better appearance. Physical quality of life includes more energy, better sleep, greater mobility, less pain and discomfort, and social quality of life, as well as better personal relationships and fewer negative feelings (Munford et al. 2020a). The greatest improvement in quality of life was revealed in the environmental domain, followed by the psychological, physical, and social domains (Munford et al. 2020a). A positive effect and statistically significant quality of life were revealed with community asset participation, and its discontinuation led to a decrease in quality of life and quality-adjusted life years (Munford et al. 2020b). The number of group members was also described as a positive predictor of quality of life over time (Wakefield et al. 2022).

Psychological well-being is associated with health behaviors, such as greater physical activity, a healthy diet, better glucose levels, and lower levels of HbA1c (Yi et al. 2008; Boehm et al. 2015; Huffman et al. 2015). Social prescribing interventions have been reported to have a moderate impact on mental health in terms of self-confidence, self-determination, personal achievement, and growth (Poulos et al. 2019; Wakefield et al. 2022), which allows people with T2DM to better manage and control their disease. Social well-being has also increased with a reported sense of purpose and direction, finding a new interest, and feeling motivated and optimistic for a new stage in one’s life (Poulos et al. 2019; Wakefield et al. 2022). Lonely people tend to receive routine primary healthcare and may use this care as a source of much-needed social connections (Poulos et al. 2019). Social prescribing programs can promote a rich social environment that allows people to feel more integrated into their communities, establish connections, and establish relationships with others (Poulos et al. 2019; Wakefield et al. 2022), as well as with a sense of community belonging (Kiely et al. 2021; Wakefield et al. 2022). It is recognized as having the potential to promote behavioral change and support people in accessing and developing activities in the community that promote engagement in one’s self-condition and improvements in self-management (Hamlin et al. 2016; Kiely et al. 2021; Wildman and Wildman 2021). Depressive symptoms and anxiety are frequently identified in people with T2DM and are related to poorer glycemic control, reduced quality of life, increased complications, and a greater mortality rate. The data analyzed from the subgroup meta-analysis of these outcomes suggest that intervention of social prescribing can play an important role in reducing these symptoms. Health literacy was not an outcome evaluated in any paper. However, Wildman and Wildman (2021) and Williams et al. (2017) highlight the importance of improving health literacy by understanding individuals in their communities to improve communication. They reflect the importance of developing holistic interventions, involving education, self-care, and behavior change support to empower the person with individual knowledge and skills (Wildman and Wildman 2021; Williams et al. 2017); however, they do not analyze this data. Regarding costs, the studies analyzed are not unanimously revealing through the analyses of quantitative data an increase in general practitioner visits, but qualitative data revealed a reduction in rates for the baseline to follow-up period (Carnes et al. 2017). Supported by a recent study, there is a lack of economic evaluation of social prescribing and more research is needed to evaluate the economic impact (Kiely et al. 2022). Another study throughout the follow-up period showed a reduction in the total costs of healthcare and that stopping community activity participation led to a large significant increase in healthcare costs (Munford et al. 2020b).

Strengths and limitations of the review

This systematic literature review employed a rigorous and quality methodology, meticulously analyzing the risk of data bias based on each study’s design. This study provides a comprehensive summary of the diverse domains of social prescribing interventions in primary healthcare for T2DM patients, detailing their potential impacts on health, behavior, and economic costs. Additionally, this review synthesizes key evidence-based barriers, such as individual characteristics, comorbidities, and socioeconomic contexts, that influence the feasibility, adherence, and acceptance of future interventions.

However, the review also acknowledges several limitations: a limited number of studies exclusively focused on T2DM patients; a lack of clear information about the measured outcomes and their specific interventions; higher dropout rates due to engagement difficulties; a high risk of bias in quality appraisal; and a scarcity of studies analyzing the economic cost-effectiveness of social prescribing interventions. These limitations underscore the need for more targeted research in these areas, particularly to enhance the understanding of the economic impacts of social prescribing and to improve engagement strategies in T2DM management.

Conclusion

This systematic review of the literature allows us to look at social prescribing and its effectiveness in achieving outcomes that respond to better management and self-care of diabetes and prevent future complications. This systematic review highlights social prescribing as a health intervention in different domains. Owing to their heterogeneity, the understanding and integration of these domains in the design of future social prescribing interventions are considered fundamental to achieving results-oriented objectives. With a suggested reduction in the number of general practitioner visits and lower expenditure on health resources in the long term, social prescribing could be a possible sustainable approach in health systems with an impact on a person’s quality of life and well-being. However, there remains a need to develop studies that improve the evidence supporting the results of economic evaluation and that support the effectiveness of social prescribing interventions.

Implication for practice and research

For further studies to promote better personal engagement in program participation and monitoring during the process, it is important to consider the barriers and limitations of sociodemographic and socioeconomic characteristics that can be imposed. It is considered important to delve deeper into the complexity of social prescribing interventions and their effects on people’s behavior, well-being, and quality of life, as these actions will allow for a better translation of the quality of the evidence and an understanding of the individual contributions of each intervention. Social prescribing programs developed in socioeconomic areas are necessary to create equal opportunities for T2DM patients and thus promote equity in healthcare. On the basis of the findings of this systematic literature review, we propose to contribute to the importance of examining social prescribing interventions as a connection between community and primary healthcare, which may play a crucial role in controlling the complications associated with T2DM and its evolution in the future.