The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis

Abstract

Objective

The objective of this systematic review and meta-analysis was to evaluate the effectiveness of social prescribing interventions in the management of long-term conditions in adults.

Data sources

Eleven electronic databases were searched for randomised and quasi-randomised controlled trials.

Review Methods

Outcomes of interest were quality of life, physical activity, psychological well-being and disease-specific measures. Bias was assessed with the Cochrane Risk of Bias 2 tool. A narrative synthesis and meta-analysis were performed.

Results

Twelve studies (n = 3566) were included in this review. Social prescribing interventions were heterogeneous and the most common risks of bias were poor blinding and high attrition. Social prescribing interventions designed to target specific long-term conditions i.e., cancer and diabetes demonstrated significant improvements in quality of life (n = 2 studies) and disease-specific psychological outcomes respectively (n = 3 studies). There was some evidence for improvement in physical activity (n = 2 studies) but most changes were within group only (n = 4 studies). Social prescribing interventions did not demonstrate any significant changes in general psychological well-being.

Conclusion

Social prescribing interventions demonstrated some improvements across a range of outcomes although the quality of evidence remains poor.

Keywords

Social prescribing long-term conditions community link-worker community health worker self-management

Introduction

Long-term conditions are lifelong health problems, which tend to be managed through medication and other therapies.^1,2. Though long-term conditions lack a universal definition³ it is acknowledged that long-term conditions may present as individual or multiple diseases co-existing simultaneously⁴ significantly impacting both physical^5,6 and mental wellbeing^7,8 and are associated with increasing age, female gender, lower income class and poor social network.⁹ Patients with long-term conditions have poor quality of life,^10,11 reduced ability to work,¹² greater dependence on hospital services¹³ and experience premature death.¹⁴ Healthcare providers are encouraged to adopt patient-centred models of care for individuals with complex multimorbidity¹⁵ to prevent the treatment burden that accompanies fragmented delivery of poorly coordinated single-disease models of care.¹⁶

Social prescribing is an innovative person-centred approach¹⁷ to help individuals from socioeconomically deprived areas address the biopsychosocial factors associated with long-term conditions¹⁸ and improve their quality of life^19–21 by linking patients in primary care with existing tertiary support services in the community.^22,23 Social prescribing may complement existing medical management by incorporating both horizontal and person-centred integration models of care.²⁴ A social prescription involves the referral of individuals by medical and allied health practitioners to non-clinical laypersons called ‘Community link-workers’ or ‘Community health workers’, who collaborate with these individuals to identify purposeful goals and co-design a social prescribing pathway involving relevant community-based support schemes.^19,25–28 For the purpose of this review, non-clinical laypersons, recruited from the local community (that do not have existing health care qualifications) will be referred to as community link-workers. Social prescribing pathways vary from light touch signposting for housing and financial needs²⁹ and community groups referral for art therapy or exercise therapy^30,31 to more intensive pathways offering increased community link-worker support to address the complex needs of individuals with long-term conditions.¹⁹

Participants of social prescribing initiatives have reported improvements in numerous health domains, for example: Increased self-esteem;³² increased sense of control and empowerment;^30,32 improvements in psychological well-being;³³ reduction in anxiety and/or depression;³⁴ and improved physical health and lifestyle.³⁵ Previous systematic reviews exploring the effectiveness of social prescribing have highlighted the heterogeneity of the methodological approaches across the research. Uncontrolled before and after studies; lack of comparative controls; patients lost to follow up and inappropriate outcome measures for the population of interest are reported as limiting factors influencing the strength of the findings.^19,25 Furthermore, previous systematic reviews were limited to specific countries^19,25,36 or had a singular focus on particular outcomes of interest³⁷ and population.³⁸ This current systematic review will bridge this gap in the evidence by including only randomised/quasi-randomised controls, from different geographical regions, focusing on outcomes that reflect the multifactorial nature of long-term conditions. Given the limitations of the literature to date, the aim of this systematic review and meta-analysis was to determine the effectiveness of social prescribing in the management of long-term conditions in community-based adults.

Methods

A systematic review of the literature was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement.³⁹ The protocol for this review is registered with Open Science Framework https://osf.io/p5vf9/.

Study design

A systematic literature review of randomised and quasi-randomised controlled studies assessing the effectiveness of a social prescribing intervention on community-based adults with long-term conditions, utilising a ‘Community link-worker’ or ‘Community health worker’ was performed. A narrative synthesis was conducted on the identified studies and a meta-analysis performed on those studies that reported haemoglobin A1C (HbA1c) levels in diabetes.

Data sources and search strategy

A comprehensive literature search (Supplementary Material #1) of electronic databases was conducted from inception until November 2022 and updated in December 2023. Databases searched were: MEDLINE and MEDLINE in Process (via Ovid), EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Cumulative Index to Nursing and Allied Health Literature (CINAHL), EU Clinical Trials Register, LILACS (Latin American and Caribbean Health Sciences Information Database), Scopus and AgeINFO. Trial registries including Clinicaltrials.gov, WHO trials search (ICTRP) and Trials Register of Promoting Health Interventions (TRoPHI) were also searched. The search was supplemented by hand-searching relevant journals and citation tracking. The Grey literature was searched using Irish Health Service Executive (HSE) Lenus, RIAN, Open Grey and World Health Organization Library Information System (WHOLIS).

Inclusion and exclusion criteria

To be included studies had to be randomised or quasi-randomised controlled trials incorporating a social prescribing model with a non-clinical community-based link-worker, recruited from the community, without a previous qualification in medical or health sciences or already working in a professional clinical role. The social prescribing interventions had to be community-based using a health promotion approach defined by the Social Prescribing Network Conference Report for Long-term Conditions in Community-Dwelling Adults.³⁴ Any long-term conditions appropriate for a social prescribing intervention could be included in this review (for example, diabetes mellitus, stroke, asthma, depression, chronic obstructive pulmonary disease, chronic kidney disease, hypertension, inflammatory arthropathies, irritable bowel syndrome, obesity, cardiovascular disease, low back pain, progressive neurological disorders, and cancer). Interventions could be face-to-face or remote. Outcome measures of interest were quality of life, physical activity, psychological well-being, and disease-specific measures. Only studies published in English were included and participants had to be at least 18 years.

All studies identified from the search strategy were exported to Covidence software.⁴⁰ After study duplicates were removed an initial screening of titles and abstracts was conducted independently by two authors (DJOS and JGMcV). Full text of suitable studies was obtained and independently screened against the inclusion criteria. Studies meeting the inclusion criteria were independently reviewed with any disagreements between the two reviewers arbitrated by a third reviewer (JH).

Data extraction

A data extraction template was developed a priori and trialled with one study. Study characteristics captured included author, year of publication, patient demographics (age, gender) and background, intervention, control, duration of the intervention, primary and secondary outcome measures, results. A further characteristic of the intervention table was also made. Both original tables may be found in the supplementary materials file.

Methodological quality evaluation and risk of bias

The methodological quality and reporting standards of this review were constructed using the Cochrane Collaboration's tool for assessing risk of bias in randomised and quasi-randomised trials (RoB2).⁴¹ The Rob2 tool is structured into five domains³⁷ including; bias arising from the randomisation process; bias due to deviations from intended interventions; bias due to missing outcome data; bias in measurement outcome; bias in selection of the reported outcome. Risk of bias was assessed independently by two reviewers (DJOS, JGMcV) and differences resolved by discussion with a third researcher (JH). A judgement was made on each study as being low, high, or unclear risk of bias.

Data synthesis

Summary data on the study characteristics and the study interventions (Table 1) were extracted and presented in tabular form, (primary study characteristics table and primary intervention table are available in Supplemental materials). A narrative synthesis was conducted, and the data was explored to interpret the relationships in the data within and between studies. Data was analysed to determine the impact of variability in study designs, populations and outcome measures. A meta-analysis, was performed on four of the 12 included studies using the Hartung-Knapp-Sidik-Jonkman ⁴² random-effects method and illustrated graphically (Figure 2). The standardised mean difference and 95% confidence interval (95% CI) were used to analyse the effect of the community link-worker intervention on HbA1c in diabetes, when comparing community link-worker interventions to the control group. Where necessary, authors were contacted to solve possible uncertainty of effect size and RoB2 interpretations. To assess between-study variance we used tau-squared (the variance of true effects). The I² statistic was then used to determine any inconsistencies within the data. These statistical analyses were performed using IBM SPSS Statistics (Version 29).⁴³ Statistical significance was set at 5%. Sensitivity analyses were performed by removing the study with the highest ‘weight’ for each cluster.

Table 1.

Characteristics of the study and social prescribing intervention.

Study	Theoretical domains & constructs	Link worker training	Link worker backgrounds	Services provided	location, duration & follow ups	Intervention delivery& mode
1. Gray et al.⁴⁴	Shaping knowledge, feedback and monitoring, goal setting, social support, advocacy, navigation	40 h of comprehensive training, including didactic sessions, In-class exercises and field practice. Health coaching and motivational interviewing.	High school or equivalent degrees and 5–8 years of experience as CLWs,	Education, social support, informal counselling, linkages to community resources, blood glucose monitoring, healthy eating, physical activity, smoking cessation	Home based, community resource locations Follow up: 12 months	CLWs meetings 0.5, 1.5, 3.5,7, 10-month Total interventions: At least four CLW visits. Mode: Face to Face
2. Bossche et al⁴⁵	Social support, coaching, advocacy, navigation	2 online training modules of 2 h with entailed communication skills, signposting	NR	Presence to patients who were socially isolated or who felt lonely or anxious, information on social distancing, navigation to healthcare	Community sites 8 weeks duration Follow up: 8 weeks	8 contacts for 2 h per over 8 weeks Total interventions: NR Mode: Telephone, text, e-mails, park walks
3. Ramirez et al⁴⁶	Community-based participatory research methods drawing on theoretical frameworks; social cognitive theory, stress and coping theory, health behaviour change	NR	NR	Social work and psychosocial services referrals, child /elderly care, transportation, financial services; appointment follow-up, fertility education, onward referral to community	Community sites 12 months duration Follow up: baseline, 3, 9, 15 months	PN-LCNS group 2.70 times; LCNS 2 times. PN-only survivors 2.69 times, 3 PN-only survivors accessed the LCNS services Total Interventions: NR Mode: Telephone
4. Mercer et al⁴⁷	The Glasgow Deep End Links Worker Programme; theory of community-oriented primary care	NR	NR	Forge relationships between general practices and community organisations, and support patients to access the nonmedical services and encourage self determination	Clinics, home, Community sites 9 months duration Follow up:9 months	As required Total interventions: 868 Mode: One to one, face to face, telephone
5. Kangovi et al⁴⁸	Participatory action research framework within the domains of coaching, social support, and advocacy	One month-long training that covers topics such as action planning and motivational interviewing.	High school diploma	Helped patients identify long-term supports, -facilitated exercise, social services; sourcing lower cost medication; referral to mental health care/ drug addiction	NR 6 months duration Follow up: baseline, 6, 9 months	Min 24 contacts; Total interventions: NR Mode: Individualised or group face to face; telephone
6. Spencer et al⁴⁹	Community-based participatory research grounded in empowerment method to facilitate self-directed behaviour change	CLWs underwent 160 h of CLW training; 80 h of diabetes education; trained in empowerment-based Approaches; motivational interviewing and goal setting.	Spanish-fluent Latinas who had completed high school or had a GED	Improve communication skills, referrals to other service systems; set goals using the five-step goal-setting model	Community site 6 months duration Follow up: baseline, 6, 12, 18 months	11 × 2-h sessions every 2 weeks; 2 × 60-min home visits monthly; phone calls Total interventions: NR Mode: Individualised, group face to face;
7. Carrasquillo et al⁵⁰	Community-level framework of chronic care model; self-management support; clinical information; healthcare organisation and community resources	75-h training curriculum, type 2 diabetes clinical and behavioural interventions (20 h), including motivational interviewing training; basic research methods on human participants research (20 h); insurance navigation	Lead CLW were non-medical staff; CLW supervisor – MSc qualification	Health education, medication refills, health coaching; assisted with nonmedical services; housing, employment, legal, financial, food resources; linkages to community services, Bimonthly exercise groups.	Home; clinic; Community 12 months duration Follow up: baseline, 12 months	4 home visits, 12 calls during the 12 months & bimonthly exercise groups in parks Total interventions: home visits received- 5, Telephone calls- 20; Participants (126 (84%) received 12 CLW contacts per year Mode: Individualised, group face to face
8. Kangovi et al⁵¹	Individualised intervention to help low-income patients achieve health goals within the domains of coaching, social support, advocacy	Month-long college accredited training covering topics such as action planning and motivational interviewing. CLWs had on-the-job training with a senior CLW.	Recruited from community Qualifications: NR	3 stages: action planning, tailored support, and connection with long-term support, Weekly patient support group	Home; community 6 months duration Follow up: baseline, 6, 9 months	38.4 h with each patient over the 6-month intervention period. 35% had 3 meetings Total interventions: NR Mode: Face to face; group classes
9 .McDermott et al⁵²	Diabetes case management approach by local community-based health workers supported by indigenous teams	Intensive 3-week training in diabetes and self-management skills, advice on medications, routine foot care, nutrition, smoking cessation	Recruited from community NR	Keep appointments, medications adherence effects of smoking; work with the family to support the patient in self-management.	Home; clinic 18 months duration Follow up:18 month	Delivery: NR Total Interventions: NR Mode: Individualised face to face
10. Spencer et al⁴⁴	Using a socioecological model, family, health system, and community-level interventions were developed to address sources of diabetes disparities at each level	CLW were underwent more than 80 h of training in empowerment-based approaches; self-determination and autonomy motivation theory and interviewing	Ethnically matched with their assigned participants Qualifications: NR	Physical fitness activity- dance, walking); weekly community farmer's market; self-management skills; facilitated necessary referrals to other services	Home; community sites; clinic 12 months duration Follow up: baseline, 6, 12 months	Home visits (2 per month, 60 min); 11 culturally tailored 2-h sessions every 2 weeks; Daily calls every 2 weeks Total interventions: NR Mode: Individualised, group face to face
11.Spencer et al⁵³	Using a socioecological model, family, health system, and community-level interventions were developed to address sources of diabetes disparities at each level	CLW were underwent more than 80 h of training. CLW were trained in empowerment-based approaches including self-determination and autonomy motivation theory and interviewing	Ethnically matched with their assigned participants Qualifications: NR	Trained CLWs, known in this study as family health advocates, promoted healthy lifestyle and diabetes self-management activities as part of the ‘Reach Detroit Community program’	Home; community resource locations; clinic 12 months duration Follow up: baseline, 6 months	Home visits (2 per month, 60 min);11 culturally tailored 2-h group sessions of 8–10 participants every 2 weeks in community: Daily calls every 2 weeks Total interventions: NR Mode: Individualised and group face to face; telephone
12.Babamoto et al⁵⁴	Cultural intervention composed of diabetes education and evaluated health behaviours	6-week training curriculum on roles and responsibilities, diabetes standards, self-management strategies incorporating patient cultural and spiritual beliefs, health behaviour change theory	High school degree or a GED degree Layperson recruited locally.	10-week ADA sessions tailored to needs; knowledge, identified problems, goals, and level of progress; routine follow-up calls to monitor self-management progress, review barriers	Home; clinic 6 months duration Follow up: baseline, 6 months	Weekly individual ADA educational sessions Total interventions: 11.3 mean Mode: Telephone; face to face

CLW: community link worker; NR: not reported; PN-LCNS: Patient Navigation-Livestrong Cancer Navigation Services; PN: patient navigation; PL: peer leader; EUC: enhanced usual care; ADA: American Diabetes Association; GED: general educational development test.

Results

Electronic searches identified 5807 potential studies. After duplicates were removed (n = 444), 5363 studies were screened for title and abstract content of which 191 studies were eligible for full text screening (n = 3566). Two reviewers (DJOS, JGMcV) independently assessed the eligibility of these studies and 12 studies were selected for this review. An updated search of the literature was conducted in December 2023 but did not identify any further studies. Figure 1 outlines the PRISMA flow chart.

Figure 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) flow diagram.

Study characteristics

The selected studies were conducted in the United States of America (n = 9),^44,46,53,54 United Kingdom (n = 1),⁴⁷ Belgium (n = 1)⁵⁵ and Australia (n = 1)⁵² and were heterogeneous in design. Cancer (n = 1)⁴⁶ and diabetes (n = 7)^48–54 were the main long-term conditions identified. Comparison groups included waiting list⁵² usual care,^{45,47,48,51,54,55} enhanced care,^46,49,50 or delayed access to the intervention.^44,53 Study duration ranged from 8 weeks⁵⁵ to 18 months^49,52. The total number of participants included in the 12 studies was n = 3566, (female n = 2179, male n = 1387) with a mean age of 48 years.

Risk of bias

Overall, nine studies were judged to have a high risk of bias^{44,45,46,47,49,52–55} and three studies were judged to have low risk of bias.^48,50,51 The ‘measurement of the outcome’ presented as the greatest risk of bias in eight studies and the ‘missing outcome data’ domain had the lowest risk of bias in all 12 studies, supplementary material. There was moderate level of agreement between the two independent reviewers’ risk of bias judgements using the Kappa coefficient (K = 0.488).

Risk of bias summary judgements and judgements on outcome domains are available in supplementary materials.

Intervention characteristics

Community link-workers led the intervention in all included studies and were recruited from the community of interest. The duration of community link-worker training ranged from 4⁵⁵ to 160 h.⁴⁹ The social prescribing interventions utilised in the included studies were grounded in behavioural change theoretical frameworks and behavioural models such as social cognitive theory^45,46 self-regulation theory⁴⁵; stress and coping theory and health behaviour change theory.⁴⁶ The attrition rate across all studies was generally high and ranged from 9% to 29%. The characteristics of each study and the social prescribing intervention are summarised in Table 1.

Outcome measures used in the social prescribing intervention

Forty-one different outcome measures (self-reported, n = 33) were used to determine the effects of a social prescribing intervention on primary and secondary outcomes. The duration of social prescribing interventions ranged from 8 weeks⁵⁵ to 18 months.^49,52 Outcomes of interest were categorised as quality of life (n = 12), physical activity (n = 2), psychological wellbeing (n = 8), disease-specific outcomes (n = 17) and uncategorised (n = 2).

Effect of the social prescribing intervention on quality of life outcomes

There are short to long-term improvements in quality of life for those receiving social prescribing interventions,⁴⁶ particularly for those attending more frequently (>3 visits).⁴⁷ Mercer et al⁴⁷ (high Risk of Bias) found significant improvements in quality of life with three or more face-to-face engagements with the community link-worker intervention as measured by the EQ-5D-5L questionnaire 0.071 (95%CI, 0.016, 0.126); P < 0.011). Male and female participants with similar cancer presentations responded differently after an enhanced community link-worker led intervention.⁴⁶ Female colo-rectal cancer survivors in remission derived up to 15 months health related quality of life improvements when measured by the Functional Assessment of Cancer Therapy – General Scale (FACT – G Scale): 0.171; (95% CI, 0.025–0.317; P = 0.021) compared to males who had only short term improvement in health-related quality of life (3 months): 10.074 (95%CI, 2.030–18.119; P = 0.014).

Effect of social prescribing intervention on physical activity

Seven studies used physical activity^{45,47,48,50,51,53,54} as a primary (n = 4)^45,47,48,54 or secondary outcome (n = 3).^50,51,53 Two high Risk of Bias studies^45,54 reported significant increments in the frequency⁵⁴ of physical activity (3 times per week) from baseline n = 21(28%) to 6-month follow-up n = 47(63%) P < 0.05) and the duration of physical activity⁴⁵ (mins/week) by 141 min (95% CI 46.4, 236.4) (p < 0.004) in the community link-worker intervention group (baseline: 12 months: 271.3(mins) (421.6) to 344.2 (mins) (455.6) (+72.8) compared to controls (baseline: 12months; 240.1 (mins) (364.1) to 199.9 (mins) (350.0) (−40.2)) who regressed during the 12-month intervention. The remaining three low-Risk-of-Bias studies^48,50,51 and two high-Risk-of-Bias studies^47,53 reported significant within-group improvements only in physical activity levels. There is some evidence from a subgroup analyses conducted in one high Risk of Bias study⁴⁷ that participants attending the ‘Glasgow Deep End’ community link-worker intervention more frequently (>3 in person visits) showed small but significant within-group improvements only in self-reported exercise levels over time 0.339 (95%CI, 0.071−0.607); P < 0.013).

Effect of the social prescribing intervention on psychological wellbeing outcomes

Three studies^47,48,55 two high Risk of Bias^47,55 and one low Risk of Bias⁴⁸ used indicators of psychological wellbeing as either primary⁵⁵ (emotional support, social isolation, anxiety measured by the PROMIS score) or secondary outcomes^47,48 (Short Form 12-Mental⁵⁶ and Hospital Anxiety Depression Scale (HADS-Anxiety / HADS-Depression)⁵⁷)). Two studies^48,55 did not demonstrate any significant between-group improvements in psychological wellbeing for participants of a community link-worker intervention. However, participants from Mercer et al⁴⁷ study that met face-to-face with the community link-worker more than three times did show significant between-group improvement in their HADS-Anxiety score (−1.380)(95%CI, −2.339, −0.421); P < 0.005) and HADS – Depression score (−1.280)(95%CI, −2.209, −0.352; P < 0.007) but overall, did not demonstrate any significant effects on this outcome at the end of the trial.

Effect of the social-prescribing intervention on disease-specific measures

HbA1c test measures the percentage of haemoglobin proteins in the blood that are saturated with glucose (normal: <42 mmol/mol (6%)). The HbA1c test is a direct indicator of long-term glycaemic control that correlates well with complications arising from diabetes.⁵⁸ Seven studies^48–54 explored the effect of a community link-worker intervention on HbA1c blood levels in patients with diabetes as a primary outcome (n = 6)^49–54 or as a secondary outcome (n = 1).⁴⁸ Four studies^49,50,52,53 reported significant between-group improvements in HbA1c levels at 6 months;^49,53 12 months^49,50 and 18 months^49,52.

Due to the heterogeneity of the intervention and outcome reporting, it was only possible to conduct a meta-analysis on the pooled data from four studies (n = 1329), 2 low Risk of Bias^48,51 and 2 high Risk of Bias^49,52 to compare the effects of community link worker interventions on individuals’ HbA1c levels from baseline to 18 months. The respective calculated effect sizes are displayed in Figure 2. The forest plot (red dashed line) indicates a small non-significant effect of −0.07 (95% CI −0.23, 0.10): P = 0.31. The Tau-square test represented the variance of the effect size across the studies, the value of 0 means that there is no significant between-study variance beyond what would be expected by chance alone.

Figure 2.

Meta-analysis of social prescribing intervention on haemoglobin A1C (HbA1c) levels in diabetic patients.

Four studies,^44,49,53,54 three of which were from the same author^44,49,53 and all having high Risk of Bias^44,49,53,54 used eight separate diabetes-specific patient-reported outcome measures to determine the effectiveness of a community link-worker intervention on diabetes-related distress, depression, self-management and self-efficacy required to control diabetes. Spencer et al^44,49,53 examined the levels of distress experienced by people with diabetes using the Problem Areas in Diabetes Scale in two early studies^44,53 and later the Diabetes Distress Scale.⁴⁹ The first of these studies⁵³ did not find any significant change between the community link-worker group and the control. However, in the later 12-month study,⁴⁴ after adjusting for demographic variables the authors reported significant changes in the intervention group (n = 72) at baseline 23.8 (95% CI, 18.7, 29.0) and six months −6.5 (95% CI, −11.2, −0.04); P < 0.05) and 6–12 months −7.8 (95% CI, −12.5, −1.4); P < 0.05) compared to the delayed intervention group (n = 92) at baseline 25.9 (95%CI, 21.2, 30.6) and six months (−1.7 (95% CI, −7.0, 5.3); P > 0.05) and 6–12 months −6.2 (95%CI, −11.0, 0.2); P > 0.05). These findings are again supported in another later study⁴⁹ using the Diabetes Distress Scale which demonstrated significant reduction in diabetes-related distress of −0.4 (95%CI, −0.7, −0.1); P < 0.05) for up to 18-months in the community link-worker group only. Spencer et al^44,49 also examined the effectiveness of a community link-worker intervention on diabetes-related depression using the Patient Health Questionairre-9.⁵⁹ In the latter of these two studies individuals randomised to the extended peer-led community link-worker intervention (6–18 months) demonstrated significant decrements in depressive episodes at 18 months −2.2 points (95% CI −4.1, −0.3) P < 0.05) compared to the enhanced usual care group. The effectiveness of Community link-worker interventions on diabetes self-management was measured in three studies^49,53,54 by the Diabetic Care Profile,⁶⁰ Summary of Diabetes Self-Care Activities Measure⁶¹ and the Diabetes Knowledge Scale.⁶² The Diabetic Care Profile⁶⁰ used by Spencer et al⁴⁹ which assesses a patients’ understanding of the social and psychological factors related to the self-management of diabetes reported the extended peer-led community link-worker group demonstrated a significant between-group improvement of 0.3 points (95% CI, 0.1, 0.6); P < 0.05) after 12 months against the enhanced usual care group but not the community link- worker only group. The Diabetes Knowledge Scale was used in one study only⁵⁴. Significant between-group results were reported at the 6-month follow-up for community link-worker intervention versus case management versus standard care (P < 0.05). Spencer et al^49,53 were the only studies to examine the effectiveness of community link-worker interventions on diabetes-related self-efficacy utilising the Perceived Competence of Diabetes Scale⁶³ and Diabetes Social Support,⁶⁴ respectively. At 6 months’ time point diabetes self-efficacy was significantly improved 0.5 (95%CI, 0.2,0.8); P < 0.01) in the community link-worker group only⁴⁹.

Five studies^{48,50,51,53,54} investigating the effect of a community link-worker intervention on body mass index,^50,51,54 cholesterol^48,50,53 and blood pressure^48,50 did not report any significant within group or between group changes across the trial periods.

Discussion

The aim of this systematic review was to determine the effectiveness of social prescribing in the management of long-term conditions in community-based adults. To the best of our knowledge, this is the first systematic review to conduct a meta-analysis of the data on the effectiveness of social prescribing focusing on outcomes that reflect the multifactorial nature of long-term conditions. Twelve randomised controlled trials across different geographical locations, in areas of socioeconomic deprivation, were included in this review. Most studies included in this review utilised a tailored social prescribing model directed at improving diabetes self-management. This review found some evidence to support the effectiveness of social prescribing in improving quality of life and disease-specific outcome measures. There is some evidence that adherence to a social prescribing intervention may result in positive outcomes for the participant. Most significant improvements were in reducing diabetes-related distress; diabetes-related depressive episodes and improving diabetes self-management efficacy. Given the heterogeneity of the included studies and outcome measures and like previous review conclusions^19,36,37 it is not possible to determine the effectiveness of social prescribing in the management of long-term conditions in community-based adults.

The results of this review suggest that an enhanced social prescribing intervention with increased uptake of support services provided over a longer duration will lead to improvements in both short and long-term quality of life outcomes.^47,65 As females reported longer-term improvements (15 months) there may be other factors influencing the gender response to the social prescribing intervention. This contrasts with previous evidence that found men with poor health, anxiety, and social networks had greater benefit from social prescribing interventions than women⁶⁶ and may be explained by the possible gender differences in coping strategies of cancer patients.⁶⁷ It is unclear if there is a gender response to social prescribing which is a possible area for future research.

There is some evidence from this review that participating in a social prescribing intervention can significantly influence a participant's uptake of physical activity in the short term⁵⁴ and also the weekly duration of physical activity in the long-term⁴⁵ helping participants with controlled diabetes meet recommended physical activity guidelines⁶⁸ with minimal support.⁴⁵ Other studies within this review^48,50,51,53 also demonstrated significant improvements in physical activity but within group only. The control groups also receiving physical activity advice and access to free services e.g., dance classes, exercise classes and walking groups may explain these improvements. No study in the present review utilised external activity monitors e.g., pedometers that would provide objective measures of activity and eliminate response bias. Social prescribing interventions did not demonstrate any significant between-group changes in psychological well-being in participants experiencing anxiety and depression^44,47 or in patients with limited social network.⁵⁵ High dropout rates and lack of reporting on intervention adherence makes it difficult to interpret these results with confidence.

The results from individual studies^{44,45,49–54} within this review suggest that targeted disease-specific community link-worker interventions can significantly improve HbA1c levels in patients with diabetes in the short (six months) and long-term (18 months) to those recommended by the American diabetes guidelines.⁶⁹ However, when the data from suitable studies^48,49,51,52 were pooled in a meta-analysis the results showed social prescribing interventions had only a small non-significant impact on HbA1c levels at six months (P = 0.31). This finding is contrasted in a recent large-scale study⁷⁰ which found a small statistically significant reduction in HbA1c (−1.11 mmol/mol) (95% CI: −1.878, −0.342); P < 0.05), however, the authors concluded this was not sufficient to be clinically significant, thus echoing our results. Psychological co-morbidities are common in people with physical long-term conditions^71,72 and may influence the lifelong trajectory of their illness.^73,74 This review has highlighted some evidence to support the role of social prescribing in significantly improving disease-related distress,⁴⁹ depression,⁴⁴ self-management knowledge⁵⁴ and self-efficacy⁵³ which play an integral role in patient empowerment.^75,76 The heterogeneity and unblinding of outcome measures (n = 41) used to measure the effect of the intervention on quality of life, physical activity, psychological wellbeing and disease-specific parameters lessens the credibility of their findings and made evidence synthesis challenging. Outcome reporting bias and inconsistency in the measurement of outcomes could be minimised through the development^77,78 and reporting⁷⁹ of standardised core outcome sets with established Minimal Clinical Important Difference values similar to other areas.⁸⁰ This review has identified key factors that may influence future clinical practice; targeted and enhanced social prescribing interventions improve self-management and self-efficacy of long-term conditions; the use of technology in the measurement of physical activity should support self-reported measures of physical activity in social prescribing interventions.

It should be noted that there are some limitations with this review. Firstly, only studies published in the English language were considered for inclusion, it is possible some studies published in another language were missed. Secondly, while the search strategy was comprehensive, including nine databases, three trial registries and the grey literature, it could be argued that the range of keywords used could have been more extensive. It is possible that using specific conditions and outcome measures may have resulted in a more focused search and perhaps additional papers. Notwithstanding this, we are confident we have identified all relevant papers.

This comprehensive systematic review only includes quasi-randomised and randomised controlled trials whose study design matches the current definition of social prescribing²³ and is the first review of social prescribing to use a meta-analysis to analyse the data. The studies included within our review were heterogeneous in terms of patient populations, interventions delivered, and outcome measures used, which substantially influences the ability to make meaningful comparisons. This review suggests that social prescribing interventions designed to target specific long-term conditions, i.e., cancer and diabetes, demonstrated significant improvements in quality of life and disease-specific psychological outcomes respectively. There was some evidence for improvement in physical activity levels, but most findings were within-group changes only. Social prescribing interventions did not demonstrate any significant changes in psychological well-being. The findings from this review suggest it is not possible to determine the effectiveness of social prescribing in the management of long-term conditions.

Clinical messages

Tailored social prescribing interventions improved quality of life in cancer remission patients.

Social prescribing interventions improved diabetes-specific psychological outcomes.

Social prescribing interventions may improve the frequency and duration of physical activity in people with diabetes.

Supplemental Material

sj-docx-1-cre-10.1177_02692155241258903 - Supplemental material for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis

Supplemental material, sj-docx-1-cre-10.1177_02692155241258903 for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis by Declan J O’Sullivan, Lindsay M Bearne, Janas M Harrington, Jefferson R Cardoso and Joseph G McVeigh in Clinical Rehabilitation

Supplemental Material

sj-docx-2-cre-10.1177_02692155241258903 - Supplemental material for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis

Supplemental material, sj-docx-2-cre-10.1177_02692155241258903 for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis by Declan J O’Sullivan, Lindsay M Bearne, Janas M Harrington, Jefferson R Cardoso and Joseph G McVeigh in Clinical Rehabilitation

Supplemental Material

sj-docx-3-cre-10.1177_02692155241258903 - Supplemental material for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis

Supplemental material, sj-docx-3-cre-10.1177_02692155241258903 for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis by Declan J O’Sullivan, Lindsay M Bearne, Janas M Harrington, Jefferson R Cardoso and Joseph G McVeigh in Clinical Rehabilitation

Supplemental Material

sj-docx-4-cre-10.1177_02692155241258903 - Supplemental material for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis

Supplemental material, sj-docx-4-cre-10.1177_02692155241258903 for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis by Declan J O’Sullivan, Lindsay M Bearne, Janas M Harrington, Jefferson R Cardoso and Joseph G McVeigh in Clinical Rehabilitation

Supplemental Material

sj-pdf-5-cre-10.1177_02692155241258903 - Supplemental material for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis

Supplemental material, sj-pdf-5-cre-10.1177_02692155241258903 for The effectiveness of social prescribing in the management of long-term conditions in community-based adults: A systematic review and meta-analysis by Declan J O’Sullivan, Lindsay M Bearne, Janas M Harrington, Jefferson R Cardoso and Joseph G McVeigh in Clinical Rehabilitation

Footnotes

Author contributions

Concept/idea/research design were done by D.J OS., J.M H., L.M B., and J.G McV. Writing Review and Editing were done by D.J OS., J.M H., L.M B., J.G McV., and J.R C. Data collection was done by D.J OS. and J.G McV. Data analysis was done by D.J OS., J.G McV. and J.R C. Project management was done by D.J OS. and J.G McV. Providing institutional liaisons was done by J.G McV. Consultation (including review of manuscript before submitting) was done by J.M H, L.M B., J.G McV. and J.R C.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Jefferson R Cardoso

Declan J O’Sullivan

Systematic review registration

The protocol was registered with the Open Science Framework

Supplemental materials

Please find the following supplemental material visualised and available to download via Figshare in the hyperlink below. Where there are more than one item, you can scroll through each tab to see each separate item 10.6084/m9.figshare.24099798

References

Hafezparast

Turner

Dunbar-Rees

, et al. Adapting the definition of multimorbidity – development of a locality-based consensus for selecting included long term conditions. BMC Fam Pract 2021; 22: 124. 20210623.

Barnett

Mercer

Norbury

, et al. Epidemiology of multimorbidity and implications for health care, research, and medical education: A cross-sectional study. Lancet 2012; 380: 37–43.

Goodman

Posner

Huang

, et al. Defining and measuring chronic conditions: Imperatives for research, policy, program, and practice. Prev Chronic Dis 2013; 10: E66. 20130425.

Dhere

. Managing complex long-term conditions and multimorbidity. Clin Med (London, England) 2016; 16: 545–547.

Sparks

. Rheumatoid arthritis. Ann Intern Med 2019; 170: Itc1–Itc16.

Lloyd

Sawyer

Hopkinson

. Impact of long-term complications on quality of life in patients with type 2 diabetes not using insulin. Value Health 2001; 4: 392–400.

Nazarinasab

Motamedfar

Moqadam

. Investigating mental health in patients with osteoarthritis and its relationship with some clinical and demographic factors. Reumatologia 2017; 55: 183–188. 2017/08/31.

Sharma

Kudesia

Shi

, et al. Anxiety and depression in patients with osteoarthritis: Impact and management challenges. Open Access Rheumatol: Res Rev 2016; 8: 103–113.

Marengoni

Angleman

Melis

, et al. Aging with multimorbidity: A systematic review of the literature. Ageing Res Rev 2011; 10: 430–439. 20110323..

10.

Fortin

Lapointe

Hudon

, et al. Multimorbidity and quality of life in primary care: A systematic review. Health Qual Life Outcomes 2004; 2: 51. 20040920..

11.

Walker

. Multiple chronic diseases and quality of life: Patterns emerging from a large national sample, Australia. Chronic Illn 2007; 3: 202–218.

12.

Sundstrup

Jakobsen

Mortensen

, et al. Joint association of multimorbidity and work ability with risk of long-term sickness absence: A prospective cohort study with register follow-up. Scand J Work Environ Health 2017; 43: 146–154. 20170106..

13.

Buja

Rivera

De Battisti

, et al. Multimorbidity and hospital admissions in high-need, high-cost elderly patients. J Aging Health 2020; 32: 259–268. 20181206..

14.

Zhang

, et al. Relationship between multimorbidity, disease cluster and all-cause mortality among older adults: A retrospective cohort analysis. BMC Public Health 2021; 21: 1080. 20210605..

15.

Salisbury

Man

Bower

, et al. Management of multimorbidity using a patient-centred care model: A pragmatic cluster-randomised trial of the 3D approach. Lancet 2018; 392: 41–50. 20180629..

16.

Wang

HHX

, et al. Healthcare needs, experiences and treatment burden in primary care patients with multimorbidity: An evaluation of process of care from patients’ perspectives. Health Expect 2022; 25: 203–213. 20210928..

17.

Wood

Ohlsen

Fenton

S-J

, et al. Social prescribing for people with complex needs: A realist evaluation. BMC Fam Pract 2021; 22: 53.

18.

O'Sullivan

Bearne

Harrington

, et al. Can social prescribing put the ‘social’ into the biopsychosocial management of people with long-term musculoskeletal disorders? Musculoskeletal Care 2023; 21: 1341–1352.

19.

Chatterjee

Camic

Lockyer

, et al. Non-clinical community interventions: A systematised review of social prescribing schemes. Arts Health 2017; 10: 97–123.

20.

Jensen

Stickley

Torrissen

, et al. Arts on prescription in scandinavia: A review of current practice and future possibilities. Perspect Public Health 2016; 137: 268–274.

21.

Heijnders

Meijs

. ‘Welzijn op recept’ (social prescribing): A helping hand in re-establishing social contacts - an explorative qualitative study. Prim Health Care Res Dev 2018; 19: 223–231.

22.

Bertotti

Frostick

Hutt

, et al. A realist evaluation of social prescribing: An exploration into the context and mechanisms underpinning a pathway linking primary care with the voluntary sector. Prim Health Care Res Dev 2018; 19: 232–245. 2017/12/08..

23.

Polley. Social Prescribing Network Conference Report 2016 UK. 2015 2016.

24.

Goodwin

. Understanding integrated care. Int J Integr Care 2016; 16: 6. 20161028..

25.

Bickerdike

Booth

Wilson

, et al. Social prescribing: Less rhetoric and more reality. A systematic review of the evidence. BMJ Open 2017; 7: e013384.

26.

While

. The benefits of social prescribing. Br J Community Nurs 2016; 21: 266–266.

27.

Alderwick

HAJ

Gottlieb

Fichtenberg

, et al. Social prescribing in the U.S. and England: Emerging interventions to address Patients’ social needs. Am J Prev Med 2018; 54: 715–718.

28.

Loftus

McCauley

McCarron

. Impact of social prescribing on general practice workload and polypharmacy. Public Health 2017; 148: 96–101.

29.

Hassan

Giebel

Morasae

, et al. Social prescribing for people with mental health needs living in disadvantaged communities: The life rooms model. BMC Health Serv Res 2020; 20: 19–19.

30.

Stickley

Eades

. Arts on prescription: A qualitative outcomes study. Public Health 2013; 127: 727–734. 2013/07/23..

31.

Williams

Hendry

France

, et al. Effectiveness of exercise-referral schemes to promote physical activity in adults: Systematic review. Br J Gen Pract 2007; 57: 979–986.

32.

Hacking

Secker

Spandler

, et al. Evaluating the impact of participatory art projects for people with mental health needs. Health Soc Care Community 2008; 16: 638–648. 2008/05/20..

33.

Potter

. Arts on prescription 2010 −2012 evaluation report: Executive summary. Cambridge: Arts and Minds. 2013.

34.

Potter

. Arts on prescription 2014-2015 evaluation report. Cambridge: Arts and Minds. 2015.

35.

Lamb

Bartlett

Ashley

, et al. Can lay-led walking programmes increase physical activity in middle aged adults? A randomised controlled trial. J Epidemiol Community Health 2002; 56: 246–252. 2002/03/16..

36.

Pescheny

Randhawa

Pappas

. The impact of social prescribing services on service users: A systematic review of the evidence. Eur J Public Health 2020; 30: 664–673.

37.

Vidovic

Reinhardt

Hammerton

. Can social prescribing foster individual and community well-being? A systematic review of the evidence. Int J Environ Res Public Health 2021; 18: 5276.

38.

Percival

Newton

Mulligan

, et al.

Systematic review of social prescribing and older adults: Where to from here?

Fam Med Community Health 2022; 10: e001829.

39.

Moher

Liberati

Tetzlaff

, et al. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Br Med J 2009; 339: b2535.

40.

Covidence. Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org 2020.

41.

Higgins

JPT

Altman

Gøtzsche

, et al. The cochrane collaboration's tool for assessing risk of bias in randomised trials. BMJ (Clinical Research ed) 2011; 343: d5928–d5928.

42.

Röver

Knapp

Friede

. Hartung-Knapp-Sidik-Jonkman approach and its modification for random-effects meta-analysis with few studies. BMC Med Res Methodol 2015; 15: 99.

43.

Meta-analysis 2023, IBM Corp. 2023. IBM SPSS Statistics for Windows (Version 29), Chicago, IL, accessed 1 Dec 2023. https://www.ibm.com/docs/en/spss-statistics/saas?topic=features-meta-analysis/.

44.

Spencer

Hawkins

Espitia

, et al. Influence of a community health worker intervention on mental health outcomes among low-income latino and African American adults with type 2 diabetes. Race Soc Probl 2013; 5: 137–146. 2013/06/01..

45.

Gray

Hoerster

Taylor

, et al. Improvements in physical activity and some dietary behaviors in a community health worker-led diabetes self-management intervention for adults with low incomes: Results from a randomized controlled trial. Transl Behav Med 2021; 11: 2144–2154.

46.

Ramirez

Choi

Munoz

, et al. Assessing the effect of patient navigator assistance for psychosocial support services on health-related quality of life in a randomized clinical trial in latino breast, prostate, and colorectal cancer survivors. Cancer 2020; 126: 1112–1123. Journal Article; Randomized Controlled Trial; Research Support, N.I.H., Extramural..

47.

Mercer

Fitzpatrick

Grant

, et al. Effectiveness of community-links practitioners in areas of high socioeconomic deprivation. Ann Fam Med 2019; 17: 518–525.

48.

Kangovi

Mitra

Norton

, et al. Effect of community health worker support on clinical outcomes of low-income patients across primary care facilities: A randomized clinical trial. JAMA Intern Med 2018; 178: 1635–1643. 2018/11/14..

49.

Spencer

Kieffer

Sinco

, et al. Outcomes at 18 months from a community health worker and peer leader diabetes self-management program for latino adults. Diabetes Care 2018; 41: 1414–1422. 2018/04/29..

50.

Carrasquillo

Lebron

Alonzo

, et al. Effect of a community health worker intervention among latinos with poorly controlled type 2 diabetes: The Miami healthy heart initiative randomized clinical trial. JAMA Intern Med 2017; 177: 948–954. 2017/05/02..

51.

Kangovi

Mitra

Grande

, et al. Community health worker support for disadvantaged patients with multiple chronic diseases: A randomized clinical trial. Am J Public Health 2017; 107: 1660–1667. 2017/08/18..

52.

McDermott

Schmidt

Preece

, et al. Community health workers improve diabetes care in remote Australian indigenous communities: Results of a pragmatic cluster randomized controlled trial. BMC Health Serv Res 2015; 15: 68. 2015/04/18.

53.

Spencer

Rosland

A-M

Kieffer

, et al. Effectiveness of a community health worker intervention among African American and Latino adults with type 2 diabetes: A randomized controlled trial. Am J Public Health 2011; 101: 2253–2260. 2011/06/16.

54.

Babamoto

Sey

Camilleri

, et al. Improving diabetes care and health measures among hispanics using community health workers: Results from a randomized controlled trial. Health Educ Behav 2009; 36: 113–126. 2009/02/04.

55.

Bossche

Lagaert

Willems

, et al. Community health workers as a strategy to tackle psychosocial suffering due to physical distancing: A randomized controlled trial. Int J Environ Res Public Health 2021; 18: 1–16. Article.

56.

Ware Jr

Kosinski

Keller

. A 12-item short-form health survey: Construction of scales and preliminary tests of reliability and validity. Med Care 1996; 34: 220–233. 1996/03/01.

57.

Bjelland

Dahl

Haug

, et al. The validity of the hospital anxiety and depression scale. An updated literature review. J Psychosom Res 2002; 52: 69–77.

58.

Sherwani

Khan

Ekhzaimy

, et al. Significance of HbA1c test in diagnosis and prognosis of diabetic patients. Biomark Insights 2016; 11: 95–104.

59.

Kroenke

Spitzer

Williams

. The PHQ-9: Validity of a brief depression severity measure. J Gen Intern Med 2001; 16: 606–613.

60.

Fitzgerald

Davis

Connell

, et al. Development and validation of the diabetes care profile. Eval Health Prof 1996; 19: 208–230.

61.

Toobert

Hampson

Glasgow

. The summary of diabetes self-care activities measure: Results from 7 studies and a revised scale. Diabetes Care 2000; 23: 943–950.

62.

Hsieh

Chen

, et al. Validation of diabetes knowledge questionnaire (DKQ) in the Taiwanese population - concurrent validity with diabetes-specific quality of life questionnaire module. Diabetes Metab Syndr Obes 2022; 15: 2391–2403. 20220809.

63.

Mohn

Graue

Assmus

, et al. Self-reported diabetes self-management competence and support from healthcare providers in achieving autonomy are negatively associated with diabetes distress in adults with type 1 diabetes. Diabet Med 2015; 32: 1513–1519. 20150704..

64.

La Greca

Bearman

. The diabetes social support questionnaire-family version: Evaluating adolescents’ diabetes-specific support from family members. J Pediatr Psychol 2002; 27: 665–676.

65.

Ramirez

Gallion

Perez

, et al. Improving quality of life among latino cancer survivors: Design of a randomized trial of patient navigation. Contemp Clin Trials 2019; 76: 41–48. Clinical Trial Protocol; Journal Article; Randomized Controlled Trial; Research Support, N.I.H., Extramural..

66.

Woodall

Trigwell

Bunyan

A-M

, et al. Understanding the effectiveness and mechanisms of a social prescribing service: A mixed method analysis. BMC Health Serv Res 2018; 18: 04.

67.

Oppegaard

Dunn

Kober

, et al. Gender differences in the use of engagement and disengagement coping strategies in patients with cancer receiving chemotherapy. Oncol Nurs Forum 2020; 47: 586–594.

68.

Harrington

Henson

. Physical activity and exercise in the management of type 2 diabetes: Where to start? Practical Diabetes 2021; 38: 35–40.

69.

Diabetes A

. Standards of medical care in diabetes—2014. Diabetes Care 2013; 37: S14–S80.

70.

Moffatt

Wildman

Pollard

, et al. Impact of a social prescribing intervention in North East England on adults with type 2 diabetes: The SPRING_NE multimethod study. Public Health Research 2023; 11: 2.

71.

Anderson

Freedland

Clouse

, et al. The prevalence of comorbid depression in adults with diabetes: A meta-analysis. Diabetes Care 2001; 24: 1069–1078.

72.

Barth

Schumacher

Herrmann-Lingen

. Depression as a risk factor for mortality in patients with coronary heart disease: A meta-analysis. Psychosom Med 2004; 66: 802–813.

73.

Leung

Fan

Mahadevan

. How do different chronic condition comorbidities affect changes in depressive symptoms of middle aged and older adults? J Affect Disord 2020; 272: 46–49.

74.

Lotfaliany

Bowe

Kowal

, et al. Depression and chronic diseases: Co-occurrence and communality of risk factors. J Affect Disord 2018; 241: 461–468.

75.

Wang

Zhou

, et al. Patient empowerment and self-management behaviour of chronic disease patients: A moderated mediation model of self-efficacy and health locus of control. J Adv Nurs 2022; 78: 1055–1065. 20211013..

76.

Fromer

. Implementing chronic care for COPD: Planned visits, care coordination, and patient empowerment for improved outcomes. Int J Chron Obstruct Pulmon Dis 2011: 605–614.

77.

Kirkham

Davis

Altman

, et al. Core outcome set-STAndards for development: The COS-STAD recommendations. PLoS Med 2017; 14: e1002447. 20171116..

78.

Remus

Smith

Wuytack

. Methodology in core outcome set (COS) development: The impact of patient interviews and using a 5-point versus a 9-point Delphi rating scale on core outcome selection in a COS development study. BMC Med Res Methodol 2021; 21: 10.

79.

Gargon

Gorst

Williamson

. Choosing important health outcomes for comparative effectiveness research: 5th annual update to a systematic review of core outcome sets for research. PLoS One 2019; 14: e0225980.

80.

Williamson

Altman

Bagley

, et al. The COMET handbook: Version 1.0. Trials 2017; 18: 280. 20170620..

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB

0.27 MB

0.02 MB

0.10 MB