Table 3 Studies examining disparities in participation or attrition from SM interventions, stratified by quality1.
Author2 | Country and setting | Study Design | Chronic Disease | Sample size | Intervention | Variables measured | Results | Quality rating |
|---|---|---|---|---|---|---|---|---|
Poduval 2018 (Murray 2017) | UK Urban public primary care practices | Subgroup analysis of RCT | Diabetes | 299 (intervention group) | Comparing 2 internet SM programmes +/− support Predictors of use | Gender, age, ethnicity, education. | No difference in frequency of programme use or registration according to any demographic predictors. User characteristics were reflective of the overall target population of the area. | JBI 12/12 S/O 10/11 |
Thorn 2011 (Day 2010) | USA Rural public primary care practices | Subgroup analysis of RCT | Chronic pain | 109 | Low-literacy pain SM (education and CBT) groups. Drop-out predictors | Demographics, literacy, pain catastrophising, disability, depression, QOL, pain intensity/interference. | Dropout before programme started was associated with low education (p < 0.02), low literacy (p < 0.05) and catastrophising (p < 0.01); failure to complete programme associated with income (under/over $13,000 – p < 0.01) and low education (p < 0.02). | JBI 12/12 S/O 9/11 |
Dattalo 2012 (Boult 2011) | USA Primary care (both insured and public patients) | Subgroup analysis of RCT | Multimorbid chronic disease | 241 | Stanford CDSMP Completion predictors | Demographics, health status, health activities, patient activation, patient-rated quality of care. | 22.8% of eligible adults completed (attended at least 5 of 6 sessions). Attendance was associated with dissatisfaction with GP (OR = 2.8) and having higher SF-36 physical health scores (OR = 2.3). Age, sex, education, race and SES were not significant. | JBI 11/12 S/O 5/11 |
Cauch-Dudek 2014 | Canada National database analysis | Cohort | Diabetes –first 8/12 post diagnosis | 46,553 | Any type of DSME Participation predictors | Age, sex, immigrant status, comorbidity, mental illness, rural residence, SES | 22% of people attended DSME within 8/12 of diagnosis. Non- attendance was associated with older age, lower SES, recent immigration or physical/mental health comorbidity (all p < 0.001). | JBI 10/11 |
Adjei-Boakye 2018 | USA National telephone survey | Cross-sectional | Diabetes | 84,179 | Any type of diabetes SM education (DSME) Participation predictors | Race, education, marital status, income, sex, health insurance, BMI, insulin use, self-care behaviour. | 53.7% reported attending DSME, with attendance less likely amongst men (adjusted OR = 0.85), Hispanics (aOR = 0.81), high school only (aOR = 0.71) or less than high school educated (aOR = 0.51), income <$15,000 (aOR = 0.70) or < $25,000 (aOR = 0.81) and the uninsured (aOR = 0.87). Attending DSME was significantly associated with adherence to SM behaviours. | JBI 8/8 |
Glasgow 2018 | USA Database analysis (health insurance organisation) | Cross-sectional | Diabetes | 2603 | Internet SM programme Participation predictors | Socio-demographics, reason for declining service, HbA1c BP, BMI, lipids, SF36, ADL, number of comorbidities | Participants were likely to be younger (p = 0.041); not Latino (p = 0.002); earning >$30,000 (p < 0.0001), greater than high school educated (p < 0.0001), non-smokers (p < 0.0001) with lower blood pressure (p = 0.028). Self-selected participants were the most likely to be white, better educated and healthier. | JBI 8/8 |
Horrell 2017 | USA National database analysis | Cross-sectional | Multimorbid chronic disease | 19,365 | Stanford CDSMP Participation and completion predictors | Enrolment and completion of CDSMP compared to high/low SES area | 83.6% of participants lived in the least impoverished areas (< 25% of population below poverty line) and 0.3% of participants lived in the most impoverished areas (> 50% below poverty line). SE area was significantly correlated with ethnicity and education level. Course completion was not associated with SES – poorer people had a higher (but non-significant) completion rate. | JBI 8/8 |
Hardman 2018 | Australia Rural community health centre | Cross-sectional | Chronic pain | 186 | Tailored pain SM Drop-out predictors | Demographics, self-efficacy, pain catastrophising, opioid dose, comorbidities. | Early dropout associated with social stressors (p = 0.002/0.029, OR = 0.08/0.30); pain causal beliefs (p = 0.005, OR = 5.01) and pain catastrophising (p = 0.048, OR = 1.03) Low income significant in bivariate analysis (p = 0.011) only. | JBI 8/8 |
Kure-Beigel 2016 | Denmark Urban community health centre | Mixed:Cross-sectional + qualitative | Diabetes, COPD or CVD | 104 | Tailored SMS Drop-out predictors | Education, age, gender, cohabitation, whether 1st meeting cancelled. | Non-completion associated with younger age (below 60) (p = 0.03, OR = 3.38). Non-significant trend of lower education associated with lack of completion. Qualitative study suggested comorbidity and low job control in low educated were factors. | JBI 8/8 |
Santorelli 2017 | USA State-wide telephone survey (New Jersey) | Cross-sectional | Diabetes | 4358 | Any type of DSME Participation predictors | Age, sex, race, income. | 42% reported attending DSME, with attendance less likely amongst lower educated (high school or less), Hispanic or ‘other’ ethnicity, those diagnosed under 2 years ago (all p < 0.001); the uninsured (p < 0.004) and those without a HCP visit for diabetes in the past year (p < 0.002). DSME attendance was not correlated to the number of certified DSME courses available in the area. | JBI 6/8 |