Despite being challenged in recent years, the hypothesis that individuals of higher socioeconomic status (SES) are more physically active than their lower SES counterparts is generally considered a fact. Recent reviews, however, have suggested that differences across groups might be related to which physical activity (PA) domains have been investigated. In the present review, searches for relevant studies were performed in the MEDLINE, ISI Web of Knowledge and SPORTDiscus databases. Search terms included “socioeconomic”, “socio-economic”, “socio economic” and “social class” to meet all variations of the variable “socioeconomic status” in combination with the term “physical activity”. Studies were included when applying the dimensions of intensity, frequency, type/mode, and duration in measuring PA. Fifty-six studies were included and were subsequently split into four PA domains: transport PA (TPA), occupational PA (OPA), housing PA (HPA) and leisure time PA (LTPA). It turned out that the positive relationship held only for LTPA, whereas the relationship was non-existent or even opposite for all other domains. It is concluded that the assumed positive relationship between SES and PA is mainly a relationship between LTPA and SES. It is further suggested that the PA domain should always be considered when studying said relationships.

Traditional methods measuring physical activity (PA) may misrepresent breast cancer survivors (BCSs) and low-socioeconomic status (SES) groups. This study identifies PA-levels, routines and experiences among BCSs, in general and by SES, and explores whether a mixed-methods approach might unveil diversities of PA in BCS across SES. 250 BCSs referred to postoperative radiation therapy in 2007-2008 participated in a longitudinal follow-up study examining health-related quality-of-life and late-effects. Subsample-data on SES and PA were collected by questionnaires (n = 52), activity-logs (n = 52) and interviews (n = 37). Parallel mixed analyses were conducted, in combination with sequential, full-sample analyses of questionnaires and contrasting case analyses of logs and interviews. Dependent on which measurement used, 23%, 35%, 54% and 63% of BCSs met PA guidelines. Questionnaire-data revealed no significant differences in PA levels between SES groups. Log-data showed more PA bouts in high-SES BCSs, but no difference in min/week across SES. Neighbourhood walking was preferred, while scheduled exercise was rare. Interview-data added that PA was medicating, normatively described and accompanied by unfulfilled ambitions, particularly in low-SES BCSs. Balancing duties and activities was demanding. PA constraints were similar across groups. Domestic PA was important in low-SES, while high-SES BCSs described more energy. Although PA levels among BCSs were similar across SES and equal to PA in the general population, SES differences became evident when measured by activity-logs and as stated in interviews. Future follow-up programs for BCSs could benefit from expanding the PA perspectives, thus better meet the needs of different SES groups.

Exercise could reduce the side-effects of adjuvant breast cancer treatment; however, socio-demographic, health, and intervention conditions may affect patients’ adherence to interventions. This study aimed to examine adherence to a 12-month outdoor post-surgery exercise program among newly diagnosed breast cancer patients during adjuvant treatment, and to identify socio-demographic and health-related predictors. In total, 47 women with invasive breast cancer stage I–II or ductal/lobular carcinoma grade 3 were included pre-surgery and randomized two weeks post-surgery to exercise (2 × 60 min/week). Patient characteristics (body-mass index (BMI), socioeconomic status, comorbidity, physical activity, and maximal oxygen uptake (VO2max)) were recorded pre-surgery. Correlations between adherence and patient characteristics and statistics for between-group differences were performed. The mean age was 54.2 years, mean BMI 27.8 kg/m², and 54.2% received chemotherapy. Completers had a mean adherence of 81%, independent of season. Withdrawals (23%) occurred after a mean of 6.5 weeks (0–24 weeks), they were suggestively older, had lower socioeconomic status and pre-surgery VO2max, and higher BMI. Household income was significantly lower among withdrawals. There were insignificant correlations between adherence and health conditions. High adherence is achievable in a Nordic outdoor physical exercise program in breast cancer patients during adjuvant treatment, including chemotherapy. Additional studies are needed to clarify follow-up needs in some groups.

Objectives: Representativeness in physical activity randomised controlled trials (RCT) in breast cancer patients is essential to analyses of feasibility and validity considering privileged- social groups. A step-by-step exclusion of less privileged groups through the trial process could reinforce health inequality. This study aimed at examining representativeness in breast cancer (BC) physical activity trials, investigate associations between socio-economic status (SES) and intervention adherence, and explore associations between representativeness and the relationship between SES and intervention adherence.Methods: Systematic, computerised searches were performed in PubMed, CINAHL, AMED, EMBASE and PsycINFO. Additional citation-based searches retrieved 37 articles. Distributions of education level, ethnicity, and marital status in study samples were compared to national populations data to estimate representativeness in less privileged groups.Results: A preponderance of studies favoured educated, married and white patients. Only six studies reported SES-adherence associations, hampering conclusions on this relationship and possible associations between representativeness and an SES-adherence relationship.Conclusion: Less educated, unmarried and non-white individuals may be underrepresented in BC physical activity RCTs, while SES-adherence associations in such trials are inconclusive. Unintentional social misrepresentations may indicate that disguised inequity warrants revived attention.

Background: There has been a call for studies investigating the assumption that professional and interprofessional identities evolve differently during educational programmes. The aim of this study was to investigate the level of professional and interprofessional identity across different years of health and social care students’ professional education. Methods: This cross-sectional study invited students across all study years from eleven health and social care higher education programmes at one university to complete a web-based questionnaire. Professional and interprofessional identity were assessed using the Macleod Clark Professional Identity Scale (MCPIS-9). Differences in identity scores between study years were examined using two-sample t-tests and multivariable regression models. Results: In total, 864 students, approximately one-fifth of the study population, participated. Across all study years, mean (SD) scores were 4.15 (0.54) for professional identity and 4.17 (0.53) for interprofessional identity (scale range 1–5). Final-year students scored slightly higher than first-year students on professional identity (mean difference 0.18, 95% CI 0.07 to 0.30), with a smaller difference observed for interprofessional identity (0.10, 95% CI − 0.01 to 0.21). The difference between first- and final-year students was 0.08 points larger for professional than for interprofessional identity. When stratified by programme length, the mean difference in professional identity between the first and final study year was 0.17 ( p = 0.034) in three-year bachelor programmes and 0.30 ( p = 0.022) in six-year professional programmes. Corresponding differences for interprofessional identity were smaller: 0.08 ( p = 0.386) for bachelor programmes and 0.24 ( p = 0.049) for six-year programmes. Conclusion: Students in later study years exhibited slightly higher professional identity scores than earlier years, with smaller between-year differences for interprofessional identity. The very small between-year differences may reflect lack of measurement sensitivity in MCPIS-9, stability in identity levels, high professional identity during the first year of study, or cohort effects inherent to cross-sectional designs.