Socio-demographic factors, behaviour and personality: associations with psychological distress

Background: Anxiety, psychological distress and personality may not be independent risk factors for cardiovascular disease; however they may contribute via their relationship with unhealthy lifestyle behaviours. This study aimed to examine the association between psychological distress, risk behaviours and patient demographic characteristics in a sample of general practice patients aged 40–65 years with at least one risk factor for cardiovascular disease. Design: Cross-sectional analytic study. Methods: Patients, randomly selected from general practice records, completed a questionnaire about their behavioural risk factors and psychological health as part of a cluster randomized controlled trial of a general practice based intervention to prevent chronic vascular disease. The Kessler Psychological Distress Score (K10) was the main outcome measure for the multilevel, multivariate analysis. Results: Single-level bi-variate analysis demonstrated a significant association between higher K10 and middle age (p = 0.001), high neuroticism (p = 0), current smoking (p = 0), physical inactivity (p = 0.003) and low fruit and vegetable consumption (p = 0.008). Socioeconomic (SES) indicators of deprivation (employment and accommodation status) were also significantly associated with higher K10 (p = 0). No individual behavioural risk factor was associated with K10 on multilevel multivariate analysis; however indicators of low SES remained significant (p < 0.001). Conclusions: When all factors were considered, psychological distress was not associated with behavioural risk factors for cardiovascular disease. Other underlying factors, such as personality type and socioeconomic status, may be associated with both the behaviours and the distress

Explaining the variation in the management of lifestyle risk factors in primary health care: a multilevel cross sectional study

BackgroundDespite evidence for the effectiveness of interventions to modify lifestyle behaviours in the primary health care (PHC) setting, assessment and intervention for these behaviours remains low in routine practice. Little is known about the relative importance of various determinants of practice.This study aimed to examine the relative importance of provider characteristics and attitudes, patient characteristics and consultation factors in determining the rate of assessment and intervention for lifestyle risk factors in PHC.MethodsA prospective audit of assessment and intervention for lifestyle risk factors was undertaken by PHC nurses and allied health providers (n = 57) for all patients seen (n = 732) over a two week period. Providers completed a survey to assess key attitudes related to addressing lifestyle issues. Multi-level logistic regression analysis of patient audit records was undertaken. Associations between variables from both data sources were examined, together with the variance explained by patient and consultation (level 1) and provider (level 2) factors.ResultsThere was significant variance between providers in the assessment and intervention for lifestyle risk factors. The consultation type and reason for the visit were the most important in explaining the variation in assessment practices, however these factors along with patient and provider variables accounted for less than 20% of the variance. In contrast, multi-level models showed that provider factors were most important in explaining the variance in intervention practices, in particular, the location of the team in which providers worked (urban or rural) and provider perceptions of their effectiveness and accessibility of support services. After controlling for provider variables, patients\u27 socio-economic status, the reason for the visit and providers\u27 perceptions of the \u27appropriateness\u27 of addressing risk factors in the consultation were all significantly associated with providing optimal intervention. Together, measured patient consultation and provider variables accounted for most (80%) of the variation in intervention practices between providers.ConclusionThe findings highlight the importance of provider factors such as beliefs and attitudes, team location and work context in understanding variations in the provision of lifestyle intervention in PHC. Further studies of this type are required to identify variables that improve the proportion of variance explained in assessment practices

Factors influencing participation in a vascular disease prevention lifestyle program among participants in a cluster randomized trial

BackgroundPrevious research suggests that lifestyle intervention for the prevention of diabetes and cardiovascular disease (CVD) are effective, however little is known about factors affecting participation in such programs. This study aims to explore factors influencing levels of participation in a lifestyle modification program conducted as part of a cluster randomized controlled trial of CVD prevention in primary care.MethodsThis concurrent mixed methods study used data from the intervention arm of a cluster RCT which recruited 30 practices through two rural and three urban primary care organizations. Practices were randomly allocated to intervention (n = 16) and control (n = 14) groups. In each practice up to 160 eligible patients aged between 40 and 64 years old, were invited to participate. Intervention practice staff were trained in lifestyle assessment and counseling and referred high risk patients to a lifestyle modification program (LMP) consisting of two individual and six group sessions over a nine month period. Data included a patient survey, clinical audit, practice survey on capacity for preventive care, referral and attendance records at the LMP and qualitative interviews with Intervention Officers facilitating the LMP. Multi-level logistic regression modelling was used to examine independent predictors of attendance at the LMP, supplemented with qualitative data from interviews with Intervention Officers facilitating the program.ResultsA total of 197 individuals were referred to the LMP (63% of those eligible). Over a third of patients (36.5%) referred to the LMP did not attend any sessions, with 59.4% attending at least half of the planned sessions. The only independent predictors of attendance at the program were employment status - not working (OR: 2.39 95% CI 1.15-4.94) and having high psychological distress (OR: 2.17 95% CI: 1.10-4.30). Qualitative data revealed that physical access to the program was a barrier, while GP/practice endorsement of the program and flexibility in program delivery facilitated attendance.ConclusionBarriers to attendance at a LMP for CVD prevention related mainly to external factors including work commitments and poor physical access to the programs rather than an individuals&rsquo; health risk profile or readiness to change. Improving physical access and offering flexibility in program delivery may enhance future attendance. Finally, associations between psychological distress and attendance rates warrant further investigation

Should I and Can I?: a mixed methods study of clinician beliefs and attitudes in the management of lifestyle risk factors in primary health care

BackgroundPrimary health care (PHC) clinicians have an important role to play in addressing lifestyle risk factors for chronic diseases. However they intervene only rarely, despite the opportunities that arise within their routine clinical practice. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about this for PHC clinicians working outside general practice. The aim of this study was to explore the beliefs and attitudes of PHC clinicians about incorporating lifestyle risk factor management into their routine care and to examine whether these varied according to their self reported level of risk factor management.MethodsA cross sectional survey was undertaken with PHC clinicians (n = 59) in three community health teams. Clinicians\u27 beliefs and attitudes were also explored through qualitative interviews with a purposeful sample of 22 clinicians from the teams. Mixed methods analysis was used to compare beliefs and attitudes for those with high and low levels of self reported risk factor management.ResultsRole congruence, perceived client acceptability, beliefs about capabilities, perceived effectiveness and clinicians\u27 own lifestyle were key themes related to risk factor management practices. Those reporting high levels of risk factor screening and intervention had different beliefs and attitudes to those PHC clinicians who reported lower levels.ConclusionPHC clinicians\u27 level of involvement in risk factor management reflects their beliefs and attitudes about it. This provides insights into ways of intervening to improve the integration of behavioural risk factor management into routine practice

An Australian general practice based strategy to improve chronic disease prevention, and its impact on patient reported outcomes: Evaluation of the preventive evidence into practice cluster randomised controlled trial

© 2017 The Author(s). Background: Implementing evidence-based chronic disease prevention with a practice-wide population is challenging in primary care. Methods: PEP Intervention practices received education, clinical audit and feedback and practice facilitation. Patients (40 69 years) without chronic disease from trial and control practices were invited to participate in baseline and 12 month follow up questionnaires. Patient-recalled receipt of GP services and referral, and the proportion of patients at risk were compared over time and between intervention and control groups. Mean difference in BMI, diet and physical activity between baseline and follow up were calculated and compared using a paired t-test. Change in the proportion of patients meeting the definition for physical activity diet and weight risk was calculated using McNemar's test and multilevel analysis was used to determine the effect of the intervention on follow-up scores. Results: Five hundred eighty nine patients completed both questionnaires. No significant changes were found in the proportion of patients reporting a BP, cholesterol, glucose or weight check in either group. Less than one in six at-risk patients reported receiving lifestyle advice or referral at baseline with little change at follow up. More intervention patients reported attempts to improve their diet and reduce weight. Mean score improved for diet in the intervention group (p = 0.04) but self-reported BMI and PA risk did not significantly change in either group. There was no significant change in the proportion of patients who reported being at-risk for diet, PA or weight, and no changes in PA, diet and BMI in multilevel linear regression adjusted for patient age, sex, practice size and state. There was good fidelity to the intervention but practices varied in their capacity to address changes. Conclusions: The lack of measurable effect within this trial may be attributable to the complexities around behaviour change and/or system change. This trial highlights some of the challenges in providing suitable chronic disease preventive interventions which are both scalable to whole practice populations and meet the needs of diverse practice structures. Trial registration: Australian and New Zealand Clinical Trials Registry (ANZCTR): ACTRN12612000578808 (29/5/2012). This trial registration is retrospective as our first patient returned their consent on the 21/5/2012. Patient recruitment was ongoing until 31/10/2012

Effectiveness of moving on: an Australian designed generic self-management program for people with a chronic illness

Background: This paper presents the evaluation of “Moving On”, a generic self-management program for people with a chronic illness developed by Arthritis NSW. The program aims to help participants identify their need for behavior change and acquire the knowledge and skills to implement changes that promote their health and quality of life. Method: A prospective pragmatic randomised controlled trial involving two group programs in community settings: the intervention program (Moving On) and a control program (light physical activity). Participants were recruited by primary health care providers across the north-west region of metropolitan Sydney, Australia between June 2009 and October 2010. Patient outcomes were self-reported via pre- and post-program surveys completed at the time of enrolment and sixteen weeks after program commencement. Primary outcomes were change in self-efficacy (Self-efficacy for Managing Chronic Disease 6-Item Scale), self-management knowledge and behaviour and perceived health status (Self-Rated Health Scale and the Health Distress Scale). Results: A total of 388 patient referrals were received, of whom 250 (64.4%) enrolled in the study. Three patients withdrew prior to allocation. 25 block randomisations were performed by a statistician external to the research team: 123 patients were allocated to the intervention program and 124 were allocated to the control program. 97 (78.9%) of the intervention participants commenced their program. The overall attrition rate of 40.5% included withdrawals from the study and both programs. 24.4% of participants withdrew from the intervention program but not the study and 22.6% withdrew from the control program but not the study. A total of 62 patients completed the intervention program and follow-up evaluation survey and 77 patients completed the control program and follow- up evaluation survey. At 16 weeks follow-up there was no significant difference between intervention and control groups in self-efficacy; however, there was an increase in self-efficacy from baseline to follow-up for the intervention participants (t=−1.948, p=0.028). There were no significant differences in self-rated health or health distress scores between groups at follow-up, with both groups reporting a significant decrease in health distress scores. There was no significant difference between or within groups in self-management knowledge and stage of change of behaviours at follow-up. Intervention group attenders had significantly higher physical activity (t=−4.053, p=0.000) and nutrition scores (t=2.315, p= 0.01) at follow-up; however, these did not remain significant after adjustment for covariates. At follow-up, significantly more participants in the control group (20.8%) indicated that they did not have a self-management plan compared to those in the intervention group (8.8%) (X2=4.671, p=0.031). There were no significant changes in other self-management knowledge areas and behaviours after adjusting for covariates at follow-up. Conclusions: The study produced mixed findings. Differences between groups as allocated were diluted by the high proportion of patients not completing the program. Further monitoring and evaluation are needed of the impact and cost effectiveness of the program. Trial registration: Australian New Zealand Clinical Trials Registry: ACTRN1260900029821

An Australian general practice based strategy to improve chronic disease prevention, and its impact on patient reported outcomes: evaluation of the preventive evidence into practice cluster randomised controlled trial

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Implementing evidence-based chronic disease prevention with a practice-wide population is challenging in primary care. Methods PEP Intervention practices received education, clinical audit and feedback and practice facilitation. Patients (40‑69 years) without chronic disease from trial and control practices were invited to participate in baseline and 12 month follow up questionnaires. Patient-recalled receipt of GP services and referral, and the proportion of patients at risk were compared over time and between intervention and control groups. Mean difference in BMI, diet and physical activity between baseline and follow up were calculated and compared using a paired t-test. Change in the proportion of patients meeting the definition for physical activity diet and weight risk was calculated using McNemar’s test and multilevel analysis was used to determine the effect of the intervention on follow-up scores. Results Five hundred eighty nine patients completed both questionnaires. No significant changes were found in the proportion of patients reporting a BP, cholesterol, glucose or weight check in either group. Less than one in six at-risk patients reported receiving lifestyle advice or referral at baseline with little change at follow up. More intervention patients reported attempts to improve their diet and reduce weight. Mean score improved for diet in the intervention group (p = 0.04) but self-reported BMI and PA risk did not significantly change in either group. There was no significant change in the proportion of patients who reported being at-risk for diet, PA or weight, and no changes in PA, diet and BMI in multilevel linear regression adjusted for patient age, sex, practice size and state. There was good fidelity to the intervention but practices varied in their capacity to address changes. Conclusions The lack of measurable effect within this trial may be attributable to the complexities around behaviour change and/or system change. This trial highlights some of the challenges in providing suitable chronic disease preventive interventions which are both scalable to whole practice populations and meet the needs of diverse practice structures

The impact of health literacy and life style risk factors on health-related quality of life of Australian patients

BACKGROUND: Limited evidence exists regarding the relationship between health literacy and health-related quality of life (HRQoL) in Australian patients from primary care. The objective of this study was to investigate the impact of health literacy on HRQoL in a large sample of patients without known vascular disease or diabetes and to examine whether the difference in HRQoL between low and high health literacy groups was clinically significant. METHODS: This was a cross-sectional study of baseline data from a cluster randomised trial. The study included 739 patients from 30 general practices across four Australian states conducted in 2012 and 2013 using the standard Short Form Health Survey (SF-12) version 2. SF-12 physical component score (PCS-12) and mental component score (MCS-12) are derived using the standard US algorithm. Health literacy was measured using the Health Literacy Management Scale (HeLMS). Multilevel regression analysis (patients at level 1 and general practices at level 2) was applied to relate PCS-12 and MCS-12 to patient reported life style risk behaviours including health literacy and demographic factors. RESULTS: Low health literacy patients were more likely to be smokers (12 % vs 6 %, P&thinsp;=&thinsp;0.005), do insufficient physical activity (63 % vs 47 %, P&thinsp;&lt;&thinsp;0.001), be overweight (68 % vs 52 %, P&thinsp;&lt;&thinsp;0.001), and have lower physical health and lower mental health with large clinically significant effect sizes of 0.56 (B (regression coefficient)&thinsp;= -5.4, P&thinsp;&lt;&thinsp;0.001) and 0.78(B&thinsp;=&thinsp;-6.4, P&thinsp;&lt;&thinsp;0.001) respectively after adjustment for confounding factors. Patients with insufficient physical activity were likely to have a lower physical health score (effect size&thinsp;=&thinsp;0.42, B&thinsp;= -3.1, P&thinsp;&lt;&thinsp;0.001) and lower mental health (effect size&thinsp;=&thinsp;0.37, B&thinsp;= -2.6, P&thinsp;&lt;&thinsp;0.001). Being overweight tended to be related to a lower PCS-12 (effect size&thinsp;=&thinsp;0.41, B&thinsp;=&thinsp;-1.8, P&thinsp;&lt;&thinsp;0.05). Less well-educated, unemployed and smoking patients with low health literacy reported worse physical health. Health literacy accounted for 45 and 70 % of the total between patient variance explained in PCS-12 and MCS-12 respectively. CONCLUSIONS: Addressing health literacy related barriers to preventive care may help reduce some of the disparities in HRQoL. Recognising and tailoring health related communication to those with low health literacy may improve health outcomes including HRQoL in general practice

The impact of a team-based intervention on the lifestyle risk factor management practices of community nurses: outcomes of the community nursing SNAP trial

BackgroundLifestyle risk factors like smoking, nutrition, alcohol consumption, and physical inactivity (SNAP) are the main behavioural risk factors for chronic disease. Primary health care is an appropriate setting to address these risk factors in individuals. Generalist community health nurses (GCHNs) are uniquely placed to provide lifestyle interventions as they see clients in their homes over a period of time. The aim of the paper is to examine the impact of a service-level intervention on the risk factor management practices of GCHNs.MethodsThe trial used a quasi-experimental design involving four generalist community nursing services in NSW, Australia. The services were randomly allocated to either an intervention group or control group. Nurses in the intervention group were provided with training and support in the provision of brief lifestyle assessments and interventions. The control group provided usual care. A sample of 129 GCHNs completed surveys at baseline, 6 and 12&thinsp;months to examine changes in their practices and levels of confidence related to the management of SNAP risk factors. Six semi-structured interviews and four focus groups were conducted among the intervention group to explore the feasibility of incorporating the intervention into everyday practice.ResultsNurses in the intervention group became more confident in assessment and intervention over the three time points compared to their control group peers. Nurses in the intervention group reported assessing physical activity, weight and nutrition more frequently, as well as providing more brief interventions for physical activity, weight management and smoking cessation. There was little change in referral rates except for an improvement in weight management related referrals. Nurses&rsquo; perception of the importance of &lsquo;client and system-related&rsquo; barriers to risk factor management diminished over time.ConclusionsThis study shows that the intervention was associated with positive changes in self-reported lifestyle risk factor management practices of GCHNs. Barriers to referral remained. The service model needs to be adapted to sustain these changes and enhance referral

An efficacy trial of brief lifestyle intervention delivered by generalist community nurses (CN SNAP trial)

<p>Abstract</p> <p>Background</p> <p>Lifestyle risk factors, in particular smoking, nutrition, alcohol consumption and physical inactivity (SNAP) are the main behavioural risk factors for chronic disease. Primary health care (PHC) has been shown to be an effective setting to address lifestyle risk factors at the individual level. However much of the focus of research to date has been in general practice. Relatively little attention has been paid to the role of nurses working in the PHC setting. Community health nurses are well placed to provide lifestyle intervention as they often see clients in their own homes over an extended period of time, providing the opportunity to offer intervention and enhance motivation through repeated contacts. The overall aim of this study is to evaluate the impact of a brief lifestyle intervention delivered by community nurses in routine practice on changes in clients' SNAP risk factors.</p> <p>Methods/Design</p> <p>The trial uses a quasi-experimental design involving four generalist community nursing services in NSW Australia. Services have been randomly allocated to an 'early intervention' group or 'late intervention' (comparison) group. 'Early intervention' sites are provided with training and support for nurses in identifying and offering brief lifestyle intervention for clients during routine consultations. 'Late intervention site' provide usual care and will be offered the study intervention following the final data collection point. A total of 720 generalist community nursing clients will be recruited at the time of referral from participating sites. Data collection consists of 1) telephone surveys with clients at baseline, three months and six months to examine change in SNAP risk factors and readiness to change 2) nurse survey at baseline, six and 12 months to examine changes in nurse confidence, attitudes and practices in the assessment and management of SNAP risk factors 3) semi-structured interviews/focus with nurses, managers and clients in 'early intervention' sites to explore the feasibility, acceptability and sustainability of the intervention.</p> <p>Discussion</p> <p>The study will provide evidence about the effectiveness and feasibility of brief lifestyle interventions delivered by generalist community nurses as part of routine practice. This will inform future community nursing practice and PHC policy.</p> <p>Trial Registration</p> <p>ACTRN12609001081202</p