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1.  A transition program to primary health care for new graduate nurses: a strategy towards building a sustainable primary health care nurse workforce? 
BMC Nursing  2014;13(1):34.
This debate discusses the potential merits of a New Graduate Nurse Transition to Primary Health Care Program as an untested but potential nursing workforce development and sustainability strategy. Increasingly in Australia, health policy is focusing on the role of general practice and multidisciplinary teams in meeting the service needs of ageing populations in the community. Primary health care nurses who work in general practice are integral members of the multidisciplinary team – but this workforce is ageing and predicted to face increasing shortages in the future. At the same time, Australia is currently experiencing a surplus of and a corresponding lack of employment opportunities for new graduate nurses. This situation is likely to compound workforce shortages in the future. A national nursing workforce plan that addresses supply and demand issues of primary health care nurses is required. Innovative solutions are required to support and retain the current primary health care nursing workforce, whilst building a skilled and sustainable workforce for the future.
This debate article discusses the primary health care nursing workforce dilemma currently facing policy makers in Australia and presents an argument for the potential value of a New Graduate Transition to Primary Health Care Program as a workforce development and sustainability strategy. An exploration of factors that may contribute or hinder transition program for new graduates in primary health care implementation is considered.
A graduate transition program to primary health care may play an important role in addressing primary health care workforce shortages in the future. There are, however, a number of factors that need to be simultaneously addressed if a skilled and sustainable workforce for the future is to be realised. The development of a transition program to primary health care should be based on a number of core principles and be subjected to both a summative and cost-effectiveness evaluation involving all key stakeholders.
PMCID: PMC4279900  PMID: 25550684
Primary Health Care; Practice Nurse; Graduate Nurse; Transition; Retention; Recruitment; Workforce; Sustainability; Australia
2.  The impact of a brief lifestyle intervention delivered by generalist community nurses (CN SNAP trial) 
BMC Public Health  2013;13:375.
The risk factors for chronic disease, smoking, poor nutrition, hazardous alcohol consumption, physical inactivity and weight (SNAPW) are common in primary health care (PHC) affording opportunity for preventive interventions. Community nurses are an important component of PHC in Australia. However there has been little research evaluating the effectiveness of lifestyle interventions in routine community nursing practice. This study aimed to address this gap in our knowledge.
The study was a quasi-experimental trial involving four generalist community nursing (CN) services in New South Wales, Australia. Two services were randomly allocated to an ‘early intervention’ and two to a ‘late intervention’ group. Nurses in the early intervention group received training and support in identifying risk factors and offering brief lifestyle intervention for clients. Those in the late intervention group provided usual care for the first 6 months and then received training. Clients aged 30–80 years who were referred to the services between September 2009 and September 2010 were recruited prior to being seen by the nurse and baseline self-reported data collected. Data on their SNAPW risk factors, readiness to change these behaviours and advice and referral received about their risk factors in the previous 3 months were collected at baseline, 3 and 6 months. Analysis compared changes using univariate and multilevel regression techniques.
804 participants were recruited from 2361 (34.1%) eligible clients. The proportion of clients who recalled receiving dietary or physical activity advice increased between baseline and 3 months in the early intervention group (from 12.9 to 23.3% and 12.3 to 19.1% respectively) as did the proportion who recalled being referred for dietary or physical activity interventions (from 9.5 to 15.6% and 5.8 to 21.0% respectively). There was no change in the late intervention group. There a shift towards greater readiness to change in those who were physically inactive in the early but not the comparison group. Clients in both groups reported being more physically active and eating more fruit and vegetables but there were no significant differences between groups at 6 months.
The study demonstrated that although the intervention was associated with increases in advice and referral for diet or physical activity and readiness for change in physical activity, this did not translate into significant changes in lifestyle behaviours or weight. This suggests a need to facilitate referral to more intensive long-term interventions for clients with risk factors identified by primary health care nurses.
Trial registration
PMCID: PMC3653785  PMID: 23607755
Primary health care; Lifestyle behaviours; Smoking; Nutrition; Alcohol; Physical activity; Community nursing
3.  Effectiveness of moving on: an Australian designed generic self-management program for people with a chronic illness 
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 behaviour change and acquire the knowledge and skills to implement changes that promote their health and quality of life.
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).
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.
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: ACTRN12609000298213
PMCID: PMC3605265  PMID: 23497326
Self-management; Primary health care; Self-efficacy; Chronic illness
5.  Is there scope for community health nurses to address lifestyle risk factors? the community nursing SNAP trial 
BMC Nursing  2012;11:4.
This paper examines the opportunity and need for lifestyle interventions for patients attending generalist community nursing services in Australia. This will help determine the scope for risk factor management within community health care by generalist community nurses (GCNs).
This was a quasi-experimental study conducted in four generalist community nursing services in NSW, Australia. Prior to service contacts, clients were offered a computer-assisted telephone interview to collect baseline data on socio-demographics, health conditions, smoking status, physical activity levels, alcohol consumption, height and weight, fruit and vegetable intake and 'readiness-to-change' for lifestyle risk factors.
804 clients participated (a response rate of 34.1%). Participants had higher rates of obesity (40.5% vs 32.1%) and higher prevalence of multiple risk factors (40.4% vs 29.5%) than in the general population. Few with a SNAPW (Smoking-Nutrition-Alcohol-Physical-Activity-Weight) risk factor had received advice or referral in the previous 3 months. The proportion of clients identified as at risk and who were open to change (i.e. contemplative, in preparation or in action phase) were 65.0% for obese/overweight; 73.8% for smokers; 48.2% for individuals with high alcohol intake; 83.5% for the physically inactive and 59.0% for those with poor nutrition.
There was high prevalence of lifestyle risk factors. Although most were ready to change, few clients recalled having received any recent lifestyle advice. This suggests that there is considerable scope for intervention by GCNs. The results of this trial will shed light on how best to implement the lifestyle risk factor management in routine practice.
PMCID: PMC3337290  PMID: 22420868
6.  An efficacy trial of brief lifestyle intervention delivered by generalist community nurses (CN SNAP trial) 
BMC Nursing  2010;9:4.
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.
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.
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.
Trial Registration
PMCID: PMC2841173  PMID: 20175932
7.  An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study 
Despite the effectiveness of brief lifestyle intervention delivered in primary healthcare (PHC), implementation in routine practice remains suboptimal. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about the process by which clinicians' perceptions shape implementation. This study aims to describe a theoretical model to understand how clinicians' perceptions shape the implementation of lifestyle risk factor management in routine practice. The implications of the model for enhancing practices will also be discussed.
The study analysed data collected as part of a larger feasibility project of risk factor management in three community health teams in New South Wales (NSW), Australia. This included journal notes kept through the implementation of the project, and interviews with 48 participants comprising 23 clinicians (including community nurses, allied health practitioners and an Aboriginal health worker), five managers, and two project officers. Data were analysed using grounded theory principles of open, focused, and theoretical coding and constant comparative techniques to construct a model grounded in the data.
The model suggests that implementation reflects both clinician beliefs about whether they should (commitment) and can (capacity) address lifestyle issues. Commitment represents the priority placed on risk factor management and reflects beliefs about role responsibility congruence, client receptiveness, and the likely impact of intervening. Clinician beliefs about their capacity for risk factor management reflect their views about self-efficacy, role support, and the fit between risk factor management ways of working. The model suggests that clinicians formulate different expectations and intentions about how they will intervene based on these beliefs about commitment and capacity and their philosophical views about appropriate ways to intervene. These expectations then provide a cognitive framework guiding their risk factor management practices. Finally, clinicians' appraisal of the overall benefits versus costs of addressing lifestyle issues acts to positively or negatively reinforce their commitment to implementing these practices.
The model extends previous research by outlining a process by which clinicians' perceptions shape implementation of lifestyle risk factor management in routine practice. This provides new insights to inform the development of effective strategies to improve such practices.
PMCID: PMC2770564  PMID: 19825189
8.  Explaining the variation in the management of lifestyle risk factors in primary health care: A multilevel cross sectional study 
BMC Public Health  2009;9:165.
Despite 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.
A 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.
There 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' socio-economic status, the reason for the visit and providers' perceptions of the 'appropriateness' 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.
The 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.
PMCID: PMC2698853  PMID: 19480660
9.  "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 
Primary 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.
A cross sectional survey was undertaken with PHC clinicians (n = 59) in three community health teams. Clinicians' 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.
Role congruence, perceived client acceptability, beliefs about capabilities, perceived effectiveness and clinicians' 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.
PHC clinicians' 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.
PMCID: PMC2267185  PMID: 18298865

Results 1-10 (10)