In a 3-page paper (excluding title page and references), evaluate the study according to research design methods, procedures and study results, for example, see Evaluating a quantitative study Include a discussion on how the study contributes to evidence-based practice (EBP) follow Rubric or Grading Criteria: (1) Evaluates research design (2) Evaluates methods/procedures and results. Please Read and Critique the following article:
R E S EAR CH A R TIC L E  Open Access
The impact of a brief lifestyle intervention delivered by generalist community nurses (CN SNAP trial)
Mark F Harris* , Bibiana C Chan, Rachel A Laws, Anna M Williams, Gawaine Powell Davies, Upali W Jayasinghe, Mahnaz Fanaian, Neil Orr, Andrew Milat and on behalf of the CN SNAP Project Team


Background:  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.
Methods: 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.
Results: 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.
Conclusion: 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: ACTRN12609001081202
Keywords: Primary health care, Lifestyle behaviors, Smoking, Nutrition, Alcohol, Physical activity, Community nursing *
Correspondence: Centre for Primary Health Care and Equity, School of Public Health and Community Medicine, University of New South Wales, Sydney, NSW 2052, Australia © 2013 Harris et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Harris et al. BMC Public Health 2013, 13:375 Background In Australia, chronic diseases such as heart disease and diabetes are the leading causes of death and disability [1]. The risk factors for these conditions include risk behaviours (in smoking, nutrition, alcohol and physical activity) and overweight (SNAPW). These are prevalent in the community, with over 90% of adults not consuming the recommended five serves of vegetables per day, over half not consuming adequate amounts of fruit, 62% overweight or obese, one third, physically inactive, one in five smoke and 21% drink alcohol at levels which pose a risk to their health [2]. Primary health care (PHC) is an important setting for addressing lifestyle risk factors because of its accessibility, continuity, and comprehensiveness of the care provided [3]. There is evidence that clients expect to receive lifestyle intervention from PHC clinicians [4]. Lifestyle interventions delivered in PHC are effective in helping clients to stop smoking [5], reduce ‘at-risk alcohol’ consumption [6], improve weight, diet and physical activity levels [7-12]. The 5As (assess, advise (including motivational interviewing) and agree on goals, assist (including referral), and arrange (follow up) have been developed as a framework for addressing these risk factors in clinical practice [13,14]. In NSW, generalist community nurses frequently see clients in their own home, providing care for patients recently discharged from hospital, the aged and those with chronic diseases. Although the traditional community nursing model of practice includes health promotion activities, community nursing services have increasingly tended to provide shorter term more clinically focused services to individual clients [15,16]. Our previous research has shown that community health nurses consider the provision of lifestyle intervention appropriate to their role and it is well accepted by clients [17]. However, few studies have evaluated the effectiveness of lifestyle interventions provided by community nurses in routine practice [18-21]. The aim of this study was to evaluate the impact of a brief lifestyle intervention delivered by community health nurses as part of their routine practice on changes in clients’ SNAPW risk factors.
Study design and setting This study was conducted in four general community nursing services in New South Wales, Australia. Services were recruited via an expression of interest mailed to all Area Health Services (AHS) in NSW (n = 8). The design was quasi-experimental, with the services randomly allocated to an ‘early intervention’ (EI) group or ‘late intervention’ (LI) (comparison) group. EI services were provided with training and support for nurses in identifying clients with high risk and offering brief SNAPW intervention during routine consultations. The protocol for the study has been previously described [22]. Intervention The intervention was designed and implemented on two levels: (a) service level and (b) client level. Service-level intervention The service-level intervention was delivered by University staff and consisted of four components:  A 1-day training program in the assessment and management of the SNAPW risk factors (including motivational interviewing) for participating community nurses delivered by the research team in conjunction with local providers. The training included the use of role-plays with simulated clients (actors), group discussions and activities;  Integration of standardised screening tools and prompts for SNAPW risk factors into the service-specific assessment processes used by the nurses in the management of clients;  Development and distribution of a local service referral directory to each community nursing team to promote referral of clients for ongoing specialist management or more / ongoing intensive lifestyle intervention; and  Provision of client resources to all participating nurses. The resources included a written guide for nurses, written action plans for use with clients on each SNAPW risk factor, tape measures for measuring waist circumference and pedometers for loan to clients to encourage self-monitoring of physical activity. A nurse from each of the EI sites was seconded to work with the research team to develop the intervention and to support its implementation at the local level. Client-level intervention The client-level intervention was provided by the participating nurses. The goals of the clinical intervention were to achieve and maintain lifestyle changes consistent with current Australian recommendations [23]:  Moderate physical activity for at least 30 minutes/ day, including walking, jogging, swimming, aerobic activity, ball games, skiing, with circuit-type resistance training if possible, twice a week;  A diet low in saturated fats, sucrose and salt with increased portions of vegetables and fruit per day (up to seven portions) in order to achieve a diet where the percentage of energy from carbohydrates = 50%, saturated fats <10%  (and total fats >< 30%, protein 1 g/kg ideal body weight per day, fibre 15 g/1000 kcal); Harris et al. BMC Public Health 2013, 13:375 Page 2 of 11  Weight reduction (if overweight) of ≥ 5 kg or 5% of body weight;  Smoking cessation (if smoker);  Limit alcohol intake (if drinking) to ≤ 2 drinks / day, including 1–2 alcohol-free days/week. The nurses assessed clients’ lifestyle risk factors and then provided brief educational intervention tailored to their readiness to change, based on the 5As Model [3] (Figure 1), for one or more SNAPW risk factors. This occurred over two or more visits. Clients who were ‘at risk’ (those who were obese, smoked or who had multiple risk behaviours or illnesses arising from them) and who were in the contemplation or action stages of change were referred to specialist providers for more intensive intervention. Late intervention Two of the four CN services were randomly allocated to the LI group. Late intervention services provided usual care for 18 months. After all data ad been collected the service level intervention was introduced into these services as well. Client recruitment Between September 2009 and September 2010 clients who met the selection criteria and who had been referred to participating services (Table 1) were invited to participate in the study. Potential participants were contacted by phone on the day of referral (where possible) by trained local recruitment officers. The client recruitment process is outlined in Figure 2. Study outcomes, measurements and data collection The study outcomes, measurement tools and timeframe for data collection are summarised in Table 2. The measurement tools were validated in other research [24-26]. The diet, physical activity, alcohol and weight outcomes were continuous measures. Diet score was the total number of serves of fruit and vegetables per day up to a maximum of 7. The physical activity score combined Ask Screening for SNAPW risk factors as part of the routine assessment process Assess Assessment of clients’ readiness to change Advise Provide feedback on SNAPW risk factors and brief stage-matched counselling for lifestyle change over at least two visits Assist Refer to support services for more intensive intervention (especially high risk clients) Arrange Follow up progress at subsequent visits Stage-matched assistance for lifestyle change Stage Approach Pre-contemplation/ Brief advice Contemplation brief motivational interviewing Preparation/action goal setting /action planning Maintenance reinforcement, relapse prevention Relapse relapse management Figure 1 5As model of brief lifestyle intervention. Harris et al. BMC Public Health 2013, 13:375 Page 3 of 11 assessment of duration of vigorous and moderate physical activity (scored 0–8, <4 considered at risk) [27]. Alcohol was  the average number of standard drinks per day. Smoking  status was a categorical variable (smoker or non-smoker).  Mediator variables included change in clients’ ‘readiness to  change’ lifestyle behaviours [28]. Process measures included  change in clients’ recall of advice or referral over the  previous 3 months. Data were collected from a 15-minute  telephone-administered survey conducted with clients  at baseline (prior to first nurse visit) and at 3 and  6 months. The telephone survey was conducted by trained  independent data collectors blinded to the group allocation  (EI or LI) groups.  Statistical analysis  Power and sample size calculation  The a priori sample size was 400 clients per group  (n = 800). This was calculated based on estimates of  Table 1 Selection criteria for recruiting clients to participate in the trial  Types Selection criteria  Inclusion criteria * Clients referred to community nursing services  * Age 30–80 years  * Able to read and understand English at a level that enables the client to participate in a  telephone-administered survey and to understand the participant information sheet.  Exclusion criteria * Palliative care clients.  * Clients receiving only one- visit or occasion of service.  * Clients with significant cognitive impairment (unable to complete telephone-administered survey).  * Clients currently receiving help in changing their lifestyle from a health professional (other than their GP)  such as a dietitian or exercise physiologist.  * Clients currently attending a chronic disease management program such as cardiac rehabilitation,  diabetes education program.  * Clients who have attended the generalist community nursing service in the previous 6 months  (and therefore may have already received lifestyle intervention).  2361 potentially eligible clients  contacted by phone  802 clients not  contactable prior to  first nursing visit  650 clients not interested in  participating  804 clients recruited into the study  33 clients declined to  participate when contacted  72 clients not contactable  by data collection team  prior to first nursing visit  909 client contact details passed to  data collection team to make contact  by phone  7874 clients screened for  eligibility  909 clients verbally consented  to participate  5513 ineligible clients  (based on the selection  criteria) excluded.  Figure 2 Client recruitment process and baseline data co
llection.  Harris et al. BMC Public Health 2013, 13:375 Page 4 of 11 change in mean risk scores of self-reported measures  of lifestyle risk factors. This was sufficient based on  a standard deviation from previous research [29], design  effect of 1.8 and loss to follow up of 20% to detect the  following changes in mean risk scores:-   1 portion of fruit and vegetables per day  (based on sd 2.02)   1 unit of physical activity score (based on sd 2.13)   5 kg of self-reported weight loss (based on sd 14.95)  Analysis  Univariate comparisons were made within group between  baseline and 3 months and between groups for receipt of  advice and referral. Change in readiness to change was  categorised at 6 months and compared between groups.  Statistical tests included t test for continuous variables  and chi square test for categorical variables.  Change in clients’ lifestyle risk factors between the EI  and LI (comparison) groups were evaluated using multilevel  models which included a number of patient level covariates  thought to possibly influence the outcomes [30]. Three  repeated measures of SNAPW were compared within  clients [31]. Multilevel linear regression analysis was  conducted on physical activity score, diet score and  weight. In the first model three levels were fitted which  included: service (level 3), client (level 2) and time  (level 1). The variance between services was found not to  be significant. For each risk factor at 6 months, a two level  regression model was fitted. This included the time and  client as levels adjusting for baseline risk, intervention,  linear time (0 = baseline; 1 = 3 months; 2 = 6 months),  gender, age, employment status, reason for referral, mental  health and physical health status, number of risk factors  and physical limitation. The multilevel statistical models  were fitted using MLwiN version 2.25 [32].  Ethics  The project was approved by the Hunter New England  Human Research Ethics Committee (Ref No 08/10/15/4.03),  and ratified by the University of New South Wales Human  Research Ethics Committee (HREC) and the Human  Research Ethics Committees in each of the participating Area Health Services. The study was conducted  in compliance with this Committees regulations and  the Helsinki declaration. All participants provided full  informed written consent for publication of findings  from this research.  Results  Baseline characteristics  A total of 804 clients were recruited from 2361 potentially  eligible clients (34.1%), 425 in the EI group and 379 in the  LI group (Figure 2). Just under half (49.3%) were female,  67.1% were 60 years of age or over and 53.1% were retired  from paid work. Few participants spoke a language other  than English or were of Aboriginal or Torres Strait Islander  descent (Table 3). There were no significant differences in  age and gender between those who accepted and those  who declined to participate or between those in the EI and  LI groups (Table 3).  The majority (61.6%) of clients rated their own health  as ‘good, very good or excellent’ and 12.7% reported that  during the past month they had felt ‘downhearted or  blue’ most or all of the time. Almost all clients (97.6%)  had at least one lifestyle risk factor and 101 (12.5%) had  at least four (Table 3). At baseline 17.2% of participants  reported being smokers, 78.5% had insufficient fruit and  vegetable dietary intake, 74.0% were overweight or obese,  36.9% had at risk drinking levels. Of those who were  able to engage in physical activity, 50.5% had inadequate  levels. There were no significant differences between  those in the EI and LI groups (Table 3).  Table 2 Study outcomes and measurement  Outcomes Measurement  Change in mean physical activity score Brief validated physical activity tool [24]  Change in mean alcohol intake score Validated AUDIT-C tool [25]  Change in mean number of serves of fruit and vegetables Validated questions from the NSW Health survey [26]  Mean weight change Self report  Change in smoking status Self report  Change in adequate levels of physical activity Self report  Change in ‘at risk’ alcohol consumption Self report  Change consumption of >=2 serves of fruit per day Self report Change in consumption of > =5 serves of vegetables per day Self report Progression in stages of change On five point intentions scales [28] At risk clients offered evidence-based advice to modify their risk factors Recall over previous 3 months At risk clients offered evidence-based referral to modify their risk factors Recall over previous 3 months Collected by client telephone survey at baseline, 3 and 6 months. Harris et al. BMC Public Health 2013, 13:375 Page 5 of 11 Table 3 Characteristics of CN SNAPW trial clients at baseline Characteristics Total (n = 804) Early interv (n = 425) Late interv (379) N%N % N % Female 396 49.3 214 50.4 182 48.0 Aboriginal/ Torres Strait Islander 4 0.5 2 0.5 2 0.5 Language other than English 35 4.4 18 4.2 17 4.5 Employed 215 26.7 115 27.1 100 26.4 Unable to work (long-term sickness/ disability) 109 13.6 50 11.8 59 15.6 Retired from paid work 419 53.1 229 53.9 190 50.1 Age (yrs) 30-39 yrs 44 5.5 22 5.2 22 5.8 40-49 78 9.7 44 10.4 34 9.0 50-59 142 17.7 76 18.0 66 17.4 60-69 256 31.9 136 32.2 120 31.7 ≥ 70 280 35.2 143 34.3 137 36.1 Self-rated health status Poor or Fair 308 38.3 158 37.2 150 39.6 Self-rated mental health status: Downhearted or blue Most to all of the time 102 12.7 49 11.5 53 14.0 Health conditions Hypertension 395 49.1 225 52.9 170 44.9 Arthritis 277 34.5 155 36.5 122 32.2 High cholesterol 239 29.7 132 31.1 107 28.2 Cancer 213 26.5 123 28.9 90 23.7 Diabetes 185 23.0 102 24.0 83 21.9 Depression 132 16.4 66 15.5 66 17.4 Heart disease 132 16.4 55 15.9 55 17.1 no risk factors 18 (2.2%) 11 (2.6%) 7 (1.8%) 1 risk only 147 (18.3%) 76 (17.9% 71 (18.7%) 2 risks 328 (40.2%) 164 (38.6%) 159 (42.0%) 3 risks 215 (26.7%) 120 (28.2 95 (25.1%) 4 risks 92 (11.4%) 50 (11.8%) 42 (11.1%) 5 risks 9 (1.1%) 4 (0.9) 5 (1.3) < 2 serves of fruit (n = 801) 336 (41.9%) 174 (40.9%) 162 (42.7%) <5 serves of veg (n = 796) 672 (84.4%) 352 (82.8%) 320 (84.4%)  At risk alcohol consumption a (n = 804) 297 (36.9%) 159 (37.4%) 138 (36.4%)  Smokers (n = 802) 138 (17.2%) 74 (17.5%) 65 (17.2%)  Overweight (OW) (n = 785) 263 (33.5%) 123 (29.8%) 140 (37.6%)  Obese (n = 785) 318 (40.5%) 182 (44.1%) 136 (36.6%)  OW or obese (n = 785) 581 (74.0%) 305 (71.8%) 276 (72.8%)  Unable to do physical activity (PA)b (n = 793) 375 (47.3%) 196 (46.2%) 179 (47.2%)  Able to do PA but inadequate (n = 418) 211 (50.5%) 120 (31.2%) 91 (25.9%)  a The 2009 national alcohol guidelines for alcohol consumption are available at: b Those with major physical limitations which (a) limited their ability to engage in physical activity a lot and (b) were estimated to last for more than 4 weeks,  or unsure.  Harris et al. BMC Public Health 2013, 13:375 Page 6 of 11 Recall of lifestyle advice and referrals of clients identified  with lifestyle risk factors at baseline and 3 months  Only a minority of participants with a SNAPW risk  factor recalled having received advice from any source in  the 3 months prior to the baseline survey. There was no  difference between the EI and LI groups in this measure.  However, in the EI sites the overall percentage of clients  who reported having received advice from any source  at 3 months increased significantly for dietary advice  (from 12.9% at baseline to 23.3% at 3 months) and physical  activity advice (from 12.5% at baseline to 19.1% at  3 months). There were no significant changes in the LI sites  and at 3 months the early intervention group was more  likely to report having received diet advice (Table 4).  There were significant increases in reported referrals  for diet, physical activity and alcohol from baseline to  3 months in t
he EI group (from 9.5 to 15.6%, 5.8 to 21.0%  and 1.2 to 6.9% respectively). There was no change in the  LI group (Table 4). There were no significant differences  between groups at three months.  ‘Readiness to change’ of clients identified with lifestyle  risk factors  At baseline, the majority of clients who were at risk were in  the contemplation, preparation or action stages of change  for weight change, physical activity, improved nutrition  or smoking (65%, 67% 59.4%, and 73.% respectively).  However, only a minority of those with at-risk alcohol  consumption were in the contemplation, preparation or  action phases (48.1%). At 6 months there was a significantly  greater shift towards higher stages of change in those who  were physically inactive, in the EI group compared to the LI  group (58.8% vs 27.8%; Chi square = 4.54, p = 0.032),  Table 5. Readiness to change smoking increased in LI but  not the EI group. There were no other significant changes  in either group.  Client self-reported risk factors  Overall, there were no significant differences in risk factors  between EI and LI groups at baseline, 3 or 6 months.  However, there were significant increases in diet scores  and physical activity between baseline and 3 months  and baseline and 6 months in both groups (Table 6).  There were no significant changes in smoking, alcohol  or self-reported weight.  Multilevel regression analysis showed that being retired  had a positive effect on diet (Table 7). Self-reported health  had a positive effect on physical activity score. Males,  young, unemployed, those with good mental health and  poor general health tended to have a negative effect on  Table 4 Proportion of at risk clients recalling being offered advice or being referred to manage risk factors  Baseline 3 months  Early intervention Late intervention Early intervention Late intervention  n /N n/N n/N n/N  %, (95%CI) %, (95%CI) %, ( 95%CI) %, (95%CI)  Offered advice from any provider  Diet 33/256 31/253 60/257 40 /247  12.9% (8.6-17.0) 12.3% (8.2-16.3) 23.3 (18.1-28.5)* # 16.2% (11.6-20.8)  Physical activity (for those able to engage in PA) 15 /120 8/91 35/183 20/162  12.5% (6.6-18.4) 8.8% (3.0-14.6) 19.1% (13.4-24.8)* 12.3% (7.3-17.4)  Smoking 10 /64 16/65 11 /46 11 /47  15.6% (6.7-24.5) 24.6% (14.1-35.1) 23.9% (11.6-36.2) 23.4% (11.3-35.5)  Alcohol 6 /105 6/93 6 /84 9/75  5.7% (1.3-10.2) 6.5% (1.5-11.4) 7.1% (1.6-12.7) 12.0% (4.7-19.4)  Referral for SNAP intervention  Diet 31/326 19/298 40 /257 29 /252  9.5% (6.3-12.7) 6.4% (3.6-9.2) 15.6% (11.0-20.0)* 11.5% (7.6-15.5)  Physical activity (for those able to engage in PA) 7 /120 5/91 21/100 9/78  5.8% (1.6-10.0) 5.5% (0.8 – 10.2) 21.0% (13.0-30.0)* 11.5% (4.5-18.6%)  Smoking 8 /74 11 /64 9 /62 10 /49  10.8% (3.7-17.9) 17.2% (7.9-26.4) 14.5% (5.8-23.3) 20.4% (9.1-31.7)  Alcohol 3 /159 4 /138 9 /131 6 /109  1.2% (0–4.0) 2.9% (0.1-5.7) 6.9% (2.5-11.2) * 5.5% (1.2-9.8)  * Significant change from baseline p >< 0.05. # Significant difference between groups p < 0.05. Harris et al. BMC Public Health 2013, 13:375 Page 7 of 11 weight loss. The intervention was not significantly related to diet score, physical activity score and weight at 6 months (Table 7). The multilevel regression model explained 16% and 42% respectively of the total client variance in the diet and physical activity scores respectively. Discussion This study demonstrated that community health nurses were able to implement lifestyle risk factor management as part of normal clinical practice. This individual support within PHC can complement broader population health approaches as part of a comprehensive approach to reducing cardiovascular risk factors across the population. Community health nurses are particularly well placed to deliver lifestyle interventions to high risk clients, many of whom have chronic disease and multiple behavioural risk factors. The intervention was associated with an increase in the provision of brief diet and physical activity advice by community nurses. In qualitative interviews we found that this was a feasible addition to routine practice by the nurses which clients found acceptable [33,34]. Whilst referrals were infrequent at baseline they increased following the intervention for diet and alcohol and physical activity in the EI but not the LI groups. Despite modest improvements in preventive care, and some shift in readiness to change physical activity, there was no evidence of a significant impact of the intervention on the SNAP behaviours or weight of clients. It may be that brief interventions from community nurses is not sufficient to achieve change in lifestyle risk factors in this group of clients, many of whom were older, had existing chronic conditions, or were recovering from acute illness. An important factor may also be that many clients were seen following discharge from hospital, and the immediate post-acute phase might not be conducive to making lifestyle change. The intervention and follow-up period in this study was relatively short and it is possible that clients might have been able to make changes once they were fully recovered. These clients may require referral onwards to more intensive interventions at an appropriate time. This requires systems to be in place for assessment of readiness to change and referral to other services. However, this was not captured in the study. Our negative findings are in contrast with other research in the effectiveness of brief lifestyles interventions in the PHC setting. Most of that research has been conducted in family practice, in services where the nurses were involved in the care of the clients in an ongoing way, or involved major input from referral programs or providers outside PHC [35-38]. However, only a minority of clients of community health nurses in this study received care for longer than 6 months. As has been noted, in the short term many clients had reduced capacity for physical activity because of their illness. Thus while community nurses have the opportunity to assess and initiate behavioural interventions, these need to be provided in the context of long-term care. Another possible contributor to the negative finding may be related to the relatively high proportion of patients Table 5 Shift to higher change stage between baseline and 6 months for clients with SNAPW risk factors Clients with SNAPW risk factors Increase fruit and vegetable intake Increase physical activity Reduce alcohol consumption Reduce or quit smoking Reduce weight Intervention site EI LI EI LI EI LI EI LI EI LI n = 101 n = 105 n =34 n =18 n = 57 n =42 n = 24 n = 18 n = 96 n = 97 Did not shift to a higher stage of change 66.3% 61.9% 41.2% 72.2% 80.7% 81.0% 70.8% 44.4% 64.6% 55.7% Shifted to a higher stage of change 33.7% 38.1% 58.8% 27.8% 19.3% 19.0% 29.2% 55.6% 35.4% 44.3% Chi square (one-sided) 0.439 4.54 0.001 2.973 1.60 p = 0.303 p = 0.032 p = 0.593 p = 0. 080 p = 0.132 Bolded figures represent significant differences between the sites. Table 6 SNAP risk factors scores at baseline, 3 and 6 months Number Baseline 3 months 6 months Early Late Early mean 95%CI Late mean 95%CI Early mean 95%CI Late mean 95%CI Early mean 95%CI Late mean 95%CI Diet scorea 195 201 3.98 (3.76-4.20) 3.98 (3.77-4.19) 4.48* (4.20-4.76) 4.30* (4.03-4.57) 4.44* (4.16-4.72) 4.54* (4.23-4.85) Physical activity scoreb 60 42 1.73 (1.39-2.07) 1.40 (0.99-1.81) 2.32* (1.87-2.77) 2.48* (1.86-3.10) 2.63* (2.15-3.11) 2.74* (2.06-3.42) Weight (overweight) 77 104 81.0 (78.9-83.1) 80.3 (78.3-82.3) 80.7 (78.2-83.2) 80.4 (78.1-82.7) 81.0 (78.5-83.5) 81.7 (79.4-84.0) Weight (obese) 112 82 101.4 (97.8-105.1) 102.3 (98.4-106.3) 100.4 (96.6-104.2) 102.3 (96.8-107.8) 100.3 (96.7-103.9) 101.6 (97.1-106.1) * Significant difference from baseline. a Total number of serves of fruit and vegetables per day up to maximum of 7. b scored 0–8, <4 considered at risk.  Harris et al. BMC Public Health 2013, 13:375 Page 8 of 11 from lower two fifths of socioeconomic disadvantage of  ma
ny community nursing service clients. This might  suggest the need for intervention to address social and  environmental factors at the community level. Certainly  transport and cost was a major barrier to referral identified  by the nurses themselves [33].  Following on from initial assessment and advice, clients  who are ready to change need to be linked into longerterm care pathways which support them in changing their  risk factors and maintaining them over time. The referral  of clients to lifestyle interventions, programs and groups  (i.e. Assist, the fourth ‘A’ in the 5As Model) might be a  necessary step for many clients to achieve improved health  outcomes and reduce risk factors [39,40]. In this study at  risk clients infrequently recalled having been referred and  other research has identified numerous barriers to referral  [41]. The fifth ‘A’, Arrange follow up, is important in the  maintenance of behaviour change even over the medium  term. Prerequisites for these two actions include adequate  availability and affordability of referral services, improved  communication, and transfer of care between community  health nurses and other providers involved in long-term  care. These long-term providers may include the client’s  GP, private or public allied health professionals, or other  community services and programs. Critical to this transfer  is clarity about who is prepared to take on the role of coordinating and monitoring the client’s lifestyle risk factors  over months and years.  There are a number of limitations in the study that  need to be acknowledged. The data are based on self-report  by clients which may have introduced bias especially for  weight. Nurses from the LI (comparison) sites commented  that simply answering the initial survey prompted them  to be more aware of the need to include addressing  lifestyle risk factors in their professional care of their  clients (i.e. the Hawthorne effect) [42]. This may account  for the improvement in physical activity and diet scores  in both groups. This study adopted a quasi-experimental  design because it was not feasible to randomise the  intervention according to individual clients or practitioners within the services. The overall response rate  could also have introduced bias affecting the generalisability  of the findings, as more interested clients may have chosen  to participate.  Conclusion  The study demonstrated that an intervention to provide  community nurse training and support for management  of clients’ SNAPW risk factors was associated with  increases in advice and referral of clients with risk factors.  This was associated with some improvement in client  readiness for physical activity. There were no changes,  however, in lifestyle behaviours or weight. This suggests a  need to facilitate referral to more intensive interventions  for clients with risk factors identified by community  health nurses and for follow up by providers involved in  Table 7 Diet and physical activity scores and weight: multilevel regression models  Diet score Physical activity score Weight  Diet Score (F & V Serves) beta SE beta SE beta SE  Time (1,2,3 = 0, 3 and 6 months) 0.039 0.044 0.003 0.077 −0.107 0.298  Intervention (early) −0.178 0.125 0.032 0.146 0.142 2.13  Male −0.776 0.110 0.195 0.133 5.376† 1.605  Age (BL) 0.006 0.007 0.002 0.008 −0.548† 0.090  Employed 0.206 0.170 0.227 0.224 −13.30† 2.300  Retired 0.420* 0.177 −0.157 0.244 2.052 2.460  Wound management −0.134 0.229 0.279 0.242 −1.013 3.708  Catheter/incontinence 0.055 0.399 0.052 0.468 −6.318 6.884  General post hospital care 0.144 0.315 0.647 0.354 6.700 4.874  Other −0.334 0.281 0.395 0.321 1.521 4,522  Mental health – good −0.240 0.133 −0.07 0.169 5.938** 1.917  Self-reported good health 0.135 0.118 0.394** 0.146 −5.169** 1.676  No. of health conditions −0.045 0.031 0.005 0.038 0.185 0.425  No. of risk factors −0.068 0.049 0.038 0.053 0.377 0.687  Variance explained  Client level 16.1% 41.6% 0%  Time level 3.8% 1.3% 15.5%  * p >< 0.05 ** p < 0.01 † p < 0.001. SE: standard error. Harris et al. BMC Public Health 2013, 13:375 Page 9 of 11 long-term continuing care. This presents a challenge for the community health care sector and to current practices regarding communication and linkage between primary health care and other services in the Australian health care system. Competing interests The authors declare that they have no competing interest in the conduct of this study. Authors’ contributions All authors contributed to the study design and reviewed and approved the final manuscript. Acknowledgements The authors wish to acknowledge the former Centre for Health Advancement, NSW Ministry of Health for funding the study. This paper is presented on behalf of the CN SNAP project team which includes: S Buckman, K Partington, A Mitchell, H Smith, J Asquith, R Whittaker, M Hilkmann, C Lisle, K Caines, S Clark, S Dunn, B Christl, M Mangold and R Phillips. Received: 12 September 2012 Accepted: 16 April 2013 Published: 22 April 2013 References 1. 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