| | A randomised controlled trial on the effectiveness of a primary health care based counselling intervention on physical activity, diet and CHD risk factorsReceived 6 March 2007; received in revised form 13 September 2007; accepted 23 September 2007. Abstract ObjectiveThe aim of the study was to determine if multiple patient-centred lifestyle counselling sessions would be of interest to patients at risk of coronary heart disease (CHD), in a primary care setting, and if such sessions would result in changes in physical activity and diet, and health status. A randomised trial was conducted to compare the counselling intervention with usual care (health promotion leaflet), among 334 mostly obese patients. MethodsPatients were randomised into an intervention group that received standard exercise and nutrition information plus up to five face-to-face counselling sessions with a Physical Activity Specialist (PAS) and Registered Dietitian (RD) over a 6-month period or to a control group that only received the standard information. ResultsOf those invited, patients randomised tended to be more obese, older and female. The mean (S.D.) sessions attended was 2.0 (1.6) with 50% attending at least 3. At 6 months, the counselling group were more active, particularly with respect to walking, and had reduced weight, blood pressure and cholesterol, but had not changed their diet, compared with the control group. Furthermore, those who did more sessions had greater increases in activity and reductions in weight, blood pressure and cholesterol. ConclusionAttending multiple sessions of client-centred counselling in primary care was of interest to patients, and generally reduced CHD risk factors. Practice implicationsThe primary care setting can be used effectively to promote particularly walking, using physical activity specialists and dietitians trained to use an adapted motivational interviewing (MI) counselling style. 1. Introduction  The global prevalence of obesity is increasing with major implications for a range of diseases such as Type 2 diabetes, heart disease, cancer [1], [2], [3] and fatigue-related problems [4], with major economic implications for society [5]. Even small changes in diet (by reducing fat consumption and increasing fruit and vegetable intake) and physical activity have been shown to reduce disease risk by up to 50% [6], [7], [8] through the prevention of a positive energy balance [9]. Primary care interventions that target both diet and energy expenditure (and not necessarily fitness) are therefore considered to be most effective for obesity management, and are at least as cost-effective as drug therapy and surgery [5]. However, the most effective way to facilitate small changes in multiple health behaviours within the primary health care setting is less clear and further research is needed [10]. Research involving primary care lifestyle counselling interventions, involving physical activity promotion, has tended to focus on changing single behaviours with just a few exceptions [11], [12], [13], [14], [15], at least in terms of how the results have been reported [16]. One good reason for this is to establish specificity in the link between an intervention (e.g., physical activity promotion) and outcome (e.g., change in physical activity). Pragmatically, patients may be interested in changing diet or physical activity or both, but it is not known how such preferences are manifested where both a dietitian and physical activity specialist advisor are available, for multiple consultations. Traditional advice giving can create resistance to change among patients especially if it is focused towards behaviour change for which there is little or no readiness to change [17]. In contrast, motivational interviewing (MI) is a client-centred counselling approach that enables patients to explore their beliefs about their health (and associated attributions) and be guided towards self-generated solutions for positive changes in health behaviours [18], [19] Patients in primary care appear to have a preference for a patient-centred approach to consultations rather than more directive advice giving [20]. There is evidence that MI interventions are generally effective for behaviour change; and reducing coronary heart disease (CHD) risk factors in health care settings, but the quality of research has been generally poor and most trials have taken place in North America [18], [21], [22]. Some studies have not included objective measures of behaviour (e.g., by accelerometer) or biological measures (of CHD risk factors), which provided a threat to external validity. Also, studies showing less effectiveness have typically involved minimal intervention intensity (e.g., a single 15 min session with a patient), delivered by health care providers (rather than a physician), and involvement of generally healthy participants [22], [23], [24], [25]. Further research is needed to explore the effectiveness of multiple sessions of MI targeted at multiple health behaviour change, delivered by health care providers, and involving patients with greater CHD risk. Objective biological measures in such research would also help to verify the effectiveness of MI on changing CHD risk. The present study therefore had several aims: (1) to determine the uptake of consultations with a Physical Activity Specialist (PAS) and Registered Dietitian (RD), in a primary care based trial, and the CHD risk factors associated with attendance. (2) To determine the effects of an MI-based intervention on CHD risk factors (i.e., diet, physical activity, body mass index (BMI), weight, blood pressure and cholesterol), among patients with one or more cardiovascular risk factors. (3) To determine the effects of number of counselling sessions attended on any change in CHD risk factors. 2. Methods 2.1. Participants and recruitment Approval was obtained from the local NHS Research Ethics committee and Research Governance committee. Participants were drawn from a patient electronic database at a local health centre. Inclusion criteria were: aged 18–65 years, and at least one of the following CHD risk factors; excess weight (BMI of 28 or more), hypertension (SBP/DBP at least 150/90mmHg) or hypercholesterolemia (at least 5.2mmol/L). A BMI of 28 or more (rather than the conventional 30) was used because this was the desired figure used for the general practice's database. No data was available for physical activity. Sample size calculations determined a need for approximately 120 in each group at follow-up in order to have a 97% of detecting a net change in BMI of 2 (S.D.=4); an 80% chance of detecting a change in SBP of 7 (S.D.=19) and a 73% chance of detecting a change of 4 (S.D.=12) in DBP. Our aim was to recruit a total of approximately 350 patients to allow for subject attrition at follow-up. A total of 1439 patients were contacted by mail with an invitation letter and information sheet telling them about the study. Three hundred and fifty eight (28%) accepted the invitation to enter the study by completing a form and returning it in a stamped addressed envelope. Sampling bias is reported in Section 3. These patients were randomised into the intervention and control arms of the study. A statistician, who had no contact with the participants, was asked to randomly allocate the participants in the ratio of 7:5 to the intervention and control groups. Randomisation was achieved by sorting the data (patient records) into strata defined by gender and age. The patients within each stratum were divided into blocks of 12 and then randomly allocated to the intervention and control groups in the ratio of 7:5, using computer generated random numbers. Unequal groups (in the ratio of 7:5) were unlikely to have an effect on the power of the test and were done because we expected a higher number of dropouts in the intervention group. This is a form of stratification and is considered acceptable to avoid ending up (by chance) with groups that are unbalanced by age and/or sex. Participants who wished to take part in the study were contacted by phone by a research assistant (RA) to ensure eligibility for inclusion in the trial and arrange a baseline assessment with a practice nurse (PN) at the health centre. Patients were requested not to eat for 12h prior to attending the session. At the first assessment, patients provided informed consent, completed various questionnaires to assess psychological constructs and lifestyle behaviour, and bio-physical tests. The practice nurse was blind to the treatment allocated to each patient at baseline and all subsequent assessments. An Emis number was used (NHS identifier) by the PN to identify patients. All participants received a standard leaflet that provided information on exercise and nutrition at their baseline assessment. Participants allocated to the counselling intervention (treatment) were then given an appointment for their first face-to-face consultation with a Physical Activity Specialist (PAS) or a Registered Dietitian (RD), with the opportunity to meet on up to four further occasions, for 20–30min, within the following 6 months. Patients were not required to attend five sessions but were offered the opportunity to do so, based on the premise that further sessions may be helpful or necessary for some patients, particularly those in the lower stages of motivational readiness to change. Participants were informed that both the PAS and RD were trained to help patients address lifestyle changes, whether these are in the area of physical activity or diet. The PAS was a graduate in Exercise Science, specialising in Exercise Psychology. She was also registered on the national Register for Exercise Professionals and had experience of promoting exercise to special populations. Within the consultations, the focus on diet or physical activity would depend largely upon the participant's priorities and readiness to change. They were informed that they would be contacted again by the RA to arrange a follow-up assessment after 6 months. 2.2. Counselling intervention The counselling sessions were delivered by one trained PAS and one trained RD. Training focused on delivering a patient-centred counselling intervention that incorporated principles and strategies from models of psychotherapy and behaviour change theory. In particular, the aim was to integrate MI with a stage-matched approached [26], and we refer to this as adapted MI (AMI). The nature of each consultation was unique to the individual and visit. However, key strategies and techniques were used that adhere to the spirit of MI [19]. Unlike traditional health education programmes, the patients were not told the reasons for change; rather, open-ended questions and reflective listening were used to elicit expressions of concern from the patients about current health status [27]. Different strategies were used depending on an individual's needs and readiness to change. 2.3. Counsellor training and treatment fidelity The PAS and RD participated in two 4-h training sessions (conducted by the first author). The first session focused on the principles of AMI, and the nature of motivation. The key principles underlying the spirit of MI that were emphasised included (1) that direct persuasion is ineffective in eliciting change (2) that it's the client's task to articulate the reasons for change and resolve ambivalence and (3) that the relationship between client and practitioner should be viewed as a partnership rather than as the traditional expert/recipient model [28]. Phase one strategies (designed to build intrinsic motivation for those in the lower stages of readiness and for those who are ambivalent about change) such as agenda setting, exploring the decisional balance and eliciting change talk by using the importance and confidence rulers were practiced. The second session focused on phase two strategies (suitable for those who are sufficiently motivated to change their behaviour) where the goal was to strengthen commitment to change and developing a plan to accomplish it. The practitioners went through a menu of possible strategies they could use with patients depending on motivational readiness. These included agenda setting, exploring the pros and cons, exploring concerns/building confidence, providing information, asking key questions and negotiating a change plan. At the end of the two training sessions, and during the first 2 weeks of consultations, the PAS and RD taped three consultations. These formed the basis for a structured dialogue between the trainer and health professional, where the practitioners were able to discuss the difficulties of conducting AMI and the trainer assisted with troubleshooting suggestions. At this meeting, the main principles and spirit of MI were re-emphasised. Throughout the intervention period, monthly meetings took place discuss issues about implementing AMI, and treatment fidelity. Analysing consultation transcripts involved several steps as advocated by Miller and Mount [29]. The first step involved assessing the degree to which they adhered to the spirit of MI and their use of key skills (i.e., asking open-questions, listening reflectively, offering statements of affirmation). The second step was to look at MI-consistent responses (e.g., affirmations, emphasising client control, and reflection) and MI-inconsistent responses (e.g., giving advice without permission, confronting, directing). The other dimension assessed was talk time. This relates to the balance of talking within a consultation and how much the practitioner talks during the session. According to Miller and Mount [29], a reasonable range is between 30 and 50%. It would appear that talk time is a reasonable indicator of likely effectiveness. Foster et al. [17] point out: “The more a clinician speaks during a session, the less effective the session will be for the patient” (p. 233). Issues relating to intervention fidelity will be further discussed in the discussion. 2.4. Outcome measures Systolic and diastolic blood pressure (SBP/DBP) (U2635, Ultracheck), fasting cholesterol, weight and height (Seca model 701 scale) were assessed by a practice nurse at baseline and at 6 months. Patients were seated quietly for 10min prior to their BP assessment. The average of three SBP and DBP readings was recorded for data entry. Patients were instructed to fast for 12h before resting blood samples were taken. Blood samples (taken between 8.30 and 11am) were couriered shortly afterwards to a nearby hospital laboratory for analysis. Self-reported physical activity was assessed using the short interview version of the International Physical Activity Questionnaire (IPAQ) [30]. The IPAQ collects data on the intensity, frequency and duration of physical activity in the previous 7 days. Subjects are asked to recall only bouts of physical activity that were at least 10min in duration of walking, moderate or vigorous intensity physical activity. Median MET-minutes for varying intensity physical activity are calculated. This is achieved by multiplying a given MET value (for the intensity of the activity) by the number of minutes in that type of intensity activity, multiplied by the number of days. The MET values for walking, moderate intensity and vigorous activity are 3.3, 4.0 and 8.0, respectively. A total physical activity score is calculated by adding up scores from the various intensity domains. The IPAQ has acceptable reliability (Spearman's rho=0.8) and criterion validity (against the MTI accelerometer), which is comparable to most other self-report validation studies [31]. Data cleaning and scoring followed the procedures outlined in the guidelines for use of the IPAQ (see http://www.ipaq.ki.se/). Fat intake (FI) was assessed using a scale from the Dietary Instrument for Nutrition Education (DINE) [32]. The DINE is a food frequency questionnaire of 19 groups of food that account for around 70% of the fat and fibre in the typical UK diet, according to the National Food Survey [33]. Foods are grouped according to nutrient content and dietary use; each group of foods is assigned a score proportional to the fat or fibre content of a standard portion size [34]. The scores are weighted according to the frequency of consumption ranging from ‘less than once a week’ to ‘six times a week or more’. Foods that are consumed more frequently are scored on a daily basis. The individual scores are added together to produce total scores for fat and fibre which can then be categorised into low, medium or high intake. The categorisation is based on the guideline of FI at 35% of energy [35]. The low fat category (a total fat score of 30 or less) is designed to represent a FI of 83g/day or less (i.e., 35% of the female energy RDA), and the high fat category (fat score greater than 40) a FI greater than 122g/day (i.e., 40% of the male energy RDA). In order to assess the validity of the DINE, a 4-day diet record, with a description of portion sizes was used as the reference method [32]. This reference method has been shown to be of acceptable validity relative to a 7-day weighed record [36], [37]. The five-a-day Community Evaluation Tool questionnaire (FACET) (www.doh.gov.uk/fiveaday) was used to collect data indicating whether patients were consuming five portions of fruit and vegetables a day. Patients were presented with a list of 14 types of food including different types of fruits and vegetables and were asked to indicate how many portions of each type of food they had eaten ‘in the last 24h’. In a recent study with a sample size of 1080 [38], 7-day food diaries were used (as the reference method) to assess the ability of the FACET questionnaire to estimate fruit and vegetable intakes. There was agreement between the food diaries and questionnaire on fruit and vegetable intake in 56% of cases. The authors conclude that the FACET questionnaire provides acceptable estimation of fruit and vegetable intakes and may be used to assess intakes in community-based projects. 2.5. Data analysis Recruitment bias was initially calculated by comparing data from patient electronic records from those who entered the trial and those invited but declined the invitation. Chi-squared (Chi2) analyses were also conducted to determine whether those with specific risk factors (i.e., smoker, obese, hypertensive, etc.) were more or less likely to attend the sessions. Changes, from baseline to 6-month follow-up, in all outcome measures were calculated and compared between the intervention and control group, using t-tests. For participants with missing data at follow-up, data was imputed, using baseline values, and intent-to-treat analyses were conducted. Those in the treatment arm of the trial were classified as low or high attendees (i.e., 0–2 vs. 3–5 counselling sessions attended). t-Tests were used to compare change in outcome variables for low vs. high attendees. 3. Results A total of 334 patients completed the baseline assessment, of whom 203 were randomised to the counselling and 131 to the control condition. Table 1 provides details of patient recruitment bias. Those entering the trial were older, more likely to be female, have a higher BMI, and a lower SBP and cholesterol. | a Chi2 value. *p<.05. ***p<.001. |
Almost all of those recruited (99%) were overweight at baseline. Furthermore, 79% of patients were obese (BMI≥30). The second most prevalent CHD risk factor was hypercholesterolemia. Fifty-seven percent of patients had elevated cholesterol at baseline (≥5.2mmol/L). With respect to physical activity, 38% of patients were insufficiently active at baseline (i.e., not meeting the recommendations as outlined in the Chief Medical Officer's report, DOH, 2004). According to the Chief Medical Officer, adults should accumulate at least 30min of moderate intensity physical activity on 5 or more days of the week [6]. In relation to blood pressure, 35% of patients had raised systolic blood pressure (≥140mmHg) and a quarter had raised diastolic blood pressure (≥90mmHg). Sixteen percent of patients were smokers at baseline. The mean (S.D.) number of counselling sessions attended was 2.0 (1.58), with the largest proportion of participants (38%) having three consultations with the PAS and/or RD over the 6-month period. Overall, 12% had four or five consultations, 14% had two consultations; 4% attended one consultation and 32% failed to attend any consultation. Half of participants attended three or more sessions. Table 2 shows the number and percentage of participants, by risk category, who attended the respective number of sessions. Due to small numbers in some cells, data was collapsed to compare those who had done less than 0–2 sessions vs. 3–5 or more sessions. The Chi-squared analyses on CHD risk factors and consultation attendance revealed no significant associations. The mean (S.E.M.) consultation attendance for smokers vs. non-smokers was 2.0 (0.13) vs. 1.9 (0.26); and for the obese vs. non-obese (2.1 (0.13) vs. 2.4 (0.25). The mean (S.E.M.) consultation attendance for hypertensives vs. non-hypertensives was 2.4 (0.28) vs. 2.1 (0.13) and for those classified as hypercholesterolemic or not was 2.2 (0.14) vs. 2.3 (0.20), respectively. Table 3 shows the baseline characteristics for all who completed only the baseline, or both assessments in each arm of the trial. There were no significant differences between the groups at baseline. Complete data from both assessments was collected from 218 (65%) participants who were randomised at baseline. Those completing only the baseline assessment (compared with both assessments) were significantly younger (48 years vs. 51 years, P<.01), tended to be less physically active (1796Met-min/week vs. 2337Met-min/week, P=.08), and walked significantly less (863Met-min/week vs. 1304Met-min/week; P=0.00) at baseline. They also went on to attend fewer counselling sessions (0.3 (0.68) vs. 3.0 (0.98)), compared with those completing both assessments. | a Met-min calculated by multiplying minutes of the respective activity in the past week by 8 (vigorous), 4 (moderate), and 3.3 (walking). Overall PA (physical activity) is the sum of vigorous, moderate and walking Met-min. |
Using an intent-to-treat analysis, t-tests (to compare mean change scores from baseline to follow-up) revealed no significant differences between the groups for vigorous and moderate physical activity, as shown in Table 4. However, the counselling group significantly increased their walking (t=−2.72, P=0.01) (by a net 114min/week), and their combined physical activity (t=−1.95, P=0.05) when compared to the control group. A Chi-squared test revealed a significant difference in change with 42% inactive (less than 600Met-min/week) at baseline and 25% at follow-up in the counselling group, compared with 31 and 27%, respectively, in the control group (P=0.005). With respect to diet, there were no differences in fruit and vegetable consumption (t=−0.61, P=0.55). Both groups increased their fruit and vegetable consumption and reduced their fat intake. However, the control group significantly reduced their fat intake compared to the counselling group (t=−2.72, P=0.01). | | |  | Outcome | Intervention group ( n= 203) | Control group ( n= 131) | | t-Value | |
|---|
| BMI (kg/m2) | −0.21 (0.10) | 0.15 (0.10) | 0.07, 0.64 | 2.48** | | | Bodyweight (kg) | −0.70 (0.25) | 0.12 (0.29) | 0.02, 1.51 | 2.02* | | | SBP (mmHg) | −2.90 (0.76) | −0.60 (0.93) | −0.13, 4.62 | 1.86 ns | | | DBP (mmHg) | −1.98 (0.51) | 0.49 (0.63) | 0.88, 4.06 | 3.05*** | | | Cholesterol (mmol/L) | −0.14 (0.05) | 0.00 (0.06) | −0.01, 0.30 | 1.86 ns | | | HDL (mmol/L) | −0.05 (0.01) | −0.07 (0.03) | −0.08, 0.03 | −0.89 ns | | | LDL (mmol/L) | 0.09 (0.07) | 0.25 (0.08) | −0.04, 0.37 | 1.55 ns | | | Triglycerides (mmol/L) | −0.17 (0.08) | −0.15 (0.08) | −0.20, 0.25 | 0.19 ns | | | Total physical activity (Met-min/week) | 245 (104) | −122 (158) | −739, 4.70 | −1.95* | | | Vigorous physical activity (Met-min/week) | 149 (64) | 50 (109) | −348, 150 | −0.78 ns | | | Moderate physical activity (Met-min/week) | 89 (72) | −29 (97) | −358, 121 | −0.98 ns | | | Walking (Met-min/week) | 198 (63) | −145 (109) | −592, −94 | −2.72** | | | Fat intake (% fat intake per day) | −0.92 (0.43) | −2.92 (0.60) | −3.46, −0.55 | −2.72** | | | Fruit and vegetable intake (portions per day) | 1.05 (0.30) | 0.73 (0.44) | −1.36, 0.72 | −0.61 ns | | | | |
| a 95% confidence interval (CI) for the mean difference in changes from baseline. |
Using an intent-to-treat analysis, t-tests (to compare mean change scores from baseline to follow-up) revealed significantly greater reductions in BMI (t=2.48, P=.01), DBP (t=3.05, P=.01) and a trend towards greater reductions in SBP (t=1.86, P=.06) and cholesterol (t=1.86, P=0.06), for the counselling vs. control condition. There were no differences between the groups in change in LDL, HDL or triglycerides. Analyses were also conducted to explore the effects of consultation attendance on the various outcomes. Data in Table 5 shows that those who attended more counselling sessions had a greater reduction in bodyweight (t=2.24; P=0.03), SBP (t=2.80; P=0.01), cholesterol (t=2.12; P=0.04), HDL (t=2.41; P=0.02), and triglycerides (t=2.42; P=0.02). High attendees lost a net (1.04kg), reduced SBP/DBP by 4.07/2.75mmHg, and cholesterol by 0.19mmol/L over the 6 months, compared to low attendees. Furthermore, of those making substantial changes in weight (5% of bodyweight or more; n=21), 86% of these were in the intervention group. There were no significant differences for any physical activity measure, although the high attendees increased their vigorous, walking and overall activity compared to low attendees. | | | | Outcome | Low attendees ( n= 102) | High attendees ( n= 101) | | t-Value | |
|---|
| BMI (kg/m2) | −0.14 (0.13) | −0.27 (0.15) | −0.26, 0.53 | 0.69 ns | | | Bodyweight (kg) | −0.09 (0.16) | −1.13 (0.43) | 0.12, 1.95 | 2.24* | | | SBP (mmHg) | −0.73 (0.73) | −4.80 (1.30) | 1.20, 6.96 | 2.80** | | | DBP (mmHg) | −0.50 (0.45) | −3.25 (0.84) | 0.86, 4.64 | 2.88** | | | Cholesterol (mmol/L) | −0.04 (0.05) | −0.23 (0.07) | 0.01, 0.36 | 2.12* | | | HDL (mmol/L) | −0.01 (0.02) | −0.07 (0.02) | 0.01, 0.11 | 2.41* | | | LDL (mmol/L) | 0.03 (0.06) | 0.13 (0.12) | −0.37, 0.16 | −0.80 ns | | | Triglycerides (mmol/L) | 0.03 (0.11) | −0.35 (0.11) | 0.07, 0.69 | 2.42* | | | Total physical activity (Met-min/week) | 171 (75) | 323 (197) | −571, 266 | −0.72 ns | | | Vigorous physical activity (Met-min/week) | 74 (54) | 225 (117) | −407, 104 | −1.17 ns | | | Moderate physical activity (Met-min/week) | 123 (69) | 56 (128) | −221, 354 | 0.46 ns | | | Walking (Met-min/week) | 164 (66) | 235 (110) | −325, 183 | −0.55 ns | | | Fat intake (percent of fat intake per day) | −0.76 (0.44) | −1.07 (0.74) | −1.39, 2.02 | 0.36 ns | | | Fruit and vegetable intake (portions per day) | 0.83 (0.27) | 1.27 (0.52) | −1.61, 0.72 | −0.75 ns | | | | |
| a 95% confidence interval (CI) for the mean difference in changes from baseline. |
We also examined the effects of the intervention for only those completing both assessments (N=218). The counselling group increased their mean (S.E.M.) amount of walking by 474 (142)Met-min/week compared with the control group who decreased by 81 (180)Met-min (t=−2.42, CI, −1001 to −102; P=0.02) (i.e., a net increase of 168min/week). Despite there being no significant differences in overall physical activity change between the groups, a Chi2 test did reveal that a significantly higher proportion of those receiving counselling (63%) compared to those in the control condition (46%), increased their overall physical activity (P=0.02). Compared with control group, the counselling group also reduced the following, shown as mean (S.E.M.) values: bodyweight by −0.96 (0.33)kg (CI, 0.07–1.96) (cf. increase of 0.06 (0.35)kg) (t=2.13, P=0.04); DBP by −3.16 (0.74) (cf. increased of 1.18 (0.84)mmHg) (CI, 2.14–6.54) (t=3.89, P<0.01); cholesterol by −0.21 (0.07)mmHg (cf. increase of 0.04 (0.09) (CI, 0.02–0.48) (t=2.18, P=0.03); LDL by −0.03 (0.08)mmHg (cf. increase of 0.29 (0.10) (CI, 0.06–0.60) (t=2.46, P=0.02). There were no differences between the groups on fruit and vegetable consumption (P=0.7), with both groups reporting an increase. The increase in the counselling group was 1.37 portions (0.28) compared to 1.20 portions (0.35) in the control group. Both groups reported a reduction in fat intake between assessments and the reduction was significantly greater (t=−2.22, P=0.03) in the control group (−4.73% (0.84)) compared to the intervention group (−2.27% (0.72) (CI, 4.64 to −0.27). 4. Discussion and conclusion 4.1. Discussion Few studies have attempted to change both physical activity and diet, with the opportunity for patients to attend multiple counselling sessions with either a Physical Activity Specialist and/or a Registered Dietitian in the primary care setting. The present study showed that almost one-third of patients with elevated CHD risk were interested in such an intervention, with less interest from hypertensives and slightly greater interest from older women, as suggested in other studies (e.g., Ref. [39]). Of those randomised to the intervention, there was generally positive interest in attending the counselling sessions. Our main question was what effects the intervention would have on behavioural and bio-physical outcomes? Using the most conservative approach our intent-to-treat analyses revealed that counselling led to an increase in total energy expended from physical activity, largely due to increases in walking (and decreases among the control group). Other primary care trials (e.g., Ref. [24]) have reported increases in physical activity in the control condition which has masked any overall net effect in the study. In the present trial we simply gave those patients assigned to the control condition a health promoting leaflet which was evidently insufficient to increase physical activity. It is not easy to explain why there appeared to be greater reductions in fat intake among the control group, especially since there were greater reductions in BMI among the counselling group. One explanation may be that patients were central to what was discussed during the AMI counselling sessions and, perhaps feeling well informed (from general media attention) about fat intake, tended not to focus conversation on how to change this aspect of their lifestyle. Certainly, the baseline data suggests that the sample ate reasonably well, with over six portions of fruit and vegetables consumed daily, and a mean of less than 25% daily fat intake. The increases in walking were encouraging, and clearly the most popular changes in physical activity. This appears to be one of the first studies to demonstrate support for the IPAQ's ability to detect differences in change, at least in terms of walking. It is unknown if the smaller changes in other moderate and vigorous activity were real or due to poor sensitivity in the survey. However, the former seems more likely based on the feedback from the PAS and RD who reported that much of their communication with patients focused on walking rather than other forms of activity. However, evidence since we conducted the trial has shown that the IPAQ may be less valid and reliable than the 7-day recall [40]. If we are to assume that the counselling intervention was effective in changing walking and not dietary behaviour, then the study provides evidence that such a change is sufficient to reduce weight, blood pressure and cholesterol. The overall reductions were relatively small, compared to our estimates for powering the study, but the study does highlight how a focus on promoting walking in primary care can make a clinical difference. Since the intervention appeared to have little impact on dietary behaviour, it could be argued that a dietitian is unnecessary. However, it may be that the tools used to gauge eating behaviour were not sufficiently sensitive to detect such changes. For future research and practice, perhaps a more appropriate title for a practitioner delivering a similar intervention could be ‘Behaviour Change Specialist’ or ‘Lifestyle Counsellor’. This could be an individual who has a good knowledge of behaviour change theories and principles and counselling skills, and could deliver client-centred counselling across a range of lifestyle behaviours including diet, physical activity, smoking, etc. We did not set out to conduct a full cost-benefit analysis but we recognise the importance of identifying the cost of such an intervention. The estimated cost of delivering the intervention was based on the hours of staff time (16h/week for 40 weeks) relative to the mean number of counselling sessions attended (mean sessions attended=2) by all those randomised into the counselling group who attended the baseline assessment (n=203). On average, each patient received 1h of counselling. Therefore, the average cost of delivering the intervention per patient was between £47 and £63 (depending on the expertise and experience of the practitioner). The cost is relatively cheap, given the potential health gains possible from using such an approach. Our final question was concerned with intervention intensity and the effects on various outcomes. The number of counselling sessions attended was not related to our behaviour measures of physical activity and diet, but was associated with greater reductions in weight, cholesterol, and triglycerides. This may be due to possible limitations with our self-reported measure of physical activity or insufficient power to detect significant differences in sub-group analyses. It does appear that there may be a dose–response relationship between counselling sessions attended and changes in important clinical outcomes which has rarely been reported in the literature (e.g., Ref. [41]). The present study was not powered to examine the dose–response effects but further research is clearly needed to confirm such a relationship, especially given the importance attached to health economics and cost-benefit analysis. However, we allowed patients to engage in up to 5 counselling sessions within the framework of AMI, and it may be that restricting patients to say 1, 3 or 5 sessions would undermine the nature of the present intervention. One limitation of the study concerns the low participation rate (28%). However, this was not entirely surprising given the opt-in procedure used (indeed required by the local NHS Ethics Committee) and that among those at risk of CHD, many are not ready to change important lifestyle behaviours and therefore are unlikely to volunteer for such a trial. Other similar trials [11] have reported equally low participation rates (36.5%) even when patients were invited by phone contact and recruited on site. One might expect a much higher participation rate, given such proactive recruitment strategies. Another limitation of the study was the exclusion of patients over 65 years old. The reasoning for this restriction was due to concerns over contraindications to do physical activity (particularly musculo-skeletal problems) and the more extensive screening procedures necessary. However, it is worth noting that the effects reported may well have been greater had older patients, with potentially more to gain, been included in the study. In reflection, the training of the PAS and RD in AMI was both a crucial and yet challenging task. It was crucial to the impact of the intervention and challenging because it was difficult to know how much training to provide or to gauge the level of support either wanted or required. With additional resources, greater attention could have been given to identifying the initial communication styles of the practitioner involved, in order to develop greater awareness of any discrepancies with an MI approach during training [42]. While we did not conduct a thorough process evaluation we do feel that the observed effects probably underestimate the potential efficacy of the intervention, and a closer analysis of treatment fidelity may well have supported this [43]. 4.2. Conclusion The present trial demonstrates that particularly obese females are interested in engaging with physical activity specialists and dietitians in the primary care setting. Multiple sessions of adapted motivational interviewing increased physical activity, especially walking, and resulted in reduced weight, blood pressure and cholesterol. Greater reductions in weight, blood pressure and cholesterol were associated with attending more counselling sessions. 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a University of Brighton, Eastbourne, UK b University of Exeter, Exeter, UK c University of Brighton, Brighton, UK  Corresponding author at: Chelsea School, Denton Road, Eastbourne, East Sussex BN20 7SR, UK. Tel.: +44 1273 643761.
PII: S0738-3991(07)00376-X doi:10.1016/j.pec.2007.09.014 © 2007 Elsevier Ireland Ltd. All rights reserved. | |
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