Background
Obesity represents a global and increasing challenge for healthcare providers. According to the World Health Organization (WHO), the worldwide prevalence of obesity nearly tripled between 1975 and 2016, with an estimated number of over 650 million (13%) adults with obesity in 2016 [
1]. In Germany, almost one in four adults (23% of men and 24% of women) can be classified as obese [
2]. This increase is alarming considering the wide range of health-related risks that are associated with obesity [
3,
4]. Obesity is associated with a lower life expectancy and a risk factor for several somatic diseases such as hypertension, coronary heart disease and diabetes [
5] as well as a range of mental disorders [
6], with individuals with obesity frequently experiencing discrimination and stigmatization [
7]. Worldwide healthcare costs for patients with obesity were found to be approximately 30% higher than for individuals without obesity, with direct obesity costs resulting in around 0.7% to 2.8% of a country’s total healthcare expenditures [
8]. Consequently, tackling obesity is a major concern of the public health sector, characterized by a growing need for effective evidence-based interventions for obesity treatment and prevention.
Concerning the management of obesity and related medical conditions, the primary care setting plays a crucial role in the delivery of care. As gatekeepers to the healthcare system, general practitioners (GPs) are among the first to be contacted when secondary diseases and comorbidities arise. Considering that their interactions with patients take place on a regular basis, GPs may be specifically suited to address overweight and obesity. An important factor for patients with obesity to attempt weight loss may thereby lie in their health care professionals’ communication of overweight status, as well as their advice to lose weight [
9,
10]. However, hindering aspects of obesity management in the primary care setting have been identified considering both GPs and patients [
11‐
15]. Barriers include GPs’ lacking recognition of obesity [
12] and insufficient amounts (42%) of GPs perceiving themselves to be well prepared for treating patients with excess body weight [
13]. On the other hand, research indicates that patients are unlikely to address weight when consulting a GP due to tight time constraints or seem to prefer other health care professionals, such as personal trainers or dieticians above medical practitioners for weight management [
14]. Another important aspect in this regard is the physician–patient-relationship. Physician–patient-interactions in primary care have previously been linked to patient’s experience of chronic care [
16] and the self-management behavior of patients such as uptake of preventive activities, management of personal distress and medication adherence [
17‐
20]. In turn, higher patient motivation and self-management behavior have been associated with better self-reported and physical health outcomes [
20,
21]. Therefore, effective tools are needed to improve communication and management of obesity in primary care. Recently, the 5A model has been proposed as a framework to improve weight counseling in the primary care context [
22]. The 5A was initially developed as a tool for counseling on smoking cessation and has later been adapted for the context of weight management counseling [
23]. The 5As comprise the assessment of risk, asking about readiness to lose weight, advising on change, assisting in establishing interventions, and arranging for follow-up visits. Previous research has promoted the 5As as an effective tool to increase quit rates and to enhance motivation in smoking cessation [
24‐
26]. In the context of counseling on weight GPs seem to be inconsistent in using the 5As with their patients [
27]. While GPs routinely ask and advise patients about losing weight, they rarely engage in the strategies of assess, assist and arrange [
27].
The Canadian Obesity Network (CON) has proposed a standardized framework for a 5A-based weight management counseling, the “5As of Obesity Management” [
28]. Comprising handout material and an online tutorial, this framework synthesizes the Canadian Obesity Guidelines [
29] with the concept of the 5As [
28]. It provides an elaborated and clear guidance in weight management counseling and motivates physicians to focus primarily on improvements in health with their patients [
22,
28]. While weight loss is an important goal to improve health and well-being in many patients, it may not be equally suitable for all patients with overweight or obesity as the amount of excess body weight alone may not be a reliable indicator of poor health per se [
9,
22,
30].
Previous research reporting positive effects of 5A-based interventions has mostly assessed effects in short-or medium-term [
31‐
33], whereas research on long-term effects of 5A-based counseling has been more inconclusive [
34,
35]. While one study found no change in the overall number of counseling dialogues regarding physical activity 6 months after a 5A training [
34], another study reported a significant change in patients’ weight 12 months post-intervention [
35]. To our knowledge, there are no results on the long-term effectiveness of the 5As of weight counseling for the German primary care context.
As competing demands on time hinder physicians to integrate preventive and counseling services in their day-to-day work [
36,
37] a brief web-based 5A application that allows for a flexible and customized use may be specifically suitable in order to improve GPs counseling technique. A web-based tutorial with brief educational information and a clear design has the advantage of providing GPs with relevant information on weight counseling right at the time they are needed (e.g. in preparation of preventive services or in between patients), which in turn may help GPs to integrate such weight counseling services to a greater extent.
The objective of this study was to investigate the effectiveness of a short and flexibly usable 5A-based online tutorial for GPs. The 5A-based online intervention aims at improving the quality of care and the physician–patient-interaction in the context of weight management. Consequently, the effectiveness of the 5A-based intervention was assessed via the patients’ perception of the quality of care provided to them.
Methods
Setting and trial design
The INTERACT study comprised a cluster-randomized controlled trial (cRCT) with an intervention condition (IG) and a waiting list condition (CG). The trial was set within the primary care setting in the region of central Germany. GPs from registered practices were invited to participate in the INTERACT study and to recruit eligible patients. Randomization took place at the level of GPs, which served as the clustering variable. GPs allocated to the IG received access to a 5A online tutorial which offers education on weight counseling according to the “5As of Obesity Management” by the Canadian Obesity Network [
28]. GPs allocated to the CG followed the care-as-usual protocol, receiving access to the 5A intervention only after the trial was completed.
Ethical considerations
The ethics committee of the University of Leipzig (reference number 248/15-ff) approved the study. Written informed consent was obtained from all GPs and participating patients. The INTERACT study was conducted according to the latest version of the Declaration of Helsinki and the Guidelines for Good Clinical Practice [
38] as well as international and local laws.
Recruitment
GPs were recruited between January and May 2016 based on a primary care physician network, as previously established by the Institute of Social Medicine, Occupational Health and Public Health of the University of Leipzig (ISAP). GPs from the IG received continuous access to the 5A online tutorial. They were asked to complete the tutorial within two months after receiving login data. GPs from the CG had no access to the online tutorial throughout the trial and received login data to the 5A tutorial 6 months after the trial ended. GPs were granted CME points (continuing medical education) upon successful completion of the tutorial. Participating GPs received a fixed allowance of 80 Euros per recruited patient. GPs of both groups were asked to fill out questionnaires following recruitment (baseline, BL), as well as at 12-month follow-up.
The patient sample included adult patients with obesity recruited through participating GPs. Patients of both treatment groups were assessed at the time of recruitment (BL), as well as 6 months (FU1, follow-up one) and 12 months (FU2, follow-up two) after BL using comprehensive questionnaires. In order to achieve adequate response rates, patients were compensated with 30 Euros for participating in the study. Using postal reminders, GPs and patients were asked to complete the follow-up assessments.
Inclusion/exclusion criteria
Patients were included if: (1) they had a body mass index (BMI) ≥ 30 kg/m2, (2) they were between 18 and 60 years old and (3) they had sufficient proficiency in the German language. Patients were excluded if they had an acute medical condition (physical or mental) that required prioritized treatment and made study participation impossible according to the attending GP. There were no in- or exclusion criteria for GPs.
Randomization and blinding
After study inclusion, GPs were sequentially allocated to intervention or control group using a computerized random number generator in an adaptive randomization process (biased coin design) [
39]. Patients were blinded to their group allocation. Blinding of GPs towards the treatment groups was not possible since GPs were directly addressed by the intervention. GPs were informed about their group allocation via postal mail with a sealed envelope after the randomization process was completed. Additionally, GPs received recruitment material and consent forms. A research assistant gave the participating GPs instructions about the recruitment material and procedure of the patient recruitment by telephone. Based on the inclusion and exclusion criteria, GPs then identified and recruited eligible patients within their practices. Patients received information about the study and they were asked to participate by their attending GP. Information material and consent forms were identical for patients of both treatment groups. A statistician who was blinded to the group allocation conducted the data analyses.
Interventions
The web-based 5A intervention
The 5A framework offers a simple tool for GPs to improve patients’ weight management counseling in primary care. It provides recommendations for sensitively discussing weight with the patient (“ASK”), assessing health status, comorbidities and causes of weight gain (“ASSESS”), advising on the health benefits of treatment and available treatment options (“ADVISE”), agreeing on weight loss expectations, treatment plan and treatment goals (“AGREE”) and assisting the patient in the continuous process of weight management (“ASSIST”). Rather than focusing on the amount of weight loss, successful weight management is conceptualized as improved overall health and well-being. Based on the 5As guidance for obesity management by the Canadian Obesity Network [
28], a short 5A online tutorial was developed. The 5A online tutorial comprises an introduction, five knowledge sections and a short knowledge quiz at the end. While the introduction includes information on learning objectives and basic principles of obesity management, each of the five knowledge sections covers one of the 5A components. For example, the “ADVISE” section contains information on obesity-related treatment options (physical exercise, nutrition, psychotherapy, medication and surgery) and the “AGREE” section covers criteria for defining realistic goals. Table
1 gives an overview of the components of the 5A intervention. The short quiz at the end of the 5A online tutorial consists of seven questions (e.g. “How would you react if a patient told you that he or she doesn’t want to talk about his or her weight?”).
Table 1
Overview of the components of the 5A intervention
ASK | • Discuss weight and motivation with the patient |
ASSESS | • Assess health status and obesity class, comorbidities and causes of weight gain |
ADVISE | • Advise on obesity risks, benefits of weight loss and treatment options |
AGREE | • Agree on health outcomes, weight loss expectations and treatment plan |
ASSIST | • Assist the patient in the continuous process of weight management and arrange follow-up visits |
TAU/Control group
Patients whose attending GP was aligned to the CG received treatment as usual (TAU). GPs of the CG were given no constraints regarding TAU. The treatment of obesity was therefore under the sole responsibility of the attending GP.
Outcomes
Primary outcome
Corresponding to the 5A framework,
provider-patient-interaction regarding the management of obesity was the primary outcome of the INTERACT study. Patients’ perspective on the provider-patient-interaction over the past 6 months was assessed using the German version of the Patient Assessment of Chronic Illness Care (PACIC 5A [
40,
41]). The PACIC is a widely used instrument to assess patient-centeredness and quality of care provided to patients with chronic diseases [
42‐
44]. The PACIC 5A is an extended version that furthermore assesses quality of care with regard to the 5A concept. The PACIC 5A consists of 26 items rated on a 5-point Likert scale ranging from 1 (= almost never) to 5 (= almost always). The first 20 items cover the five subscales patient activation, delivery of care, goal setting, problem solving, and follow-up. The remaining 6 items cover the 5A approach. The scoring instruction provided by Rosemann et al. [
40] was applied to calculate the PACIC 5A sum score. The PACIC 5A sum score can range from 25 to 125, with higher scores indicating a stronger perceived congruency to the 5A approach.
Secondary outcomes
Weight status was assessed using the BMI. The BMI was calculated through self-reported height (at BL) and weight (at every point of assessment).
Patients’
health-related quality of life was measured using the German version of the EQ-5D-5L [
45]. The EQ-5D-5L comprises a visual analog scale (EQ VAS) from 0 (= worst health) to 100 (= best health) and 5 questions which cover perceived impairments in five dimensions of health-related quality of life (mobility, self-care, usual activities, pain/discomfort, anxiety/depression). The five items are rated on a 5-point response scale ranging from 1 to 5 (e.g. 1 = “I have no pain or discomfort”, 5 = “I have extreme pain or discomfort”). The EQ-5D-5L sum score was calculated according to Hinz et al. [
46].
Patients’
willingness to engage in weight management strategies was measured with an adapted version of the Readiness Ruler [
47,
48], a visual analog scale assessing the readiness for a change of lifestyle in order to achieve weight loss on a scale from 0 (= not ready to change) to 10 (= ready to change).
Depressive symptoms within the last two weeks were measured with the German version of the PHQ-9 [
49,
50]. The PHQ-9 comprises nine items (e.g. “little interest or pleasure in doing things”, “poor appetite or overeating”) to be rated on a 4-point scale ranging from 0 (= not at all present) to 3 (= present nearly every day). The PHQ-9 sum score ranges from 0 (= no depression) to 27 (= severe depression), with higher scores indicating a more severe symptomatology.
Internalized weight bias was assessed using the German adaptation of the Weight Bias Internalization Scale (WBIS) [
51,
52]. The WBIS comprises 11 Items with a 7-point response scale ranging from 1 (= strongly disagree) to 7 (= strongly agree). Higher scores indicate a stronger internalized weight bias.
Weight loss intentions and activities of weight management were assessed using an adapted version of the stages of change algorithm [
53,
54]. This algorithm comprises four questions with a yes/no response scale, resulting in four categories of change (precontemplation, contemplation, action, maintenance).
Other measures
Apart from sociodemographic characteristics (age, gender, education, and marital status), anxiety symptoms, personality traits and counseling experiences of patients were also assessed.
Anxiety symptoms were measured using the subscales for ‘panic syndrome’ and ‘other anxiety syndrome’ of the PHQ-D [
49]. The subscale for panic syndrome comprises 15 items with a yes/no response scale. The subscale for other anxiety syndrome consists of 7 items scored on a 3-point response scale from 1 (= not at all present) to 3 (= present for more than half the days).
The 10-item Big Five Inventory (BFI-10) [
55] was used to assess
personality traits. The BFI-10 measures five personality dimensions with two items each on a 5-point response scale ranging from 1 (= disagree strongly) to 5 (= agree strongly).
Counseling experiences of patients with their attending GP were assessed using four yes/no questions (“Have you seen your GP within the last six months?”, “How often have you seen your GP within the last six months?, “Has your weight been discussed in the consultation and who took the initiative?”, and “Which aspects of weight have been discussed?”).
Assessment of GPs
Questionnaires for GPs contained closed questions on referral and counseling behavior of patients with obesity, satisfaction with own knowledge about obesity, attitudes towards obesity as a chronic disease, relevance of different causes of weight gain and attitudes on different aspects of obesity management.
Additionally,
stigma concerning obesity was assessed using a German adaptation of the short form of the Fat Phobia Scale (FPS) [
56,
57]. The FPS comprises 14 pairs of adjectives on a semantic differential (e.g. active = 1 vs. inactive = 5). The FPS sum score was calculated as the mean score of all 14 items. Higher scores indicate higher negative attitudes.
Moreover, GPs from the IG were asked to evaluate the 5A online tutorial concerning the relevance of its knowledge contents and its usability within the primary care setting 12 months’ post-intervention.
Sample size
According to Rueda-Clausen et al. [
31], a 15 point difference prior to post-intervention was regarded as a clinical significant change in the PACIC 5A sum score. With a power of 95%, a standard deviation of 20 points [
31] and considering an intraclass correlation coefficient of 5%, we calculated a sample size of n = 86 patients per group to measure an effect at follow-up. Power calculation and sample size have been described in detail in the study protocol [
58].
Statistical analysis
Statistical analyses were conducted using IBM SPSS Statistics (25 SPSS Inc., Chicago, IL, USA) and STATA 13.1 SE software package (StataCorp LP, College Station, TX). Descriptive statistics are presented as number of cases with percentages or means with 95% confidence intervals. Inspection of missing values in outcomes and covariates at BL revealed no systematic patterns in both treatment groups; missing information was thus handled by case wise deletion. Mixed-effects linear regression models were calculated to estimate mean differences between treatment groups in primary and secondary outcomes from BL to FU2. The models included indicators of treatment group (IG vs. CG), time (BL, FU1, and FU2) and the interaction between treatment group and time, and were adjusted for the BL outcome value and confounding factors (i.e., age, gender, education, marital status and neuroticism). Covariates were included based on previous research linking patient characteristics to patient satisfaction with the received health care [
59‐
64]. With regard to personality, neuroticism has been included as a confounding factor as it has been linked to BMI variations over time [
65], poorer health outcomes [
66], lower psychological well-being, and reduced life satisfaction [
67,
68]. Neuroticism may further affect patients’ presentation of symptoms in a way that influences medical care [
69]. In order to control for non-random dropout effects, all analyses were intention-to-treat as recommended according to the guidelines of the CONSORT statement [
70]. Standard errors were corrected for the clustered trial design using the Huber/White sandwich estimator. Regression analyses results are presented as adjusted mean group differences in outcome scores at follow-up. In addition, we estimated standard effect sizes of treatment on primary and secondary outcomes at follow-up (Cohen’s d). For all statistical analyses, the level of statistical significance was set at
p < 0.05.
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