Jolien Plaete

A Self-Regulation eHealth Intervention to Increase Healthy Behavior Through General Practice: Protocol and Systematic Development

Background Chronic diseases are the principal cause of morbidity and mortality worldwide. An increased consumption of vegetables and fruit reduces the risk of hypertension, coronary heart disease, stroke, and cancer. An increased fruit and vegetable (FV) intake may also prevent body weight gain, and therefore indirectly affect type 2 diabetes mellitus. Insufficient physical activity (PA) has been identified as the fourth leading risk factor for global mortality. Consequently, effective interventions that promote PA and FV intake in a large number of people are required. Objective To describe the systematic development of an eHealth intervention, MyPlan 1.0, for increasing FV intake and PA. Methods The intervention was developed following the six steps of the intervention mapping (IM) protocol. Decisions during steps were based upon available literature, focus group interviews, and pilot studies. Results Based on needs assessment (Step 1), it was decided to focus on fruit and vegetable intake and physical activity levels of adults. Based on self-regulation and the health action process approach model, motivational (eg, risk awareness) and volitional (eg, action planning) determinants were selected and crossed with performance objectives into a matrix with change objectives (Step 2). Behavioral change strategies (eg, goal setting, problem solving, and implementation intentions) were selected (Step 3). Tablet computers were chosen for delivery of the eHealth program in general practice (Step 4). To facilitate implementation of the intervention in general practice, GPs were involved in focus group interviews (Step 5). Finally, the planning of the evaluation of the intervention (Step 6) is briefly described. Conclusions Using the IM protocol ensures that a theory- and evidence-based intervention protocol is developed. If the intervention is found to be effective, a dynamic eHealth program for the promotion of healthy lifestyles could be available for use in general practice.

What do general practitioners think about an online self-regulation programme for health promotion? Focus group interviews

BackgroundChronic diseases may be prevented through programmes that promote physical activity and healthy nutrition. Computer-tailoring programmes are effective in changing behaviour in the short- and long-term. An important issue is the implementation of these programmes in general practice. However, there are several barriers that hinder the adoption of eHealth programmes in general practice. This study explored the feasibility of an eHealth programme that was designed, using self-regulation principles.MethodsSeven focus group interviews (a total of 62 GPs) were organized to explore GPs’ opinions about the feasibility of the eHealth programme for prevention in general practice. At the beginning of each focus group, GPs were informed about the principles of the self-regulation programme ‘My Plan’. Open-ended questions were used to assess the opinion of GPs about the content and the use of the programme. The focus groups discussions were audio-taped, transcribed and thematically analysed via NVivo software.ResultsThe majority of the GPs was positive about the use of self-regulation strategies and about the use of computer-tailored programmes in general practice. There were contradictory results about the delivery mode of the programme. GPs also indicated that the programme might be less suited for patients with a low educational level or for old patients.ConclusionsOverall, GPs are positive about the adoption of self-regulation techniques for health promotion in their practice. However, they raised doubts about the adoption in general practice. This barrier may be addressed (1) by offering various ways to deliver the programme, and (2) by allowing flexibility to match different work flow systems. GPs also believed that the acceptability and usability of the programme was low for patients who are old or with low education. The issues raised by GPs will need to be taken into account when developing and implementing an eHealth programme in general practice.

The Reliability and Validity of Short Online Questionnaires to Measure Fruit and Vegetable Intake in Adults: The Fruit Test and Vegetable Test

The first aim of this study was to investigate the stability of the Fruit Test and Vegetable Test over time and whether the Fruit Test and Vegetable Test are capable of measuring fruit and vegetable intake with consistency. Second, the study aimed to examine criterion (concurrent) validity of the Fruit Test and Vegetable Test by testing their agreement with 7-day food diary-derived measures of fruit and vegetable intake. In total 58 adults (31% male, mean age = 30.0±12.09y) completed the Flemish Fruit and Vegetable test by indicating the frequency of days that they ate fruit and vegetables and the number of portions during the past week. Validity was tested by using a 7-day food diary as a golden standard. Adults were asked to register their fruit and vegetable intake daily in a diary during one week. Spearman correlations were measured to compare total intake reported in the Fruit and Vegetable Test and in the 7-day diary. Agreement plots were used to illustrate absolute agreement. Test-retest reliability was evaluated by having participants completing the Fruit Test and Vegetable Test twice. The Fruit Test (ICC = 0.81) and Vegetable Test (ICC = 0.78) showed excellent and substantial reliability. The Fruit Test (ρ = 0.73) and Vegetable Test showed good validity. Agreement plots showed modest variability in differences between vegetable and fruit intake as measured by the Vegetable and Fruit Test and the 7-day food diary. Also a small underestimation of fruit intake in the Fruit test and vegetable intake in the Vegetable test against the 7-day food diary was shown. Based on the results, it is suggested to include portion size pictures and consumption of mixed vegetables to prevent underestimation. To prevent overestimation, it is concluded to add a moderate number of representative fruit and vegetable items, questions on portion size, household sizes with sufficient detail and food items highly tailored to the dietary behaviors and local food items of the population surveyed. The questionnaires can easily be adapted for the use in other diets (e.g. Asian diet), but reliability and validity should then be examined again. Also, validity remains to be tested in other population groups (i.e. low socio economic status groups, other age groups).

Effect of the Web-Based Intervention MyPlan 1.0 on Self-Reported Fruit and Vegetable Intake in Adults Who Visit General Practice: A Quasi-Experimental Trial.

Background Web-based interventions typically have small intervention effects on adults’ health behavior because they primarily target processes leading to an intention to change leaving individuals in an intention-behavior gap, they often occur without contact with health care providers, and a limited amount of feedback is provided only at the beginning of these interventions, but not further on in the behavior change process. Therefore, we developed a Web-based intervention (“MyPlan 1.0”) to promote healthy behavior in adults. The intervention was based on a self-regulation perspective that also targets postintentional processes and guides individuals during all phases of behavior change. Objective The study investigated the effectiveness of MyPlan1.0 on fruit and vegetable intake of Flemish adults visiting general practice (3 groups: control group, intervention group recruited by researchers, and intervention group recruited and guided by general practitioners [GPs]). Second, it examined whether there was a larger intervention effect for the intervention group guided by GPs compared to the intervention group recruited by researchers. Methods Adults (≥18 years) were recruited in 19 Flemish general practices. In each general practice, patients were systematically allocated by a researcher either for the intervention group (researchers’ intervention group) or the waiting-list control group that received general advice. In a third group, the GP recruited adults for the intervention (GPs intervention group). The two intervention groups filled in evaluation questionnaires and received MyPlan 1.0 for a behavior of choice (fruit, vegetable, or physical activity). The waiting-list control group filled in the evaluation questionnaires and received only general information. Self-reported fruit and vegetable intake were assessed at baseline (T0), 1 week (T1), and 1 month (T2) postbaseline. Three-level (general practice, adults, time) linear regression models were conducted in MLwiN. Results A total of 426 adults initially agreed to participate (control group: n=149; GPs’ intervention group: n=41; researchers’ intervention group: n=236). A high attrition rate was observed in both intervention groups (71.8%, 199/277) and in the control group (59.1%, 88/149). In comparison to no change in the control group, both the GPs’ intervention group (fruit: χ2 1=10.9, P=.004; vegetable: χ2 1=5.3, P=.02) and the researchers’ intervention group (fruit: χ2 1=18.0, P=.001; vegetable: χ2 1=12.8, P<.001) increased their intake of fruit and vegetables. Conclusions A greater increase in fruit and vegetable intake was found when the Web-based intervention MyPlan 1.0 was used compared to usual care of health promotion in general practice (ie, flyers with general information). However, further investigation on which (or combinations of which) behavior change techniques are effective, how to increase response rates, and the influence of delivery mode in routine practice is required. Trial Registration ClinicalTrials.gov NCT02211040; https://clinicaltrials.gov/ct2/show/NCT02211040 (Archived by WebCite® at http://www.webcitation.org/6f8yxTRii)

The use and evaluation of self-regulation techniques can predict health goal attainment in adults: an explorative study

Background. Self-regulation tools are not always used optimally, and implementation intention plans often lack quality. Therefore, this study explored participants’ use and evaluation of self-regulation techniques and their impact on goal attainment. Methods. Data were obtained from 452 adults in a proof of concept (POC) intervention of ‘MyPlan’, an eHealth intervention using self-regulation techniques to promote three healthy behaviours (physical activity (PA), fruit intake, or vegetable intake). Participants applied self-regulation techniques to a self-selected health behaviour, and evaluated the self-regulation techniques. The quality of implementation intentions was rated by the authors as a function of instrumentality (instrumental and non-instrumental) and specificity (non-specific and medium to highly specific). Logistic regression analyses were conducted to predict goal attainment. Results. Goal attainment was significantly predicted by the motivational value of the personal advice (OR:1.86), by the specificity of the implementation intentions (OR:3.5), by the motivational value of the action plan (OR:1.86), and by making a new action plan at follow-up (OR:4.10). Interaction-effects with behaviour showed that the specificity score of the implementation intention plans (OR:4.59), the motivational value of the personal advice (OR:2.38), selecting hindering factors and solutions(OR:2.00) and making a new action plan at follow-up (OR:7.54) were predictive of goal attainment only for fruit or vegetable intake. Also, when participants in the fruit and vegetable group made more than three plans, they were more likely to attain their goal (OR:1.73), whereas the reverse was the case in the PA group (OR:0.34). Discussion. The chance that adults reach fruit and vegetable goals can be increased by including motivating personal advice, self-formulated action plans, and instructions/strategies to make specific implementation intentions into eHealth interventions. To increase the chance that adults reach short-term PA goals, it is suggested to keep eHealth PA interventions simple and focus only on developing a few implementation intentions. However, more research is needed to identify behaviour change techniques that can increase health goal attainment at long-term.

The Effect of the eHealth Intervention ‘MyPlan 1.0’ on Physical Activity in Adults Who Visit General Practice: A Quasi-Experimental Trial

Physical inactivity is one of the major risk factors for poor health in the world. Therefore, effective interventions that promote physical activity are needed. Hence, we developed an eHealth intervention for adults, i.e., ‘MyPlan 1.0’, which includes self-regulation techniques for behaviour change. This study examined the effect of ‘MyPlan 1.0’ on physical activity (PA) levels in general practice. 615 adults (≥18 years) were recruited in 19 Flemish general practices, for the intervention group (n = 328) or for the wait-list control group (n = 183). Participants in the intervention group received the web-based intervention ‘MyPlan 1.0’ and were prompted to discuss their personal advice/action plan with their general practitioner. Participants in the wait-list control group only received general advice from the website. Self-reported physical activity was assessed with the International Physical Activity Questionnaire (IPAQ) at baseline and after one month. A three-level (general practice, adults, time) regression analysis was conducted in MLwiN. Significant intervention effects were found for total PA and moderate to vigorous PA with an increase for the intervention group compared to a decrease in the control condition. However, there was a high dropout rate in the intervention group (76%) and the wait-list control group (57%). Our self-regulation intervention was effective in increasing physical activity levels in adults. Future studies should consider strategies to prevent the large dropout from participants.

Process Evaluation of an eHealth Intervention Implemented into General Practice: General Practitioners’ and Patients’ Views

(1) Background: It has been shown that online interventions can be enhanced by providing additional support; accordingly, we developed an implementation plan for the use of an eHealth intervention targeting physical activity and healthy nutrition in collaboration with general practitioners (GPs). In this study, GPs and patients evaluated the actual implementation; (2) Methods: Two hundred and thirty two patients completed the feasibility questionnaire regarding the implementation of “MyPlan 1.0” in general practice. Individual interviews were conducted with 15 GPs who implemented “MyPlan 1.0” into their daily work flow; (3) Results: The majority of the patients indicated that general practice was an appropriate setting to implement the online intervention. However, patients were not personally addressed by GPs and advice/action plans were not discussed with the GPs. The GPs indicated that this problem was caused by the severe time restrictions in general practice. GPs also seemed to select those patients who they believed to be able to use (e.g., highly educated patients) and to benefit from the intervention (e.g., patients with overweight); (4) Conclusions: Although GPs were involved in the development of the online intervention and its implementation plan, the programme was not used in general practice as intended.

The insights of health and welfare professionals on hurdles that impede economic evaluations of welfare interventions

ABSTRACT Background: Four hurdles associated with economic evaluations in welfare interventions were identified and discussed in a previous published literature review. These hurdles include (i) ‘Ignoring the impact of condition-specific outcomes’, (ii) ‘Ignoring the impact of QoL externalities’, (iii) ‘Calculation of costs from a too narrow perspective’ and (iv) ‘The lack of well-described & standardized interventions’. This study aims to determine how healthcare providers and social workers experience and deal with these hurdles in practice and what solutions or new insights they would suggest. Methods: Twenty-two professionals of welfare interventions carried out in Flanders, were interviewed about the four described hurdles using a semi-structured interview. A thematic framework was developed to enable the qualitative analysis. The analysis of the semi-structured interviews was facilitated through the use of the software program QRS NVivo 10. Results: The interviews revealed a clear need to tackle these hurdles. The interviewees confirmed that further study of condition-specific outcomes in economic evaluations are needed, especially in the field of mental health and stress. The proposed dimensions for the condition-specific questionnaires varied however between the groups of interviewees (i.e. general practitioners vs social workers). With respect to QoL externalities, the interviewees confirmed that welfare interventions have an impact on the social environment of the patient (friends and family). There was however no consensus on how this impact of QoL externalities should be taken into account in welfare interventions. Professionals also suggested that besides health care costs, the impact of welfare interventions on work productivity, the patients’ social life and other items should be incorporated. Standardization appears to be of limited added value for most of the interviewees because they need a certain degree of freedom to interpret the intervention. Furthermore, the target population of the interventions is diverse which requires a tailor-made approach. Conclusion: This qualitative research demonstrated that these hurdles occur in practice. The proposed solutions for these hurdles can contribute to the improvement of the methodological quality of economic evaluations of welfare interventions.

Hurdles That Impede Economic Evaluations of Health Care Interventions Tested By General Practitioners In Flanders: A Qualitative Study

PHP152 Hurdles THaT ImPede economIc evaluaTIons of HealTH care InTervenTIons TesTed By General PracTITIoners In flanders: a QualITaTIve sTudy Schepers J1, Plaete J2, De Bourdeaudhuij I2, Lieven A2, Simoens S1 1KU Leuven, Leuven, Belgium, 2UGent, Gent, Belgium objeCtives: Four hurdles associated with economic evaluations in health care interventions were identified and examined in a previous published literature review. These hurdles include (i) ‘Ignoring the impact of condition-specific outcomes’, (ii) ‘Ignoring the impact of QoL externalities’, (iii) ‘Calculation of costs from a too narrow perspective’ and (iv) ‘The lack of well-described & standardized interventions’. This study aims to determine how healthcare providers experience and deal with these hurdles in practice and what solutions or new insights they would suggest. Methods: Fourteen general practitioners (GPs), who were participating in a health care intervention in Flanders, were interviewed about the four described hurdles in a semi-structured way. A thematic framework was developed to enable the qualitative analysis. Results: The interviews revealed a clear need to tackle these hurdles. GPs confirmed that more condition-specific outcomes in economic evaluations are needed, especially in the field of mental health and stress. The proposed dimensions for the condition-specific questionnaires varied however between the GPs. With respect to QoL externalities, GPs confirmed that health care interventions have an impact on the environment of the patient (friends and family). There was however no consensus on how this impact of QoL externalities should be taken into account. Besides health care costs, the impact of health care interventions on work productivity, the patients’ social life (culture, sport) and other items such as traffic accidents must be incorporated to provide an overall picture. Standardization appears to be of limited added value for most of the interviewed GPs because they need a certain degree of freedom to interpret the intervention. Lack of time has been claimed by GPs as the biggest issue for standardization of health care interventions. ConClusions: This qualitative research demonstrated that these hurdles occur in practice and contributes to improve the methodological quality of economic evaluations of health care interventions.