Overweight and obese adults have low intentions of seeking weight-related care:A cross-sectional survey

Background The prevalence of obesity is growing worldwide. Obesity guidelines recommend increasing the level of weight-related care for persons with elevated levels of weight-related health risk (WRHR). However, there seems to be a discrepancy between need for and use of weight-related care. The primary aim of this study is to examine predisposing factors that may influence readiness to lose weight and intention to use weight-related care in an overweight population. Methods A population-based, cross-sectional survey was conducted. Data were collected using an online self-administered questionnaire sent to a population-representative sample of 1,500 Dutch adults on the Health Care Consumer Panel (n = 861 responded). Data were used from individuals (n = 445) with a mildly, moderately or severely elevated level of WRHR. WRHR status was based on self-reported data on Body Mass Index, risk assessment for diabetes mellitus type 2 (DM2) and cardiovascular disease (CVD), or co-morbidities. Results 55.1% of persons with increased WRHR were ready to lose weight (n = 245). Depending on level of WRHR; educational level, marital status, individuals with an accurate perception of their weight and better perceptions and expectations of dietitians were significantly related to readiness to lose weight. Most of them preferred individual weight-loss methods (82.0% of n = 245). 11% (n = 26 of n = 245) intended to use weight-related care. Weight-related care seeking was higher for those with moderate or severe WRHR. Expectations and trust in dietitians did not seem to influence care seeking. Conclusions Many Dutch adults who are medically in need of weight-related care are ready to lose weight. Most intend to lose weight individually, and only a few intend to use weight-related care. Therefore, obesity prevention initiatives should focus on monitoring weight change and weight-loss plans, and timely referral to obesity management. However, many people are not ready to lose weight. For this group, strategies for behaviour change may depend on WRHR, perceptions of weight and dietitians, educational level and marital status. Obesity prevention initiatives should focus on increasing the awareness of the seriousness of their condition and offering individually appropriate weight management programmes. Keywords: Overweight, Obesity, Weight change, Patient’s acceptance of health care, Perception, Dietary service

Lessons learned from a living lab on the broad adoption of eHealth in primary health care

Background: Electronic health (eHealth) solutions are considered to relieve current and future pressure on the sustainability of primary health care systems. However, evidence of the effectiveness of eHealth in daily practice is missing. Furthermore, eHealth solutions are often not implemented structurally after a pilot phase, even if successful during this phase. Although many studies on barriers and facilitators were published in recent years, eHealth implementation still progresses only slowly. To further unravel the slow implementation process in primary health care and accelerate the implementation of eHealth, a 3-year Living Lab project was set up. In the Living Lab, called eLabEL, patients, health care professionals, small- and medium-sized enterprises (SMEs), and research institutes collaborated to select and integrate fully mature eHealth technologies for implementation in primary health care. Seven primary health care centers, 10 SMEs, and 4 research institutes participated. Objective: This viewpoint paper aims to show the process of adoption of eHealth in primary care from the perspective of different stakeholders in a qualitative way. We provide a real-world view on how such a process occurs, including successes and failures related to the different perspectives. Methods: Reflective and process-based notes from all meetings of the project partners, interview data, and data of focus groups were analyzed systematically using four theoretical models to study the adoption of eHealth in primary care. Results: The results showed that large-scale implementation of eHealth depends on the efforts of and interaction and collaboration among 4 groups of stakeholders: patients, health care professionals, SMEs, and those responsible for health care policy (health care insurers and policy makers). These stakeholders are all acting within their own contexts and with their own values and expectations. We experienced that patients reported expected benefits regarding the use of eHealth for self-management purposes, and health care professionals stressed the potential benefits of eHealth and were interested in using eHealth to distinguish themselves from other care organizations. In addition, eHealth entrepreneurs valued the collaboration among SMEs as they were not big enough to enter the health care market on their own and valued the collaboration with research institutes. Furthermore, health care insurers and policy makers shared the ambition and need for the development and implementation of an integrated eHealth infrastructure. Conclusions: For optimal and sustainable use of eHealth, patients should be actively involved, primary health care professionals need to be reinforced in their management, entrepreneurs should work closely with health care professionals and patients, and the government needs to focus on new health care models stimulating innovations. Only when all these parties act together, starting in local communities with a small range of eHealth tools, the potential of eHealth will be enforced

Expectations and needs of patients with a chronic disease toward self-management and eHealth for self-management purposes

Background: Self-management is considered as an essential component of chronic care by primary care professionals. eHealth is expected to play an important role in supporting patients in their self-management. For effective implementation of eHealth it is important to investigate patients’ expectations and needs regarding self-management and eHealth. The objectives of this study are to investigate expectations and needs of people with a chronic condition regarding self-management and eHealth for self-management purposes, their willingness to use eHealth, and possible differences between patient groups regarding these topics. Methods: Five focus groups with people with diabetes (n = 14), COPD (n = 9), and a cardiovascular condition (n = 7) were conducted in this qualitative research. Separate focus groups were organized based on patients’ chronic condition. The following themes were discussed: 1) the impact of the chronic disease on patients’ daily life; 2) their opinions and needs regarding self-management; and 3) their expectations and needs regarding, and willingness to use, eHealth for self-management purposes. A conventional content analysis approach was used for coding. Results: Patient groups seem to differ in expectations and needs regarding self-management and eHealth for self-management purposes. People with diabetes reported most needs and benefits regarding self-management and were most willing to use eHealth, followed by the COPD group. People with a cardiovascular condition mentioned having fewer needs for self-management support, because their disease had little impact on their life. In all patient groups it was reported that the patient, not the care professional, should choose whether or not to use eHealth. Moreover, participants reported that eHealth should not replace, but complement personal care. Many participants reported expecting feelings of anxiety by doing measurement themselves and uncertainty about follow-up of deviant data of measurements. In addition, many participants worried about the implementation of eHealth being a consequence of budget cuts in care. Conclusion: This study suggests that aspects of eHealth, and the way in which it should be implemented, should be tailored to the patient. Patients’ expected benefits of using eHealth to support self-management and their perceived controllability over their disease seem to play an important role in patients’ willingness to use eHealth for self-management purposes

Exploring physiotherapists' personality traits that may influence treatment outcome in patients with chronic diseases : a cohort study

BACKGROUND: During treatment of patients with Chronic Diseases (CD) the therapist-patient interaction is often intense, and the strategies used during treatment require physiotherapists to assume a coaching role. Uncovering therapist factors that explain inter-therapist variation might provide tools to improve treatment outcome and to train future therapists. The purpose of this study was to explore the so-called 'therapist-effect', by looking at the influence of intrinsic therapist factors, specifically personality traits, on treatment outcome in patients with CD. METHODS: A cohort study was performed using data from the NIVEL Primary Care Database (NPCD) in 2011-2012 and an additional questionnaire. Patients with CD (n = 393) treated by Dutch physiotherapists working in outpatient practices (n = 39) were included. Patient and treatment outcome variables were extracted from NPCD. The course of complaint was measured using the Numeric Rating Scale. Therapist variables were measured using a questionnaire consisting of demographics and the Big Five traits: Extraversion, Neuroticism, Agreeableness, Conscientiousness and Openness to experiences. Data were analysed using multilevel linear regression. RESULTS: Only Neuroticism was found to be significant (Neuroticism F = 0.71, P = 0.01; therapist gender F = 0.72, P = 0.03; life events F = -0.54, P = 0.09; patient gender F = -0.43, P = 0.10; patient age F = 0.01, P = 0.27). Subgroup analyses of 180 patients with Osteoarthritis and 30 therapists showed similar results. CONCLUSIONS: There are indications that patients with CD who are treated by therapists who tend to be calmer, more relaxed, secure and resilient have a greater reduction in severity of complaints compared to patients treated by therapists who show less of these traits. Being a male therapist and having experienced life events influence outcome positively. However, more extensive research is needed to validate the current findings

Factors associated with the number of consultations per dietetic treatment: an observational study

Abstract Background Greater understanding of the variance in the number of consultations per dietetic treatment will increase the transparency of dietetic healthcare. Substantial inter-practitioner variation may suggest a potential to increase efficiency and improve quality. It is not known whether inter-practitioner variation also exists in the field of dietetics. Therefore, the aims of this study are to examine inter-practitioner variation in the number of consultations per treatment and the case-mix factors that explain this variation. Methods For this observational study, data were used from the National Information Service for Allied Health Care (LiPZ). LiPZ is a Dutch registration network of allied health care professionals, including dietitians working in primary healthcare. Data were used from 6,496 patients who underwent dietetic treatment between 2006 and 2009, treated by 27 dietitians working in solo practices located throughout the Netherlands. Data collection was based on the long-term computerized registration of healthcare-related information on patients, reimbursement, treatment and health problems, using a regular software program for reimbursement. Poisson multilevel regression analyses were used to model the number of consultations and to account for the clustered structure of the data. Results After adjusting for case-mix, seven percent of the total variation in consultation sessions was due to dietitians. The mean number of consultations per treatment was 4.9 and ranged from 2.3–10.1 between dietitians. Demographic characteristics, patients’ initiative and patients’ health problems explained 28% of the inter-practitioner variation. Certain groups of patients used significantly more dietetic healthcare compared to others, i.e. older patients, females, the native Dutch, patients with a history of dietetic healthcare, patients who started the treatment on their own initiative, patients with multiple diagnoses, overweight, or binge eating disorder. Conclusions Considerable variation in number of consultations per dietetic treatment is due to dietitians. Some of this inter-practitioner variation was reduced after adjusting for case-mix. Further research is necessary to study the relation between inter-practitioner variation and the effectiveness and quality of dietetic treatment.</p