The effect on participation rates of including focused spirometry information in a health check invitation: a cluster-randomised trial in Denmark.

BACKGROUND: Early detection of lung disease may help reduce disease development. Detection through preventive health checks may be beneficial. Nevertheless, the knowledge is sparse on how to enhance the participation rate in health checks among citizens at risk of developing lung disease. This study investigates if focused information on spirometry can increase the participation rate in a general health check. METHODS: We conducted an open-label, household cluster-randomised trial with a two-group parallel design including 4407 citizens aged 30-49 years in Denmark and an average cluster size of 1.55 citizens per household. The control group (n = 2213) received a standard invitation describing the content of the general health check and containing practical information. The intervention group (n = 2194) received an extended invitation highlighting the benefits of early detection and prevention of lung disease. The primary outcome was difference in participation rate between the two groups. The secondary outcome was the proportion of participants at risk of lung disease in both groups. Risk profile was defined as current smoking or self-reported lung symptoms. The inclusion period was 25 November 2015-3 February 2017. RESULTS: No major difference in participation rate was seen between the intervention group (53.4%) and the control group (52.0%). Participants had statistically significantly higher education level compared to non-participants. A total of 24.2% of the participants were at risk of developing lung disease, but no difference was found between the intervention group and the control group. CONCLUSION: This study revealed no effect on participation rate of including focused spirometry information in the health check invitation. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02615769 . Registered on 25 November 2015. The trial protocol has been published.

Oral health and type 2 diabetes in a socioeconomic perspective.

AIMS: This study aimed to examine the association between type 2 diabetes and poor self-rated oral health, and to investigate whether such association is modified by socioeconomic position. METHODS: We conducted a cross-sectional study, including a population aged 18-75 years with self-reported type 2 diabetes (N = 41,884) and a sex-, age- and municipality-matched reference population from the Health in Central Denmark survey (2020). Multivariable logistic regression was used, and effect modification of indicators of socioeconomic position was examined. RESULTS: Oral health was rated as poor in 37.0% of the population with type 2 diabetes and in 23.8% of the reference population without diabetes. Individuals with diabetes had higher risk of poor oral health (adjusted odds ratio (OR) 1.46 (95% CI: 1.39; 1.53)) than references. Interaction was seen between type 2 diabetes and highest attained education (p < 0.001). Stratified analyses showed higher risk of poor oral health in people with type 2 diabetes across all educational levels. CONCLUSIONS: People with type 2 diabetes were more likely to rate their oral health as poor than the reference population. Low education strengthened the association between diabetes and poor oral health.

ChatGPT- versus human-generated answers to frequently asked questions about diabetes: A Turing test-inspired survey among employees of a Danish diabetes center.

Large language models have received enormous attention recently with some studies demonstrating their potential clinical value, despite not being trained specifically for this domain. We aimed to investigate whether ChatGPT, a language model optimized for dialogue, can answer frequently asked questions about diabetes. We conducted a closed e-survey among employees of a large Danish diabetes center. The study design was inspired by the Turing test and non-inferiority trials. Our survey included ten questions with two answers each. One of these was written by a human expert, while the other was generated by ChatGPT. Participants had the task to identify the ChatGPT-generated answer. Data was analyzed at the question-level using logistic regression with robust variance estimation with clustering at participant level. In secondary analyses, we investigated the effect of participant characteristics on the outcome. A 55% non-inferiority margin was pre-defined based on precision simulations and had been published as part of the study protocol before data collection began. Among 311 invited individuals, 183 participated in the survey (59% response rate). 64% had heard of ChatGPT before, and 19% had tried it. Overall, participants could identify ChatGPT-generated answers 59.5% (95% CI: 57.0, 62.0) of the time, which was outside of the non-inferiority zone. Among participant characteristics, previous ChatGPT use had the strongest association with the outcome (odds ratio: 1.52 (1.16, 2.00), p = 0.003). Previous users answered 67.4% (61.7, 72.7) of the questions correctly, versus non-users' 57.6% (54.9, 60.3). Participants could distinguish between ChatGPT-generated and human-written answers somewhat better than flipping a fair coin, which was against our initial hypothesis. Rigorously planned studies are needed to elucidate the risks and benefits of integrating such technologies in routine clinical practice.

Cohort profile: Health in Central Denmark (HICD) cohort - a register-based questionnaire survey on diabetes and related complications in the Central Denmark Region.

PURPOSE: The Health in Central Denmark (HICD) cohort is a newly established cohort built on extensive questionnaire data linked with laboratory data and Danish national health and administrative registries. The aim is to establish an extensive resource for (1) gaining knowledge on patient-related topics and experiences that are not measured objectively at clinical health examinations and (2) long-term follow-up studies of inequality in diabetes and diabetes-related complications. PARTICIPANTS: A total of 1.3 million inhabitants reside in the Central Denmark Region. Using register data and a prespecified diabetes classification algorithm, we identified 45 507 persons aged 18-75 years with prevalent diabetes on 31 December 2018 and a group without diabetes of equal size matched by sex, age and municipality. A 90-item questionnaire was distributed to eligible members of this cohort on 18 November 2020 (estimated time required for completion: 15-20 min). FINDINGS TO DATE: We invited 90 854 persons to take part in the survey, of whom 51 854 answered the questionnaire (57.1%). Among these respondents, 2,832 persons had type 1 diabetes (55.9%), 21,140 persons had type 2 diabetes (53.2%), while 27,892 persons were part of the matched group without diabetes (60.4%). In addition to questionnaire data, the cohort is linked to nationwide registries that provide extensive data on hospital diagnoses and procedures, medication use and socioeconomic status decades before enrolment while laboratory registries has provided repeated measures of biochemical markers, for example, lipids, albuminuria and glycated haemoglobin up to 10 years before enrolment. FUTURE PLANS: The HICD will serve as an extensive resource for studies on patient-related information and inequality in type 1 diabetes and type 2 diabetes. Follow-up is planned to continue for at least 10 years and detailed follow-up questionnaires, including new topics, are planned to be distributed during this period, while registry data are planned to be updated every second year.

Effectiveness of the population-based 'check your health preventive programme' conducted in a primary care setting: a pragmatic randomised controlled trial.

BACKGROUND: Health checks have been suggested as an early detection approach aiming at lowering the risk of chronic disease development. This study aimed to evaluate the effectiveness of a health check programme offered to the general population, aged 30-49 years. METHODS: The entire population aged 30-49 years (N=26 216) living in the municipality of Randers, Denmark, was invited to a health check during 5 years. A pragmatic household cluster-randomised controlled trial was conducted in 10 505 citizens. The intervention group (IG, N=5250) included citizens randomised to the second year and reinvited in the 5th year. The comparison group (CG, N=5255) included citizens randomised to the 5th year. Outcomes were modelled cardiovascular disease (CVD) risk; self-reported physical activity (PA) and objectively measured cardio respiratory fitness (CRF); self-rated health (short-form 12 (SF-12)), self-rated mental health (SF-12_Mental Component Score (MCS)) and, registry information on sick-leave and employment. Due to low participation, we compared groups matched on propensity scores for participation when reinvited. RESULTS: Participation in the first health check was 51% (N=2698) in the IG and 40% (N=2120) in the CG. In the IG 26% (N=1340) participated in both the first and second health checks. No intervention effects were found comparing IG and CG. Mean differences were (95% CI): modelled CVD risk: -0.052 (95% CI -0.107 to 0.003)%, PA: -0.156 (-0.331 to 0.019) days/week with 30 min moderate PA, CRF: 0.133 (-0.560 to 0.826) mL O2/min/kg, SF-12: -0.003 (-0.032 to 0.026), SF-12_MCS: 0.355 (-0.423 to 1.132), sick leave periods ≥3 weeks: -0.004 (-0.025 to 0.017), employment: -0.004 (-0.032 to 0.024). CONCLUSIONS: Preventive health checks offered to the general population, aged 30-49 years, had no effects on a wide range of indicators of chronic disease risk. TRIAL REGISTRATION NUMBER: NCT02028195.