Objectives: The observational ‘Feeling Hot’ study aims to evaluate the feasibility of employing overnight penile temperature measurements for the detection of nocturnal erections, thereby... Show moreObjectives: The observational ‘Feeling Hot’ study aims to evaluate the feasibility of employing overnight penile temperature measurements for the detection of nocturnal erections, thereby contributing to the advancement and modernization of a non-invasive diagnostic system for erectile dysfunction. Subjects/Patients and Methods: In this proof-of-concept study, 10 healthy men aged 20–25 were recruited, following the methodology outlined in the ‘Staying Hot’ study by Torenvlied et al. Participants underwent ambulatory overnight penile temperature measurements concurrent with RigiScan recordings. Key outcome measures included baseline and peak penile temperatures during RigiScan-annotated nocturnal erections. Reference measurements of the thigh temperature were also taken to assess nocturnal temperature variations. Results: Statistically significant penile temperature increases (p = 0.008, n = 9) were observed during nocturnal erections, with an average elevation of 1.47C noted during the initial erections. This underscores the practical utility of penile temperature measurements in detecting erection onset. Challenges arose in accurately determining erection duration and subsequent erection onsets due to the persistence of elevated temperatures following initial erections, termed the ‘Staying Hot effect’. Reference thigh temperature measurements aided in addressing this challenge. Conclusion: Examining overnight penile temperature alongside simultaneous RigiScan recordings has yielded valuable insights into the viability of using the temperature methodology for detecting nocturnal erections. The ‘Feeling Hot’ study findings demonstrate significant penile temperature elevation during nocturnal erections in healthy young men, highlighting the potential of integrating this measurement methodology into the design of a modernized tool for ambulatory erectile dysfunction diagnostics. Further development of an advanced sensor system to comprehensively assess erection duration and quality is essential for enhancing clinical applicability. Show less
Aims/hypothesis There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM)... Show moreAims/hypothesis There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM) that integrates medical, psychological and behavioural aspects and connected wearables to support patients and healthcare professionals in shared decision making and diabetes self-management.Methods Participants with type 1 or type 2 diabetes (aged >18 years) from hospital outpatient diabetes clinics in the Netherlands and Spain were randomised using randomisation software to POWER2DM or usual care for 37 weeks. This RCT assessed the change in HbA(1c) between the POWER2DM and usual care groups at the end of the study (37 weeks) as a primary outcome measure. Participants and clinicians were not blinded to the intervention. Changes in quality of life (QoL) (WHO-5 Well-Being Index [WHO-5]), diabetes self-management (Diabetes Self-Management Questionnaire - Revised [DSMQ-R]), glycaemic profiles from continuous glucose monitoring devices, awareness of hypoglycaemia (Clarke hypoglycaemia unawareness instrument), incidence of hypoglycaemic episodes and technology acceptance were secondary outcome measures. Additionally, sub-analyses were performed for participants with type 1 and type 2 diabetes separately.Results A total of 226 participants participated in the trial (108 with type 1 diabetes; 118 with type 2 diabetes). In the POWER2DM group (n=111), HbA(1c) decreased from 60.6 +/- 14.7 mmol/mol (7.7 +/- 1.3%) to 56.7 +/- 12.1 mmol/mol (7.3 +/- 1.1%) (means +/- SD, p<0.001), compared with no change in the usual care group (n=115) (baseline: 61.7 +/- 13.7 mmol/mol, 7.8 +/- 1.3%; end of study: 61.0 +/- 12.4 mmol/mol, 7.7 +/- 1.1%; p=0.19) (between-group difference 0.24%, p=0.008). In the sub-analyses in the POWER2DM group, HbA(1c) in participants with type 2 diabetes decreased from 62.3 +/- 17.3 mmol/mol (7.9 +/- 1.6%) to 54.3 +/- 11.1 mmol/mol (7.1 +/- 1.0%) (p<0.001) compared with no change in HbA(1c) in participants with type 1 diabetes (baseline: 58.8 +/- 11.2 mmol/mol [7.5 +/- 1.0%]; end of study: 59.2 +/- 12.7 mmol/mol [7.6 +/- 1.2%]; p=0.84). There was an increase in the time during which interstitial glucose levels were between 3.0 and 3.9 mmol/l in the POWER2DM group, but no increase in clinically relevant hypoglycaemia (interstitial glucose level below 3.0 mmol/l). QoL improved in participants with type 1 diabetes in the POWER2DM group compared with the usual care group (baseline: 15.7 +/- 3.8; end of study: 16.3 +/- 3.5; p=0.047 for between-group difference). Diabetes self-management improved in both participants with type 1 diabetes (from 7.3 +/- 1.2 to 7.7 +/- 1.2; p=0.002) and those with type 2 diabetes (from 6.5 +/- 1.3 to 6.7 +/- 1.3; p=0.003) within the POWER2DM group. The POWER2DM integrated e-health support was well accepted in daily life and no important adverse (or unexpected) effects or side effects were observed.Conclusions/interpretation POWER2DM improves HbA(1c) levels compared with usual care in those with type 2 diabetes, improves QoL in those with type 1 diabetes, improves diabetes self-management in those with type 1 and type 2 diabetes, and is well accepted in daily life.Trial registration ClinicalTrials.gov NCT03588104.Funding This study was funded by the European Union's Horizon 2020 Research and Innovation Programme (grant agreement number 689444). Show less
Hybrid e-health support was given to 11 insulin-dependent type 2 diabetes mellitus (DM2) patients, with electronic support plus a multi-disciplinary health support team. Challenges were low ICT and... Show moreHybrid e-health support was given to 11 insulin-dependent type 2 diabetes mellitus (DM2) patients, with electronic support plus a multi-disciplinary health support team. Challenges were low ICT and health literacy. After 50 weeks, attractiveness and feasibility of the intervention were perceived as high: recommendation 9.5 out of 10 and satisfaction 9.6 out of 10. Technology acceptance model (TAM) surveys showed high usefulness and feasibility. Acceptance and health behaviours were reinforced by the prolonged health results: aerobic and strength capacity levels were improved at 50 weeks, plus health related quality of life (plus biometric benefits and medication reductions, reported elsewhere). Regarding e-health theory, we conclude that iterative skill growth cycles are beneficial for long-term adoption and e-relationships. Next, the design analysis shows opportunities for additional affective and social support, on top of the strong benefits already apparent from the direct progress feedback loops used within the health coach processes. Show less
Scheper, H.; Derogee, R.; Mandad, R.; Wal, R.J.P. van der; Nelissen, R.G.H.H.; Visser, L.G.; Boer, M.G.J. de 2019
