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L.P.A. Simons
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19 records found
1
Dementia is one of the most pressing health problems in the world. Still, the good news is that it is much better preventable than (advanced-stage) treatable. Over the years, a new narrative has come up: heart health = brain health. But its translation into healthcare interventions has been slow. In this design approach, we propose two empowerment options for patients, caregivers, and their health professionals. Firstly, we describe how cardiac health successes in enticing senior citizens to large lifestyle improvements may be used for treating early-stage dementia and cognitive decline. Biologically, this uses causality between blood pressure and cardiovascular health on the one hand and dementia outcomes on the other. Practically, it enables daily success feedback, which empowers patients in their health improvement experiments. Secondly, we describe and user-test an AI Health Research Assistant to extract the best available lifestyle findings from literature, to keep up with over 100,000 new health publications flooding us every year. Our user test highlights challenges and opportunities for a Health AI, especially regarding claim transparency, data quality, and risks of hallucinations. We suggest research metadata criteria to evaluate ambiguous or conflicting health science claims.
...
Dementia is one of the most pressing health problems in the world. Still, the good news is that it is much better preventable than (advanced-stage) treatable. Over the years, a new narrative has come up: heart health = brain health. But its translation into healthcare interventions has been slow. In this design approach, we propose two empowerment options for patients, caregivers, and their health professionals. Firstly, we describe how cardiac health successes in enticing senior citizens to large lifestyle improvements may be used for treating early-stage dementia and cognitive decline. Biologically, this uses causality between blood pressure and cardiovascular health on the one hand and dementia outcomes on the other. Practically, it enables daily success feedback, which empowers patients in their health improvement experiments. Secondly, we describe and user-test an AI Health Research Assistant to extract the best available lifestyle findings from literature, to keep up with over 100,000 new health publications flooding us every year. Our user test highlights challenges and opportunities for a Health AI, especially regarding claim transparency, data quality, and risks of hallucinations. We suggest research metadata criteria to evaluate ambiguous or conflicting health science claims.
Healthy lifestyle behaviours are effective in preventing and treating cardiovascular disease. However, the growing body of scientific literature and the prevalence of conflicting studies make it challenging for healthcare practitioners and patients to stay informed. Large Language Models (LLMs), combined with Retrieval-Augmented Generation (RAG), enable automated claim verification and summarization. We enhanced RAG-LLM with extra modules and evaluated performance. Inclusion-Criteria-based filtering of PubMed papers improved verdict performance. Next, for health claims, PICO-based (Population, Intervention, Comparison, Outcome) paper mapping and summarization improves transparency of evidence used for verdict generation (like ‘Berries reduce blood pressure’). Still, the RAG-LLM models we tested have biases towards positivity (too many foods deemed heart healthy) and neutrality (no clear direction). We discuss mechanisms at play and challenges on the route forward.
...
Healthy lifestyle behaviours are effective in preventing and treating cardiovascular disease. However, the growing body of scientific literature and the prevalence of conflicting studies make it challenging for healthcare practitioners and patients to stay informed. Large Language Models (LLMs), combined with Retrieval-Augmented Generation (RAG), enable automated claim verification and summarization. We enhanced RAG-LLM with extra modules and evaluated performance. Inclusion-Criteria-based filtering of PubMed papers improved verdict performance. Next, for health claims, PICO-based (Population, Intervention, Comparison, Outcome) paper mapping and summarization improves transparency of evidence used for verdict generation (like ‘Berries reduce blood pressure’). Still, the RAG-LLM models we tested have biases towards positivity (too many foods deemed heart healthy) and neutrality (no clear direction). We discuss mechanisms at play and challenges on the route forward.
Beyond Average Results in Hypertension E-Support and Self-Management
Three Pilot Studies With Social Learning
Hypertension is a major risk factor worldwide for early death. Well-established interventions like the Dash diet on average have modest results (5 mmHg systolic and 3 mmHg diastolic pressure improvement). We compare three employee eHealth intervention pilots with results that are three to six times larger, analysing them for eSupport design lessons. In these pilots, various tools and daily microlearning strategies have been used. Small-scale Self-Management Support (SMS) groups for hypertension control foster high degrees of learning, interaction, and personalization. Average blood pressure improvements in the pilots were 161/112 to 129/90 mmHg, resp. 145/92 to 126/86 mmHg, and 155/95 to 139/85 mmHg. User evaluation (n=20) showed the importance of core SMS components: information transfer, daily monitoring, promoting health competences and follow-up. A cross-case finding is that more daily social learning and ICT-enabled microlearning feedback increases success: for competence building and for blood pressure results.
...
Hypertension is a major risk factor worldwide for early death. Well-established interventions like the Dash diet on average have modest results (5 mmHg systolic and 3 mmHg diastolic pressure improvement). We compare three employee eHealth intervention pilots with results that are three to six times larger, analysing them for eSupport design lessons. In these pilots, various tools and daily microlearning strategies have been used. Small-scale Self-Management Support (SMS) groups for hypertension control foster high degrees of learning, interaction, and personalization. Average blood pressure improvements in the pilots were 161/112 to 129/90 mmHg, resp. 145/92 to 126/86 mmHg, and 155/95 to 139/85 mmHg. User evaluation (n=20) showed the importance of core SMS components: information transfer, daily monitoring, promoting health competences and follow-up. A cross-case finding is that more daily social learning and ICT-enabled microlearning feedback increases success: for competence building and for blood pressure results.
Designing and Evaluating an LLM-based Health AI Research Assistant for Hypertension Self-Management
Using Health Claims Metadata Criteria
Hypertension is a condition affecting most people over 45 years old. Health Self-Management offers many opportunities for prevention and cure. However, most scientific health literature is unknown by health professionals and/or patients. Per year about 200.000 new scientific papers on cardiovascular health appear, which is too much for a human to read. Hence, an LLM-based Health AI research assistant is developed for mining scientific literature on blood pressure and food. A user evaluation was conducted with n=8 participants who just completed an intensive lifestyle intervention for blood pressure self-management. They highlighted several challenges and opportunities for a Health AI, especially regarding claim transparency, data quality and risks of hallucinations. In the discussion we propose seven criteria using metadata and information characteristics to help evaluate ambiguous or conflicting health science claims.
...
Hypertension is a condition affecting most people over 45 years old. Health Self-Management offers many opportunities for prevention and cure. However, most scientific health literature is unknown by health professionals and/or patients. Per year about 200.000 new scientific papers on cardiovascular health appear, which is too much for a human to read. Hence, an LLM-based Health AI research assistant is developed for mining scientific literature on blood pressure and food. A user evaluation was conducted with n=8 participants who just completed an intensive lifestyle intervention for blood pressure self-management. They highlighted several challenges and opportunities for a Health AI, especially regarding claim transparency, data quality and risks of hallucinations. In the discussion we propose seven criteria using metadata and information characteristics to help evaluate ambiguous or conflicting health science claims.
A majority of employees over the age of 40 have hypertension, impacting their health and performance. A two-week self-management support (SMS) intervention was tested, with daily feedback and microlearning cycles to improve health self-management competences. On average, participants (n = 8) reduced their blood pressure from 145/92 mmHg to 126/86 mmHg. User evaluation confirmed the importance of core SMS aspects: information transfer, daily monitoring, enhancing problem solving/decision making, self-treatment using a tailored action plan, coping skills, and skilful coach follow-up. Several lessons are drawn on microlearning, peer coaching, health results, intrinsic motivation, and social learning, which appear useful for other health improvement initiatives.
...
A majority of employees over the age of 40 have hypertension, impacting their health and performance. A two-week self-management support (SMS) intervention was tested, with daily feedback and microlearning cycles to improve health self-management competences. On average, participants (n = 8) reduced their blood pressure from 145/92 mmHg to 126/86 mmHg. User evaluation confirmed the importance of core SMS aspects: information transfer, daily monitoring, enhancing problem solving/decision making, self-treatment using a tailored action plan, coping skills, and skilful coach follow-up. Several lessons are drawn on microlearning, peer coaching, health results, intrinsic motivation, and social learning, which appear useful for other health improvement initiatives.
Hypertension Self-Management Success in 2 weeks
3 Pilot Studies
Hypertension Self-Management is more powerful when done in groups, and with daily (e)Support for maximum impact. Small intervention groups enable high degrees of personalization, interaction, and learning. We compare three Self-Management Support (SMS) pilots of two weeks duration, in which various tools and daily microlearning strategies were used. Average blood pressure improvements in the pilots were 161/112 to 129/90 mmHg, resp. 145/92 to 126/86 mmHg, and 155/95 to 139/85 mmHg. User evaluations (n=20) were collected on perceived effectiveness of the various support components. This showed the importance of core SMS components: information transfer, daily monitoring, promoting health competences and follow-up. A tentative cross-case conclusion is that more daily social learning and microlearning feedback helps build more success: for blood pressure results and for competence building.
...
Hypertension Self-Management is more powerful when done in groups, and with daily (e)Support for maximum impact. Small intervention groups enable high degrees of personalization, interaction, and learning. We compare three Self-Management Support (SMS) pilots of two weeks duration, in which various tools and daily microlearning strategies were used. Average blood pressure improvements in the pilots were 161/112 to 129/90 mmHg, resp. 145/92 to 126/86 mmHg, and 155/95 to 139/85 mmHg. User evaluations (n=20) were collected on perceived effectiveness of the various support components. This showed the importance of core SMS components: information transfer, daily monitoring, promoting health competences and follow-up. A tentative cross-case conclusion is that more daily social learning and microlearning feedback helps build more success: for blood pressure results and for competence building.
Health 2050
Faster cure via bioinformatics and quantified self; a design analysis
Four areas make up 75% of our healthcare costs: cardio-, onco-, neuro- and metabolic diseases. These are largely preventable, even reversible. Instead, they are currently often ‘managed’ and made chronic, not cured. This is too costly. Research is showing new opportunities for enhancing our body’s self-repair in a matter of hours or days. Our research question: what could be an intervention- and bio-feedback portfolio to promote health self-repair within hours or days? There are large cross-domain differences regarding: intervention aims, (self-)measurement options, focus on symptoms vs. causes, plus degree of attention for health self-management. Given recent research into rapid cure, we advise advanced daily bioinformatics feedback, using molecular biomarkers. This creates a quantified self ‘endoself’, showing key biological opportunities for cure and self-repair. Thus, we shift from the current ‘antibiotics/external fix’ paradigm of healthcare to a ‘wound healing’ paradigm, improving use of resources in health.
...
Four areas make up 75% of our healthcare costs: cardio-, onco-, neuro- and metabolic diseases. These are largely preventable, even reversible. Instead, they are currently often ‘managed’ and made chronic, not cured. This is too costly. Research is showing new opportunities for enhancing our body’s self-repair in a matter of hours or days. Our research question: what could be an intervention- and bio-feedback portfolio to promote health self-repair within hours or days? There are large cross-domain differences regarding: intervention aims, (self-)measurement options, focus on symptoms vs. causes, plus degree of attention for health self-management. Given recent research into rapid cure, we advise advanced daily bioinformatics feedback, using molecular biomarkers. This creates a quantified self ‘endoself’, showing key biological opportunities for cure and self-repair. Thus, we shift from the current ‘antibiotics/external fix’ paradigm of healthcare to a ‘wound healing’ paradigm, improving use of resources in health.
High blood pressure is a leading cause of premature death. Healthy lifestyle choices (of diet, exercise, sleep and stress) could offer significant results. However, health literacy and -competence are lacking in most people, compared to best practice health choices, so there is room for improvement in creating hypertension self-management results. We tested an intensive two-week Self-Management Support (SMS) pilot, using daily feedback and microlearning cycles. Participants (n=8) reduced their blood pressure from 145/92 to 126/86 mmHg on average. User evaluation on effectiveness of the health support elements highlighted the importance of key SMS components like: information transfer, daily monitoring, enhancing problem solving/decision making, self-treatment using a tailored action plan, coping skills and ongoing follow-up with skilled coaches. Moreover, several aspects from microlearning, peer coaching, results-achievement and feeling better (=intrinsic motivation) were useful and hold promise for future intervention updates.
...
High blood pressure is a leading cause of premature death. Healthy lifestyle choices (of diet, exercise, sleep and stress) could offer significant results. However, health literacy and -competence are lacking in most people, compared to best practice health choices, so there is room for improvement in creating hypertension self-management results. We tested an intensive two-week Self-Management Support (SMS) pilot, using daily feedback and microlearning cycles. Participants (n=8) reduced their blood pressure from 145/92 to 126/86 mmHg on average. User evaluation on effectiveness of the health support elements highlighted the importance of key SMS components like: information transfer, daily monitoring, enhancing problem solving/decision making, self-treatment using a tailored action plan, coping skills and ongoing follow-up with skilled coaches. Moreover, several aspects from microlearning, peer coaching, results-achievement and feeling better (=intrinsic motivation) were useful and hold promise for future intervention updates.
E-health relationships diabetes
50 weeks evaluation
Journal article
(2022)
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Luuk P.A. Simons, Hanno Pijl, John Verhoef, Hildo J. Lamb, Ben van Ommen, Bas Gerritsen, Maurice B. Bizino, Marieke Snel, Ralph Feenstra, Catholijn M. Jonker
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 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.
...
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 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.
Globally, the burden of disease is rising. High performance employees and organisations need to improve their health self-management options and skills. Unfortunately, there are an overwhelming number (> 500,000) of new health publications every year. We aim to design a health AI on top of Scholar Google, to support rapid employee do-it-yourself (DIY) health improvement. Thus, we analysed user requirements, based on design analyses for two cases: hypertension and type-2 diabetes (T2D), two major diseases of affluence in our society, which are reversible with healthy living. We show how a hybrid AI may empower employees instead of medicalising them. To conclude, we propose a next level of quantified self for worker health self-management.
...
Globally, the burden of disease is rising. High performance employees and organisations need to improve their health self-management options and skills. Unfortunately, there are an overwhelming number (> 500,000) of new health publications every year. We aim to design a health AI on top of Scholar Google, to support rapid employee do-it-yourself (DIY) health improvement. Thus, we analysed user requirements, based on design analyses for two cases: hypertension and type-2 diabetes (T2D), two major diseases of affluence in our society, which are reversible with healthy living. We show how a hybrid AI may empower employees instead of medicalising them. To conclude, we propose a next level of quantified self for worker health self-management.
Health Literature Hybrid AI for Health Improvement
A Design Analysis for Diabetes & Hypertension
Increasingly, front runner patients and practitioners want to use state-of-the-art science for rapid lifestyle based cure of diseases of affluence. However, the number of new health studies per year (>500.000) is overwhelming. How to quickly assess state-of-the-art and use new opportunities for rapid patient DIY (Do-It-Yourself) health improvement? In order to develop a health literature hybrid AI to aid DIY rapid health improvement, we analyze user side functional requirements. A cross case design analysis is conducted for hypertension and T2D (Type 2 Diabetes), two major cardiometabolic conditions in our society. Our analysis shows that current DIY health support is ‘watered down’ advise, prone to medicalizing rather than empowering patients. We propose hybrid AI user requirements and discuss how a 2030 hybrid AI health support system can stimulate new ways of working in health and cure.
...
Increasingly, front runner patients and practitioners want to use state-of-the-art science for rapid lifestyle based cure of diseases of affluence. However, the number of new health studies per year (>500.000) is overwhelming. How to quickly assess state-of-the-art and use new opportunities for rapid patient DIY (Do-It-Yourself) health improvement? In order to develop a health literature hybrid AI to aid DIY rapid health improvement, we analyze user side functional requirements. A cross case design analysis is conducted for hypertension and T2D (Type 2 Diabetes), two major cardiometabolic conditions in our society. Our analysis shows that current DIY health support is ‘watered down’ advise, prone to medicalizing rather than empowering patients. We propose hybrid AI user requirements and discuss how a 2030 hybrid AI health support system can stimulate new ways of working in health and cure.
Health 2050: Bioinformatics for Rapid Self-Repair
A Design Analysis for Future Quantified Self
About 75% of our healthcare costs go to four domains (cardio -, onco -, neuro - and metabolic) of diseases which are largely preventable or even reversible. Instead, they are ‘managed’ and made chronic, not cured. This is very costly and unsustainable for the future. Research is showing new opportunities for enhancing our body’s self -repair in a matter of hours or days. We want to empower personal cure with rapid feedback for self - management. What could be an intervention - and bio- feedback portfolio to promote health self -repair within hours or days? Using a cross -case design analysis, we found large differences across the four health domains regarding: intervention aims, (self - )measurement options, focus on symptoms vs causes, plus degree of attention for health self - management. Given recent developments in rapid cure, we advise advanced daily bioinformatics feedback, instead of current quarterly cycles, to improve our self - repair effectiveness.
...
About 75% of our healthcare costs go to four domains (cardio -, onco -, neuro - and metabolic) of diseases which are largely preventable or even reversible. Instead, they are ‘managed’ and made chronic, not cured. This is very costly and unsustainable for the future. Research is showing new opportunities for enhancing our body’s self -repair in a matter of hours or days. We want to empower personal cure with rapid feedback for self - management. What could be an intervention - and bio- feedback portfolio to promote health self -repair within hours or days? Using a cross -case design analysis, we found large differences across the four health domains regarding: intervention aims, (self - )measurement options, focus on symptoms vs causes, plus degree of attention for health self - management. Given recent developments in rapid cure, we advise advanced daily bioinformatics feedback, instead of current quarterly cycles, to improve our self - repair effectiveness.
EHealth WhatsApp for social support
Design lessons
WhatsApp was evaluated as group support tool for a high impact healthy lifestyle intervention, with 11 young professionals. Users valued the WhatsApp group as an attractive social support addition to the existing eTools and personal coaching. Based on preliminary results: 1) the WhatsApp group generated higher participation than most other social media; 2) deploying social media use motives; 3) possibly due to the relatively high 'presence' and 'engagement' attributes of WhatsApp; 4) contributing to healthy behaviours and health advocacy. Peer coaching was confirmed as promising. However, participation declined after the initial weeks. A design lesson was that users wanted more support for community forming. Several improvement suggestions are provided.
...
WhatsApp was evaluated as group support tool for a high impact healthy lifestyle intervention, with 11 young professionals. Users valued the WhatsApp group as an attractive social support addition to the existing eTools and personal coaching. Based on preliminary results: 1) the WhatsApp group generated higher participation than most other social media; 2) deploying social media use motives; 3) possibly due to the relatively high 'presence' and 'engagement' attributes of WhatsApp; 4) contributing to healthy behaviours and health advocacy. Peer coaching was confirmed as promising. However, participation declined after the initial weeks. A design lesson was that users wanted more support for community forming. Several improvement suggestions are provided.
WhatsApp was evaluated as a peer coach group support tool in a healthy lifestyle intervention with 15 young professionals. These individuals were time-constrained professionals, so two design challenges were to create enough attractiveness and quality in the peer group interactions. There were three main health domains: food, physical activity, and mental energy. As a result of the 12 week pilot, there were 127 WhatsApp peer coaching inputs. The variety of inputs was better than in a previous pilot; peer coaching quality improved; plus there was more continuity following the initial two weeks. Community building remained a challenge, especially in the longer run. Two design solutions seemed to work: pre-designed coach-inputs across health domains, plus the instructions for a health advocate from the group, per health domain. Based on the results, the authors hypothesize that user needs in the first five weeks …
...
WhatsApp was evaluated as a peer coach group support tool in a healthy lifestyle intervention with 15 young professionals. These individuals were time-constrained professionals, so two design challenges were to create enough attractiveness and quality in the peer group interactions. There were three main health domains: food, physical activity, and mental energy. As a result of the 12 week pilot, there were 127 WhatsApp peer coaching inputs. The variety of inputs was better than in a previous pilot; peer coaching quality improved; plus there was more continuity following the initial two weeks. Community building remained a challenge, especially in the longer run. Two design solutions seemed to work: pre-designed coach-inputs across health domains, plus the instructions for a health advocate from the group, per health domain. Based on the results, the authors hypothesize that user needs in the first five weeks …
eHealth WhatsApp Group for Social Support
Preliminary Results
Within groups that are starting a healthy lifestyle intervention together, there is potential for social e-support, as an addition to individual coaching. However, the support technology should be low-tech, low-threshold and preferably already omnipresent. A WhatsApp group was chosen as support tool, given the large variety of groups normally coached: from elderly, IT-phobic diabetics to highly educated young professionals.
In this explorative pilot study, 11 young professionals volunteered. Despite their time-constrained schedules, 81 user inputs were generated in the first weeks, and the users valued the WhatsApp group as an attractive social support addition to the existing eTools and personal coaching which have a more functional focus on individual progress. Based on preliminary results: a) the WhatsApp group generated higher participation than most other social media, b) deploying social media use motives, c) possibly due to the relatively high ‘presence’ and ‘engagement’ attributes of WhatsApp, and d) contributing to healthy behaviours and health advocacy. ...
In this explorative pilot study, 11 young professionals volunteered. Despite their time-constrained schedules, 81 user inputs were generated in the first weeks, and the users valued the WhatsApp group as an attractive social support addition to the existing eTools and personal coaching which have a more functional focus on individual progress. Based on preliminary results: a) the WhatsApp group generated higher participation than most other social media, b) deploying social media use motives, c) possibly due to the relatively high ‘presence’ and ‘engagement’ attributes of WhatsApp, and d) contributing to healthy behaviours and health advocacy. ...
Within groups that are starting a healthy lifestyle intervention together, there is potential for social e-support, as an addition to individual coaching. However, the support technology should be low-tech, low-threshold and preferably already omnipresent. A WhatsApp group was chosen as support tool, given the large variety of groups normally coached: from elderly, IT-phobic diabetics to highly educated young professionals.
In this explorative pilot study, 11 young professionals volunteered. Despite their time-constrained schedules, 81 user inputs were generated in the first weeks, and the users valued the WhatsApp group as an attractive social support addition to the existing eTools and personal coaching which have a more functional focus on individual progress. Based on preliminary results: a) the WhatsApp group generated higher participation than most other social media, b) deploying social media use motives, c) possibly due to the relatively high ‘presence’ and ‘engagement’ attributes of WhatsApp, and d) contributing to healthy behaviours and health advocacy.
In this explorative pilot study, 11 young professionals volunteered. Despite their time-constrained schedules, 81 user inputs were generated in the first weeks, and the users valued the WhatsApp group as an attractive social support addition to the existing eTools and personal coaching which have a more functional focus on individual progress. Based on preliminary results: a) the WhatsApp group generated higher participation than most other social media, b) deploying social media use motives, c) possibly due to the relatively high ‘presence’ and ‘engagement’ attributes of WhatsApp, and d) contributing to healthy behaviours and health advocacy.
Improving Employee Health
Lessons from an RCT
Journal article
(2017)
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Luuk Simons, Maurits P.J. Hafkamp, David van Bodegom, A Dumaij, Catholijn Jonker
Work site healthy lifestyle interventions hold promise for improving health and employability. As part of a larger employer vitality program and a work site randomised controlled trial (RCT, n = 59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was six weeks waiting list and then start of the hybrid eHealth support (n = 57). Our analysis supports three conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after six weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patients appeared generalisable to employees: it did help to offer support at a moment of high motivation, instead of later. Hence, offering employees active health support directly after physical measurements (health check-ups) is more effective for improving health and self-management than the common practice of focusing on the employee check-up itself. Third, a design analysis was conducted to help improve ICT-enabled health interventions. This resulted in several recommendations and improved user adoption.
...
Work site healthy lifestyle interventions hold promise for improving health and employability. As part of a larger employer vitality program and a work site randomised controlled trial (RCT, n = 59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was six weeks waiting list and then start of the hybrid eHealth support (n = 57). Our analysis supports three conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after six weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patients appeared generalisable to employees: it did help to offer support at a moment of high motivation, instead of later. Hence, offering employees active health support directly after physical measurements (health check-ups) is more effective for improving health and self-management than the common practice of focusing on the employee check-up itself. Third, a design analysis was conducted to help improve ICT-enabled health interventions. This resulted in several recommendations and improved user adoption.
Diabetes Lifestyle (e)Coaching 50 Weeks Follow Up
Technology Acceptance & e-Relationships
Conference paper
(2017)
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L.P.A. Simons, Hanno Pijl, John Verhoef, HJ Lamb, B van Ommen, Bas Gerritsen, MB Bizino, M Snel, Ralph Feenstra, C.M. Jonker
We report on the 50 weeks follow up results from a healthy lifestyle pilot (High Intensity Nutrition, Training & coaching), conducted with 11 insulin - dependent Type 2 Diabetes Mellites (DM2) patients. Hybrid eH ealth support was given, with electronic support plus a multi - disciplinary health support team. Regarding the pilot goal of long term healthy lifestyle adoption in senior DM2 patients, challenges were: low ICT - and health literacy. This exploratory design analysis formulates design lessons based on 50 weeks follow up. The first 12 weeks contained intensive face - to - face and eSupported coaching. After that, patient self - management and eTools were key. After 50 weeks, attractiveness and feasibility of the in tervention were perceived as high: recommendation 9,5 out of 10 and satisfaction 9,6 out of 10. TAM (Technology Acceptance Model) surveys showed high usefulness and feasibility. Acceptance and health behaviours were reinforced by the prolonged health resu lts: Aerobic and strength capacity levels were improved at 50 weeks, plus Health Related Quality of Life (and biometric benefits and medication reductions, reported elsewhere). We draw three types of conclusions. First, patients’ health literacy and qualit y of life improved strongly, which both supported healthy behaviours, even after 50 weeks. Second, regarding eHealth theory, iterative growth cycles are beneficial for long term adoption and e - relationships. Third, a design analysis was conducted regarding long term service mix efficacy in relation to key requirements for designing ICT - enabled lifestyle interventions. Several suggestions for long term lifestyle eSupport are given.
...
We report on the 50 weeks follow up results from a healthy lifestyle pilot (High Intensity Nutrition, Training & coaching), conducted with 11 insulin - dependent Type 2 Diabetes Mellites (DM2) patients. Hybrid eH ealth support was given, with electronic support plus a multi - disciplinary health support team. Regarding the pilot goal of long term healthy lifestyle adoption in senior DM2 patients, challenges were: low ICT - and health literacy. This exploratory design analysis formulates design lessons based on 50 weeks follow up. The first 12 weeks contained intensive face - to - face and eSupported coaching. After that, patient self - management and eTools were key. After 50 weeks, attractiveness and feasibility of the in tervention were perceived as high: recommendation 9,5 out of 10 and satisfaction 9,6 out of 10. TAM (Technology Acceptance Model) surveys showed high usefulness and feasibility. Acceptance and health behaviours were reinforced by the prolonged health resu lts: Aerobic and strength capacity levels were improved at 50 weeks, plus Health Related Quality of Life (and biometric benefits and medication reductions, reported elsewhere). We draw three types of conclusions. First, patients’ health literacy and qualit y of life improved strongly, which both supported healthy behaviours, even after 50 weeks. Second, regarding eHealth theory, iterative growth cycles are beneficial for long term adoption and e - relationships. Third, a design analysis was conducted regarding long term service mix efficacy in relation to key requirements for designing ICT - enabled lifestyle interventions. Several suggestions for long term lifestyle eSupport are given.
Conference paper
(2016)
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Luuk P.A. Simons, Hanno Pijl, John Verhoef, Hildo J. Lamb, Ben van Ommen, Bas Gerritsen, Maurice B. Bizino, Marieke Snel, Ralph Feenstra, Catholijn M. Jonker
Advanced diabetes-type-2 patients often have high insulin resistance. Over the years their insulin medication rises, which further increases their insulin resistance and glucose management problems. A HINTc (High Intensity Nutrition, Training & coaching) pilot study was conducted with 11 insulin-dependent patients. Hybrid eHealth support was given, with electronic support plus a multi-disciplinary health support team. Based on preliminary 12 week results, attractiveness and feasibility of the intervention were high: recommendation 9,0 out of 10 and satisfaction 9,1 out of 10. TAM (Technology Acceptance Model) surveys showed high usefulness, feasibility and intentions for future use. Acceptance and health behaviours were also reinforced by the rapid results (average 9% weight loss, 20% lower fasting glucose and 71% lower insulin medication, plus a 46% increase on the Quality of Life Physical Health dimension). Our analysis supports three types of conclusions. First, patients’ health literacy and quality of life improved strongly, both supporting healthier behaviours. Second, a virtuous cycle was started, helping patients reverse diabetes-2 progression. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions.
...
Advanced diabetes-type-2 patients often have high insulin resistance. Over the years their insulin medication rises, which further increases their insulin resistance and glucose management problems. A HINTc (High Intensity Nutrition, Training & coaching) pilot study was conducted with 11 insulin-dependent patients. Hybrid eHealth support was given, with electronic support plus a multi-disciplinary health support team. Based on preliminary 12 week results, attractiveness and feasibility of the intervention were high: recommendation 9,0 out of 10 and satisfaction 9,1 out of 10. TAM (Technology Acceptance Model) surveys showed high usefulness, feasibility and intentions for future use. Acceptance and health behaviours were also reinforced by the rapid results (average 9% weight loss, 20% lower fasting glucose and 71% lower insulin medication, plus a 46% increase on the Quality of Life Physical Health dimension). Our analysis supports three types of conclusions. First, patients’ health literacy and quality of life improved strongly, both supporting healthier behaviours. Second, a virtuous cycle was started, helping patients reverse diabetes-2 progression. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions.
Work site healthy lifestyle interventions hold promise for improving health and
employability. As part of a larger employer vitality program and a work site RCT
(Randomized Controlled Trial, n=59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was a six weeks waiting list and then start of the hybrid eHealth support (n=57).
Based on preliminary 6 week- and 3 month-results, the hybrid eHealth support
generated statistically significant risk factors improvement (like LDL cholesterol). The waiting list condition yielded no significant improvements. The late start after the waiting list did yield significant improvements, but not as large as a direct start. The direct start also appears to yield higher satisfaction and intention to recommend.
Our analysis supports three types of conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after 6 weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patient appeared generalizable to employees: it did help to offer support at a moment of high motivation, instead of later. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions. This resulted in several recommendations and improved service adoption. ...
employability. As part of a larger employer vitality program and a work site RCT
(Randomized Controlled Trial, n=59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was a six weeks waiting list and then start of the hybrid eHealth support (n=57).
Based on preliminary 6 week- and 3 month-results, the hybrid eHealth support
generated statistically significant risk factors improvement (like LDL cholesterol). The waiting list condition yielded no significant improvements. The late start after the waiting list did yield significant improvements, but not as large as a direct start. The direct start also appears to yield higher satisfaction and intention to recommend.
Our analysis supports three types of conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after 6 weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patient appeared generalizable to employees: it did help to offer support at a moment of high motivation, instead of later. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions. This resulted in several recommendations and improved service adoption. ...
Work site healthy lifestyle interventions hold promise for improving health and
employability. As part of a larger employer vitality program and a work site RCT
(Randomized Controlled Trial, n=59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was a six weeks waiting list and then start of the hybrid eHealth support (n=57).
Based on preliminary 6 week- and 3 month-results, the hybrid eHealth support
generated statistically significant risk factors improvement (like LDL cholesterol). The waiting list condition yielded no significant improvements. The late start after the waiting list did yield significant improvements, but not as large as a direct start. The direct start also appears to yield higher satisfaction and intention to recommend.
Our analysis supports three types of conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after 6 weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patient appeared generalizable to employees: it did help to offer support at a moment of high motivation, instead of later. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions. This resulted in several recommendations and improved service adoption.
employability. As part of a larger employer vitality program and a work site RCT
(Randomized Controlled Trial, n=59 intervention arm) to assess cardiac risk impacts, we conducted a design analysis on a hybrid eHealth solution. The control condition was a six weeks waiting list and then start of the hybrid eHealth support (n=57).
Based on preliminary 6 week- and 3 month-results, the hybrid eHealth support
generated statistically significant risk factors improvement (like LDL cholesterol). The waiting list condition yielded no significant improvements. The late start after the waiting list did yield significant improvements, but not as large as a direct start. The direct start also appears to yield higher satisfaction and intention to recommend.
Our analysis supports three types of conclusions. First, the hybrid eHealth intervention did significantly improve physical risk factor variables after 6 weeks. Motivation and measurement alone (waiting list) did not. Second, theory on timing of health support for patient appeared generalizable to employees: it did help to offer support at a moment of high motivation, instead of later. Third, a design analysis was conducted regarding service mix efficacy in relation to key requirements for designing ICT-enabled lifestyle interventions. This resulted in several recommendations and improved service adoption.