scholarly journals Electronic Health Program to Empower Patients in Returning to Normal Activities After General Surgical and Gynecological Procedures: Intervention Mapping as a Useful Method for Further Development (Preprint)

2018 ◽  
Author(s):  
Chantal M den Bakker ◽  
Frederieke G Schaafsma ◽  
Eva van der Meij ◽  
Wilhelmus JHJ Meijerink ◽  
Baukje van den Heuvel ◽  
...  
Keyword(s):  
Intervention Program ◽  
Intervention Mapping ◽  
Theoretical Framework ◽  
Mobile App ◽  
Survey Study ◽  
Program Outcomes ◽  
Activity Tracker ◽  
Electronic Health ◽  
Ehealth Intervention ◽  
Further Development

BACKGROUND Support for guiding and monitoring postoperative recovery and resumption of activities is usually not provided to patients after discharge from the hospital. Therefore, a perioperative electronic health (eHealth) intervention (“ikherstel” intervention or “I recover” intervention) was developed to empower gynecological patients during the perioperative period. This eHealth intervention requires a need for further development for patients who will undergo various types of general surgical and gynecological procedures. OBJECTIVE This study aimed to further develop the “ikherstel” eHealth intervention using Intervention Mapping (IM) to fit a broader patient population. METHODS The IM protocol was used to guide further development of the “ikherstel” intervention. First, patients’ needs were identified using (1) the information of a process evaluation of the earlier performed “ikherstel” study, (2) a review of the literature, (3) a survey study, and (4) focus group discussions (FGDs) among stakeholders. Next, program outcomes and change objectives were defined. Third, behavior change theories and practical tools were selected for the intervention program. Finally, an implementation and evaluation plan was developed. RESULTS The outcome for an eHealth intervention tool for patients recovering from abdominal general surgical and gynecological procedures was redefined as “achieving earlier recovery including return to normal activities and work.” The Attitude-Social Influence-Self-Efficacy model was used as a theoretical framework to transform personal and external determinants into change objectives of personal behavior. The knowledge gathered by needs assessment and using the theoretical framework in the preparatory steps of the IM protocol resulted in additional tools. A mobile app, an activity tracker, and an electronic consultation (eConsult) will be incorporated in the further developed eHealth intervention. This intervention will be evaluated in a multicenter, single-blinded randomized controlled trial with 18 departments in 11 participating hospitals in the Netherlands. CONCLUSIONS The intervention is extended to patients undergoing general surgical procedures and for malignant indications. New intervention tools such as a mobile app, an activity tracker, and an eConsult were developed. CLINICALTRIAL Netherlands Trial Registry NTR5686; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5686 

scholarly journals Tailoring Persuasive Electronic Health Strategies for Older Adults on the Basis of Personal Motivation: Web-Based Survey Study (Preprint)

2018 ◽  
Author(s):  
Lex van Velsen ◽  
Marijke Broekhuis ◽  
Stephanie Jansen-Kosterink ◽  
Harm op den Akker
Keyword(s):  
Older Adults ◽  
Factor Structure ◽  
Individual Characteristics ◽  
Survey Study ◽  
Living Situation ◽  
Web Based ◽  
Cronbach Alpha ◽  
Personal Motivation ◽  
Electronic Health ◽  
Ehealth Intervention

BACKGROUND Persuasive design, in which the aim is to change attitudes and behaviors by means of technology, is an important aspect of electronic health (eHealth) design. However, selecting the right persuasive feature for an individual is a delicate task and is likely to depend on individual characteristics. Personalization of the persuasive strategy in an eHealth intervention therefore seems to be a promising approach. OBJECTIVE This study aimed to develop a method that allows us to model motivation in older adults with respect to leading a healthy life and a strategy for personalizing the persuasive strategy of an eHealth intervention, based on this user model. METHODS We deployed a Web-based survey among older adults (aged >60 years) in the Netherlands. In the first part, we administered an adapted version of the revised Sports Motivation Scale (SMS-II) as input for the user models. Then, we provided each participant with a selection of 5 randomly chosen mock-ups (out of a total of 11), each depicting a different persuasive strategy. After showing each strategy, we asked participants how much they appreciated it. The survey was concluded by addressing demographics. RESULTS A total of 212 older adults completed the Web-based survey, with a mean age of 68.35 years (SD 5.27 years). Of 212 adults, 45.3% were males (96/212) and 54.7% were female (116/212). Factor analysis did not allow us to replicate the 5-factor structure for motivation, as targeted by the SMS-II. Instead, a 3-factor structure emerged with a total explained variance of 62.79%. These 3 factors are intrinsic motivation, acting because of deriving satisfaction from the behavior itself (5 items; Cronbach alpha=.90); external regulation, acting because of externally controlled rewards or punishments (4 items; Cronbach alpha=.83); and a-motivation, a situation where there is a lack of intention to act (2 items; r=0.50; P<.001). Persuasive strategies were appreciated differently, depending on the type of personal motivation. In some cases, demographics played a role. CONCLUSIONS The personal type of motivation of older adults (intrinsic, externally regulated, and/or a-motivation), combined with their educational level or living situation, affects an individual’s like or dislike for a persuasive eHealth feature. We provide a practical approach for profiling older adults as well as an overview of which persuasive features should or should not be provided to each profile. Future research should take into account the coexistence of multiple types of motivation within 1 individual and the presence of a-motivation.

scholarly journals Tailoring Persuasive Electronic Health Strategies for Older Adults on the Basis of Personal Motivation: Web-Based Survey Study

10.2196/11759 ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. e11759 ◽  
Author(s):  
Lex van Velsen ◽  
Marijke Broekhuis ◽  
Stephanie Jansen-Kosterink ◽  
Harm op den Akker
Keyword(s):  
Older Adults ◽  
Factor Structure ◽  
Individual Characteristics ◽  
Survey Study ◽  
Living Situation ◽  
Web Based ◽  
Cronbach Alpha ◽  
Personal Motivation ◽  
Electronic Health ◽  
Ehealth Intervention

Background Persuasive design, in which the aim is to change attitudes and behaviors by means of technology, is an important aspect of electronic health (eHealth) design. However, selecting the right persuasive feature for an individual is a delicate task and is likely to depend on individual characteristics. Personalization of the persuasive strategy in an eHealth intervention therefore seems to be a promising approach. Objective This study aimed to develop a method that allows us to model motivation in older adults with respect to leading a healthy life and a strategy for personalizing the persuasive strategy of an eHealth intervention, based on this user model. Methods We deployed a Web-based survey among older adults (aged >60 years) in the Netherlands. In the first part, we administered an adapted version of the revised Sports Motivation Scale (SMS-II) as input for the user models. Then, we provided each participant with a selection of 5 randomly chosen mock-ups (out of a total of 11), each depicting a different persuasive strategy. After showing each strategy, we asked participants how much they appreciated it. The survey was concluded by addressing demographics. Results A total of 212 older adults completed the Web-based survey, with a mean age of 68.35 years (SD 5.27 years). Of 212 adults, 45.3% were males (96/212) and 54.7% were female (116/212). Factor analysis did not allow us to replicate the 5-factor structure for motivation, as targeted by the SMS-II. Instead, a 3-factor structure emerged with a total explained variance of 62.79%. These 3 factors are intrinsic motivation, acting to derive satisfaction from the behavior itself (5 items; Cronbach alpha=.90); external regulation, acting because of externally controlled rewards or punishments (4 items; Cronbach alpha=.83); and a-motivation, a situation where there is a lack of intention to act (2 items; r=0.50; P<.001). Persuasive strategies were appreciated differently, depending on the type of personal motivation. In some cases, demographics played a role. Conclusions The personal type of motivation of older adults (intrinsic, externally regulated, and/or a-motivation), combined with their educational level or living situation, affects an individual’s like or dislike for a persuasive eHealth feature. We provide a practical approach for profiling older adults as well as an overview of which persuasive features should or should not be provided to each profile. Future research should take into account the coexistence of multiple types of motivation within an individual and the presence of a-motivation.

scholarly journals Electronic Health Program to Empower Patients in Returning to Normal Activities After General Surgical and Gynecological Procedures: Intervention Mapping as a Useful Method for Further Development

2019 ◽  
Vol 21 (2) ◽  
pp. e9938 ◽  
Author(s):  
Chantal M den Bakker ◽  
Frederieke G Schaafsma ◽  
Eva van der Meij ◽  
Wilhelmus JHJ Meijerink ◽  
Baukje van den Heuvel ◽  
...  
Keyword(s):  
Health Program ◽  
Intervention Mapping ◽  
Electronic Health ◽  
Further Development

Examining the Adoption and Implementation of Behavioral Electronic Health Records by Healthcare Professionals Based on the Clinical Adoption Framework (Preprint)

2020 ◽  
Author(s):  
Sooyoung Yoo ◽  
Kahyun Lim ◽  
Se Young Jung ◽  
Keehyuck Lee ◽  
Donghyun Lee ◽  
...  
Keyword(s):  
Quantitative Study ◽  
Organizational Support ◽  
Healthcare Professionals ◽  
Mobile App ◽  
Ease Of Use ◽  
Path Coefficient ◽  
Significant Information ◽  
Adoption And Implementation ◽  
Electronic Health ◽  
Clinical Adoption

BACKGROUND The US Health Information Technology for Economic and Clinical Health Act of 2009, which was intended to stimulate the use of electronic health record (EHR) systems, has been amended to cover the behavioral health sector. Consequently, there is an increased need for research on the adoption of behavioral EHR systems by healthcare professionals. Various quantitative studies based on the unified theory of acceptance and use of technology model and technology acceptance model have been conducted in the general medical sectors, but few studies have been conducted in the behavioral sector and they have all been interview-based qualitative studies. OBJECTIVE To evaluate the adoption and implementation of a behavioral EHR system for behavioral clinical professionals through a modified clinical adoption (CA) research model quantitative study. METHODS We modified the existing CA framework to be suitable for evaluating the adoption of the EHR system by behavioral clinical professionals. The existing CA framework did not present questionnaire items. Accordingly, we designed a questionnaire with items that fit into the dimensions of the CA framework and it was verified through the review of behavioral clinical professionals and a pre-survey. The full-scale survey was administered in 5 US behavioral hospitals. The data were analyzed using a structural equation analysis. Additionally, open-ended question responses were qualitatively analyzed. RESULTS We derived a total of 7 dimensions, excluding dimensions that were evaluated as inappropriate for behavioral clinical professionals to respond. In addition, for 2 dimensions, 2 sub-dimensions were classified. A total of 409 behavioral clinical experts from 5 hospitals were surveyed. The ease of use and organizational support significantly influenced the use of the behavioral EHR system. Although the results were not significant, information quality (path coefficient=1.19, P>.05) and service quality (path coefficient=.085, P>.05) tended to influence the ease of use of the system. And Ease of Use (path coefficient=.253, P<.05) and the Organization (path coefficient=.802, P<.05) influenced the use of the system. The qualitative results indicated that the greatest advantage of the adoption of the behavioral EHR system was the ability to search for information quickly, work efficiently, and access patient information even outside of the hospital through the mobile app, resulting in having more time with patients. Conversely, the greatest disadvantage was an overdependence on the EHR system. Many staff members voiced concerns that their work could be paralyzed when the system was unstable. CONCLUSIONS This study designed a model for evaluating behavioral EHR adoption and conducted a quantitative study to derive the factors associated with the successful introduction of an EHR system in a behavioral environment. CLINICALTRIAL The study was approved by the Institutional Review Board of Seoul National University Bundang Hospital (SNUBH) (IRB No.: B-1904-534-301).

Developing a novel diabetes distress e-learning program for diabetes educators: an intervention mapping approach

2021 ◽  
Author(s):  
Jennifer A Halliday ◽  
Jane Speight ◽  
Sienna Russell-Green ◽  
Eric O ◽  
Virginia Hagger ◽  
...  
Keyword(s):  
Cognitive Theory ◽  
Tertiary Education ◽  
Emotional Health ◽  
Intervention Mapping ◽  
Diabetes Distress ◽  
Learning Program ◽  
Program Outcomes ◽  
Mapping Approach ◽  
E Learning ◽  
Diabetes Educators

Abstract Diabetes distress is a common negative emotional response to the ongoing burden of living with diabetes. Elevated diabetes distress is associated with impaired diabetes self-management and quality of life yet rarely identified and addressed in clinical practice. Health professionals report numerous barriers to the provision of care for diabetes distress, including lack of skills and confidence, but few diabetes distress training opportunities exist. The purpose of this paper is to describe how we utilized Intervention Mapping to plan the development, implementation, and evaluation of a novel diabetes distress e-learning program for diabetes educators, to meet a well-documented need and significant gap in diabetes care. A multidisciplinary team (combining expertise in research, health and clinical psychology, diabetes education, nursing, tertiary education, and website architecture) developed a diabetes distress e-learning program. We followed a six-step process (logic model of the problem, program outcomes and objectives, program design, program production, program implementation plan, and evaluation plan) known as Intervention Mapping. The program is underpinned by educational and psychological theory, including Bloom’s Taxonomy of Educational Objectives and social cognitive theory. We developed a short (estimated 4 h) e-learning program for diabetes educators, which draws on the content of the Diabetes and Emotional Health handbook and toolkit. It integrates a 7As model, which provides a stepwise approach to identifying and addressing diabetes distress. Our diabetes distress e-learning program has been developed systematically, guided by an Intervention Mapping approach. In the next phase of the project, we will trial the e-learning.

scholarly journals Patients’ moral attitudes toward electronic health records: Survey study with vignettes and statements

2021 ◽  
Vol 27 (1) ◽  
pp. 146045822098003
Author(s):  
Tania Moerenhout ◽  
Ignaas Devisch ◽  
Laetitia Cooreman ◽  
Jodie Bernaerdt ◽  
An De Sutter ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
De Novo ◽  
Information Access ◽  
Survey Study ◽  
Sensitive Information ◽  
Patient Portal ◽  
Care Providers ◽  
Health Records ◽  
Electronic Health ◽  
Moral Attitudes

Patient access to electronic health records gives rise to ethical questions related to the patient-doctor-computer relationship. Our study aims to examine patients’ moral attitudes toward a shared EHR, with a focus on autonomy, information access, and responsibility. A de novo self-administered questionnaire containing three vignettes and 15 statements was distributed among patients in four different settings. A total of 1688 valid questionnaires were collected. Patients’ mean age was 51 years, 61% was female, 50% had a higher degree (college or university), and almost 50% suffered from a chronic illness. Respondents were hesitant to hide sensitive information electronically from their care providers. They also strongly believed hiding information could negatively affect the quality of care provided. Participants preferred to be informed about negative test results in a face-to-face conversation, or would have every patient decide individually how they want to receive results. Patients generally had little experience using patient portal systems and expressed a need for more information on EHRs in this survey. They tended to be hesitant to take up control over their medical data in the EHR and deemed patients share a responsibility for the accuracy of information in their record.

scholarly journals Diabetes Management Experience and the State of Hypoglycemia: National Online Survey Study

JMIR Diabetes ◽  
10.2196/17890 ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. e17890
Author(s):  
Karim Zahed ◽  
Farzan Sasangohar ◽  
Ranjana Mehta ◽  
Madhav Erraguntla ◽  
Khalid Qaraqe
Keyword(s):  
Blood Sugar ◽  
Online Survey ◽  
Diabetes Management ◽  
Nonparametric Tests ◽  
Mobile App ◽  
Survey Study ◽  
Management Tool ◽  
False Alarms ◽  
Diabetic Patients ◽  
Cross Sectional

Background Hypoglycemia, or low blood sugar levels, in people with diabetes can be a serious life-threatening condition, and serious outcomes can be avoided if low levels of blood sugar are proactively detected. Although technologies exist to detect the onset of hypoglycemia, they are invasive or costly or exhibit a high incidence of false alarms. Tremors are commonly reported symptoms of hypoglycemia and may be used to detect hypoglycemic events, yet their onset is not well researched or understood. Objective This study aimed to understand diabetic patients’ perceptions of hypoglycemic tremors, as well as their user experiences with technology to manage diabetes, and expectations from a self-management tool to ultimately inform the design of a noninvasive and cost-effective technology that detects tremors associated with hypoglycemia. Methods A cross-sectional internet panel survey was administered to adult patients with type 1 diabetes using the Qualtrics platform in May 2019. The questions focused on 3 main constructs: (1) perceived experiences of hypoglycemia, (2) experiences and expectations about a diabetes management device and mobile app, and (3) beliefs and attitudes regarding intention to use a diabetes management device. The analysis in this paper focuses on the first two constructs. Nonparametric tests were used to analyze the Likert scale data, with a Mann-Whitney U test, Kruskal-Wallis test, and Games-Howell post hoc test as applicable, for subgroup comparisons to highlight differences in perceived frequency, severity, and noticeability of hypoglycemic tremors across age, gender, years living with diabetes, and physical activity. Results Data from 212 respondents (129 [60.8%] females) revealed statistically significant differences in perceived noticeability of tremors by gender, whereby males noticed their tremors more (P<.001), and age, with the older population reporting lower noticeability than the young and middle age groups (P<.001). Individuals living longer with diabetes noticed their tremors significantly less than those with diabetes for ≤1 year but not in terms of frequency or severity. Additionally, the majority of our participants (150/212, 70.7%) reported experience with diabetes-monitoring devices. Conclusions Our findings support the need for cost-efficient and noninvasive continuous monitoring technologies. Although hypoglycemic tremors were perceived to occur frequently, such tremors were not found to be severe compared with other symptoms such as sweating, which was the highest rated symptom in our study. Using a combination of tremor and galvanic skin response sensors may show promise in detecting the onset of hypoglycemic events.

scholarly journals Adults’ Preferences for Behavior Change Techniques and Engagement Features in a Mobile App to Promote 24-Hour Movement Behaviors: Cross-Sectional Survey Study (Preprint)

2019 ◽  
Author(s):  
Ann DeSmet ◽  
Ilse De Bourdeaudhuij ◽  
Sebastien Chastin ◽  
Geert Crombez ◽  
Ralph Maddison ◽  
...  
Keyword(s):  
Behavior Change ◽  
Repeated Measures ◽  
Self Regulation ◽  
Mobile App ◽  
User Preferences ◽  
Movement Behavior ◽  
Survey Study ◽  
User Engagement ◽  
Behavior Change Techniques ◽  
Self Monitoring

BACKGROUND There is a limited understanding of components that should be included in digital interventions for 24-hour movement behaviors (physical activity [PA], sleep, and sedentary behavior [SB]). For intervention effectiveness, user engagement is important. This can be enhanced by a user-centered design to, for example, explore and integrate user preferences for intervention techniques and features. OBJECTIVE This study aimed to examine adult users’ preferences for techniques and features in mobile apps for 24-hour movement behaviors. METHODS A total of 86 participants (mean age 37.4 years [SD 9.2]; 49/86, 57% female) completed a Web-based survey. Behavior change techniques (BCTs) were based on a validated taxonomy v2 by Abraham and Michie, and engagement features were based on a list extracted from the literature. Behavioral data were collected using Fitbit trackers. Correlations, (repeated measures) analysis of variance, and independent sample <italic>t</italic> tests were used to examine associations and differences between and within users by the type of health domain and users’ behavioral intention and adoption. RESULTS Preferences were generally the highest for information on the health consequences of movement behavior self-monitoring, behavioral feedback, insight into healthy lifestyles, and tips and instructions. Although the same ranking was found for techniques across behaviors, preferences were stronger for all but one BCT for PA in comparison to the other two health behaviors. Although techniques fit user preferences for addressing PA well, supplemental techniques may be able to address preferences for sleep and SB in a better manner. In addition to what is commonly included in apps, sleep apps should consider providing tips for sleep. SB apps may wish to include more self-regulation and goal-setting techniques. Few differences were found by users’ intentions or adoption to change a particular behavior. Apps should provide more self-monitoring (<italic>P</italic>=.03), information on behavior health outcome (<italic>P</italic>=.048), and feedback (<italic>P</italic>=.04) and incorporate social support (<italic>P</italic>=.048) to help those who are further removed from healthy sleep. A virtual coach (<italic>P</italic><.001) and video modeling (<italic>P</italic>=.004) may provide appreciated support to those who are physically less active. PA self-monitoring appealed more to those with an intention to change PA (<italic>P</italic>=.03). Social comparison and support features are not high on users’ agenda and may not be needed from an engagement point of view. Engagement features may not be very relevant for user engagement but should be examined in future research with a less reflective method. CONCLUSIONS The findings of this study provide guidance for the design of digital 24-hour movement behavior interventions. As 24-hour movement guidelines are increasingly being adopted in several countries, our study findings are timely to support the design of interventions to meet these guidelines.

scholarly journals Exploring the potential for collaborative use of an app-based platform for n-of-1 trials among healthcare professionals that treat patients with insomnia

2020 ◽  
Author(s):  
Jason R. Bobe ◽  
Jessica K. De Freitas ◽  
Benjamin S. Glicksberg
Keyword(s):  
New York ◽  
Healthcare Professionals ◽  
Clinical Medicine ◽  
Educational Interventions ◽  
Mobile App ◽  
School Of Medicine ◽  
Level 1 ◽  
Electronic Health ◽  
Data Driven Decisions ◽  
Selection Of

AbstractBackgroundN-of-1 trials are single patient, multiple crossover, comparative effectiveness experiments. Despite their rating as “level 1” evidence, they are not routinely used in clinical medicine to evaluate the effectiveness of treatments.ObjectiveWe explored the potential for implementing a mobile app-based n-of-1 trial platform for collaborative use by clinicians and patients to support data-driven decisions around the treatment of insomnia.MethodsA survey assessing awareness and utilization of n-of-1 trials was administered to healthcare professionals that frequently treat patients with insomnia at the Icahn School of Medicine at Mount Sinai in New York City. 1M electronic health records were analyzed to evaluate evidence for a comorbid relationship between insomnia and dementia or Alzheimer’s disease among a patient population that may benefit from n-of-1 trials for the selection of optimal sleep treatments.ResultsA total of 45 healthcare professionals completed the survey and were included in the analysis. We found that 64% of healthcare professionals surveyed had not heard of n-of-1 trials. After a brief description of these methods, 75% of healthcare professionals reported that they are likely or highly likely to use an app-based n-of-1 trial at least once in the next year if the service were free and easy to offer to their patients.ConclusionsAn app-based n-of-1 trials platform might be a valuable tool for clinicians and patients to identify the best treatments for insomnia. Educational interventions that raise awareness and provide training are also likely necessary. The electronic health record (EHR) may help identify eligible patients.

scholarly journals I-THS-1908 A Big Data Electronic Health Record for Patient Care Management and Analytics

2019 ◽  
Author(s):  
Ahmad Hidayat ◽  
Arief Hasani
Keyword(s):  
Big Data ◽  
Electronic Health Record ◽  
Patient Care ◽  
Care Management ◽  
Patient Care Management ◽  
Health Conditions ◽  
Health Record ◽  
Complex Variety ◽  
Electronic Health ◽  
Further Development

The I-THS-1908, a big data electronic health record platform, is capable of establishing its capability as an electronic health record to tackle the large volume of data with high velocity and complex variety of patient data by providing the value to the patient care management and analytics. The further development of I-THS-1908 opens the opportunity to use the electronic health record for patient care management and analytics for all type of health conditions.

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