Using collective intelligence methods to improve government data infrastructures and promote the use of complex data: The example of the Northern Ireland Longitudinal Study.

BACKGROUND: This paper discusses how collective intelligence (CI) methods can be implemented to improve government data infrastructures, not only to support understanding and primary use of complex national data but also to increase the dissemination and secondary impact of research based on these data. The case study uses the Northern Ireland Longitudinal Study (NILS), a member of the UK family of census/administrative data longitudinal studies (UKLS). METHODS: A stakeholder-engaged CI approach was applied to inform the transformation of the NILS Research Support Unit (RSU) infrastructure to support researchers in their use of government data, including collaborative decision-making and better dissemination of research outputs. RESULTS: We provide an overview of NILS RSU infrastructure design changes that have been implemented to date, focusing on a website redesign to meet user information requirements and the formation of better working partnerships between data users and providers within the Northern Ireland data landscape. We also discuss the key challenges faced by the design team during this project of transformation. CONCLUSION: Our primary objective to improve government data infrastructure and to increase dissemination and the impact of research based on data was a complex and multifaceted challenge due to the number of stakeholders involved and their often conflicting perspectives. Results from this CI approach have been pivotal in highlighting how NILS RSU can work collaboratively with users to maximize the potential of this data, in terms of forming multidisciplinary networks to ensure the research is utilized in policy and in the literature and providing academic support and resources to attract new researchers.

Chronic pain self-management in middle-aged and older adults: A collective intelligence approach to identifying barriers and user needs in eHealth interventions.

Objectives: eHealth refers to health services and health information delivered or enhanced through the internet and related technologies. The number of eHealth interventions for chronic pain self-management is increasing. However, little evidence has been found for the overall efficacy of these interventions for older adults. The aim of the current study was to use a Collective Intelligence approach to identify the barriers and specific user needs of middle-aged and older adults using eHealth for chronic pain self-management. Methods: A Collective Intelligence workshop was conducted with middle-aged and older adults to generate, clarify, select, and structure ideas in relation to barriers to eHealth use and specific design requirements for the purposes of chronic pain self-management. Prior to attending the workshop, participants received a trigger question requesting the identification of five barriers to eHealth use for chronic pain self-management. These barriers were categorised and presented to the group along with barrier-related scenarios and user need prompts, resulting in the generation of a set of ranked barriers and a set of user needs. Results: A total of 78 barriers were identified, from which six categories emerged: Content, Support, Technological, Personal, Computer Literacy and Accessibility. Additional idea-writing and group reflection in response to these barriers revealed 97 user needs. Conclusion: This is the first study to use Collective Intelligence methods to investigate barriers to eHealth technology use and the specific user needs of middle-aged and older adults in the context of chronic pain self-management. The results of the current study provide a platform for the design and development of enhanced eHealth interventions for this population.

Acceptability of a Mobile Health Behavior Change Intervention for Cancer Survivors With Obesity or Overweight: Nested Mixed Methods Study Within a Randomized Controlled Trial.

BACKGROUND: A significant proportion of cancer survivors have overweight or obesity. Although this has negative implications for health, weight management is not a standard component of oncology aftercare. Mobile health (mHealth) technology, in combination with behavior change techniques (BCTs), has the potential to support positive lifestyle changes. Few studies have been carried out with cancer survivors; therefore, the acceptability of these tools and techniques requires further investigation. OBJECTIVE: The aim of this study is to examine the acceptability of a behavior change intervention using mHealth for cancer survivors with a BMI of 25 or more and to gather constructive feedback from participants. METHODS: The intervention consisted of educational sessions and an 8-week physical activity goal setting intervention delivered using mobile technology (ie, Fitbit activity monitor plus SMS contact). In the context of a two-arm randomized controlled trial, semistructured interviews were conducted to assess the retrospective acceptability of the intervention from the perspective of the recipients. The theoretical framework for the acceptability of health care interventions was used to inform a topic guide. The interviews were transcribed and analyzed using thematic analysis. A quantitative survey was also conducted to determine the acceptability of the intervention. A total of 13 participants were interviewed, and 36 participants completed the quantitative survey. RESULTS: The results strongly support the acceptability of the intervention. The majority of the survey respondents held a positive attitude toward the intervention (35/36, 97%). In qualitative reports, many of the intervention components were enjoyed and the mHealth components (ie, Fitbit and goal setting through text message contact) were rated especially positively. Responses were mixed as to whether the burden of participating in the intervention was high (6/36, 17%) or low (5/36, 14%). Participants perceived the intervention as having high efficacy in improving health and well-being (34/36, 94%). Most respondents said that they understood how the intervention works (35/36, 97%), and qualitative data show that participants' understanding of the aim of the intervention was broader than weight management and focused more on moving on psychologically from cancer. CONCLUSIONS: On the basis of the coherence of responses with theorized aspects of intervention acceptability, we are confident that this intervention using mHealth and BCTs is acceptable to cancer survivors with obesity or overweight. Participants made several recommendations concerning the additional provision of social support. Future studies are needed to assess the feasibility of delivery in clinical practice and the acceptability of the intervention to those delivering the intervention. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13214.

Examining the Impact of an mHealth Behavior Change Intervention With a Brief In-Person Component for Cancer Survivors With Overweight or Obesity: Randomized Controlled Trial.

BACKGROUND: Cancer survivorship in Ireland is increasing in both frequency and longevity. However, a significant proportion of cancer survivors do not reach the recommended physical activity levels and have overweight. This has implications for both physical and psychological health, including an increased risk of subsequent and secondary cancers. Mobile health (mHealth) interventions demonstrate potential for positive health behavior change, but there is little evidence for the efficacy of mobile technology in improving health outcomes in cancer survivors with overweight or obesity. OBJECTIVE: This study aims to investigate whether a personalized mHealth behavior change intervention improves physical and psychological health outcomes in cancer survivors with overweight or obesity. METHODS: A sample of 123 cancer survivors (BMI≥25 kg/m2) was randomly assigned to the standard care control (n=61) or intervention (n=62) condition. Group allocation was unblinded. The intervention group attended a 4-hour tailored lifestyle education and information session with physiotherapists, a dietician, and a clinical psychologist to support self-management of health behavior. Over the following 12 weeks, participants engaged in personalized goal setting to incrementally increase physical activity (with feedback and review of goals through SMS text messaging contact with the research team). Direct measures of physical activity were collected using a Fitbit accelerometer. Data on anthropometric, functional exercise capacity, dietary behavior, and psychological measures were collected at face-to-face assessments in a single hospital site at baseline (T0), 12 weeks (T1; intervention end), and 24 weeks (T2; follow-up). RESULTS: The rate of attrition was 21% (13/61) for the control condition and 14% (9/62) for the intervention condition. Using intent-to-treat analysis, significant reductions in BMI (F2,242=4.149; P=.02; ηp2=0.033) and waist circumference (F2,242=3.342; P=.04; ηp2=0.027) were observed in the intervention group. Over the 24-week study, BMI was reduced by 0.52 in the intervention condition, relative to a nonsignificant reduction of 0.11 in the control arm. Waist circumference was reduced by 3.02 cm in the intervention condition relative to 1.82 cm in the control condition. Physical activity level was significantly higher in the intervention group on 8 of the 12 weeks of the intervention phase and on 5 of the 12 weeks of the follow-up period, accounting for up to 2500 additional steps per day (mean 2032, SD 270). CONCLUSIONS: The results demonstrate that for cancer survivors with a BMI≥25 kg/m2, lifestyle education and personalized goal setting using mobile technology can yield significant changes in clinically relevant health indicators. Further research is needed to elucidate the mechanisms of behavior change and explore the capacity for mHealth interventions to improve broader health and well-being outcomes in the growing population of cancer survivors. TRIAL REGISTRATION: ISRCTN Registry ISRCTN18676721; https://www.isrctn.com/ISRCTN18676721. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13214.

Designing an e-learning tool to support health practitioners caring for patients taking multiple medications.

Background: Population ageing and improvements in healthcare mean the number of people living with two or more chronic conditions, or 'multimorbidity', is rapidly increasing. This presents a challenge to current disease-specific care delivery models. Adherence to prescribed medications appears particularly challenging for individuals living with multimorbidity, given the often-complex drug regimens required to treat multiple conditions. Poor adherence is associated with increased mortality, as well as wasted healthcare resources. Supporting medication adherence is a key priority for general practitioners (GPs) and practice nurses as they are responsible for much of the disease counselling and medication prescribing associated with chronic illnesses. Despite this, practical resources and training for health practitioners on how to promote adherence in practice is currently lacking. Informed by the principles of patient and public involvement (PPI), the aim of this research was to develop a patient informed e-learning resource to help GPs and nurses support medication adherence.  Method: Utilising collective intelligence (CI) and scenario-based design (SBD) methodology, input was gathered from 16 stakeholders to gain insights into barriers to supporting people with multimorbidity who are receiving polypharmacy, strategies for overcoming these barriers, and user needs and requirements to inform the design of the e-learning tool. Results: In total, 67 barriers to supporting people who are taking multiple medications were identified across 8 barrier categories. 162 options for overcoming the identified barriers were then generated. This data was used in the design of a short and flexible e-learning tool for continuous professional development, that has been integrated into general practice and clinical education programmes as a supportive tool. Conclusions: Using CI and SBD methodology was an effective way of facilitating collaboration, idea-generation, and the co-creation of design solutions amongst a diverse group of stakeholders. This approach could be usefully applied to address other complex healthcare-related challenges.

Examining the Impact of a Personalized Self-Management Lifestyle Program Using Mobile Technology on the Health and Well-Being of Cancer Survivors: Protocol and Rationale for a Randomized Controlled Trial (The Moving On Study).

BACKGROUND: Cancer survivorship in Ireland is increasing in both frequency and longevity. However, a significant proportion of cancer survivors are overweight. This has negative implications for long-term health outcomes, including increased risk of subsequent and secondary cancers. There is a need to identify interventions, which can improve physical and psychological outcomes that are practical in modern oncology care. Mobile health (mHealth) interventions demonstrate potential for positive health behavior change, but there is little evidence for the efficacy of mobile technology to improve health outcomes in cancer survivors. OBJECTIVE: This study aims to investigate whether a personalized mHealth self-management lifestyle program is acceptable to participants and can improve physical and psychological outcomes of a subgroup of cancer survivors with increased health risks related to lifestyle behaviors. METHODS: A sample of 123 cancer survivors (body mass index >25 kg/m2) was randomly assigned to the control (n=61) or intervention (n=62) group. The intervention group attended a 4-hour tailored lifestyle information session with a physiotherapist, dietician, and clinical psychologist to support self-management of health behavior. Over the following 12 weeks, participants engaged in personalized goal setting to incrementally increase physical activity (with feedback and review of goals through short message service text messaging contact). Objective measures of health behavior (ie, physical activity) were collected using Fitbit (Fitbit, Inc). Data on anthropometric, physiological, dietary behavior, and psychological measures were collected at baseline (T0), 12 weeks (T1; intervention end), and 24 weeks (T2; follow-up). Semistructured interviews were conducted to explore the retrospective acceptability of the Moving On program from the perspective of the recipients. RESULTS: This paper details the protocol for the Moving On study. The project was funded in August 2017. Enrolment started in December 2017. Data collection completed in September 2018. Data analysis is underway, and results are expected in winter 2019. CONCLUSIONS: The results of this study will determine the efficacy and acceptability of an mHealth intervention using behavior change techniques to promote health behaviors that support physical health and well-being in cancer survivors and will therefore have implications for health care providers, patients, health psychologists, and technologists. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13214.

Factors Influencing the Application of a Biopsychosocial Perspective in Clinical Judgement of Chronic Pain: Interactive Management with Medical Students.

BACKGROUND: Though there is wide support for the application of biopsychosocial perspectives in clinical judgement of chronic pain cases, such perspectives are often overlooked due to either inadequate training or attitudes favoring a biomedical approach. Recent research has indicated that despite such explanations, both established general practitioners (GP) and medical students account for some psychosocial factors when making clinical judgements regarding chronic pain cases, but report not being likely to apply these in real-world, clinical settings due to numerous factors, including available time with patients. Thus, it is evident that a greater understanding of clinical judgement-making processes and the factors that affect application of these processes is required, particularly regarding chronic pain. OBJECTIVES: The aims of the current study were to investigate medical students' conceptualizations of the factors that influence application of a biopsychosocial approach to clinical judgement-making in cases of chronic pain using interactive management (IM), model the relationships among these factors, and make recommendations to chronic pain treatment policy in light of the findings. STUDY DESIGN: The current study used IM to identify and model factors that influence the application of a biopsychosocial approach to clinical judgement-making in cases of chronic pain, based on medical students' conceptualizations of these factors. SETTING: Two university classrooms. METHODS: IM is a systems thinking and action mapping strategy used to aid groups in developing outcomes regarding complex issues, through integrating contributions from individuals with diverse views, backgrounds, and perspectives. IM commonly utilizes the nominal group technique and interpretive structural modeling, which in this context were employed to help medical students identify, clarify, and model influences on the application of biopsychosocial perspectives in treating chronic pain patients. RESULTS: Results of IM group work revealed 7 core biopsychosocial approach application categories: GP attitudes, cost, GP knowledge, time, patient-doctor relationship, biomedical factors. and patient perception. GP attitudes was the most critical driver of all other competencies in the system, with cost and GP knowledge revealed as secondary drivers. LIMITATIONS: Potential differences in level of prior biopsychosocial perspective knowledge across participants and a potentially small sample size (though consistent with past research and appropriate for an exploratory study of this nature - for purposes of achieving the depth and richness of the deliberation and qualitative insights revealed by participants using the IM methodology). CONCLUSIONS: Results from this study may be used to both recommend further research on the identified factors influencing application of biopsychosocial perspectives in treatment of chronic pain and support amendment to extant health care policy, particularly with respect to cost, GP attitudes, and knowledge. Though this research claims neither that the influences identified are the only influences on biopsychosocial application, nor the order of their importance, the research does contribute to an on-going effort to better understand the factors that influence doctors in their treatment of chronic pain.Key words: Chronic pain, biopsychosocial, medical education, clinical judgement, interactive management, pain management.