scholarly journals Identification of Factors That Motivate People With Multiple Sclerosis to Participate in Digital Data Collection in Research: Sequential Mixed Methods Study (Preprint)

2019 ◽  
Author(s):  
Astrid Karnoe ◽  
Lars Kayser ◽  
Lasse Skovgaard
Keyword(s):  
Multiple Sclerosis ◽  
Content Analysis ◽  
Mixed Methods ◽  
Data Collection ◽  
Phase 1 ◽  
Mixed Methods Study ◽  
Digital Data ◽  
Phase 2 ◽  
Data Collection Tool ◽  
Sequential Mixed Methods

BACKGROUND Digital data collection has the potential to reduce participant burden in research projects that require extensive registrations from participants. To achieve this, a digital data collection tool needs to address potential barriers and motivations for participation. OBJECTIVE This study aimed to identify factors that may affect motivation for participation and adoption of a digital data collection tool in a research project on nutrition and multiple sclerosis (MS). METHODS The study was designed as a sequential mixed methods study with 3 phases. In phase 1, 15 semistructured interviews were conducted in a Danish population of individuals with MS. Interview guide frameworks were based on dimensions from the electronic health literacy framework and the Health Education Impact Questionnaire. Data from phase 1 were analyzed in a content analysis, and findings were used to inform the survey design in phase 2 that validates the results from the content analysis in a larger population. The survey consisted of 14 items, and it was sent to 1000 individuals with MS (response rate 42.5%). In phase 3, participants in 3 focus group interviews discussed how findings from phases 1 and 2 might affect motivation for participation and adoption of the digital tool. RESULTS The following 3 categories related to barriers and incentives for participation were identified in the content analysis of the 15 individual interviews: (1) life with MS, (2) use of technology, and (3) participation and incentives. Phase 1 findings were tested in phase 2’s survey in a larger population (n=1000). The majority of participants were comfortable using smartphone technologies and participated actively on social media platforms. MS symptoms did cause limitations in the use of Web pages and apps when the given pages had screen clutter, too many colors, or too small buttons. Life with MS meant that most participants had to ration their energy levels. Support from family and friends was important to participants, but support could also come in the form of physical aids (walking aids and similar) and digital aids (reminders, calendar functions, and medication management). Factors that could discourage participation were particularly related to the time it would take every day. The biggest motivations for participation were to contribute to research in MS, to learn more about one’s own MS and what affects it, and to be able to exchange experiences with other people with MS. CONCLUSIONS MS causes limitations that put demands on tools developed for digital data collection. A digital data collection tool can increase chances of high adoption rates, but it needs to be supplemented with a clear and simple project design and continuous communication with participants. Motivational factors should be considered in both study design and the development of a digital data collection tool for research.

scholarly journals Identification of Factors That Motivate People With Multiple Sclerosis to Participate in Digital Data Collection in Research: Sequential Mixed Methods Study

10.2196/13295 ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. e13295 ◽  
Author(s):  
Astrid Karnoe ◽  
Lars Kayser ◽  
Lasse Skovgaard
Keyword(s):  
Multiple Sclerosis ◽  
Content Analysis ◽  
Mixed Methods ◽  
Data Collection ◽  
Phase 1 ◽  
Mixed Methods Study ◽  
Digital Data ◽  
Phase 2 ◽  
Data Collection Tool ◽  
Sequential Mixed Methods

Background Digital data collection has the potential to reduce participant burden in research projects that require extensive registrations from participants. To achieve this, a digital data collection tool needs to address potential barriers and motivations for participation. Objective This study aimed to identify factors that may affect motivation for participation and adoption of a digital data collection tool in a research project on nutrition and multiple sclerosis (MS). Methods The study was designed as a sequential mixed methods study with 3 phases. In phase 1, 15 semistructured interviews were conducted in a Danish population of individuals with MS. Interview guide frameworks were based on dimensions from the electronic health literacy framework and the Health Education Impact Questionnaire. Data from phase 1 were analyzed in a content analysis, and findings were used to inform the survey design in phase 2 that validates the results from the content analysis in a larger population. The survey consisted of 14 items, and it was sent to 1000 individuals with MS (response rate 42.5%). In phase 3, participants in 3 focus group interviews discussed how findings from phases 1 and 2 might affect motivation for participation and adoption of the digital tool. Results The following 3 categories related to barriers and incentives for participation were identified in the content analysis of the 15 individual interviews: (1) life with MS, (2) use of technology, and (3) participation and incentives. Phase 1 findings were tested in phase 2’s survey in a larger population (n=1000). The majority of participants were comfortable using smartphone technologies and participated actively on social media platforms. MS symptoms did cause limitations in the use of Web pages and apps when the given pages had screen clutter, too many colors, or too small buttons. Life with MS meant that most participants had to ration their energy levels. Support from family and friends was important to participants, but support could also come in the form of physical aids (walking aids and similar) and digital aids (reminders, calendar functions, and medication management). Factors that could discourage participation were particularly related to the time it would take every day. The biggest motivations for participation were to contribute to research in MS, to learn more about one’s own MS and what affects it, and to be able to exchange experiences with other people with MS. Conclusions MS causes limitations that put demands on tools developed for digital data collection. A digital data collection tool can increase chances of high adoption rates, but it needs to be supplemented with a clear and simple project design and continuous communication with participants. Motivational factors should be considered in both study design and the development of a digital data collection tool for research.

scholarly journals Codeveloping a multibehavioural mobile phone app to enhance social and emotional well-being and reduce health risks among Aboriginal and Torres Strait Islander women during preconception and pregnancy: a three-phased mixed-methods study

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e052545
Author(s):  
Michelle Kennedy ◽  
Ratika Kumar ◽  
Nicole M Ryan ◽  
Jessica Bennett ◽  
Gina La Hera Fuentes ◽  
...  
Keyword(s):  
Mixed Methods ◽  
Mobile Phone ◽  
Phase 1 ◽  
Qualitative Interviews ◽  
Mixed Methods Study ◽  
Phase 2 ◽  
Community Members ◽  
Phase 3 ◽  
Aboriginal Community ◽  
Aboriginal Women

ObjectiveDescribe the development and pretest of a prototype multibehavioural change app MAMA-EMPOWER.DesignMixed-methods study reporting three phases: (1) contextual enquiry included stakeholder engagement and qualitative interviews with Aboriginal women, (2) value specification included user-workshop with an Aboriginal researcher, community members and experts, (3) codesign with Aboriginal researchers and community members, followed by a pretest of the app with Aboriginal women, and feedback from qualitative interviews and the user-Mobile Application Rating Scale (U-MARS) survey tool.SettingsAboriginal women and communities in urban and regional New South Wales, Australia.ParticipantsPhase 1: interviews, 8 Aboriginal women. Phase 2: workshop, 6 Aboriginal women. Phase 3: app trial, 16 Aboriginal women. U-MARS, 5 Aboriginal women.ResultsPhase 1 interviews revealed three themes: current app use, desired app characteristics and implementation. Phase 2 workshop provided guidance for the user experience. Phase 3 app trial assessed all content areas. The highest ratings were for information (mean score of 3.80 out of 5, SD=0.77) and aesthetics (mean score of 3.87 with SD of 0.74), while functionality, engagement and subjective quality had lower scores. Qualitative interviews revealed the acceptability of the app, however, functionality was problematic.ConclusionsDeveloping a mobile phone app, particularly in an Aboriginal community setting, requires extensive consultation, negotiation and design work. Using a strong theoretical foundation of behavioural change technique’s coupled with the consultative approach has added rigour to this process. Using phone apps to implement behavioural interventions in Aboriginal community settings remains a new area for investigation. In the next iteration of the app, we aim to find better ways to personalise the content to women’s needs, then ensure full functionality before conducting a larger trial. We predict the process of development will be of interest to other health researchers and practitioners.

scholarly journals A comparison of holistic, analytic, and part marking models in speaking assessment

2020 ◽  
Vol 37 (3) ◽  
pp. 333-360
Author(s):  
Nahal Khabbazbashi ◽  
Evelina D. Galaczi
Keyword(s):  
Mixed Methods ◽  
Phase 1 ◽  
Mixed Methods Study ◽  
Measurement Properties ◽  
Phase 2 ◽  
Strong Correlations ◽  
Speaking Test ◽  
Speaking Assessment ◽  
Ability Levels

This mixed methods study examined holistic, analytic, and part marking models (MMs) in terms of their measurement properties and impact on candidate CEFR classifications in a semi-direct online speaking test. Speaking performances of 240 candidates were first marked holistically and by part (phase 1). On the basis of phase 1 findings—which suggested stronger measurement properties for the part MM—phase 2 focused on a comparison of part and analytic MMs. Speaking performances of 400 candidates were rated analytically and by part during that phase. Raters provided open comments on their marking experiences. Results suggested a significant impact of MM; approximately 30% and 50% of candidates in phases 1 and 2 respectively were awarded different (adjacent) CEFR levels depending on the choice of MM used to assign scores. There was a trend of higher CEFR levels with the holistic MM and lower CEFR levels with the part MM. Although strong correlations were found between all pairings of MMs, further analyses revealed important differences. The part MM was shown to display superior measurement qualities particularly in allowing raters to make finer distinctions between different speaking ability levels. These findings have implications for the scoring validity of speaking tests.

scholarly journals Hypothesis Formalization: Empirical Findings, Software Limitations, and Design Implications

2022 ◽  
Vol 29 (1) ◽  
pp. 1-28
Author(s):  
Eunice Jun ◽  
Melissa Birchfield ◽  
Nicole De Moura ◽  
Jeffrey Heer ◽  
René Just
Keyword(s):  
Content Analysis ◽  
Mixed Methods ◽  
Data Analysis ◽  
Data Collection ◽  
Statistical Models ◽  
Mixed Methods Study ◽  
Search Process ◽  
Research Papers ◽  
Proxy Variables ◽  
Key Steps

Data analysis requires translating higher level questions and hypotheses into computable statistical models. We present a mixed-methods study aimed at identifying the steps, considerations, and challenges involved in operationalizing hypotheses into statistical models, a process we refer to as hypothesis formalization . In a formative content analysis of 50 research papers, we find that researchers highlight decomposing a hypothesis into sub-hypotheses, selecting proxy variables, and formulating statistical models based on data collection design as key steps. In a lab study, we find that analysts fixated on implementation and shaped their analyses to fit familiar approaches, even if sub-optimal. In an analysis of software tools, we find that tools provide inconsistent, low-level abstractions that may limit the statistical models analysts use to formalize hypotheses. Based on these observations, we characterize hypothesis formalization as a dual-search process balancing conceptual and statistical considerations constrained by data and computation and discuss implications for future tools.

scholarly journals Developing a Competency Model for Nurses Certified in Infection Control in Japan

2020 ◽  
Vol 41 (S1) ◽  
pp. s514-s515
Author(s):  
Kazumi Kawakami ◽  
Hanako Misao
Keyword(s):  
Infectious Disease ◽  
Mixed Methods ◽  
Infection Control ◽  
Phase 1 ◽  
Competency Model ◽  
Full Time ◽  
Career Stage ◽  
Phase 2 ◽  
Sequential Mixed Methods ◽  
Competency Domains

Background: In July 2019, 2,793 nurses were registered as certified nurse in infection control (CNIC) at the Japanese Nursing Association (JNA). Most CNICs work as full-time infection preventionists (IPs) in hospitals. However, a competency model for CNICs has not been developed in Japan yet. Therefore, we developed a competency model for CNICs. Methods: We conducted a 2-phase explanatory sequential mixed-methods study between November 2013 and October 2019. The participants were 1,711 CNICs listed on the JNA website. Phase 1 was a cross-sectional study using self-administered questionnaires that included 10 competency domains based on the Association for Professionals in Infection Control and Epidemiology Competency Assessment Tool. Considering years of experience as an IP and full-time position, participants’ career stages were novice, competent, proficient, and expert. The CNICs who answered the questionnaire were included in the interview during phase 2, which was a descriptive qualitative study. Specifically, 10–30 participants were selected from each career stage. Semi-structured individual interviews were conducted, and verbatim transcripts were analyzed qualitatively. The knowledge, skills, and abilities of CNICs were extracted at each career stage. This study was approved by the Research Ethics Committee of Juntendo University (approval no. 25-27). Results: During phase 1, 1,711 CNICs were invited to participate: 975 returned the questionnaire (57% response rate) and 969 (99.3%) responses were valid and used in the analysis. Only 257 participants agreed to attend the interviews. In phase 2, interviews were conducted with 67 CNICs: 30 novice, 20 competent, 13 proficient, and 4 expert. The mean years of experience as a nurse and CNIC were 22.2 (SD, 7.0) and 5.3 (SD, 3.1), respectively. As the career stage advanced, the contents and range of infection prevention role and activities in the hospital or community expanded across competency domains. In clarification of infection process, one of the crucial competencies, the novice needed to consult reference material about the infectious disease each time due to lack of knowledge. Although the competent CNICs understood the frequent occurrence of infectious disease, they needed the specialist’s advice. However, the proficient and expert CNICs could interpret information independently, and importantly, expert CNICs could distinguish between what they know and do not know. Conclusions: Using an explanatory sequential mixed-methods approach, we developed a competency model for CNICs that may encourage CNICs to develop their expertise and that is useful in assessing the qualities or abilities of CNICs. In the future, this model can be used to develop systematic educational programs for CNICs.Funding: This study was supported by JSPS KAKENHI.Disclosures: None

scholarly journals Development and Early Feasibility of Chatbots for Educating Patients With Lung Cancer and Their Caregivers in Japan: Mixed Methods Study

JMIR Cancer ◽  
10.2196/26911 ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. e26911
Author(s):  
Yuki Kataoka ◽  
Tomoyasu Takemura ◽  
Munehiko Sasajima ◽  
Naoki Katoh
Keyword(s):  
Lung Cancer ◽  
Mixed Methods ◽  
Health Care Providers ◽  
Medical Information ◽  
Phase 1 ◽  
Test Phase ◽  
Mixed Methods Study ◽  
Phase 2 ◽  
Care Providers ◽  
Web Based

Background Chatbots are artificial intelligence–driven programs that interact with people. The applications of this technology include the collection and delivery of information, generation of and responding to inquiries, collection of end user feedback, and the delivery of personalized health and medical information to patients through cellphone- and web-based platforms. However, no chatbots have been developed for patients with lung cancer and their caregivers. Objective This study aimed to develop and evaluate the early feasibility of a chatbot designed to improve the knowledge of symptom management among patients with lung cancer in Japan and their caregivers. Methods We conducted a sequential mixed methods study that included a web-based anonymized questionnaire survey administered to physicians and paramedics from June to July 2019 (phase 1). Two physicians conducted a content analysis of the questionnaire to curate frequently asked questions (FAQs; phase 2). Based on these FAQs, we developed and integrated a chatbot into a social network service (phase 3). The physicians and paramedics involved in phase I then tested this chatbot (α test; phase 4). Thereafter, patients with lung cancer and their caregivers tested this chatbot (β test; phase 5). Results We obtained 246 questions from 15 health care providers in phase 1. We curated 91 FAQs and their corresponding responses in phase 2. In total, 11 patients and 1 caregiver participated in the β test in phase 5. The participants were asked 60 questions, 8 (13%) of which did not match the appropriate categories. After the β test, 7 (64%) participants responded to the postexperimental questionnaire. The mean satisfaction score was 2.7 (SD 0.5) points out of 5. Conclusions Medical staff providing care to patients with lung cancer can use the categories specified in this chatbot to educate patients on how they can manage their symptoms. Further studies are required to improve chatbots in terms of interaction with patients.

scholarly journals Challenges in multiple sclerosis care: Results from an international mixed-methods study

2021 ◽  
Vol 50 ◽  
pp. 102854
Author(s):  
Sophie Péloquin ◽  
Klaus Schmierer ◽  
Thomas P. Leist ◽  
Jiwon Oh ◽  
Suzanne Murray ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Mixed Methods ◽  
Mixed Methods Study

scholarly journals Nurses’ educational needs when dealing with aggression from patients and their families: a mixed-methods study

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e041711
Author(s):  
Kana Sato ◽  
Yoshimi Kodama
Keyword(s):  
Mixed Methods ◽  
Nursing Students ◽  
Phase I ◽  
Phase Ii ◽  
Mixed Methods Study ◽  
Self Awareness ◽  
Two Phase ◽  
Sequential Mixed Methods ◽  
Nursing Professionals ◽  
Educational Contents

ObjectivesTo explore the type of education needed for nurses when dealing with aggression from patients and their families.DesignA two-phase sequential mixed-methods study.SettingThis study was conducted in Japan, with phase I from March to November 2016 and phase II in November 2018.Main outcome measuresThe challenges faced by nurses when dealing with incidents of aggression from the neutral perspective of neither nurse nor patient/family and perceptions of the educational contents developed in this study. Descriptive analyses were used to examine the data retrieved from both phases.ParticipantsPhase I entailed semistructured interviews among 11 neutral-party participants who observed aggressive incidents between nurses and patients/families. Phase II consisted of a web survey conducted among 102 nursing students and 308 nursing professionals.ResultsPhase I resulted in the identification of the following five main educational components: understanding the mechanisms of anger and aggression, maintaining self-awareness, observant listening, managing the self-impression, and communicating based on specific disease characteristics. Each component was related to improved communication through self-awareness. The results of phase II indicated that participants positively perceived these educational contents as likely to be effective for dealing with aggression from patients/families.ConclusionsThis study clarified the type of education needed for nurses when dealing with aggression based on multiple viewpoints. Specifically, neutral-party interviews revealed that communication should be improved through self-awareness. A subsequent survey among nurses and nursing students showed that the identified educational contents were positively received.

How the environment is conceptualised and represented globally in social work codes of ethics

2021 ◽  
pp. 002087282110200
Author(s):  
Kang Liu ◽  
Catherine A Flynn
Keyword(s):  
Human Rights ◽  
Social Justice ◽  
Social Work ◽  
Mixed Methods ◽  
Physical Environment ◽  
Codes Of Ethics ◽  
Mixed Methods Study ◽  
Sequential Mixed Methods ◽  
The Social ◽  
Holistic Understanding

While the environment is fundamental to humankind’s wellbeing, to date, social work has been largely focused on the social, rather than the physical, environment. To map how the broader environment is captured in the profession’s foundational documents, an exploratory sequential mixed methods study (QUAL → quan) analysed data from 64 social work codes of ethics. Findings indicate that although the environment is mentioned in the majority of these, there is a continued focus on the social, overlooking to some degree the physical, predominantly the built, environment. A more holistic understanding of the environment would enable social work to better fulfil its commitment to human rights and social justice.

Sign in / Sign up

Export Citation Format

Share Document