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Home»Lifestyle»Development and usability of the “Cognitive Evergreenland” app to engage individuals at high risk of dementia in lifestyle interventions
Lifestyle

Development and usability of the “Cognitive Evergreenland” app to engage individuals at high risk of dementia in lifestyle interventions

March 17, 2025No Comments
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Setting

The Cognitive Evergreenland app was developed in this study, primarily to target patients at high risk of dementia, defined as older people (aged ≥ 60 years) who are experiencing SCD or MCI. These individuals have not yet progressed to the stage of dementia, according to the Jessen criteria (clinically normal on objective assessment, self/informant reported cognitive decline, and decline not better explained by a major medical, neurological, or psychiatric diagnosis).

Theoretical framework

First, factors influencing adherence to mobile lifestyle interventions for older adults at high risk of dementia, based on the Capability, Opportunity, and Motivation—Behaviour (COM-B) model within the BCW theory, were analyzed30. The COM-B model is a framework for understanding behavior, through analysis of COM as influences on behavior, as well as their potential interactions and resulting behaviors, and forms the core of the BCW. The Theoretical Domains Framework (TDF) was employed to identify drivers and barriers to behavioral change and diagnose behavioral issues, pinpointing key elements and proposing corresponding solutions31. These elements were then mapped to BCW intervention functions based on the relationship matrix between COM-B components and BCW intervention functions. Subsequently, intervention functions were selected according to the APEASE criteria (Affordability, Practicability, Effectiveness, Acceptability, Safety, and Equity)32. Then, appropriate behavior change techniques (BCTs) were filtered for correspondence with the Behavior Change Technique Taxonomy version 1 (BCTTv1) list33. Overall, this comprehensive approach integrated BCW and TDF theories, to provide a systematic and effective framework for understanding and addressing factors affecting adherence to lifestyle interventions for older adults at high risk of dementia. The development process is reported following the Guidance for Reporting Intervention Development Studies in Health Research checklist, consisting of 14-item quality criteria (Additional file 1)34.

Development process

The Cognitive Evergreenland development process referred to the BCW model and was subdivided into three main phases, each containing key sub-steps, to ensure that user needs were systematically understood and met. Detailed descriptions of each stage are provided below.

Stage I: Understanding the problem and user preferences

Step 1: define the problem in behavioral terms

The first step was to identify specific barriers to the implementation of lifestyle interventions for older adults at high risk of dementia. To achieve this, two researchers conducted a comprehensive literature review. The review focused on identifying who performs the behaviors and listing other factors that may influence problem behaviors. The researchers systematically searched eight databases for studies published in the past five years, using search terms such as “dementia OR cognitive decline OR cognitive impairment,” “facilitator OR motivat* OR benefit* OR barrier*,” and “lifestyle OR lifestyle intervention.” The findings were categorized using the COM-B model, which included physical and psychological capability, physical and social opportunity, and automatic and reflective motivation.

Steps 2 and 3: select and specify target behaviors

Data from evidence-based research was incorporated to identify target behaviors of older adults at high risk for dementia. Once a target behavior was selected, specific elements of the selected target behavior were further clarified; for example, who needs to do this, what they need to do differently to elicit change, and when and where it needs to happen, as well as how often and with whom. These specifications were discussed and finalized during a series of research group meetings, where consensus was reached on the final target behaviors. The meetings involved in-depth discussions on the feasibility, relevance, and potential impact of the selected behaviors, ensuring alignment with the needs of the target population and the goals of the intervention.

Step 4: identify what needs to change

Based on a review of the literature, focus group interviews with older people at high risk for dementia, who were interested in participating in a multidomain lifestyle intervention, were organized, with the aim of collecting information about potential barriers and facilitators to adherence to the intervention (Additional file 2). Focus groups concentrated on 14 known barriers to adherence to multidomain lifestyle interventions among older adults at high risk for dementia, mapped on the COM-B model generated in step 1; each session lasted approximately 1 h. At the end of each focus group, one of the researchers provided a summary of the discussion and an opportunity to clarify or add any missing points, and the content of each focus group was recorded in detail.

Stage II: identification of intervention options and policy recommendations

Steps 5 and 6: identify intervention functions and policy categories

Intervention functions most likely to influence primary behavior change were preliminarily identified through a comprehensive review of the findings of COM-B and TDF behavior analysis. To further refine and validate these findings, focus group discussions were conducted. The APEASE criteria were used to guide selection of the relevant intervention functions; these criteria are: (1) Affordability, (2) Practicability, (3) Effectiveness and cost-effectiveness, (4) Acceptability, (5) Side effects/safety, and (6) Equity. Additionally, specific policy categories supporting each intervention function were identified; these were determined using the policy categories provided in the BCW guide (such as marketing, guidelines, service provision, etc.). These policy categories help to support the execution and promotion of an application, ensuring its successful implementation and maximizing its impact on the target user group.

Stage III: Identification of application function modules and usability evaluation

Step 7: selection of BCTs

The BCTTv1, proposed by Michie et al.33, describes how each BCT is associated with various intervention functions. Focus group discussions, providing valuable insights based on their diverse backgrounds and expertise in the field, were used to select the most effective and feasible techniques from the potential list of BCTs, based on the APEASE criteria, to guide dementia-prone older adults in adhering to long-term lifestyle interventions. The focus group discussions were structured such that participants were divided into four groups, with each group responsible for in-depth exploration of one or more intervention functions and their corresponding BCTs. Each group presented their findings and received feedback from both peer groups and the moderator. Following the initial broad categorization of intervention content, we conducted detailed analyses to determine the precise BCTs to be employed.

Step 8: determining the mode of delivery

After selection of BCTs, the next step involved integrating these techniques into the functionalities of the Cognitive Evergreenland app. This process entailed collaboration with mobile app design and development companies, to determine the specific mode of delivery most suitable for Cognitive Evergreenland, such as a mobile app, WeChat Mini Program, or web-based online support, to ensure that users can easily access and use the app.

Step 9: assessment and refinement of app usability

Once the mode of delivery was selected, two rounds of pilot testing were conducted to assess the app’s usability. Through purposive sampling, older adult participants with SCD and MCI were recruited from the Geriatric Medicine Centre in Fujian Province, China, to pilot the application.

The pilot process included online or face-to-face interviews, using the Usability Evaluation Opinions Collection Form (Additional file 3) to assess the completion rate of application users independently or with assistance, and continuously collecting user feedback and modification suggestions until data saturation was achieved, indicated by no new themes or suggestions emerging from the interviews. Based on the feedback received, the application was revised and optimized. After optimization, a second round of pilot testing was conducted with a new group of older adults with SCD and MCI, who were asked to complete the Mobile Health App Usability Questionnaire for Standalone mHealth Apps—Patient Version (MAUQ-SP) to assess usability35. The MAUQ-SP questionnaire comprises three dimensions: usability, interface and satisfaction, and effectiveness, with a total of 18 items. Each item is rated on a scale from “strongly disagree” to “strongly agree” with scores ranging from 1 to 7. The scores of all items are summed and averaged to obtain a total score, with higher scores indicating better usability. Our previous research validated the Chinese version of this questionnaire, showing a Cronbach’s α coefficient of 0.979, a split-half reliability of 0.919, and a test–retest reliability of 0.974, demonstrating good reliability and validity36.

Ethics and consent

This study obtained approval from the Ethics Committee of Fujian Provincial Hospital (K2021-03-029) and was carried out in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants, ensuring that they were informed in advance about the potential benefits and risks of participating in the research. Participants were confident in the confidentiality and anonymity of their information.

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