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- 01GMTFN6Q9ZPKDQD4AEYDM83VM classification A1.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM date "2022".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM language "eng".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM type journalArticle.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM hasPart 01GMTFS5XFPVMPYPS06XWPDTSV.pdf.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM subject "Medicine and Health Sciences".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM doi "10.1186/s12889-022-14455-4".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM issn "1471-2458".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM issue "1".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM volume "22".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM abstract "Background: Despite effectiveness of action and coping planning in digital health interventions to promote physical activity (PA), attrition rates remain high. Indeed, support to make plans is often abstract and similar for each individual. Nevertheless, people are different, and context varies. Tailored support at the content level, involving suggestions of specific plans that are personalized to the individual, may reduce attrition and improve outcomes in digital health interventions. The aim of this study was to investigate whether user information relates toward specific action and coping plans using a clustering method. In doing so, we demonstrate how knowledge can be acquired in order to develop a knowledge-base, which might provide personalized suggestions in a later phase. Methods: To establish proof-of-concept for this approach, data of 65 healthy adults, including 222 action plans and 204 coping plans, were used and were collected as part of the digital health intervention MyPlan 2.0 to promote PA. As a first step, clusters of action plans, clusters of coping plans and clusters of combinations of action plans and barriers of coping plans were identified using hierarchical clustering. As a second step, relations with user information (i.e. gender, motivational stage, ...) were examined using anova's and chi(2)-tests. Results: First, three clusters of action plans, eight clusters of coping plans and eight clusters of the combination of action and coping plans were identified. Second, relating these clusters to user information was possible for action plans: 1) Users with a higher BMI related more to outdoor leisure activities (F = 13.40, P < .001), 2) Women, users that didn't perform PA regularly yet, or users with a job related more to household activities (X-2 = 16.92, P < .001; X-2 = 20.34, P < .001; X-2 = 10.79, P = .004; respectively), 3) Younger users related more to active transport and different sports activities (F = 14.40, P < .001). However, relating clusters to user information proved difficult for the coping plans and combination of action and coping plans. Conclusions: The approach used in this study might be a feasible approach to acquire input for a knowledge-base, however more data (i.e. contextual and dynamic user information) from possible end users should be acquired in future research. This might result in a first type of context-aware personalized suggestions on the content level.".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM author 09AED7E4-F0EE-11E1-A9DE-61C894A0A6B4.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM author 2BF85A14-F0EE-11E1-A9DE-61C894A0A6B4.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM author 3A51043A-F0EE-11E1-A9DE-61C894A0A6B4.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM author F56D04D6-F0ED-11E1-A9DE-61C894A0A6B4.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM author F86BC8CA-F0ED-11E1-A9DE-61C894A0A6B4.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM dateCreated "2022-12-21T13:58:37Z".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM dateModified "2024-10-29T18:56:06Z".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM name "Towards more personalized digital health interventions : a clustering method of action and coping plans to promote physical activity".
- 01GMTFN6Q9ZPKDQD4AEYDM83VM pagination urn:uuid:79156b50-bcbc-4cdf-b060-1424f48b9c1f.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM publisher urn:uuid:f299f8c5-3523-42f9-8688-138182e63ec8.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM sameAs LU-01GMTFN6Q9ZPKDQD4AEYDM83VM.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM sourceOrganization urn:uuid:14384a89-bf4a-4641-847a-8c06c865db88.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM sourceOrganization urn:uuid:4a5ac31e-c795-48f1-a210-a8108d02c94e.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM sourceOrganization urn:uuid:8f8139f7-7a54-4d17-8b2b-0c50de1d1ede.
- 01GMTFN6Q9ZPKDQD4AEYDM83VM type A1.