Knowledge, Skills, and Experience With Technology in Relation to Nutritional Intake and Physical Activity Among Older Adults at Risk of Falls: Semistructured Interview Study.

BACKGROUND: More than one-third of older adults (aged ≥65 y) experience falls every year. The prevalent modifiable risk factors for falling are malnutrition and physical inactivity, among others. The involvement of older adults in the prevention of falls can decrease injuries, hospitalizations, and dependency on health care professionals. In this regard, eHealth can support older adults' self-management through more physical activity and adequate food intake. eHealth must be tailored to older adults' needs and preferences so that they can reap its full benefits. Therefore, it is necessary to gain insight into the knowledge, skills, and mindset of older adults living at home who are at risk of falls regarding eHealth. OBJECTIVE: This qualitative study aims to explore older adults' use of everyday digital services and technology and how they acquire knowledge about and manage their nutritional intake and physical activity in relation to their health. METHODS: Semistructured interviews were conducted with 15 older adults (n=9, 60% women; n=6, 40% men; age range 71-87 y) who had all experienced falls or were at risk of falling. These individuals were recruited from a geriatric outpatient clinic. The interviews were analyzed using deductive content analysis based on a modification of the Readiness and Enablement Index for Health Technology framework. RESULTS: The qualitative data showed that the informants' social networks had a positive impact on their self-management, use of technology, and mindset toward nutritional intake and physical activity. Although the informants generally lived active lives, they all lacked knowledge about how their food intake influenced their physical health, including their risk of falling. Another finding was the large diversity in the use of technology among the informants, which was related to their mindset toward technology. CONCLUSIONS: Older adults can use technology for everyday purposes, but some need additional introduction and support to be able to use it for managing their health. They also need to learn about the importance of proper nutritional intake and physical activity in preventing falls. Older adults need a more personalized introduction to technology, nutrition, and physical activity in their contact with health professionals.

An educative nutritional intervention supporting older hospital patients to eat sufficiently using eHealth: a mixed methods feasibility and pilot study.

BACKGROUND: Insufficient food intake is common in older hospital patients and increases the risk of readmission, mortality, and decline in functional status. To improve food intake in older patients, an eHealth solution (Food'n'Go) enabling them to participate in their own nutritional care was implemented in a hospital unit. We developed an educative nutritional intervention (ENI) to support hospitalized older adults (aged ≥ 65 years) to participate in their own nutritional care using Food'n'Go. In this study, we evaluate the feasibility of the ENI and its potential to improve nutritional intake. METHODS: Feasibility was evaluated using process evaluation, and nutritional intake was examined by using a pre- and post-test design. Assessment of feasibility: Contextual factors (availability of Food'n'Go and prevalence of counseling by a dietitian); Intervention fidelity (whether patients were informed of nutrition and Food'n'Go, and whether their needs for support were assessed); and Mechanism of impact (patients' knowledge and skills related to nutrition and the use of Food'n'Go and their acceptance of the ENI). Assessment of nutritional intake: Patients' intake of protein and energy based on one-day observations before implementation of the ENI (pre-test; n = 65) and after a three-month intervention (post-test; n = 65). RESULTS: Feasibility: Food'n'Go was available for more patients after the intervention (85 vs. 64%, p = .004). Most patients managed the use of Food'n'Go and were involved in ordering their food, but only a few monitored their food intake. Information on nutrition was not provided sufficiently to all patients. In general, the ENI had high acceptability among the patients. Nutritional intake: Compared to patients in the pre-test, patients in the post-test had a higher daily mean intake of energy (kJ) (6712 (SD: 2964) vs. 5660 (SD: 2432); difference 1052 (95% CI 111-1993)), and of protein (g) (60 (SD: 28) vs. 43 (SD: 19); difference 17 (95% CI 9-26)). Likewise, there was an increase in the mean attainment of protein requirements: 73% (SD: 34) vs. 59% (SD: 29) (p = .013). CONCLUSION: The ENI is feasible for supporting hospitalized older adults to participate in their own nutrition using eHealth and preliminary results indicate that it may lead to an increasing energy and protein intake.

Theory-driven development of an educative nutritional intervention (ENI) supporting older hospital patients to eat sufficiently, assisted by an eHealth solution: an intervention mapping approach.

BACKGROUND: Insufficient protein and energy intake is a prevalent and serious problem in older hospital patients. Here, we describe the development of a program consisting of 1) an educative nutritional intervention (ENI) to support older hospital patients to participate in their own nutritional care using the eHealth solution Food'n'Go, and 2) a plan for education and support of healthcare professionals, enabling them to conduct the ENI. Further, we describe the evaluation of the acceptability of the program as perceived by nursing staff and dieticians. METHODS: The Intervention Mapping (IM) framework was used to design and develop the ENI through six steps: 1) a logic model of the problem was developed; 2) performance objectives and related change objectives were defined for patients, relatives, and healthcare professionals; 3) the intervention was designed using relevant theory-based change methods; 4) program materials were produced; and finally, 5) implementation and maintenance were planned and 6) evaluation of the program was planned. End users (patients, relatives, and healthcare professionals) were involved in the design and development of the ENI. RESULTS: Based on the logic model, the personal determinants (knowledge, skills, self-efficacy, outcome expectation, social support, attitude, and awareness) related to the patients and their relatives were addressed in the ENI, and those related to the healthcare professionals were addressed in the plan for their education and support. Theories of behavioral change, technology acceptance, and nutritional management for older persons were applied. A plan for evaluation of the effectiveness (intake of energy and protein) and feasibility of the ENI was conducted. The feasibility measurements were the behaviors and determinants related to the intervention outcome that were identified in the logic model of change. The ENI was perceived as acceptable by the nursing staff and dieticians. CONCLUSION: We developed a theory- and evidence-based intervention guided by the IM framework and a sociotechnical approach, which was perceived as acceptable and ready for use to support older hospital patients to eat sufficiently assisted by eHealth.