Background: Functional decline is common in nursing home residents. Nursing staff can help prevent this decline, by encouraging residents to be more active in functional activities. Questionnaires measuring the extent to which nursing staff encourage functional activity among residents are lacking. In addition, there are no measurement instruments to gain insight into nursing staff perceived barriers and facilitators to this behavior. The aim of this study was to develop, and study the usability, of the MAastrIcht Nurses Activities INventory (MAINtAIN), an inventory assessing a) the extent to which nursing staff perceive to perform behaviors that optimize and maintain functional activity among nursing home residents and b) the perceived barriers and facilitators related to this behavior. Methods: Using a mixed-methods approach the MAINtAIN was developed and its usability was studied. Development was based on literature, expert opinions, focus group (N = 3) and individual interviews (N = 14) with residents and staff from nine nursing homes in the Netherlands. Usability was studied in a cross-sectional study with 37 nurses and certified nurse assistants; data were analyzed using descriptive statistics. Results: Development of the MAINtAIN resulted in two distinctive parts: MAINtAIN-behaviors and MAINtAIN-barriers. MAINtAIN-behaviors, targeting nursing staff behavior to optimize and maintain functional activity, includes 19 items covering activities of daily living, household activities, and miscellaneous activities. MAINtAIN-barriers addresses the perceived barriers and facilitators related to this behavior and comprises 33 items covering barriers and facilitators related to the residents, the professionals, the social context, and the organizational and economic context. The usability study showed that the inventory was not difficult to complete, that items and response options were clear,and that the number of missing values was low. Few items showed a floor or ceiling effect. Conclusions: The newly developed inventory MAINtAIN provides a usable method for researchers and nursing homes to obtain insight into nursing staff perceived behavior in optimizing functional activity among residents and their perceived barriers and facilitators related to this behavior. Outcomes of the MAINtAIN may contribute to change in nursing staff behavior and may improve nursing care. Further research with regard to the psychometric properties of the MAINtAIN is recommended.
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Objective:This study investigated whether visual function is associated with cognitive activity engagement and mild cognitive impairment in middle-aged and elderly individuals. Method:This cross-sectional study was conducted on 120 individuals aged 50–89. The Florida Cognitive Activity Scale (FCAS) was used to assess cognitive activity engagement. Visual function was assessed by near visual acuity(nVA) and contrast sensitivity (CS), and both combined to obtain a visual function (VF) compound score. Multi-variable linear regression models, adjusted for confounders, were used to assess the association between the determinants and FCAS. Results:After confounder adjustment, nVA was not associated with overall cognitive activity engagement. CS was significantly associated with the FCAS“Higher Cognitive Abilities”subscale score (BHC= 5.5 [95% CI 1.3; 9.7]).Adjustment for nVA attenuated the association between CS and engagement in tasks of Higher Cognitive Abilities(BHC= 4.7 [95% CI 0.1; 9.3]).In retired individuals(N= 87), theVF compound score was associated with a lower Cognitive Activity Scale score(BCA=−1.2 [95% CI−2.3;−0.1]), lower Higher Cognitive Abilities score(BHC=−0.7 [95% CI−1.3;−0.1])and lower Frequent Cognitive Abilities score (BFA=−0.5 [95% CI−0.9;−0.1]). Conclusion:CS, but not nVA, plays a role in engagement in tasks associated with Higher Cognitive Abilities in middle-aged and elderly individuals. In retired individuals, the VF compound score is associated with lower Cognitive Activity score, lower Higher Cognitive Abilities score and lower Frequent Cognitive Abilities score.
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Ambient activity monitoring systems produce large amounts of data, which can be used for health monitoring. The problem is that patterns in this data reflecting health status are not identified yet. In this paper the possibility is explored of predicting the functional health status (the motor score of AMPS = Assessment of Motor and Process Skills) of a person from data of binary ambient sensors. Data is collected of five independently living elderly people. Based on expert knowledge, features are extracted from the sensor data and several subsets are selected. We use standard linear regression and Gaussian processes for mapping the features to the functional status and predict the status of a test person using a leave-oneperson-out cross validation. The results show that Gaussian processes perform better than the linear regression model, and that both models perform better with the basic feature set than with location or transition based features. Some suggestions are provided for better feature extraction and selection for the purpose of health monitoring. These results indicate that automated functional health assessment is possible, but some challenges lie ahead. The most important challenge is eliciting expert knowledge and translating that into quantifiable features.
