Objective: The Tilburg Frailty Instrument (TFI) is an instrument for assessing frailty in community-dwelling older people. Since its development, many studies have been carried out examining the psychometric properties. The aim of this study was to provide a review of the main findings with regard to the reliability and validity of the TFI. Methods: We conducted a literature search in the PubMed and CINAHL databases on May 30, 2020. An inclusion criterion was the use of the entire TFI, part B, referring to the 15 components. No restrictions were placed on language or year of publication. Results: In total, 27 studies reported about the psychometric properties of the TFI. By far, most of the studies (n = 25) were focused on community-dwelling older people. Many studies showed that the internal consistency and test–retest reliability are good, which also applies for the criterion and construct validity. In many studies, adverse outcomes of interest were disability, increased health-care utilization, lower quality of life, and mortality. Regarding disability, studies predominantly show results that are excellent, with an area under the curve (AUC) >0.80. In addition, the TFI showed good associations with lower quality of life and the findings concerning mortality were at least acceptable. However, the association of the TFI with some indicators of health-care utilization can be indicated as poor (eg, visits to a general practitioner, hospitalization). Conclusion: Since population aging is occurring all over the world, it is important that the TFI is available and well known that it is a user-friendly instrument for assessing frailty and its psychometric properties being qualified as good. The findings of this assessment can support health-care professionals in selecting interventions to reduce frailty and delay its adverse outcomes, such as disability and lower quality of life.
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Objective: To predict mortality with the Tilburg Frailty Indicator (TFI) in a sample of community-dwelling older people, using a follow-up of 7 years. Setting and Participants: 479 Dutch community-dwelling people aged 75 years or older. Measurements: The TFI, a self-report questionnaire, was used to collect data about total, physical, psychological, and social frailty. The municipality of Roosendaal (a town in the Netherlands) provided the mortality dates. Conclusions and Implications: This study has shown the predictive validity of the TFI for mortality in community-dwelling older people. Our study demonstrated that physical and psychological frailty predicted mortality. Of the individual TFI components, difficulty in walking consistently predicted mortality. For identifying frailty, using the integral instrument is recommended because total, physical, psychological, and social frailty and its components have proven their value in predicting adverse outcomes of frailty, for example, increase in health care use and a lower quality of life.
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Abstract: Due to rapidly aging human populations, frailty has become an essential concept, as it identifies older people who have higher risk of adverse outcomes, such as disability, institutionalization, lower quality of life, and premature death. The Tilburg Frailty Indicator (TFI) is a user-friendly questionnaire based on a multidimensional approach to frailty, assessing physical, psychologic, and social aspects of human functioning. This review aims to explore the efficiency of the TFI in assessing frailty as a means to carry out research into the antecedents and consequences of frailty, and its use both in daily practice and for future intervention studies. Using a multidimensional approach to frailty, in contexts where health care professionals or researchers may have no time to interview or examine the client, we recommend employing the TFI because there is robust evidence of its reliability and validity and it is easy and quick to administer. More studies are needed to establish whether the TFI is suitable for intervention studies not only in the community, but also for specific groups such as patients in the hospital or admitted to an emergency department. We conclude that it is important to not only determine the deficits that frail older people may have, but also to assess their balancing strengths and resources. In order to be able to meet the individual needs of frail older persons, traditional and often fragmented elderly care should be developed toward a more proactive elderly care, in which frail older persons and their informal network are in charge.
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Objective: The Tilburg Frailty Indicator (TFI) is a self-report user-friendly questionnaire for assessing multidimensional frailty among community-dwelling older people. The main aim of this study is to re-evaluate the validity of the TFI, both cross-sectionally and longitudinally, focusing on the predictive value of the total TFI and its physical, psychological, and social domains for adverse outcomes disability, indicators of healthcare utilization, and falls. Methods: The validity of the TFI was determined in a sample of 180 Dutch communitydwelling older people aged 70 years and older. The participants completed questionnaires including the TFI, the Groningen Activity Restriction Scale (GARS) for assessing disability, and questions with regard to health care utilization and falls in 2016 and again one year later. Results: The physical and psychological domains of the TFI were significantly correlated as expected with adverse outcomes disability, many indicators of healthcare utilization, and falls. Regression analyses showed that physical frailty was mostly responsible for the effect of frailty on the adverse outcomes. The cross-sectional and longitudinal predictive validity of total frailty with respect to disability and receiving personal care was excellent, evidenced by Areas Under the Curves (AUCs) >0.8. In most cases, using the cut-off point 5 for total frailty ensured the best values for sensitivity and specificity. Conclusion: The present study provided new, additional evidence for the validity of the TFI for assessing frailty in Dutch community-dwelling older people aiming to prevent or delay adverse outcomes, including disability.
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Abstract: Disability is associated with lower quality of life and premature death in older people. Therefore, prevention and intervention targeting older people living with a disability is important. Frailty can be considered a major predictor of disability. In this study, we aimed to develop nomograms with items of the Tilburg Frailty Indicator (TFI) as predictors by using cross-sectional and longitudinal data (follow-up of five and nine years), focusing on the prediction of total disability, disability in activities of daily living (ADL), and disability in instrumental activities of daily living (IADL). At baseline, 479 Dutch community-dwelling people aged 75 years participated. They completed a questionnaire that included the TFI and the Groningen Activity Restriction Scale to assess the three disability variables. We showed that the TFI items scored different points, especially over time. Therefore, not every item was equally important in predicting disability. ‘Difficulty in walking’ and ‘unexplained weight loss’ appeared to be important predictors of disability. Healthcare professionals need to focus on these two items to prevent disability. We also conclude that the points given to frailty items differed between total, ADL, and IADL disability and also differed regarding years of follow-up. Creating one monogram that does justice to this seems impossible.
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Purpose: To examine the development of multidimensional frailty, including physical, psychological and socialcomponents, over a period of seven years. To determine the effects of sociodemographic factors (gender, age, marital status, education, income) on the development of frailty. Methods: : This longitudinal study was conducted in sample of 479 community-dwelling people aged ≥ 75 years living in the municipality of Roosendaal, the Netherlands. The Tilburg Frailty Indicator (TFI), a self-report questionnaire, was used to collect data about frailty. Frailty was assessed annually. Results: : Frailty increased significantly over seven years among the people who completed the entire TFI all years (n = 121), the average score was 3.75 (SD 2.80) at baseline and 5.05 (SD 3.18) after seven years. Regarding frailty transitions, most participants remained unchanged from their baseline status. The transition from non-frail to frail was present in 8.3% to 12.6% of the participants and 5.1% to 10.7% made a transition from frail to nonfrail. Gender (woman), age (≥80 years), marital status (not married/cohabiting), high level of education, and incomes from €601-€1800 were significantly associated with a higher frailty score. Conclusion: : This study showed that multidimensional frailty, assessed with the TFI, increased among Dutch community-dwelling people aged ≥75 years using a follow-up of seven years. Gender, age, marital status, education, and income were associated with frailty transitions. These findings provide healthcare professionals clues to identify people at increased risk of frailty, and target interventions which aim to prevent or delay frailty and its adverse outcomes, such as disability and mortality.
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Wil je in een gezonde omgeving leven? Kies dan niet Tilburg als je thuis. In de lijst van gezonde steden van Nederland bungelt Tilburg ergens onderaan. Eindhoven doet het niet veel beter. Waar ligt dat aan? Pauline van den Berg, onderzoeker bij het lectoraat De Ondernemende Regio, schijnt haar licht op dit onderwerp.
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Abstract Purpose: This study aimed to establish which determinants had an effect on frailty among acutely admitted patients, where frailty was identified at discharge. In particular, our study focused on associations of sex with frailty. Methods: A cross-sectional study was designed using a sample of 1267 people aged 65 years or older. The Tilburg Frailty Indicator (TFI), a user-friendly self-report questionnaire was used to measure multidimensional frailty (physical, psychological, social) and determinants of frailty (sex, age, marital status, education, income, lifestyle, life events, multimorbidity). Results: The mean age of the participants was 76.8 years (SD 7.5; range 65-100). The bivariate regression analyses showed that all determinants were associated with total and physical frailty, and six determinants were associated with psychological and social frailty. Using multiple linear regression analyses, the explained variances differed from 3.5% (psychological frailty) to 20.1% (social frailty), with p values < 0.001. Of the independent variables age, income, lifestyle, life events, and multimorbidity were associated with three frailty variables, after controlling for all the other variables in the model. At the level of both frailty domains and components, females appeared to be more frail than men. Conclusion: The present study showed that sociodemographic characteristics (sex, age, marital status, education, income), lifestyle, life events, and multimorbidity had a different effect on total frailty and its domains (physical, psychological, social) in a sample of acute admitted patients.
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International comparative analysis of former textile cities and their 'comeback strategies'. In this chapter results are showed from the design workshop by students from the Tilburg Academy of Architecture and Urbanism
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Background: Modern modeling techniques may potentially provide more accurate predictions of dichotomous outcomes than classical techniques. Objective: In this study, we aimed to examine the predictive performance of eight modeling techniques to predict mortality by frailty. Methods: We performed a longitudinal study with a 7-year follow-up. The sample consisted of 479 Dutch community-dwelling people, aged 75 years and older. Frailty was assessed with the Tilburg Frailty Indicator (TFI), a self-report questionnaire. This questionnaire consists of eight physical, four psychological, and three social frailty components. The municipality of Roosendaal, a city in the Netherlands, provided the mortality dates. We compared modeling techniques, such as support vector machine (SVM), neural network (NN), random forest, and least absolute shrinkage and selection operator, as well as classical techniques, such as logistic regression, two Bayesian networks, and recursive partitioning (RP). The area under the receiver operating characteristic curve (AUROC) indicated the performance of the models. The models were validated using bootstrapping. Results: We found that the NN model had the best validated performance (AUROC=0.812), followed by the SVM model (AUROC=0.705). The other models had validated AUROC values below 0.700. The RP model had the lowest validated AUROC (0.605). The NN model had the highest optimism (0.156). The predictor variable “difficulty in walking” was important for all models. Conclusions: Because of the high optimism of the NN model, we prefer the SVM model for predicting mortality among community-dwelling older people using the TFI, with the addition of “gender” and “age” variables. External validation is a necessary step before applying the prediction models in a new setting.
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