The aim of this study was to compare the predictive values of three short postal screening instruments for identifying community dwelling frail older persons: the Groningen Frailty Indicator (GFI), the Tilburg Frailty Indicator (TFI) and the Sherbrooke Postal Questionnaire (SPQ).
The associated AUC values, between 0.54 and 0.67, indicate poor performance regarding prediction of any of the dependent variables (development of disability, mortality, and hospital admission). Despite high prevalences of frailty (between 40 and 60%), the positive predicted values of the tools are low. The adjusted odds ratios show that those identified as frail have more than twice the risk (GFI, 2.62; TFI, 2.00; SPQ, 2,49) for developing disabilities within 1 year compared to the non-frail group; those identified as frail by the TFI and SPQ have more than twice the risk of being admitted to a hospital.
This is the first time that these three instruments are compared in one study for their predictive values. The postal procedure proved to be feasible with high response rates. A limitation of our study can be that, by dichotomizing development of disabilities, we might have missed more subtle changes in performance of activities. However, from a clinical perspective, a change from independent to dependent seems more important. Previous studies into frailty used a similar approach for the development of disabilities [18, 19]. One could argue that the follow-up period of 1 year is too short to monitor relevant adverse outcomes. However, in our study 24% of older persons did develop disabilities over a one-year period, and from a GP perspective, 1 year seems a reasonable timeframe for pro-active elderly care. The study may have been biased due to treatments that participants received (or did not receive) during the follow-up period influencing changes in disability. However, general practitioners were unaware of the frailty state of their patients and if care was received then this is the case for both frail and non frail respondents.
It is likely that cognitive impairments in the target population have affected the validity of the self reported data. Persons with severe impairments may have been part of the non-responders, thereby influencing the underestimation of frailty prevalences. Further, responders with cognitive impairments may have provided non-reliable information in returned questionnaires. No data are available though about the cognitive impairments among the target population. Based on the high response and the minor changes in disability in the population over a 1 year period, we assume that the influence of (severe) cognitive impairments on the validity of the data is small.
Finally, the SPQ was not used according to protocol , as non-responders were excluded from analyses. If we had considered non-responders also at risk, this would have resulted at T1 in a frailty prevalence estimate of 67.0% instead of 59.1%.
The prevalence estimates of 40% to 60% found in the present study are high compared to other studies [19, 20]. It is important to realize that prevalence estimates strongly depend on the interpretation of the concept of frailty and the approach that is chosen to measure it. The instruments chosen for this study are based on a multifactorial approach to frailty; lower prevalence estimates are found for instruments based on the definition of physical frailty. Interesting is that frailty scores did not change dramatically over a one-year time period. There are several possible explanations. There may have been a balance in the number of older persons with new incidents of frailty and those who were frail and passed away. Further, we have to consider that frailty is a dynamic process including transitions from frail to non-frail. On the other hand, the frailty instruments may not be sensitive enough to detect small changes in frailty status.
Our diagnostic values of the SPQ for development of disabilities are comparable with those Hébert et al.  found among elderly persons over 74 (sensitivity 75% and specificity 52%). Gobbens et al.  presented for the TFI a sensitivity of 84% and specificity of 76% for identifying frail elderly at risk for disability. However, this was based on a cross-sectional study design. As mentioned earlier, the adjusted odds ratios show that those identified as frail by the GFI, TFI, and SPQ have, more than twice the risk for developing disabilities within 1 year. Sarkisian et al.  found in a cohort study that elders identified as frail with the CHS frailty index, as proposed by Fried et al. , had a age-adjusted odds ratio of 4.4 for disability over a 4 year period. Ensrud et al.  found, in a prospective cohort study for women (≥69) identified frail with the CHS frailty index, a higher age adjusted risk (OR 2.2-2.8) for disability (≥1 new IADL disability) over a period of 4 and a half years. Differences in estimated risks between those and our study may be attributed for a large part to variation in follow-up periods.
There is a public health need for effective interventions targeting community-dwelling frail elderly promoting their independent functioning in daily life . Prevention of disability in frail older persons contributes to the maintenance of quality of life and reduced health care costs . Supporting primary care to address the needs and health risks of frail elderly is a strategy to control costs as it is expected to prevent institutional care and promote consistency and coordination of individual care . A multifactorial and multidisciplinary approach towards disability prevention in community dwelling frail elderly seems promising [25, 26]. For an example of an innovative primary care intervention we refer to a description of our disability-prevention programme . Effective screening is a crucial first step in these programmes to select the appropriate target group. Postal screening questionnaires such as the GFI, TFI and SPQ do have potential to identify older persons at risk.
Our previous study  showed that extensive assessment after screening is necessary, as the scalability of the instruments is poor. The current study shows that the predictive power of the instruments is not sufficient yet. The high prevalence of frailty may point to the possibility that a substantial proportion of these elderly is pre-frail. In a two-step approach towards screening, the sensitivity will be the most relevant criterion. In that perspective, the SPQ scores best, followed by the GFI. The SPQ has the highest sensitivity (83%) for development of disabilities; though with a specificity of 48%, a large proportion of older persons that do not develop disabilities are identified. A number of 18 out of 103 elderly who developed disabilities were not identified as frail and thus will not receive an additional assessment. General practitioners who wish to start pro-active elderly care could consider the use of a short postal screening tool in combination with strategies to reduce the number of false positives and false negatives. The additional use of clinical judgment with an instrument as the Clinical Frailty Scale  after the preliminary screening might be an option to reduce false positives. This judgment could be based on a recent consultation or a new appointment in which the GP focuses on recent transitions in functioning. Still, more research is necessary to optimize screening in community-dwelling frail elderly.