This project is going to use the STEADI tool kit as a primary tool for preventing cases of falls in geriatric patients, aged 65+ years old. The tool kit consists of three core elements:
- screening;
- assessing;
- intervening.
On the screening stage, a healthcare practitioner is provided with algorithms for fall risk screening, assessments, and interventions, brochures on fall facts, guidelines on patient encounters (Johnston et al., 2018).
In the assessment stage, a doctor uses checklists and forms for assessing modifiable risk factors and medication management (Phelan, Mahoney, Voit, & Stevens, 2015). In the intervention stage, a clinician reduces the risks of falls by using community strategies and distributing caregiver education materials (Phelan et al., 2015). The project will adapt the aforementioned strategies and adjust them to ensure independent uniform reporting.
As presented in Table 1, geriatric patients will be required to answer a close-ended three-item questionnaire, adapted from the Centers for Disease Control and Prevention (2020), with a simple yes/no. The questionnaire will be scored as follows: 1 point will be given for every “Yes” answer and 0 points will be given for every “No” answer.
Table 1. Screening Questionnaire for Fall Prevention.
Note. Adapted from “Materials for healthcare providers” by Centers for Disease Control and Prevention, 2020. Copyright 2020 by Centers for Disease Control and Prevention.
If the respondent gives affirmative answer to one or more of these questions, the healthcare practitioner will distribute an additional tool (electronic or handwritten for their convenience) for a patient to use for further recording of symptoms. Using this tool, an elderly individual will be asked to provide the following information every month:
- frequency of falls in the past month;
- injuries, if any, acquired after falling;
- concerns, if any, about falling in the future.
Appropriate ways of responding would be brief comments and “N/A” in case the question does not apply to the respondent. The collected data will be used in the regular appointments with GP to facilitate future fall prevention strategies. Total scores of 2 and more will be given more close attention with possible intervention programs advised. Two levels of measurements are adapted used for this instrument: ordinal and interval. The first questionnaire adapts an ordinal level of measurement, assessing low/high risk of falls, while the tool with open-ended comments utilizes interval level, accounting for fixed data values, expressed through frequencies of falling.
The STEADI tool kit uses face validity, predictive validity, and inter-rater reliability as instrument measurements. As supported by Lohman et al. (2017), the empirical evidence of the tool suggests that the STEADI tool accurately predicts target high-risk individuals, which signifies its predictive validity. The face validity of the method is explained through the straightforward criterion-related questions that test what the instrument aims to test.
Face validity and predictive validity are strikingly different from external and internal validity. According to Casey et al. (2017), internal validity tests to which extent a specific piece of evidence supports a cause-effect relationship within a particular study. In contrast, external validity accounts for the universality of the results (Casey et al., 2017). Though closely associated with predictive validity, there is no sufficient academic research to ensure external validity for the newly introduced electronic or handwritten tool for this project. The same reasoning relates to the internal validity, as the main goal of the study does not lay in the establishment of a cause-effect relationship for the lack of empirical research on the subject matter.
Apart from the aforementioned types of validity, the instrument uses inter-rater reliability. As explained by Aliakbari, Parvin, Heidari, & Haghani (2015), the inter-rater reliability of the STEADI tool kit is demonstrated in a similar way geriatric patients interpret the questions. Consistent interpretation of questions by respondents adds up to the external reliability of the tool with a possibility to replicate the results of the future study.
References
Aliakbari, F., Parvin, N., Heidari, M., & Haghani, F. (2015). Learning theories application in nursing education. Journal of Education and Health Promotion, 4, 3-11. Web.
Casey, C., Parker, E., Winkler, G., Liu, X., Lambert, G., & Eckstrom, E. (2017). Lessons learned from implementing CDC’s STEADI falls prevention algorithm in primary care. The Gerontologist, 57(4), 787–796. Web.
Centers for Disease Control and Prevention. (2020). Materials for healthcare providers. Web.
Johnston, Y. A., Bergen, G., Bauer, M., Parker, E. M., Wentworth, L., McFadden, M.,… Garnett, M. (2018). Implementation of the stopping elderly accidents, deaths, and injuries initiative in primary care: An outcome evaluation. The Gerontologist, XX(XX), 1-10. Web.
Lohman, M., Crow, R., DiMilia, P., Nicklett, E., Bruce, M., & Batsis, J. (2017). Operationalisation and validation of the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) fall risk algorithm in a nationally representative sample. Journal of Epidemiology and Community Health, 71(12), 1191–1197. Web.
Phelan, E., Mahoney, J., Voit, J., & Stevens, J. (2015). Assessment and management of fall risk in primary care settings. Medical Clinics of North America, 99(2), 281-293. Web.