Thinking Ahead—Outcome Measures
Thinking Ahead—Outcome Measures
| Variable of Interest | Data Needed | Frequency of Data Collection | Methods of Data Collection | Who Will Collect the Data | Analysis |
| Gait | The patient’s ability to walk without assistance | Once a week | Questionnaire | Nurse | The patient can walk on their own without assistance. |
| Stability | patients’ ability to stand without falling | Once a week | Questionnaire | Nurse | The patient can stand without falling. |
| Environment | Accessibility of the living quarters.
Are there railings on the stairs and entryway? Are there loose mats that could cause falls? Lighting. |
Once a month | Home visits. Data will be collected through interviews and digital recordings such as videos and pictures. | Health worker/social worker | The home has various risks of falls, such as loose mats and poor lighting |
| Adherence to intervention Plan | Has the patient been exercising as advised by the clinician? How often? | Once a week | Questionnaires | Family or caregiver | The patient is adhering to the weekly jogging and swimming plans. |
| Recent Falls | Has the patient fallen recently? If yes, how many times? | Once a month | Questionnaires | Family or caregiver | The patient has had fewer falls since the implementation of the intervention. |
Narrative
As part of conducting a research project, statistical techniques are used to organize, develop, gather data, analyze, make relevant conclusions, and report the results. A study of statistics provides a framework for understanding the useless facts. Only if the right statistical tests are employed can the findings and conclusions be considered accurate. A researcher needs to understand the fundamental ideas of the statistical procedures used in conducting a study. Well-designed research will provide reliable and valid data if followed. Inappropriate use of statistical tools may lead to inaccurate findings, resulting in inaccuracies and diminishing the article’s importance. Poor statistics may lead to shoddy research, which may lead to unethical actions. A thorough understanding of statistics and the skilful use of statistical tests is thus essential.
The statistics for this project can be manipulated by increasing the sample size of the stud. We can assume that the study was conducted among 20 individuals, 10 of whom took part in the exercise intervention and ten who did not participate in the exercise plan. A research’s sample size must be calculated at the time the study is suggested; a sample that is both excessive and unscientific, on the other hand, is also unethical. It is possible to determine the appropriate sample size using statistical software depending on specific assumptions. An arbitrary sample size can be used for pilot research if no assumptions can be made (Andrade, 2020). Due to the variability in patient characteristics, nonspecific treatment factors, rating techniques, and settings. You may calculate sample sizes manually or using statistical tools; internet calculators that provide free service are readily recognizable by search engines.
To motivate my team to collect the data, I will educate them on patient data in treatment. When the unit is aware of the importance of data collection, they will be encouraged to take part in the patient intervention program. I will also encourage the family or caregivers to collect the data by providing them with materials they need for data collection. I will also make it easier for the team to share the data through electronic means such as emails to avoid asking the family to commute to the clinic to bring in the questionnaires.
References
Andrade, C. (2020). Sample size and its importance in research. Indian Journal of Psychological Medicine, 42(1), 102-103. https://doi.org/10.4103/ijpsym.ijpsym_504_19