hia630 wk3 discussion1 sorelle
docx
keyboard_arrow_up
School
Ashford University *
*We aren’t endorsed by this school
Course
630
Subject
Health Science
Date
Nov 24, 2024
Type
docx
Pages
2
Uploaded by mewood2305
part 1
Measurements are classified in a series of levels according to the nature and
amount of information they capture.
Nominal-level measurement distinguishes between observations in terms of
kind or quality and does not indicate the quantity of a variable. A nominal
measurement strategy is a dichotomous classification according to whether a
particular characteristic is present or not. Examples of nominal measurement
are marital status, race/ethnicity, and birthplace.
Ordinal-level measurements distinguish between observations in terms of
relative amounts, such as whether one observation contains more, less, or
about the same quantity as another. Observations are placed in hierarchical
order. One Ordinal-level measurement strategy is a direct comparison. For
example, rating your job satisfaction on a scale from 1 to 10, with 10
representing complete satisfaction.
In interval-level measurement, numbers form a continuum and provide
information about the amount of difference, but the scale lacks a true zero.
The differences between adjacent numbers are equal or unknown. The
Fahrenheit and Celsius temperature scales are examples of internal
measurements. In those scales, 0-degree Fahrenheit or 0 degrees Celcius do
not indicate an absence of temperature
ratio scales has all the characteristics of interval scales as well as a true
zero, which refers to the complete absence of the characteristic being
measured. Physical characteristics of persons and objects can be measured
with a ratio scale; thus, height and weight are examples of ratio
measurement. A score of zero means there is complete absence of height or
weight.
Measurement reliability is the extent to which a measurement is free of
random error and thus obtains consistent outcomes when the true value is
constant. Measurement validity is the extent to which a measurement
accurately measures the construct it is intended to measure. A valid
measurement is free of both random and systematic error. Reliability and
validity are essential in research because they ensure that data are sound
and replicable and the results are accurate. Reliability is a necessary but not
sufficient condition for validity, and a valid measurement also is reliable.
part 2
the article by (Schneider et al., 2019) presents a study where adolescents
with asthma were introduced to a mobile health app called the asthma self-
management app to help self-manage their symptoms and better
communicate with their care team to keep their asthma under control.
Twenty adolescents participated in the study to see how well they could use
the app daily to enter their asthma symptoms and peak-flow values so that
the app could determine their asthma status and recommend action plans. In
case of extreme symptoms, the provider will be notified immediately by the
app, and they will have to contact the patient directly for assistance. The
study aims to find a better way to manage asthma.
In this study, the independent variable is the adolescent with asthma, and
the dependent variable is asthma self-management, which depends on how
well the participants use the app. This study presents an ordinal
measurement where the author rates the participants' satisfaction with using
the asthma self-management app. Overall, the study was reliable and valid
because the participants' feedback about using the app was primarily
positive. The app was able to increase awareness and medication adherence
and improved the asthma status of participants. Overall, participants felt that
their asthma symptoms or how they self-manage their asthma improved
since they began using the app(Schneider et al., 2019).
Schneider, T., Baum, L., Amy, A., & Marisa, C. (2019). I have most of my
asthma under control, and I know how my asthma acts: Users' perceptions of
asthma self-management mobile app tailored for adolescents.
Health
Informatics Journal
. https://doi.org/10.1177/1460458218824734
Kviz, F. J. (2020).
Conducting health research: Principles, process, and
methods
. SAGE.
Reply
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help