Mobility Research Critique Amy Bradley, Karilyn …amybradleyrntobsn.weebly.com/uploads/8/9/8/2/8982971/mobility... · Mobility Research Critique Amy Bradley, Karilyn Bufka and Jessica

Running head: MOBILITY RESEARCH CRITIQUE 1

Mobility Research Critique

Amy Bradley, Karilyn Bufka and Jessica Riley

Ferris State University

MOBILITY RESEARCH CRITIQUE 2

Abstract

Reduction of risks to improve patient safety has been a nursing topic well studied for several

years. This paper summarizes and critiques a primary research article regarding a mobility

protocols effect on patient outcomes. An analysis of the data was determined through research

critique guidelines provided by Nieswiadomy (2012). The ability to critique a research article is

an important aspect of nursing that ensures the data accumulated from the research is good

enough to be used in nursing practice.

Keywords: Research, mobility, patient outcomes, safety, critique


Mobility Research Critique

Research has become a large part of nursing with the push towards using evidence based

practice in healthcare settings. Being able to understand research and determine its strengths and

weaknesses is an important part of both nursing students and nurses alike. In this course we

performed a thorough critique of an article by Padula, Hughes, and Baumhover (2009) titled the

“Impact of a nurse-driven mobility protocol on functional decline in hospitalized older adults.”

Critique guidelines were provided by the Foundations of Nursing Research by Nieswiadomy

(2012).

Throughout this paper, the authors used critical thinking and the research process to

determine threats to internal and external validity. These threats can then be analyzed and help

determine if the article provides sound research that should be applied to healthcare settings or if

more research is needed. Each section was critiqued independently and those critiques helped

the authors determine if the article should be used as evidence to critique research articles with in

the future.

Purpose and Problem

Purpose Statement

Evidence

Padula et al. (2009) objective of the mobility article was "to determine the impact of

mobility protocol on functional decline in hospitalized patients" (p. 1). The purpose statement is

presented in title, the first sentence of the abstract and last sentence of the first paragraph in the

study as Nieswiadomy (2012) stated it should.


Support

The purpose statement is blatantly presented in title, the first sentence of the abstract and

last sentence of the first paragraph in the study as Nieswiadomy (2012) stated it would be (p.

300). This topic is important to the nursing profession to enhance positive patient outcomes.

Data obtained from several hospital facilities were collected regarding patient mobility after an

admission for acute medical illnesses. Detail for the diagnosis was omitted from the study. The

impact on mobility for those hospitalized was significantly high, "31% decline in ADL at

discharge" (Padula et al., 2009, p. 1). Subjects were screened by monitoring different variables

(age, gender, diagnosis, assistive devices, fall risk, restrictions), along with a Barthel Index, Get

Up and Go test, and a Mini-Mental State Examination (Padula et al., 2009, p. 3). After

intervening with a Genesis program, subjects showed to have a lowered fall-risk.

Analysis

The purpose is somewhat strong with some significant data to uphold its statement. It is

also feasible and ethical. This study has statistical documentation of how patients were

negatively affected during various hospitalizations. It gave support for positive outcomes after

implementing a prevention program but lacks content depth of the study.

Problem Statement

Evidence

The problem stated in the article is to determine the impact nurse-driven mobility has on

the functional status of patients and length of stay during acute hospitalization (Padula et al.,

2009). Padula et al. (2009) discuss the positive impact mobilization has on patient recovery and

continued independence when instituted during acute hospitalization.


Support

The research problem should include specific information about the population and

variables that are to be studied (Nieswiadomy, 2012). According to Nieswiadomy (2012) the

problem should be clearly stated early in the report in order to guide the reader and help

determine the importance of the research. “The feasibility and the significance of the study

should be apparent” (Nieswiadomy, 2012, p. 300).

Analysis:

The problem statement is weak and is not stated clearly in the reading. This can lead to

confusion with regards to the relationships between the different variables in the study. By

stating a clear problem it would “… help focus attention on the kinds of data that would have to

be collected to provide that answer” to the problem (Nieswiadomy, 2012, p. 34). The data

obtained from the research is strong enough to support the relevance of the study for the nursing

profession, making the study feasible and ethical.

Review of Literature

Evidence

The article does not contain a specific literature review section. However it is included in

the introduction. The sources are all relevant to the topic, appear to be critically appraised, and

cited correctly. Paraphrases are used as opposed to direct quotes. The sources are a mixture of

classic and current and most are primary sources. However, opposing theory and research is

lacking.


Support

Nieswiadomy (2012) states that research articles should contain a comprehensive review

of the literature with both supporting and opposing views. Most should be from primary sources

as opposed to secondary sources, where authors can misinterpret or leave out pertinent

information. Sources should be a mixture of classic and recent articles (within five years); using

paraphrasing as opposed to direct quotes (Nieswiadomy, 2012).

Analysis

Padula et al. (2009) have a fairly strong literature review. It may not be in its own

section, but it is easily distinguished in the introduction. They did not use direct quotes and

sources were a good mixture of classic and current. However, they did not reference sources that

were of opposing views and this would have given them an even stronger literature review. If

they were unable to find any opposing views they should have clearly stated that in the article.

Theoretical/Conceptual Model

Evidence

The authors utilized a conceptual model by applying a geriatric program called Geriatric

Friendly Environment through Nursing Evaluation and Specific Interventions for Successful

Healing (GENESIS) (Padula et al., 2009). “The GENESIS program includes a nurse-driven

mobility protocol; that specific protocol served as the intervention for [their] research” (Padula et

al., 2009, p. 327).

Support

According to Nieswiadomy (2012), conceptual models are primarily involved with the

significant impact nursing has on patient care and outcomes. “Common concepts identified in

nearly all of the nursing models are person, environment, health, and nursing” (Nieswiadomy,


2012, p. 85). Conceptual models tend to be intangible and difficult to utilize in experiments

because their concepts tend to be wide-ranging and inexact (Nieswiadomy, 2012). The

conceptual framework assists in the development and explanation of nursing concepts by

providing definitions for terms and variables used throughout the study (Nieswiadomy, 2012).

Analysis

The conceptual framework is weak and not stated plainly in the reading. The conceptual

framework was difficult to define and adding a heading is not required but may have aided the

reader with its distinction from the review of literature and purpose statement. There were no

definitions for terms or variables noted in the article, which also made it difficult for the reader to

understand the concepts and effectively evaluate the study findings.

Hypothesis and Research questions

Evidence

The hypothesis was clearly stated in the article: “Study hypothesis were as follows: (1)

older adults who participate in a mobility protocol will maintain or improve functional status

from admission to discharge and (2) older adults who participate in a mobility protocol will have

a reduced LOS” (Padula et al., 2009, p. 326).

Support

According to Nieswiadomy (2012) a hypothesis is an extremely important component

used to connect the cause and effect of research studies. It “is a statement of the predicted

relationship between two or more variables” (Nieswiadomy, 2012, p. 100). A hypothesis can be

classified several ways, including simple hypothesis, complex hypothesis, null hypothesis,

research hypothesis, nondirectional research hypothesis, and directional hypothesis. A simple

hypothesis is defined as the correlation between one cause and one effect, or one independent


variable and one dependent variable (Nieswiadomy, 2012). In contrast, “a complex hypothesis

concerns a relationship where two or more independent variables, or two or more dependent

variables, or both, are being examined in the same study” (Nieswiadomy, 2012, p. 101). The

null hypothesis foresees no correlation between the variables in a study and it is open to

statistical analysis. However, the research hypothesis expresses the expected findings from the

relationship between the variables and the research data (Nieswiadomy, 2012, p. 101). Lastly, a

hypothesis can be characterized as nondirectional or directional. A directional hypothesis is

when the relationship between the variables is forecasted or predicted and a nondirectional

hypothesis gives no explanation as to what kind of relationship exists between variables, just that

a relationship exists (Nieswiadomy, 2012).

Analysis

This article has two simple hypotheses that are clearly stated, easily found and are tied

directly to the study, which makes this a strong section of the study. However, there is no null

hypothesis clearly stated which leaves the reader open to assumptions when evaluating the

research data. The hypothesis contains a population and variables. The population in this study

is older adults. The two variables consist of mobility to maintain or improve functional status

from admission to discharge and mobility to have a reduced length of stay (Padula et al., 2009).

Nieswiadomy (2012) considers this to an example of a directional research hypothesis because it

“states the type and correlation or difference that the researcher expects to find” (p. 108). The

first hypothesis contains two predictions. One prediction is that the subject will maintain the

same level of mobility. The second prediction of the hypothesis suggests that the level of

functional status will show improvements, all of which can be empirically tested. Overall, this

section of the article would have been considered very strong had a null hypothesis been given.


.Research (Study) Design

Evidence

The research design as stated by Padula et al. (2009) is a nonequivalent control group

design. The independent variable was the mobility protocol and the dependent variables were

functional status and length of stay (Padula et al., 2009). The groups were two different floors at

The Miriam Hospital in Providence, Rhode Island. The inclusion criteria were a length of stay in

the hospital of three or more days, ability to understand English, no physical limitation that

would limit mobility, and intact cognitive ability. A research nurse screened the applicants.

Support

According to Nieswiadomy (2012), an experimental design observes cause-and-effect

relationships (how one variable affects another) and involves manipulating variables to

determine if there is a positive or negative affect on a population or individual. Nonexperimental

designs do not deal with manipulation of variables as the research is descriptive (Nieswiadomy,

2012). A quasi-experimental design is one in which current intact groups are used as opposed to

randomly assigned groups (Nieswiadomy, 2012). It is thought that by doing so, the natural

world is more closely mimicked than random assignments (Nieswiadomy, 2012). This is the

type of study of the article in question and more specifically it is a nonequivalent control group

design, which is a type of quasi-experimental design.

Internal validity in this type of study is threatened by history, testing, maturation, and

instrumentation change and selection bias (Nieswiadomy, 2012). Selection bias occurs when the

researchers attribute the changes to an experimental variable when they were actually due to

subject differences (Nieswiadomy, 2012). In a quasi-experimental design, randomization is not


present because the researcher is using a group that already exists. An example would be

choosing a classroom in a school or an entire unit of a hospital.

Control is required in research studies to help provide evidence that a variable is in some

way changing an outcome. If there is no control, the results of the study cannot be attributed to

the variable because there may be other factors that are interfering with the results. Control is

difficult in studies with humans because of ethical issues and is one of the reasons

nonexperimental designs are used (Nieswiadomy, 2012).

Analysis

This article had a weak experimental design and therefore the outcome could be affected.

The design was clearly stated and the independent and dependent variables were listed. This

design was appropriate for the study as the selection provided a viable population for the

research question. There are several types of experimental designs that could have been chosen,

but a quasi-experimental design is appropriate here because the subjects are not randomly

assigned (Nieswiadomy, 2012). The authors tried to control internal threats by having specific

inclusion criteria, but they are not successful due to the fact that the groups are not the same

(Padula et al., 2009). They clearly defined where the study was taking place and the selection of

the nursing units used was identified. They were on different floors of the hospital, which even

though seems necessary to control the staff and use of the mobility protocol, there may also be

factors of why they were placed on different floors. The patients in the control group may have

had secondary factors that limited them and could not be controlled for. All trials that use

humans as subjects are very difficult to control (Nieswiadomy, 2012). Knowing this and the

limitations of the study, researchers can view this study as limited but provides information that

may help future research and interventions with patients.


Sample and Sampling Methods

Evidence

The targeted population the researchers used was adults older than 60 years (Padula et al.,

2009). The sampling plan was a convenience sample of 84 subjects. Subjects were included in

the study if their length of stay was three or more days, fluent in the English language, the

absence of physical immobility, and they needed to be alert and oriented (Padula et al., 2009).

Subjects were excluded from the study if their score on a mini mental exam was less than 24.

Exclusions were also due to discharge prior required length of stay, transfer, procedure, and

anxiety. Thirty four subjects were lost or excluded leaving a total of 50 suitable subjects (Padula

et al., 2009, p. 327).

Support

A researcher can use multiple types of sampling. To select and assign subjects to groups,

it is important to interview participants to obtain accurate data. Researchers can use probability

or nonprobability types of sampling methods (Nieswiadomy, 2012). Probability sample methods

use “random selection process to obtain a sample from members or elements of a population”

(Nieswiadomy, 2012, p. 147). Examples of a probability sample methods include simple,

stratified, cluster, and systematic. Nonprobability sampling methods are “chosen from the

population by nonrandom methods” (Nieswiadomy, 2012, p. 152). Examples or nonprobability

samples are convenience, quota, and purposive. External validity may be affected because the

subject is aware of a study being conducted, the Hawthorne effect, or behavior from the

researching influencing the subject, the experimenter effect (Nieswiadomy, 2012, p. 117).

Internal validity may be affected by selection bias, history, maturation, testing, instrumentation

change, or mortality. Nonrandom methods are generally at risk for bias related to the inability to


“estimate the probability that each element of the population will be included in the sample”

(Nieswiadomy, 2012, p. 152). In fact, elements may be completely omitted from the sample.

Convenience samples may especially be at risk for sampling bias because they are frequently

used when there are financial or time restraints.

Analysis

The targeted and accessible population was identified. The researchers chose a

nonprobability sampling method (Padula et al., 2009), which is a convenience sample. The

sampling method and details were stated in the text. The sampling method was not appropriate

for the study because of the variety in population, threats to validity, and bias. The sample size

is not representative of the population. The central limit theorem recommends a sample size of

100 to ensure “sample values tend to be normally distributed around the population value”

(Nieswiadomy, 2012, p. 226). Sampling biases and dropout subjects are identified in the text.

Overall, this is a weak section due to the convenience sample.

Data Collection Methods

Evidence

The researchers used nominal levels of measurements in this study. An advance practice

nurse was trained on the instruments used prior to the study. Data to be collected included “age;

gender; primary diagnosis; use of assistive devices; fall risk assessment; presence of any

restrictions to mobility; use of occupational or physical therapy; length of stay; first and number

of times out of bed; and type of out-of-bed activity” (Padula et al., 2009, p. 328) using a

demographic sheet created especially for use during this study. In addition, a Barthel Index, Up

& Go test, and Mini-Mental examination were also used. Data was to be collected for two weeks


prior to admission in their home, assisted living, or nursing home. Data would be collected again

on admission and at discharge from the hospital.

Support

Nieswiadomy (2012) explains four different levels of measurement (nominal, ordinal,

interval, and ratio). Nominal categorizes the data in all ways possible. The data must be

different and should be calculated by adding the amount in each category (Nieswiadomy, 2012).

The ordinal level of measurement ranks the data in order as well as categorizing it

(Nieswiadomy, 2012). Interval takes actual numbers and places them in order. Ratio is the most

accurate way to calculate data. This data can be placed in order and into groups. In addition

there must be a zero point where “there is a total absence of the quantity being measured”

(Nieswiadomy, 2012, p. 165). Nieswiadomy (2012) states that for the data-collection process the

researcher must determine who they would like to involve in their team to collect data. A

location and time frame should be decided along with what data they are trying to collect. A

data collection method and instruments should be decided to gather information. Hawthorne

effects may be a risk to internal validity if the subject reacts in a differently because they have

knowledge of being observed (Nieswiadomy, 2012).

Analysis

Details of the qualifications of who was collecting the data were poorly demonstrated.

The information given for when data intake will take place is lacking time of day and expected

length of time for collection process (Padula et al., 2009). The level of measurement of the

instruments used in the study was not clearly explained in the text leaving the reader unsure if

the correct statistical test was performed, which is a threat to internal validity. There is also a

threat to external validity as the Hawthorne and researcher effects could play a role because the


subjects are aware of a study being conducted. Results may have been skewed if efforts have not

been made to prevent false effects on data. Overall, it is a weak section.

Instrument

Evidence

The authors used a demographic data collection sheet that was designed for this research

study to collect information such as age, gender, primary diagnosis, restrictions to mobility, use

of occupational or physical therapy, length of stay, first and number of times out of bed, and type

of activity (Padula et al., 2009). Since it was first developed, no information is available on

reliability and validity.

Two different instruments were chosen to measure functional status (Padula et al., 2009).

The first is the modified Barthel Index (BI). BI was used to determine “self-perceived level of

function at the time of admission, for 2 weeks prior to admission, and at discharge” (Padula, et

al., 2009, p. 328). Padula et al. (2009) state that the correlation coefficient with the Frail Elderly

Functional Assessment is 0.91, indicating that validity is high for the study. Reliability was not

mentioned.

The second instrument was the Get Up and Go test and it is “an objective assessment that

measures subjects’ ability to stand from an armchair, walk 3 m, turn around, return, and sit down

in the chair again” (Padula et al., 2009, p. 328). Padula et al. (2009) state that it has been found

to be both reliable and valid with the BI.

A Mini-Mental State Examination was used to test cognitive status. If the patient’s score

was less than 24, their significant other’s opinion on patient abilities was used (Padula et al.,

2009). Reliability and validity were not discussed.


Support

Instruments are required to collect data (Nieswiadomy, 2012) and therefore help

determine the outcome of a trial or study. Ensuring that the correct instrument is selected is

imperative and the instrument should measure what the authors are testing (Nieswiadomy, 2012).

An instrument must be reliable. Reliability is the consistency and stability of an instrument

(Nieswiadomy, 2012). For example, an automatic blood pressure cuff can only be reliable if it

measure the blood pressure the same as a manual cuff. Correlation coefficients are used to

determine the reliability and can range from -1.00 to +1.00, where closer to +/- 1.00 indicates

better reliability (Nieswiadomy, 2012). If the correlation coefficient is less than 0.7, it is

considered risky to use the instrument (Nieswiadomy, 2012).

There are different types of reliability. Stability reliability is concerned with the

instruments ability to stay consistent over time and uses the test-retest reliability, testing before

and during the study (Nieswiadomy, 2012). Equivalent reliability is when two different forms of

the instrument (or two different observers use a single instrument) get the same results

(Nieswiadomy, 2012). If two different forms of the instrument are used, it is considered

alternate forms reliability and when different observers but the same instrument are used it is

considered parallel forms reliability (Nieswiadomy, 2012). Internal consistency reliability is

concerned with the extent that the parts of the instrument are examining the same thing

(Nieswiadomy, 2012). For example, if a survey about pain is given, all questions should

measure pain, not another outcome such as anxiety.

Validity is the other important concern when determining if an instrument is appropriate

for a study. The level of validity shows how well the instrument gathers the data that it is

intended to gather (Nieswiadomy, 2012). Nieswiadomy (2012) states that “the greater the


validity of an instrument, the more confidence you can have that the instrument will obtain data

that will answer the research questions or test the research hypotheses” (p. 171). Face validity is

present when a preliminary test shows that the instrument measures what it is supposed to

measure and it is rarely used alone (Nieswiadomy, 2012). Content validity is an estimate of

whether or not the items present are sufficient to measure the concept (Nieswiadomy, 2012).

Criterion validity is “concerned with the extent to which an instrument corresponds to or is

correlated with some criterion measure of the variable of interest” (Nieswiadomy, 2012, p. 172).

It helps to predict responses now and in the future. Construct validity is the most difficult to

measure and it is a measure of how well the instrument measures the construct (a theory or

concept such as anxiety) determined by the author (Nieswiadomy, 2012).

Measuring reliability and validity are not easy. However, it is a very important step in

research studies. Without them, we would have no idea how accurate the study was and couldn’t

determine if the data measured was of use.

Analysis

Padula et al. (2009) had a section specifically for instruments, making it easy for the

reader. The description of the BI and the Get Up and Go test were fairly thorough, but the

section on the Mini Mental State Examination was lacking as reliability and validity were not

discussed. Both of the functional assessment tests had been conducted previously and the

correlation coefficient of the BI was given, indicating reliability (Padula et al., 2009). They also

state that the Get Up and Go test was found to be reliable and valid with BI (Padula et al., 2009),

but do not expand further on where they got that information. Reliability of the BI was not

mentioned except in relation to the other instrument. Specific types of reliability and validity

were not discussed for any of the instruments. The authors could have expanded this section. If


they would have described the types of validity and reliability, the outcome of the study would

be better explained and easier to utilize for other. A pilot study would have also been useful and

further improved the research paper. According to Nieswiadomy (2012), a pilot study is a

smaller version of the study and it helps determine that the instrument is measuring what the

authors intended it to do and allows them to change the instrument if needed.

Data Analysis (Descriptive and Inferential Statistics)

Descriptive Statistics

Evidence

Padula et al. (2009) used a mean of 80.4 years and a range of 62 to 97 years to represent

the population given. Percentages were calculated to determine the amount of patients that were

admitted from home, assisted living and nursing homes. Padula et al. 2009) gave two tables to

describe 'Nursing staff characteristics by unit for study period' (p. 327) and 'Barthel scores' to

illustrate evidence of significant improvement or decrease in discharge scores (p. 329).

Support

Descriptive statistics "organize and summarize numerical data gathered from samples"

(Nieswiadomy, 2012, p. 205). Measures should be taken to condense data by frequency

distributions, graphic presentations and percentages. Statistics that describe the average, typical,

or most common value for a group of data are better known as measure of central tendency

(Nieswiadomy, 2012). Calculations of the mode, median, and mean can be used to simplify

numbers and show the impact of the values.

Analysis

The types of descriptive statistics included in the research report are measures to

condense data and central tendency. The statistics were not appropriate for the level of


measurement of the variables because it was lacking significant data. The measures of central

tendency and variability were both presented (Padula et al., 2009). The demographic

characteristics of the subjects were clearly stated in the results. The descriptive statistics in this

study were stated within the text but was not utilized enough in the graphs to help the reader

understand the findings. The tables represent the data within the text. More tables and graphs

would allow the reader to visualize the significant differences in scores. A scatter plot could

have been used to represent the relationship between two variables. A contingency table could

have easily shown if a relationship between categories exist (Nieswiadomy, 2012, p. 217),

strengthening this section.

Inferential Statistics

Evidence

Padula et al. (2009) state that they “recruited a convenience sample of (N = 50) of adults

60 years or older who were admitted with medical diagnoses to 1 of 2 nursing units (n = 25

each)” (p.327). The fall-risk subjects studied showed scores for pre-admission P = 0.05,

admission (7.5 treatment vs. 9.5 control) P = 0.07, compared to (1.86 treatment vs. 2.4 control) P

= 0.04 after treatment. The control group function between preadmission to the time of

discharge was P = 0.006. Results for those testing in the Up and Go scored 1.16 on admission

vs. 1.04 at the time of discharge, 1.35 on admission, and 1.17 at discharge (control) (Padula et

al., 2009).

Support

Inferential statistics are "based on laws of probability” and that “the assumption that

chance (sampling error, random error) is the only explanation for relationships that are found in

research studies” (Nieswiadomy, 2012, p. 225). The purposes of inferential statistics are to test


predictions of results and estimate population parameters. The null hypothesis is when the

sample population chosen does not have correlation with the variables (Nieswiadomy, 2012). To

determine whether or not to reject the null hypothesis, if the p value attained is less than the set

level of significance (alpha), the researcher would be able to reject the null hypothesis

(Nieswiadomy, 2012, p. 233). Nieswiadomy (2012) also states “if small differences or low

correlations are found, chance is considered to be the reason” (p. 229-230). The null hypothesis

therefore would be accepted. The null hypothesis is rejected “if the results of the analysis show

the difference or correlation is too large to be the result of chance” (Nieswiadomy, 2012, p. 230).

There are two different types of errors when determining results. A type I error occurs when the

null hypothesis is false and it the researcher failed to reject it. The second type of error (type II)

is when it is failed to be rejected and the null hypothesis is actually false. A correct decision is

made when you reject a false null hypothesis (Nieswiadomy, 2012). A t test is a parametric test

that studies two groups to compare the difference between the mean values. The test compares

the means for small sample sizes of either independent (unrelated) or dependent (related)

samples (Nieswiadomy, 2012).

Analysis

The inferential statistics were presented in the report although it is difficult to determine

whether the appropriate tests were used because of lack of information. Calculated values,

including inferential statistics and level of significance, were available for the reader. The null

hypothesis was not clearly stated, which leaves the reader open to assumptions when evaluating

the research data.


Study Findings

Evidence

The study presented by Padula et al. (2009) found that the treatment group had a lower

fall-risk score than the control group on admission (7.5 treatment vs. 9.5 control; P=.07), but that

this score was not significant (p. 328). The treatment group was also found to have a lower

quantity of fall-risks during the study (1.86 treatment vs. 2.4 control; P=.04), which supports the

finding that the treatment group had lower fall-risk scores on admission (Padula et al., 2009, p.

328).

Padula et al.(2009) presented a table illustrating Barthel scores for the groups which

revealed the subjects’ beliefs regarding what they thought their functionality was two weeks

prior to admission, during admission and compared the scores with what the subjects felt their

functionality was after discharge. The treatment group showed a substantial improvement from

admission to discharge scores (P= .05), while the control group had no significant change (6.9)

(Padula et al., 2009). A considerable decrease in the function between preadmission and

discharge was shown by the control group (P=.006) (Padula et al., 2009). “Scores for the Up and

Go test improved slightly for both groups (1.16 admission vs. 1.04 discharge, treatment; 1.35

admission vs. 1.17 discharge, control) but were not significant” (Padula et al., 2009, 329).

Padula et al. (2009) indicated the treatment group had a substantially shorter length of

stay than the control group (4.96 days treatment vs. 8.72 days control; P< .001) despite the

treatment group being out of bed and to the chair less frequently (5.9 times treatment vs. 8.7

times control; P = .05) and ambulated in the room less (5.54 times treatment vs. 7.16 times

control; NS) than the control group. Even though the treatment group was less active than the


control they ambulated earlier (2.7 days treatment vs. 4.9 days control, P= .007) (Padula et al.,

2009).

Support

According to Nieswiadomy (2012) the study findings should be documented as

“empirical data or facts” (p. 247). The data should be obtained based on the examination of the

statistics gathered from the study and should clearly correlate with the hypotheses

(Nieswiadomy, 2012). The data can be reported both narratively and in the form of tables, but

the findings must be reported clearly and concisely (Nieswiadomy, 2012).

Analysis

Padula et al. (2009) provided a decent overview of their research findings. The study

findings were reported clearly, concisely, and objectively by using both a narrative form and by

using a table. The study findings were directly connected to the two hypotheses presented by the

study.

Study Discussion of Findings

Evidence

Padula et al. (2009) have interpreted their findings and related them to their two stated

hypotheses. The first hypothesis proposed that older adults who were involved with a mobility

protocol were able to sustain or increase their functional status during hospitalization. Their

research results support this hypothesis (Padula et al., 2009). The second hypothesis was also

supported by the research results and stated that older adults who partake in a mobility program

have a reduced length of stay.

The limitations of the research study were also discussed by Padula et al. (2009). It was

noted that the control group’s diminished functional level could have caused a longer length of


stay and possibly prevented early ambulation (Padula et al., 2009). These diminished functional

levels experienced by the control group could have been contributed by other things such as

acuity and other burdens of disease. Other factors were not explored in the study and there is

further research needed for the quantification of the impacts these diseases have on patients and

their functional levels (Padula et al., 2009). There is also some question as to the differences

between the groups’ baseline functional statuses, even though there was no significant

differences detected there is still the possibility that differences existed and had the possibility to

affect the study findings (Padula et al., 2009). Further exploration is also needed to examine the

results of the modified Get Up and Go test, which was used to objectively measure functional

ability, because it did not reveal any differences in functional capability that was recognized by

the Barthel Index (Padula et al., 2009). Lastly, the authors discussed how the presence of an

advanced practice nurse on the control unit could have affected the outcome of the results by

having a positive influence on patient mobility (Padula et al., 2009).

Support

According to Nieswiadomy (2012) the discussion of findings should examine the quality

of the study results, previous research on the topic, and any limitations that may interfere with

the findings. There should be no new information brought forth in this section because it could

take credibility away from the authors, making it appear they did more research after the findings

to make their findings more believable (Nieswiadomy, 2012). Nieswiadomy (2012) also points

out that a study should not overgeneralize, but the study should make assumptions that reflect the

correlation between the data, sample size, and sampling method. This section of a research study

should also discuss the theoretical framework of the study and how it applies to the study

findings (Nieswiadomy, 2012).


Analysis

The discussion of findings appears to be somewhat flimsy. The authors presented many

limitations found in their research study, but had failed to correlate them with the theoretical

framework which was inadequate in the study to begin with. The sample population for the

groups was weak and the authors’ tended to generalize their findings to all populations instead of

the populations they specifically studied. Lastly, the authors made no effort to suggest any

changes that could make the next research study stronger.

Study Conclusions, Implications, & Recommendations, Recommendations

Evidence

Padula et al. (2009) did include a conclusion however it was very short. The conclusion

stated that “findings suggest that early and ongoing ambulation in the hallway may be an

important contributor to maintaining functional status during hospitalization and to shortening

length of stay” (Padula et al., 2009, p. 330). The authors believed that their findings supported

previous research studies.

Support

According to Nieswiadomy (2012), a conclusion should be clearly stated to ensure that

the reader understands the findings of the study. Authors must be careful not to overgeneralize

the results of their study; considering the size of the sample versus the population is imperative

(Nieswiadomy, 2012). Implications of the study should also be clearly stated. Stating what

should happen with the findings can be included here. For example, if more research is needed

or nurses should change their practice based on the findings, would be included here

(Nieswiadomy, 2012). Recommendations for future research based on the findings should also

be addressed (Nieswiadomy, 2012).


Analysis

The conclusion of this article by Padula et al. (2009) is very short and does not cover all

of the required points. It leaves the reader with more questions than it concludes. The findings

are stated as above, but little expanding is done on the topic. This is a very weak section of the

article. Padula et al. (2009) do state that nurses should look at ambulation as a priority for an

implication of the study, but it is left at that. No recommendations for future research are

explained. This section could have been much stronger had they expanded implications and

added the recommendations.

Conclusion

Medical facilities are constantly striving to improve policies through evidence based

practice in order to provide the best possible outcomes for patients. This paper has analyzed a

research mobility article using guidelines provided by Nieswiadomy (2012). The analysis of the

mobility article included a thorough examination of its purpose, problem, review of literature,

theoretical/conceptual model, hypothesis/research questions, research design, sampling methods,

data collection methods, instruments, both descriptive and inferential data analysis, study

findings, and study discussion.

The mobility article that was evaluated in this paper did not cover all of the aspects

provided by Nieswiadomy (2012) to be considered a strong research article. After the authors

had systematically scrutinized the mobility article they found the article’s strengths lied in the

purpose, review of literature, hypotheses, research design, and the study findings. The other

areas of the article that seemed to be the most important parts of a good research study seemed to

be weak, these areas include the problem statement, theoretical/conceptual framework, sampling

method, data collection, instruments, data analysis, study of discussion findings, and the


conclusion, implication and recommendation. After reading the mobility article the authors were

left wanting more in many areas and feel that this article is a good base for more research that

would include an enhanced sample group with a stronger conceptual framework and a more

thorough explanation of the instruments in order to aid in a better understanding of the research

findings.


References

Nieswiadomy, R.M. (2012). Foundations of nursing research. (6th ed.). Upper Saddle River, NJ:

Pearson Education Inc.

Padula, C. A., Hughes, C., & Baumhover, L. (2009). Impact of a nurse-driven mobility protocol

on functional decline in hospital older adults. Journal of Nursing Care Quality, 24(4),

325-331. doi: 10.1097/NCQ.0b013e3181a4f79b


Research Critique Grading Criteria

APA Format: up to 30 points or 30% can be removed after the paper is graded for Title page, abstract, headers Margins, spacing, and headings, reference page, title page, abstract Sentence structure, spelling, grammar & punctuation.

Headings Possible Points

Points Earned

Comments

Abstract and Introduction: No heading

for intro, but there should be a introduction of the study and what your paper will

address, why you are doing the critique

10

Purpose & Problem Statement (Identify the problem & purpose and

analyze whether they are clear to the reader. Are there

clear objectives & goals? Analyze whether you can determine feasibility and significance of the study)

10

Review of the Literature and Theoretical

Framework (Analyze relevance of the sources; Identify a theoretical or

conceptual framework & appropriateness for study)

10

Hypothesis(es) or Research Question(s)

(Analyze whether clearly and concisely stated; discuss

whether directional, null, or nondirectional hypothesis[es])

10

Sample & Study Design (Describe sample & sampling method &

appropriateness for study; analyze appropriateness of design; discuss how ethical

issues addressed)

10

Data Collection Methods & Instruments (Describe &

analyze the appropriateness of the what, how, who,

where and when; describe

10


&analyze reliability and validity of instrument)

Data Analysis (Describe

descriptive & inferential statistics & analyze whether

results are presented accurately & completely)

10

Discussion of Findings (Analyze whether results are

presented objectively & bound to the data, whether

there is a comparison to previous studies and

whether new literature is introduced that was not

included in the Literature Review

10

Conclusions, Implications, & Recommendations

(Analyze whether the conclusions are based on

the data, whether hypotheses were supported or not supported, whether implications are a result of

the findings, and recommendations consider

limitations

10

Your paper should end with a brief conclusion of your

critique

10

PAPER POINTS 100

Deductions for APA, grammar and Spelling

Final GRADE

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