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Running head: MOBILITY PROTOCOL ARTICLE CRITIQUE 1

Mobility Protocol Article Critique

Katrina Lampman, Tina Palmer, Shelly Parker, and Carol Zinn

Ferris State University

NURS 350

MOBILITY PROTOCOL ARTICLE CRITIQUE 2

Abstract

This paper is designed to read and critique the article “Impact of Nurse-Driven Mobility Protocol

on Functional Decline in Hospitalized Older Adults” by Padula, Hughes & Baumbover (2009) by

using Nieswiadomy’s (2010) book titled “Foundations of Nursing Research” as a guide. This

article was broken down into the steps of the nursing research process and critiqued accordingly.

Keywords: mobility, functional decline, protocol, internal validity, external validity


Mobility Protocol Article Critique

The purpose of this paper is to establish students’ skills at critiquing research work as a

group. The article critiqued was “Impact of a Nurse-Driven Mobility Protocol on Functional

Decline in Hospitalized Older Adults” by Padula, Hughes & Baumbover (2009). Nieswiadomy

(2010) was used as a resource for evidence-based practice and critique models.

According to Nieswiadomy (2010), a nursing researcher article should include a purpose

and problem statement, review of literature and theoretical framework, a hypothesis or

hypotheses, sample and study design, data collection methods and instruments, data analysis,

discussion of findings, and conclusions, implications, and recommendations. This paper shows

the evidence, support, and analysis of each of these sections of the article critiqued.

Purpose

Evidence

According to Nieswiadomy (2012, p. 34), the purpose of an article can be determined by

why the study was done. In this article, the purpose was clearly stated as it had the words “the

purpose of the study” in the sentence. Padula, Hughes & Baumbover (2009, p. 326) state “the

purpose of the study was to determine the impact of a nurse-driven mobility protocol on

functional decline in hospitalized older adults”. In a review of the text book materials, the book

described the purpose statement and noted the difference between a purpose and a problem,

avoiding any possibility of confusion.

Support

The purpose of the study should be written in the article in such a way that it will leave

no doubt to the reader what it is (Nieswiadomy, 2012, p. 300). Before the study even begins, the

reasons for the study should be determined. The purpose statement is usually written in the


abstract and again in the introductory section of the article (Nieswiadomy, 2012, p. 34). The text

does also state that the purpose statement should be in the form of a study purpose

(Nieswiadomy, 2012, p. 300). It is also noted that the broad purpose of the study may be more

specific in the form of objectives or goals.

Analysis

The purpose of the mobility article is pretty strong in this section as it is well defined and

the reader is able to understand what is going to happen, but the conclusion in the article

included the length of stay which was not mentioned in the purpose statement. According to

Nieswiadomy (2012, p. 303), the conclusion of the study answers the purpose of the study.

There was no abstract with a purpose statement attached to this article.

Problem Statement

Evidence

The problem statement is not clearly defined in this article; however, it can be found at

the end of the introductory paragraph, which is the correct placement according to Nieswiadomy

(2012, p. 300). The writers make the problem statement difficult to single out.

The problem in the article is “the goal of this study was to determine the impact of the

mobility protocol on the functional decline in hospitalized patients” (Padula, Hughes, and

Baumhover, 2009, p. 325).

Support

According to Nieswiadomy (2012, pp. 33-34), the reader should be able to identify the

problem statement at the beginning of the introductory paragraph. The text indicates that the

problem of the study should be clearly identified. It further indicates that early in the report there

should be a mention of the broad problem of the study. The more specific statement of the


problem can be found in the abstract and at the end of the introductory section of the report. The

text also states that the problem statement can be in the form of a declarative problem statement,

a purpose statement, or a research question. The problem statement should contain the

population and major variables and indicate the data may be gathered empirically. The

feasibility and significance of the study should be apparent. In many reports the purpose may be

more easily identified than the problem (Nieswiadomy, 2012, p. 300).

This research article, “Impact of a Nurse-Driven Mobility Protocol on Functional Decline

in Hospitalized Older Adults” (Padula, Hughes & Baumhover, 2009) is of quantitative design.

Therefore, there should be a clear problem statement at the beginning of the article. The goal of

this article is feasible so it is capable of being carried out successfully as the costs are low, data

can be easily gathered, assessed, and the subjects are easily accessible. This study is also

beneficial to healthcare workers, physicians, and patients.

Analysis

Since the reader is unable to clearly define the problem statement at the beginning of the

article, it is weak. The reader may have to read the manuscript very closely to identify what the

problem is. The purpose statement is clear, however. The study is ethical as the patients were

informed by a letter approved by a review board and then gave consent. There was no harm

done to the patients. The study was low in costs as it did not require any additional staff or

expensive equipment. The subjects were readily available, which enabled the studied to be

completed.

There are benefits to all the healthcare professionals and the patients as patient

satisfaction and level of functioning improve with this intervention. Although the subjects were

carefully screened for functional mobility and cognitive ability prior to the study, there were still


a lot of variables. For example, the fall risk factors were higher in the control group than the

treatment group, meaning that there were already some weaknesses or decreases in mobility.

Further, there was a wide age range and some varying levels of independence as some came

from home, some from assisted living, and some from a nursing home. It is not clear how the

data was gathered or exactly what the data is, therefore the reader is not sure how the authors

support their conclusion.

Review of Literature

Evidence

The beginning of the review of literature (ROL) is at the end of the first paragraph in the

article after the problem statement. The article goes right from its introduction into the ROL. It

cites several articles with statistics to indicate there is an ongoing problem with functional

decline in activities of daily living (ADL’s) and ambulation in hospitalized patients. It goes on

to discuss how this decline is associated with poor outcomes and prolonged length of stay.

The article then presents its findings associated with increased mobility while

hospitalized and how this increased mobility yielded positive outcomes for the patients. The

article then concludes its ROL with a short statement regarding maintenance of mobility in

critically ill people and how this is crucial in the achievement of positive outcomes. There was

some critiquing of the articles, but nothing substantial.

Support

Nieswiadomy indicates in the text that the ROL should be all-inclusive and to the point.

It should have a nice flow and be easy to understand. All sources should be relevant to the study

topic and should be critically appraised. The research should be critiqued in the article such that

the reader knows if the findings are weak or strong (Nieswiadomy 2012, pp. 78-79).


ROL should include classic sources as well as current sources. Most references should

not be more than 5 years old. The ROL should be mostly paraphrases and not direct quotes, but

both should be cited when referencing the writings of others. One should be able to determine if

the researcher is using primary sources or secondary sources (Nieswiadomy 2012, p. 71).

However, this is not always clear in the writings. To distinguish between the two it may

be necessary to look at the reference list for hints. It is to be expected that research journals are

primary sources, while secondary sources are items like book chapters and literature reviews.

The only way to know for certain would be to review each reference personally but this is

unlikely to be an option. Supporting and opposing theory and research should be presented in

the ROL section.

All sources should be cited on the reference list and should be without errors

(Nieswiadomy, 2012, pp. 78-79). The ROL can be found toward the beginning of the article or

toward the end of the article, depending on the design. The ROL should “provide an adequate

summary of the existing body of knowledge on the phenomenon of interest” (Nieswiadomy,

2012, p. 306). The ROL should end “with a sentence or two that indicates how the present study

will contribute to the existing body of knowledge in that subject area” (Nieswiadomy 2012, p.

300).

Analysis

The ROL is not clearly marked but it is distinguishable because it flowed from the

purpose statement as indicated it should according to (Nieswiadomy, 2012, p. 79). It is easy to

tell when the article moves into discussing the ROL as it starts to give statistics and cites where

these statistics come from. The information is to the point, but not convincing that it is all-

inclusive and the flow of the information seemed a little off. It is not clear by reading the article


whether the sources used are primary or secondary. When reviewing the citations at the end of

the article, it is apparent that they are mostly primary sources, but some of them were difficult to

determine. There are some book references which could be secondary sources as these could be

considered classic sources and the articles as current sources. Some of the resources used in the

article were more than five years old so the ROL is a weak section. While the article does not

indicate direct quotes, specific statistics cannot be paraphrased which is what Nieswiadomy

states should be (Nieswiadomy, 2012, p. 300). The researchers also did not critique the articles

that they used to determine if the resources are appropriate. According to Nieswiadomy (2012,

pp. 78-79), this is part of the ROL process.

This ROL is at the beginning of the article as Nieswiadomy indicates it should be. The

article does provide some opposing information but not much. Nieswiadomy (2010, p. 79) states

that both supporting and opposing theory should be represented, which makes this section of the

article weak as well.

Theoretical Framework

Evidence

Under the Intervention heading, the researcher does mention that education had been

provided to nurses on the GENESIS model (Geriatric Friendly Environment through Nursing

Evaluation and Specific Interventions for Successful Healing) (Padula, Hughes & Baumbover,

2009, pp. 327-328). However, there was no information provided on the theories of the

GENESIS program. It would be more beneficial to the readers of this study to know what

GENESIS is. The framework is not clearly defined in this article.


Support

The theoretical framework provides a general explanation of the relationships between

concepts of interest in the study, and is based on one existing theory. The conceptual framework

explains the relationships between concepts and can link the concepts from several theories. The

theories are based on previous results or from the experience of the researcher. The concepts

should flow in a logical manner and are less well developed than a theoretical framework

(Nieswiadomy, 2012, p. 88).

Conceptual frameworks can act like maps. According to Nieswiadomy, theoretical or

conceptual framework assists in the selection of the study variables and in defining them. The

conceptual framework should define the terms, propositions, and assumptions of the researchers

(Nieswiadomy, 2012, pp. 87-88). The framework also directs the hypothesis and the

interpretation of the findings (Nieswiadomy, 2012, p. 35).

Analysis

The article is weak in showing the conceptual framework clearly. The framework is not

clearly defined and there is no conceptual framework heading to point the reader in locating the

information. There is reference to the educational program provided to the nursing staff called

GENESIS, but there is not much information about what GENESIS is, or the theories related to

the program.

The researcher attempted to provide definitions of the variables, especially as noted in

describing the instruments used. However, when the researcher used the term functional status,

the term was not clearly defined which made it difficult to determine that functional status had

actually improved. Finally, the type of hospital used for the research study was not clearly

defined.


Hypothesis

Evidence

According to the article by Padula, Hughes & Baumhover (2009, p. 327), there are two

hypotheses stated. The first hypothesis states “older adults who participate in a mobility protocol

will maintain or improve functional status from admission to discharge” (Padula, Hughes &

Baumhover, 2009, p. 327). This means that the research will prove that elderly patients, that are

part of the mobility study, will improve their functional level of mobility or at least maintain it.

The other hypothesis states “older adults who participate in a mobility protocol will have

a reduced LOS” (Padula, Hughes & Baumhover, 2009, p. 327). This means that the length of

stay will be decreased for those who participate in the mobility exercise. The independent

variable, or cause, is the mobility protocol. There are two dependent variables, or effects, and

they are the functional status and length of stay. The population in this study is elderly adults

and it was plainly identified that the elderly patients were over the age of 60 (Padula, Hughes &

Baumhover, 2009, p. 327).

Support

According to Nieswiadomy (2012, p. 36), a hypothesis should be written in the present

tense. The goal of the hypothesis is to be specific in identifying the part of the theory being

tested. The hypothesis should answer the research question. The knowledge that is gained

through the study is used to either support or reject the hypothesis or theory. Both positive and

negative findings are important to the research. The hypothesis predicts the relationship between

one or more variables. A variable is something that is different among the population being

studied (Nieswiadomy, 2012, pp. 36, 41, 100).


In the text by Nieswiadomy (2012, pp. 101-104), there exist different hypotheses; simple,

complex, research, null, directional, and nondirectional. A simple hypothesis looks at the

relationship between one independent variable, or cause, and one dependent variable, or effect.

A complex hypothesis looks at the relationship of two or more independent or dependent

variables or both. A null hypothesis states that there will be no relationship between the

variables. The researcher’s goal is to disprove the null hypothesis. The research hypothesis

expects that there will be a relationship between the variables. Hopefully, the outcome of the

research supports the research hypothesis and rejects the null hypothesis. A nondirectional

hypothesis is one where a research predicts that there is a relationship between the variables.

The expectation of the researcher may not be clear. In a directional hypothesis the relationship

between the variables is clear, as are the expectations of the study (Nieswiadomy, 2012, pp. 101-

104).

A hypothesis is used in a quantitative research design because it contains the researcher’s

expectation about the results of the research. A hypothesis must also predict the answer to the

research question, contain the population, variables, and be able to be tested in an empirical

fashion, which means one should be able to validate the findings of the research by realistic

means such as using the senses (Nieswiadomy, 2012, pp. 105-106).

Analysis

This article did contain two clearly stated hypotheses which are written in the present

tense. The dependent variable, the functional status, and length of stay are clearly stated as well

as the independent variable, and the mobility protocol. The hypothesis is a directional

hypothesis as the relationship between the variables is clear. It uses two dependent variables,

and one independent variable; the results of the study support the research hypothesis. The null


hypothesis is not clearly defined, but may be assumed in this study. The population is addressed

in the hypothesis, and it can be empirically tested. One can see the results and hear about the

results.

More positive findings were addressed in the study than negative. There was a direct

correlation between the research question and the hypothesis. The article is strong in clearly

stating what the hypotheses are and that the LOS decreased and that mobility had increased and

the hypothesis are easily identified within the article. The article was weak in stating what the

null hypothesis is.

Research Design

Evidence

In the article by Padula, Hughes & Baumbover (2009, p. 327), they clearly state that the

study used the “nonequivalent control group design”. It is clearly stated under the headings

“Research Methods” and “Design” what control group design was used as their research method.

In addition, it is clearly stated under this heading what the independent and dependent variables

are. The independent variable is “mobility protocol” and the dependent variables are “functional

status and LOS” (Padula, Hughes & Baumbover, 2009, p. 327).

Support

“The research design is the plan for how the study will be conducted” (Nieswiadomy,

2012, p. 37). There are several kinds of research designs. One example is Quantitative designs

which consist of experimental and non-experimental research. The experimental research

focuses on the cause and effect relationship of the research which means that one happening

causes another. Experimental studies involve exploiting the independent variable which is the

cause and then measuring the dependent variable which is the effect (Nieswiadomy, 2012, p.


114). Experimental design is then broken down further into three sub groups. These include true

experimental designs, quasi-experimental designs, and pre-experimental designs. True

experimental designs are designs where the researcher has a vast amount of control over the

research. In order to create a true experimental design the researcher must have manipulation of

the independent variable, a control group, and a random assignment of study participants

(Nieswiadomy, 2012, pp. 118-119).

Three types of true experimental design discussed in the text are the pretest-posttest

control group design, the posttest-only control group design, and the Solomon four-group design.

The pretest-posttest control group design is the most used research design. It consists of random

selection of groups, one control, and one who receives the experimental treatment. Both groups

are given a test before and after treatment or perceived treatment. Equality of groups is able to

be determined prior to initiation of treatment. The posttest-only control group design is the same

as the pre and posttest control group except there is no pretesting. The Solomon four-group

design is made up of two control groups and two experimental groups with randomly assigned

participants. While only two of the groups are pretested, all of the groups are post tested

(Nieswiadomy, 2012, pp. 119-121).

The Quasi-experimental designs are those designs where there is neither a control group

nor where the study participants are not randomly assigned. When using this type of research

design the researcher uses pre-established groups for the experimental and control groups. The

nonequivalent control group design is a sub category of the quasi-experimental design group.

The nonequivalent control group design is the same as the pre and posttest design group;

however, there are no random assignments of participants to the groups (Nieswiadomy, 2012, pp.


121-122). Non-experimental research is descriptive and does not involve manipulation of the

research (Nieswiadomy, 2012, p. 123).

Internal and external validity is associated with experimental studies. Internal validity

refers to the degree in which changes in the effect can be credited to the cause. External validity

refers to the level at which study results can be influenced by outside items (Nieswiadomy, 2012,

pp. 115, 117). Examples of things that can affect the internal validity of a study are selection

bias, history, maturation, testing, instrument changes, and mortality or attrition. Examples of

things that can affect the external validity include the Hawthorne, the experimenter effects, or

reactive effects of the pretest. A control group is needed so that the effects of the experimental

group can be tested. Without a control group, you cannot get a good idea of what the research is

trying to show (Nieswiadomy, 2012, pp. 115-117).

Analysis

The research design of the nonequivalent control group design in the mobility article is

weak due to the threat of internal and external validity. The internal validity is decreased due to

the groups not being equal. The external validity is decreased as well because the groups cannot

be replicated. The two groups in the study are not equal and the results may be a result from

sampling bias.

What is concerning about the groups is the Mini Mental State Exam (MMSE). This part

of the study requirement can be confusing as in one area it states that participants were used only

if the MMSE was 24 or more. However, in another area it reports that those with MMSE lower

than 24, the significant other’s perception of the patient’s abilities was taken into consideration

(Padula, Hughes & Baumbover, 2009, p. 329). This can skew the groups and because of this it

makes the research design of the article weak. The article is strong in that the research design is


clearly identified. There is a decrease in internal validity because the groups are not equal, and a

decrease in the external validity because you are not able to externalize the results of this study

to the outside population.

Sample and Study Design

Evidence

The article begins by clearly stating the study is geared toward older hospitalized adult’s

population. The article also reveals a "sample" heading to locate the sample selected for this

study which was of adults 60 years or older admitted with medical diagnoses to one of two

nursing units (Padula, Hughes & Baumbover, 2009, p. 327). The population was picked from

medical patients versus surgical patients. The sample size was also clearly stated in this section

as 50 or 25 in each unit. The sample also had a length of stay 3 or greater days, was able to

speak English, and did not have physical abilities that would limit the ability to be mobile. The

sample were also cognitively able to participate or had a significant other would could

participate. This was determined through the use of a mini mental exam with a score of 24 or

better. In order to select the sample, a research nurse screened 453 eligible patients and came up

with a sample size of 84 and then eliminated patients for various reasons until 50 were selected

(Padula, Hughes & Baumhover, 2009, p. 327).

Support

According to Nieswiadomy (2012, p. 146), a population is a complete set of persons or

objects that possess some common characteristic of interest to the researcher. The goal of

sampling in a quantitative research is to be able to make generalizations about the population

from which the sample was drawn (Nieswiadomy, 2012, p. 146).


The population consists of a target and accessible population. The target population is

people or things who have the same set of criteria for the researcher to study. It can be a

challenge to obtain a population with the same set of criteria, so the researcher may use

accessible population or study population to obtain a sample that allows the researcher to report

conclusions about the generalities of the study findings (Nieswiadomy, 2012, p. 146).

An entire population is not generally used in a research study because it is not possible to

gain access to the entire population, so a sample is used instead. Samples are chosen through

two types of sampling: probability and nonprobability (Nieswiadomy, 2012, p. 147). Probability

or random sampling involves taking random samples in a systematic, scientific process, to obtain

a representative sample of a population (Nieswiadomy, 2012, p. 147). There is no guarantee in

random sampling that the results will be the same as what it would be with a total population, but

the hope is the sample selected would mimic that of a total population study.

There are four types of random sampling: simple, stratified, cluster and systematic. In a

simple sampling method, each element chosen has an equal chance of being selected. A method

of obtaining the sample is identified and examples include drawing a slip of paper out of a hat or

using a table of random numbers to choose from. Advantages include that little knowledge of

the population is needed, unbiased probability methods, easy to analyze and compute errors,

increases probability that the sampling is representative and assures adequate number of cases

for subgroups. Disadvantages include that a complete list of the population is necessary and the

process is time consuming and expensive (Nieswiadomy, 2012, p. 148).

The stratified sampling method divides populations into a strata format. The advantages

are that the method increases the probability that the sample is representative and it assures the

adequate number of cases for subgroups. The disadvantages include that the method requires


accurate knowledge of the population, is costly to prepare the stratified list, and is more

complicated (Nieswiadomy, 2012, pp. 148-150). The cluster sample uses groups rather than

people to select the population. Advantages include that the method saves time and money, and

arrangements made with the small number of sampling units and characteristics of clusters as

well as those of population can be estimated. The disadvantages include larger sampling errors

than other probability samples, requires assignment of each member of the population uniquely

to a cluster, and statistics are more complicated (Nieswiadomy, 2012, pp. 150-151).

Systematic sampling is to obtain listing of the population, determine the sampling side,

determine sampling intervals, select random starting point and select every kth element, for

example, every 5th, 10th or 15th element. Advantages include that this method is easy to draw the

sample, is economic, and is a time saving technique. The disadvantages include that the samples

may be biased if order of the population is not random, and population members do not have

equal chance of being drawn (Nieswiadomy, 2012, pp. 151-152).

Nonprobability sampling methods select elements from a population in a nonrandom

method and are more likely to produce a more biased sample. There is no guarantee that element

in a population will be selected, but most nursing research studies use this type of sampling

method. The methods used in nonprobability sampling include convenience, quota, and

purposive. Convenience sampling uses people or objects that are readily available. Snowball

sampling or network sampling is a method of convenience sampling where people give the

names of other people they know that fit the qualifications of the study. Quota sampling, like

stratified sampling, divides the population into a strata and selects from the strata by means of

convenient samples. Purposive or judgmental sampling is handpicking subjects by the

researcher or an expert (Nieswiadomy, 2012, pp. 152-154).


Other important items in sampling include longitudinal studies which include following

the subject over a period of time in the future, whereas a cross-sectional study examines the

subject at one point in time (Nieswiadomy, 2012, p. 154). Sample error is the difference

between data obtained from samples and data that would be obtained if an entire population was

studied. Sampling bias occurs when samples are not carefully selected (Nieswiadomy, 2012, p.

161).

Analysis

The researchers in this study did well at explaining the sample size and population used

as evidenced by the literature that the population was over the age of 60 and took place in 2 units

that are similar within a hospital setting. However, the use of the sampling was weak. The

sampling was consistent with the age population and that they were in a hospital setting, had to

have the ability to be mobile and were cognitively intact, but there was no comparison to the

level of illness and impact on the diseases that impacted the patients, therefore the groups may

not be similar at all. There was not enough information about the groups and how they were

assigned.

There was also involvement by the significant other if the patient did not score greater

than 24 on a mini mental exam; however, there was no discussion of the support systems

involved that may have improved the chances of mobility for the patients involved in the study.

The sample group of the patients selected was rather small, but maybe not. There was no

description of the amount of admissions each unit actually received and if this was or was not an

adequate sample size as compared to the patient turnover. There could be many other factors

that could have attributed to increasing the mobility of the patients involved in the study.


The internal and external validity were again decreased in this section of the mobility

article. For the internal validity, the groups are not equal even though the researchers tried to do

internal and external conclusion. The external validity was decreased because there was no

demographic data provided about the population to know if these groups were even similar.

Data Collection Methods

Evidence

A research nurse screened 453 patient records for study eligibility. In this screening she

was able to register 84 patients for the study. There were, however, 34 of those 84 that had

either withdrawn or been disqualified due to not meeting criteria which left a total of 50

participants (Padula, Hughes & Baumhover, 2009, p. 327). An advanced practice nurse with

expertise in gerontology and geriatrics actually collected the data from the screened and

approved participants. The nurse was trained by the geriatric clinical nurse specialist and the

principal investigator. The nurse collected data and tracked the data on a spreadsheet. The

spreadsheet included several items including gender, diagnosis, use of assistive devices, fall risk

assessments, mobility restrictions, use of therapies, length of stay, first and number of times out

of bed, and type of out of bed activity. This information was gathered via chart review, and

discussions with nursing staff and the patients themselves.

The Barthel Index (BI) and the Get Up and Go test were also tools that were utilized for

data collection. The BI measures the ability of one to complete self-activities of daily living.

The BI in this case was used to measure self-perceived levels of function at admission, 2 weeks

prior to admission, and at discharge. The Get Up and Go test was used to determine patient’s

abilities to stand from a chair, ambulate 3 m, turn around, ambulate back and then return to

sitting in a chair (Padula, Hughes & Baumhover, 2009, p. 328). This was completed on


admission and at discharge. Cognitive status of the study sample was also tested via the Mini

Mental State Exam (MMSE). For those with MMSE scores below 24 the subject’s significant

other was utilized for information (Padula, Hughes & Baumhover, 2009, p. 329). The

researchers conducted their study at a private, not for profit 247 bed acute care facility in

Providence, Rhode Island. Two nursing units similar in size and patient type were used for this

study.

Support

According to Nieswiadomy (2012, p. 165), there are four levels of measurement. These

levels include nominal, ordinal, interval, and ratio. Nominal levels of measurement include the

naming or categorizing of the events. These categories are distinct from one another and are

called mutually exclusive categories. Additionally, these categories include all of the possible

ways of categorizing the data which is referred to as exhaustive categories. The number of

categories can range from two to several. This type of data is acquired via counting the rate or

percentage of incidents in each category. Some examples of nominal data include gender or

marital status. Nominal data is the least precise of the level of measurement methods

(Nieswiadomy, 2012, pp. 164-165).

The next level of measurement is called ordinal level of measurement. Ordinal level of

measurement is data that can be rank ordered and placed into categories. Differences between

the ranks cannot be distinguished. Data represents an order instead of an amount (Nieswiadomy,

2012, p.165). Interval level of measurement consists of real number data such as ages of

participants. This data can be ranked and placed into categories and the distance between the

ranks can be determined (Nieswiadomy, 2012, p. 165). The last level of measurement is the ratio

level of measurement. This is the most precise level of measurement because the data can be


ranked, placed into categories, the distance between ranks can be determined, and a natural zero

point can be determined (Nieswiadomy, 2012, p. 165).

In the text, Nieswiadomy indicates that there are several ways in which to collect the

data. These include interviews, attitude scales, Delphi techniques, observational methods,

physiological measures, preexisting data, psychological tests, Q-sort, questionnaires, and visual

analogue scale (Nieswiadomy, 2012, pp. 328-329). Attitude scales are “self-reported data

collection instruments that ask respondents to report their attitudes or feelings on a continuum”

(Nieswiadomy, 2012, p. 316). The Delphi technique “uses several rounds of questions to seek a

consensus on a particular topic from a group of experts on that topic” (Nieswiadomy, 2012, p.

318). Pre-existing data is data that has been previously obtained but not used for research

purposes (Nieswiadomy, 2012, p. 323). Q sort or Q methodology is where “subjects are asked to

sort statements into categories according to their attitudes toward, or rating of, the statements”


Finally, the visual analogue scale is where “subjects are presented with a straight line

anchored on each end with words or phrases that represent the extremes of some phenomenon”

(Nieswiadomy, 2012, p. 326). For example, the 0-10 pain scale that we use to determine pain

levels. The researcher effect or experimenter effect is when the person conducting the research

skews the data by influencing the subject’s behaviors with their own behaviors and attitudes


Another thing that can skew the data results is the Hawthorne effect. This occurs when

the study participants are aware they are being monitored and their behaviors are influenced

because of this (Nieswiadomy, 2012, p. 117). It would be difficult as a nurse not to affect your


patient’s behavior. The patients knew about the study because they had to be in agreement to

participate, so there would have to be some behavior modifications.

According to Nieswiadomy (2012, p. 166), what is important for data collection is to ask

these five questions: Who? What? Where? When? How? You need to know who will be

collecting the data, what type of data is going to be collected, where will the collection of data

occur, when will it be collected, and how will it be collected (Nieswiadomy, 2012, pp. 166-167).

Analysis

The authors did a good job in describing the who, what, where, and when of the data

collection; however, they did a poor job of explaining the why. The information was jumbled

together and not clear cut. It was hard to determine which levels of measurements they were

using for this study. It feels as if the way in which they chose to conduct this study made it very

difficult to really get good accurate results from each patient

The Hawthorne effect, as well as the researcher effect, could be a factor in this study as

participants were aware of the study being conducted and were asked questions based on their

perception. The author should have just stuck to concrete facts and not used perception as this

can be highly interpretational. It also feels as though this particular study was not very well

thought out and that there are just too many variables in this situation. There are a lot of

variables so it is difficult to know how valid the study is.

This section is weak as there were not enough specifics as to how the data was collected.

The internal validity is decreased due to there not being enough specific detail as to how the data

was collected. The external validity is also decreased because the Hawthorne and researcher

effects may have contributed to the study results.


Instruments

Evidence

The instruments used and how they were used are listed under the levels of measurement.

The data collected by the nurse for the spread sheet is an example of nominal data and interval

data, whereas the Barthel Index (BI) and the Get Up and GO instruments are examples of ordinal

data collection. The researchers were not specific in their descriptions of the reliability and

validity of their chosen instruments. The article does indicate that the BI is the standard for

clinical research purposes, and that when compared to the Frail Elderly Functional Assessment

the BI was reported to be a better tool overall (Padula, Hughes & Baumhover, 2009, p. 328). In

regards to the Get Up and Go instrument, the article indicates that the instrument has been shown

to be reliable and valid and has been correlated with the BI instrument. Again, there are not any

other specifics as to why or how this instrument has been determined to be reliable and valid.

Support

According to Nieswiadomy the practicality, reliability, and validity of the instrument

must be considered when choosing data collection methods. Practicality of the tool must first be

determined. In order to determine the practicality of the instrument, one must consider the cost

of the instrument and the appropriateness of the instrument to the study population. One must

also consider if there are any specialists needed to conduct or interpret the data (Nieswiadomy,

2012, pp. 168-169).

Reliability of the instrument must then be examined. This is measured by the consistency

and stability of the instrument. The extent of the reliability is determined by the correlation

coefficients. Correlation coefficients are determined by two sets of scores or between the ratings

of two judges. The higher the correlation coefficient, the more reliable the instrument is.


Generally speaking, the more items that the instrument contains the more reliable it is. However,

reliability does not always sustain itself over time. It must be continually re-evaluated as it is

used throughout the study (Nieswiadomy, 2012, p. 169). The text goes on to indicate that there

are three different types of reliability. These are stability, equivalence, and internal consistency.

The stability reliability of a study refers to the consistency of the study over time

(Nieswiadomy, 2012, p. 169). The equivalence reliability refers to the level in which two

different forms of an instrument achieve the same results. It can also refer to two or more

observers using one instrument and achieving the same result (Nieswiadomy, 2012, p. 170).

Lastly, internal consistency reliability refers to the amount of all items on the instrument that

measures the same variable. This type of reliability is only used when testing one concept at a

time (Nieswiadomy, 2012, p. 171). Finally, the validity of the instrument must be determined.

The validity is determined by the instruments ability to gather the intended data. The subject

matter of the instrument is up most important when determining validity of the instrument.

Validity of the instrument is based on a panel of experts or examination of the current literature

on the topic.

There are four subgroups to validity: face, content, criterion, and construct

(Nieswiadomy, 2012, p. 171). Face validity is when the instrument shows at first look that it is

measuring what it is intended to measure. “Content validity is concerned with the scope or range

of items used to measure the variable” (Nieswiadomy, 2012, p. 172). Criterion validity is when

the instrument is assessed for determination of participant’s responses now or in the future.

There are again subgroups under criterion validity which are concurrent validity and predictive

validity. Concurrent validity refers to the way the instrument compares with another instrument


that measures the same thing, and predictive validity refers to the ability of the instrument to

predict the behavior of the participants in the future.

Lastly, construct validity, which is the hardest to measure, refers to the level of the

variable that is not directly observable. It is developed from an underlying theory that is used to

explain the variable. Construct validity also has two subgroups which are known-groups

procedure and factor analysis. Known-groups procedure refer administration of the instrument

in question to two groups who are expected to give different answers, whereas factor analysis

refers to the methods used to identify groups of connected objects on the instrument

(Nieswiadomy, 2012, pp. 173-174). Reliability and validity are used together intimately.

Generally reliability is determined first as it is a precursor to validity (Nieswiadomy, 2012, p.

174). Instruments must be reliable and valid so as not to skew the data. If the instrument is not,

then the research will not be accurate and the data obtained from the research will not have

meaning.

Analysis

There is not enough information on the reliability and validity of the instruments used in

this research article. The use of the BI instrument in this particular case is based on patient

perception. The purpose of this study was to determine if the nurse-driven mobility protocol had

an impact on functional decline in the hospitalized patient. To do this, concrete data should be

used and not the perception of the patient because the patient perception is not always reality.

One patient’s perception is much different than another’s. It is not known for sure that these

instruments really measured accurately what the researches intended. The perception of the

patient is not a reliable source of information as so much can skew this. This study would have


been better served using instruments such as the Tenetti balance scale or comparing ambulation

distances at admission and at discharge.

There is just not enough information to assure validity of the instruments or the results of

the research so this section is weak. The researchers do not explain to the reader the instruments

used. There is again a decrease in the internal and external validity because the article does not

state the reliability and validity of the instruments.

Data Analysis

Descriptive statistics

Evidence. In the mobility article, descriptive statistics were done for the study variables

and to compare the two groups on the baseline characteristics that were examined (Padula,

Hughes & Baumbover, 2009, p. 329). Two contingency type tables were used in the article.

One showed the characteristics of the nursing staff for the treatment and control groups. The

other table showed the Barthel scores for the treatment and control groups. Measures of central

tendency stats were used as they used the mean to describe the average age and diagnoses of the

sample groups. The mean age was 80.4 and mean diagnosis 6.7 (Padula, Hughes, & Baumbover,

p. 329).

Support. Descriptive statistics are “statistics that organize and summarize numerical

data gathered from samples” (Nieswiadomy, 2012, p. 205). There are several ways that

descriptive statistics can be categorized. Nieswiadomy categorizes them into four different

groups. They are as follows: measures to condense data, measures of central tendency, measures

of variability, and measures of relationships.

First, measures to condense data are statistics that summarize and condense the data,

which involves frequency distributions, percentages, and graphic presentations. Frequency


distributions are used to report the numerical values from the data which are listed from the

lowest to highest or vice versa. Percentages are used to represent the proportion of a subgroup to

compare it to the total group (Nieswiadomy, 2012, p. 210). The percentage will be the most

useful and valid if the size of the total group is at least 20. Graphic presentation involves putting

the data into a graph such as a bar graph, histogram, or a frequency polygon (Nieswiadomy, pp.

208-210).

Second, measures of central tendency are “statistics that describe the average, typical, or

most common value for a group of data” (Nieswiadomy, 2012, p. 211). Measures of central

tendency include mode, median, and mean. The mode is the value that occurs the most often in

the group of data, the median is the middle value of the data, and the mean is the average sum of

the data of the group.

Third, measures of variability statistics describe how the values spread out in the

distribution of values. The range, percentile, standard deviation, variance, and z scores are used

in variability statistics. The range is the distance between lowest and highest value in the group

of scores, and a percentile is the data point below that puts a certain percentage of the values in a

frequency distribution. A standard deviation is a statistic that shows the average variation of all

the values from the mean in a set of data, the variance is the square of the standard deviation, and

the z score indicates how many standard deviations that a value is from the mean of the set of

values (Nieswiadomy, 2012, pp. 213-214).

Lastly, measures of relationships are concerned with the correlation between the

variables. Measures of relationship include correlation of coefficients, scatter plots, and

contingency tables. Correlation coefficients are statistics that present “the magnitude and

direction of a relationship between two variables” (Nieswiadomy, 2012, p. 215). Correlation


coefficients are symbolized by the letter r. These vary between -1.00 and +1.00. A correlation

coefficient of -1.00 shows a perfect negative relationship whereas a +1.00 shows a perfect

positive relationship. If the correlation coefficient is 0, then there is no relationship in the

variables. A scatter plot shows the relationship of the two variables by placing the variables on

an X and Y axis on a graph, and a contingency table is a table that shows the relationship

between the sets of nominal data in a visual sense.

Analysis. The article stated that descriptive statistics were used, but was not clear as to

which types they used. Only two contingency type tables were used and the information used in

the tables was not helpful with what the research article was about. It would have been more

beneficial to have tables or graphs to show the results of the study hypothesis that were presented

in the article. Only one descriptive statistics was used, which was the age of the participants, so

this section of the article is weak. Both the internal and external validity were decreased due to

not having enough information.

Inferential Statistics

Evidence. In the article by Padula, Hughes & Baumbover (2009, p. 329), they used

inferential statistics to determine the differences between the control and treatment group on the

dependent variables. The inferential statistics are found in the results section of the article.

When a p value is seen in the article, it is known that an inferential statistic was used. Parametric

statistical tests are used in this article because population parameters are used.

Subjects in the treatment group showed a decreased fall risk score on admission (P = 0.7)

(Padula, Hughes & Baumbover, 2009, p. 329). The Barthel scores upon discharge for the

treatment was higher and the control group was lower in comparison to their admission scores.

The treatment group was P = .05 and the control group was P = .006 (Padula, Hughes &


Baumbover, 2009, p. 329). For the Up and Go test, both the treatment and control groups score

had improvement in p scores. For hypothesis 1 of the study, the treatment group had greater

improvement in functional status than the control group at P = .05 (Padula, Hughes &

Baumbover, 2009, p. 330). Hypothesis 2 showed the length of stay at P < .001 (Padula, Hughes

& Baumbover, 2009, p. 330).

Support. According to Nieswiadomy (2012, p. 225), inferential statistics are types of

statistics that use the characteristics of the samples or populations, and uses sample data to make

an interpretation about the population, and are based on the laws of probability. The purpose of

inferential statistics is to estimate the population parameters from the sample data and to test the

hypothesis.

The level of significance is the probability of rejecting the null hypothesis when it is true

(Nieswiadomy, 2012, p. 320). The letter p or the Greek letter alpha symbol is used to represent

the probability level of the test. In nursing studies, the most common level of significance is p =

.05, which means that the researcher is wrong 5% (5 times out of 100) of the time when rejecting

the null hypothesis (Nieswiadomy, 2012, p. 231).

The t test is a test that examines the difference between the mean values of two groups.

This is one of the most popular tests in statistics. The t test is valuable with small sample sizes

but can be used with any size sample. The t test is a parametric test, which means that the

sample data has been taken from populations that have been normally distributed and have

similar variances. There are two forms of t tests. One uses independent variables and the other

uses dependent variables. The independent t test is used when there is no relationship between

the two sets of scores being compared, whereas the dependent t test is used when one set of

scores is dependent on the other set of scores (Nieswiadomy, 2012, p. 235).


In Nieswiadomy’s book, this chapter is confusing, but did find it helpful in using the term

“chance” (Nieswiadomy, 2012, p. 225) to better understand the meaning of inferential statistics.

It is also noted that the terms sampling error and random error are used interchangeably.

Additionally, it made more sense in understanding that the larger the difference found between

the groups, the lower the probability that the difference occurred by chance (Nieswiadomy, 2012,

p. 225).

Analysis. The article provides a large amount of statistical data which is somewhat

confusing to understand. Having the statistics comparing the findings of the treatment and

control groups placed in a graph or table would make it easier to follow. The information

submitted in the article was really neither weak nor strong. It does state in the article that the

differences in the fall risk scores were not significant, but overall the article could have done a

better job on providing more detail for this information. There was no impact of internal and

external validity in this section.

Study Findings

Evidence

The findings that the researchers in the mobility article present are that the subjects in the

treatment group had shorter lengths of stay and ambulated in the hallway earlier than those in the

control group, which supports the hypothesis that “older adults who participate in a mobility

protocol will maintain or improve functional status from admission to discharge” (Padula,

Hughes & Baumhover, 2009, p. 327). The findings supported that the treatment group showed

greater improvement using the Barthel Index instrument than the control group as well. The

Barthel Index measures the individual’s capacity to perform certain ADL’s. The hypothesis that

the treatment group will show a reduction in length of stay as compared to the control group was


also supported. Since there were some significant limitations due to variables between the

groups, it is hard to determine how strong the support of the findings really is.

Support

According to (Nieswiadomy, 2012, p. 247), the study findings are the final phase of the

research where the findings are presented with empirical data and facts and then discussed. At

the end of the research, implications and conclusions should be pulled together.

Recommendations should be given according to data collected and the findings. The study

findings should state what has been learned and also make recommendations about what should

be studied in the future. This should all be placed under separate headings at the end of the

report such as: conclusions, implications, recommendations, findings, and discussion of findings.

In a quantitative study such as this the results should be presented as facts or empirical data,

meaning it can be seen or heard. The opinions or reactions of the study should not be

personalized. The findings need to be presented in past tense. Data should be collected and

analyzed before the research report is written.

Descriptive statistics should be used to describe the sample and present the findings.

Inferential statistics, which are used to make inferences or decisions about a population, should

be used when presenting the findings. These statistics are usually presented in narrative form or

in tables. If the findings are presented in narrative form, they must be clear and succinct. The

narrative form usually contains direct quotes from the participants. In a quantitative study the

hypotheses are tested and the report should present the data that supports or fails to support the

hypotheses. In a study finding there is information that should always be included, such as

degrees of freedom and probability value. Tables should be used to organize data, according to

(Nieswiadomy, 2012, pp. 247-250).


Analysis

The findings should be under different headings, but this article goes from the results,

into the discussion, and then the conclusion without separate headings for the findings,

implications, and recommendations. The findings were at the final phase of the report as they

should be; however, the report does not state what has been learned or make references to

possible future study. It does make the recommendation that early ambulation and ongoing

ambulation help improve functional status and shorten length of stay.

The report was presented in the past tense. The data was gathered and analyzed prior to

writing the report, so it is not known how clearly and concisely the findings were presented.

Statistics were given in table and in narrative form. Once again, the findings are weak as there

were many limitations in the study as well as several variables that can skew the findings. The

study was not well thought out and the groups were distributed evenly to get a good picture of

what results they were looking for. As far as the internal and external validity goes, there was no

impact.

Discussion of Findings

Evidence

In the mobility article by Padula, Hughes & Baumhover (2009, p. 330), both hypotheses

were supported with the improvement in the functional status of the treatment group, and the

reduction in length of stay in the treatment group as compared to the control group. In the

research the probability, limitations, and instruments used were discussed.

Support

According to Nieswiadomy, the discussion of findings should be more subjective than the

presentation of findings. In this section, the researcher makes interpretations of the findings.


Nieswiadomy (2012, p. 249) states “the findings are interpreted in the light of the theoretical

framework and within the context of the literature review”. There should not be any literature

sources cited here that were not referred to in the literature section of the report, as it would seem

that the researcher gathered information after data was already collected to support the study

findings.

In this section, the researcher talks about the features of the results that agree or do not

agree with the previous research collected. The researcher also discusses study limitations,

which are weaknesses in the study, and uncontrolled variables which may affect results.

However, this section is not a place to list all weaknesses and disregard findings based on

whether they agree with the theoretical framework, which is based on a theory that there is a

relationship between concepts. In this section, interpretations of findings are presented and the

strengths and weaknesses of the study should only be mentioned.

Analysis

The relationship between concepts in the mobility article is the relationship between

increased mobility on length of stay and functional status. The framework is the study of

increased mobility on functional status and length of stay in hospitalized patients. The

limitations are some of the variables between the control group and treatment group. The

treatment group had a lower fall-risk score than the control group, so this could skew the results

as they had some mobility issues to begin with. The article recognized that the functional level

of the control group was lower than that of the treatment group, but that did not feel it affected

the results significantly. It would seem that this, along with the lower fall-risk score, would have

a significant effect on the findings. The researchers stated they calculated the differences in

groups using inferential statistics (Padula, Hughes & Baumhover, 2009, p. 329).


The interpretation of the findings, according to the article, was consistent with the

literature, but it was not discussed how the limitations or weakness affected the findings, only

that these differences may have affected the findings. The researchers did not generalize the

results to all populations. The results were specific to the elderly population in an acute hospital

unit. It appears that all sources used in the report were accounted for in the reference section.

There were not any suggestions in the mobility article found to improve upon the research.

This section of the article is weak and there was no threat to the internal and external

validity. There was no information provided regarding the socioeconomic status, nutritional

status, demographics, income, or insurance information on the participants in the study.

Conclusions, implications, and Recommendations

Evidence

In the mobility article, a conclusion is provided at the end stating that the research does

support literature. The conclusion of this article is very short and to the point. It states that the

findings are suggestive of functional decline starting prior to admission to the hospital and

continues if early ambulation and mobility is not initiated which can in turn be linked to

increased length of stays in the hospital.

Support

According to Nieswiadomy, in the study conclusion the researcher summarizes the

findings and demonstrates what has been learned by the research. The researcher validates the

worth and the meaning of the research study (Nieswiadomy, 2012, p.303). The problem is again

referred to as well as the purpose, hypothesis, and theoretical framework. It should be made

clear to the reader what the study has revealed in each of these parts. The sample size of the

study must be considered when drawing conclusions from the findings. The conclusion should


not just reinforce the findings, it should go beyond the findings by applying them to similar

populations. It is permissible to use the word appears in the conclusion because one cannot

prove the findings when research is conducted using people.

Analysis

In the mobility article the conclusion is quite brief. The problem is identified at the

beginning of the paragraph and the purpose is clearly stated. The hypothesis is referred to in the

section as well. There is not a strong theoretical framework. This conclusion does not clearly

apply the findings to populations other than the sample groups, so this is weak. The conclusion

could have been more in depth. It does generalize the problem to older adults in the beginning of

the conclusion paragraph. The researchers do not try to state that the findings are absolute rather

that they may suggest the hypotheses are true, which is in keeping with the criteria for the

conclusion. In ending the paragraph, the researchers reinforce the theory of ambulation being an

important part of nursing care, but do not state why. There was no effect on the internal and

external validity in this section.

Conclusion

The conclusion of this article is that is overall weak. It does not speak to all of the

requirements set by Nieswiadomy. It is felt that the research project was a waste of time as isn’t

it just common sense that if you don’t get people up and moving while in the hospital they will

become weaker? Again, the whole article is weak and not very well thought out or prepared for.

Paper Conclusion

In conclusion, our student group found the article, “Impact of a Nurse-Driven Mobility

Protocol on Functional Decline in Hospitalized Older Adults” by Padula, C. A., Hughes, C., &

Baumbover, L. (2009), weak on many aspects, especially the theoretical framework. The


theoretical framework is not clear to the reader. The authors discussed the nurses in the control

group being educated on the GENESIS program, but did not describe exactly what the GENESIS

program is.

The purpose of this study was clearly defined, but the reader finds it difficult to find the

problem statement. Another weak feature of this article was that the study groups were not equal

due to differences in fall-risk factors, pre-functional, among other variables, so it is difficult to

determine the validity of the study. There was not enough information given on the study

groups. The reader is aware that the study groups were selected by convenience sampling, but

there is not enough information about that population of patients selected, such as the

socioeconomic background, insurance coverage, level of education, and demographics to really

compare the groups for equality. The statistics were not explained well. There were not many

tables or graphs to make the findings clear. The article stated which instruments were used, but

were weak on discussing the reliability and validity of the instruments.

Some of the stronger points of the article were the hypotheses. These were made clear to

the reader and were supported by the findings. Another stronger section of the article was the

discussion of data used. The article gave details as to who gathered the data, what the data was,

and the location it was gathered from, but did not really explain why the data was collected. Our

group feels that more research needs to be conducted with fewer variables and more details to

better apply the findings of the study.

Overall, this study could have been organized better with more headings to differentiate

between the sections, explain in more detail what the nursing protocol was between the units

studied, and what was done differently with the control group and the treatment group.


However, we are in agreement that increasing one’s mobility during a hospital stay will decrease

complications and maintain function which will ultimately reduce the length of hospital stay.


References

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

NJ: Pearson.

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

on functional decline in hospitalized older adults. Journal of Nursing Care Quality,

24(4), 325-331.

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