Theory Paper Big Tank ONLY

Please contact me if you have any questions. It needs to be done by Sunday morning so I can proofread and make it my own. Do not worry about doing the introduction. The original theory that I am assigned to is the Theory of Unpleasant Symptoms. Please follow the detailed rubric and let me know if you have any questions.
1

N 5327: Exploration of Science and Theories for Nursing

Grading Rubric for Description & Evaluation of Theory Paper

Criteria

Levels of Achievement

Excellent/ Outstanding

90-100%

Above Average

80-89%

Average/

Acceptable

70-79%

Below Average/ Not Acceptable

60-69%

Failing

8 types of errors

(5 or less pts)
N5327 Exploration of Science and Theories for Nursing

Theory Description and Evaluation Paper Criteria

Identify a theory that uses a concept of interest that might be applied in research and nursing practice (clinical, education, or administration). The purpose of this paper is for you to describe and evaluate the theory using the following criteria. This is a professional paper in which headings, full sentences, paragraphs, correct grammar and punctuation, and correct citation of sources are required.

Introduction. Identify your concept of interest and briefly discuss why you chose that concept (explain whether it was observed in clinical practice, identified from relevant literature, or some other reason.) Identify the theory (that utilizes your concept of interest) which will be described and evaluated in this paper. Give the reader a sense of what to expect in this paper. The introduction should be one very short paragraph, and there should not be a heading for the introduction.

Theory Description. Provide a brief description of the theory using an original source or as close to the original source as possible. Include a brief discussion of the origins of the theory and the scope/level (grand, middle range, practice/situation specific) of the theory. Identify the major concepts of the theory and discuss how they are related (propositions). Pick two of the concepts, including your concept of interest, and state the theoretical definitions of these concepts. (30 points)

Application of Theory to Research. Find two published, original sources in which researchers used the theory as a framework to support their research. Briefly discuss how those researchers utilized the theory to support their research. Include in the discussion of each study the purpose of the study, how the researchers used the theory in their study, how the concept of interest was used in their study, and how the researchers operationally defined the concept of interest. (20 points)

Application of Theory to Practice. Briefly discuss how the theory might be used to support nursing practice (clinical, education, or administration). Include in the discussion the purpose of the practice application and how the concept of interest might be operationally defined in practice. Provide an example of how you might use the theoretical and operational definitions of your concept of interest in your future practice or research. Include a potential practice question based on the propositions of your theory. (20 points)

Theory Evaluation. Briefly discuss whether/how the theory appears to be accurate/valid (based on empirical testing of the theory as discussed above). Discuss generalizability of the theory. Summarize the strengths and weaknesses of the theory. Briefly discuss whether/how the theory is congruent with current nursing standards and current nursing interventions or therapeutics. Explain whether/how the theory is relevant socially and cross-culturally. Describe briefly how the theory might contribute to the discipline of nursing. (20 points)

Conclusion . Include a conclusion only if specified by your course section faculty.

Style & Format. The paper will include a title page (using specified format), 7-8 pages of text, and a reference list. It will be double-spaced, written in 12-point Times New Roman font, and have 1-inch margins. Professional and orderly presentation of ideas (precision, clarity, format, headings, grammar, spelling, & punctuation) with appropriate citation of sources in text and reference list is required. Up to 0.5 points will be deducted for each type of grammar, spelling, punctuation, or format error. (10 points)

Fall 2017 – Final version; Minor revision Spring 2018REVIEW PAPER

Integrative review: postcraniotomy pain in the brain tumour patient

Rebecca Elizabeth Guilkey, Diane Von Ah, Janet S. Carpenter, Cynthia Stone & Claire B. Draucker

Accepted for publication 17 November 2015

Correspondence to R.E. Guilkey:

e-mail: refoust@iupui.edu

Rebecca Elizabeth Guilkey PhD(c) RN

CCRN

PhD Candidate

Indiana University School of Nursing,

Indianapolis, Indiana, USA

Diane Von Ah PhD FAAN RN

Assistant Professor

Indiana University School of Nursing,

Indianapolis, Indiana, USA

Janet S. Carpenter PhD FAAN RN

Distinguished Professor and Associate Dean

for Research and Scholarship

Indiana University School of Nursing,

Indianapolis, Indiana, USA

Cynthia Stone DrPH RN

Associate Professor and Director of Health

Policy Management Doctoral Program

Indiana University Fairbanks School of

Public Health, Indianapolis, Indiana, USA

Claire B. Draucker PhD FAAN RN

Angela Barron McBride Endowed Professor

in Mental Health Nursing

Indiana University School of Nursing,

Indianapolis, Indiana, USA

GUILKEY R . E . , VON AH D . , CARPENTER J . S . , STONE C . & DRAUCKER C .B .

( 2 0 1 6 ) Integrative review: postcraniotomy pain in the brain tumour patient. Jour-

nal of Advanced Nursing 72(6), 1221–1235. doi: 10.1111/jan.12890

Abstract Aim. To conduct an integrative review to examine evidence of pain and

associated symptoms in adult (≥21 years of age), postcraniotomy, brain tumour

patients hospitalized on intensive care units.

Background. Healthcare providers believe craniotomies are less painful than

other surgical procedures. Understanding how postcraniotomy pain unfolds over

time will help inform patient care and aid in future research and policy

development.

Design. Systematic literature search to identify relevant literature. Information

abstracted using the Theory of Unpleasant Symptoms’ concepts of influencing

factors, symptom clusters and patient performance. Inclusion criteria were

indexed, peer-reviewed, full-length, English-language articles. Keywords were

‘traumatic brain injury’, ‘pain, post-operative’, ‘brain injuries’, ‘postoperative

pain’, ‘craniotomy’, ‘decompressive craniectomy’ and ‘trephining’.

Data sources. Medline, OVID, PubMed and CINAHL databases from

2000–2014.

Review method. Cooper’s five-stage integrative review method was used to assess

and synthesize literature.

Results. The search yielded 115 manuscripts, with 26 meeting inclusion criteria.

Most studies were randomized, controlled trials conducted outside of the United

States. All tested pharmacological pain interventions. Postcraniotomy brain

tumour pain was well-documented and associated with nausea, vomiting and

changes in blood pressure, and it impacted the patient’s length of hospital stay,

but there was no consensus for how best to treat such pain.

Conclusion. The Theory of Unpleasant Symptoms provided structure to the

search. Postcraniotomy pain is experienced by patients, but associated symptoms

and impact on patient performance remain poorly understood. Further research is

needed to improve understanding and management of postcraniotomy pain in this

population.

Keywords: brain tumour, craniotomy, integrative review, literature review,

nurses, nursing, pain, theory of unpleasant symptoms

© 2016 John Wiley & Sons Ltd 1221

info:doi/10.1111/jan.12890
Introduction

Background

Brain tumour is the seventeenth-most diagnosed cancer

worldwide, with 256,000 new cases of brain tumour diag-

nosed in 2012. Men suffer from brain cancer slightly more

frequently than women (Bondy et al. 2008, World Cancer

Research Fund International 2013, Central Brain Tumor

Registry of the United States 2014, Ferlay et al. 2015) and

incidence rates are higher in developed countries than in

lesser developed countries (Bondy et al. 2008, World Can-

cer Research Fund International 2013, Central Brain Tumor

Registry of the United States 2014). Scientific advances have

resulted in improvements in the diagnosis and treatment of

brain tumours (Bondy et al. 2008). In fact, 1- and 5-year

survival rates have increased from 7�3% in 1970 to over 18% in 2011 (Informational Services Division of the

National Health Services 2010, Cancer Research UK 2014,

Ferlay et al. 2015, Queen’s University Belfast 2015).

Approximately 90% of patients with brain tumours

undergo craniotomies for excision and removal of the

tumour to increase survival (National Cancer Institute

2014). Surgical procedures are generally understood to be

painful (McCaffery & Pasero 1999) but less is understood

about postcraniotomy pain. Healthcare providers commonly

believe that craniotomies are less painful than other types of

surgery due to lack of innervation in the brain (Hassouneh

et al. 2010, American Brain Tumor Association 2012) and

are thus less apt to treat pain. In addition, postcraniotomy

pain is often untreated or undertreated due to concerns that

it may mask neurological changes in these patients (Talke &

Gelb 2005, Durieux & Himmelseher 2007, Lai et al. 2012).

Pain is often associated with other symptoms including anxi-

ety and depression (McCaffery & Pasero 1999, Rocha-Filho

2015) and nausea and/or vomiting (Dolin & Cashman

2005). Understanding postcraniotomy pain in brain tumour

patients is important because postoperative pain is a com-

mon cause of delayed mobilization (Saha et al. 2013),

lengthened hospital stay (Chung et al. 1997, Casler et al.

2005, Saha et al. 2013), disability and decreased quality of

life (Andrasik et al. 2011, O’Connor & Dworkin 2011). In

addition, research has shown that under-treated, generalized

postoperative pain is a predictor of the development of per-

sistent pain (Macrae 2001, Dobrogowski et al. 2008, Watt-

Watson & McGillion 2011, Wu & Raja 2011, Lamacraft

2012). To date, postcraniotomy pain and the symptoms

associated with it is poorly understood. Researchers have

called for additional studies to understand influencing fac-

tors and associated symptoms of postcraniotomy pain and to

determine how to best treat it to prevent negative health out-

comes (Talke & Gelb 2005, Roberts 2005, Watson 2011,

De Oliveira Ribeiro et al. 2013, Rocha-Filho 2015).

Definitions and theory

The International Society for the Study of Pain describes

pain as a subjective sensory and emotional experience

(McCaffery & Pasero 1999, Watt-Watson & McGillion

2011, Gelinas et al. 2013). Pain is a complex symptom com-

prised of at least four dimensions (intensity, affect, quality

and location) (Puntillo et al. 2002, Jensen & Karoly 2011).

Physical, psychological, social and cultural factors influence

the experience of pain (Melzack 1999, Saha et al. 2013).

The Theory of Unpleasant Symptoms (TOUS), which

suggests that symptoms such as pain are multidimensional

and interactive, is commonly used to support pain research,

because it is relevant to practice and can be used as a

Why is this research or review needed?

� Brain tumour patients have long been believed to experi- ence little pain postcraniotomy due to lack of innervation

in the brain.

� Understanding symptoms correlated with postcraniotomy pain in brain tumour patients will help healthcare provi-

ders provide better treatment.

� Addressing untreated and undertreated postcraniotomy pain will improve patient-centred outcomes and quality of

life.

What are the key findings?

� Postcraniotomy patients experience significant levels of pain, but current treatment of postcraniotomy pain lacks

evidence-based guidelines.

� Postcraniotomy pain in brain tumour patients may be asso- ciated with nausea, vomiting and changes in blood pres-

sure and may play a role in health care use such as longer

hospital stays.

How should the findings be used to influence policy/ practice/research/education?

� Understanding the manner in which postcraniotomy pain unfolds should inform healthcare providers’ recognition of

the symptom.

� Recognition of the intensity of postcraniotomy pain and its impact should lead to timely treatment of the symptom

and improve patient outcomes.

1222 © 2016 John Wiley & Sons Ltd

R.E. Guilkey et al.

framework for making decisions related to patient care

(Myers 2009, Lenz et al. 2013). The TOUS includes three

main concepts: (1) physiological, measureable symptoms

experienced by the patient; (2) influencing factors which

alter the patient’s experience of the symptom and (3)

patient performance (Lenz et al. 1997, 2013). Influencing

factors are physiological, psychological and situational in

nature and can catalyse each other affecting patient perfor-

mance (Lenz et al. 1997, 2013). Performance is the impact

of the symptom on patient outcomes including functional

performance (the ability to physically function) and cogni-

tive performance (the ability to think) (Lenz et al. 1997,

2013). Researchers using the TOUS have termed groups of

associated symptoms as ‘clusters’ (Lenz et al. 1997). This

review will also use the term cluster to identify these groups

of co-related symptoms.

The review

Aim

The aim of this study was to conduct an integrative review

using the TOUS as a guiding framework to synthesize and

examine what is known about the phenomenon of pain in

adult (≥21 years of age), postcraniotomy, brain tumour

patients. Specifically, this review sought to answer the

following research questions: (1) What is the evidence for

postcraniotomy, postbrain tumour pain in adult (≥21 years

of age) patients hospitalized on intensive care units?; and

(2) What is the evidence for a postcraniotomy symptom

cluster associated with pain in adult (≥21 years of age)

patients hospitalized on intensive care units?

Design

Cooper’s (2010) integrative review method guided the

review. This method of integrative review was chosen

because it provides a systematic framework to synthesize the

current literature about postcraniotomy pain in the brain

tumour patient (Whittemore & Knafl 2005, Cooper 2010).

Cooper’s method includes five stages: advance formulation of

the problem, data collection, data extraction, evaluation,

analysis and interpretation (Cooper 2010). The formulation

of the problem, the first stage of the method, was informed

by a preliminary literature search and the researchers’ clinical

experience that suggested a greater understanding of acute

postcraniotomy pain was warranted. The authors felt an inte-

grative review was necessary to synthesize the current litera-

ture and further the state of the science (Whittemore & Knafl

2005, Cooper 2010).

Search methods

Data collection, the second stage, consisted of a literature

search. Studies were identified for inclusion by purposive

searching of electronic databases including Medline, OVID,

PubMed and CINAHL. In addition, hand-searching of ref-

erences and an examination of citations from identified

published reviews were conducted. Two experienced

reference librarians provided consultation on the search

process. Search terms for all databases and searches

included traumatic brain injury; pain, postoperative; brain

injuries; postoperative pain; craniotomy; decompressive

craniectomy; and trephining. Inclusion criteria were as fol-

lows: (1) data-based quantitative and qualitative articles

focused on postcraniotomy pain in adult brain tumour

patients aged 21 or older; (2) published between 1 January

2000–12 December 2014; (3) English-language; (4) neuro-

surgical inpatients and (5) intensive care unit settings.

Abstracts, editorials, dissertations, theses, reviews and

articles concerning intraoperative pain control, end-of-life

care, or institutional practices were excluded.

Search outcome

The search strategy generated 115 studies. The studies

which were recorded in a Preferred Reporting Items for Sys-

tematic Review and Meta-Analyses (PRISMA) diagram

(Figure 1). A total of 109 potentially relevant studies

remained after the initial screening of titles for duplicates,

publication in English and publication dates. The remaining

abstracts were reviewed for type of study, population, study

setting and discussion of pain. After application of the

inclusion and exclusion criteria, we eliminated 83 addi-

tional articles from review, including five qualitative studies

that either did not meet inclusion criteria because they did

not focus on pain or the participants were not inpatients.

This resulted in a sample of 26 quantitative articles to be

reviewed in full-text format (Table 1). Data from eligible

studies were abstracted into tables listing general informa-

tion, level of evidence and concepts defined in the TOUS.

Quality appraisal

In the third stage, two authors completed a quality apprai-

sal on the 26 articles. Using a 3-point scale (yes, no,

unclear) described by Gazarian, they rated the studies on

nine criteria including aims, design, methods, sample,

ethical considerations, results, limitations, implications and

sponsorship (2013). The studies were also appraised for

bias using the Cochrane Risk of Bias tool. Twenty-one of

© 2016 John Wiley & Sons Ltd 1223

JAN: REVIEW PAPER Integrative review – postcraniotomy pain

the studies used a randomized design. Of the five studies

that did not use randomization, two were retrospective

(Thibault et al. 2007, Ducic et al. 2012) and three were

prospective trials (Irefin et al. 2003, Grossman et al. 2007,

Nair & Rajshekhar 2011). The team determined that these

five studies nonetheless met inclusion criteria and thus all

26 studies are included in the review.

Data abstraction

The fourth stage includes data analysis and interpretation

(Cooper 2010). In this stage, all of the included studies

were read in full and relevant data were extracted and tab-

ulated. Table 1 displays the authors’ names; dates and

countries of publication; purpose and design; sample, set-

ting and intervention; medication tested; and pain preva-

lence, incidence and intensity. (Table 1).

Data synthesis

In the fifth and final stage, the tabulated data were synthe-

sized to address the research questions (Cooper 2010). The

authors grouped the data into categories suggested by the

TOUS including incidence of pain, influencing factors, cluster

and patient performance (Table 2). Two of the authors (RG

&DVA) reviewed each study and verified the accuracy of data

as presented and over several meetings compiled the results.

Results

Description of the studies

Of the 26 studies included, all were pharmacological pain

management trials (pain medications) and most were ran-

domized, controlled trials (RCTs) (n = 21). The studies

included 1892 total patients and were originally designed to

test local wound infiltration or medications to control pain

(intravenous, intramuscular, oral medications, nerve blocks,

general anaesthesia) (Table 1). The medications that were

tested varied but mostly included bupivacaine, ropivacaine,

tramadol, parecoxib, paracetamol and morphine.

The mean ages of the participants in the studies ranged

from 45-55 and approximately equal numbers of men and

women were represented. The comprehensive search identi-

fied five qualitative studies; however, these did not meet

inclusion criteria (focus not on pain or participants not

inpatients) and were excluded from final analysis. The

majority of trials took place outside of the United States at

non-profit, urban, academic medical institutions. Only one

study reported racial characteristics of the sample that con-

sisted mostly of Caucasians (52 vs. 12 non-Caucasian)

(Morad et al. 2009). Reports included both supratentorial

surgeries and infratentorial surgeries with mean lengths of

surgery ranging between 200 and 300 minutes.

115 total papers screened from

electronic search of 4 databases (OVID

Medline, Nursing @ OVID, PubMed, and

CINAHL) 6 articles excluded for not meeting inclusion criteria (duplicates, not published

in English, published prior to 2000)

83 articles excluded for not meeting inclusion

criteria: 27 not solely brain tumor population

16 not pain focused 11 traumatic brain injury 8 pediatric/adolescent 6 technique/procedure

focused 5 not postoperative

5 review 4 healthcare staff focus

1 letter to editor

109 potentially relevant citations

identified

26 articles to be reviewed in full-text

format

Figure 1 PRISMA diagram of systematic search.

1224 © 2016 John Wiley & Sons Ltd

R.E. Guilkey et al.

Table 1 Summarization of studies.

Author, year, Country Design, sample size, medication Existence of pain and pain intensity, rating scale used

Bala et al. (2006)

India

Prospective, double-blind RCT; N = 40

Medication: Scalp nerve block (bupivacaine)

60% experienced moderate-severe pain in first

12 hours post-op (control)

25% experienced moderate-severe pain in first

12 hours post-op (intervention)

Rating Scale: NRS; scores 0-22�5 out of 100 Batoz et al. (2009)

France

Prospective, single-blinded study; N = 52

Medication: Incisional infiltration (ropivacaine);

nalbuphine postsurgery

VAS scores higher in control group

Persistent pain significantly lower in intervention

group at 2 months (56% in control group vs. 8%

in intervention group)

Rating Scale: VAS; scores 0-35 out of 50

Biswas and

Bithal (2003)

India

Prospective, double-blind RCT; N = 50

Medication: Incisional infiltration (bupivacaine)

vs. fentanyl

Additional medication needed in 60% of

bupivacaine group and 57% of fentanyl group

Rating Scale: VAS; scores 0-4 out of 10

Ducic et al. (2012)

United States

Retrospective interview of patients; N = 7

Medication: None tested

86% experienced pain greater than 80% on

migraine index

Rating Scale: VAS; scores 2-10 out of 10

Ferber et al. (2000)

Poland

Multi-stage prospective study; N = 35

Medication: Intravenous tramadol

Pain relief in 50% of patients receiving one dose;

in 88% of patients receiving 2 or 3 doses

Rating Scale: VRS; scores 0-4 out of 5

Girard et al. (2010)

Canada

Prospective, double-blind RCT; N = 30

Medication: Cervical plexus nerve block

(lidocaine and bupivacaine) vs. intravenous

morphine bolus

Similar pain scores between nerve block and

morphine groups

Rating Scale: NRS; scores 2-7 out of 10

Grossman et al. (2007)

Israel

Open, prospective, double-blind non-randomized,

placebo- controlled study; N = 40

Medication: Incisional infiltration (lidocaine and

bupivacaine); metamizol intra-operatively

13 patients needed additional pain medication

Rating Scale: NRS; scores 0-4 out of 10

Irefin et al. (2003)

United States

Prospective study; N = 128

Medication: None tested

No significant difference in pain scores between

groups

Rating Scale: VAS; scores 0-5 out of 10

Jellish et al. (2006)

United States

Prospective, double-blind RCT; N = 120

Medication: PCA (morphine or morphine plus

ondansetron)

Up to 76% experienced post-op pain

Administered analgesia was inadequate

Rating Scale: VAS; scores 4�5-6�1 out of 10 Jones et al. (2009)

Australia

Prospective, double-blind RCT; N = 50

Medication: Intravenous parecoxib; morphine

postoperatively

89% of patients required additional pain

medication (morphine)

Pain scores significantly lower in parecoxib group

only at 6 hours

Rating Scale: VAS; scores 0-35 out of 100

Law-Koune et al. (2005)

France

Prospective, double-blind RCT; N = 80

Medication: Incisional infiltration (bupivacaine

plus epinephrine) vs. ropivacaine

Placebo group received more morphine than

bupivacaine or ropivacaine groups (22�2 mg; 12�7 mg; 10�5 mg respectively) Rating Scale: VAS; scores 0-7 out of 10

Magni et al. (2005)

Italy

Prospective, randomized, open-label clinical trial;

N = 120

Medication: General anaesthesia

(sevoflurane-fentanyl vs. propofol-remifentanil)

10% of ropivacaine group and 6% of sevoflurane

group experienced pain at 45 minutes

Rating Scale: VAS; scores unclear out of 100

Magni et al. (2009)

Italy

Prospective, double-blind RCT; N = 120

Medication: General anaesthesia

(sevoflurane vs. desflurane)

22% of sevoflurane group and 17% of desflurane

group required additional medication for pain

Rating Scale: VAS; scores unclear out of 100

Morad et al. (2009)

United States

Prospective RCT (unblinded); N = 64

Medication: as needed intravenous

fentanyl vs. PCA (fentanyl)

Patients in PCA group had significantly lower pain

scores than PRN group (2�53 vs. 3�62, respectively)

PCA group received significantly more fentanyl

Rating Scale: NRS; scores 2-4�7 out of 10

© 2016 John Wiley & Sons Ltd 1225

JAN: REVIEW PAPER Integrative review – postcraniotomy pain

Table 1 (Continued).

Author, year, Country Design, sample size, medication Existence of pain and pain intensity, rating scale used

Nair and Rajshekhar

(2011)

India

Prospective longitudinal study; N = 43

Medication: Oral paracetamol

5% had moderate pain in first post-op hour

Significant pain reported by 63% of patients

during first 48 hours; severe pain in 12% within

first 12 hours; incidence decreased over first

48 hours

Rating Scale: VAS; not stated out of 10

Nguyen et al. (2001)

Canada

RCT; N = 30

Medication: Scalp nerve block (ropivacaine)

70% of patients in saline group experienced

moderate pain in first 48 hours post-op

Rating Scale: VAS; scores 1�6-4�4 out of 10 Rahimi et al. (2006)

United States

Prospective, single-blinded RCT; N = 27

Medication: Oral narcotics vs. oral COX-2

inhibitors

Pain scores significantly higher in narcotics-alone

group than COX-2 group (P = 0�003) Rating Scale: VAS; scores 2-5�3 out of 10

Rahimi et al. (2010)

United States

Prospective, blinded RCT; N = 50

Medication: Oral narcotics vs. tramadol

Tramadol group had significantly lower pain scores

than narcotics-alone group (P < 0�005) Pain scores between groups significantly different

(P = 0�001435) Rating Scale: VAS; scores 1-8 (narcotics-along

group), 0-7 (tramadol group) out of 10

Saringcarinkul and

Boonsri (2008)

Thailand

Prospective, double-blind RCT; N = 50

Medication: Incisional infiltration (bupivacaine)

33% of bupivacaine group pain free at 30 minutes;

decreased to 4% at 8 hours

16% of control group pain free at 30 minutes;

decreased to 4% at 1 hour

Rating Scale: VNS; scores 2�5-3�5 out of 10 Simon et al. (2012)

Hungary

Prospective RCT; N = 90

Medication: Pre-operative oral diclofenac

Significant difference in incidence of pre-operative

headache between intervention and control

groups (P = 0�0045) 77�7% experienced pain (first post-op day); 69�4% experienced pain (fifth post-op day) Rating Scale: VAS; scores 0-9 out of 10

Sudheer et al. (2007)

Wales

Prospective RCT; N = 60

Medication: PCA (morphine vs. tramadol) vs.

intramuscular codeine

4 patients did not require additional medication in

first postoperative hour; 5 had severe pain

necessitating withdrawal from study

Less pain in morphine and codeine groups;

significant residual pain noted in tramadol group

Rating Scale: VRS; scores 0-10 out of 10

Thibault et al. (2007)

Canada

Retrospective chart review; N = 299

Medication: None tested

24% experienced mild pain, 51�5% moderate pain and 24�5% severe pain Overall prevalence of pain = 76%

Rating Scale: VRS; scores unclear out of 10

Ture et al. (2009)

Turkey

Prospective RCT; N = 80; 75 completed study

Medication: Oral gabapentin vs. oral phenytoin

Pain scores significantly higher in phenytoin group

at 15, 30 and 60 minutes (P < 0�001) Total morphine consumption significantly higher

in phenytoin group (P = 0�01) Rating Scale: VAS; scores 0-4 out of 10

Verchere et al. (2002)

France

Prospective, blind, RCT; N = 64

Medication: Paracetamol vs. paracetamol plus

tramadol vs. paracetamol plus nalbuphine

Paracetamol-only group stopped quickly due to

inadequate analgesia in 75% of patients

Rating Scale: VAS; scores 5-30 out of 100

Williams et al. (2011)

Australia

Prospective, double-blind RCT; N = 100

Medication: Intravenous parecoxib

70% of control group and 61% of parcoxib group

needed additional pain medication

Rating Scale: VAS; scores 2-5 out of 10

1226 © 2016 John Wiley & Sons Ltd

R.E. Guilkey et al.

Main results

As previously discussed, we used the TOUS as the guiding

framework for describing the experiences and cluster associ-

ated with postcraniotomy pain in brain tumour patients,

which resulted in five categories: (1) evidence of pain; (2)

manner of pain assessment; (3) influencing factors; (4) symp-

tom cluster and (5) patient performance (Tables 1 and 2).

Evidence of pain

Fifteen studies reported specific percentages of participants

experiencing moderate-severe pain. These percentages were

as high as 60-96% within the first 2 days after surgery,

despite the use of analgesics. Participants in eight studies

required additional pain medications and in one study,

inadequate analgesia in 75% of participants necessitated

the removal of one study arm (Verchere et al. 2002). In

this arm, six of eight patients experienced inadequate

analgesia and multiple infusions of additional pain

medication were required to reduce pain intensity scores

to below 30 (out of 100) (Verchere et al. 2002). An

additional study reported the withdrawal of five partici-

pants for severe pain in the first postoperative hour

(Sudheer et al. 2007).

Manner of pain assessment

Measures that were used to assess pain varied but most

used one-dimensional assessments of intensity including

visual analogue scales (VAS), numerical rating scales

(NRS), visual rating scales (VRS) or visual numeric

scales (VNS). Study authors did not measure other

dimensions of pain such as timing, distress, affect and

quality. Twenty-one studies (81%) identified inadequate

pain relief.

Influencing factors

Table 2 displays the evidence of postcraniotomy pain,

factors that may influence its development, an associ-

ated symptom cluster and possible impact on patient

performance. Many authors did not report all elements of

the TOUS. Eleven of the 26 studies (42%) discussed some

physiological, psychological or situational factors influenc-

ing postcraniotomy pain.

Several studies examined physiological influencing factors

such as included gender and age but findings were inconsis-

tent. One study found that women tended to experience

higher pain levels than men (Morad et al. 2009) while

another study found that men were more likely to ask for

pain medication than women (Jellish et al. 2006). The

impact of age in the development of postcraniotomy pain

also was not clear. One study found that older age was

associated with less pain (Thibault et al. 2007) while

another found increased pain levels in older patients (van

der Zwan et al. 2005).

Psychological influencing factors are the patient’s emo-

tional reactions to the disease and can include mood and

perceived level of self-sufficiency (Lenz et al. 1997, 2013).

No studies examined psychological factors that may influ-

ence the experience of postcraniotomy pain.

Situational factors are found in the social and physical

environment and can include surgical positioning, site of

surgery and use of anaesthetics. Three studies reported less

pain among patients with frontal craniotomies (Thibault

et al. 2007, Morad et al. 2009, Ducic et al. 2012) and one

study found that perioperative nerve blockade decreased the

incidence of postoperative pain (Morad et al. 2009). Gen-

eral anaesthetics used included sevoflurane and desflurane.

The use of sevoflurane resulted in less pain in one study

(Magni et al. 2005), while in another, patients receiving

sevoflurane required additional medication to control their

pain (Magni et al. 2009).

Clusters

Clusters in the TOUS are groups of co-related symptoms

that interact, affecting the patient’s symptom experience

(Lenz et al. 1997, 2013). Although the researchers did not

explicitly explore ‘symptom clusters’, 21 (81%) studies

discussed symptoms related to pain. Symptoms reported

Table 1 (Continued).

Author, year, Country Design, sample size, medication Existence of pain and pain intensity, rating scale used

van der Zwan et al. (2005)

The Netherlands

Prospective, double-blind RCT; N = 50

Medication: Remifentanil vs. fentanyl

No significant difference in pain intensity between

groups

13 of remifentanil group (45%) required

additional pain medication

Rating Scale: VAS; scores 1-4 out of 10

RCT, randomized controlled trial; 4NRS, numerical rating scale; VAS, visual analogue scale; VRS, visual rating scale; VNS, visual numeric scale.

© 2016 John Wiley & Sons Ltd 1227

JAN: REVIEW PAPER Integrative review – postcraniotomy pain

Table 2 Summarization of studies using theory of unpleasant symptoms concepts.

Author, Year Influencing factors Symptom cluster Patient performance

Bala et al. (2006) • Length of surgery – – Batoz et al. (2009) – • Vomiting

• Agitation • Shivering • Hypertension

Biswas and Bithal (2003) – • Change in diastolic blood pressure

Ducic et al. (2012) • Surgical site ● Altered intracranial pressure

● Altered quality of life ● Development of persistent pain

Ferber et al. (2000) – – • Change in systolic and/or diastolic blood pressure

• Changes in heart rate • Changes in partial pressure of

oxygen

• Altered intracranial pressure Girard et al. (2010) – • Nausea

• Vomiting • Change in systolic

blood pressure

Grossman et al. (2007) – • Nausea • Vomiting • Elevated blood

pressure

Irefin et al. (2003) • Gender • Surgical site

● Nausea ● Vomiting

Jellish et al. (2006) • Surgical approach • Gender

● Nausea ● Vomiting ● Headache

● Length of hospital stay ● Patient satisfaction ● Increased cost of medication used ● Delayed discharge from hospital

Jones et al. (2009) – • Nausea • Vomiting

● Sedation

Law-Koune et al. (2005) – • Nausea • Vomiting • Itching • Change in blood

pressure

• Bladder dysfunction

● Sedation

Magni et al. (2005) – • Nausea • Vomiting • Shivering • Change in blood

pressure

• Change in heart rate

• Change in Glasgow Coma Scale

Magni et al. (2009) – • Change in heart rate • Change in partial

pressure of oxygen

● Need for reintubation ● Changes in Glasgow Coma Scale

Morad et al. (2009) • Gender • Age • Surgical site • Surgical approach • Perioperative

neural blockade

● Nausea ● Vomiting ● Change in blood pressure ● Change in heart rate ● Change in mean arterial

pressure

● Neurological deterioration

1228 © 2016 John Wiley & Sons Ltd

R.E. Guilkey et al.

include headache nausea and vomiting, shivering, fatigue,

dizziness, respiratory depression, constipation, neurologic

changes, increased risk of intracranial bleeding and

agitation. The top three most common symptoms

described were nausea (15 studies; 58%), vomiting (16

studies; 62%) and changes in blood pressure including,

but not limited to, the development of hypertension (9

studies, 35%).

Table 2 (Continued).

Author, Year Influencing factors Symptom cluster Patient performance

Nair and

Rajshekhar (2011)

– • Agitation • Sympathetic Nervous

System (SNS)

stimulation

• Altered blood pressure • Brain swelling

● Development of postoperative complications

● Increased length of hospital stay ● Increased mortality rate

Nguyen et al. (2001) • Incisional site – – Rahimi et al. (2006) • Surgical site • Nausea

• Vomiting • Respiratory depression • Constipation • Neurological changes • Constipation

● Altered mental status ● Increased cost of medication used

Rahimi et al. (2010) – – • Increased cost of medication used • Increased length of hospital stay

Saringcarinkul and Boonsri (2008) – • Nausea • Vomiting

● Sedation ● Change in Glasgow Coma Scale

Simon et al. (2012) • Headache (presence prior to surgery

increased postsurgical

pain)

– • Increased length of hospital stay

Sudheer et al. (2007) • Surgical site (frontal associated with

less pain)

● Nausea ● Vomiting ● Change in partial

pressure of oxygen

Thibault et al. (2007) • Surgical site (frontal associated with less pain)

• Age (increased age associated with lower

pain scores)

• Muscle reflection

● Nausea ● Vomiting

Ture et al. (2009) – • Fatigue • Dizziness

Verchere et al. (2002) – • Nausea • Vomiting • Shivering • Risk of intracranial

bleeding

• Agitation • Hypertension

Williams et al. (2011) – • Nausea • Vomiting

● Sedation ● Change in Glasgow Coma Scale

van der Zwan et al. (2005) • Age (increasing age experienced more pain)

• Surgical site

● Nausea ● Vomiting ● Change in partial pressure

of oxygen

Total Studies Discussing Concept 11 21 14

NRS, numerical rating scale; VAS, visual analogue scale; VRS, visual rating scale; VNS, visual numeric scale.

© 2016 John Wiley & Sons Ltd 1229

JAN: REVIEW PAPER Integrative review – postcraniotomy pain

Patient performance

Patient performance is frequently assessed in terms of

tangible functional outcomes, such as length of stay, readi-

ness to be discharged and perceived quality of life.

Although performance related to postcraniotomy pain was

not explicitly examined, almost half of the studies described

potential results of postcraniotomy pain (Table 2). How-

ever, it was unclear if the impact on patient performance

was a direct result of pain, the use of pain medication, or

other factors. Other functional performance outcomes

reported included increased cost of medication and

increased hospital length-of-stay. In two different studies,

poorly managed postcraniotomy pain resulted in delayed

discharge and altered quality of life (Jellish et al. 2006,

Ducic et al. 2012). Four studies described changes in cogni-

tive performance using the proxy measure of level of con-

scious assessed by the Glasgow Coma Scale (GCS) (Magni

et al. 2005, Saringcarinkul & Boonsri 2008, Magni et al.

2009, Williams et al. 2011). Two studies found changes in

level of consciousness due to type and amount of analgesic

used (Saringcarinkul & Boonsri 2008, Williams et al. 2011)

and one identified these changes as being the result of

uncontrolled pain (Magni et al. 2005).

Discussion

To our knowledge, this is the first integrative review of

data-based studies examining: (1) evidence for postcran-

iotomy, postbrain tumour pain; and (2) the evidence for a

postcraniotomy pain symptom cluster in brain tumour

patients. Brain tumours affect many worldwide and pain

has been identified as a public health priority. Accordingly,

most research on postcraniotomy pain has been conducted

in other countries. Research to date has focused solely on

pharmacological intervention and fails to explore the multi-

dimensional nature of pain through comprehensive assess-

ment (Leslie & Troedel 2002, Nemergut et al. 2007,

Hansen et al. 2011, Guilfoyle et al. 2013). Although phar-

macological interventions exist, no one therapeutic medica-

tion has been identified as most efficacious (National

Pharmaceutical Council 2003, Paolino et al. 2006, Institute

of Medicine Committee on Advancing Pain Research, C.

and Education 2011, Saha et al. 2013). Our review found

that despite the use of 18 different analgesics, moderate to

severe pain still occurred among postcraniotomy brain

tumour patients and that many patients expressed inade-

quate pain management resulting in the need for more anal-

gesics. This review provides strong evidence for the

existence of postcraniotomy pain and the need for more

research to develop evidence-based practice guidelines in

this population.

While researchers have begun to study patients’ subjective

experiences after craniotomy, such as their fears, expecta-

tions and satisfaction (Khu et al. 2010, Milian et al. 2014),

these investigations have not yet addressed pain. Patients’

experiences of pain will necessarily be affected by amount

of pain control and healthcare provider interaction, but the

extent to which these influence postcraniotomy, postbrain

tumour patient experience has not yet been made clear.

Due to the complicated nature of postcraniotomy pain, fur-

ther research is warranted to provide evidence-based care.

A full understanding of the postcraniotomy pain experi-

ence from the patients’ perspectives would improve assess-

ment of pain, planning of interventions and evaluation of

care (Melzack 1999, Andrasik et al. 2011, Watt-Watson &

McGillion 2011). This review serves as a call to action to

describe the context and unfolding of postcraniotomy brain

tumour pain from the patient’s perspective and provides

evidence to challenge the commonly held belief that

postcraniotomy pain is not an important problem (Has-

souneh et al. 2010, American Brain Tumor Association

2012).

The intensity of postcraniotomy, postbrain tumour pain

is well-documented. Measures such as VASs are capable of

reflecting this intensity and change in pain over time (Jensen

& Karoly 2011). However, pain intensity is not necessarily

correlated with level of patient distress and resulting patient

performance (Melzack 1999, Jensen & Karoly 2011, Turk

& Melzack 2011, Turk & Robinson 2011, Watt-Watson &

McGillion 2011). Consequences such as the development of

dysfunction and disability reflect broader dimensions of

pain that cannot be assessed by mere measures of intensity

and distress (Turk & Melzack 2011, Watt-Watson &

McGillion 2011). Current research fails to explore the pain

experience beyond intensity and does not address the clus-

ter of associated symptoms that may magnify pain and/or

moderate treatment effects.

The limited and conflicting nature of the evidence con-

cerning physiological factors that influence the development

of postcraniotomy pain in the brain tumour patient suggests

that additional, more comprehensive description is needed.

Increased awareness of the experiences of postcraniotomy

pain across age groups is needed (Andrasik et al. 2011).

Investigations of the experience of postcraniotomy, post-

brain tumour pain by gender could lead to the development

of targeted approaches for men and women. Similarly,

while incidence of brain tumour is higher in Caucasians

than in those of other racial backgrounds (National Cancer

Institute 2014), few authors report racial characteristics of

1230 © 2016 John Wiley & Sons Ltd

R.E. Guilkey et al.

the study sample, preventing clear understanding of the

manner in which postcraniotomy pain unfolds among

different groups.

Psychological factors influencing the development of

postcraniotomy, postbrain tumour pain are also thought to

be important (McCaffery & Pasero 1999, Melzack 1999

Andrasik et al. 2011, Turk & Robinson 2011, Lenz et al.

2013). None of the studies in the review, however,

addressed these factors and thus it is not yet clear what role

emotions, mood and perceived level of self-sufficiency play

in the unfolding and experience of postcraniotomy pain.

Situational factors that affect the unfolding and experi-

ence of postcraniotomy pain also need further clarification.

Longer surgical time influences length of intensive care unit

stays in cardiac patients (Chu et al. 2008) and length of

surgery influences the severity of postoperative pain in

ambulatory care surgical patients (Chung et al. 1997). In

postcraniotomy patients, longer surgeries may increase post-

surgical pain due to greater time spent in surgical positions,

increased duration of muscle retraction, larger incisions and

the potential for more involved surgical procedures (Casler

et al. 2005, Ducic et al. 2012). Researchers should there-

fore investigate the impact of length of surgery on the

development of postcraniotomy pain.

More detailed comparisons could also be made if surgical

diagnoses were consistently reported. For example, it is

known that postoperative headache in occipital surgeries

stems from resulting occipital neuralgia (Ducic et al. 2012).

Examining the effect of surgical location on development of

postcraniotomy headache could lead to better targeted

interventions.

The existence of a symptom cluster would call for com-

prehensive postcraniotomy pain assessment (Melzack 1999

Andrasik et al. 2011, Saha et al. 2013). Little is known,

however, about the cluster associated with postcraniotomy,

postbrain tumour pain. In the current science, effects of

pharmaceutical interventions, postcraniotomy pain, other

symptoms such as pain and anxiety and patient perfor-

mance are often confounded. Research that explicates the

nature of symptom clusters in this population is needed.

Literature shows that postoperative pain may affect

performance by increasing length of stay, cost of hospital-

ization and delaying discharge (Watt-Watson & McGillion

2011, Saha et al. 2013). Some research links postcran-

iotomy pain to increased length of stay and delayed readi-

ness to be discharged in the traumatic head injury

population (Honeybul 2010, Honeybul & Ho 2010).

However, only a few studies have examined the impact of

postcraniotomy pain on brain tumour patients’ functional

and cognitive performance.

In the broader pain literature, untreated acute pain has

been correlated with the development of long-term pain

due to nervous system plasticity (Melzack 1999, Turk &

Robinson 2011, Watt-Watson & McGillion 2011, Ducic

et al. 2012). In addition, researchers of general postsurgical

pain have shown that inadequate postoperative analgesia

has led to the development of persistent pain (Horn &

Munafo 1997, McCaffery & Pasero 1999, Watt-Watson &

McGillion 2011). Batoz et al. (2009) have shown that

improved pain management in postcraniotomy patients

during the acute postoperative period decreases the devel-

opment of persistent pain at 2 months, but the relationship

between postoperative pain management and persistent

pain has not been well-studied in postcraniotomy brain

tumour patients. Therefore, describing the connection

between postcraniotomy pain and patient performance

could lead to the development of interventions to prevent

or minimize both postcraniotomy pain and its resulting

effects.

Over 40 years of research have repeatedly illustrated that

pain is under-assessed, under-recognized and undertreated.

The treatment of postcraniotomy pain is further compli-

cated by a lack of understanding of the manner in which it

unfolds over the course of the postoperative period and a

reluctance to treat it aggressively for fear of masking neuro-

logical changes. The result is an unclear risk-benefit ratio

associated with the treatment of postcraniotomy pain in

brain tumour patients. Additional research would illuminate

the relationship between postcraniotomy pain, influencing

factors, associated clusters and patient performance, leading

to the development of timely interventions to control pain

without increasing risk to patients.

Limitations

This review was limited to examining studies that discussed

particular influencing factors, associated clusters and the

effect of postcraniotomy, postbrain tumour pain on patient

performance. It is possible that studies looking at postcran-

iotomy pain in a different context were missed. In addition,

this review does not represent ongoing or unpublished

studies, nor does it include published work that has not

undergone the peer review process.

Conclusion

Evidence suggests that postcraniotomy, postbrain tumour

patients experience significant postsurgical pain but no

guidelines have been established to treat this pain. Postcran-

iotomy pain may influence length of hospital stay, cost of

© 2016 John Wiley & Sons Ltd 1231

JAN: REVIEW PAPER Integrative review – postcraniotomy pain

medications, quality of life and development of persistent

pain. However, little research has been conducted on the

complex nature and experience of postcraniotomy, post-

brain tumour pain. Mitigating or preventing postcran-

iotomy pain in the brain tumour population will likely

result in improved patient outcomes. Patient-centred out-

comes research should focus on attempting to understand

postcraniotomy pain, which will pave the way for the

development of timely interventions and standardization of

treatment for postcraniotomy pain to improve functional

outcomes and quality of life.

Acknowledgement

The authors thank and acknowledge the T32 programme

leadership of Dr. Susan Rawl.

Funding

The work reported in this publication was supported by the

National Institute of Nursing Research of the National

Institutes of Health under Award Number T32NR007066.

The content is solely the responsibility of the authors and

does not necessarily represent the official views of the

National Institutes of Health. This work was also sup-

ported by a Jonas Leadership Scholarship from the Jonas

Center for Nursing Excellence, and the Irene and Nathaniel

Aycock Scholarship and the Cheryl A. Bean Scholarship

from the Indiana University School of Nursing.

Conflict of interest

The authors had no conflicts of interest.

Author contributions

All authors have agreed on the final version and meet at

least one of the following criteria [recommended by the

ICMJE (http://www.icmje.org/recommendations/)]:

� substantial contributions to conception and design, acquisition of data or analysis and interpretation of

data;

� drafting the article or revising it critically for impor- tant intellectual content.

Supporting Information

Additional Supporting Information may be found in the

online version of this article at the publisher’s web-site.

References

American Brain Tumor Association (2012) Surgery [Online].

American Brain Tumor Association, Chicago, IL. Retrieved from

http://www.abta.org/secure/surgery.pdf on 14 May 2014.

Andrasik F., Buse D. & Lettich A. (2011) Assessment of headaches.

In Handbook of Pain Assessment, 3rd edn (Turk D. & Melzack

R., eds), The Guilford Press, New York, pp. 354–375.

Bala I., Gupta B., Bhardwaj N., Ghai B. & Khosla V.K. (2006)

Effect of scalp block on postoperative pain relief in craniotomy

patients. Anaesthesia and Intensive Care 34(2), 224–227.

Batoz H., Verdonck O., Pellerin C., Roux G. & Maurette P.

(2009) The analgesic properties of scalp infiltrations with

ropivacaine after intracranial tumor resection. Anesthesia

Analgesia 109, 240–244.

Biswas B.K. & Bithal P.K. (2003) Preincision 0.25% bupivicaine

scalp infiltration and postcraniotomy pain: A randomized

double-blind, placebo-controlled study. Journal of Neurosurgical

Anesthesiology 15(3), 234–239.

Bondy M., Scheurer M., Malmer B., Barnholz-Sloan J., Davis F.,

Il’yasova D., Kruchko C., McCarthy B., Rajaraman P.,

Schwartzbaum J., Sadetzki S., Schlehofer B., Tihan T., Wiemels

J., Wrensch M. & Buffler P. (2008) Brain tumor epidemiology:

consense from the Brain Tumor Epidemiology Consortium

(BTEC). Cancer, 113(S7), 1953–1968.

Cancer Research UK (2014) Brain, Other CNS and Intracranial

Tumors Survival Statistics [Online]. Cancer Research UK,

London. Retrieved from http://www.cancerresearchuk.org/cancer-

info/cancerstats/types/brain/survival/brain-and-central-nervous-sys

tem-cancer-survival-statistics#ten 2015 on 23 April 2015.

Casler J., doolittle A. & Mair E. (2005) Enodscopic surgery of the

anterior skull base. The Laryngoscope 115, 16–24.

Central Brain Tumor Registry of the United States (2014) 2014

CBTRUS Fact Sheet [Online]. Central Brain Tumor Registry of

the United States, Hinsdale, IL. Retrieved from http://

www.cbtrus.org/factsheet/factsheet.html 2015 on 6 June 2014.

Chu D., Bakaeen F., Wang X., Lemaire S., Coselli J. & Huh J.

(2008) Does the duration of surgery affect outcomes in patients

undergoing coronary artery bypass grafting. American Journal of

Surgery 196(5), 652–656.

Chung F., Ritchie E. & Su J. (1997) Postoperative pain in

ambulatory surgery. Anesthesia Analgesia 85(4), 808–816.

Cooper H. (2010) Research Synthesis and Meta-Analysis: A Step-

by-Step Approach Sage Publications Inc, Thousand Oaks, CA.

De Oliveira Ribeiro M.D.O., Pereira C., Sallum A., Martins-Filho

P., Desantana J., da Silva Nunes M. & Hora E. (2013)

Immediate post-craniotomy headache. Cephalalgia 33(11), 897–

905.

Dobrogowski J., Przeklasa-Muszynska A. & Wordliczek J. (2008)

Persistent post-operative pain. Folia Medica Cracoviensia 49(1–

2), 27–37.

Dolin S. & Cashman J. (2005) Tolerability of acute postoperative

pain management: nausea, vomiting, sedation, pruritis and

urinary retention. Evidence from published data. British Journal

of Anaesthesia 95(5), 584–591.

Ducic I., Felder J.M.I. & Endara M. (2012) Postoperative headache

following acoustic neuroma resection: occipital nerve injuries are

associated with a treatable occipital neuralgia. Headache 52,

1136–1145.

1232 © 2016 John Wiley & Sons Ltd

R.E. Guilkey et al.

http://www.icmje.org/recommendations/
http://www.abta.org/secure/surgery.pdf
http://www.cancerresearchuk.org/cancer-info/cancerstats/types/brain/survival/brain-and-central-nervous-system-cancer-survival-statistics#ten
http://www.cancerresearchuk.org/cancer-info/cancerstats/types/brain/survival/brain-and-central-nervous-system-cancer-survival-statistics#ten
http://www.cancerresearchuk.org/cancer-info/cancerstats/types/brain/survival/brain-and-central-nervous-system-cancer-survival-statistics#ten
http://www.cbtrus.org/factsheet/factsheet.html
http://www.cbtrus.org/factsheet/factsheet.html
Durieux M. & Himmelseher S. (2007) Pain control after

craniotomy: off balance on the tightrope? Journal of

Neurosurgery 106, 207–209.

Ferber J., Juniewicz H., Glogowska E., Wronski J., Abraszko R. &

Mierzwa J. (2000) Tramadol for postoperative analgesia in

intracranial surgery: its effect on ICP and CPP. Neurologia i

Neurochirurgia Polska 34, 70–79.

Ferlay J., Soerjomataram I., Ervik M., Dikshit R., Eser S., Mathers

C., Rebelo M., Parkin D., Forman D. & Bray F. (2015)

Worldwide Data [Online]. World Cancer Research Fund

International, London. Retrieved from http://www.wcrf.org/

int/cancer-facts-figures/worldwide-data on 23 April 2015.

Gelinas C., Puntillo K.A., Joffe A.M. & Barr J. (2013) A validated

approach to evaluating psychometric properties of pain assessment

tools for use in nonverbal critically ill adults. Seminars in

Respiratory and Critical Care Medicine 34, 153–168.

Girard F., Quentin C., Charbonneau S., Ayoub C., Boudreault D.,

Chouinard P., Ruel M. & Moumdjian R. (2010) Superficial

cervical plexus block for transitional analgesia in infratentorial

and occipital craniotomy: a randomized trial. Canadian Journal

of Anesthesia 57(12), 1065–1070.

Grossman R., Ram Z., Perel A., Yusim Y., Zalansky R. &

Berkenstadt H. (2007) Control of postoperative pain after awake

craniotomy with local intradermal analgesia and metamizol.

Israeli Medical Association Journal 9, 380–382.

Guilfoyle M., Helmy A., Duane D. & Hutchinson P. (2013)

Regional scalp block for postcraniotomy analgesia: a systematic

review and meta-analysis. Anesthesia Analgesia 116(5), 1093–

1102.

Hansen M.S., Brennum J., Moltke F.B. & Dahl J.B. (2011) Pain

treatment after craniotomy: where is the (procedure-specific)

evidence? A qualitative systematic review. European Journal of

Anaesthesiology 28(12), 821–829.

Hassouneh B., Centofanti J.E. & Reddy K. (2010) Pain

management in post-craniotomy patients: a survey of Canadian

neurosurgeons. Canadian Journal of Neurological Science 38,

456–460.

Honeybul S. (2010) Complications of decompressive craniectomy

for head injury. Journal of Clinical Neuroscience 17(4),

430–435.

Honeybul S. & Ho K. (2010) Long-term complications of

decompressive carniectomy for head injury. Journal of

Neurotrauma 28(6), 929–935.

Horn S. & Munafo M. (1997) Pain: Theory, Research and

Intervention. Open University Press, Philadelphia, PA.

Informational Services Division of the National Health Services

(2010) Cancer Statistics: Brain and Central Nervous System

[Online]. ISD Scotland, Edinburgh. Retrieved from http://

www.isdscotland.org/Health-Topics/Cancer/Cancer-Statistics/Brain

-and-Central-Nervous-System/2015 on 6 April 2015.

Institute of Medicine Committee on Advancing Pain Research, C.

and Education (2011) Relieving Pain in American: A Blueprint

for Transforming Prevention, Care, Education and Research

[Online]. National Academies Press, Washington, DC. Retrieved

from http://www.ncbi.nlm.nih.gov/books/NBK92516/2014 on 27

March 2015.

Irefin S.A., Schubert A., Bloomfield E.L., Deboer G.E. &

Mascha E.J. (2003) The effect of craniotomy location on

postoperative pain and nausea. Journal of Anesthesia 17, 227–

231.

Jellish W.S., Leonetti J.P., Kristina S., Douglas A. & Origitano

T.C. (2006) Morphine/ondansetron PCA for postoperative pain,

nausea and vomiting after skull base surgery. Otolaryngology –.

Head and Neck Surgery 135(2), 175–181.

Jensen M. & Karoly P. (2011) Self-report scales and procedures for

assessing pain in adults. In Handbook of Pain Assessment, 3rd

edn (Turk D. & Melzack R., eds), The Guilford Press, New

York.

Jones S., Cormack J., Murphy M. & Scott D. (2009) Parecoxib for

analgesia after craniotomy. British Journal of Anaesthesia 102

(1), 76–79.

Khu K., Doglietto F., Radovanovic I., Taleb F., Mendelsohn D.,

Zadeh G. & Bernstein M. (2010) Patients’ perceptions of awake

and outpatient craniotomy for brain tumor: a qualitative study.

Journal of Neurosurgery 112(5), 1056–1060.

Lai L.T., Ortiz-Cardona J.R. & Bendo A.A. (2012) Perioperative

pain management in the neurosurgical patient. Anesthesiology

Clinics 20, 347–367.

Lamacraft G. (2012) The link between acute postoperative pain

and chronic pain syndromes. South African Journal of

Anaesthesia and Analgesia 18(1), 45–50.

Law-Koune J.-D., Szekely B., Fermanian C., Peuch C., Liu N. &

Fischler M. (2005) Scalp infiltration with bupivicaine plus

epinephrine or plain ropivicaine reduces postoperative pain after

supratentorial craniotomy. Journal of Neurosurgery

Anaesthesiology 17(3), 139–143.

Lenz E., Pugh L.C., Milligan R.A., Gift A. & Suppe F. (1997) The

middle-range theory of unpleasant symptoms: an update.

Advances in Nursing Science 19(3), 14–27.

Lenz E., Gift A., Pugh L.C. & Milligan R.A. (2013) Unpleasant

symptoms. In Middle Range Theories: Application to Nursing

Research, 3rd edn (Peterson S.J. & Bredow T.S., eds), Wolters

Kluwer, Philadelphia, PA.

Leslie K. & Troedel S. (2002) Does anesthesia care affect the

outcome following craniotomy? Journal of Clinical Neuroscience

9(3), 231–236.

Macrae W. (2001) Chronic pain after surgery. British Journal of

Anaesthesia 87(1), 88–98.

Magni G., Baisi F., Rosa I.L., Imperiale C., Fabbrini V.,

Pannacchiotti M. & Rosa G. (2005) No difference in emergence

time and early cognitive function between sevoflurane-fentanyl

and propofol-remifentanil in patients undergoing craniotomy for

supratentorial intracranial surgery. Journal of Neurosurgical

Anesthesiology 17, 134–138.

Magni G., Rosa I.L., Melillo G., Savio A. & Rosa G. (2009) A

comparison between sevoflurane and desflurane anesthesia in

patients undergoing craniotomy for supratentorial intracranial

surgery. Anesthesia and Analgesia 109(2), 567–571.

McCaffery M. & Pasero C. (1999) Pain: Clinical Manual, 2nd edn.

Mosby, Philadelphia.

Melzack R. (1999) From the gate to the neuromatrix. Pain 82,

S121–S126.

© 2016 John Wiley & Sons Ltd 1233

JAN: REVIEW PAPER Integrative review – postcraniotomy pain

http://www.wcrf.org/int/cancer-facts-figures/worldwide-data
http://www.wcrf.org/int/cancer-facts-figures/worldwide-data
http://www.isdscotland.org/Health-Topics/Cancer/Cancer-Statistics/Brain-and-Central-Nervous-System/2015
http://www.isdscotland.org/Health-Topics/Cancer/Cancer-Statistics/Brain-and-Central-Nervous-System/2015
http://www.isdscotland.org/Health-Topics/Cancer/Cancer-Statistics/Brain-and-Central-Nervous-System/2015
http://www.ncbi.nlm.nih.gov/books/NBK92516/2014
Milian M., Tatgiba M. & Feigl G. (2014) Patient response to

awake craniotomy – a summary overview. Acta Neurochirurgica

156(6), 1063–1070.

Morad A.H., Winters B.D., Yaster M., Stevens R.D., White E.D.,

Thompson R.E., Weingart J.D. & Gottschalk A. (2009) Efficacy

of intravenous patient-controlled analgesia after supratentorial

intracranial surgery: a prospective randomized controlled trial.

Journal of Neurosurgery 111, 343–350.

Myers J. (2009) A comparison of the Theory of Unpleasant

Symptoms and the conceptual model of chemotherapy-related

changes in cognitive function. Oncology Nursing Forum 36(1),

E1–E10.

Nair S. & Rajshekhar V. (2011) Evaluation of pain following

supratentorial craniotomy. British Journal of Neurosurgery 25

(1), 100–103.

National Cancer Institute (2014) Adult Brain Tumors Treatment

(PDQ) [Online]. National Institutes of Health, Bethesda. Retrieved

from http://www.cancer.gov/cancertopics/pdq/treatment/adult

brain/HealthProfessional/page3 on 6 June 2014.

National Pharmaceutical Council (2003) Improving the Quality of

Pain Management Through Measurement and ActionJoint

Commission on Accreditation of Healthcare Organizations,

Oakbrook Terrace, IL.

Nemergut E., Durieux M., Missaghi N. & Himmelseher S. (2007)

Pain management after craniotomy. Best Practice and Research –

Clinical Anasethesiology 21(4), 557–573.

Nguyen A., Girard F., Boudreault D., Fugere F., Ruel M.,

Moumdjian R., Bouthilier A., Caron J.L., Bojanowski M.W. &

Girard D.C. (2001) Scalp nerve blocks decrease the severity of

pain after craniotomy. Neurosurgical Anesthesia 93, 1272–1276.

O’Connor A. & Dworkin R. (2011) Assessment of pain and

health-related quality of life in chronic pain clinical trials. In

Handbook of Pain Assessment, 3rd edn (Turk D. & Melzack R.,

eds), The Guilford Press, New York, pp. 474–486.

Paolino A., Ruppert J., Anderson M. & Garrison-Lanham J. (2006)

Guide to the Care of the Patient with Craniotomy Post-Brain

Tumor Resection. American Association of Neuroscience Nurses,

Glenview, IL.

Puntillo K., Wild L., Morris A., Stanik-Hutt J., Thompson C. &

White C. (2002) Practices and predictors of analgesic

interventions for adults undergoing painful procedures. American

Journal of Critical Care 11(5), 415–431.

Queen’s University Belfast (2015) N. Ireland Cancer Registry

[Online]. Queen’s University Belfast, Belfast. Retrieved from

http://www.qub.ac.uk/research-centres/nicr/CancerData/OnlineSta

tistics/Brain/on 27 March 2015.

Rahimi S.Y., Vender J.R., Macomson S.D., French A., Smith J.R.

& Alleyne C.H. Jr (2006) Postoperative pain management after

craniotomy: evaluation and cost analysis. Neurosurgery 59(4),

852–857.

Rahimi S.Y., Alleyne C.H. Jr, Vernier E., Witcher M.R. & Vender

J.R. (2010) Postoperative pain management with tramadol after

craniotomy: evaluation and cost analysis. Journal of

Neurosurgery 112, 268–272.

Roberts G. (2005) Post-craniotomy analgesia: current practices in

British neurosurgical centres – A survey of post-craniotomy

analgesic practices. European Journal of Anaesthesiology 22(5),

328–332.

Rocha-Filho P. (2015) Post-craniotomy headache: a clinical view

with a focus on the persistent form. Headache 55(5), 733–738.

Saha P., Chattopadhyay S., Rudra A. & Roy S. (2013) Pain after

craniotomy: a time for reappraisal? Indian Journal of Pain 27(1),

7–11.

Saringcarinkul A. & Boonsri S. (2008) Effect of scalp infiltration

on postoperative pain relief in elective supratentorial craniotomy

with 0.5% bupivacaine with adrenaline 1:400,000. Journal of

the Medical Association of Thailand 91(10), 1518–1523.

Simon E., Bank J., Gal J., Siro P., Novak L., Fulesdi B. & Molinar

C. (2012) Administration of preemptive analgesia by diclofenac

to prevent acute postcraniotomy headache. Ideggyogyaszati

Szemle 65(9–10), 302–306.

Sudheer P., Logan S., Terblanche C., Ateleanu B. & Hall J. (2007)

Comparison of the analgesic efficacy and respiratory effects of

morphine, tramadol and codeine after craniotomy. Anaesthesia

62, 555–560.

Talke P.O. & Gelb A.W. (2005) Editorial: postcraniotomy pain

remains a real headache!. European Journal of Anaesthesiology

22, 325–327.

Thibault M., Girard F., Moumdjian R., Chouinard P., Boudreault

D. & Ruel M. (2007) Craniotomy site influences postoperative

pain following neurosurgical procedures: a retrospective study.

Canadian Journal of Anesthesia 54(7), 544–548.

Ture H., Sayin M., Karlikaya G., Bingol C.A., Aykac B. & Ture U.

(2009) The analgesic effect of gabapentin as a prophylactic

anticonvulsant drug on postcranitomy pain: a prospective

randomized study. Neurosurgical Anesthesiology and

Neuroscience 109(5), 1625–1631.

Turk D. & Melzack R. (2011) The measurement of pain and the

assessment of people experiencing pain. In Handbook of Pain

Assessment, 3rd edn (Turk D. & Melzack R., eds), The Guilford

Press, New York, pp. 3–18.

Turk D. & Robinson J. (2011) Assessment of patients with chronic

pain: a comprehensive approach. In Handbook of Pain

Assessment, 3rd edn (Turk D. & Melzack R., eds), The Guilford

Press, New York, pp. 188–212.

Verchere E., Grenier B., Mesli A., Siao D., Sesay M. & Maurette

P. (2002) Postoperative pain management after supratentorial

craniotomy. Journal of Neurosurgical Anesthesiology 14(2),

96–101.

Watson C. (2011) A death knell for codeine for acute pain after

craniotomy. Canadian Journal of Neurological Science 38(3),

390–391.

Watt-Watson J. & McGillion M. (2011) Pain as a symptom

outcome. In Nursing Outcomes: The State of the Science, 2nd

edn (Doran D., ed.), Jones and Bartlett Learning, Sudbury, pp.

201–239.

Whittemore R. & Knafl K. (2005) The integrative reivew: updated

methodology. Journal of Advanced Nursing 52(5), 546–553.

Williams D., Pemberton E. & Leslie K. (2011) Effect of

intravenous parecoxib on post-craniotomy pain. British Journal

of Anaesthesia 107(3), 398–403.

World Cancer Research Fund International (2013) Comparing

More and Less Developed Countries [Online]. World Cancer

Research Fund International, London. Retrieved from http://

www.wcrf.org/int/cancer-facts-figures/comparing-more-less-develo

ped-countries on 19 February 2015.

1234 © 2016 John Wiley & Sons Ltd

R.E. Guilkey et al.

http://www.cancer.gov/cancertopics/pdq/treatment/adultbrain/HealthProfessional/page3
http://www.cancer.gov/cancertopics/pdq/treatment/adultbrain/HealthProfessional/page3
http://www.qub.ac.uk/research-centres/nicr/CancerData/OnlineStatistics/Brain/on
http://www.qub.ac.uk/research-centres/nicr/CancerData/OnlineStatistics/Brain/on
http://www.wcrf.org/int/cancer-facts-figures/comparing-more-less-developed-countries
http://www.wcrf.org/int/cancer-facts-figures/comparing-more-less-developed-countries
http://www.wcrf.org/int/cancer-facts-figures/comparing-more-less-developed-countries
Wu C. & Raja S. (2011) Treatment of acute postoperative pain.

The Lancet 377(9784), 2215–2225.

van der Zwan T., Baerts W., Perez R. & Delange J. (2005)

Postoperative condition after the use of remifentanil with a small

dose of piritramide compared with a fentanyl-based protocol in

patients undergoing craniotomy. European Journal of

Anaesthesiology 22(6), 438–441.

The Journal of Advanced Nursing (JAN) is an international, peer-reviewed, scientific journal. JAN contributes to the advancement of

evidence-based nursing, midwifery and health care by disseminating high quality research and scholarship of contemporary relevance

and with potential to advance knowledge for practice, education, management or policy. JAN publishes research reviews, original

research reports and methodological and theoretical papers.

For further information, please visit JAN on the Wiley Online Library website: www.wileyonlinelibrary.com/journal/jan

Reasons to publish your work in JAN:

• High-impact forum: the world’s most cited nursing journal, with an Impact Factor of 1·527 – ranked 14/101 in the 2012 ISI Jour- nal Citation Reports © (Nursing (Social Science)).

• Most read nursing journal in the world: over 3 million articles downloaded online per year and accessible in over 10,000 libraries worldwide (including over 3,500 in developing countries with free or low cost access).

• Fast and easy online submission: online submission at http://mc.manuscriptcentral.com/jan. • Positive publishing experience: rapid double-blind peer review with constructive feedback. • Rapid online publication in five weeks: average time from final manuscript arriving in production to online publication. • Online Open: the option to pay to make your article freely and openly accessible to non-subscribers upon publication on Wiley Online Library, as well as the option to deposit the article in your own or your funding agency’s preferred archive (e.g. PubMed).

© 2016 John Wiley & Sons Ltd 1235

JAN: REVIEW PAPER Integrative review – postcraniotomy pain

http://www.wileyonlinelibrary.com/journal/jan
http://mc.manuscriptcentral.com/jan

Original Article

Symptom Cluster as a Predictor of Physical Activity in Multiple Sclerosis: Preliminary Evidence Robert W. Motl, PhD, and Edward McAuley, PhD Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

Abstract Thepresent studyexamined thesymptomcluster of fatigue, pain, anddepression, and itsdirect and indirect prediction of physical activitybehavior in a sampleof individualswith multiple sclerosis(MS) usingaprospectiveresearchdesign andtheTheoryof Unpleasant Symptoms. The sampleincluded 292 individualswith a definitediagnosisof MS. Theparticipantscompleted self-report measuresof fatigue, depression, pain, self-efficacy, and functional limitationsat baselineand six monthslater, worean accelerometer for seven daysand completed a self-report measureof physical activitybehavior. Thedata analysisindicated that: 1) fatigue, depression, and pain represented a symptom cluster; 2) thesymptom cluster had a strong and negative predictiverelationship with physical activitybehavior; and 3) functional limitations, but not self-efficacy, accounted for thepredictiverelationshipbetween thesymptomcluster and physical activitybehavior. Such findingsprovidepreliminarysupport totheimportanceof considering symptomclustersasameaningful correlateof physical activitybehavior in personswithMS. J Pain Symptom Manage 2009;38:270e 280. Ó 2009 U.S. Cancer Pain Relief Committee. Published byElsevier Inc. All rightsreserved.

Key Words Symptom cluster, fatigue, depression, pain, physical activity behavior, multiplesclerosis

Introduction There is accumulating evidence that physi-

cal activity behavior is associated with desirable consequences in persons with multiple sclero- sis (MS). Two recent meta-analyses have dem- onstrated that physical activity behavior is

associated with improvements in walking mo- bility1 and quality of life 2 in persons with MS. Nevertheless, there is considerable evi- dence that individuals with MS are largely sed- entary, as demonstrated by a literature review3 and a meta-analysis.4 One objective of current research has been the identification of vari- ables that correlate with physical activity behav- ior among those with MS. This is based on the assumption that such variables might serve as targets of a well-designed intervention for in- creasing physical activity behavior in this population. Symptoms are perceived indicators of change

in normal functioning, sensation, or appear- ance,5 and have been identified as a correlate of

Funded by the National Institute of Neurological Diseases and Stroke (NS054050) . Address correspondence to: Robert W. Motl, PhD, De- partment of Kinesiology and Community Health , University of Illinois at Urbana-Champaign, 350 Freer Hall, 906 S. Goodwin Avenue, Urbana, IL 61801, USA. E-mail: robmotl@uiuc.edu Accepted for publication: August 17, 2008.

Ó 2009 U.S. Cancer Pain Relief Committee Published by Elsevier Inc. All rights reserved.

0885-3924/ 09/ $e see front matter doi:10.1016/ j.jpainsymman.2008.08.004

270 Journal of Pain and Symptom Management Vol. 38 No. 2 August 2009

physical activitybehavior among personswith MS in cross-sectional analyses. For example, one study reported that the number of symptoms ex- perienced during the past 30 days was negatively associated with physical activity behavior,6 whereas a second study reported that worsening of overall symptomsacross a three-to five-year pe- riod was independentlyand negativelyassociated with self-reported levels of physical activitybehav- ior.7 Another studyreported that higher levels of overall symptoms were directly and indirectly as- sociated with lower levels of physical activity behavior, and the indirect pathwayinvolved diffi- culty walking (i.e., functional limitations8) . One final studyreported that the frequencyof overall symptomsand motor symptomswere directlyand indirectly associated with physical activity behav- ior bywayof self-efficacy.9 These previous studies have generally focused

on either a single dimension of overall symptoms or a single specific symptom as cross-sectional or temporally proximal correlates of physical activ- ity behavior in MS. There are definitional, con- ceptual, and theoretical bases for considering a symptom cluster rather than an overall or spe- cific symptom as a prospective or temporally dis- tal correlate ofphysical activitybehavior in MS.By definition, a symptom cluster represents ‘‘three or more concurrent symptoms (e.g., pain, fa- tigue, sleep in sufficiency) that are related to each other.’’ 10, p. 465 This definition underscores the two primary features of a symptom cluster, namelythe existence of three or more symptoms and an interrelationship, either through a com- mon etiology or statistically as a cluster or latent variable.11 Conceptually, the studyof a symptom cluster recognizes that: 1) multiple symptoms of- ten occur concurrently and 2) co-occurring symptoms likely provide a better prediction of consequences (e.g., behavior, function, or quality of life) than a single symptom. The concept of a symptom cluster and its

possible influence on performance outcomes, including physical activitybehavior, is the central theme of the Theory of Unpleasant Symptoms.5 This theory suggests that symptoms can occur as separate entities or concurrently as a symptom cluster, and the symptoms have antecedents (e.g., physiological, environmental, and per- sonal factors) and temporally proximal and dis- tal consequences (e.g., functional limitations and physical inactivity) . Significantly, one central tenet of the Theoryof Unpleasant Symptoms5 is

that concurrent symptoms likelyhave a stronger effect on consequences compared with a single symptom. This stronger effect is based on the fact that co-occurring symptoms likely catalyze each other (e.g., pain is considerably worse when one is fatigued) , thereby resulting in a dis- proportionately more severe and disruptive symptom experience.5 We further note that the inclusion of both temporally proximal (e.g., cross-sectional) and distal (e.g., prospective) per- formance consequences in this theory provides a basis for considering a symptom cluster as po- tentially having a prospective association with physical activity behavior. One commonlyreported cluster of symptoms

includes fatigue, depression, and pain . This symptom cluster has been identified in persons undergoing treatment for cancer,12 and the same symptom cluster might exist in persons with MS and influence physical activity behav- ior. The symptoms of fatigue, depression, and pain often co-occur in persons with MS,13e 17 and are likelyto have synergistic effects.14 These symptoms are interrelated through common neuropathic consequences, including co-occur- ring and diffuse axonal damage ( i.e., lesions) across different regions of the central nervous system.18 To our knowledge, researchers have neither established the existence of this symp- tom cluster in persons with MS nor examined the prospective or temporally distal relation- ship between the symptom cluster and physical activity behavior in th is population. The present study examined the symptom

cluster of fatigue, pain , and depression, and its direct and indirect association with physical ac- tivitybehavior in a sample of individualswith MS using a prospective research design and the TheoryofUnpleasant Symptoms.We first exam- ined the existence of fatigue, pain , and depres- sion as a prespecified symptom cluster in persons with MS, and secondly, examined the possibility that th is symptom cluster would pre- dict levels of physical activitybehavior after a six- month period. This second purpose examined the possibility of a temporally distal association between the symptom cluster and physical activity in persons with MS. We subsequentlyex- amined the possibility that the symptom cluster predicted physical activity behavior directly or indirectly through a pathway that included self-efficacy and functional limitations, in part, consistent with our previous research.6e 9

Vol. 38 No. 2 August 2009 271Symptom Cluster

Methods Participants This study included a convenience sample of

persons with MS. The sample was recruited through: 1) research announcements mailed to previous study participants; 2) advertisements placed in MSConnection; and 3) e-bursts distrib- uted to registered members of three state chap- ters of the National MS Society. There were 511 individuals who expressed interest in the study, and 387 underwent screening for possible inclu- sion. The screening criteria were: 1) a definite di- agnosis of MS; 2) relapse free in the last 30 days; and 3) ambulatory with minimal assistance. Of those who underwent screening, 27 individuals did not satisfyour inclusion criteria, and 16 indi- viduals declined participation. We sent an in- formed consent document and verification letter to the remaining 344 individuals, and the forms were returned by 300 of the individ- uals (87% response rate) . Of those who re- turned the forms, eigh t did not continue with participation, resulting in the final sample of 292 individuals with MS (3% attrition) . The cat- egorical descriptive characteristics of the sam- ple are provided in Table 1. The mean age of the sample was 48.0 years (standard deviation

[SD] ¼ 10.3) , and the mean duration since diag- nosis of MS was 10.3 years (SD ¼ 7.9) .

Instruments

Physical Activity. We measured physical activity behavior using an ActiGraph accelerometer (model 7164 version; Health One Technology, Fort Walton Beach, FL) and the Godin Lei- sure-Time Exercise Questionnaire (GLTEQ).19 Both the accelerometer and the GLTEQ have evidence of validity in individuals with MS,20,21 and the combined use of self-report and objective measures has been recognized as ideal by experts,22 and allowed for modeling physical activity behavior as a latent variable. The ActiGraph accelerometer has a vertical axis piezoelectric bender element that gener- ates an electrical signal that is proportional to the force acting on it. The positive and negative acceleration signals are digitized by an analog-to-digital converter, numerically in- tegrated over an epoch interval, and the inte- grated value of movement counts is stored in random access memory and the integrator is reset. The accelerometer is programmed for start time and epoch interval, and the move- ment counts are retrieved for analysis by means of a personal computer in terface and software provided with the ActiGraph. The downloaded data from the accelerometers are then entered into Microsoft Excel for pro- cessing. Regarding processing, participants re- corded the time that the accelerometer was worn on a log, and this was verified by inspec- tion of the minute-by-minute accelerometer data. We further examined the accelerometer data for long periods of continuous zeros as a check of compliance with wearing the device, and we used a criterion of 60 minutes of con- tinuous zeros for noncompliance. We based the judgment of a valid day of measurement on 10 hours of wear time during the waking hours, defined as the moment of getting out of bed in the morning through the moment of getting to bed in the evening. We consid- ered the data to be spurious when counts ex- ceeded 20,000 per minute, and we required the participants to have three valid days of data for a reliable estimate of weekly physical activity behavior. There were four participants with three valid days, seven with four valid days, 13 with five valid days, 12 with six valid

Table1 Categorical Demographic Characteristics of the Sample of 292 Individuals with MS

Variable n %

Type of MS Relapsing-remitting 239 82 Secondary progressive 34 12 Primary progressive 12 4 Benign 7 2

Sex Female 245 84 Male 47 16

Race Caucasian 272 93 African American 20 7

Marital status Married 199 69 Single 45 15 Divorced/ separated 39 13 Widow/ widower 9 3

Employment status Employed 154 53 Unemployed 138 47

Education High school 41 14 Some college 83 28 College graduate 168 58

272 Vol. 38 No. 2 August 2009Motl and McAuley

days, and 229 with seven valid days of acceler- ometer data; 27 participants had missing accel- erometer data based on either unit malfunction or not wearing the unit. The movement counts for each day were summed and then averaged across the period of valid days of data. This resulted in accelerometer data expressed in total movement counts per day ( i.e., usual physical activity behavior) . The intraclass correlation for those with seven days of accelerometer data was 0.92. The GLTEQ is a self-administered two-part

measure of usual physical activity behavior; we only included the first part in th is study, consistent with previous research .20,21 The first part has three items that measure the fre- quency of strenuous (e.g., jogging) , moderate (e.g., fast walking) , and mild (e.g., easy walk- ing) exercise for periods of more than 15 min- utes during one’s free time in a typical week. The weekly frequencies of strenuous, moder- ate, and mild activities are multiplied by 9, 5, and 3 metabolic equivalents, respectively, and summed to form a measure of total leisure ac- tivity. This study used the previous week as a time frame for the GLTEQ, and participants completed the GLTEQ after wearing an accel- erometer for the seven-day period.

Fatigue. Fatigue was measured with the Fa- tigue Severity Scale (FSS23) . The FSS has nine items that are rated on a 7-point scale of 1 (strongly disagree) and 7 (strongly agree) . The item scores are averaged, and the overall scores range between 1 and 7,with higher scores forming an overall measure of fatigue’s impact on activities. This scale has good evidence of in- ternal consistency, test-retest reliability, and score validity.23 Coefficient alpha for the FSS was 0.93 in the present study.

Depression. Depression was measured using the Hospital Anxiety and Depression Scale (HADS24) . The HADS contains 14 items; seven items measure anxiety symptoms and seven items measure depression symptoms. The items are rated on a 4-point scale of 0 (most of the time) and 3 (not at all) , and items are reverse-scored and then summed. HADS de- pression and anxiety scores range between 0 and 21, and higher scores indicate more fre- quent depression and anxiety symptoms. This scale has good evidence of score reliability

and validity.24 Coefficient alpha for the depres- sion component of the HADS was 0.82 in the present study. We only included the measure of depression because of our a priori focus on its role in the symptom cluster.

Pain. Pain was measured with the short-form McGill Pain Questionnaire (SF-MPQ25) . The SF-MPQ contains a 15-item adjective checklist that assesses sensory (e.g., ‘‘stabbing,’’ ‘‘sharp’’) and affective (e.g., ‘‘sickening,’’ ‘‘tiring-exhaust- ing’’) dimensions of typical whole bodypain in- tensity. The items are rated using a 4-point in tensity scale of 0 (none) and 3 (severe) , and the item scores are summed. Scores on the SF- MPQ range between 0 and 45, and higher scores indicate more intense overall pain . The scores from the items are summed to form a pain-rat- ing index. The SF-MPQ is internally consistent, reliable across time, and has evidence of score validity.25 Coefficien t alpha for the SF-MPQ was 0.88 in the present study.

Self-Efficacy. Self-efficacy was assessed by the Exercise Self-Efficacy Scale (EXSE) .26 The EXSE scale has six items that assess an individ- ual’s beliefs in his or her ability to engage in 20þ minutes of moderate physical activity be- havior three times per week, in one-month in- crements, across the next six months. The first item on the EXSE was: ‘‘I am able to participate in physical activity behavior three times per week at a moderate intensity, for 20þ minutes without quitting for the NEXT MONTH.’’ The next five items on the EXSE progressively in- creased the length of the physical activitybehav- ior period in one-month increments from two through six months. The items on the EXSE scale are rated based on a 100-point percentage scale comprised of 10-point increments, rang- ing from 0% (not at all confiden t) to 100% (highly confident) . An overall exercise self-effi- cacy score is computed by averaging the item scores from the EXSE scale with higher scores represen ting greater efficacy for engaging in physical activity behavior; scores range from 0 to 100. This scale is in ternally consistent and has evidence of score validity.26 Coefficient al- pha for EXSE was 0.99 in the present study.

Functional Limitation. Functional limitation was measured using the function component of the abbreviated version of the Late-Life

Vol. 38 No. 2 August 2009 273Symptom Cluster

Function and Disability Instrument (LL- FDI) .27 The function component of the abbre- viated LL-FDI contains a 15-item self-report measure of functional limitations ( limitations in a person’s ability to perform discrete actions or activities) that correspond to advanced lower extremity function, basic lower extremity function, and upper extremity function. The 15 items were rated using a 5-point scale of 1 (none) and 5 (cannot do) , and were reverse- scored and then summed to form a composite measure of functional limitation; higher scores represent better functioning. Researchers have provided evidence for the reliability and valid- ity of LL-FDI scores in individuals with MS.28

Procedure All participants provided written informed

consent, and the procedures were approved by a University Institutional Review Board. The baseline and follow-up materials for the study were delivered and returned through the U.S. postal service, and all participants received $40 on returning the study materials. The participants completed self-report mea- sures of fatigue, depression, pain , self-efficacy, and functional limitations at baseline and six months later, wore an accelerometer for seven days and completed the self-report measure of physical activity behavior after the week of ac- celerometer data collection. The six-month follow-up of physical activity behavior allowed for an examination of the prospective or distal relationship between the symptom cluster and physical activity behavior.

Data Analysis The data were primarily analyzed using

covariance modeling with Full Information Maximum Likelihood (FIML) estimation in Mplus 3.0 (Muthen & Muthen , Los Angeles, CA).29 The FIML estimator was selected be- cause there were missing accelerometer (9% missing data) and GLTEQ (5% missing data) data, and the rate of missing data was different per measure. The FIML estimator is a theoreti- callybased method for the treatment of missing data in covariance modeling.30 This approach is standard in covariance modeling programs, and does not require any manipulation of the data (e.g., mean centering) ; it estimates the model and its parameters using all available data from the participants, and has resulted in

unbiased estimates of parameters and model fit with up to 25% of simulated missing data.30 We initially tested a measurement model, whereby FSS, HADS, and MPQ scores served as indicators of the symptom cluster latent vari- able. We then performed a cluster analysis in SPSS, version 15.0 for Windows (SPSS, Chicago, IL) as a method of clustering persons with MS into groupsbased on experienceswith the three symptoms. After establishing the symptom clus- ter as a latent variable, we conducted an analysis, whereby the symptom cluster latent variable predicted physical activity behavior as a latent variable with accelerometer counts and GLTEQ scores as indicators. The final analysis involved testing EXSE and LL-FDI scores as mediators of the relationship between the symptom clus- ter and physical activity behavior latent vari- ables. We based a good-model data fit on a nonsignificant Chi-square value and combina- tory rules of standardized root mean squared residual (SRMR) # 0.08 and comparative fit index (CFI) $ 0.95.31

Results DescriptiveStatistics The descriptive statistics and correlations

among the variables are provided in Tables 2 and 3, respectively. We did not transform the physical activity behavior data as the estimates of skewness and kurtosis for the accelerometer were 1.3 and 2.6, respectively, and for the GLTEQ were 1.6 and 3.1, respectively, indicating a reason- able approximation of a normal distribution. The correlations among FSS, HADS, and MPQ scores, in particular, were moderate in magni- tude,32 supporting the notion of a symptom clus- ter.10,33 There was a moderate correlation between GLTEQ scores and accelerometer counts, consistent with previous research20,21

Table2 Descriptive Statistics for the Measures

in the Sample of 292 Individuals with MS

Measure Mean Score

Standard Deviation

Range of Scores

FSS 5.0 1.4 1e 7 HADS 6.0 4.2 0e 18 MPQ 10.7 7.8 0e 33 EXSE 72.1 32.9 0e 100 FDI 55.0 11.8 28e 75 GLTEQ 26.1 23.9 0e 133 Accelerometer 207,475 105,419 26,541e 694,878

274 Vol. 38 No. 2 August 2009Motl and McAuley

and our expectations. We expected a moderate rather than strong association given that accel- erometer counts provided an overall measure of usual physical activity behavior, whereas the GLTEQ provided a measure of leisure-time physical activity behavior. There were no significant differences be-

tween men and women on FSS, HADS, MPQ, EXSE, LL-FDI, GLTEQ, or accelerometer scores. There were significant differences on FSS, HADS, MPQ, EXSE, LL-FDI, and acceler- ometer scores as a function of employment status. Those who were unemployed reported higher levels of fatigue, depression, pain , and functional limitations, and had less self-efficacy and physical activitybehavior on the accelerom- eter. Age was not significantly correlated with FSS, HADS,MPQ, or EXSE scores, but it was cor- related with LL-FDI, GLTEQ, and accelerome- ter scores. Those who were older reported more functional limitations and had less physi- cal activitybehavior on both the GLTEQ and ac- celerometer measures. Therefore, we controlled for employment status and age in the analyses examining symptom cluster as a predictor of physical activity behavior.

Model 1: Symptom Cluster Latent Variable The single-factor measurement model in

Fig. 1 provided an excellent fit for the data (c 2 ¼ 0, df ¼ 0, P ¼ 0.73, SRMR ¼ 0.00, CFI ¼ 1.00) . The factor loadings for the indicators of the symptom cluster laten t variable were all statistically significant and sufficiently large in magnitude.33 The additional cluster analysis identified three groups or clusters of individ- uals with relatively low (n ¼ 58; 20%), moder- ate (n ¼ 140; 48%), and high (n ¼ 94; 32%) scores across the measures of FSS, HADS, and MPQ. This is displayed in Fig. 2.

Model 2: Direct Association Between Symptom Cluster and Physical Activity The second model that we tested had a di-

rect path between symptom cluster and physi- cal activity behavior latent variables, and it represen ted a good fit for the data (c 2 ¼ 4.98, df ¼ 4, P ¼ 0.29, SRMR ¼ 0.03, CFI ¼ 1.00) . The path coefficient in Fig. 3 between the symptom cluster and physical activity be- havior was statistically significant (g ¼ 0.49) , and indicated that those who reported

the symptom cluster of worse fatigue, depres- sion, and pain were less physically active. This relationsh ip was unaffected in an additional analysis that accounted for employment status and age. Figure 4 provides the mean acceler- ometer and GLTEQ scores across the three groups of individuals with low, moderate, and

Table3 Correlations Among Variables for the Sample of 292 Individuals with MS

Latent/ Manifest Variable 1 2 3 4 5 6 7

1. FSS d 2. HADS 0.50 d 3. MPQ 0.42 0.35 d 4. EXSE 0.43 0.30 0.24 d 5. FDI 0.55 0.42 0.44 0.53 d 6. GLTEQ 0.23 0.16 0.07 0.30 0.29 d 7. Accelerometer 0.35 0.18 0.19 0.25 0.47 0.43 d All correlations are statistically significant (P < 0.05) with the exception of the correlation between MPQ and GLTEQ.

Symptom Cluster

FSS HADS MPQ

.77 .65 .54

Fig. 1. Single-factor model tested using confirma- tory factor analysis for establishing the symptom cluster of fatigue, depression, and pain in the sam- ple of 292 individuals with multiple sclerosis. All coefficients are standardized estimates.

Vol. 38 No. 2 August 2009 275Symptom Cluster

high symptom experiences based on the symp- tom cluster of fatigue, depression, and pain .

Model 3: Indirect Association Between Symptom Cluster and Physical Activity The th ird model that we tested had an indi-

rect path between symptom cluster and physi- cal activity behavior latent variables by way of self-efficacy and functional limitations as man- ifest variables. The model represented a good fit for the data (c 2 ¼ 21.79, df ¼ 11, P ¼ 0.03, SRMR ¼ 0.04, CFI ¼ 0.98) . The

statistically significan t path coefficients are provided in Fig. 5, which indicate that those who reported the symptom cluster of worse fa- tigue, depression, and pain had lower function (g ¼ 0.71) and self-efficacy (g ¼ 0.51) , and those who reported lower function (b ¼ 0.55) , but not self-efficacy (b ¼ 0.07) , had less physi- cal activity behavior. Therefore, the relation- ship between the symptom cluster and physical activity behavior was significantly and indirectly accounted for by functional limita- tions (gb ¼ 0.39) , but not self-efficacy (gb ¼ 0.04) . These relationsh ips were unaffected in an additional analysis that accounted for employment status and age.

Discussion Using a prospective research design and the

Theory of Unpleasant Symptoms, the current study examined the symptom cluster of fa- tigue, depression, and pain as a predictor of physical activity behavior among persons with MS. Our results indicated that: 1) fatigue, de- pression , and pain represented a symptom cluster based on bivariate correlations, covari- ance modeling, and cluster analysis; 2) th is symptom cluster had a moderate and negative predictive relationsh ip with physical activity be- havior; and 3) functional limitation, but not self-efficacy, accounted for the predictive rela- tionship between the symptom cluster and physical activity behavior. Such findings

0

4

8

12

16

20

FSS HADS MPQ Measure

M ea

n ±

St an

da rd

E rr

or

Low (n=58) Moderate (n=140) High (n=94)

Fig. 2. Mean scores and standard errors for the measures of fatigue, depression, and pain based on the low, moderate, and high symptom clusters identified in the cluster analysis with the sample of 292 individuals with multiple sclerosis.

Symptom Cluster

FSS HADS MPQ

Physical Activity

GLTEQ ACCEL

D1

−.49

.54 .80.84 .60 .51

Fig. 3. Model tested using covariance modeling for understanding the association between symptom cluster and physical activity behavior in a sample of 292 individuals with multiple sclerosis. All coefficients are standardized estimates. Accel ¼ accelerometer counts.

276 Vol. 38 No. 2 August 2009Motl and McAuley

provide preliminary support for the impor- tance of considering a symptom cluster as a meaningful correlate of physical activity be- havior in persons with MS. There is a growing body of research that has

identified symptoms as a cross-sectional or tem- porally proximal correlate of physical activity behavior in MS.6e 9 All these studies were af- fected by a set of limitations that included the general focus on the overall frequency or

intensity of symptoms, lack of a guiding symp- tom-based theoretical framework, and a cross- sectional research design. The present study extended previous research by focusing on a symptom cluster of fatigue, depression, and pain as a temporally distal predictor of physical activity behavior after a six-month period using a prospective design and based on the Theoryof Unpleasant Symptoms.5 Our findings are con- sistent with the Theory of Unpleasant Symp- toms, that is, 1) the symptom cluster of fatigue, depression, and pain was moderately and negatively associated with physical activity behavior; and 2) the relationship between the symptom cluster and physical activity behavior was indirect through functional limitations. The present study further extended previous research6e 9 by considering both self-efficacy and functional limitations as possible interven- ing variables between the symptom cluster and physical activity behavior in MS. To that end, our results provided evidence that functional limitations, rather than self-efficacy, repre- sented the stronger intermediate variable in the temporally distal association between the symptom cluster and physical activity behavior. The results of previous research and the cur-

rent studymight have implications for the pro- motion and maintenance of a physically active lifestyle in persons with MS. Indeed, individuals

0

10

20

30

40

50

Low (n=58) Moderate (n=140) High (n=94)

Accelerometer GLTEQ

Fig. 4. Mean scores and standard errors for the ac- celerometer counts and GLTEQ scores across the three groups of individuals with low, moderate, and high symptom experiences identified in the cluster analysis. Accelerometer data are expressed in units of original values 10 4 so that the units are easily graphed and compared in magnitude with GLTEQ scores.

Symptom Cluster

FSS HADS MPQ

Physical Activity

GLTEQ ACCEL

D3

.53 .81.79 .62 .56

EXSE

D1

FDI

D2

−.51

−.71 .55

.07

Fig. 5. Model tested using covariance modeling for understanding the associations among symptom cluster, self- efficacy, functional limitation, and physical activity behavior in a sample of 292 individuals with multiple sclerosis. All coefficients are standardized estimates. Solid lines represent statistically significant paths, and dashed lines represent nonsignificant paths. Accel ¼ accelerometer counts.

Vol. 38 No. 2 August 2009 277Symptom Cluster

with MS are often physically inactive and seden- tary,3,4 and emerging evidence indicates that symptoms might be a determinan t of inactivity among persons with MS. The management of symptoms, therefore, represents a possible strat- egy for the promotion and maintenance of physical activity behavior among those with MS. This might be accomplished, in particular, through a program that includes provisions for the management of fatigue, depression, and pain as a cluster of symptoms. To that end, there is a growing bodyof evidence regard- ing programs for managing symptoms, such as fatigue, depression, and pain in MS.34e 36We be- lieve that one direction for future research in- volves incorporating elements of these programs into a multidimensional in tervention for promoting physical activity behavior in per- sons with MS. An additional important finding of this

study is the confirmation of a symptom cluster of fatigue, depression, and pain in persons with MS. The symptom cluster has been identi- fied in persons undergoing treatment for can- cer,12 and was established in the current study based on three sets of analyses, including 1) the bivariate correlations among the three vari- ables; 2) the fit of a single latent variable for the three variables; and 3) the cluster analysis that yielded three distinct groups of individ- uals with relatively low, moderate, and high scores across the cluster of three variables. This is consistent with the recommendations in the literature for statistically identifying a symptom cluster,10,33,37 particularly the re- cent call for using two conceptual approaches for identifying symptom clusters ( i.e., bivariate correlations and factor analysis) and sub- groups of individuals based on experiences with a symptom cluster ( i.e., cluster analysis38) . We further note that the symptoms of fatigue, depression, and pain are linked through a com- mon etiology based on neuropathic conse- quences, including co-occurring and diffuse axonal damage ( i.e., lesions) across different regions of the central nervous system.18 There- fore, we provide preliminary evidence for the existence of a symptom cluster of fatigue, de- pression, and pain in individuals with MS, and this is consistent with the literature on persons with cancer.12 There are several limitations of the current

study. One limitation is that we focused on

a six-month follow-up for measuring symptoms, and the magnitude of the relationship between the symptom cluster and physical activitymight differ with shorter or longer follow-up periods. The second limitation is that we did not control for baseline activityin the analysis nor did we ex- amine the relationship between changes in the symptom cluster and physical activity behavior across time. The focus on only three symptoms of fatigue, depression, and pain is a third limita- tion, and future researchers might consider ad- ditional symptoms within this cluster and other clusters of symptoms in MS. The symptom di- mensions that were measured varied across the FSS, HADS, and SF-MPQ. For example, the FSSmeasured the impact of fatigue on activ- ities, whereas the HADS measured the fre- quency of depressive symptoms. This is a the fourth limitation of the present study, and fu- ture researchers should be cautious in using measures that share common symptom dimen- sions. The final limitation is that the relation- ship between the symptom cluster and physical activity behavior was only studied in a sample of persons with MS, and future re- searchers might consider extending our find- ings into those with other disease conditions, including cancer. In conclusion, the results of the present

study provide a preliminary basis for consider- ing the role of the symptom cluster of fatigue, depression, and pain within the growing body of knowledge that symptoms play a role in mul- tiple behavioral outcomes, including physical activity behavior, in persons with MS. The role of symptoms in physical activity behavior of individuals with MS, in particular, is an area substantial with research potential for promoting and main taining physical activity behavior. The promotion and maintenance of an activity lifestyle is an important compo- nent for enhancing the lives of persons with MS.1,2

References 1. Snook EM, Motl RW. Effect of exercise training on walking mobility in multiple sclerosis: a meta– analysis. Neurorehabil Neural Repair 2009;23: 108e 116.

2. Motl RW, Gosney JL. Effect of exercise training on quality of life in multiple sclerosis: a meta-analy- sis. Mult Scler 2008;14:129e 135.

278 Vol. 38 No. 2 August 2009Motl and McAuley

3. Motl RW. Physical activity and its measurement and determinants in multiple sclerosis. Minerva Med 2008;99:157e 165.

4. Motl RW, McAuley E, Snook EM. Physical activ- ity and multiple sclerosis: a meta-analysis. Mult Scler 2005;11:459e 463.

5. Lenz ER, Pugh LC, Milligan RA, Gift A, Suppe F. The middle-range theory of unpleasant symptoms: an update. Adv Nurs Sci 1997;19:14e 27.

6. Motl RW, Snook EM, McAuley E, Gliottoni R. Symptoms, self-efficacy, and physical activity among individuals with multiple sclerosis. Res Nurs Health 2006;29:597e 606.

7. Motl RW, Arnett PA, Smith MM, et al. Worsen- ing of symptoms is associated with lower physical activity levels in individuals with multiple sclerosis. Mult Scler 2008;14:140e 142.

8. Motl RW, Snook EM, Schapiro RT. Symptoms and physical activity behavior in individuals with multiple sclerosis. Res Nurs Health 2008;31: 466e 475.

9. Snook EM, Motl RW. Physical activity behavior in individuals with multiple sclerosis: roles of overall and specific symptoms, and self-efficacy. J Pain Symptom Manage 2008;36:46e 53.

10. Dodd MJ, Miaskowski C, Paul SM. Symptom clusters and their effect on the functional status of patients with cancer. Oncol Nurs Forum 2001;28: 465e 470.

11. Miaskowski C, Dodd M, Lee K. Symptom clus- ters: the new frontier in symptom management research. J Natl Cancer Inst Monogr 2004;32:17e 21.

12. Fox SW, Lyon DE. Symptom clusters and quality of life in survivors of lung cancer. Oncol Nurs Forum 2006;33:931e 936.

13. Crayton HJ, Rossman HS. Managing the symp- toms of multiple sclerosis: a multimodal approach. Clin Ther 2006;28:445e 460.

14. Krupp LB. Fatigue in multiple sclerosis: A guide to diagnosis and management. New York: Demos Medical Publishing, 2004.

15. Minden SL, Frankel D, Hadden L, et al. The Sonya Slifka Longitudinal Multiple Sclerosis Study: methods and sample characteristics. Mult Scler 2006;12:24e 38.

16. National Multiple Sclerosis Society. Multiple sclerosis information sourcebook. New York: Infor- mation Resource Center and Library of the National Multiple Sclerosis Society, 2005.

17. O’Connor AB, Schwid SR, Herrmann DN, Markman JD, Dworkin RH. Pain associated with multiple sclerosis: systematic review and proposed classification. Pain 2008;137:96e 111.

18. Lublin FD. Clinical features and diagnosis of multiple sclerosis. Neurol Clin 2005;23:1e 15.

19. Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci 1985;10:141e 146.

20. Gosney JL, Scott JA, Snook EM, Motl RW. Phys- ical activity and multiple sclerosis: validity of self-report and objective measures. Fam Commun Health 2007;30:144e 150.

21. Motl RW, McAuley E, Snook EM, Scott JA. Valid- ity of physical activity measures in ambulatory indi- viduals with multiple sclerosis. Disabil Rehabil 2006;28:1151e 1156.

22. Dishman RK, Washburn RA, Schoeller DA. Mea- surement of physical activity. Quest 2001;53:295e 309.

23. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 1989;46:1121e 1123.

24. Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand 1983; 67:361e 370.

25. Melzack R. The short form McGill Pain Ques- tionnaire. Pain 1987;30:191e 197.

26. McAuleyE. Self-efficacy and the maintenance of exercise participation in older adults. J Behav Med 1993;16:103e 113.

27. McAuley E, Konopack JF, Motl RW, Rosengren K, Morris KS. Measuring disability and function in older women: psychometric properties of the late-life function and disability instrument. J Gerontol A Biol Sci Med Sci 2005;60A:M901e M909.

28. Motl RW, Snook E,GosneyJL,McAuleyE.Measur- ing disabilityand function in individualswith multiple sclerosis: psychometric properties of the Late-Life Function and Disability Instrument. In: Goldfarb PM, ed. Psychological tests and testing. Hauppauge, NY: Nova Science Publishers, 2007: 251e 263.

29. Muth én LK, Muth én BO. Mplus. Los Angeles: Author, 1998e 2003.

30. Enders CK, Bandalos DL. The relative perfor- mance of full information maximum likelihood esti- mation for missing data in structural equation models. Struct Equat Model 2001;8:430e 457.

31. Hu L, Bentler PM. Cutoff criteria for fit indices in covariance structure analysis: conventional crite- ria versus new alternatives. Struct Equat Model 1999;6:1e 55.

32. Cohen J. Statistical power analysis for the behav- ioral sciences, 2nd ed. Hillsdale, NJ: Lawrence Erl- baum, 1988.

33. Barsevick AM. The elusive concept of the symp- tom cluster. Oncol Nurs Forum 2007;34:971e 980.

34. Kos D, Duportail M, D’hooghe MB, Nagels G, Kerckhofs E. Multidisciplinary fatigue management programme in multiple sclerosis: a randomized clin- ical trial. Mult Scler 2007;13:996e 1003.

Vol. 38 No. 2 August 2009 279Symptom Cluster

35. Mathiowetz VG, Matuska KM, Finlayson ML, Luo P, Chen HY. One-year follow-up to a random- ized controlled trial of an energy conservation course for persons with multiple sclerosis. In t J Re- habil Res 2007;30:305e 313. 36. Mohr DC, Hart S, Vella L. Reduction in disabil- ity in a randomized controlled trial of telephone-ad- ministered cognitive-behavioral therapy. Health Psychol 2007;26:554e 563.

37. Barsevick AM, Whitmer K, Nail LM, Beck SL, Dudley WN. Symptom cluster research: conceptual, design, measurement, and analysis issues. J Pain Symptom Manage 2006;31:85e 95. 38. Miaskowski C, Aouizerat BE, Dodd M, Cooper B. Conceptual issues in symptom clusters re- search and their implications for quality-of-life as- sessment in patients with cancer. J Natl Cancer Inst Monogr 2007;37:39e 46.

280 Vol. 38 No. 2 August 2009Motl and McAuley

 
Do you need a similar assignment done for you from scratch? We have qualified writers to help you. We assure you an A+ quality paper that is free from plagiarism. Order now for an Amazing Discount!
Use Discount Code "Newclient" for a 15% Discount!

NB: We do not resell papers. Upon ordering, we do an original paper exclusively for you.

Buy Custom Nursing Papers