RESEARCH ARTICLE ANALYSIS Written Assignment

Received: 15 January 2019 | Revised: 19 June 2019 | Accepted: 10 July 2019 DOI: 10.1002/nop2.361

R E S E A R C H A R T I C L E

Are patient education and self‐care advantageous for patients

with head and neck cancer? A feasibility study

Anne Söderlund Schaller1 | Elena Dragioti1 | Gunilla M. Liedberg2 |

Britt Larsson1

1 Pain and Rehabilitation Centre and

Department of Medical and Health

Sciences, Linköping University, Linköping,

Sweden

2 Division of Occupational Therapy,

Department of Social and Welfare Studies,

Faculty of Health Sciences, Campus

Norrkoping, Linköping University, Linköping,

Sweden

Correspondence

Anne Söderlund Schaller, Rehabilitation

Medicine, Department of Medicine and

Health Sciences (IMH), University of

Linköping, Linköping SE‐581 85, Sweden.

Email: [email protected]

1 | I NTR O DUCTI O N

1.1 | Background and objectives

Pain prevalence in patients with head and neck cancer (HNC) is

50%–80% and related to tumour, surgery, chemotherapy and ra‐

diotherapy treatment (RT) (van der Molen et al., 2009). Poor pain

management can be due to inadequate pain assessment and lack

of knowledge among caregivers as well as among patients with

cancer (Oldenmenger, Sillevis Smitt, van Dooren, Stoter, & van der

Rijt, 2009). For example, despite severe pain, patients with cancer

only used about half their prescribed medication (Miaskowski et

al., 2001) and patients' beliefs such as fear of addiction, misunder‐

standing about dosages and feelings that it is not possible to treat

the pain adequately can provide barriers to optimal management of

cancer pain (Gunnarsdottir, Donovan, Serlin, Voge, & Ward, 2002;

Ward et al., 1993). Systematic reviews conclude a decrease in pain

intensity for patients with cancer is associated with education about

pain (Bennett, Bagnall, & Jose Closs, 2009; Howell, Harth, Brown,

Bennett, & Boyko, 2017; Jho, Myung, Chang, Kim, & Ko, 2013; Koller,

Miaskowski, De Geest, Opitz, & Spichiger, 2012; Ling, Lui, & So,

2012; Marie, Luckett, Davidson, Lovell, & Lal, 2013). One system‐

atic review concludes positive effects of education for patients with

cancer on depression, anxiety and quality of life (QoL) (Howell et al.,

2017). However, one review found no effect of patient education on

QoL in patients with cancer (Ling et al., 2012). Educational interven‐

tions for sleep disturbance are sparse (Langford, Lee, & Miaskowski,

2012). Self‐care (SC) refers to what patients do on their own to

achieve, maintain and promote optimal health (Denyes, Orem, Bekel,

& SozWiss, 2001) and may decrease pain in several pain conditions

(Du et al., 2011; Oliveira et al., 2012). Pain in patients with HNC has

been reported to be difficult to treat with analgesics (Epstein et al.,

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© 2019 The Authors. Nursing Open published by John Wiley & Sons Ltd.

Nursing Open. 2019;00:1–14. wileyonlinelibrary.com/journal/nop2 | 1

Abstract

Aim: This study evaluates whether patient education and individually self‐care re‐

duces pain and improves QoL, mood and sleep during and after radiotherapy treat‐

ment for patients with head and neck cancer.

Design: A longitudinal, two‐armed feasibility study design was performed.

Methods: Sixty‐four participants with curative intent were included in the study. All

participants answered questions about pain three times a week and completed a sur‐

vey questionnaire about pain, QoL, psychological aspects and barriers towards pain

management at baseline, at 4 weeks and at 10 weeks. Thirty‐four of the participants

attended in two education sessions on pain based on their beliefs about pain and

received individualized self‐care instructions based on their weekly rating of pain.

Result: This study did not find any significant group differences for the pain, QoL,

mood and sleep.

K E Y WO R D S

education, head and neck cancer, pain, psychological symptoms, quality of life, self‐care

2 | SÖDERLUND SCHALLER Et AL.

2010; Ling & Larsson, 2011). Patients with HNC often suffer from

symptoms that negatively affect QoL (Rogers et al., 2016), mood

(Haisfield‐Wolfe et al., 2012) and sleep (Shuman et al., 2010).

The effect of education and SC on pain and other common symp‐

toms in patients with HNC needs to be elucidated. This study evalu‐

ated whether patient education and individually tailored SC reduces

pain intensity and improves QoL, mood and sleep during and after

RT treatment.

We hypothesized that individually tailored patient education and

adapted SC can help reduce pain, maintain QoL, stabilize mood and

improve sleep in patients with HNC during and after RT.

2 | MET HODS

2.1 | Trial design

This two‐armed feasibility study compared patient education on

management of cancer pain in combination with advice on SC. This

trial is registered in ClinicalTrials.gov Identification NCT03089736.

2.2 | Participants

The participants were patients with HNC undergoing RT and re‐

ferred to the Pain and Rehabilitation Centre (PRC) (University

Hospital, Linköping, Sweden) for anticipated pain. It was not possible

to include patients in the present study before the start of RT. The

Swedish law restricts contact to patients before enrolment to the

PRC. The patients were included within 2 weeks after receiving on‐

going RT. The following inclusion criteria were used as follows: able

to read, write and understand Swedish, registered in RT with cura‐

tive intent and 18 years of age or older. In connection with scheduled

RT, verbal and written information about the study was provided to

all available patients by trained research nurses (TRN). After 1 week,

the eligible patients were asked whether they wanted to be included

in the study. Data in this study were collected as short message ser‐

vices (SMS) and at the PRC.

2.3 | Interventions

2.3.1 | Both groups

All participants answered a SMS with seven items on pain intensity

and interference every Monday, Wednesday and Friday during the

10‐study weeks. If the SMS survey showed ≥3 numeric rating scales

step increase on any items, a TRN phoned the patient the same

day (no later than 3 days if a weekend). Based on the SMS scores,

pharmacological treatment was promptly prescribed or adjusted.

If the patient was displeased with the pain relief at the next day's

phone contact with a TRN (or at next scheduled individual weekly

follow‐up if imminent), the pharmacological treatment was adjusted.

Both groups were offered care as usual at the PRC. Thus, they were

encouraged to contact the TRNs by phone and had access to ad‐

vice from the TRNs. The pharmacological treatment was based on

identical principles for both groups and prescribed by the physicians

according to the ward's policies (Appendix S1).

2.3.2 | The intervention group

Two‐tailored Patient Education Sessions

The scientific literature (Koller et al., 2012; Lovell et al., 2014) on patient

education on management of cancer pain was scrutinized. Six essential

education areas were identified: pain and pain physiology, pain medica‐

tion, side effects of medication and prevention of side effects, abuse of

medications and advice on sleep and anxiety. To make it possible to tai‐

lor education interventions for each patient, a procedure to match The

Barriers Questionnaire II (BQ‐II) items to the six educational areas was

undertaken. Thus, the BQ‐II scoring of the items (several items could

be assigned the same education area) coordinated by most of a group

of nurses (10 experienced nurses employed at PRC and the first author

[AS]) to each education area (Table 1) constituted the base for the in‐

dividual tailoring of education. The inter‐rater reliability of the item‐to‐

education coordination process was measured using a two‐way mixed,

consistency, average‐measures intraclass correlation (ICC) to assess the

degree that the 11 coders provided consistency in their ratings of educa‐

tion areas across the 27 items of the BQ‐II. The ICC was .91. A minimum

summed BQ‐II score (Table 1) of the group of items assigned to each ed‐

ucation area decided whether and which education should be delivered.

At week 1 (baseline [BL]), a TRN delivered a PowerPoint pre‐

sentation covering the education areas. This presentation was

labelled education session 1 (ES 1). To ensure that as many cur‐

rent needs as possible were addressed at week 4 (ES 2), the TRN

initiated a structural discussion with the patient on the specific

education areas presented at ES1. If needed, based on the sec‐

ond scoring of BQ‐II 1 week before the ES 2, additional education

areas were presented at ES 2.

Individually tailored self‐care

The scientific literature of SC for patients with cancer was reviewed

(Johnston et al., 2009; Wong et al., 2006; Worthington et al., 2011),

which was supplemented with the first authors and six nurses em‐

ployed at PRC clinical experiences of pain care regarding patients

with HNC. Fourteen SC measures were identified that covered

maintaining well‐being, prevention of symptoms and pain relief of

mouth and throat (Appendix S2). At weekly follow‐ups at the PRC,

adjustments or initiations of SC were suggested depending on

the previous three SMS scores. As the intention was a preventive

approach, SC measurement was systematically selected and sug‐

gested (Table 2) if the score on any of the SMS items was ≥3 (except

≥1 on the item pain interferences on general activities). In addition,

the TRN verbally presented and provided structured and detailed

written information on the recommended SC (Appendix S2).

2.3.3 | The control group

The control group did not receive the individual tailored education

sessions and the systematic adjustments of SC at weekly follow‐up.

| SÖDERLUND SCHALLER Et AL. 3

TA B L E 1 Items of the Barriers Questionnaire II (BQ‐II) and corresponding education area

Items in BQ‐II (number of the item in BQ‐II)

Confusion from pain medicine cannot be controlled (5)

Using pain medicine blocks your ability to know if you have any new pain (7)

If you take pain medicine when you have some pain, then it might not work as well if the pain becomes worse (15)

Pain medicine can keep you from knowing what's going on in your body (16)

If you use pain medicine now, it won't work as well if you need it later (21)

Pain medicine can mask changes in your health (22)

Education area (least aver‐

age score of adjacent items

for the education to be

offered)

Pain and pain physiology

(12)

Drowsiness from pain medicine is difficult to control (3)

Nausea from pain medicine cannot be relieved (10)

Using pain medicine can harm your immune system (13)

Pain medicine makes you say or do embarrassing things (14)

Constipation from pain medicine cannot be relieved (17)

Pain medicine can hurt your immune system (19)

It is easier to put up with pain than with the side effects that come from pain medicine (20)

Side effects and prevention

of side effects (14)

Cancer pain can be relieved (1)

Pain medicine can effectively control cancer pain (8)

Medicine can relieve cancer pain (24)

Advice on anxiety (reverse

score: items 1, 8, 24 [<9])

How satisfied are you with your current sleep (28) Advice on sleep (2)

However, the weekly follow‐up of the control group was consistent

with the usual care at the PRC. That is, if the patient asked for advice

or if it was apparent to a TRN that one or more unstructured SCs

would be beneficial, verbal advice regarding SC that the TRN came

to think of was provided. This was necessary for ethical reasons.

2.4 | Outcomes

2.4.1 | Primary outcomes

Pain intensity and pain interference

The primary outcome measurements included seven items about

pain intensity and pain interference the previous 24 hr reported by

both groups of patients and collected by SMS every Monday,

Wednesday and Friday during the 10‐study weeks.

The University of California San Francisco (UCSF) Oral Cancer

Pain Questionnaire (Connelly & Schmidt, 2004) measures pain ex‐

periences from the oral cavity and consists of eight items scored on

a scale from 0 (no pain)–10 (the most intense pain). In the SMS sur‐

vey, two items from the Oral Cancer Pain Questionnaire were added

on pain intensity in connection with and without speaking, talking

and drinking. The Oral Cancer Pain Questionnaire is valid for pa‐

tients with oral cancer pain (Connelly & Schmidt, 2004; Kolokythas,

Connelly, & Schmidt, 2007).

The Brief Pain Inventory (BPI) measures two targets: the sub‐

jective intensity of pain and how pain interferes with daily activities

(Cleeland & Ryan, 1994). The BPI consists of 12 items: five items

related to pain intensity and seven items related to pain interfer‐

ence on function both rated on a 0 (no interference)–10 (inter feres

completely) scale. In the SMS survey, five items on pain interference

Advice on anxiety (16) Pain medicine weakens the immune system (4)

It is important to be strong by not talking about pain (11)

It is important for the doctor to focus on curing illness and not waste time controlling pain (12)

If doctors have to deal with pain, they won't concentrate on curing the disease (18)

Pain medicine can mask changes in your health (22)

Doctors might find it annoying to be told about pain (25)

Reports of pain could distract a doctor from curing the cancer (26)

If I talk about pain, people will think I'm a complainer (27)

Abuse about medications (6) There is a danger of becoming addicted to pain medicine (2)

Many people with cancer get addicted to pain medicine (9)

Pain medicine is very addictive (23)

When you use pain medicine, your body becomes used to its effects and soon it won't work anymore (6) Pain medication (14)

Using pain medicine blocks your ability to know if you have any new pain (7)

Pain medicine makes you say or do embarrassing things (14)

If you take pain medicine when you have some pain, then it might not work as well if the pain becomes worse (15)

Pain medicine can keep you from knowing what's going on in your body (16)

If you use pain medicine now, it won't work as well if you need it later (21)

Pain medicine can mask changes in your health (22)

4 | SÖDERLUND SCHALLER Et AL.

TA B L E 2 Self‐care measurements recommended at weekly

follow‐up when NRS score ≥3 on any item (≥1 on the item pain

interferences on general activities) of the short message services

(SMS) scores

Pain intensity

When talking, eating and drinking 3–4, 9–11

When not talking, eating or drinking 3–4, 9–11

Pain interference

General activities 1–4

Mood 1–2, 8

Relations with other people 8

Sleep 5–7

Enjoyment of life 1–2, 8

a Number of self‐care refers to numbers in Appendix S2.

from the BPI were included general activities, mood, relations,

sleep and enjoyment of life. The BPI instrument has been validated

for patients with cancer (Cleeland & Ryan, 1994; Kumar, 2011).

For each subscale and item, the average score of the three

weekly scores was calculated.

2.4.2 | Secondary outcomes

A survey questionnaire including seven validated patient‐re‐

ported outcome measurements was used to collect the outcomes.

Answered at BL, at 4 weeks and at 10 weeks, the secondary out‐

comes cover QoL, pain intensity, pain interference, psychological

aspects and barriers towards pain management. A part of the sec‐

ondary outcomes BL data are reported elsewhere (Schaller, Dragioti,

Liedberg, & Larsson, 2017).

Quality of life

The Euro QoL‐5 Dimension Questionnaire (EQ‐5D) assesses health out‐

come and perceived state of health (Brooks, 1996). The questionnaire

comprises five items: mobility, self‐care, usual activities, pain and discom‐

fort, anxiety and depression. Each item has three response scales – no

problems, some problems and extreme problems – and the answers were

coded 1–3. An algorithm developed for EQ‐5 D was used to calculate the

final individual score. The EQ‐5D score has a range from −0.5–1, where

negative values mean low QoL and 1 means no reduction in QoL. The

EQ‐5D scores were determined by applying scores from standard popu‐

lation values (Dolan, 1997). The second part of the EQ‐5D is the Euro

Quality of Life Vertical Visual Analogue Scale (EQ‐VAS), which measures

the respondent's general health on a vertical visual analogue line with

100‐scale steps with the endpoints labelled “Best imaginable health

state” and “Worst imaginable health state” (Fayers & Machin, 2013).

The EQ‐5D, a valid and reliable instrument (Coons, Rao,

Keininger, & Hays, 2000), was selected because it is a generic in‐

strument that can be used for patients with different conditions and

diseases (Fayers & Machin, 2013).

Pain intensity and pain interference

The Brief Pain Inventory (BPI) measures intensity of pain and pain

interference (see description above) (Cleeland & Ryan, 1994). The

scores were summed, and mean values of the items of pain interfer‐

ence and pain intensity items were calculated. The Swedish version

of BPI used in this study has been linguistically validated (Anderson,

2019) but has not yet been psychometrically validated.

Anxiety and depression

The Hospital Anxiety and Depression Scale (HADS) assesses anxi‐

ety and depression (Bjelland, Dahl, Haug, & Neckelmann, 2002).

This scale consists of 14 items: seven items are related to anxiety

Abbreviations: M, mean; SD, Standard deviation. a Student t test for continuous variables or chi‐square test for categorical variables.

TA B L E 3 Participant characteristics at

baseline

Self‐care instruction

Items on pain three times weekly by SMS recommendeda

Characteristic; N (%), un‐

less otherwise stated

Total (N = 64)

Intervention

group (N = 34)

Control group

(N = 30)

p‐valuea

Age (years) (M, SD) 65.05 (±10.47) 64.0 (±10.42) 66.3 (±10.57) .38

Women 25 (39.1) 12 (35.3) 13 (43.3) .51

Living situation

Not living alone 42 (65.6) 22 (64.7) 20 (66.7) .86

Living alone 22 (34.4) 12 (35.3) 10 (33.3)

Education

Primary 10 (15.6) 4 (11.8) 6 (20.0) .25

Second upper school/

vocational

28 (43.8) 13 (38.2) 15 (50.0)

College/University 26 (40.6) 17 (50.0) 9 (30.0)

Smoking habits

Non‐smokers 26 (40.6) 15 (44.1) 11 (36.7) .83

Smokers 10 (15.6) 5 (14.7) 5 (16.7)

Ex‐smokers 28 (43.8) 14 (41.2) 14 (46.7)

| SÖDERLUND SCHALLER Et AL. 5

p‐value

Regression coefficients

(95% CI) B Control group (N = 30)

Intervention group

(N = 34) Variables

TA B L E 4 Mean scores (SD) and regression coefficients for primary outcomes by short message services answers

Pain intensity Q1 (0–10) (M, SD)

Overall effect: p = 0.50

1 week (baseline) 1.94 (2.09) 1.80 (2.22) – –

2 weeks 2.11 (1.46) 2.62 (2.31) 0.82 (0.36 to 1.28) .001

3 weeks 2.90 (1.72) 3.63 (2.59) 1.83 (1.11 to 2.56) .000

4 weeks 3.00 (1.77) 3.74 (2.71) 1.99 (1.13 to 2.84) .000

5 weeks 3.13 (1.62) 3.72 (2.80) 1.94 (0.98 to 2.89) .000

6 weeks 3.28 (1.90) 3.73 (2.76) 1.90 (0.95 to 2.84) .000

7 weeks 2.70 (1.95) 3.34 (2.37) 1.38 (0.35 to 2.40) .009

8 weeks 2.21 (1.76) 2.64 (2.61) 0.71 (−0.48 to 1.90) .240

9 weeks 2.04 (1.68) 2.04 (2.26) 0.34 (−0.74 to 1.44) .530

10 weeks 2.23 (1.86) 1.83 (2.03) −0.19 (−1.32 to 0.95) .743

Pain intensity Q2 (0–10) (M, SD)

Overall effect: p = 0.36

1 week (baseline) 1.30 (1.45) 1.33 (1.93) – –

2 weeks 1.52 (1.26) 1.93 (1.94) 0.60 (0.25 to 0.95) .001

3 weeks 2.17 (1.41) 2.95 (2.49) 1.62 (1.06 to 2.19) .000

4 weeks 2.32 (1.56) 3.12 (2.51) 1.87 (1.18 to 2.57) .000

5 weeks 2.39 (1.56) 3.02 (2.56) 1.77 (1.02 to 2.52) .000

6 weeks 2.61 (1.74) 2.96 (2.63) 1.71 (0.93 to 2.48) .000

7 weeks 2.14 (1.81) 2.67 (2.33) 1.25 (0.36 to 2.14) .006

8 weeks 1.88 (1.65) 2.10 (2.28) 0.84 (−0.13 to 1.80) .090

9 weeks 1.62 (1.52) 1.57 (1.98) 0.44 (−0.46 to 1.35) .338

10 weeks 1.74 (1.54) 1.46 (1.67) −0.008 (−0.95 to 0.93) .987

Pain interference Q1 (0–10) (M, SD)

Overall effect: p = 0.83

1 week (baseline) 1.29 (1.41) 1.21 (1.98) – –

2 weeks 1.56 (1.44) 1.64 (2.03) 0.43 (−0.19 to 1.05) .176

3 weeks 2.10 (1.78) 2.26 (2.56) 1.05 (0.24 to 1.86) .011

4 weeks 2.44 (1.83) 2.57 (2.99) 1.42 (0.43 to 2.41) .005

5 weeks 2.60 (2.05) 2.87 (3.05) 1.73 (0.92 to 2.53) .000

6 weeks 2.67 (2.12) 2.52 (2.61) 1.34 (0.50 to 2.18) .002

7 weeks 2.70 (2.46) 2.55 (2.55) 1.26 (0.39 to 2.12) .004

8 weeks 2.28 (2.19) 2.07 (2.38) 0.93 (−0.01 to 1.87) .052

9 weeks 2.13 (2.14) 1.51 (2.13) 0.48 (−0.42 to 1.38) .297

10 weeks 2.19 (2.06) 1.27 (1.78) 0.03 (−0.79 to 0.84) .948

Pain interference Q2 (0–10) (M, SD)

Overall effect: p = 0.73

1 week (baseline) 1.28 (1.31) 1.29 (1.82) – –

2 weeks 1.53 (1.44) 1.72 (2.08) 0.43 (0.16 to 0.70) .002

3 weeks 2.04 (1.73) 2.31 (2.36) 1.02 (0.56 to 1.48) .000

4 weeks 2.09 (1.84) 2.26 (2.59) 1.09 (0.050 to 1.68) .000

5 weeks 2.17 (1.89) 2.38 (2.59) 1.19 (0.46 to 1.91) .001

6 weeks 2.26 (1.95) 2.30 (2.37) 1.11 (0.50 to 1.72) .000

(Continues)

6 | SÖDERLUND SCHALLER Et AL.

Note: Values presented are model estimates of generalized estimating equations models with a random intercept and adjusted for baseline.

Regression coefficients can be interpreted as the time effect for the groups at a certain follow‐up moment compared with baseline. Significant dif‐

ferences are bold. The estimated impact (i.e. overall effect) of treatment reflects the “combined” within‐ and between‐subjects effects and Q = ques‐

tion. Pain intensity: Q1 = with speaking, talking and drinking, Q2 = without speaking, talking and drinking. Pain interference: Q1 = general activities,

Q2 = mood, Q3 = relations, Q4 = sleep, Q5 = enjoyment of life.

Abbreviations: M, mean; SD, standard deviation.

TA B L E 4 (Continued)

Intervention group

Regression coefficients

Variables (N = 34) Control group (N = 30) (95% CI) B p‐value

7 weeks 2.23 (2.08) 2.17 (2.34) 0.95 (0.34 to 1.56) .002

8 weeks 2.00 (1.96) 1.82 (2.15) 0.68 (−0.01 to 1.38) .054

9 weeks 1.72 (1.91) 1.38 (2.03) 0.43 (−0.32 to 1.18) .259

10 weeks 1.67 (1.57) 1.20 (1.86) 0.29 (−0.36 to 0.94) .386

Pain interference Q3 (0–10) (M, SD)

Overall effect: p = 0.58

1 week (baseline) 1.03 (1.21) 1.00 (1.76) – –

2 weeks 1.23 (1.39) 1.43 (2.14) 0.44 (0.90 to 0.80) .014

3 weeks 1.81 (1.65) 2.11 (2.37) 1.12 (0.59 to 1.66) .000

4 weeks 1.86 (1.67) 2.36 (2.70) 1.50 (0.75 to 2.24) .000

5 weeks 2.10 (1.91) 2.38 (2.59) 1.50 (0.75 to 2.26) .000

6 weeks 2.23 (1.98) 2.07 (2.27) 1.24 (0.59 to 1.88) .000

7 weeks 2.16 (2.21) 2.03 (2.24) 1.18 (0.60 to 1.77) .000

8 weeks 1.74 (1.79) 1.77 (2.37) 0.95 (0.21 to 1.69) .012

9 weeks 1.55 (1.64) 1.42 (2.12) 0.87 (0.03 to 1.71) .043

10 weeks 1.54 (1.52) 1.16 (1.83) 0.74 (−0.02 to 1.49) .056

Pain interference Q4 (0–10) (M, SD)

Overall effect: p = 0.25

1 week (baseline) 1.70 (2.09) 1.17 (1.73) – –

2 weeks 1.84 (1.96) 1.88 (2.28) 0.71 (0.24 to 1.18) .003

3 weeks 2.00 (1.97) 2.18 (2.47) 1.01 (0.47 to 1.55) .000

4 weeks 1.92 (2.00) 2.19 (2.66) 1.07 (0.52 to 1.62) .000

5 weeks 1.72 (1.86) 2.44 (2.62) 1.31 (0.68 to 1.94) .000

6 weeks 1.46 (1.59) 2.49 (2.68) 1.44 (0.81 to 2.06) .000

7 weeks 1.46 (1.56) 2.01 (2.24) 0.81 (0.36 to 1.26) .000

8 weeks 1.08 (1.19) 1.70 (2.05) 0.81 (0.23 to 1.40) .007

9 weeks 1.12 (1.23) 1.55 (2.24) 0.84 (0.12 to 1.55) .022

10 weeks 1.07 (1.29) 1.22 (1.03) 0.69 (−0.08 to 1.46) .078

Pain interference Q5 (0–10) (M, SD)

Overall effect: p = 0.52

1 week (baseline) 1.30 (1.72) 1.24 (1.96)

2 weeks 1.39 (1.79) 1.64 (2.36) 0.40 (0.07 to 0.73) .019

3 weeks 1.72 (1.93) 2.17 (2.62) 0.92 (0.46 to 1.39) .000

4 weeks 1.78 (1.95) 2.04 (2.53) 0.95 (0.40 to 1.51 .001

5 weeks 1.87 (2.00) 2.31 (2.67) 1.20 (0.43 to 1.97) .002

6 weeks 1.85 (1.83) 1.92 (2.41) 0.85 (0.27 to 1.44) .004

7 weeks 1.93 (2.06) 1.73 (2.15) 0.60 (0.09 to 1.11) .022

8 weeks 1.74 (1.81) 1.60 (2.19) 0.62 (−0.09 to 1.33) .087

9 weeks 1.51 (1.83) 1.36 (1.03) 0.50 (−0.19 to 1.19) .158

10 weeks 1.36 (1.51) 1.16 (1.72) 0.49 (−0.14 to 1.12) .128

| SÖDERLUND SCHALLER Et AL. 7

Randomized (n = 64)

Assessed for eligibility (n = 119)

Excluded (n = 55)

Not meeting inclusion criteria (n = 16)

Declined to participate (n = 39)

F I G U R E 1 CONSORT flow chart of the

recruitment process

and seven to depression and is rated on a four‐point scale ranging

from 0–3. The scores were summed, and the range for each subscale

is 0–21. Higher scores indicate likelihood of anxiety or depressive

symptoms. A score of 7 or less indicates a non‐case, a score of 8–10

a doubtful case and a score of 11 or more a definite case. HADS, a

valid and reliable instrument (Bjelland et al., 2002; Zigmond & Snaith,

1983), is widely used in clinical practice, pain care and research and

detects anxiety and depressive symptoms in a general setting.

Pain catastrophizing

The Pain Catastrophizing Scale (PCS) measures thoughts or feelings of

catastrophizing in relation to how individuals experience pain (Sullivan,

Bishop, & Pivik, 1995). The questionnaire comprises 13 items, includ‐

ing subscales for rumination, magnification and helplessness. Each

item is scored on a five‐point scale from 0 (not at all)–4 (all the time). In

this study, the total score was used and summed, and mean values of

the items were calculated. The score range is 0–52, with higher scores

indicating a worse situation. The PCS, a valid and reliable instrument

(Osman et al., 2000), is used in clinical settings and research.

Barriers towards pain

The Barriers Questionnaire II (BQ‐II) comprises 27 items on patient‐

reported beliefs on pain and pain management (Gunnarsdottir et al.,

2002; Ward et al., 1993). Each item is measured on a six‐point scale

– 0 (do not agree at all)–5 (agree very much) – with a total score of

0–135 with higher scores indicating higher barriers. Before this study,

BQ‐II was translated into Swedish using a backward–forward proce‐

dure (Appendix S1, text 1). Cronbach's alpha coefficient was .90. The

BQ‐II has been found to have good validity for patient‐related barriers

to pain management in several studies involving patients with cancer

(Gunnarsdottir et al., 2002; Valeberg et al., 2009; Ward et al., 1993).

Current sleep pattern

The Insomnia Severity Index (ISI), a self‐reported questionnaire,

measures insomnia and provides a measure of the severity of sleep

disorders (Bastien, Vallieres, & Morin, 2001). The ISI comprises

seven items, and each item is rated on a scale from 0–4, and the

total score ranges from 0–28. A higher score suggests more severe

insomnia. In this study, one issue about sleep from the ISI was added

at the end of the BQ‐II and reads as follows: How satisfied are you

with your current sleep? The ISI has been found to be a valid and

reliable instrument (Savard, Savard, Simard, & Ivers, 2005) and was

used because sleep disorders are common in patients with pain.

2.5 | Sample size and randomization

The sample size was assessed based on pain intensity (0–10 scale).

With an assumed clinically relevant average difference in four scale

steps (SD 3), an alpha value of .05 and a power of 80%, each group

was calculated to include approximately 30 patients.

Every second patient of eligible patients was assigned to the con‐

trol group (30 patients), and every second patient was assigned to

the intervention group (34 patients).

2.6 | Allocation concealment mechanism

When patients agreed to participate in the study, their personal data

were documented in consecutive order on a list in a confidential data

Allocation

Follow-Up

Analysis

Analysed (n = 34)

Excluded from analysis (n = 0)

Analysed (n = 30)

Excluded from analysis (n = 0)

Lost to follow-up (n = 0)

Discontinued intervention (n = 0)

Lost to follow-up (n = 0)

Discontinued intervention (n = 0)

Allocated to control group (n = 30) Allocated to intervention group (n = 34)

Received allocated intervention (n = 33)

Did not receive allocated intervention (poor

health) (n = 1)

Enrolment

8 | SÖDERLUND SCHALLER Et AL.

10

8

6

4

2

0

Time

10

8

6

4

2

0

Time

F I G U R E 2 Scores of primary pain intensity outcomes by short

message services (SMS) answers and standard deviation (vertical

bars), for the intervention group (N = 34) and the control group

(N = 30). Q1 = with speaking, talking and drinking, Q2 = without

speaking, talking and drinking. Page 27, Figure 3, above the figure:

Q1 = general activities, Q2 = mood, Q3 = relations, Q4 = sleep,

Q5 = enjoyment of life

file. All patients were assigned a code number and were consecu‐

tively distributed to the intervention group or to the control group

– every other patient to the control group and every other to the

intervention group.

The first author generated the distribution sequence, registered

participants and assigned participants to the intervention or control

group.

2.7 | Statistical methods

All the data were analysed using SPSS 23.0 for Windows (IBM Corp.).

All tests were two‐tailed, and statistical significance was defined as

a value of p ≤ .05. The data are presented as median or mean values

with standard deviation (SD) or minimum and maximum values and as

percentages (%). The differences between groups at baseline were

tested by the Student t tests for continuous variables and chi‐square

test for dichotomous variables. For the primary outcomes, first

the average score was calculated for three time points every week

to measure the primary outcomes for 10 weeks. Then, a linear‐re‐

peated‐measures multilevel model (generalized estimating equations

[GEE] continuous variables) was used to determine the effectiveness

of the intervention compared with control conditions over time. The

estimated impact (i.e. overall effect; Table 4) of treatment on the

outcome in the GEE model reflects the “combined” within‐ and be‐

tween‐subjects effects. The results are presented as regression coef‐

ficients (B) with 95% confidence intervals (CI) and can be interpreted

as the time effect for the groups at a certain follow‐up compared with

baseline. In multilevel analysis, missing scores do not need an impu‐

tation strategy, as this analysis is flexible in handling missing data. A

repeated‐measures ANOVA/mixed model (continuous variables) with

Bonferroni post hoc tests was used for the secondary outcomes.

3 | R ES UL TS

A total of 119 patients were eligible, and 64 were selected (i.e., ran‐

domized) (Figure 1). The patients were randomly assigned to either

the control group (30 patients) or the intervention group (34 pa‐

tients). All 64 patients were analysed on an intention‐to‐treat basis.

Excluded patients (N = 55) did not meet the inclusion criteria (N = 16)

or declined to participate (N = 39). The process of inclusion was on‐

going between January 2015–December 2016.

The 64 patients were diagnosed with HNC and informed on the

curative intent of RT about 6.0 weeks (median) (min 2–max 711) be‐

fore inclusion in the study.

The patients completed the first survey questionnaire in mean

7.4 days (SD 5.9 days) after the start of RT. Mean age of the par‐

ticipants was 65.1 years (SD 10.5 years), and the mean age of the

non‐participants was 70.3 years (SD 12.8 years). Among the partic‐

ipants, 39 (60.9%) were men; the corresponding figure for the non‐

participants was 31 (66.0%). The only reason reported for denying

participating was poor health. Most participants cohabitated (42;

65.6%), most were former smokers (28; 43.8%), 10 (15.6%) were

current smokers, and 26 (40.6%) had a university degree ( Table 3).

We previously have presented descriptive (and BL) data from most

participants elsewhere (Schaller et al., 2017). Of the 34 patients, 33

(97.0%) in the intervention group completed the interventions. The

reason for withdrawal was poor health.

3.1 | Primary outcomes

We evaluated the effects of the intervention with education and SC

on pain intensity and pain interference based on the SMS answers

by performing repeated‐measures GEE model (Table 4; Figures 2 and

3). Missing values were 2%–3% from week 7 to week 10 with respect

to all primary outcomes. The results showed no overall significant

differences between the control and intervention groups over time.

Intervention group

Control group

Intervention group

Control group

P a in

in te

ns ity

Q 2

P a in

in te

ns ity

Q 1

B a

s e

lin e

( w

e e

k 1

) B

a s

e lin

e (

w e e k

1 )

2 w

e e

k s

2 w

e e k

s

3 w

e e

k s

3 w

e e k

s

4 w

e e

k s

4 w

e e k

s

5 w

e e

k s

5 w

e e k

s

6 w

e e

k s

6 w

e e k

s

7 w

e e

k s

7 w

e e k

s

8 w

e e

k s

8 w

e e k

s

9 w

e e

k s

9 w

e e k

s

1 0

w e

e k s

1

0 w

e e k s

| SÖDERLUND SCHALLER Et AL. 9

P a

in in

te rf

e re

n ce

Q 2

P a in

in te

rf e

re n

ce Q

4

B a

se lin

e (

w e

e k

1 )

2 w

e e

ks

3 w

e e

ks

4 w

e e

ks

5 w

e e

ks

6 w

e e

ks

7 w

e e

ks

8 w

e e

ks

9 w

e e

ks

1 0 w

e e

ks

10

8 Intervention group

10 Intervention group

10 Intervention group

Control group 8

6

6

4 4

2

2

0 0

Control group 8

6

4

2

0

Control group

Time Time Time

10

Intervention group

10 Intervention group

8 Control group 8

6 6

4 4

2 2

Control group

0 0

Time Time

F I G U R E 3 Scores of primary pain interference outcomes by short message services (SMS) answers and standard deviation (vertical bars),

for the intervention group (N = 34) and the control group (N = 30)

As expected, time was associated with the primary outcomes

(Table 4) in both groups. Compared with BL pain intensity, pain inter‐

ference on mood and enjoyment of life were higher for weeks 2–7,

pain interference on general activities was higher for weeks 3–7, and

pain interference on relations with other people and on sleep was

higher weeks 2–9. Student's t tests showed results identical to the

GEE analyses.

3.2 | Secondary outcomes

The effects of intervention with education and SC on the secondary

outcomes were examined using mixed repeated‐measures ANOVA

(Table 5; Figures 4 and 5). The between‐subjects factor consisted of

the two groups (intervention and control), and the within‐subjects

factor was three time points (BL, 4 and 10 weeks).

No statistically significant differences existed between the two

groups except for higher EQ‐VAS at BL (Table 5) and sleep satisfac‐

tion at 10 weeks (Figure 4) in the intervention group.

For both groups, time was associated with the secondary outcomes

(Table 5). Pain intensity and interference were significantly lower at

BL compared with 4 weeks and decreased significantly between 4–

10 weeks. Quality of life (EQ‐VAS) was statistically significantly

higher at BL compared with 4 and 10 weeks. Depressive symptoms

(HAD depression) were statistically significantly lower at BL compared

with 4 weeks. Barriers to pain management (BQ‐II) were significantly

lower at 4 and 10 weeks compared with BL. Student's t tests showed

results identical to the mixed repeated‐measures ANOVA analyses.

4 | D ISC USSI O N

This study did not find any significant group differences for the primary

outcomes or for the secondary outcomes during RT. The only exception

was sleep satisfaction, which was significantly higher in the interven‐

tion group at the end of RT. Although the QoL BL scores were signifi‐

cantly higher in the intervention group at BL, they were decreased to

the similar level as the control group at the weeks 4 and 10. As expected

for both groups, associations with time regarding all outcomes during

the RT were found. To our knowledge, no study on pain education and

SC for patients with HNC during RT has been published.

Our results are partly in line with previous RCTs on tailored pain

education and SC during treatment including, for example, RT for

patients with various cancer diseases that did not find any differ‐

ences in pain intensity (Kravitz et al., 2011). The authors of a review

on education and SC (Koller et al., 2012) conclude no improvements

for outpatients, a finding that agrees with our study comprised en‐

tirely of outpatients. One review concluded, however, that patients

with cancer reduced their pain after education and SC (Bennett et

P a in

in te

rf e

re n

ce Q

3

P a

in in

te rf

e re

n ce

Q 1

B a

se lin

e (

w e

e k

1 )

2 w

e e

ks

3 w

e e

ks

4 w

e e

ks

B a

se lin

e (

w e

e k

1 )

2 w

e e

ks

3 w

e e

ks

4 w

e e

ks

5 w

e e

ks

6 w

e e

ks

7 w

e e

ks

8 w

e e

ks

9 w

e e

ks

1 0 w

e e

ks

5 w

e e

ks

6 w

e e

ks

7 w

e e

ks

8 w

e e

ks

9 w

e e

ks

1 0

w e e

ks

B a

se lin

e (

w e

e k

1 )

2 w

e e

ks

3 w

e e

ks

4 w

e e

ks

5 w

e e

ks

6 w

e e

ks

7 w

e e

ks

8 w

e e

ks

9 w

e e

ks

1 0 w

e e

ks

B a

se lin

e (

w e

e k

1 )

2

w e e

ks

3 w

e e

ks

4 w

e e

ks

5 w

e e

ks

6 w

e e

ks

7 w

e e

ks

8 w

e e

ks

9 w

e e

ks

P a

in in

te rf

e re

n ce

Q 5

1 0

w e e

ks

TA B L E 5 Secondary outcomes results from baseline, 4 and 10 weeks and comparisons between‐ and within‐subjects effects (ANOVA)

Baseline mean (SD) 4 weeks, mean (SD) 10 weeks, mean (SD)

p‐value p‐value p‐value p‐value

Intervention Control (be‐ Intervention Control (be‐ Intervention Control (be‐ (within‐sub‐

group group tween group group tween group group tween jects effect Significant post hoc

Variables (N = 34) (N = 30) groups) (N = 34) (N = 30) groups) (N = 34) (N = 30) groups) over time) comparisons

EQ‐5D‐index (range 0.85 (0.16) 0.78 (0.27) .20 0.71 (0.20) 0.68 (0.27) .62 0.76 (0.21) 0.73 (0.27) .71 .003 BL versus 4 weeks; p = .003

−1–+1)

Overall effect: p = .57

EQ‐VAS (range 80.74 (14.24) 68.90 .02 68.28 (19.94) 61.88 .24 74.83 (17.92) 72.43 .67 .000 BL versus 4 weeks; p = .000

0–100) (22.34) (21.22) (22.41) BL versus 10 weeks; p = .001

Overall effect: p = .28

BPI‐intensity (range 6.85 (7.94) 8.13 (9.48) .56 13.0 (8.12) 14.27 .64 8.28 (8.63) 8.46 .94 .000 4 weeks versus BL; p = .000

0–50) (11.56) (10.23) 4 weeks versus 10 weeks;

p = .003

Overall effect: p = .93

BPI‐interference 8.26 (9.57) 8.46 .94 14.82 (11.75) 15.96 .78 9.53 (10.85) 12.67 .41 .001 4 weeks versus BL; p = .002

(range 0–70) (11.18) (17.02) (15.83) 4 weeks versus 10 weeks;

p = .037

Overall effect: p = .91

HAD‐anxiety (range 3.79 (3.29)

0–21)

3.63 (3.86) .86 2.97 (2.88) 3.19 (3.85) .80 2.90 (3.23) 2.88 (3.66) .98 .454 NA

Overall effect: p = .59

HAD depression 2.38 (2.34) 3.67 (3.74) .11 3.42 (2.90) 4.28 (3.76) .35 3.55 (3.41) 3.72 (3.34) .85 .008 BL versus 4 weeks; p = .007

(range 0–21)

Overall effect: p = .73

PCS (range 0–52) 8.82 (9.33) 9.34 .83 7.70 (7.76) 9.88 (12.53) .46 9.65 (9.37) 7.20 (9.42) .34 .627 NA (10.38)

Overall effect: p = .74

Sleep pattern (range 2.21 (1.57) 2.15 (1.56) .88 1.42 (1.39) 1.20 (1.44) .56 1.00 (1.37) 2.08 (1.77) .02 .002 BL versus 4 weeks; p = .001

0–4) BL versus 10 weeks; p = .045

BQ‐II (range 0–135) 54.67 (20.45) 48.10

(20.99)

.27 39.33 (20.78) 38.50

(24.47)

.90 38.38

(21.49)

38.26

(28.53)

.99 .000 BL versus 4 weeks; p = .000

BL versus 10 weeks; p = .001

Notes: Significant differences are in bold. The estimated impact (i.e. overall effect) of treatment reflects the “combined” within‐ and between‐subjects effects.

Abbreviations: BL, baseline; BP I, Brief Pain Inventory; BQ‐II, Barrier Questionnaire; EQ‐5D, EuroQoL‐5‐Dimension Questionnaire; EQ‐VAS, Euro Quality of Life Vertical Visual Analogue Scale; HAD, Hospital

Anxiety and Depression Scale; NA, not applicable; PCS, Pain Catastrophizing Scale; SD, standard deviation.

Overall effect: p = .11

Overall effect: p = .56

1 0

|

S Ö

D E R

L U

N D

S C H

A L L E R

E t A

L.

| SÖDERLUND SCHALLER Et AL. 11

Intervention group

Control group

M e

a n P

C S

M e

a n

B Q

-I I

M e

a n

B P

I I n

te rf

e re

n c

e

F I G U R E 4 Scores of secondary

outcomes and standard deviation (vertical

bars), for the intervention group (N = 34)

and the control group (N = 30)

1.0

0.5

0.0

–0.5

Intervention group

Control group

100

80

60

40

20

Intervention group

Control group

–1.0

50

Intervention group

Control group

0

Baseline 4 weeks 10 weeks

Time

40

60

30

40 20

10 20

0

Baseline 4 weeks 10 weeks

Time

0

Baseline 4 weeks 10 weeks

Time

Baseline 4 weeks 10 weeks

Time

30

20

15 20

10

10

5

0

Baseline 4 weeks 10 weeks

Time

Intervention group

4 Control group

3

0

Baseline 4 weeks 10 weeks

Time

80

60

2 40

F I G U R E 5 Scores of secondary

outcomes with and standard deviation

(vertical bars), for the intervention group

(N = 34) and the control group (N = 30)

1

0

Baseline 4 weeks 10 weeks

Time

20

0

Baseline 4 weeks 10 weeks

Time

20

15

Intervention group

Control group

10

5

0

Intervention group

Control group

Baseline 4 weeks

Time

10 weeks

Intervention group

Control group

Intervention group

Control group

M e

a n

H A

D -A

n xi

e ty

M

e a

n E

Q -5

D -i

n d

e x

S

le e

p p

a tt

e rn

M

e a

n B

P I

In te

n s it y

M e

a n

H A

D -D

e p re

s s io

n

M e

a n

E Q

-V A

S

12 | SÖDERLUND SCHALLER Et AL.

al., 2009). Consistent with previous research (Babin et al., 2008;

Bennett et al., 2009; Ling et al., 2012), all patients in our study re‐

ported high QoL, which significantly decreased during RT. This was

also the case for depressive symptoms. The literature is, however,

contradictory regarding the effects of education and SC on depres‐

sive symptoms in patients with cancer (Dodd et al., 2010; Howell et

al., 2017; Krischer, Xu, Meade, & Jacobsen, 2007).

The improvement on sleep satisfaction favouring the intervention

group at week 10 should be treated with caution as the overall results

do not point to significant effects of education and SC, and therefore,

this could represent a random finding. Moreover, sleep satisfaction

was measured using only one item of the ISI despite the fact that this

item was derived from the Swedish version of the ISI, which has good

internal consistency (Dragioti, Wiklund, Alföldi, & Gerdle, 2015). Both

groups had the significantly highest barriers to pain management at

BL. Self‐gathering of knowledge (Wong, 2012) and the weekly follow‐

ups might have been sources of appropriate information and subse‐

quently reduced barriers in both groups. Our results are in line with

a review that concluded that the influence of education on pain man‐

agement barriers is limited (Oldenmenger et al., 2009).

One explanation for the mainly similar outcomes of the groups

might be the amount of attention given. That is, SMS, the weekly fol‐

low‐ups and the survey questionnaire, which included both groups,

might have influenced the relative impact of our interventions.

During the study period, both groups with ongoing cancer treat‐

ment in our study necessarily met regularly with other healthcare

professionals – such as oncologists, radiotherapists and dentists –

who provided advice according to their treatment as usual. This es‐

sential advice together with the interventions of our project might

have been experienced as excessive information to make efficient

use for the patients and thus might have contributed to a maybe rel‐

atively limited impact of our education and SC interventions. In line

with a study of Astrup, Rustøen, Miaskowski, Paul, and Bjordal (2015)

but in contrast to two other studies (Elting, Cooksley, Chambers, &

Garden, 2007; Epstein, Wilkie, Fischer, Kim, & Villines, 2009), the

patients in our study reported relatively low pain intensity. This

might have constituted a floor effect and thus limited effects of our

interventions.

Eight critical core elements of SC education inventions for

patients with cancer have been identified (Howell et al., 2017).

Several of the core elements were closely observed in our study

but some were probably not emphasized enough. Many fac‐

tors serve as barriers and facilitators to SC (Riegel, Jaarsma, &

Strömberg, 2012), and our consideration of these factors may

have been insufficient.

We found a tendency, although not significant, to less pain in‐

tensity in the intervention group when speaking, eating and talking

and when not performing the above‐mentioned activities at approx‐

imately the middle of the study period (Figure 2).

The main limitations include the simple method of randomiza‐

tion, which may lead to poor allocation concealment and the lack of

blindness, which further accounts for a significant risk of confound‐

ing. However, due to the nature of the disease, the blindness in this

study was not possible. The relatively low BL pain intensity may clar‐

ify why no significant differences were found (i.e. small possibility of

improvement) and possibly constitutes an unintended bias related

to denial to participate in the study by patients most affected by

the HNC. One may argue that nurses are not trained in teaching pa‐

tients, although in our study the intervention was structured, the

TRNs were clinically experienced in the field of pain management

for HNC patients and we can assume that our nursing staff was

highly qualified. The interventions were manualized but treatment

fidelity was not assessed, which might have influenced the accuracy

of the delivered interventions (Dragioti, Dimoliatis, Fountoulakis, &

Evangelou, 2015) beyond their “home‐made” nature. Hence, threats

to internal validity may be present.

The strengths of this study include the very low dropout rates,

little missing data and the participants' recruitment from the

ordinary flow of patients at a department specialized in pain

management at a university hospital. The representativeness of

socio‐demographics in our sample was in line with the general

socio‐demographic profile of patients with HNC. Thus, we can infer

that our results have population validity. However, ecological

validity and further generalizability also may be limited due to the

relatively less impaired population.

5 | C O NCLUS IO NS

The study concluded that all included patients felt relatively healthy

during and after RT. The patients generally reported low pain and

good QoL, mood and sleep. However, it was not possible to confirm

that patient education and SC reduced pain intensity or improved

QoL, mood and sleep during and after RT treatment for HNC.

6 | C LI NI CAL IMPLICATIONS AND FUTURE

RESE ARCH

The study's methodology is based on the structure and the con‐

tinuity of the personal meeting between the patient and the car‐

egiver and close reporting of symptoms (i.e. pain, QoL, mood and

sleep). This applies to both the control and intervention groups (i.e.

irrespective of patient education). A secondary effect of the study

method probably encouraged the patient to pay attention to per‐

ceived symptoms and thus give the caregiver the opportunity to ini‐

tiate adequate pain management in time. The study shows that it is

not primarily pain education that the patient needs. Future research

should include the identification of other needs that arise during the

cancer treatment and how to optimize treatment for the patient's

pain management and QoL.

ACKNOWLEDGEMENTS

We thank Anna Peterson and Marie Berggarden for including pa‐

tients in the study and implementing the interventions.

| SÖDERLUND SCHALLER Et AL. 13

AUTHOR CONTRIBUTIONS

ASS and BL: Study conception and study design. ED, BL ASS and

GL: Data analyses and manuscript drafting. All authors discussed the

results, commented on the manuscript in different versions and ap‐

proved the current version of the manuscript.

RESE ARCH E THIC S COMMIT TEE APPROVAL

All procedures performed in studies involving human participants

were in accordance with the ethical standards of the institutional

and/or national research committee. (Medical Ethical Board of

Linköping University diary number 2014/356‐31) and with the 1964

Helsinki declaration and its later amendments or comparable ethi‐

cal standards. Informed consent was obtained from all participants

included in the study.

ORCID

Anne Söderlund Schaller https://orcid.org/0000‐0002‐0380‐3365

Elena Dragioti https://orcid.org/0000‐0001‐9019‐4125

Gunilla M. Liedberg https://orcid.org/0000‐0003‐2980‐2835

Britt Larsson https://orcid.org/0000‐0001‐6924‐9910

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SUPPORTING INFORMATION

Additional supporting information may be found online in the

Supporting Information section at the end of the article.

How to cite this article: Söderlund Schaller A, Dragioti E,

Liedberg GM, Larsson B. Are patient education and self‐care

advantageous for patients with head and neck cancer? A

feasibility study. Nursing Open. 2019;00:1–14. https://doi.

org/10.1002/nop2.361