Depression is considered the most frequent mental disorder among the older population

CLINICAL ISSUES

The effect of nurse–patient interaction on anxiety and depression in cognitively intact nursing home patients

Gørill Haugan, Siw T Innstrand and Unni K Moksnes

Aims and objectives. To test the effects of nurse–patient interaction on anxiety and depression among cognitively intact

nursing home patients.

Background. Depression is considered the most frequent mental disorder among the older population. Specifically, the

depression rate among nursing home patients is three to four times higher than among community-dwelling older people,

and a large overlap of anxiety is found. Therefore, identifying nursing strategies to prevent and decrease anxiety and depres-

sion is of great importance for nursing home patients’ well-being. Nurse–patient interaction is described as a fundamental

resource for meaning in life, dignity and thriving among nursing home patients.

Design. The study employed a cross-sectional design. The data were collected in 2008 and 2009 in 44 different nursing

homes from 250 nursing home patients who met the inclusion criteria.

Methods. A sample of 202 cognitively intact nursing home patients responded to the Nurse–Patient Interaction Scale and

the Hospital Anxiety and Depression Scale. A structural equation model of the hypothesised relationships was tested by

means of LISREL 8.8 (Scientific Software International Inc., Lincolnwood, IL, USA).

Results. The SEM model tested demonstrated significant direct relationships and total effects of nurse–patient interaction on

depression and a mediated influence on anxiety.

Conclusion. Nurse–patient interaction influences depression, as well as anxiety, mediated by depression. Hence, nurse–

patient interaction might be an important resource in relation to patients’ mental health.

Relevance to clinical practice. Nurse–patient interaction is an essential factor of quality of care, perceived by long-term nurs-

ing home patients. Facilitating nurses’ communicating and interactive skills and competence might prevent and decrease

depression and anxiety among cognitively intact nursing home patients.

Key words: anxiety, depression, nurse–patient interaction, nursing home, structural equation model analysis

Accepted for publication: 11 September 2012

Introduction

With advances in medical technology and improvement in the

living standard globally, the life expectancy of people is

increasing worldwide. The document An Aging World (US

Census Bureau 2009) highlights a huge shift to an older popu-

lation and its consequences. Within this shift, the most rapidly

growing segment is people over 80 years old: by 2050, the per-

centage of those 80 and older would be 31%, up from 18% in

1988 (OECD 1988). These perspectives have given rise to the

notions of the ‘third’ (65–80 years old) and the ‘fourth age’

(over 80 years old) in the lifespan developmental literature

(Baltes & Smith 2003). These notions are also referred to as

the ‘young old’ and the ‘old old’ (Kirkevold 2010).

Authors: Gørill Haugan, PhD, RN, Associate Professor, Faculty of

Nursing, Research Centre for Health Promotion and Resources,

Sør-Trøndelag University College, HIST, Trondheim; Siw T

Innstrand, PhD, Associate Professor, Research Centre for Health

Promotion and Resources Norwegian University of Science and

Technology, NTNU, Trondheim; Unni K Moksnes, PhD, RN,

Associate Professor, Faculty of Nursing, Research Centre for

Health Promotion and Resources, Sør-Trøndelag University

College, HIST, Trondheim, Norway

Correspondence: Gørill Haugan, Associate Professor, Research

Centre for Health Promotion and Resources, HIST/NTNU, NTNU,

SVT/ISH, 7491 Trondheim, Norway. Telephone:

+47 73 55 29 27.E-mail: gorill.haugan@hist.no

© 2013 Blackwell Publishing Ltd 2192 Journal of Clinical Nursing, 22, 2192–2205, doi: 10.1111/jocn.12072

 

 

For many of those in the fourth age, issues such as physi-

cal illness and approaching mortality decimates their func-

tioning and subsequently lead to the need for nursing home

(NH) care. A larger proportion of older people will live for

shorter or longer time in a NH at the end of life. This

group will increase in accordance with the growing popula-

tion older than 65, and in particular for individuals older

than 80 years. Currently, 1�4 million older adults in the USA live in long-term care settings, and this number is

expected to almost double by 2050 (Zeller & Lamb 2011).

In Norway, life expectancy by 2050 is 90�2 years for men and 93�4 years for women (Statistics of Norway 2010). Depression is one of the most prevalent mental health

problems facing European citizens today (COM 2005);

and, the World Health Organization (WHO 2001) has esti-

mated that by 2020, depression is expected to be the high-

est ranking cause of disease in the developed world.

Moreover, depression is described to be one of the most

frequent mental disorders in the older population and is

particularly common among individuals living in long-term

care facilities (Choi et al. 2008, Karakaya et al. 2009,

Lattanzio et al. 2009, Drageset et al. 2011, Phillips et al.

2011). A linear increase in prevalence of depression with

increasing age is described (Stordal et al. 2003); the three

strongest explanatory factors on the age effect of depression

are impairment, diagnosis and somatic symptoms, respec-

tively (Stordal et al. 2001, 2003). Worse general medical

health is seen as the strongest factor associated with depres-

sion among NH patients (Djernes 2006, Barca et al. 2009).

A review that included 36 studies from various countries,

reported a prevalence rate for major depression ranging

from 6–26% and from 11–50% for minor depression.

However, the prevalence rate for depressive symptoms ran-

ged from 36–49% (Jongenelis et al. 2003). Twice as many

women are likely to be affected by depression than men

(Kohen 2006), and older people lacking social and emo-

tional support tend to be more depressed (Grav et al.

2012). A qualitative study on successful adjustment among

women in later life identified three main areas as being the

main obstacles for many; these were depression, maintain-

ing intimacy through friends and family and managing the

change process associated with older age (Traynor 2005).

Significantly more hopelessness, helplessness and depres-

sion are found among patients in NHs compared with those

living in the community (Ron 2004). Jongenelis et al.

(2004) found that depression was three to four times higher

in NH patients than in community-dwelling adults. Moving

to a NH results from numerous losses, illnesses, disabilities,

loss of functions and social relations, and approaching mor-

tality, all of which increases an individual’s vulnerability

and distress; in particular, loneliness and depression are iden-

tified as risks to the well-being of older people (Routasalo

et al. 2006, Savikko 2008, Drageset et al. 2012). The NH

life is institutionalised, representing loss of social relation-

ships, privacy, self-determination and connectedness.

Because NH patients are characterised by high age, frailty,

mortality, disability, powerlessness, dependency and vulner-

ability, they are more likely to become depressed. A recent

literature review showed several studies reporting prevalence

of depression in NHs ranging from 24–82% (Drageset et al.

2011). Also, with a persistence rate of more than 50% of

depressed patients still depressed after 6–12 months, the

course of major depression and significant depressive symp-

toms in NH patients tend to be chronic (Rozzini et al.

1996, Smalbrugge et al. 2006a).

Moreover, studies in NHs report a large co-occurrence of

depression and anxiety (Beekman et al. 2000, Kessler et al.

2003, Smalbrugge et al. 2005, Van der Weele et al. 2009,

Byrne & Pachana 2010). A recent review concerning anxi-

ety and depression reports a paucity of findings on anxiety

in older people (Byrne & Pachana 2010). Hence, more

research is urgently required into anxiety disorders in older

people, as these are highly prevalent and associated with

considerable disease burden (ibid.).

Depression and anxiety in NH patients are associated

with negative outcomes such as poor functioning in

activities of daily living and impaired quality of life (QoL)

(Smalbrugge et al. 2006b, Diefenbach et al. 2011, Drageset

et al. 2011), substantial caregiver burden and worsened

medical outcomes (Bell & Goss 2001, Koenig & Blazer

2004, Sherwood et al. 2005), increased risk of hospital

admission (Miu & Chan 2011), a risk of increased demen-

tia (Devanand et al. 1996) and a higher mortality rate

(Watson et al. 2003, Ahto et al. 2007). Accordingly, efforts

to prevent and decrease depression and anxiety are of great

importance for NH patients’ QoL.

Social support and relations to significant others are

found to be a vital resource for QoL and thriving among

NH patients (Bergland & Kirkevold 2005, 2006, Drageset

et al. 2009a, Tsai et al. 2010, Tsai & Tsai 2011), as well

as the nurse–patient relationship (Haugan Hovdenes 2002,

Cox & Bottoms 2004, Franklin et al. 2006, Medvene &

Lann-Wolcott 2010, Burack et al. 2012). The perspective

of promoting health and well-being is fundamental in nurs-

ing and a major nursing concern in long-term care (Nakrem

et al. 2011, Drageset et al. 2009b). However, low rates of

recognition of depression by staff nurses is found (Bagley

et al. 2000, Volkers et al. 2004).

Through the last decades, the importance of establishing

the nurse–patient relationship as an integral component of

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Clinical issues Nurse-patient-interaction, depression, and anxiety

 

 

nursing practice has been well documented (Nåden &

Eriksson 2004, Arman 2007, Carpiac-Claver & Levy-

Storms 2007, Granados Gámez 2009, Rchaidia et al. 2009,

Fakhr-Movahedi et al. 2011). Excellent nursing care is

characterised by a holistic view with inherent human values

and moral; thus, excluding the patient as a unique human

being should be regarded as noncaring and amoral practice

(Haugan Hovdenes 2002, Nåden & Eriksson 2004, Aust-

gard 2008, Watson 2008). NH patients are in general

extremely vulnerable and hence the nurse–patient relation-

ship and the nurse–patient interaction are critical to their

experience of dignity, self-respect, sense of self-worth and

well-being (Dwyer et al. 2008, Harrefors et al. 2009,

Heliker 2009). NH patient receiving self-worth therapy

showed statistically significantly reduced depressive symp-

toms relative to control groups members 2 months after

receiving the intervention (Tsai et al. 2008). Self-worth

therapy comprised establishment of a therapeutic relation-

ship offering feedback and focusing the patient’s dignity,

emotional and mental well-being (ibid.).

Caring nurses engage in person-to-person relationships

with the NH patients as unique persons. Good nursing care

is defined by the nurses’ way of being present together with

the patient while performing nursing activities, in which

attitudes and competence are inseparately connected. ‘Pres-

ence’, ‘connectedness’ and ‘trust’ are described as funda-

mental cores of holistic nursing care (McGilton & Boscart

2007, Potter & Frisch 2007, Carter 2009) in the context of

the nurse–patient relationship in which the nurse–patient

interaction is taking place. Trust is seen as a confident

expectation that the nurses can be relied upon to act with

good will and to secure what is best for the individuals

residing in the NH. Hence, trust is the core moral ingredi-

ent in nurse–patient relationships; even more basic than

duties of beneficence, respect, veracity, and autonomy

(Carter 2009).

Caring is a context-specific interpersonal process that is

characterised by expert nursing practice, interpersonal sen-

sitivity, and intimate relationships (Finfgeld-Connett 2008)

which increases patient’s well-being (Nakrem et al. 2011,

Hollinger-Samson & Pearson 2000, Cowling et al. 2008,

Rchaidia et al. 2009, Reed 2009). The relationship between

NH staff attention and NH patients’ affect and activity par-

ticipation have been assessed among depressed NH

patients, showing that positive staff engagement was signifi-

cantly related to patients’ interest, activity participating,

and pleasure (Meeks & Looney 2011). These results suggest

that staff behaviour and engagement could be a reasonable

target for interventions to increase positive affect among

NH patients (ibid.).

In summary, the literature suggests depression as a com-

mon mental disorder among older people characterised by

high age, impairment, and somatic symptoms. In addition,

a large overlap of anxiety is reported. The patients’ sense

of loss of independency and privacy, feelings of isolation

and loneliness, and lack of meaningful activities are risk

factors for depression in NH patients. Nurse–patient inter-

action might be a resource for preventing and decreasing

depression among NH patients. To the authors’ knowl-

edge, previous research has not examined these relation-

ships in NHs by means of structural equation modelling

(SEM).

Aims

The main aim of this study was to investigate the relation-

ships between nurse–patient interaction, anxiety and

depression among cognitively intact NH patients by means

of SEM. Based on the theoretical and empirical knowledge

of depression, anxiety and nurse–patient interaction our

research question was: ‘Does the nurse–patient interaction

affect anxiety and depression in cognitively intact NH

patients?’ The following hypotheses were formulated:

� Hypothesis 1 (H1): nurse–patient interaction positively affects anxiety.

� Hypothesis 2 (H2): nurse–patient interaction positively affects depression.

� Hypothesis 3 (H3): depression negatively affects anxiety.

Methods

Design and ethical considerations

The study employed a cross-sectional design. The data was

collected in 2008 and 2009 in 44 different NHs from 250

NH patients who met the inclusion criteria: (1) local

authority’s decision of long-term NH care; (2) residential

time six months or longer; (3) informed consent compe-

tency recognised by responsible doctor and nurse; and (4)

capable of being interviewed. Two counties comprising in

total 48 municipalities in central Norway were selected,

from which 25 (at random) were invited to contribute in

this study. In total, 20 municipalities were partaken. Then,

all the NHs in each of the 20 municipalities was asked to

participate. A total of 44 NHs took part in the study. To

include as many participants from rural and central NHs,

respectively, the NHs was one by one invited to participate,

until the minimum of n = 200 was reached. The NH

patients were approached by a head nurse they knew

well. The nurse presented them with oral and written

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G Haugan et al.

 

 

information about their rights as participants and their

right to withdraw at any time. Each participant provided

informed consent. Because this population has problems

completing a questionnaire independently, three trained

researchers conducted one-on-one interviews in the patient’s

room in the actual NH. Researchers with identical profes-

sional background were selected (RN, MA, trained and

experienced in communication with older people, as well as

teaching gerontology at an advanced level) and trained to

conduct the interviews as identically as possible. Inter-rater

reliability was assessed by comparing mean scores between

interviewers by means of Bonferroni-corrected one-way

ANOVAs. No statistically significant differences were found

that were not accounted for by known differences between

the areas in which the interviewers operated.

The questionnaires relevant for the present study were part

of a questionnaire comprising 130 items. The interviews

lasted from 45–120 minutes due to the individual partici-

pant’s tempo, form of the day, and need for breaks. Inter-

viewers held a large-print copy of questions and possible

responses in front of the participants to avoid misunder-

standings. Approval by the Norwegian Social Science Data

Services was obtained for a licence to maintain a register

containing personal data (Ref. no. 16443) and likewise we

attained approval from The Regional Committee for

Medical and Health Research Ethics in Central Norway

(Ref. no. 4.2007.645) as well as the directory of the 44 NHs.

Participants

The total sample comprised 202 (80�8%) of 250 long-term NH patients representing 44 NHs. Long-term NH care was

defined as 24-hour care; short-term care patients, rehabilita-

tions patients, and cognitively impaired patients were not

included. Participants’ age was 65–104, with a mean of

86 years (SD = 7�65). The sample comprised 146 women (72�3%) and 56 men (27�7%), where the mean age was

87�3 years for women and 82 years for men. A total of 38 (19%) were married/cohabitating, 135 (67%) were widows/

widowers, 11 (5�5%) were divorced, and 18 (19%) were single. Duration of time of NH residence when interviewed

was at mean 2�6 years for both sexes (range 0�5–13 years); 117 were in rural NHs, while 85 were in urban NHs. In

all, 26�1% showed mild to moderate depression, only one woman scored >15 indicating severe depression, 70�4% was not depressed, and nearly 88% had no anxiety disor-

der. Missing data was low in frequency and was handled

by means of the listwise procedure; for the nurse–patient

interaction 4�0% and for anxiety and depression 5�0% had some missing data.

Measures

The Nurse–Patient Interaction Scale (NPIS) was developed

to identify important characteristics of NH patients’ experi-

ences of the nurse–patient interaction. The NPIS comprises

14 items identifying essential relational qualities stressed in

the nursing literature (Watson 1988, Martinsen 1993,

Eriksson 1995a,b, Nåden & Eriksson 2004, Nåden &

Sæteren 2006, Levy-Malmberg et al. 2008). Examples of

NPIS-items include ‘Having trust and confidence in the staff

nurses’; ‘The nurses take me seriously’, ‘Interaction with

nurses makes me feel good’ as well as experiences of being

respected and recognised as a person, being listened to and

feel included in decisions. The items were developed to

measure the NH patients’ ability to derive a sense of well-

being and meaningfulness through the nurse–patient inter-

action (Haugan Hovdenes 1998, 2002, Hollinger-Samson

& Pearson 2000, Finch 2006, Rchaidia et al. 2009). The

NPIS has shown good psychometric properties with good

content validity and reliability among NH patients;

(Haugan et al. 2012). The NPIS is a 10-points scale from 1

(not at all)–10 (very much); higher numbers indicating

better nurse–patient interaction (Appendix 1). Cronbach’s

Table 1 Means (M), standard deviations (SD), Cronbach’s alpha, and correlation coefficients for the study variables

Construct M SD Cronbach’s alpha NPIS HADS-A HADS-D

NPIS (10 items) 8�19 1�73 0�92 – HADS-A (5 items) 0�40 0�50 0�79 �0�114 – HADS-D (5 items) 0�74 0�58 0�66 �0�294* 0�340* – HADS (14 items) 2�85 0�34 0�78

*p < 0�01. NPIS, Nurse–Patient Interaction Scale; HADS, Hospital Anxiety and Depression Scale; HADS-A, Hospital Anxiety and Depression Scale –

Anxiety; HADS-D, Hospital Anxiety and Depression Scale – Depression.

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Clinical issues Nurse-patient-interaction, depression, and anxiety

 

 

a = 0�92 (Table 1) and composite reliability = 0�92 (Table 2) of the NPIS construct was good.

Anxiety and depression were assessed by the Hospital

Anxiety and Depression Scale (HADS), comprising 14 items

(Appendix 2), with subscales for anxiety (HADS-A; seven

items) and depression (HADS-D seven items). Each item is

rated from 0–3, where higher scores indicate more anxiety

and depression. The maximum score is 21 on each subscale.

The ranges of scores for cases are as follows: 0–7 normal,

8–10 mild disorder, 11–14 moderate disorder, and 15–21

severe disorder (Snaith & Zigmond 1994). HADS has been

tested extensively and has well-established psychometric

properties (Herrmann 1997). To increase acceptability and

avoid individuals feeling as though they are being tested for

mental disorders, symptoms of severe psychopathology

have been excluded. This makes HADS more sensitive to

milder psychopathology (Stordal et al. 2003). HADS is

translated into Norwegian and found to be valid for older

people (Stordal et al. 2001, 2003).

Examples of sample-items are for depression: ‘I still enjoy

the things I used to enjoy’, ‘I can laugh and see the funny side

of things’, ‘I feel cheerful’, ‘I have lost interest in my appear-

ance’, and ‘I look forward with enjoyment to things’, and for

anxiety: ‘I feel tense and wound up’, ‘I get a sort of frightened

feeling as if something awful is about to happen’, ‘Worrying

thoughts go through my mind’, ‘I get a sort of frightened feel-

ing like ‘butterflies’ in the stomach’, and ‘I get sudden feeling

of panic’. The items were scored on a four-point scale ranging

from totally disagrees to totally agree. The internal consis-

tence of the anxiety and depression constructs (Table 1) was

satisfactory; a = 0�79 and a = 0�66, respectively. Composite reliability (qc) displayed values between 0�70–0�92 (Table 2); values >0�60 are desirable, whereas values >0·70 are good (Diamantopolous & Siguaw 2008, Hair et al. 2010).

Statistical analysis

A structural equation model (SEM) of the hypothesised

relations between the latent constructs of depression and

self-transcendence was tested by means of LISREL 8.8 (Scien-

tific Software International Inc., Lincolnwood, IL, USA)

(Jøreskog & Sørbom 1995). Using SEM accounts for ran-

dom measurement error and the psychometric properties of

the scales in the model are more accurately derived. Since

the standard errors are estimated under non-normality, the

Satorra–Bentler scaled chi-square statistic was applied as a

goodness-of-fit statistic, which is the correct asymptotic

mean even under non-normality (Jøreskog et al. 2000). In

line with the rules of thumb of conventional cut-off criteria

(Schermelleh-Engel et al. 2003), the following fit indices

were used to evaluate model fit: chi-square (v2); a small v2

and a non-significant p-value corresponds to good fit

(Jøreskog & Sørbom 1995). Further we used the root mean

square error of approximation (RMSEA) and the standar-

dised root mean square residual (SRMS) with values below

0�05 indicating good fit, while values smaller than 0�08 are interpreted as acceptable (Hu & Bentler 1998, Schermelleh-

Engel et al. 2003). The comparative fit index (CFI) and the

non-normed fit index (NNFI) with an acceptable fit at 0�95, and good fit at 0�97 and above were used, and the normed fit index (NFI) with an acceptable fit at 0�90, while a good fit was set to 0�95 (ibid.). Before examining the hypothesised relationships in the

SEM analysis, the measurement models were tested by con-

firmatory factor analysis (CFA). The CFA provided a good

fit to the observed data for the nurse–patient interaction

construct comprising ten items (v2 = 92�32, df = 77,

Table 2 Measurement models included in Model 1: nurse–patient

interaction (NPIS) to anxiety (HADS-A) and depression (HADS-D)

Items Parameter Lisrel estimate t-value R2

NPIS

NPIS1 kx1,1 0�63 6�04** 0�39 NPIS2 kx2,1 0�74 8�99** 0�55 NPIS3 kx3,1 0�74 10�41** 0�55 NPIS4 kx4,1 0�81 12�84** 0�65 NPIS5 kx5,1 0�66 6�16** 0�43 NPIS7 kx6,1 0�72 8�25** 0�51 NPIS9 kx7,1 0�77 14�39** 0�60 NPIS11 kx8,1 0�77 11�36** 0�59 NPIS12 kx9,1 0�69 8�18** 0�47 NPIS13 kx10,1 0�78 9�45** 0�61 HADS-A

HADS1 ky5,2 0�62 – 0�39 HADS3 ky7,2 0�73 7�04** 0�53 HADS5 ky11,2 0�62 4�65** 0�39 HADS9 ky13,2 0�69 5�60** 0�40 HADS13 kx14,2 0�66 6�00** 0�43 HADS-D

HADS2 ky1,1 0�74 – 0�54 HADS4 ky2,1 0�67 7�43** 0�45 HADS6 ky3,1 0�65 5�86** 0�42 HADS10 ky5,1 0�20 2�33* 0�04 HADS12 ky6,1 0�51 4�94** 0�26 qc NPIS 10 items qc 0�92 – – qc HADS-A 5 items qc 0�80 – – qc HADS-D 5 items qc 0�70 – –

Standardised factor loadings and t-values. Squared multiple correla-

tions (R2). †Composite reliability, qc ¼

P kð Þ2P

kð Þ2þP hð Þ � � (Hair et al. 2010).

*p < 0�05; **p < 0�01. HADS, Hospital Anxiety and Depression Scale; NPIS, Nurse–

Patient Interaction Scale.

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G Haugan et al.

 

 

p < 0�0110, RMSEA = 0�032, SRMR = 0�045, NFI = 0�97, NNFI = 0�99, CFI = 1�00) and the two-factor construct (HADS) of anxiety and depression comprising 10 items

(v2 = 54�22, df = 34, p < 0�015, RMSEA = 0�056, SRMR = 0�071, NFI = 0�93, NNFI = 0�96, CFI = 0�97). All parameter estimates were significant (p < 0�05) and loaded positively and clearly on their intended latent vari-

able with standardised factor loadings between 0�20–0�81. For scaling, the first factor loadings of each dependent

latent variable were set to 1.

Results

Descriptive analysis

Table 1 displays the means (M), standard deviations (SD),

Cronbach’s a and Pearson’s correlation matrix for the con-

structs of nurse–patient interaction, anxiety and depression.

The correlations between the measures were in the expected

direction. Moderate correlations were found between the

latent constructs included in the SEM model (Table 1). The

a-levels for the various measures indicate an acceptable

level of inter-item consistency in the measures (Nunally &

Bernstein 1994) with Cronbach’s a coefficients of 0�66 or higher.

Structural equation modelling (SEM)

To investigate how the nurse–patient interaction related to

anxiety and depression, model-1 was estimated. Figure 1

shows Model-1 with its measurement and structural

models, while Table 2 displays the factor loadings, R2 and

t-values. All estimates were significant (p < 0�05) and the

factor loadings ranged between 0�51–0�81 (except from item HADS10 ‘I have lost interest in my appearance’ with

factor loading = 0�20 and R2 = 0�04) and R2 values between 0�26–0�65. Model-1 fit well with the data: v2 = 211�44, p = 0�011, df = 167, RMSEA = 0�037, p- value = 0�92, NFI = 0�94, NNFI = 0�99, CFI = 0�99, and SRMR = 0�060. Table 3 shows the standardised regression coefficients of

the directional relationships and the total and indirect

effects between the latent constructs in Model-1. As

hypothesised, the directional paths from nurse–patient

interaction to depression displayed a significant negative

relationship (c1,1 = �0�37). The path between nurse– patient interaction and anxiety was not significant

(c1,2 = �0�09); however, a significant path from depression to anxiety (b1,2 = 0�55) was found, indicating a mediated effect (by depression) on anxiety (Table 3).

A scrutiny of the total effects of nurse–patient interaction

revealed statistical significant total effects on depression

(�0�37), as well as a significant total effect on anxiety from depression (0�55). Also, a significant indirect (mediated) effect from nurse–patient interaction on anxiety (�0�20) was displayed (Table 3).

Discussion

The aim of this study was to explore the associations

between nurse–patient interaction, anxiety, and depression

in cognitively intact NH patients. By doing so we sought to

contribute to a holistic nursing perspective of promoting

well-being in NH patients in three ways:

1 This study supplies empirical knowledge to the growing

body of nurse–patient interaction knowledge by exploring

Figure 1 SEM Model-1. Measurement models

and directional relationships for nurse–patient

interaction (NPIS) to anxiety (HADS-A) and

depression (HADS-D).

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Clinical issues Nurse-patient-interaction, depression, and anxiety

 

 

cognitively intact NH patient’s’ experiences of the nurse–

patient interaction.

2 This study provides empirical insight to the associations

between, nurse–patient interaction, anxiety, and depres-

sion in a NH population, and

3 By means of advanced statistical analysis such as struc-

tural equation modelling (SEM), the result from this

study suggests a guideline for clinical nursing strategies

promoting well-being and decreasing depression and anx-

iety in NH patients. Finding ways to improve NH staff

nurses’ way of being present, connecting, and interacting

with the patients might be beneficial in this matter.

More specifically, three hypotheses were tested, from

which two were supported (H1, H3). We found that the

hypothesised relationship between nurse–patient interaction

and depression was fully supported; good nurse–patient

interaction was negatively associated with depression; the

better nurse–patient interaction the less depression. The

path from nurse–patient interaction to anxiety was not sig-

nificant; however, a significant relation between depression

and anxiety was found. Accordingly, also an indirect effect

of nurse–patient interaction on anxiety was displayed, med-

iated by the influence on depression. Hence, the model

tested indicates that nurse–patient interaction influences

both depression and anxiety. These findings are consistent

with previous research demonstrating significantly decrease

in depression for NH patients receiving self-worth therapy

and positive attention from NH staff (Tsai et al. 2008,

Meeks & Looney 2011).

Consequently, nursing approaches facilitating NH

patient’s confidence and trust in the staff nurses might pre-

vent and decrease depression in NH patients. In accordance

with former research, trust is a core moral ingredient in

helping relationships (Carter 2009). Therefore, facilitating

patients’ confidence that the staff nurses make all possible

effort to relieve ones’ plagues appear to be crucial for pre-

serving dignity (Cochinov 2002) and prevent depression.

Professional nursing care is determined by the way nurses

are using their knowledge, attitudes, behaviour and com-

munication skills to appreciate the uniqueness of the person

being cared for (Warelow et al. 2008). Accordingly, nurse–

patient interaction fostering experiences of being respected

and recognised as a person, being listened to and taken seri-

ously are positively associated with lower depression scores

among NH patients.

Previous research underlines that the nurse–patient

relationships and the nurse–patient interaction are critical

to patients’ sense of dignity, self-respect, feelings of self-

worth, meaning in life, and well-being (Haugan Hovdenes

2002, Dwyer et al. 2008, Harrefors et al. 2009, Heliker

2009). Moreover, dignity in NH patients has been differen-

tiated into intrapersonal dignity and relational dignity,

socially constructed by the act of recognition (Pleschberger

2007). Thus, nurse–patient interaction facilitating patients’

sense of being taken seriously and recognised as a unique

person might provide a sense of dignity, self-worth, and

thereby prevent and decrease depression among NH

patients.

Consequently, taking time for interestingly listening to

the NH patient appears as vital for preventing and decreas-

ing depression. Former research has pointed to continuity

of care provider to be critical for developing relationships

with patients’ overtime (McGilton 2002). Moreover, mutu-

ality in individuals’ relationships confirming women’s exis-

tence and value has been described as a major influence on

depression in women, whereas depressive symptoms results

Table 3 Structural equation modelling analysis: Model-1, standar-

dised gamma, total and indirect effects of nurse–patient interaction

on nursing home patients’ anxiety and depression

Construct Parameter Lisrel estimate t-value

NPIS to HADS-A c 1,1 �0�09 �0�84 NPIS to HADS-D c 1,2 �0�37 �4�58** HADS-D to HADS-A b 1,2 0�55 4�05**

NPIS t-value

Total effects of nurse–patient interaction on anxiety and depression

HADS-D

HADS2 �0�23 �4�58** HADS4 �0�21 �4�32** HADS6 �0�18 �3�62** HADS10 �0�08 �2�03* HADS12 �0�18 �3�48** HADS-A

HADS1 �0�05 �1�30 HADS3 �0�06 �1�34 HADS5 �0�05 �1�27 HADS9 �0�05 �1�25 HADS13 �0�05 �1�36

Indirect effect of nurse–patient interaction on anxiety and

depression

Anxiety �0�20 �3�11** Depression – –

*Significant at the 5% level.

**Significant at the 1% level.

Model 1: comprising six HADS-variables and 10 NPIS-variables.

Standardised gamma: standardised regression coefficients represent-

ing directional relationships between NPIS, anxiety, and depression.

Total effects: represents the total influence of the explanatory

variable on anxiety and depression.

Indirect effects: mediated influence.

HADS, Hospital Anxiety and Depression Scale; NPIS, Nurse–

Patient Interaction Scale.

© 2013 Blackwell Publishing Ltd 2198 Journal of Clinical Nursing, 22, 2192–2205

G Haugan et al.

 

 

from violating their sense of worthiness (Hedelin & Jonsson

2003). Consequently, nurses must be aware that their atti-

tude, appearance and behaviour are interpreted as a confir-

mation of the patient’s worthiness or worthlessness (ibid.).

In a recent study investigating the concept of receiving care,

one main theme was identified; ‘being of value despite any

potential disadvantages’ (Lundgren & Berg 2011). NH

patients are particularly vulnerable and dependent, thus

there are not many choices available. Receiving care high-

lights the human mode of being, which includes experiences

of being exposed resulting in an increased sense of vulnera-

bility; in turn, this motivates a seeking for valued and

appreciated mutual interactions within a caring process

(ibid.). Thus, taking time, ensuring continuity, and being

educated in interactional skills are not enough to enhance

well-being, a sense of meaning in life, and decrease depres-

sion; the care provider must be engaged in some way, such

as learning about the person through life histories (McGil-

ton & Boscart 2007, Walent 2008, Heliker 2009, Heliker

& Hoang Thanh 2010, Medvene & Lann-Wolcott 2010,

Wright 2010). The NH patient needs to feel understood,

acknowledged, confirmed, and valued, all of which provides

a sense of meaning in life, self-worth, and alleviates suffer-

ing (Haugan Hovdenes 2002, Medvene & Lann-Wolcott

2010).

Nursing homes are unique social environments; tradition-

ally, they offer limited privacy opportunities. Accordingly

NH patients may have infrequent contact with friends and

family members. Thus, NH staff nurses are particularly the

most important providers of social reinforcement (Haugan

Hovdenes 2002, Drageset et al. 2012). However, research

illustrates that NH staff rarely engages in social interac-

tions during mealtimes and does not appreciate this as an

important part of their duties (Pearson & Fitzgerald 2003),

as well as hardly responds to patients’ social engagement,

and seldom displays engagement-supportive behaviour

(Stabell et al. 2004, Meeks & Looney 2011). Caregiving

relationships involve all kinds of social interaction during the

course of which the patient’s sense of self-worth can either

be enhanced or thwarted (Haugan Hovdenes 2002, Hedelin

& Jonsson 2003, Halldorsdottir 2008). The nurse–patient

relationship has been designated as a sense of spiritual con-

nection which is experienced as a bond of energy (Hall-

dorsdottir 2008); a life-giving nurse–patient interaction

which is greatly empowering for the patient. By confirma-

tion, recognising, and empowering the older individuals’

views of who they are and would like to be, NH staff

nurses can positively influence NH patients well-being

(Randers et al. 2002, Tsai et al. 2008, Haugan et al.

2012), thriving (Bergland & Kirkevold 2005), and

consequently depression (Haugan & Innstrand 2012) and

anxiety.

Strengths and limitations

A notable strength of this research is the empirical exami-

nation of associations that have not been tested previously.

This study expands previous studies by testing the asso-

ciations between nurse–patient interaction, anxiety, and

depression among NH patients by using structural equa-

tion modelling. Using SEM accounts for random measure-

ment error and the psychometric properties of the scales

in the model are more accurately derived. The study builds

on a strong theoretical foundation with use of question-

naires demonstrating good psychometrical properties. Nev-

ertheless, the findings of this study must be discussed with

some limitations in mind.

First, Model-1 comprises 20 variables, indicating a desir-

able n = 200, while in the present study, n = 191. Informa-

tion input to the SEM estimation increases both with more

indicators per latent variable, as well as with more sample

observations (Westland 2010). The latent variables in the

model are measured by five and ten indicators that

strengthen the reliability. In this respect, the sample size in

the present study is suitable. Nevertheless, a larger sample

would significantly increase statistical power of the tests.

The present sample included fewer men than women,

reflecting the gender composition among the population of

that age in NHs.

Second, the cross-sectional design does not allow us to

determine conclusion regarding causality. A longitudinal

design would have strengthened the study by allowing

changes to be assessed and compared over time.

A third limitation concerns the use of self-reported data,

which implies a certain risk that the findings are based on

common-method variance (Podsakoff et al. 2003).

The fact that the researchers visited the participants to

help fill in the questionnaires might have introduced some

bias into the respondents’ reporting. The questionnaires

were part of a battery of questionnaires comprising 130

items. Thus, frail, older NH patients might tire when com-

pleting the questionnaires; this represents a possible bias to

their reporting. To avoid such a bias, experienced research-

ers were carefully selected and trained in conducting the

interviews following a standardised procedure including

taking small breaks on specific points during the process.

This procedure worked out very well; in just three cases the

interview had to be completed the next day due to respon-

dent’s fatigue. Actually, most participants were even more

vigorous after completing the interview.

© 2013 Blackwell Publishing Ltd Journal of Clinical Nursing, 22, 2192–2205 2199

Clinical issues Nurse-patient-interaction, depression, and anxiety

 

 

Relevance to clinical nursing

According to the European Commission’s Green Paper on

mental health (COM 2005), depression is one of the most

prevalent mental health problems facing European citizens

today. Taking into account the highly chronic nature of these

psychological states, we consider our findings noteworthy in

their suggestion that nurse–patient interaction might be an

important resource in relation to NH patients’ mental health.

Knowledge of how nurse–patient interaction, anxiety and

depression relate to each other in this respect is important for

researchers, nurses, nursing educators and clinicians.

This study demonstrates that nurse–patient interaction

influences depression as well as anxiety mediated by depres-

sion. Accordingly, facilitating nurse–patient interaction to

provide patients’ sense of worthiness, meaning in life, self-

acceptance and adjustment to the life situation and one’s

disabilities would promote integrity and well-being and pre-

vent despair and depression.

Due to a combination of factors such as patients’ commu-

nication impairment, clinicians’ focus on treating medical

conditions, normalisation of depression in later life and a

lack of training in mental health among staff in NHs, depres-

sion can easily go undetected among the NH population

(Bagley et al. 2000, Martin et al. 2007). Therefore, facilitat-

ing nurse–patient interaction and the staff nurses’ awareness

in assessing patients’ mood and connectedness resources

appear to be crucial. Offering connectedness might be a cen-

tral aspect of NH care (Lundman et al. 2010); enhancing

inner strength by acceptance of the self, death and one’s life

situation might prevent and decrease depression among NH

patients (Haugan & Innstrand 2012).

The interpersonal relationship in nurse–patient interac-

tions has been found to be an essential factor of quality of

care, as perceived by long-term care patients (Haugan Hovd-

enes 2002, Bergland & Kirkevold 2006, Brown Wilson &

Davies 2009). Nurse–patient interaction can enhance both

intrapersonal and interpersonal self-transcendence (Haugan

et al. 2012) and help NH patients preserve their dignity,

identity and integrity (Coughlan & Ward 2007, Tsai et al.

2008, Burack et al. 2012). By means of listening to the

patients, communicating and treating the patients with

respect, by using empathic understanding, and acknowledg-

ing him/her as a person who is to be taken seriously and

attended to, staff nurses might positively influence depres-

sion, anxiety, and well-being (Hollinger-Samson & Pearson

2000, Haugan Hovdenes 2002, Asmuth 2004, Finch 2006,

Jonas-Simpson et al. 2006, Haugan et al. 2012).

Therefore, NH staff nurses should be given more time

available interacting with their patients. A philosophical

shift from care and protection of the body to a person-cen-

tred care would be beneficial (Medvene & Lann-Wolcott

2010, Wright 2010, Jones 2011). In addition, some factors

seem crucial regarding quality of nurse–patient interaction;

in general, staffing levels are low while staff turnover is

high (Baughman & Smith 2010). Further, staff members

are generally poorly trained in nurse–patient interaction

providing well-being, and often they perceive a lack of

autonomy in job performance, feeling that they are not

respected for management (Castle & Engberg 2007, Caspar

& O’Rourke 2008, Bishop et al. 2009). To become a car-

ing caregiver, one must first be treated in a caring way

(Sikma 2006, Tellis-Nayak 2007). Hence, moving from the

traditional institutional model to a responsive, patient-cen-

tred homelike approach might have benefits for both NH

patients and staff (Jones 2010). Educational nursing curric-

ula should underline and facilitate nurse–patient interaction

in order of advancing staff nurses’ presence to assess,

prevent and decrease depression and anxiety among NH

patients. Also, essential is for nurses to develop confidence

in using the therapeutic tools available to create the best

mental health outcomes for the older person.

Acknowledgements

The authors wish to acknowledge the Sør-Trøndelag

University College, Faculty of Nursing, Trondheim, Nor-

way, for supporting this study, as well as the older patients

who voluntarily participated in the study.

Contributions

Study design: GH; data collection and analysis: GH and

manuscript preparation: GH, STI, UKM.

Conflict of interest

No conflict of interest has been declared by the authors.

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