CLINICAL ISSUESThe effect of nurse–patient interaction on .docx

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: [email protected]
© 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
Journal of Clinical Nursing, 22, 2192–2205 2193
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
2194 Journal of Clinical Nursing, 22, 2192–2205
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.

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 Þ2
P
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.
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).
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.

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.
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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Appendix 1. Measurement instrument: Nurse–Patient Interaction
Scale (NPIS) means score and
standard deviation
NPIS item
Total
n = 199
Men
n = 56
Women
n = 143
Mean SD Mean SD Mean SD
NPIS1 Having confidence and trust in the nurses 8�75 1�948
8�84 1�886 8�71 1�977
NPIS2 The nurses take me seriously 8�44 2�185 8�43 2�214
8�44 2�181
NPIS3 Interaction with the nurses makes me feel good 8�02
2�252 8�21 2�230 7�94 2�264
NPIS4 The nurses understand me 7�65 2�419 7�71 2�341
7�63 2�457
NPIS5 The nurses make all possible effort to relieve my plagues
8�80 1�969 9�02 1�753 8�71 2�047
NPIS6 The nurses involve me in decisions regarding my daily
life 6�96 2�984 6�45 2�923 7�16 2�993

NPIS7 The nurses treat me with respect 8�68 2�175 8�70
2�097 8�68 2�213
NPIS8 The nurses ask me how I am 7�70 2�959 7�82 2�924
7�66 2�981
NPIS9 The nurses are listening interestingly to me 7�47 2�743
7�74 2�474 7�37 2�840
NPIS10 I often get hurt or sad from how the nurses interact*
8�29 2�510 8�15 2�825 8�35 2�386
NPIS11 Interaction with the nurses contributes to meaning in
my life 7�83 2�531 8�04 2�449 7�75 2�567
NPIS12 The nurses pay attention to me as a person 8�07 2�266
8�13 2�281 8�05 2�268
NPIS13 I am satisfied with the communication with the nurses
8�32 2�126 8�54 2�097 8�23 2�138
NPIS14 Interaction with nurses is the most important to my
thriving 8�86 2�066 9�09 1�890 8�78 2�131
NPIS: total means score 8�13 1�630 8�21 1�654 8�11 1�626
The NPIS is based on a 10-point scale ranging from 1 (not at
all) to 10 (very much).
The concept of nurses involves all staff caregivers.
*The item NPIS10 is reversed.
G Haugan et al.
Appendix 2. Measurement instrument: Hospital Anxiety and
Depression Scale (HADS) means score
and standard deviation

HADS item
Total
n = 198
Men
n = 56
Women
n = 142
Mean SD Mean SD Mean SD
HADS1 I feel tense and wound up 0�460 0�680 0�339 0�581
0�507 0�712
HADS2 I still enjoy the things I used to enjoy 0�879 0�822
0�893 0�779 0�873 0�841
HADS3 I get a sort of frightened feeling as if something awful
is about to happen 0�434 0�709 0�400 0�655 0�447 0�731
HADS4 I can laugh and see the funny side of things 0�621
0�845 0�589 0�826 0�634 0�855
HADS5 Worrying thoughts go through my mind 0�394 0�710
0�339 0�640 0�416 0�737
HADS6 I feel cheerful 0�533 0�759 0�582 0�686 0�514
0�788
HADS7 I can sit at ease and feel relaxed 0�459 0�689 0�611
0�738 0�401 0�664
HADS8 I feel as I’m slowed down 1�209 1�075 1�226 1�050
1�203 1�088
HADS9 I get a sort of frightened feeling like ‘butterflies’ in the
stomach 0�369 0�613 0�339 0�581 0�380 0�627
HADS10 I have lost interest in my appearance 0�803 1�079
0�946 1�119 0�747 1�061

HADS11 I feel restless as if have to be on the move 0�523
0�793 0�636 0�825 0�479 0�778
HADS12 I look forward with enjoyment to things 0�864 0�943
0�857 0�999 0�866 0�924
HADS13 I get sudden feeling of panic 0�347 0�658 0�357
0�699 0�343 0�643
HADS14 I can enjoy a good book or TV programme 0�561
0�857 0�464 0�713 0�599 0�907
HADS anxiety sum score 3�03 2�903 3�03 2�903 2�99
3�383
HADS depression sum score 5�57 3�238 5�57 3�238 5�42
3�879
HADS: total means score 8�59 5�079 8�59 5�079 8�40
6�078
The STS is based on a 4-point scale ranging from 0 (not at all),
1 (very little), 2 (somewhat) to 3 (very much).
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anxiety
J O U R N A L O F T R A U M A N U R S I N G
WWW.JOURNALOFTRAUMANURSING.COM 17
RESEARCH
ABSTRACT
A retrospective study examined in-hospital antidepressant
medication (ADM) use in adult trauma patients with an

intensive care unit stay of 5 or more days. One fourth of
patients received an ADM, with only 33% of those patients
having a documented history of depression. Of patients
who received their first ADM from a trauma or critical care
physician, only 5% were discharged with a documented
plan for psychiatric follow-up. The study identified a need for
standardized identification and management of depressive
symptoms among trauma patients in the inpatient setting.
Key Words
antidepressant medication , critical care , depression ,
injury ,
psychiatry , trauma
Author Affiliations: UnityPoint Health, Des Moines, Iowa
(Ms Spilman
and Drs Smith and Tonui); and Fort Sanders Regional Medical
Center,
Knoxville, Tennessee (Dr Schirmer).
The abstract was presented at 47th Annual Society for
Epidemiological
Research (SER) Meeting, Seattle, Washington, June 24–27,
2014.
None of the authors have any conflicts of interest to disclose.
Correspondence: Sarah K. Spilman, MA, Trauma Services,
Iowa Methodist
Medical Center, 1200 Pleasant St, Des Moines, IA 50309 (
[email protected]
unitypoint.org ).
Evaluation and Treatment of Depression in Adult
Trauma Patients

Sarah K. Spilman , MA ■ Hayden L. Smith ,
PhD ■ Lori L. Schirmer , PharmD ■ Peter M.
Tonui , MD
approaches require resources and training of hospital
personnel. 5 Regardless of the method, however, assess-
ment of depression is often confounded by the variable
nature of depressive symptoms. Some depressive symp-
toms (eg, fatigue, insomnia, weight loss) can be similar
to symptoms of other medical illnesses or may resemble
temporary conditions, such as delirium or adjustment dis-
order. 6 , 7 In addition, trauma patients in the intensive care
unit (ICU) may often lack the ability to display or report
classic depressive symptoms due to the effects of medica-
tion, pain, or sleep deprivation. 8 , 9
A major issue, though, is that many hospitals do not
routinely screen for depression or assess depressive
symptoms during hospitalization. To our knowledge,
there is no consensus as to when assessments (and re-
assessments) are appropriate. Symptoms of depression
most often are noted through subjective observation by
family or nurses and reported to physicians. Because of
limited resources, mental health experts are often only
involved in the most severe or complicated cases. This is
a fundamental problem in that large numbers of patients
may be overlooked because of the subjective nature and
timing of these observations. Findley and colleagues 4
found that when a psychiatrist was actively involved in
the trauma service, identification and treatment of psy-
chopathology were increased by 78%. While the rate of
mood and anxiety disorders recognized by trauma phy-
sicians remained unchanged, involvement of psychiatry
resulted in a broader range of psychiatric diagnoses and
more than doubled the treatment of substance abuse or
dependence.

Complicating matters further, many trauma patients
present with preexisting depression. Traumatic injury is
related to depression as both a causal factor and a result-
ing condition. 2 , 4 , 10 If patients are unable to self-report
their
health history, the trauma team relies on family report
or pharmacy records. This presents challenges in timely
reinitiation of medications.
STUDY RATIONALE
A review of the medical literature found no relevant
published research on physician and medical team re-
sponse to depressive symptoms during the patient’s ini-
tial hospitalization within settings where mental health
screening is not the standard of care. Current research DOI:
10.1097/JTN.0000000000000102
I
t is well-established in the literature that critically ill
trauma patients can often suffer from depression and
posttraumatic stress disorder in the months and years
following hospitalization. 1-3 Many hospitals may not
have a standardized process for assessing and treat-
ing trauma patients with depressive symptoms. 3-5 During
the acute phase of recovery, the trauma team is primarily
in charge of treating the injuries and preparing to dis-
charge the patient to the next phase of recovery. With-
out a standardized process for recognizing, screening,
and treating the psychological and emotional needs of
the patient, there may be increased risk that depression
will go unrecognized and untreated or misinterpreted and
improperly treated.
Formal assessment of depression can be accom-

plished through clinical interview or screening tools; both
Copyright © 2015 Society of Trauma Nurses. Unauthorized
reproduction of this article is prohibited.
JTN-D-14-00071.indd 17JTN-D-14-00071.indd 17 06/01/15
8:45 PM06/01/15 8:45 PM
18 WWW.JOURNALOFTRAUMANURSING.COM Volume 22 |
Number 1 | January-February 2015
that examines depression screening has been primarily
funded by grant dollars, which provide hospitals with
resources to staff special assessment teams (eg, Dicker
et al 2 ) and may not represent practices at many hospi-
tals. These studies have established the importance of
early detection of depression, although this may be ex-
tremely difficult in hospitals that do not have protocols
for managing depression in the critically ill or special
teams for assessing, treating, and reassessing mental
health symptoms.
The purpose of this study was to examine how a trau-
ma team recognizes and treats depression in the absence
of a screening tool and to document antidepressant medi-
cation (ADM) usage and prescribing patterns. Study data
can assist in the evaluation and understanding of institu-
tion processes and possibly help design protocols to miti-
gate some of the long-term mental health issues that can
result from traumatic injury.
METHODS
Study Design and Patient Sample

A retrospective study was performed at an urban tertiary
hospital in the Midwestern region of the United States.
The hospital’s trauma registry was used to identify adult
patients (aged 18 years or older) who met trauma criteria
during the 5-year study period of 2008 to 2012. A trauma
patient was defined as an individual who sustained a
traumatic injury with an International Classification of
Diseases, 9th Revision, Clinical Modification code rang-
ing from 800 and 959.9, excluding codes for late effects
of injury (905-909.9), superficial injuries (910-924.9), and
foreign bodies (930-939.9). Patients were included in the
study if they were admitted to the hospital and stayed in
the ICU for 5 or more days. The study was approved by
the hospital’s institutional review board.
Study Data
Study variables were grouped into 3 categories: patient
and injury characteristics, depression diagnoses, and
ADM use. Patient characteristics included gender, race,
age, hospital length of stay (LOS), ICU LOS, and mechani-
cal ventilator days. Discharge status was coded as alive or
deceased, while discharge location was coded as home
or institutional setting (including hospice facility, rehabili-
tation facility, skilled nursing facility, federal hospital, or
intermediate care facility).
Injury characteristics included the Injury Severity Score,
which is an anatomical coding system ranging from 0 (no
injury) to 75 (most severe). Finally, mechanism of injury
was recorded on the basis of the External Causes of In-
jury and Poisoning Code (E-Code): Vehicle accident (810-
848), Accidental Fall (880-888), or Other.
Depression diagnoses were assessed retrospectively
through chart review. Patients were classified as having
a documented history of depression if it was specifically

noted in the medical history or if the patient was taking
an ADM at the time of hospital admission. If the patient’s
history was not obtained at admission, the patient was
considered to be on a prior ADM if he or she received
a dose within the first 72 hours of the hospital stay. We
also noted if a patient received a psychiatric consultation
during their stay and if the patient was discharged with
a plan for psychiatric follow-up. The latter was used to
indicate whether or not discharge instructions included
directions for psychiatry follow-up.
The ADM use was ascertained through pharmacy dis-
pensing records. Specifically, it was recorded if a patient
received any of the following drugs: selective seroto-
nin reuptake inhibitors (SSRIs; citalopram, escitalopram,
fluoxetine, fluvoxamine, paroxetine, sertraline); selective
norepinephrine reuptake inhibitors (SNRIs; desvenlafax-
ine, duloxetine, venlafaxine); dopamine reuptake inhibi-
tors (bupropion); and alpha-2 antagonists (mirtazapine).
Some ADMs were excluded from the study, including
tricyclics and monoamine oxidase inhibitors, which can
be used to treat other diagnoses in addition to depres-
sion; vilazodone, which was not approved by the Food &
Drug Administration until 2011; trazodone because it can
be prescribed as a sleep aid; and milnacipran because its
Food & Drug Administration indication is for fibromyalgia.
The first dispensed ADM was used for basic descrip-
tive purposes. For example, if a patient received multiple
ADMs during the stay, only the first ADM was used to
describe patient treatment. If an ADM was not a medica-
tion taken prior to admission, it is hereafter referred to as
a new ADM. Days between hospital admission and first
ADM dose were used to calculate time of initiation. If an
ADM medication was listed in the discharge summary or
the patient received a dose of the medication on the last

day of the stay, then the patient was classified as being
discharged on an ADM.
Statistical Procedures
Descriptive statistics were reported for continuous data as
medians with interquartile ranges; normality was tested
using the Shapiro-Wilk test. Categorical data were re-
ported as counts with percentages. Comparative statistics
were conducted by stratifying patients based on whether
or not they received an ADM during their hospital stay.
These groups were examined using the Fisher exact test
(nominal variables) and the independent samples Mann-
Whitney U Test (2-group medians). All analyses were
2-tailed and based on a 0.05 significance level. Analy-
ses were performed with IBM SPSS Basic Statistics for
Windows, version 19.0 (IBM Corp, 2010; Armonk, NY).
8:45 PM06/01/15 8:45 PM
Trauma Patients Admitted During
Study Period (N=4947)
ICU Length of Stay < 5 Days
(n=4635)
ICU Length of Stay > 5 Days
(n=312)

Received No Antidepressant
Medication (n=230)
Restarted Antidepressant
Medication (n=55)
Received New Antidepressant
Medication (n=27)
Figure 1. Trauma patients admitted to the hospital during the
study period, 2008-2012. ICU indicates intensive care unit.
RESULTS
There were 4947 trauma patients admitted to the hospital
during the 5-year study period, with 312 (6.3%) staying in
the ICU for 5 or more days (see Figure 1 ). Patient char-
acteristics are presented in Table 1 . More than two-thirds
of the patients in the study sample were male, and the
majority of patients were white. Fifteen percent of the
patients died.
There were 82 patients (26.3%) who received an ADM
during the hospital stay (see Table 2 ). Bivariate analy-
ses (not shown) revealed significant differences in age,
with older patients more likely to receive an ADM than
younger patients ( P = .002). Men were less likely to re-
ceive an ADM. There were no significant bivariate differ-
ences between patients based on hospital LOS, ICU LOS,
ventilator days, Injury Severity Score, discharge location,
or injury mechanism.
Patients who received an ADM during the hospital stay
were significantly more likely to have a documented his-
tory of depression upon admission to the hospital. Specif-
ically, 67.1% of patients who received an ADM during the

hospital stay were taking an ADM prior to admission and
19.5% had depression mentioned in their medical history.
Patients who received an ADM were also significantly
more likely to receive a psychiatric consultation during
the hospital stay and were more likely to be discharged
with a plan for psychiatric follow-up.
Of the 82 trauma patients who received an ADM dur-
ing hospitalization, 9 (11.0%) were initiated by a psychia-
trist and 73 (89.0%) were initiated by a critical care or
other nonpsychiatric physician (see Table 3 ). One-third
of patients who received an ADM during their stay were
prescribed a new ADM; 29.6% of these new prescriptions
were initiated by psychiatry and 70.3% were initiated by
a nonpsychiatric physician. There were no significant
differences in ADM choice based on the physician who
initiated the medication.
Patients whose ADM was prescribed by a psychiatrist
received their first dose many days later in the hospital
stay than those patients whose ADM was prescribed by
a critical care or other physician. Patients whose ADM
was prescribed by psychiatry were also more likely to be
discharged with a plan for psychiatric follow-up. Nearly
all patients who received an ADM during hospitalization
were discharged with the medication, regardless of the
provider who initiated it.
DISCUSSION
Study data revealed that 26.3% of trauma patients spend-
ing 5 of more days in the ICU received an ADM during
the hospital stay; 33% of these patients did not have a
documented history of depression or ADM use upon ad-
mission. This is considerably higher than ADM use in the
general population, which is estimated at 10% to 11%. 11 , 12

Female trauma patients were more likely to receive an
ADM than male patients, which is consistent with trends
in the general population. 12
Trauma or critical care physicians were the practition-
ers most likely to continue home ADMs and initiate new
ADMs, compared with psychiatry physicians. However,
TABLE 1 Descriptive Characteristics for
Trauma Patients With Intensive Care
Unit Length of Stay 5 or More Days,
2008-2012 (N = 312) a
All Trauma Patients
(N = 312)
Male 218 (70.1%)
White 271 (86.9%)
Median age, y 55.00 (39.75-69.00)
Median hospital length of stay, d 17 (10-25)
Median intensive care unit length
of stay, d
8.5 (6-14)
Median ventilator days 5 (1.5-10)
Deceased 48 (15.4%)
Discharged to home 68 (25.8%)
Median injury severity score 25 (15.5-33.25)

Injury mechanism
Vehicle accident 174 (55.8%)
Fall 105 (33.7%)
Other 31 (9.9%)
a Data are presented in medians (interquartiles) and counts
(percentages).
8:45 PM06/01/15 8:45 PM
leads to oversights in posttrauma care. Primary care
physicians or other health care providers may not be
alerted to the task of titrating the medication, monitor-
ing adherence to the medication, and/or evaluating the
appropriateness of the ADM in the months and years
after the trauma.
when the ADM was initiated by trauma or critical care
physicians, patients were frequently discharged without
a plan for psychiatric follow-up. This may be a critical
omission, especially for patients started on new ADMs.
Since the trauma or critical care physician manages care
during the acute phase of the injury, this potentially

TABLE 2 Prescription of Antidepressant Medication in
Trauma Patients (N = 312) a
ADM Received During
Stay (n = 82)
ADM Not Received During
Stay (n = 230)
Fisher Exact
Test, P b
Documented history of depression 56 (68.3%) 17 (7.4%) < .001
Taking ADM prior to admission 55 (67.1%) 7 (3.0%) < .001
Depression mentioned in medical history 16 (19.5%) 13 (5.7%)
< .001
Received psychiatric consultation visit
during stay
17 (20.7%) 18 (7.8%) .004
Discharged with plan for psychiatric
follow-up c
8 (12.1%) 6 (3.0%) .009
Abbreviation: ADM, antidepressant medication.
(percentages).
b p values are presented for comparisons between patients
based on whether or not they received an ADM during their

hospital stay.
c Excludes patients who expired.
TABLE 3 Prescribing Patterns for Patients Who Received an
Antidepressant Medication,
2008-2012 (n = 82) a
First Dose Prescribed
by Psychiatry (n = 9)
First ADM Prescribed by
Other Physician (n = 73) P b
Taking ADM prior to admission 1 (11.1%) 54 (74.0%) < .001
Median days between hospital
admission and first dose
12 (7.25-19.75) 2.5 (2-7) .010
New ADM during hospitalization 8 (88.9%) 19 (26.0%) < .001
Escitalopram 5 (62.5%) 6 (31.6%) .206
Citalopram 2 (25.0%) 7 (36.8%) .676
Sertraline 1 (12.5%) 2 (10.5%) 1.00
Paroxetine … 2 (10.5%) …
Mirtazapine … 1 (5.3%) …
Venlafaxine … 1 (5.3%) …
Discharged with plan for

follow-up c
4 (44.4%) 4 (5.5%) 0.005
Discharged with prescription for
ADM c
9 (100.0%) 62 (93.9%) 1.00
Abbreviation: ADM, antidepressant medication.
(percentages).
b p values are presented for comparisons between patients
based on whether the first dose of an ADM was authorized by a
psychiatrist or another
physician.
c Excludes patients who expired.
8:45 PM06/01/15 8:45 PM
The study explores ADM use in the trauma and acute
care setting. While ADM use is not a direct measure of de-
pression, it serves as a proxy for how trauma and critical
care teams recognize and respond to depression in the

absence of screening tools. Many hospitals lack a stand-
ardized process for assessing and treating trauma patients
with depressive symptoms; therefore, we expect that
these results are generalizable to other facilities where
mental health screening is not standard of care. When
a patient is taking an ADM prior to hospitalization, the
trauma team must ensure that the medications are restart-
ed when the patient is hemodynamically stable. But the
situation is less clear in prescribing new ADMs. Initiation
of a new ADM may be done when the physician, nurse,
or family members recognize emerging symptoms of de-
pression or as a preventative approach for symptoms that
are likely to emerge in the future.
We recognize that pharmacological intervention
should not be the first-line treatment to manage depres-
sion. However, since our hospital does not have a stand-
ardized screening tool for depression and does not have
a mental health care professional embedded in the core
trauma team, we believe that these findings are similar to
patterns at other hospitals. It is presumed that patients are
started on ADMs based on feedback from nursing and
family members or recognition of depressive symptoms
during the recovery process, but further analysis is war-
ranted to determine how these decisions are made. Some
patients may be placed on an ADM without warrant, and
conversely, depressed patients may go untreated. Both
scenarios may complicate recovery and lead to adverse
psychological and physical outcomes following the trau-
matic injury.
It deserves mention that it would be ideal for all trau-
ma patients to be screened for depression and mental
health issues. This could potentially improve their recov-
ery process and reduce the likelihood of traumatic injury
in the future, 2 but such an approach may not be practical

in many settings. It is unclear how often patients would
need evaluation to detect change, and how well they can
self-report their symptoms in the first place. Future re-
search efforts should be directed at prospective evaluation
of increased involvement of psychiatrists in the treatment
of trauma patients, as well as increased use of screening
tools for early detection of depressive symptoms. Because
our trauma population is primarily older adults, additional
analyses should focus on the mental health needs of this
aging population and the role that preexisting depression
plays in their injury patterns and recoveries.
Limitations
This study had several limitations. Identification of the
prevalence of depression and ADM use was performed
retrospectively. Reliance on medical documentation to
Acknowledgments
The authors thank Catherine Hackett Renner, James
Rasmussen, and Eric Barlow for assistance in data collec-
tion, analysis, and interpretation.
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Schnyder U , Shalev
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determine history of depression may be inaccurate in in-
stances for patients with an undocumented history of de-
pression or patients who received depression diagnoses
based on inadequate clinical assessments. Other mental
health diagnoses may have been present, such as anxi-
ety or adjustment disorder, but they too may have been
misdiagnosed, underdiagnosed, or misdocumented. Re-
latedly, information was lacking from the medical record
if the patient or a family member was unable to provide
a medical history upon admission to the emergency de-

partment. Given the study design, it was not possible to
access compliance with home medications. In particular,
an ADM in a patient’s medical history may not neces-
sarily depict whether the patient was actively taking the
medication prior to admission. Finally, the main focus of
the study was to examine how physicians assess and treat
depression in trauma patients admitted to the ICU for 5
or more days, which does not allow for generalizations
toward general trauma populations.
CONCLUSIONS
Despite difficulties in the diagnosis of depression in
trauma patients, critical care physicians and psychiatrists
do initiate ADMs in patients who exhibit symptoms of
clinical depression. This study identifies a need to more
accurately identify depressive symptoms among trauma
patients and reveals a need for protocols to assess for
mental health diagnoses and manage ADM use among
trauma patients in the inpatient setting and postdis-
charge.
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Psychopharmacologic treatment
of depression in the medically ill . Psychosomatics . 1998 : 39
:

S2S19 .
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Hopkins RO , Girard TD , Ely
EW . Post-traumatic stress disorder and post-traumatic stress
symptoms following critical illness in medical intensive care
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Care. 2007 ; 11 : R27 .
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. Posttraumatic stress
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October 2011 : 76 .
8:45 PM06/01/15 8:45 PM
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Rates and Predictors of Postpartum Depression by Race
and Ethnicity: Results from the 2004 to 2007 New York City
PRAMS Survey (Pregnancy Risk Assessment Monitoring
System)
Cindy H. Liu • Ed Tronick
Published online: 25 October 2012
� Springer Science+Business Media New York 2012
Abstract The objective of this study was to examine
racial/ethnic disparities in the diagnosis of postpartum
depression (PPD) by: (1) identifying predictors that account
for prevalence rate differences across groups, and (2) com-
paring the strength of predictors across groups. 3,732 White,
African American, Hispanic, and Asian/Pacific Islander
women from the New York City area completed the Preg-
nancy Risk Assessment Monitoring System from 2004 to
2007, a population-based survey that assessed sociodemo-

graphic risk factors, maternal stressors, psycho-education
provided regarding depression, and prenatal and postpartum
depression diagnoses. Sociodemographic and maternal
stressors accounted for increased rates in PPD among Blacks
and Hispanics compared to Whites, whereas Asian/Pacific
Islander women were still 3.2 times more likely to receive a
diagnosis after controlling for these variables. Asian/Pacific
Islanders were more likely to receive a diagnosis after their
providers talked to them about depressed mood, but were less
likely than other groups to have had this conversation. Pre-
natal depression diagnoses increased the likelihood for PPD
diagnoses for women across groups. Gestational diabetes
decreased the likelihood for a PPD diagnosis for African
Americans; a trend was observed in the association between
having given birth to a female infant and increased rates of
PPD diagnosis for Asian/Pacific Islanders and Whites. The
risk factors that account for prevalence rate differences in
postpartum diagnoses depend on the race/ethnic groups

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