for Inpatient Nursing Services
Melissa M. Koerner
HK & ASSOCIATESThis exploratory study examines the conceptual domain of service quality study is to identify service quality dimensions that supplement those that have already been described.
for inpatient nursing services. The findings suggest that the prevailing
What criteria do customers use to evaluate an organization’s
conceptual definition of service quality, as articulated by Parasuraman,
service quality? Parasuraman, Zeithaml, and Berry (1985, 1988)
Zeithaml, and Berry (1985, 1988), does not accurately describe service
qual-have developed a conceptual definition of service quality they
ity for the customers of inpatient nursing services. A definition of inpatient
believe answers this question for all types of services. Their
nursing service quality is provided, and an instrument based on that
defini-definition is well-known, widely accepted, and viewed by
tion, the Inpatient Nursing Service Quality Scale, is presented. The
instru-both scholars and practitioners as an important contribution
ment’s construct validity, nomological validity, and reliability are examined,
to the field of service quality. However, the definition lacks
and the findings are favorable. The results of the study reveal that service
several elements that may be integral to the service quality
quality perceptions for hospital inpatients consist of five dimensions:
compas-construct in many service settings. These elements include
sion, uncertainty reduction, reliability, close relationships, and
individ-the quality of interpersonal relationships between service
pro-ualized care.The dimensions are significant predictors of several outcomes,
viders and those they serve (Berry, 1983; Brown and Swartz,
including global perceptions of service quality, willingness to recommend,
1989; Crosby, Evans, and Cowles, 1990; Gummesson, 1987),
and repurchase intentions. It is argued that industry-specific qualitative
service provider effort (Mohr and Bitner, 1995a, 1995b),
emo-research should be conducted before using generic service quality
measure-tion and affect (Fineman, 1993; Gummesson, 1991;
Hochs-ment tools or instruHochs-ments developed in other industries. J BUSN RES2000.
child, 1983), social support (Adelman, Ahuvia, and Goodwin,
48.267–283. 2000 Elsevier Science Inc. All rights reserved.
1994; Adelman and Ahuvia, 1995), and individualized service (Berry, 1995; Sasser and Fulmer, 1990).
This study examines the conceptual domain of service qual-ity for one type of service: inpatient nursing. Inpatient nursing
T
he purpose of this exploratory study is to broaden andwas chosen, because it was believed that the emotional inten-deepen the conceptual domain of service quality for
sity of the inpatient experience and the strong interpersonal one service industry, inpatient nursing, by focusing
elements of the nurse–patient relationship would highlight ser-on elements of service quality that have received insufficient
vice quality themes that might otherwise go unnoticed (O’Gu-attention in previous research. A conceptual definition of
inpa-inn and Faber, 1989; Schouten, 1991). In addition, satisfaction tient nursing service quality is provided, and an instrument
with inpatient nursing services has been shown to contribute based on that conceptualization is presented. The instrument’s
more significantly than any other service to over-all percep-construct validity, nomological validity and reliability are
ex-tions of a hospital’s service quality (Carman, 1990; Woodside,
amined, and its relationship to SERVQUAL (Parasuraman, Frey, and Daly, 1989).
Zeithaml and Berry, 1985, 1988), an instrument that opera-tionalizes the prevailing conceptual definition of service
qual-The Prevailing Conceptualization
ity and has been used extensively in service quality research,
is also investigated. The assumption underlying this study is
of Service Quality
not that the prevailing definition of service quality is incorrect,
Parasuraman, Zeithaml, and Berry (1985, 1988) (hereafter but rather, that isincomplete. Thus, the general intent of the
referred to as PZB) have undertaken a broad research agenda intended to define and measure the construct of service qual-ity. In their initial research, they developed a series of
proposi-Address correspondence to: Dr. M. M. Koerner, HK & Associates, 2299
Wyo-ming St., Salt Lake City, UT 84109, USA. tions that were then integrated into a model, part of which
Journal of Business Research 48, 267–283 (2000)
2000 Elsevier Science Inc. All rights reserved. ISSN 0148-2963/00/$–see front matter
is called “perceived quality,” which represents the conceptual Similarly,individualized service—identifying and responding domain of service quality. To measure the “perceived quality” to the customer’s true needs in a way that acknowledges his portion of the model, PZB developed the SERVQUAL scale, or her individuality—is viewed by several researchers as critical and they have assessed its reliability and validity repeatedly. to service quality (Berry, 1995; Sasser and Fulmer, 1990, Sur-Initially, 10 categories of service quality were identified. After prenant and Solomon, 1987; Treacy and Wiersema, 1995), but subsequent testing, these categories were reduced to the fol- it is not addressed fully in SERVQUAL. Individualized service
lowing five dimensions. is one aspect of PZB’s empathy dimension, but rather than
focusing on delivering service consistent with an individual’s Reliability: the degree to which a promised service is
per-unique circumstances, the emphasis is on “individual attention” formed dependably and accurately
and “personal attention.” Again, it seems that SERVQUAL mea-Assurance: the extent to which service providers are
knowl-sures a relatively mild form of individualized service. edgeable and courteous, and able to inspire trust and
confi-Adelman, Ahuvia, and Goodwin (1994) suggest thatsocial dence
support, which consists of reducing uncertainty, improving Tangibles: the degree to which physical facilities, equipment,
self-esteem, and enhancing one’s social connection to others, and appearance of personnel are adequate
is an important aspect of service quality that has been over-Responsiveness: the degree to which service providers are
looked. Social support has been found to increase customers’ willing to help customers and provide prompt service
willingness to recommend a service to others and to enhance Empathy: the extent to which customers are given caring,
over-all perceptions of service quality (Adelman and Ahuvia, individualized attention
1995). Research in the nursing field suggests that one form of social support, regular and open information sharing between In their research PZB consistently have found that
custom-nurses and patients, is viewed positively by patients (Fos-ers ratereliabilityas the most important service quality
dimen-binder, 1994; Ludwig-Beymer, Ryan, Johnson, Hennessy, Got-sion, regardless of the service studied. They also have found
tuso, and Epsom, 1993; Morse, Bottorff, Anderson, O’Brien, reliability to be the dimension with the greatest discrepancy
and Solbert, 1992). Social support is not addressed directly between customers’ expectations and the service firm’s
perfor-or indirectly in SERVQUAL. mance. They conclude that “The number one concern of
cus-Service providereffortalso may have an important impact tomers today, regardless of type of service, is reliability”
(Zei-on customers’ evaluati(Zei-ons of service (Mohr and Bitner, 1995a, thaml, Parasuraman, and Berry, 1990, p. 28).
1995b). Service provider competence and courtesy are ad-Despite SERVQUAL’s widespread acceptance and use, a
dressed in SERVQUAL’s assurance dimension, and service pro-number of criticisms have been brought against it. First, some
vider promptness and helpfulness are assessed in the respon-researchers are skeptical that the dimensions apply to all
ser-siveness dimension, but in rating these dimensions, the service vice operations (Babakus and Boller, 1992; Cronin and Taylor,
provider’scapability andeffortare being evaluated simultane-1992; Dabholkar, Thorpe, and Renz, 1996). Otto and Ritchie
ously. Mohr and Bitner (1985) believe that effort may make (1995) found several common elements in consumers’ service
a unique contribution to service quality evaluations; they experiences in five different service sectors, but they also
found that effort had a positive influence on customers’ service observed significant differences in the nature and magnitude
evaluations, even when the service outcome was statistically of the experiences across industries, with particularly striking
controlled. In particular, service failures may be viewed quite differences between high- and low-involvement industries.
differently, depending upon whether customers attribute the Thus, it may not be possible foranyinstrument to measure
problem to factors within the service provider’s control (i.e., service quality accurately in all industries.
effort), or outside their control (Folkes, 1987; Weiner, 1986). A second set of criticisms relate to the restricted view of
Finally, the quality of therelationshipbetween service pro-service reflected in SERVQUAL. For example, Gummesson
viders and their customers is likely to be important in de-(1991) suggests that emotional components of service
qual-termining service quality perceptions (Dwyer, Schurr, and ity—compassion, sense of humor, and love—have received
Oh, 1987), particularly in professional services (Berry, 1995; fairly superficial treatment in service quality research, and that
Gro¨nroos, 1995). Bowen and Jones (1986) suggest that close, emotion should be measured in all service quality instruments,
collaborative customer relationships are especially important particularly those used in the helping professions. There is
when the service is characterized by high performance ambi-increasing evidence that emotional reactions to service
en-guity and high buyer/seller goal congruity—conditions that counters are common and, in fact, represent “the essence of
apply to many health-care service encounters. None of the the service experience” (Otto and Ritchie, 1995, p. 54). In
items on the SERVQUAL scale addresses customer/provider the PZB model,empathyis defined as “caring, individualized
relationships. service given to customers”; however, its operational
defini-In addition to concerns with SERVQUAL’s conceptual tion, as reflected in SERVQUAL, emphasizes the “personal
framework, several researchers have been critical of SERV-attention” rather than the “caring” aspect of the dimension.
QUAL’s measurement properties, including its unstable factor It seems that SERVQUAL addresses relatively superficial
its use of self-reported importance weights, the validity, relia- to improve the service experience for both customers and service providers. This goal is furthered when service quality bility and methodology of the scale, and ambiguity
sur-rounding the “expectations” section of the instrument (Baba- tools take both customer and service provider perspectives into account and are used to pinpoint the similarities and kus and Boller, 1992; Brown, Churchill, and Peter, 1993;
Carman, 1990; Cronin and Taylor, 1992, 1994; Taylor, 1995; differences between customers and employees in their defini-tions of what constitutes high-quality service. Many research-Teas, 1993, 1994). However, despite these criticisms,
SERV-QUAL and its derivatives (e.g., SERVPERF, Taylor, 1995) are ers imply that the service provider’s opinion is irrelevant when developing service measures, some even suggesting that “the still used extensively in service quality research and theory
development (e.g., Crompton and MacKay, 1989; Cronin and only criteria that count in evaluating service quality are defined by customers” (Zeithaml, Parasuraman, and Berry, 1990, Taylor, 1994; Dabholkar, Thorpe, and Rentz, 1996; Dunlap,
Dotson, and Chambers, 1988; Finn and Lamb, 1991; Reiden- p. 16). However, when services are high in credence properties (as many medical services are), customers may not have the bach and Sandifer-Smallwood, 1990; Scardina, 1994; Spreng
and Singh, 1993; Taylor, 1995; Woodside, Frey, and Daly, expertise to judge their quality at all (Darby and Karni, 1973). Health-care providers’ quality judgements arenot irrelevant 1989). Interestingly, even the most ardent of these critics (e.g.,
Cronin and Taylor, 1992, p. 58) have indicated that the model when it comes to the health or survival of the patient. In fact, research has shown that front-line employees have a unique seems to “define the domain of service quality adequately,”
and they have continued to conduct research based on that and valuable “back stage” perspective of service (Mangold
and Babakus, 1991) and that the behaviors, perceptions, and conceptual domain. Although measurement issues are not
the primary focus of this study, the growing concern about attitudes of service providers often are strikingly similar to those of their customers (Parkington and Schneider, 1979; SERVQUAL’s measurement properties provides further
impe-tus to explore alternative ways to define and measure service Schlesinger and Zornitsky, 1991; Schneider and Bowen, 1985; Tornow and Wiley, 1991). Thus, accurate measures of service quality in different industries.
quality have the potential to generate data that improve service to customers, while also increasing the quality of work life
The Need for Accurate
for service providers.Measures of Service Quality
Organizations need accurate measures of service quality to
Method
assure their continued survival and success. Research has
The study was conducted in two general phases. In phase shown repeatedly that service quality influences many
impor-one, qualitative research methods were used to explore the tant organizational outcomes. For example, service quality
conceptual domain of service quality and clarify the service and customer satisfaction both have been found to be related
quality dimensions used by patients to evaluate an inpatient to repurchase intentions (Bearden and Teel, 1983; Bolton and
nursing experience. The qualitative findings of the study have Drew, 1992; Cronin and Taylor, 1992; Oliver and Swan,
been reported in detail previously (Koerner, 1996) and, there-1989; Woodside, Frey, and Daly, 1989), and customers who
fore, are summarized only briefly here. In phase two of the rate service as “excellent” and particularly likely to intend to
study, scale development and testing, quantitative methods repurchase (Gale, 1994). Other behavioral intentions, such
were used to develop an instrument to measure the dimensions as word of mouth referrals and defections, also may be
influ-identified in phase one and to assess the instrument’s validity enced by service quality (Zeithaml, Berry, and Parasuraman,
and reliability. The development and testing of this instru-1996). Service encounter satisfaction has been linked to actual
ment, called the Inpatient Nursing Service Quality (INSQ) purchase behavior (LaBarbera and Mazursky, 1983), and
ser-Scale, is the primary focus of this paper. Following a brief vice quality perceptions are related to willingness to
recom-description of the qualitative research phase, the four stages mend a company’s service to others (Boulding, Kalra, Staelin,
in developing and testing the instrument are described. and Zeithaml, 1993; Parasuraman, Berry, and Zeithaml, 1991;
Both the qualitative and quantitative portions of the study Parasuraman, Zeithaml, and Berry, 1988). Gale (1994) has
were conducted through the hospitals of a major health-care written extensively on the need for organizations to achieve
system located in a large western community. Recent inpa-“market-perceived quality versus competitors.” He argues that
tients of the hospitals and nurses providing inpatient nursing customer attraction and loyalty cannot be attained simply by
services were the research subjects. providing superior service quality; customers must believe an
organization’s offerings are a superior value in relation to
Phase One: Qualitative Research to
competitors’ offering. Any instrument that purports to
mea-Conceptualize Inpatient Nursing Service Quality
sure service quality should be capable of predicting the
organi-zational outcomes described above and should offer explicit The qualitative research that preceded the development of the INSQ Scale consisted of three steps. First, an interdisciplinary guidance on which aspects of service must be addressed to
Table 1. Conceptual Definitions of Inpatient Nursing Service Quality Dimensions
Compassion
Positive experiences involved nurses who were perceived to demonstrate genuine compassion, defined as a sympathetic consciousness of each individual patient’s vulnerability along with a desire to lessen it. Generally, more compassion was related to more positive experiences, and less compassion or indifference was related to more negative experiences.
Preserving dignity
Positive experiences involved nurses who treated patients respectfully and were concerned about helping them avoid embarrassment and preserve their sense of dignity. Generally, more concern for maintaining patient dignity was associated with more positive experiences.
Close relationships
Positive experiences involved nurses who were viewed as having ongoing, interpersonally close relationships with patients, including family-like relationships and friendships characterized by trust, liking, or love. In general, closer relationships occurred in more positive experiences, and more distant, professional, or businesslike relationships occured in more negative experiences.
Individualized care
Positive experiences involved nurses who were percieved to be sensitive to each individual patient’s unique situation and needs, flexible and adaptable in their delivery of care, inclined to offer options to patients, able to anticipate patient needs, and able to make the best use of the patient’s individual capabilities. Generally, more positive experiences were associated with more individualized service, and more negative experiences were associated with more standardized service.
Uncertainty Reduction
Positive experiences involved nurses who helped reduce patients’ uncertainty by teaching and explaining, reporting on the patient’s progress and status, interpreting information from doctors and providing additional support. Generally, more uncertainty reduction was related to more positive experiences and less uncertainty reduction was related to more negative experiences.
Extra effort
Positive experiences involved nurses who were perceived as psychologically engaged in their interactions with patients andtrying hard, which included working with extra intensity, putting in extra time, taking unusual risks, performing extra-role activities, and displaying extra responsiveness. In general, high effort was related to more positive experiences and average or low effort was related to negative experiences.
ment. On the basis of those findings, an interview protocol dures, the nurses and patients were asked to describe in detail one or two of their most positive patient care experiences and was developed and used to conduct depth interviews with
nurses and patients. one or two of their most negative patient care experiences.
The interviews were audiotaped and transcribed and then To recruit informants for the qualitative phase of the study,
an announcement memo was sent from the hospital adminis- were analyzed using Strauss and Corbin’s (1990) constant
comparative method. According to this method’s procedures, trator to the heads of all nursing departments. Managers were
urged to discuss the study with their nurses and request interview transcripts were first examined closely and open
codingwas used to name and categorize phenomena. At the volunteers. Two or three nurses were recruited from each
nursing unit, including intensive care/critical care, intermedi- conclusion of this step, the major themes that emerged in the interviews were identified (e.g., “receiving compassionate ate care, pediatrics, obstetrics–gynecology,
orthopedics/urol-ogy, and medical/surgical. Those who volunteered for the care” and “being embarrassed”), and examples of each theme,
taken from the interviews, were compiled. Next, the tran-study participated in a brief telephone interview with the
researcher to determine their suitability for the study. In this scripts were re-read andaxial codingwas used to examine the context and conditions under which the phenomena occurred interview, each nurse was asked to identify a patient with
whom he or she had a recent positive experience, and this and the causes and consequences of the phenomena. This
step served to clarify how the themes related to each other patient was also contacted for an interview. In all, 15 nurses
and 14 of their patients were interviewed. The nurses ranged and to very positive and very negative service experiences. For example, positive experiences were associated with indi-in age from 25 to 55, and all were Caucasian. Two were males
and 13 were females, and their nursing experience ranged vidualized care and close personal relationships with nurses; whereas, negative experiences were associated with standard-from 2 to 35 years. The patients ranged in age standard-from 16 to
74, and all were Caucasian. Nine were female and 5 were ized care and businesslike or distant relationships with nurses. Finally,selective codingwas used to assemble the findings into male. The patients had been hospitalized for a wide variety
of reasons, including childbirth, knee surgery, cancer, heart an emergent model, which included conceptual definitions for the six service quality dimensions that were identified in attack, meningitis, head trauma, and back injury.
The interviews were conducted within one hospital owned the analysis. The themes that emerged in nurses’ and patients’ interviews were very similar, so they were integrated into one and operated by the health-care system sponsoring the
Table 2. Phase Two: INSQ Scale Development and Testing cluded in the instrument (e.g., “The nurses were consistently Procedures courteous with me” and “The nurses gave me prompt care”).
The decision to use only theperceptionssection of SERVQUAL
Stage 1: Domain specification
(rather than both the expectations and perceptions sections)
Refine conceptual definitions of dimensions
was made because of the growing concern among researchers
Generate scale items
Review and pretest items about SERVQUAL’s use of difference scores and explicit
expec-Stage 2: Data collection tations ratings, and in light of compelling evidence that the Design survey administration procedures
perceptions section alone is a superior predictor of service
Select sample
quality (Taylor, 1995).
Administer survey
Five items were included on the instrument to measure
Stage 3: Development of measurement model
Step 1: dependent variables commonly used in service quality
re-Perform exploratory factor analysis (SERVQUAL, New Items) search: global perception of nursing service quality (two Determine dimensions (INSQ) items), perception of service quality relative to competitors Modify instrument
(one item), intentions to repurchase the service (one item),
Step 2:
and willingness to recommend the service to others (one item).
Perform confirmatory factor analysis
Assess convergent and discriminant validity and reliability The instrument was pretested with five former patients
Refine instrument (nonacademic associates of the researcher who had experi-Stage 4: Assessment of nomological validity
enced a hospitalization) to measure completion times,
deter-Examine relationships among dimensions and service quality
mine areas of confusion, and assess affective responses to the
constructs
survey. Several minor modifications were made based on the pretesting.
STAGE 2: DATA COLLECTION. The sample frame for data col-one of the research are compassion, preserving dignity, close
lection consisted of patients who had been discharged from relationships, individualized care, uncertainty reduction,andextra
the sponsoring organization’s inpatient medical facilities dur-effort. The conceptual definitions for these dimensions are
ing the month before the survey was administered. To select shown in Table 1.
participants from the sample frame the following procedure was used. The sponsoring organization conducted a brief
tele-Phase Two: Scale Development and Testing
phone survey with all former inpatients within 10 days of As Briggs and Cheek (1986, p. 142) and others have argued,
their discharge from its hospitals. Over a 2-week period, at “thorough conceptual analysis should precede data collection.”
the end of the telephone survey, respondents were asked if The purpose of phase one, therefore, was to identify and
they would be willing to complete a written survey focusing conceptualize the new service quality dimensions; phase two
on the nursing care they received during their hospital stay. was intended to create and test a tool to measure those
dimen-Four-hundred-eighteen volunteers were identified through sions. INSQ Scale development and testing occurred in four
this process and were sent the survey the following week. stages, which are summarized in Table 2.
Approximately 4 weeks after volunteers were solicited for the
STAGE 1: DOMAIN SPECIFICATION. The objective of this stage study, 249 questionnaires had been returned. This represents was to specify the definition for each new service quality a response rate of 60% of those who received the question-dimension further. The researcher accomplished this by writ- naire, and approximately 21% of those who were asked during ing survey items to operationalize each dimension, being care- the telephone survey to participate in the mail survey. ful to follow closely the conceptual definitions. During this The demographic characteristics of respondents are as fol-process, care was taken to use simplified language, and when- lows. Women were over-represented in the study: 69% of the
ever possible, words and phrases used by the patients them- respondents were female, and 31% were male. Participants
selves during the interviews were included in the questions were fairly evenly distributed across age categories: 17% were
(e.g., “The nurses genuinely cared about me” and “The nurses between the ages of 18 and 25; 36% were between 26 and
really understood my personal situation”). 45; 20% were between 46 and 64, and 25% were over 64.
A pool of between 5 and 15 survey items was developed Respondents had been hospitalized at six different hospitals
for each dimension, with the goal of having 4 to 8 items per in one state, ranging from small, community-based hospitals dimension in the final version of the instrument (Bagozzi, to large tertiary care hospitals.
1994). The items were reviewed by two individuals with
sur-STAGE 3: DEVELOPMENT OF MEASUREMENT MODEL
vey development experience, four experienced professors of
Exploratory Factor Analysis. The first step in developing marketing and management, and the sponsoring
organiza-the measurement model was to examine several potentially tion’s research department staff. Survey items were modified
meaningful structures in the data collected from former pa-based on their feedback.
tients. Exploratory factor analysis (EFA) is commonly viewed In addition to the items generated for this study, the 22
Table 3. Factor Matrix for SERVQUAL Items, After EFA
Factor
1 2 3 4 5 Item
Factor 1
0.82 0.20 0.26 0.14 0.06 The nurses had my best interests at heart. (empathy) 0.80 0.32 0.24 0.14 0.17 The nurses gave me personal attention. (empathy)
0.76 0.36 0.09 0.21 0.17 When I had a problem, the nurses showed a sincere interest in solving it. (reliability) 0.74 0.16 0.35 0.28 0.03 The nurses understood my spacific needs. (empathy)
0.72 0.37 0.29 0.07 0.25 The nurses were always willing to help me. (responsiveness) 0.71 0.37 0.11 0.21 0.20 The nurses gave me individual attention. (empathy) 0.66 0.25 0.47 0.07 0.10 The behavior of the nurses instilled confidence. (assurance)
0.66 0.46 0.19 0.22 0.08 The nurses were never too busy to respond to my requests. (responsiveness) 0.60 0.32 0.36 0.09 0.29 The nurses appeared neat. (tangibles)
0.59 0.33 0.27 0.08 0.33 The nurses were consistantly courteous with me. (assurance) 0.55 0.23 0.43 0.23 0.18 The nurses had the knowledge to answer my questions. (assurance)
Factor 2
0.31 0.89 0.13 0.14 0.11 When the nurses said they would do something by a certain time, they did it. (reliability) 0.37 0.80 0.26 0.11 0.14 The nurses provided care at the time they said they would. (reliability)
0.43 0.79 0.28 0.09 0.10 The nurses gave me prompt care. (responsiveness)
Factor 3
0.20 0.26 0.80 0.17 0.12 The hospitial had modern-looking equipment. (tangibles) 0.15 0.10 0.78 0.19 0.20 The hospitial’s facilities were visually appealing. (tangibles) 0.51 0.16 0.63 0.18 20.01 I felt safe in the environment at the hospital. (empathy)
0.51 0.21 0.60 0.12 0.13 The nurses performed treatment and care right the first time. (reliability)
Factor 4
0.14 0.09 0.21 0.88 0.15 The written information I received from the nurses about my medical condition was visually appealing. (tangibles)
0.45 0.22 0.28 0.67 20.05 The nurses told me exactly when procedures would be performed. (reliability)
Factor 5
0.29 0.19 0.26 0.15 0.84 The hospital had visiting hours convenient to all its patients and their families. (empathy)
12.44 1.41 0.98 0.91 0.68 Eigenvalue
59 7 5 4 3 Percentage of variance explained
59 66 71 75 78 Cumulative percentage of variance explained
1986); therefore, a series of EFAs were performed. For each one factor contained items from each of the five SERVQUAL dimensions, another factor contained a combination of reliabil-EFA, principal components analysis and orthogonal rotation
were used because the objectives of the analysis were: (1) to ityandresponsivenessitems, and a third factor contained items from thetangiblesdimension. The two remaining factors con-summarize the data into a minimum number of factors; (2)
to identify relatively discrete factors; and (3) to use the factors tained two items and one item, respectively, but were not interpretable. As shown in Table 3, the eigenvalue for the for prediction purposes (Hair, 1995). In addition, for each
EFA, several criteria were used in determining the number of first factor was 12.44, representing 59% of the variance. The second, third, fourth, and fifth factors’ eigenvalues were 1.41, factors to extract (e.g., eigenvalues and scree tests), rather
than using the “eigenvalue-one” procedure, which can produce 0.98, 0.91, and 0.68, respectively. The five factors represented a total of 78% of the variance in the SERVQUAL variables. distorted results if used in an arbitrary manner (Comrey, 1978).
Because the items developed for this study were intended Second, EFA was performed on the service quality items
developed for this study (excluding the SERVQUAL items) in to supplement, rather than replace, the SERVQUAL scale, EFA
was first performed on the SERVQUAL items to determine an iterative fashion to determine their dimensionality. Based
on the qualitative research phase of the study, a “first stage that scale’s dimensionality. In light of the extensive previous
testing of SERVQUAL’s five-factor structure, it was decided conception” of the factor structure (Comrey, 1978) was formu-lated: six factors were expected to be produced. However, to extract five factors. Table 3 shows the SERVQUAL items
and their factor loadings, after EFA. The SERVQUAL items after examining a variety of solutions, the most meaningful
Table 4. Factor Matrix for INSQ Scale, After EFA
Factor
1 2 3 4 5 Item
Compassion
0.76 0.29 0.18 0.12 0.20 The nurses treated me with respect.
0.72 0.28 0.39 0.23 0.13 I had the nurses’ full attention when they were with me. 0.71 0.33 0.15 0.20 0.23 The nurses genuinely cared about me.
0.64 0.18 0.30 0.23 0.23 The nurses helped me keep my sense of dignity during my hospital stay. 0.62 0.29 0.26 0.32 0.24 The nurses were kind to me.
Uncertainty Reduction
0.29 0.79 0.21 0.13 0.14 The nurses gave me and my family members frequent updates on my condition. 0.26 0.77 0.16 0.20 0.16 The nurses helped me understand information given to me by my doctor. 0.45 0.66 0.13 0.16 0.11 The nurses regularly explained what was or would be happening to me during my
hospital stay.
0.21 0.62 0.25 0.23 0.36 The nurses regularly checked with me to see if I had any special concerns or questions. 0.11 0.60 0.12 0.28 0.47 The nurses sometimes knew what I wanted or needed even before I asked for it.
Reliability
0.19 0.16 0.89 0.18 0.14 When the nurses said they would do something by a certain time, they did it. 0.30 0.21 0.84 0.14 0.21 The nurses gave me prompt care.
0.23 0.18 0.83 0.19 0.20 The nurses provided care at the time they said they would. 0.45 0.26 0.50 0.20 0.29 The nurses were never too busy to respond to my requests.
Close Relationships
0.12 0.16 0.18 0.83 0.09 The nurses and I talked about things in our lives other than my medical concerns. 0.20 0.18 0.14 0.78 0.15 The nurses and I sometimes kidded, laughed, or joked with each other.
0.33 0.26 0.14 0.61 0.41 The nurses and I enjoyed each other’s company. 0.36 0.29 0.25 0.60 0.37 The nurses and I liked each other.
Individualized Care
0.41 0.25 0.21 0.28 0.65 The nurses took my unique situation into account in caring for me.
0.51 0.10 0.28 0.05 0.62 The nurses were willing to do things a little differently for me if my situation required it. 0.31 0.37 0.34 0.31 0.57 The nurses really understood my personal situation.
0.35 0.43 0.21 0.25 0.50 The nurses knew my individual preferences and needs.
0.09 0.37 0.32 0.35 0.57 The nurses made sure I understood any instructions I was given.
12.71 1.53 1.27 1.00 0.74 Eigenvalue
55 7 6 4 3 Percentage of variance explained
55 62 67 72 75 Cumulative percentage of variance explained
with hypothesized dimensions:close relationships, uncertainty the INSQ Scale, because this was the only dimension that was clearly interpretable and not already represented by the other reduction, andindividualized care. Items from the dimensions
of compassion and dignity consistently loaded together and INSQ dimensions. All of the items in this factor werereliability/ responsiveness items. The factor matrix for the INSQ Scale, were combined to form a single dimension. Items from the
effortdimension produced dominant loadings on all four di- after the EFA, is shown in Table 4. The eigenvalues for the INSQ Scale factors were 12.71, 1.53, 1.27, 1.00, and 0.74, mensions, so effort was disregarded as a distinct dimension.
The eigenvalues for the four factors were 10.83, 1.26, 1.05, and represent 55, 7, 6, 4, and 3% of the variance, respectively. In all, 75% of the variance in INSQ items is explained by the and 0.75, and explained 57, 7, 6, and 4% of the variance,
respectively. In total, the four factors represented 73% of the five factors.
After completing the EFA for the INSQ Scale, the remaining variance in the new items developed for this scale.
Third, the service quality items developed for this study service quality items produced primary loadings on a single factor and secondary loadings differing by 0.10 or more. Five were combined with SERVQUAL to form the Inpatient
Nurs-ing Service Quality (INSQ) Scale, and EFA was performed on distinct factors emerged:compassion, close relationships, uncer-tainty reduction, individualized care, andreliability.
these items. The original intent was to include all of the
SERVQUAL dimensions in this procedure. However, after Confirmatory Factor Analysis. Once a clear 5-factor structure
had been identified for the INSQ, the solution was subjected inspecting the SERVQUAL factor matrix, it was decided to
Table 5. Goodness-of-Fit Indices for SERVQUAL and INSQ Scale
Model n x2 df GFI AGFI RMR
INSQ Scale
Null model 202 1843.66* 91 0.222 0.103 0.483
4-Factor model 202 114.40* 67 0.917 0.870 0.037
SERVQUAL
Null model 181 3639.10* 210 0.131 0.044 0.550
5-Factor model 184 767.24* 179 0.709 0.625 0.066
GFI5goodness-of-fit index; AGFI5adjusted goodness-of-fit index; RMR5root mean squared residual. *p,0.001.
was used because of its ability to provide detailed diagnostic Convergent Validity. Convergent validity of the INSQ Scale information about a measure’s reliability and validity, includ- was assessed in five ways. First, the goodness-of-fit indices ing the degree of model fit, data regarding convergent and are above or approaching 0.90, which in intself is an indication discriminant validity, and information about method and error of convergent validity (Bagozzi and Yi, 1988). Second, all of
variance (Bagozzi, Yi, and Phillips, 1991). the individual items have a statistically significant factor
load-During the CFA, several items were deleted from the INSQ ing on their assigned dimensions as indicated by the factor Scale as indicated by the modification indices. In the analysis, loadings andt-values listed in Table 6 (Anderson and Gerbing, items were permitted to load only on their assigned factors, 1988). Third, as was seen in Table 4, the secondary loadings with cross-loadings set to zero, and the intercorrelations among on factors to which items are not assigned arenotlarge. Fourth, the factors were freely estimated. The covariance matrix for Table 6 indicates that the average proportion of variance ex-the items was used in ex-the analysis, and parameter estimates plained by each dimension is 0.59 or higher, which exceeds were made under the maximum-likelihood method. For com- Bagozzi and Yi’s (1988) criterion of 0.5 or higher. Therefore,
parison purposes, the analysis also included a null model (no the dimensions specified in the INSQ Scale measurement
constructs were recognized among the observed variables). model seem to account for a substantial proportion of variance
The results of this analysis are shown in Table 5. in the items used to measure them. These findings suggest
The fit tests that are relatively less dependent on sample that convergent validity is established for the INSQ Scale. size suggest a good fit for the 5-factor model (GFI50.917, Discriminant Validity. Discriminant validity was assessed in AGFI 5 0.870), although the chi-square tests for both the
three ways. First, the correlation between each pair of dimen-null and 5-factor models of the combined scale are significant,
sions was examined to determine if it is significantly different suggesting an unsatisfactory fit (x2 5 1843, 91 df for the
than 1.0 (Schmitt and Stults, 1986). Although this test is not null model, and x2 5 114, 67 df for the 5-factor model).
a rigorous one, Table 7 shows that the dimensions are not Nevertheless, the 5-factor model produced a chi-square
statis-highly correlated. A similar procedure for assessing discrimi-tic of less than twice the degrees of freedom, which is a
com-nant validity is to determine if the covariance plus two stan-monly accepted method of assessing fit (Podsakoff and
MacKen-dard errors for each pair of dimensions add to less than 1.0 zie, 1994). In addition, the difference between the chi-square
(Dabholkar, Thorpe, and Rentz, 1996). This procedure pro-statistic in the 5-factor model does show significant
improve-duced values ranging from 0.36 to 0.63 for each pair of ment over the null model (xd21729, 24df; GFID0.70).
dimensions, suggesting that the INSQ dimensions are distinct The complete SERVQUAL scale also was subjected to CFA,
even when measurement error is taken into consideration. with items assigned to their hypothesized dimensions. Again,
A third, more stringent method of assessing discriminant items in the 5-factor SERVQUAL scale were permitted to load
validity has been outlined by Fornell and Larcker (1981). only on their assigned factors, with cross loadings set to zero,
They contend that the average variance accounted for by the and the intercorrelations among the factors were freely
esti-construct among the individual items included in the con-mated. The covariance matrix for the items, again, was used
struct should be greater than the amount of variance the in the analysis, and parameter estimates were made under the
construct shares with any other construct. Satisfying this crite-maximum-likelihood method. For the SERVQUAL scale, the
rion shows that the measures within the dimension have more analysis indicated a poor fit for the null model (x25 3639,
in common with each other than the dimension has with other 210df; GFI50.131, AGFI50.044) as well as for the 5-factor
dimensions. Table 6 shows the average variance extracted for model (x2 5 767, 179 df; GFI 5 0.79, AGFI 5 0.63). For
each dimension, and Table 7 shows the variance shared by the 5-factor model the x2 is more than twice its degrees of
each pair of dimensions. Again, in every case, the square of freedom, again, suggesting a poor fit, although there is
im-the construct intercorrelations is less than im-the average variance provement in the 5-factor model over the null model (x2 5
Table 6. Pattern Coefficients, Reliabilities andt-values for INSQ Scale Items
Individual Average
Pattern Item Variance
Coefficient* Reliability Extracted t-value Item Description
0.60 Compassion
0.81 (0.050) 0.65 12.40 I had the nurses’ full attention when they were with me. 0.81 (0.050) 0.66 12.57 The nurses genuinely cared about me.
0.73 (0.058) 0.54 10.87 The nurses were kind to me.
0.59 Uncertainty Reduction
0.75 (0.055) 0.56 11.23 The nurses helped me understand information given to me by my doctor.
0.73 (0.057) 0.53 10.86 The nurses regularly explained what was or would be happening to me during my hospital stay.
0.81 (0.048) 0.66 12.62 The nurses regularly checked with me to see if I had any special concerns or questions.
0.77 (0.052) 0.59 11.74 The nurse sometimes knew what I wanted or needed even before I asked for it.
0.82 Reliability
0.94 (0.047) 0.88 15.38 The nurses gave me prompt care.
0.87 (0.047) 0.75 13.67 The nurses provided care at the time they said they would.
0.66 Individualized Care
0.80 (0.047) 0.64 12.53 The nurses took my unique situation into account in caring for me.
0.85 (0.041) 0.73 13.74 The nurses really understood my personal situation. 0.78 (0.050) 0.60 11.96 The nurses knew my individual preferences and needs.
0.62 Close Relationships
0.70 (0.065) 0.49 10.03 The nurses and I sometimes kidded, laughed or joked with each other.
0.86 (0.062) 0.74 12.79 The nurses and I enjoyed each other’s company.
Standard errors are listed in parentheses following the factor loadings.
* Pattern coefficients represent the relationship between the observed indicators (items) and the latent constructs (dimensions).
evidence for the discriminant validity of dimension in the pair of dimensions at a time. For each pair of dimensions, this procedure resulted in significantly lower chi-square values INSQ Scale.
As a final assessment of discriminant validity, the phi matrix for the unconstrained models, with differences that exceeded the critical chi-square value atp,0.01 in every case. Again, for each pair of dimensions was fixed at 1.0, and then freed,
and chi-square difference tests were performed to determine this provides substantial evidence for the discriminant validity of the dimensions.
whether the values for the unconstrained models were
signifi-cantly lower than those of the constrained models (Anderson Reliability. Individual item reliabilities are listed in Table 6. All but one are above 0.5, which exceeds Bagozzi and Yi’s and Gerbing, 1988). This procedure was performed for one
Table 7. Means, Standard Deviations, Alphas and Intercorrelations for INSQ Scale Dimensions
r
Dimension M SD a 1 2 3 4 5
1. Compassion 6.12 0.86 0.83 1.0
2. Individualized care 5.39 1.17 0.86 0.69 (0.48) 1.0
3. Reliability 5.79 1.18 0.91 0.63 (0.40) 0.66 (0.44) 1.0
4. Relationships 5.56 1.15 0.74 0.60 (0.36) 0.69 (0.48) 0.48 (0.23) 1.0
5. Uncertainty reduction 5.32 1.10 0.86 0.70 (0.49) 0.75 (0.56) 0.62 (0.38) 0.60 (0.36) 1.0
Nursing service quality 6.12 1.20 0.94 0.75 0.72 0.70 0.63 0.77
Table 8. Summary of Initial Nomological Validity Assessment
Nursing Service Willingness To Intent To Service Quality
Dimension Quality Recommend Repurchase Relative to Competitors
Compassion 0.75* 0.71* 0.63* 0.62*
Individualized care 0.72* 0.62* 0.55* 0.61*
Reliability 0.70* 0.62* 0.55* 0.51*
Close relationships 0.63* 0.52* 0.43* 0.47*
Uncertainty reduction 0.77* 0.63* 0.55* 0.57*
Note:For all dimensions, Pearson correlations are reported. * Significant,0.01.
(1988) criterion. Additionally, INSQscalereliability was as- variance in over-all quality of nursing is explained by the sessed by calculating the internal consistency reliability (Cron- INSQ dimensions. Thet-values for all of the dimensions except bach, 1951) of the items included in each of the dimensions. individualized careare significant (p,0.01).Uncertainty reduc-As shown in Table 7, Cronbach’s alphas ranged from 0.74 to tion, reliability,and compassionare the best predictors in the
0.91, suggesting highly reliable scales. equation, followed byclose relationships. This finding
contra-dicts PZB’s assertion that reliability is the most significant
STAGE 4: ASSESSMENT OF NOMOLOGICAL VALIDITY. To
exam-contributor to over-all service quality perceptions. The finding ine the nomological validity of the INSQ Scale, several analyses
also shows that the INSQ dimensions do contribute to global were conducted to investigate the nature of the instrument
service quality perceptions, which is another indication of the and its relationship to several other service quality constructs.
scale’s nomological validity. Of primary interest were four dependent variables commonly
Second,service quality relative to competitorswas regressed used in service quality research: over-all perceptions of nursing
on the INSQ dimensions. Although the equation is significant quality, perceptions of hospital service quality relative to
com-(43% of the variance in service quality is accounted for by petitors, willingness to recommend the hospital to others, and
the dimensions), onlycompassionand individualized care are intention to repurchase the hospital’s service.
significant predictors.
Third,willingness to recommendwas regressed on the INSQ
Relationships Among INSQ Scale
dimensions. Again, the equation is significant; 55% of the
Dimensions and Dependent Variables
variance in willingness to recommend is accounted for by theAs an initial assessment of the relationships among the INSQ INSQ dimensions. In this equation, however,compassionand dimensions and each of the dependent variables, correlation reliabilityare the only significant predictors.
analysis was performed. Table 8 shows that each of the dimen- Finally, intent to repurchase was regressed on the INSQ sions is positively and significantly related to the dependent dimensions. Again, the equation is significant, 43% of the
variables. This outcome was expected in light of previous variance in intent to repurchase is explained by the INSQ
research suggesting that favorable perceptions of important dimensions. In this equation onlycompassion and reliability aspects of service quality lead to willingness to recommend are significant predictors.
and intent to repurchase the service. The finding provides In summary, the results of the regression analyses provide
evidence of nomological validity of the INSQ Scale. further support for the nomological validity of the INSQ Scale.
Another preliminary assessment involved examining the correlation between the INSQ Scale’s 14 items and
SERV-QUAL’s 21 items, with all items equally weighted and aver-
Discussion
aged. (It should be noted that the INSQ Scale contains two
Inpatient Nursing Service Quality Dimensions
items that are also used in SERVQUAL). The correlation
be-The major finding of the study is that five dimensions—all tween the two scales is high (0.90) and demonstrates
substan-but one different from the dimensions included PZB’s service tial nomological validity of the INSQ.
quality model—account for a substantial proportion of vari-Next, a series of regression analyses were conducted to
ance in patient perceptions of inpatient nursing service quality. determine the extent to which INSQ dimensions predict
val-Of these five dimensions,uncertainty reductionhas the greatest ued organizational outcomes. For each of these analyses, all
influence on nursing service quality perceptions, followed five INSQ dimensions were entered into the equation, using
closely byreliabilityandcompassion, and then, byclose relation-SPSS PC. The detailed results of these analyses are presented
ships. Individualized care is a significant predictor of service in Table 9, and summarized in Table 10.
quality relative to competitors despite the fact that it does First, theover-all nursing qualityscale was regressed on the
Table 9. Regression Coefficients for Analysis of the Effect of INSQ In contrast to prior research, dimensions with affective Scale Dimensions on Dependent Variables characteristics strongly influenced service quality perceptions.
Although PZB’s research consistently has foundreliabilityto
Variable b beta t p
be the most important contributor to service quality and
empa-Dependent variable: Over-all nursing service quality thyto be one of the least important contributors, this research Compassion 0.35 0.27 4.437 0.000 foundcompassion, uncertainty reduction,andclose relationships Indiv. care 5.00 0.05 0.731 0.465
to be critical indicators of perceived nursing service quality
Reliability 0.24 0.24 4.502 0.000
andcompassionandindividualized careto be critical indicators
Relationships 0.13 0.13 2.383 0.018
of perceived service quality relative to competitors. In the
Uncertainty 0.33 0.30 4.765 0.000
(F-ratio for equation is 92.71, df 5, 196,p5 0.000, R square5 analysis,reliabilityinfluenced nursing service quality
percep-0.70, adjusted R square50.70) tions less than uncertainty reduction and about the same as
compassion. In the context of inpatient nursing care, patients
Dependent variable: Service quality relative to competitors
and their families may place increased emphasis on factors
Compassion 0.450 0.270 3.001 0.003
Indiv. care 0.300 0.240 2.401 0.017 other than the technical aspects of service, perhaps because
Reliability 0.120 0.098 1.258 0.210 they can judge those dimensions more capably. Relationships 3.900 0.032 0.383 0.702
Two of the nursing service quality dimensions were found
Uncertainty 0.158 0.116 1.259 0.210
to have an impact on behavioral intentions related to the
(F-ratio for equation is 26.41, df 5, 176,p5 0.000, R square5
hospital, which supports prior research regarding the strong
0.43, adjusted R square50.41)
influence of inpatient nursing on over-all service quality
evalu-Dependent variable: Willingness to recommend ations. The implication of this finding is that hospitals should Compassion 0.66 0.48 6.571 0.000
continue to place a high priority on strategies that improve
Indiv. care 3.60 0.04 0.423 0.673
nursing service quality perceptions, particularly in the service
Reliability 0.21 0.07 3.174 0.002
Relationships 7.40 0.07 1.054 0.293 areas identified in the study as high priorities for patients.
Uncertainty 6.80 0.06 0.778 0.438
(F-ratio for equation is 50.18, df 5, 196,p5 0.000, R square5
Measurement Model for
0.56, adjusted R square50.55)
INSQ Scale versus SERVQUAL Scale
Dependent variable: Intent to repurchase An instrument, the INSQ Scale, was created to investigate the Compassion 0.613 0.410 4.939 0.000
degree to which the identified dimensions represent patient
Indiv. care 4.000 0.035 0.379 0.705
perceptions of nursing service quality. An examination of the
Reliability 0.268 0.238 3.266 0.001
measurement model for the INSQ Scale revealed that it
mea-Relationships 5.700 0.005 0.066 0.948
Uncertainty 8.400 0.067 0.781 0.436 sured service quality more effectively than SERVQUAL in the
(F-ratio for equation is 31.26, df 5, 196,p5 0.000, R square5 population surveyed. Results of the INSQ’s confirmatory factor
0.44, adjusted R square50.43) analysis suggested a good fit of the over-all model and the
model’s internal structure. A variety of procedures was used to examine the instrument’s convergent, discriminant, and perceptions. Individualized care and nursing service quality nomological validity, and the results supported the validity perceptions are, however, quite highly correlated. These find- and reliability of the INSQ Scale.
ings refute prior research asserting that the five PZB service In contrast, testing of the measurement model developed quality dimensions ofreliability, responsiveness, empathy, assur- to assess SERVQUAL’s adequacy revealed a poor fit, based on ance, and tangibles capture the essence of service quality in indices of over-all model fit and tests of the fit of the model’s all service situations. It seems that a different set of dimensions internal structure. Thus, when the measurement models of
more accurately depict service quality perceptions in inpatient the INSQ Scale and SERVQUAL are compared, the INSQ
Scale’s measurement model is superior. nursing services.
Table 10. Summary of Effect of Service Quality Dimensions on Dependant Variables
Nursing Service Service Quality Willingness to Repurchase
Dimension Quality Relative to Competitors Recommend Intentions
Uncertainty reduction ✓
Reliability ✓ ✓ ✓
Compassion ✓ ✓ ✓ ✓
Relationships ✓
Individualized care ✓
did not emerge as a distinct dimension of service quality, it
Nonapplicability of PZB
probably does not influence overall evaluations of service
Dimensions to Inpatient Nursing Services
quality. The qualitative portion of the study identified several service
quality dimensions quite different from those contained in
Compassion
the PZB model. The quantitative analysis further demonstrated
The strength of compassion relative to reliability contradicts that the dimensions in the PZB model do not reflect the
prior research that has established the prominence ofreliability conceptual categories used by patients to evaluate their
hospi-in service quality perceptions. In this study, reliability and tal nursing experience. Indeed, the results of the SERVQUAL
compassioninfluenced nursing service quality perceptions to exploratory factor analysis suggested that patients do not
dis-a simildis-ar degree. As with compassion, reliability influenced tinguish between the skills, knowledge, and courtesy shown
willingness to recommend and repurchase intentions, but to by nurses (assurance) and the care and concern they
demon-a lesser extent thdemon-ancompassion, andreliabilitywas not found strate for patients (empathy), their willingness to help patients
to be a significant predictor of service quality relative to com-and to do the job right (reliability and responsiveness), and
petitors. Thus, the influence ofcompassionseemed to extend their appearance (tangibles); items taken from all five of these
beyond attitudes about the service being evaluated to attitudes SERVQUAL dimensions loaded on a single factor.
SERV-about the hospital’s over-all service, which presumably are QUAL’s exploratory factor analysis results did not support its
based on the entire hospitalization experience. This finding a priori5-factor structure and, in fact, suggested that
SERV-is especially notable in light of research suggesting that hospital QUAL could be reduced to only one significant dimension.
repurchase intentions often are not predicted by patient satis-This finding is consistent with other research conducted with
faction but rather, by such access issues as location and park-SERVQUAL in the health-care field, in which the a priori
ing (Abramowitz, Cote, and Berry, 1987; Doering, 1983), 5-factor structure was not supported (Carman, 1990;
Reiden-although some studies have indicated otherwise (Woodside, bach and Sandifer-Smallwood, 1990).
Frey, and Daly, 1989). Perhaps patients view hospital services In contrast, the exploratory factor analysis of the INSQ Scale,
largely as commodities, andcompassionserves to differentiate
which included one SERVQUAL dimension—reliability—
one hospital from another. suggested that patientsdodistinguish between the extent to
The finding from the factor analysis that patients perceive which nurses show them kindness, sensitivity, and respect
compassionandpreserving dignityto be inseparable was unex-(compassion); pay close attention to their needs for information
pected. It is possible that patients associate withcompassion and provide them with the information they need (uncertainty
those actions that demonstrate compassion, such as showing reduction); follow through on promises and give them prompt
patients respect and helping them avoid embarrassment. care (reliability); take their individual situations into account
It should be noted thatcompassion,as defined in this study, and treat them differently than others if necessary (
individual-is quite different from the empathy dimension in the PZB ized care); and form close interpersonal relationships with
model. Despite theconceptualdefinition of empathy, items on them (close relationships).
SERVQUAL focus primarily on personal attention. In contrast, It is possible that the PZB dimensions are relatively accurate
both the conceptual and operational definitions ofcompassion, descriptors of services characterized by superficial, short-term
as defined in the current study, directly address kindness, interactions with customers, such as banking and retail
opera-genuine caring, and respect shown to customers by service tors—industries where the model originated—but they may
providers. Thus, compassion can be viewed as a dimension not apply as well to services in the helping professions. In
that is deeper and less superficial thanempathy, and one that such high-contact, helping-oriented services as nursing, the
places considerably more emphasis on service provider caring consequences of poor service are more serious, customers’
and concern. relationships with service providers are closer, and service
From the organization’s perspective,compassion’sdominant workers have greater identification with their roles (Ashforth
position in nursing service quality is positive, because compas-and Humphrey, 1993). These differences may cause customers
sion is “free.” Theoretically, the level of compassion shown to to think about and evaluate the services differently.
patients by a hospital’s nurses could increase dramatically without incurring any additional expense. However, hospitals
Effort
may not be capable of manipulating employees’ emotionalEffortwas a dominant theme in the qualitative portion of the responses. There is growing sentiment among organizational
study. However, in testing the INSQ Scale, items from the researchers that employers cannot regulate the emotions of
effortdimension loaded on all of the other dimensions—often their service workers, and that the harder organizations try quite highly—suggesting thateffortis associated with all of the to instill or promote such emotions as compassion, the more other dimensions. It is possible that extra effort can enhance a counterproductive those efforts will be (Ashforth and
Hum-customer’s assessment of any dimension, based on the type phrey, 1993; Van Maanen and Kunda, 1989). Thus, nurses
be given to patients. This finding underscores the importance ences were characterized by casual, enjoyable, open interac-tions, mutual liking, in-depth knowledge of the patient, and of recruiting and selecting nurses who not only are clinically
competent, but also identify strongly with the compassionate a willingness to exceed job boundaries on behalf of the patient. In the study, close relationships seemed to be intrinsically aspects of the nursing role. The finding also emphasizes the
importance of ensuring that nurses have adequate support satisfying to both the nurse and the patient, but they also
served three purposes: to generate information useful in help-networks so they can avoid emotional exhaustion and be
available emotionally to give compassionate care to patients ing nurses accomplish their clinical tasks; to motivate nurses to provide outstanding care to patients, and to enhance feel-(Kahn, 1993).
ings of well-being for both nurses and patients. Thus, in addition to being valuable in themselves, nurse–patient
rela-Individualized Care
tionships may enhance other dimensions of service quality. The results supportedindividualized careas a distinct
dimen-Although close relationships were significantly related to sion of nursing service quality perceptions. Interestingly,
indi-perceptions of nursing service quality, they were not found vidualized carewas highly correlated with nursing service
qual-to predict repurchase intentions or willingness qual-to recommend. ity perceptions, but multiple regression analysis revealed that
This may have occurred, because in most hospitals nurse– it contributed very little unique variance to the regression
patient relationships are both person- and situation-specific; equation; it was not a significant predictor for nursing service
there is no reason to believe that one would receive care from quality perceptions.
the same nurse if one were to be rehospitalized, nor would However, despite its failure to contribute significantly to
one expect a friend to whom the hospital was recommended nursing service quality perceptions, individualized care was
to be assigned the same nurse. Thus, it seems logical that the one of only two dimensions that predicted perceived service
advantage of close relationships in inpatient nursing would quality relative to competitors. If Gale’s (1994) contention is
be isolated to the immediate service situation. Nevertheless, correct (i.e., that market-perceived quality versus competitors
because close nurse–patient relationships influence service is more critical to a firm’s success than service quality
percep-quality perceptions strongly, hospitals would be well advised tions), thenindividualized carehas particular relevance to
hos-to find ways hos-to establish relationships between nurses and pital marketing efforts. Abramowitz, Cote, and Berry (1987)
patients. Primary nursing, for example, facilitates close nurse– infer that hospital services are viewed by consumers as
com-patient relationships in a systematic and intensive way, al-modities; therefore, hospitals must find ways to differentiate
though relationships also can be facilitated at a less intensive themselves from competing hospitals. The current study’s
re-level through staff scheduling and patient assignments. The sults suggest that marketing and delivering individualized care
results of this study suggest that primary nursing and other may be one way to accomplish this goal.
staffing and management strategies that facilitate nurse– Kopytoff’s (1986) discussion of singularization may help
patient relationships will influence service quality perceptions to explain why patients appreciate individualized care and
favorably. why they view standardized care so negatively. First, Kopytoff
notes that some objects and services, such as medicine in
Uncertainty Reduction
some societies, are inherently singular (i.e., not exchangeable),
because they are only effective when used by the intended The qualitative part of the study suggested that patients enter person. To a certain degree, nursing care may be viewed in the hospital with a wide variety of questions and concerns this manner. Second, life-and-death medical situations have and that they appreciate receiving information regularly to sacred characteristics, and Kopytoff notes that singularization increase their sense of control. The quantitative part of the is one important method of reinforcing the sacredness of an study supported this finding by showing thatuncertainty reduc-object or event. Finally, Kopytoff argues that human attributes tionis the strongest predictor of nursing service quality percep-(and genuine compassion and emotional support may be ex- tions. In this study,uncertainty reductionwas more than simple amples) simply cannot be exchanged for money; they must information sharing; it involved being sensitive to the amount be singularized. Thus, circumstances associated with inpatient and type of information needed coupled with the skill and nursing service may make individualized care more important willingness to provide it. Thus, it seems that this aspect of
than it would be in other service settings. social support has an important impact on patients’ service
quality perceptions.
Close Relationships
Uncertainty reduction seems to consist of two facets. One facet involves attentiveness—checking with patients, asking The analysis revealed that close relationships are significantlythem if they have questions or needs, and updating them related to perceptions of nursing service quality. In the
qualita-regularly on what is or will be happening to them. The second tive portion of the study, patients’ negative experiences often
facet involves providing information, for example, by ex-were characterized by businesslike or professional
relation-plaining procedures and interpreting information patients re-ships; detached politeness resulted inunfavorableperceptions
