Effect of an intervention on the congruence of nurses’ and
patients’ perceptions of patient-centred care: a pre-test post-test
study
Abstract
Aims and objectives: To evaluate measurement invariance of the Individualized Care Scale
across patients and nurses, and assess the degree of congruence in nurses’ and patients’ perceptions on patient-centredness and the impact of an intervention thereon.
Methods: A pre-post intervention study design with an experts by experience intervention
was conducted in 2016-2017. Nurses (n=138) and patients (n=199) of two hospital departments in Belgium were surveyed. Patient-centredness was measured using the Individualized Care Scale (ICS-Nurse and ICS-Patient). Measurement invariance was evaluated by conducting multiple group confirmatory factor analysis. Unpaired t-tests and difference in difference analysis were used to evaluate the degree of congruence in nurses’ and patients’ perceptions on patient-centredness and assess pre-post changes in nurses’ and patients’ scores, respectively. SQUIRE guidelines were followed to report the study.
Results: There was no evidence of measurement non-invariance. Nurses perceived the
individuality of care more positively than patients both before and after the implementation of the intervention. Pre-post changes in nurses’ and patients’ scores were not statistically significant.
Conclusion: There is a significant gap between the perceptions of nurses and patients
individualized than patients do. To orient nurses’ perspectives more towards their patients’ perspective, multicomponent interventions are needed. Researchers and hospital managers may use the ICS to evaluate interventions that have the ability to close the gap in nurses’ and patients’ perceptions of patient-centredness. Embedding experts by experience in the professionals’ team has the potential to foster patient-centredness but needs to focus on patients and nurses equally.
Key Words
Introduction
During the last two decades, patient-centredness has gained importance. It is seen as a biopsychosocial approach and attitude that aims to deliver care that is respectful, individualized and empowering. Patient-centredness assumes the individual participation of a patient and is built on a relationship of mutual trust, sensitivity, empathy and shared knowledge 1. The concept dates from 1955, when Michael Balint introduced patient-centred medicine as “another way of medical thinking” 2. It gained renewed attention since 2001 when it was promoted as one of the six characteristics of improvement goals to enhance quality of care 3. However, its translation in hospital practices is insufficient 4. One of the key facilitators in implementing patient-centred interventions is measurement and feedback 5,6.
We identify two gaps in the existing literature when it is of interest to compare perspectives on patient-centredness across nurses and patients. First, no attention has been given to evaluating measurement invariance of the concept of patient-centredness across nurses and patients. Measurement invariance is a prerequisite to make fair comparisons across groups. It is defined as “the extent to which respondents across groups perceive and interpret the content of survey instrument items in the same way” 13. To compare nurses’ and patients’ opinions on patient-centredness, it is crucial that respondents of each group hold similar conceptualizations of the constructs which are surveyed. Several statistical techniques have recently become widely available to examine this important issue.
Second, the current studies were cross-sectional and observational. However, one would expect that a patient-centered intervention would reduce the gap between nurses and patients after a certain period. In this respect, Berg et al. (2012) already called for interventions that could close the gap for example by introducing the patient perspective in nursing care.
Methods
Aims
To overcome these two gaps, the aim of this interventional study is twofold. Our first objective is to evaluate measurement invariance of the Individualized Care Scale across patients and nurses. Second, if measurement invariance can be established, we evaluate the degree of congruence in nurses’ and patients’ perceptions on patient-centredness and assess the impact of an intervention on this congruence.
A pre-test post-test study design was used to evaluate the effect of the piloted intervention in two hospital departments. The SQUIRE guidelines are followed for reporting the intervention 14 (See Supplementary File 1).This study is part of a broader research program that is guided
evaluation of hospital services, was piloted. During nine months, these trained patients were part of the professionals’ team. They had two main tasks: supporting their peers mentally, socially and practically and evaluating the care delivered by the health care professionals. They supported their peers through individual and group conversations. Experts by experience were also involved in therapy sessions, for example to demonstrate actions (e.g. walking stairs while having a leg amputation, drinking when arms are paralyzed). Experts by experience supported the health care professionals by collecting complaints and dissatisfactions and by suggesting actions to improve care and the organization of care. As such, experts by experience complemented the professionals’ insights. The intervention is described in detail by using the TIDieR template 17 (See Appendix A).
To evaluate this intervention, we used qualitative (21 interviews with patients and 9 focus groups with experts by experience and health care professionals) and quantitative methods. The results of the qualitative study were positive. Patients, nurses and other health care staff reported an enhancement of patient-centred aspects.
Figure 1: Study design Participants
inclusion criteria were: admitted or present in the aforementioned hospital services during the period of data collection, of adult age (≥ 18 years), able to read and understand Dutch. Patients with limited cognitive skills or with a disorder in the production and comprehension of language were excluded. With respects to nurses, inclusion criteria were: present in the aforementioned hospital services during the period of data collection, able to read and understand Dutch, and closely involved in direct patient care in the targeted hospital services. Berg et al. (2012) previously reported an average score of 3.90 (SD 0.82) for patients’ assessment on individualized care (ICS-A). With a probability of a Type I error of 0.05, a probability of a Type II error of 0.10 (i.e. power is 90%), an effect size of 0.4 and equal proportions of subjects in the pre-test and post-test, 89 patients are required at the pre-test and post-test, for a total of 178 patients. Given smaller standard deviations for the patient ICS-B (0.61), nurse ICS-A (0.45) and nurse ICS-B (0.47) reported by Berg et al. (2012), less patients and nurses would be required to illustrate a similar effect under the same assumptions.
Data collection
Instrument
bipartite questionnaires, each consisting of 34 items, grouped in two subscales which each consists of 17 items. Subscale A (ICS-A) aims to explore views on how individuality is supported and subscale B (ICS-B) aims to explore views on how individuality in care is provided. Both subscales each cover clinical situation (7 items), personal life situation (4 items), decisional control over care (6 items). The items are scored on a 5-point Likert-type scale, ranging from 1 = strongly disagree to 5 = strongly agree.
As the co-design trajectory is part of the intervention itself, surveys were collected before the start of the co-design trajectory (January 2016) and immediately after (June 2017) the intervention.
Ethical considerations
The study protocol (B322201627024) was approved by an Ethical Committee. All respondents provided informed consent.
Data analysis
First, we described the sample of nurses and patients before and after the introduction of the intervention. Chi squared tests are used to compare sample characteristics.
the other hand. We then assessed measurement invariance of the ICS dimensionality across nurses and patients by conducting multiple group confirmatory factor analysis (MGCFA). This technique allows an assessment of various types of invariance. Configural invariance pertains to showing the same pattern of association between items and factors, and the same number of factors. In this model, factor loadings and thresholds are free across groups. Metric invariance on the other hand includes equality of factor loadings. And scalar invariance also includes equality of factor thresholds. Evidence of scalar invariance is a requirement for drawing meaningful comparisons across groups 18. For multiple group confirmatory factor‐ analysis, we used weighted least squares estimation using delta parameterization. Model fit evaluation was based on Hu and Bentler’s (1999) cut-off criteria and Chen’s (2007) allowed changes in these fit indices when studying invariance. The Comparative Fit Index (CFI) 19 and Tucker-Lewis Index 20 range between 0 and 1, are reasonable if >0.90 and very good if >0.95. A change of ≥−0.01 indicates non-invariance. The Root Mean Square Error of Approximation (RMSEA) 21 also ranges between 0 and 1, is reasonable if <0.08 and very good if <0.05. A change of ≥0.015 indicates non-invariance.
fixed effects, we evaluated whether any pre-post changes in nurses’ and patients’ ICS scores were statistically significantly different. Last we also used paired t-tests to evaluate the difference in ICS-A and ICS-B within each time point and within each group. Some ICS (sub)scales showed negatively skewed distributions, suggesting deviation from normality. Non-parametric analysis using the Wilcoxon rank sum test did not alter conclusions about significant differences across groups, scales or over time.
Mplus version 7.1 was used to estimate factor analytic models 22. The descriptive analysis and chi-squared tests for this paper were generated using SAS software, Version 9.4 of the SAS System for Windows. Copyright ©2016 SAS Institute Inc. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc., Cary, NC, USA.
Validity, reliability and rigour
The ICS is characterized by factorial, criterion, construct and content validity. The internal consistency of the ICS-Nurse is proven to be acceptable and that of the ICS-Patient is high (Suhonen et al., 2013, 2010, 2005). Overall, the ICS is the most often reported and
extensively tested instrument which is used in several countries and thus translated in several languages (Acaroglu, Suhonen, Sendir, & Kaya, 2011; Köberich, Suhonen, Feuchtinger, & Farin, 2015; Suhonen et al., 2012).
Results
Sample characteristics
The total sample (pre-test and post-test together) consisted of 337 respondents of which 138 nurses and 199 patients. In the rehabilitation centre the sample consisted of 38 (response rate = 65.5%) nurses and 28 patients (response rate = 96.5%), in the renal centre 100 nurses (response rate = 70%) and 171 patients (response rate = 78.4%) were involved.
Table 1 displays the sample characteristics for nurses and patients. Most of the nurses were female and held a bachelor degree. There was no significant difference between the nurses in the pre-test compared to the post-test. Most of the patients were male, aged above 70 years and held a diploma from high school. With respect to gender and age there was a significant difference in the patient group before and after the implementation of the intervention.
Evaluating measurement variance
Evaluating support and provision of individuality
Following Berg et al. a mean score >4.5 indicates a high level of individualized care. At the subscale level, no mean scores exceeded the 4.5 threshold (Table 3).
Before the intervention, nurses perceived the support and provision of individual care more positively than patients. This significant gap remained after the implementation of the intervention, except ICS-B personal life situation. This is despite an increase in all mean scores over time, which was not once statistically significant when it came to nurses, but was statistically significant for the overall ICS-B score and in three out of six subscale scores (ICS-A clinical situation, ICS-B personal life situation, and ICS-B decisional control) when it came to patients. The evaluation of the consistency of effects across participating wards did not alter any conclusions. Findings from the difference in difference analysis showed that pre-post changes in nurses’ and patients’ ICS scores were not statistically significantly different. Last, both before (t-value=-5.08, value<0.001) and after (t-value=-2.84, P-value=0.006) the intervention nurses’ scores on the ICS-A were significantly higher than their scores on the ICS-B. Patients’ scores on ICS-A and ICS-B did not differ significantly, neither before (t-value=1.55, P-value=0.12) nor after (t-value=1.97, P-value=0.05) the intervention.
Discussion
The data of this interventional study could add to three insights regarding the measurement of individuality in care.
Patient, conceptualized the construct of individualized care similarly. Therefore, the ICS-Nurse and ICS-Patient allow comparison of scores across nurses and patients.
Second, similar to the findings of Berg et al. (2012) and Suhonen et al. (2012), the results of this study show incongruence between the perceptions of patients and nurses regarding individuality of the delivered care. More specifically, nurses scored the degree of individuality significantly higher than patients. This might indicate that nurses overestimate their patient-centred attitude. Furthermore, patients’ scores on ICS-A and ICS-B did not differ significantly. This is in contrast to the scores of nurses which are statistically significantly higher on ICS-A than on ICS-B. The latter might indicate that nurses felt that there is organizational and managerial support but that they fail to effectively bring their patient-centred attitude into action. In literature, nurses and patients score the ICS-B higher than ICS-A, except in Finland where the results are similar to our results 10,11.
Unfortunately, taken together, contrary to what we had hoped for, our findings suggested a limited impact of our intervention in patients only. Because the magnitude of this effect in patients was small, our difference in difference analysis showed that the intervention did not reduce the gap in nurses’ and patients’ opinions of patient-centredness. Either the moderate effect was due to the relatively short intervention period (i.e. nine months) or the intervention was not powerful enough to attain the desired effect
However, the lack of strong statistical relevance does not mean that the intervention also lacks clinical relevance. Next to an improvement in patients’ scores, the analysis shows an increase in the mean scores of nurses. This improvement was also reflected in the qualitative data analysis. Patients, and nurses as well, indicated positive effects of the intervention on the patient-centredness of care. The work of the experts by experience gave them insights into the psychosocial aspects of patients’ disease and enabled them to deliver care that takes into account several issues that come along with a long-term disease or disability. Nurses also reported higher job satisfaction because they became aware that, with minimal efforts, they could do more for their patients than they currently did.
Limitations
evaluation to assess the intervention dose, which was different in the two hospital departments (e.g. at the rehabilitation centre, six experts by experience were employed in duo, three times a week while at the renal centre four experts by experience were employed, each one time a week). In this study, we merged the data of two hospital departments of which the intervention dose was different. By doing this, the overall effect is likely to be reduced.
Conclusion
The ICS is able to compare the perceptions of patient-centredness between nurses and patients. As such, researchers and hospitals managers may use the ICS to evaluate interventions that aim to close the gap in nurses’ and patients’ perceptions. The results of our study indicate that embedding experts by experience in the professionals’ team has the potential to foster patient-centredness but needs to focus on patients and nurses equally. Therefore there is a need for multicomponent interventions that convey to both nurses and patients. The preferable design of these interventions is al long-term multicentre pre-test and post-test intervention study with a control group.
Acknowledgements
We wish to acknowledge Dr Deborah Seys for the preliminary data analysis and Prof. Dr Ann Van Hecke and colleagues for translating the Individualized Care Scale.
Conflict of Interest Statement
References
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Tables
Table 1. Sample characteristics
Nurses (n=138) Patients (n=199) Pre (n=64) % (n) Post (n=74) % (n) χ² test Pre (n=106) % (n) Post (n=93) % (n) χ² test Gender Male 15.0 (9) 13.9 (9) χ²=0.00 P=0.85 68 (68.7) 45 (52.9) χ²=4.8 P=0.03 Female 85.0 (51) 86.1 (56) 31 (31.3) 40 (47.1)
Missing data value 4 9 7 8
Age
P=0.68 P=0.02 30-39 27.0 (17) 26.8 (19) 1 (1) 3.4 (3) 40-49 12.7 (8) 16.8 (12) 4.9 (5) 5.6 (5) 50-59 36.5 (23) 29.6 (21) 17.5 (18) 4.5 (4) 60-69 1.6 (1) 0.0 (0) 21.4 (22) 24.7 (22) ≥70 0.0 (0) 0.0 (0) 51.5 (53) 61.8 (55)
Missing data value 1 3 3 4
Education Primary school -- --χ²=2.1 P=0.15 25.2 (26) 28.2 (24) χ²=4.6 P=0.33 Secondary school (lower) -- -- 28.2 (29) 32.9 (28)
Secondary school (upper) -- -- 21.4 (22) 23.5 (20) Professional bachelor 90.5 (57) 81.7 (58) 13.6 (14) 11.8 (10) Academic bachelor/master 9.5 (6) 18.3 (13) 11.6 (12) 3.6 (3)
Missing data value 1 3 3 8
Table 2. Single-group and multiple group confirmatory factor analysis evaluating ICS dimensionality across nurses and patients
Comparative Fit Index
(CFI) Tucker-Lewis Index (TLI)
Root Mean Square Error Of Approximation (RMSEA)
Single group confirmatory factor analysis
for nurses (n=138) 0.972 0.969 0.068
Single group confirmatory factor analysis
for patients (n=199) 0.972 0.969 0.062
Multiple group confirmatory factor analysis for nurses and patients: configural measurement invariance model
0.972 0.969 0.064
Multiple group confirmatory factor analysis for nurses and patients: scalar
measurement invariance model 0.969 0.969 0.065
Table 3. Nurses’ and patients assessments’ on individualised care at scale and subscale levels before and after the intervention
Pre intervention Post-intervention Pre versus post intervention Nurses Patients t-test
nurses versus patients
Nurses Patients t-test nurses versus patients
t-test
nurses t-test patients
Difference in difference analysis Mean (SD) Mean (SD) Mean (SD) Mean (SD)
ICS-A 4.28 (0.54) 3.51 (0.94) t-value=5.9P<0.001* 4.36 (0.55) 3.76 (0.94) t-value=4.9P<0.001* t-value=0.9P=0.39 t-value=1.82P=0.07 Est=0.17P=0.34 Clinical situation 4.36 (0.60) 3.59 (0.94) t-value=5.8P<0.001* 4.46 (0.50) 3.89 (0.80) t-value=5.3P<0.001* t-value=1.12P=0.27 t-value=2.33P=0.02* Est=0.21P=0.24 Personal life situation 4.02 (0.70) 3.45 (1.04) t-value=3.5P<0.001* 4.05 (0.75) 3.70 (1.07) t-value=2.3P=0.021 t-value=0.26P=0.80 t-value=1.31P=0.19 Est=0.23P=0.34 Decisional control 4.28 (0.55) 3.43 (0.96) t-value=6.0P<0.001* 4.40 (0.55) 3.71 (1.05) t-value=5.1P<0.001* t-value=1.32P=0.19 t-value=1.62P=0.11 Est=0.07P=0.71
ICS-B 4.11 (0.53) 3.58 (0.94) t-value=4.2P<0.001* 4.24 (0.46) 3.93 (0.76) t-value=3.1P=0.002* t-value:1.5P=0.13 t-value=2.80P=0.006* Est=0.20P=0.25 Clinical situation 4.27 (0.60) 3.62 (1.03) t-value=4.6P<0.001* 4.42 (0.50) 3.88 (0.82) t-value=4.9P<0.001* t-value=1.54P=0.13 t-value=1.86P=0.07 Est=0.11P=0.58 Personal life situation 3.77 (0.74) 3.44 (1.05) t-value=2.2P=0.033* 3.88 (0.67) 3.76 (0.89) t-value=0.98P=0.33 t-value=1.0P=0.35 t-value=2.20P=0.029* Est=0.19P=0.36 Decisional control 4.16 (0.54) 3.68 (0.95) t-value=3.64P<0.001* 4.28 (0.53) 4.02 (0.90) t-value=2.19P=0.030* t-value=1.34P=0.18 t-value=2.43P=0.016* Est=0.22P=0.24 *statistically significant
