Background
Chronic diseases (CDs) are a growing health problem worldwide, causing 89 % of all mortality in the Dutch population in 2014 [
1]. As CDs, such as cardiovascular diseases, cancers, chronic respiratory diseases, arthritis and diabetes, are generally of long duration and low progression, patients need ongoing management over a period of months, years or decades. Besides this, patients with CD generally need more healthcare than patients with non-CD [
2]. In daily physiotherapy practice, treatment sessions are often prolonged compared to patients with non-CD [
3]. Considerable research has gone into how to treat patients with CD in daily physiotherapy practice. This information forms the basis of Dutch physiotherapy evidence-based statements and guidelines regarding these diseases [
4‐
9]. In these guidelines the core components of treatment are similar: (1) patients learn to manage and live with their disease in daily life and (2) they learn how to become and stay physically fit [
10]. Both cases require a change in the patients’ behaviour and a need to adopt the skill of self-management.
Research by Lewis and colleagues [
11] shows that physiotherapists can influence treatment outcome. In their study comparing two randomized clinical trials (RCTs) therapists accounted for around 3–7 % of the overall effect in patient disability outcome scores. The use of strategies to direct behavioural change and self-management within treatment requires physiotherapist to adopt a coaching role [
4‐
10]. In addition, the prolonged therapy sessions lead to more contact with the treating party. Lewis et al. [
11] hypothesized that an approach focusing on coaching may contribute to the effect of therapists on treatment outcomes. Based on these considerations, we assume that therapist-patient interaction is more intense in the treatment of patients with CD and therefore treatment outcome might be subject to greater influence by therapist related factors: the so-called ‘therapist effect’.
Identifying therapist related factors that affect treatment outcome could provide tools to improve treatment outcome in patients with CD. Some research has gone into extrinsic therapist related factors such as physiotherapists’ experience and education, [
11‐
18] showing no consistent influence on patient outcome. Only organizational related stress was associated with better physical patient outcomes. Unfortunately, the study’s conclusions are limited due to it being a cross-sectional analysis - time and influences at different hierarchical level were not taken into account [
19]. Although proposed, [
12,
15,
18] rather less attention has been paid to exploring intrinsic therapist factors such as personal beliefs, calmness or empathy.
The influence of intrinsic healthcare professionals’ characteristics on treatment outcome has been studied in related professional fields. Boerebach et al. [
20] conducted a systematic review in which they examined the influence of clinicians’ personality and interpersonal behaviour on the quality of patient care. However, based on the low number of studies found, they could give no conclusion regarding the effect of personality on patient care. In their study, four articles were found showing a small effect of ‘Openness to experience’ [
21], no effect of ‘Agreeableness’ , Openness to experiences’ [
22,
23] or ‘Extraversion’ [
24], and inconsistent findings for ‘Neuroticism’ and ‘Conscientiousness’ [
22‐
24]. In a sample of patients with anxiety and mood disorders, Heinonen et al. [
25] showed that active, engaging and extrovert psychotherapists achieved a faster symptom reduction in short-term treatment while more cautious, non-intrusive therapists realized greater benefits during long-term treatment. Also, treatments by psychotherapists who had lower confidence and did not enjoy their work predicted poorer outcomes on the short- and long-term [
25]. In four studies, [
26‐
29] more empathic psychotherapists and general practitioners affected treatment outcome in a positive manner.
A systematic approach to examining intrinsic physiotherapist factors is to look at personality traits, as contained in the Big Five personality theory [
30,
31]. The Big Five is a widely used and accepted approach to examining the structure of inter-individual differences, using five personality dimensions. Based on prior theoretical research such as psycholexical theory [
32], these personality dimensions have been shown to closely reflect actual behaviour traits [
33]. Greater understanding of the influence of personality traits may contribute to general understanding of the physiotherapist effect and might be useful for general training of therapists. To our knowledge, no study has investigated the influence of physiotherapists’ personality traits on treatment outcome in patients with CD. Therefore, the objective of this study is to explore the influence of physiotherapists’ personality traits, using the Big Five, on treatment outcome in patients with CD in primary care.
Results
Non-responding therapists and missing cases
Fifty-six therapists (77 %) completed the BFI questionnaire. The 17 non-responding therapists (23 %) did not significantly differ from the responding therapists with regard to gender (Chi2 = 0.30, P = 0.59), age (Z = 1.59, P = 0.11) but significantly for years working experience (Z = 2.03, P = 0.043). A total of thirteen BFI items (0.7 %) were not filled in; items were not mentioned twice. There were no significant differences between therapists who omitted an item and those who did not, regarding gender and age for Extraversion (respectively Z = −1.02, P = 0.31 and Z = −0.86, P = 0.39), Neuroticism (respectively Chi2 = 1.07, P = 0.30 and Z = 0.12, P = 0.90), Conscientiousness (respectively Chi2 = 0.01, P = 0.98 and Z = 0.87, P = 0.38), Agreeableness (Chi2 = 0.24, P = 0.63) and Openness to experiences (respectively Chi2 = 0.49, P = 0.48 and Z = −0.53, P = 0.59).
In the patient cases without an ICPC code there was no difference between missing and completed patient cases with regard to patient’s gender (Chi2 = 1.93, P = 0.17), age (Z = 0.34, P = 0.73) and significant difference in education (Z = −3.17, P = 0.002).
Characteristics
Thirty-nine therapists and 393 patients were included in the analysis. Therapists had an average age of 53 years (SD 1.6, range 28–69) and were mainly male. They had worked on average 27 years (SD 1.4, range 4–40). Besides being a general physiotherapist, therapists were specialized in the pelvis (
n = 2, 5 %), paediatrics (
n = 2, 5 %), manual therapy (
n = 10, 26 %) oedema (
n = 1, 3 %), sport (
n = 4, 10 %) and/or other specializations (
n = 4, 10 %). The therapists treated an average of 10 patients with CD within the three-year period (range 1–51). The BFI scores were generally higher on Openness to experiences (mean 3.42, SD 0.09), Extraversion (mean 3.49, SD 0.07), Conscientiousness (mean 3.69, SD 0.08) and Agreeableness (mean 3.75, SD 0.06) and lower on Neuroticism (2.39, SD 0.09). The range of all but one trait (Neuroticism) was limited. Therapists’ characteristics are shown in Table
2.
Table 2
Descriptive statistics of the physiotherapists (n = 39)
Gender, n (%) | Female/Male | 10 (26)/29 (74) |
Age (yrs.), n (%) | ≤30 | 1 (2.5) |
| 31–45 | 6 (17) |
| 46–59 | 23 (57.5) |
| 60+ | 9 (22.5) |
Educationa, n (%) | Specialization | 9 (23) |
| Academic Education (MSc.) | 2 (5) |
| Course aimed at chronic patients | 12 (30) |
| Course aimed at communication & coaching | 15 (38) |
| Course aimed at self-management | 7 (18) |
| None of above | 13 (33) |
Life-changing event ≤3 years., n (%) | Yes/No | 19 (52)/17 (47) |
Big Five, mean (min – max) | Neuroticism | 2.38 (1.25–3.88) |
| Extraversion | 3.49 (2.63–4.63) |
| Agreeableness | 3.75 (3.00–4.78) |
| Conscientiousness | 3.69 (2.89–4.89) |
| Openness to experiences | 3.42 (2.70–4.80) |
Patients’ average age was 67 years (SD 15, range 18–98) and they were mostly female. Overall, the patients experienced a clinically important reduction in their complaint (Mean −3.66, SD 2.5, −9 min – -2 max). The most frequent diagnosis was Osteoarthritis disorders (
n = 180, 46 %), followed by Rheumatoid Arthritis (
n = 40, 10 %) and Cerebral Vascular Accident (
n = 39, 10 %). Patients’ characteristics are shown in Table
3.
Table 3
Descriptive statistics of patients (n = 393)
Gender, n (%) | Female/Male | 240 (61)/153 (39) |
Age yrs., n (%) | ≤30 | 9 (2.3) |
| 31–45 | 22 (5.6) |
| 46–59 | 81 (20.6) |
| 60–75 | 154 (39.2) |
| 76–85 | 99 (25.2) |
| ≥86 | 28 (3.1) |
Education, n (%) | Lower | 143 (36.3) |
| Middle | 83 (21.1) |
| Higher | 46 (11.7) |
| Othera | 121 (31) |
Recurrence of the complaint, n (%) | Yes | 139 (36) |
| No | 250 (64) |
Severity, mean (SD, 95 % C.I.) | Start therapy | 6.84 (0.1, 6.6–7.0) |
| End therapy | 3.19 (0.1, 2.9–3.4) |
Disease, n | Cancer | Neoplasm or lymphatic system | 1 |
| | Esophageal malignancy | 1 |
Nervous system | 1 |
Neoplasm bronchus/lung | 1 |
| Cardiovascular | Heart failure | 2 |
Heart valve disease | 2 |
Cerebral ischemia | 1 |
Cerebrovascular accident | 39 |
Claudicatio intermittent | 18 |
| Rheumatic disorders | Fibromyalgia | 15 |
Rheumatoid arthritisb | 40 |
Other arthritis | 26 |
Tietze syndrome | 4 |
| Degenerative bone and joint disorders | Osteoarthritis of the Spine | 76 |
Osteoarthritis of the Hip | 34 |
Osteoarthritis of the Knee | 70 |
Osteoporosis | 16 |
| Disorder (central) nervous system | Multiple sclerosis | 6 |
Parkinson | 15 |
Alzheimer disease | 2 |
| Lung diseases | Chronic bronchitis | 2 |
Emphysema/COPD | 17 |
Asthma | 2 |
| Metabolic disorders | Cystic fibrosis | 1 |
Diabetes Mellitus | 1 |
Multilevel analysis
The analysis is shown in Table
4.
Table 4
Steps to prediction model for the course of complaints
Model 0 |
Intercept | | −3.66 | 0.19 | | | −4.02 – -3.30 | |
Total Model | | | | | | | |
Var. Th. level | | 0.47 | 0.31 | | | 0.13–1.73 | 0.076 |
Var. Pt. level | | 5.75 | 0.43 | | | 4.96–6.66 | |
Model I |
Patients |
| Gender | −0.47 | 0.25 | −1.88 | 0.060 | −0.96–0.02 | |
| Age | 0.01 | 0.01 | 1.76 | 0.079 | −0.002–0.03 | |
Intercept | | −2.90 | 0.44 | | | −3.76 – -2.03 | |
Total Model | | | | | | | |
Var. Th. level | | 0.41 | 0.29 | | | 0.11–1.63 | 0.067 |
Var. Pt. level | | 5.68 | 0.43 | | | 4.90–6.58 | |
Model II |
Patients |
| Gender | −0.48 | 0.25 | −1.94 | 0.053 | −0.97–0.006 | |
| Age | 0.01 | 0.01 | 1.63 | 0.103 | −0.003–0.03 | |
Therapists | | | | | | |
| Neuroticism | 0.59 | 0.32 | 1.81 | 0.070 | −0.048–1.22 | |
Intercept | | −4.27 | 0.88 | | | −5.99 – -2.56 | |
Total Model | | | | | | |
Var. Th. level | 0.36 | 0.26 | | | 0.09–1.46 | 0.060 |
Var. Pt. level | 5.65 | 0.42 | | | 4.88–6.54 | |
Model III |
Patients |
| Gender | −0.43 | 0.25 | −1.66 | 0.098 | −0.92–0.08 | |
| Age | 0.01 | 0.01 | 1.11 | 0.269 | −0.01–0.03 | |
Therapists | | | | | | |
| Neuroticism | 0.71 | 0.29 | 2.47 | 0.014* | 0.15–1.28 | |
| Gender | 0.72 | 0.32 | 2.21 | 0.027* | 0.08–1.35 | |
| Life events | −0.54 | 0.32 | −1.68 | 0.092 | −1.16–0.09 | |
Intercept | | −5.42 | 0.94 | | | −7.27 − -3.57 | |
Total Model | | | | | | | |
Var. Th. level | | 0.12 | 0.19 | | | 0.01–2.57 | 0.021 |
Var. Pt. level | | 5.60 | 0.43 | | | 4.82–6.52 | |
Of the initial model 7.6 % (ICC 0.076) was ascribed to inter-therapists variation (Model 0, Table
4). The patients’ gender (
P = 0.06) and age (
P = 0.08) were found to be eligible and were entered into the model (Model I, Wald Chi
2 = 6.71,
P = 0.03). The ICC was reduced to 6.7 %, meaning that a small part of the variance (9 %) between therapists was explained by these patient variables.
Of the Big Five variables, only Neuroticism was found to be eligible (Model II, Wald Chi
2 = 10.11,
P = 0.02). Therapist gender and experienced life events were added as confounders (Model III). Neuroticism was found to be significant (Wald Chi
2 = 16.82,
P = 0.005). Table
5 describes how the R
2 was calculated. 70 % of the variation between therapists could be explained by Neuroticism, therapist gender and experienced life events.
Table 5
Amount of explained variance per model
Total R2 | (0→I) |
\( \frac{\left(0.47-5.75\right)-\left(0.41+5.68\right)}{\left(0.47+5.75\right)} \)
| =0.13 |
Therapist variablesR2 | (I→III) |
\( \frac{0.41-0.12}{0.41} \)
| =0.71 |
Patient variablesR2 | (0→I) |
\( \frac{5.75-5.68}{5.75} \)
| =0.01 |
The subgroup analysis using only patients with Osteoarthritis (n = 180) treated by 30 therapists showed similar results to the main model, with Neuroticism as the independent variable and Conscientiousness and therapists’ gender as confounders: constant F = −10.18, Neuroticism F = 1.15, p = 0.003 (0,40–1.91 95 % CI), Conscientiousness F = 0.68, p = 0,07 (−0,04–1.41 95 % CI), therapists’ gender F = 0.76, p = 0.55 (−0.02–1.54 95 % CI). This might give an indication that the kind of chronic disease is unrelated to the influence of therapist on treatment outcome.
Discussion
The purpose of this study was to explore the influence of therapists’ personality traits on treatment outcome in patients with CD. Specht et al. [
46] indicated that personality can change not only change due to maturation, [
64] but also due to social demands and experiences. These changes are more pronounced at younger and older ages, but occur throughout a person’s lifetime [
46]. As personality traits might be accounted for, knowledge of traits that influence treatment outcome might be useful for general training of therapists and specifically for patients with CD. Generally, the results indicate that Neuroticism might have an influence on treatment outcome in patients with CD. A higher score on Neuroticism was associated with worse treatment outcomes. The current variables Neuroticism, gender and life events, explained approximately 71 % of the total variance between therapists. Therefore future research looking at the differences between therapists in treatment outcome should include the identified variables. Of the Big Five trait, Neuroticism was the only personality trait that was associated with better treatment outcomes. This suggests that treatment by therapists who tend to be calmer, more relaxed, secure and hardy, may produce better treatment outcomes in patients with CD.
To the author’s knowledge, this is the first study that looks systematically at physiotherapists’ personality traits in relation to treatment outcome. The indication of the possible relevance of Neuroticism corresponds with evidence found in the field of psychotherapy, showing that being treated by secure therapists predicts a better outcome [
25]. Moreover, the overall ICC of 0.075 found in this study is similar to previous research showing an ICC of 0.03–0.07 on therapist level [
11]. The results are based on a sample of predominantly older women with chronic diseases, treated by older male therapists. Therefore caution should be exercised when generalizing the current results. More research into the influence of these traits on treatment outcome in a more heterogeneous sample is needed. Evidently, this study supports prior research that a physiotherapist effect does exist [
11].
Contrary to expectations, no evidence was found for the four other personality traits. This finding contradicts previous research in psychotherapy suggesting that traits including being empathic, [
25‐
27,
29] cautious, non-intrusive, [
25] respectful, being able to adjust and exuding warmth [
29] (as a psychotherapist or general practitioner) improve treatment outcome. The contradiction with earlier research might be due to limited distribution of the personality traits and the difference in professions and diagnosis being examined. Further research with a sample of therapists with a wider range of Big Five scores is needed to obtain a better understanding of the influence of all Big Five traits. The influence of therapists’ gender confirmed the results of another physiotherapy study that investigated the placebo effect and its relation to personality [
28]. The study indicated that a female therapist was associated with better outcomes in patients with an irritable bowel syndrome.
While little is known about the influence of being more neurotic as a therapist on patient outcome in research, more is known of the influence on the therapist himself. Studies in the fields of psychotherapy and general practitioners underline that being less neurotic reduces the practitioner’s chances of emotional exhaustion (a form of burn-out) [
65] and increases their sense of satisfaction with life [
66]. If a therapist does not feel mentally stable, it is reasonable to assume that this might have consequences for his or her attitude when interacting with the patient. Further research is needed to clarify these assumptions.
Reflecting on ones personality as a physiotherapist could yield information on the existence of negative influencers, like Neuroticism. In the fields of psychotherapy and general practice, training has been advised as part of the professional education [
67]. Tools like communication skills training might be used as supplement to reflection, [
68] but the authors believe that self-awareness and reflection training during the early stages of study are needed, before these tools can be used effectively.
Other mechanisms such as patient personality traits, health beliefs, moral compass, placebo effects and other interaction mechanisms might affect both the patient and the therapist and therefore treatment outcome [
69]. For example, the patients’ beliefs regarding the effect of treatment or previous experiences with their goal of ‘getting physically active’ might influence their motivation towards adopting a more active role in the self-management process, which could influence treatment outcome [
69]. In the same way, a therapist who experienced negative results when engaged in physical exercise may have created a different conceptualization of the goal ‘getting physically active’. This, combined with having a certain personality trait, like being more neurotic, might increase the chance of a negative outcome when getting others to be physically active. Future studies that focus on the physiotherapist’s effect on treatment outcome ought therefore to not only look at the personality domains as such, but also take other mechanisms like experiences, health beliefs, etc. into consideration.
There are implications that CDs influence patients’ wellbeing differently [
70,
71]. For example, it is known that anxiety and depression are common in patients with Chronic Obstructive Pulmonary Diseases [
72]. Consequently, knowledge of personality traits that influence treatment outcome in specific CD groups would support therapists during treatment as they could adjust their approach accordingly. Therefore, analysis of specific CD groups might be of interest. In the current study, the outcome in the subgroup analysis points to patients with Osteoarthritis, showing that both Neuroticism and Conscientiousness are possible influencing factors. The association between Conscientiousness and Neuroticism has been described in previous studies [
22,
23].
When investigating the therapist’s effect, interdependency of the cases have to be taken into account as this can change the outcome considerably [
63]. A multilevel analysis, especially including subgroup analysis, requires large sample sizes. This can be a hindrance when performing this type of analysis. The current study gives an example of the use of longitudinal electronic patient record data for multilevel research into the physiotherapist effect. The use of the NPCD database reduced the organizational burden considerably, particularly in view of the number of therapists and patients needed. Furthermore, the database provided standard patient care data. Accordingly, missing patients were not study-specific and therapists were not aware of the patient data researched for this study.
Limitations
Unfortunately, in the NPCD database, around 60 % of the outcome variable was missing, causing a loss in the number of patients and therapists that could be studied. The missing data in the patient database was due to the fact that the study was based on voluntary registration of some of the variables in the NPCD. The authors did compare the missing data with the existing data. The demographic data did not differ significantly between missing and non-missing patients and therapists’ cases. Despite the amount of missing data, there were enough patients and therapists included to perform the analysis and there was a higher average of patients treated per therapist than estimated (ten vs. six) for the patient sample size. For the therapist data, the authors did try to reduce non-responsiveness by sending two reminders. It could be that a specific group of therapists, with specific personality traits, did not respond. However, there was variation in the BFI scales, albeit low. Therefore no large effect of missing a subgroup is expected.
Although the authors tried to account for the influence of a life event on personality traits [
46], it was not specified if the experience was positive or negative. As the effect can be the opposite depending on the experience, no judgement can be made on the kind of influence the item life events has on Neuroticism [
46]. Further research is needed to study this in greater depth.
Personality inventories like the NEO-FFI might possibly have been more precise for measure personality traits [
45]. That said, the BFI was chosen for practical reasons, since it does not take too long for therapist to fill out. Besides, the BFI provides a general view on personality, which was the purpose of the study.
Competing interests
This study has no competing interests. This work was performed by NIVEL, the Netherlands Institute for Health Services Research. NPCD is subsidized by the Ministry of Health, Welfare and Sport.
Authors’ contributions
EMB, MK, IS, MP and CV were involved in the conception of the research question. EMB was involved in analysing the data. All authors contributed to the interpretation of the data. EMB drafted the manuscript, which was reviewed and approved by all authors.