The association between pain self-efficacy and patient-reported outcome measures for hand disorders: a cross-sectional study

Abstract

Introduction

Multiple psychological factors influence the functioning of patients with hand disorders. Pain self-efficacy is a positive psychological factor, which concerns an individual’s confidence to function despite experiencing pain. This study aimed to analyse the association between pain self-efficacy and a patient-reported outcome measure (PROM) for hand and wrist disorders.

Methods

Cross-sectional data from patient records were collected prior to hand therapy to analyse the correlation between pain self-efficacy and a PROM for hand and wrist disorders. The assessment tools consisted of the Dutch translations of the Pain Self-Efficacy Questionnaire Short Form (PSEQ-2) and the Patient Rated Wrist Hand Evaluation (PRWHE).

Results

The findings were reported for the entire sample of 185 respondents (61% women). The PSEQ-2 and the PRWHE were strongly and significantly correlated, which signifies that a higher pain self-efficacy was associated with less pain and disability as measured by the PRWHE. Within a multivariable regression model which accounted for confounding variables, pain self-efficacy independently predicted 28% of the PRWHE scores.

Conclusions

A strong association between the Dutch PSEQ-2 and the PRWHE was found in this sample of hand therapy patients. This study was limited by the use of retrospective data and by the lack of validation of the Dutch PSEQ-2. The findings were consistent with existing research which reported similar correlations between upper extremity PROM scores and pain self-efficacy. The positively worded PSEQ presents a chance to routinely assess pain self-efficacy as a key psychological factor while also affirming a positive coping strategy.

Keywords

Self-efficacy pain patient-reported outcome measures hand routinely collected data

Introduction

A wide evidence base supports the limiting influence of negative psychological factors on the functioning of patients with hand disorders.^1,2 However, seminal authors Seligman and Csikszentmihalyi³ proposed a new paradigm of positive psychology, which values character traits such as optimism, thankfulness, and resilience. One of these positive psychological factors was self-efficacy, which Bandura^4,5 conceptualised within social cognitive theory as a person’s expectation to master a particular situation. The more specific construct of “pain self-efficacy” referred to the confidence to function despite experiencing pain.⁶ Multiple studies have investigated the role of pain self-efficacy in cohorts with upper limb disorders^7–10 and in cohorts with a specific diagnosis such as distal radius fractures¹¹ and proximal interphalangeal joint dislocations.¹² These prior studies have investigated the association of pain self-efficacy with upper extremity patient-reported outcome measures (PROMs),^7–12 namely the Disabilities of the Arm Shoulder Hand (DASH), the QuickDASH and the Patient-Reported Outcomes Measurement Information System - Physical Function - Upper Extremity (PROMIS-PF-UE). However, there was a gap in the literature regarding a PROM specific to hand and wrist conditions and injuries. This study’s primary research question was to identify whether there was a correlation between pain self-efficacy and a PROM for hand and wrist disorders. The secondary research question was to analyse the predictive value of pain self-efficacy on a PROM, accounting for diagnosis, comorbidities, and demographic variables.

Methods

Study design

This cross-sectional study analysed routinely gathered, retrospective data within existing patient records. The study was completed as part of the Hand Therapy Master programme of the University of Derby and ethical approval was granted by both the ethics committees of the University of Derby in the United Kingdom and the St Antonius Hospital in the Netherlands. The study was reported using the STROBE cross-sectional reporting guidelines.¹³

Data collection

The data were collected from March to August 2021 in the hand therapy department of the St Antonius Hospital, which is a secondary level care hospital in the Netherlands. Patients routinely completed two questionnaires in Dutch at the beginning of hand therapy, namely the Pain Self-Efficacy Questionnaire Short Form (PSEQ-2)¹⁴ and the Patient Rated Wrist/Hand Evaluation (PRWHE).¹⁵ These questionnaires were completed within the personalised hospital digital environment before the first hand physiotherapy or occupational therapy session or on paper at the first therapy session.

Assessment tools

Pain self-efficacy was assessed by means of the PSEQ-2¹⁴ (Box 1), which was found to have the same test-retest reliability and content validity as the full-length PSEQ in chronic pain patients.¹⁴ The PSEQ-2 was scored from zero to 12, in which zero denotes the lowest pain self-efficacy and 12 denotes the highest pain self-efficacy. The Dutch PSEQ-2 was obtained for clinical use by deleting all items except items five and nine from the validated full-length Dutch PSEQ.¹⁶ In addition, the validated Dutch translation of the Patient Rated Wrist/Hand Evaluation (PRWHE-DLV) was used as a hand and wrist-specific PROM.^17,18 A PRWHE score of zero indicates that a respondent has no pain or disabilities, whereas a maximum score of 100 indicates the worst pain and disabilities.

Box 1. Pain Self-Efficacy Questionnaire Short Form (PSEQ-2)

Please rate how confident you are that you can do the following things at present, despite the pain. To indicate your answer circle one of the numbers on the scale under each item, where 0 = not at all confident and 6 = completely confident.

Remember, this questionnaire is not asking whether or not you have been doing these things, but rather how confident you are that you can do them at present, despite the pain.

1. I can do some form of work, despite the pain (“work” includes housework, paid and unpaid work).

2. I can live a normal lifestyle, despite the pain.

Participants

Sample size was calculated based on the correlation coefficient in prior cross-sectional research regarding the PSEQ in a similar study population.⁸ A sample of at least 84 patients was required to test an association of r = 0.3 with a power of 80% and a significance level of 5%.¹⁹ The hospital ethics committee exempted the study from requesting retrospective informed consent from patients who had been discharged from the service. This ensured the full demographic spread of the data and avoided potential issues with response bias. The exemption allowed the use of electronic data of patients who had not objected to the use of their data for research purposes. Children, persons with legal incompetence, cognitive disability or not fluent in the Dutch language are likely to experience difficulties in understanding their rights within healthcare, for example, the right to object to the use of their records for research purposes. Therefore, these vulnerable individuals were excluded to protect against the inadvertent use of data against their will. Eligible participants were identified via hand therapy notes and the central coding of the patient record overview. Inclusion criteria were adults who had attended at least one session of hand therapy with pathology located in the hand, wrist and forearm (including multiple injuries) and had completed PSEQ-2 and PRWHE.

Data management

Data were collected from the hospital files and entered into the data management system Research Electronic Data Capture (REDCap).²⁰ The data management process is outlined in the Supplemental material. The referral diagnosis was categorised into four categories to detail the type of hand pathology, which allowed analysis of the contribution of biomechanical factors to the PRWHE score. The researcher also extracted data for five variables previously reported as associated with PROMs, namely: age,²¹ gender,²¹ prior hand injury,²¹ diabetes²² and longstanding neurological disorders such as multiple sclerosis.²³ Lastly, mental health disorders were extracted because low self-efficacy has been associated with a history of mental illness.²⁴

Analysis

Data analysis proceeded by exporting the anonymised data to IBM SPSS Statistics version 26.0²⁵. The PRWHE and PSEQ-2 data were assessed for normality by the Shapiro-Wilk test and visual inspection of the histogram. Dependent on the data distribution, the Pearson or Spearman correlation coefficient was calculated to investigate the relationship between the PSEQ-2 and PRWHE. In addition, hierarchical multiple regression was conducted to calculate the predictive value of pain self-efficacy independent of potential confounders. The assumptions of regression were checked by inspecting boxplots for outliers and residual plots for a normal distribution. Residuals are the errors of the regression equation, and a normal distribution of residuals indicates that other data assumptions have been sufficiently met.²⁶ The hierarchical regression was ordered based on the secondary research question. Variables were entered into the hierarchical regression in two blocks. Firstly, demographics, diagnosis and comorbidities, followed by pain self-efficacy to assess whether it further improved the prediction of the PRWHE score.

Results

Descriptive statistics

Electronic data of 229 patients were extracted over the 6 months of available data based on the presence of a completed PSEQ-2 or PRWHE questionnaire in the patient record. Forty-four patients were excluded due to a missing PSEQ-2 or PRWHE (n = 31), aged under 18 years (n = 7), language barrier (n = 3), therapy not attended (n = 2) or objection to use of data (n = 1). This resulted in 185 patients who satisfied all the selection criteria. The patients consisted of 113 women (61%) and 72 men (39%), aged 18–83 years old (mean 53; SD 15.4). The findings are reported for the entire sample of 185 respondents. The median PSEQ-2 score was 8 (IQR 6–10), which is a higher pain self-efficacy than the mean score of 5 in chronic pain patients.¹⁴ The median PRWHE score was 59 (IQR 36–74), which represents a high level of pain and disability compared to the median of zero in the general Dutch population.²¹ The presence of comorbidities varied between 3–7% in the sample (Table 1) and the referral diagnosis category of non-operative management of non-traumatic conditions was most common, representing 34% of the respondents.

Table 1.

Comorbidities and diagnosis frequency.

Comorbidities	Frequency	Diagnoses	Frequency
Prior hand injury	9 (5%)	Non-operative management non-traumatic conditions	63 (34%)
Neurological disorder	6 (3%)	Non-operative management traumatic injuries	43 (23%)
Mental health disorder	9 (5%)	Surgical management non-traumatic conditions	44 (24%)
Diabetes	12 (7%)	Surgical management traumatic injuries	35 (19%)

Correlation

Spearman’s rank correlation coefficient was calculated since normality testing revealed a statistically significant Shapiro-Wilk test for both the PSEQ-2 (p < 0.001) and PRWHE (p = 0.002) and both histograms displayed negatively skewed data. The PSEQ-2 was significantly correlated with the PRWHE (Spearman’s ρ = −0.59; p < 0.001; 95% CI = −0.64 to −0.42). The 0.59 correlation represents a moderately strong association (>0.5).¹⁹ The scatterplot (Figure 1) and the negative sign both demonstrate an inverse relationship, that is a higher pain self-efficacy was associated with lower levels of pain and disability as measured by the PRWHE.

Figure 1.

Scatterplot of PSEQ-2 and PRWHE. PSEQ-2: Pain Self-Efficacy Questionnaire Short Form; PRWHE: Patient Rated Wrist Hand Evaluation.

Regression

Hierarchical multiple regression was performed to assess if the addition of pain self-efficacy improved the prediction of the PRWHE beyond that given by diagnosis, comorbidities, and demographic variables. Inspection of the data revealed a normal distribution of the residuals and no outliers, meeting the underlying assumptions of regression. There were 18 observations per predictor variable. Since recommendations in the literature varied between 10 to 20 observations,^19,26 the sample size was determined as adequate to support the regression analysis.

Age and gender were entered in the first step but did not significantly predict PRWHE scores (R² = 0.02, p = 0.166, Table 2). Comorbidities and referral diagnoses were entered in the second block, yet this did not significantly improve the regression model (R² change = 0.05, p = 0.191). Finally, the PSEQ-2 was entered in the third block, significantly improving the predictive ability of the model by 28% (R² change = 0.28, p < 0.001).

Table 2.

Model summary table with dependent variable PRWHE.

Model	R	R Square	Adjusted R square	Standard error of estimate	R Square change	F Change	Significance F change
1	0.140^a	0.020	0.009	23.17	0.020	1.81	0.166
2	0.270^b	0.073	0.025	22.97	0.054	1.44	0.191
3	0.594^c	0.353	0.315	19.25	0.280	75.1	<0.001

^aPredictors: (Constant), Gender, Age.

^bPredictors: (Constant), Gender, Age, Diagnosis Non-Operative Non-Traumatic, Diagnosis Surgical Non-Traumatic, Diagnosis Non-Operative Traumatic, Comorbidity Neurological Disorder, Comorbidity Prior Hand Injury, Comorbidity Mental Health Disorder, Comorbidity Diabetes.

^cPredictors: (Constant), Gender, Age, Diagnosis Non-Operative Non-Traumatic, Diagnosis Surgical Non-Traumatic, Diagnosis Non-Operative Traumatic, Comorbidity Neurological Disorder, Comorbidity Prior Hand Injury, Comorbidity Mental Health Disorder, Comorbidity Diabetes, PSEQ-2.

The total regression model was statistically significant (Table 3) and explained 35% of the variance in PRWHE scores (F (10, 174) = 9.48; p < 0.001). Within this model, the PSEQ-2 had an unstandardised regression coefficient (B) of −4.25 (95% CI = −5.2 to −3.2, Table 4). This indicated that an increase of one point in the PSEQ-2 score predicted a decrease of 3–5 points in the PRWHE score. In summary, the regression model predicted 35% of the PRWHE and, within this model, the PSEQ-2 independently explained 28% of the variance in the PRWHE.

Table 3.

ANOVA with dependent variable PRWHE.

Model		Sum of squares	Degrees of freedom	Mean square	F	Significance
1	Regression	1947.663	2	973.831	1.814	0.166^a
	Residual	97,704.816	182	536.840
	Total	99,652.478	184
2	Regression	7280.282	9	808.920	1.533	0.140^b
	Residual	92,372.196	175	527.841
	Total	99,652.478	184
3	Regression	35,144.837	10	3514.484	9.480	0.000^c
	Residual	64,507.641	174	370.734
	Total	99,652.478	184

^aPredictors: (Constant), Gender, Age

Table 4.

Coefficients with dependent variable PRWHE.

Model		Unstandardised coefficients		Standardised coefficients			95% confidence interval for B
Model		B	Standard error	Beta	t	Signifi-cance	Lower Bound	Upper Bound
1	(Constant)	49.356	6.312		7.820	0.000	36.902	61.810
	Age	0.149	0.111	0.099	1.348	0.179	−0.069	0.368
	Gender	−4.512	3.497	−0.095	−1.290	0.199	−11.411	2.387
2	(Constant)	50.737	6.762		7.503	0.000	37.391	64.083
	Age	0.089	0.115	0.059	0.772	0.441	−0.138	0.315
	Gender	−5.154	3.615	−0.108	−1.426	0.156	−12.289	1.981
	Prior hand injury	6.087	7.976	0.056	0.763	0.446	−9.655	21.828
	Neurological disorder	13.698	9.676	0.105	1.416	0.159	−5.399	32.794
	Mental health disorder	7.917	7.948	0.073	0.996	0.321	−7.769	23.603
	Diabetes	6.542	7.034	0.069	0.930	0.354	−7.339	23.603
	Diagnosis non-operative non-traumatic	−0.537	5.194	−0.011	−0.103	0.918	−10.787	9.714
	Diagnosis surgical non-traumatic	6.871	5.466	0.126	1.257	0.210	−3.917	17.660
	Diagnosis non-operative traumatic injuries	−3.942	5.313	−0.072	−7.42	0.459	−14.428	6.545
3	(Constant)	78.700	6.521		12.069	0.000	65.830	91.570
	Age	0.128	0.096	0.085	1.332	0.185	−0.062	0.318
	Gender	−0.596	3.075	−0.013	−1.94	0.847	−6.665	5.474
	Prior hand injury	7.824	6.687	0.073	1.170	0.244	−5.375	21.022
	Neurological disorder	11.976	8.111	0.091	1.476	0.142	−4.034	27.985
	Mental health disorder	3.791	6.678	0.035	0.568	0.571	−9.389	16.970
	Diabetes	2.702	5.911	0.029	0.457	0.648	−8.965	14.369
	Diagnosis non-operative non-traumatic	1.877	4.362	0.038	0.430	0.668	−0.6.732	10.485
	Diagnosis surgical non-traumatic	5.751	4.583	0.105	1.255	0.211	−3.295	14.796
	Diagnosis non-operative traumatic injuries	−1.224	4.464	−0.022	−0.274	0.784	−10.034	7.587
	PSEQ-2	−4.248	0.490	−5.44	−8.670	0.000	−5.215	−3.281

Discussion

This study primarily aimed to analyse the correlation between the Dutch PSEQ-2 and the PRWHE. A statistically significant and moderately strong correlation of −0.59 was identified, signifying that a high pain self-efficacy was associated with better patient-reported hand function in this sample. Previous studies^7–12 also reported a significant association between pain self-efficacy and upper extremity PROMs (DASH, QuickDASH, PROMIS-PF-UE), which was consistent with the PRWHE as a hand and wrist-specific PROM in this study. In contrast to several prior studies which reported only weak or moderate correlation,^8,9,11,12 this study found a strong association. This might be a consequence of using the PRWHE, which has been found to have good construct validity and responsiveness in hand and wrist disorders.^18,27 The upper extremity questionnaires used in previous studies^8,9,11,12 might be less sensitive to the hand disorders of their study population, potentially explaining the weaker correlation.

The second objective was to investigate the ability of the PSEQ-2 to predict the PRWHE score. PSEQ-2 score predicted 28% of the PRWHE, in addition to diagnosis, comorbidities, age and gender. Hageman et al.⁸ similarly calculated a predictive value of 35% for pain self-efficacy, although they did not account for other factors in the regression. Four other studies^7,9,10,12 specifically reported the predictive value of pain self-efficacy as 3%–14%, which was distinctly lower than the 28% in this study. A reason for this difference might be that these four studies assessed other psychological factors in addition to pain self-efficacy, such as anxiety, depression and catastrophising. Within the theoretical framework of social cognitive theory, low self-efficacy beliefs are closely associated with mental health disorders such as anxiety.⁵ A strong correlation between regression variables results in multicollinearity¹⁹ and in a lower unique predictive value for each variable.²⁶ Therefore, the highly correlated psychological factors likely accounted for the lower independent predictive value of pain self-efficacy in prior studies compared to this study.

Study limitations

The inclusion criterion of a completed PSEQ-2 and PRWHE might have resulted in a selection bias since the questionnaires were primarily offered to patients through the digital hospital environment. Although paper questionnaires were available at the first therapy session, the use of these depended on the time available and the priorities of the therapist. A lower digital literacy has been identified in patients who were elderly and had less formal education.²⁸ As a result, young and highly educated patients potentially accessed the digital hospital environment more easily and could be overrepresented in this study.

A potential shortcoming of the use of patient medical records was that these might not be complete. This was likely to be an issue for comorbidities in this study since a representative survey²⁹ reported that 26% of Dutch adults experienced mental health problems in the last year, whereas this study registered mental health disorders in only 5% of the respondents. Therefore, the presence of comorbidities, and especially of mental health conditions, might be underestimated due to the incompleteness of patient records.

This study addressed abstract concepts of self-efficacy and perceived hand function and the extent to which the chosen assessment tools could successfully quantify these concepts was crucial to the validity of the findings. This study focused on the total PRWHE score since the sub-scales were found to be less reliable by Moumni et al.¹⁷ However, this prevented analysis of the PSEQ-2 correlation with the pain or function sub-scales of the PRWHE. In addition, no validation studies of the Dutch PSEQ-2 were found in the literature. This was a shortcoming in this study’s methods because the measurement error of the Dutch PSEQ-2 for assessing pain self-efficacy was unknown.

Generalisability

The sample size and the selection criteria impact the external validity of our findings. The sample of 185 patients provided sufficient power for statistical tests of correlation and regression. The realisation of a large sample was a key strength of this study since it met an important precondition for generalising results from sample to population.¹⁹ Furthermore, the inclusion of all pathology in the forearm, wrist and hand yielded a sample that was representative of the hand therapy patient population of a Dutch hospital.

Interpretation

This study reported a strong correlation between pain self-efficacy and PRWHE. A first explanation for this correlation might be the overlap in concepts measured with the PSEQ-2 and PRWHE. However, this overlap was not supported by factor analysis studies who identified “coping strategies in response to nociception” as the underlying construct measured by the PSEQ³⁰ and “disability” as underlying the PRWHE.^17,27 This difference can be accounted for by the theoretical basis of the PSEQ-2 in social cognitive theory^5,6 in contrast to the theoretical grounding of the PRWHE in the International Classification of Functioning.^31,32 A second explanation was that high self-efficacy motivates individuals to attempt tasks in the face of adversity.⁵ In the context of musculoskeletal pain, high self-efficacy helps patients to increase their efforts to reach functional goals despite experiencing an obstacle such as pain. This stronger resolve helped individuals to perform activities, leading to less pain and disability, as reflected in better PROM scores. Longitudinal studies associated a strong pain self-efficacy with better PROMs at 6 weeks to 6 months follow-up,^9,11 complementing this study’s cross-sectional findings in support of a causal relationship in which pain self-efficacy positively influences patient-reported outcome measures.

Implications for practice

Since pain self-efficacy impacts self-reported function in patients with hand disorders, therapists are challenged to incorporate this evidence into practice. This might be achieved by routine application of the PSEQ and within the patient-therapist relationship. A multitude of psychological factors has been reported to impact PROMs in hand disorders.^2,9,11 For hand therapy practice this presents the dilemma of which factor to routinely assess and focus on. One consideration in this choice might be the impact of the questionnaire itself on the respondent. Rigorous RCTs by Claessen et al.³³ and Özkan et al.³⁴ found that respondents reported a better hand function and had a higher grip strength directly after completing a positively worded questionnaire compared to the same, negatively worded questionnaire. Claessen et al.³³ attributed this effect to “semantic priming,” which is the subconscious influencing of an individual’s mindset using words. Accordingly, routine use of the PSEQ as a positively worded questionnaire has the benefit of focusing on a patient’s strengths and thus affirming a positive coping strategy. Routine application of the PSEQ has the further benefit of facilitating a conversation concerning the patient’s coping style. Especially if a patient scores poorly for pain self-efficacy, the patient would benefit from psycho-education about the meaning of pain. We suggest that this could be realised within group sessions guided by a mental health professional in collaboration with a hand therapist. Furthermore, hand therapy protocols specifically targeting self-efficacy have been designed, although they have not proven to be more effective than usual care.^35,36 In contrast to these standardised interventions, the patient-therapist relationship could strengthen a patient’s self-efficacy more effectively. This is termed “social modelling” in social cognitive theory,⁵ in which the therapist’s self-efficacy serves as an example for the patient within a trusting relationship. A systematic review of qualitative studies³⁷ concluded that physiotherapists trained in including psychological aspects in their therapy experienced an improved alliance with their patients. This trusting patient-therapist relationship is fundamental to increasing patients’ confidence to attempt activities and persevere despite the pain. Thus, hand therapists are encouraged to routinely assess and strengthen pain self-efficacy within a trusting relationship with their patients.

Conclusions

In conclusion, a strong correlation between the Dutch PSEQ-2 and the PRWHE was found in this sample of hand therapy patients. This signifies that a high pain self-efficacy was strongly associated with the PRWHE as a hand and wrist specific PROM, which was consistent with existing research applying upper extremity PROMs. Although this cross-sectional study could not establish a causal relationship, social cognitive theory⁵ and prior longitudinal studies^9,11 indicate that a high pain self-efficacy motivates individuals with hand disorders to attempt activities despite their pain, leading to improved PROMs. The application of the positively worded PSEQ presents a chance to routinely assess pain self-efficacy as a key psychological factor while also affirming a positive coping strategy.

Supplemental Material

Supplemental Material - The association between pain self-efficacy and patient-reported outcome measures for hand disorders: a cross-sectional study

Supplemental Material for The association between pain self-efficacy and patient-reported outcome measures for hand disorders: a cross-sectional study by Ilona Overduin, Cate Allen and Jomina Aret in Hand Therapy

Supplemental Material

Supplemental Material - The association between pain self-efficacy and patient-reported outcome measures for hand disorders: a cross-sectional study

Supplemental Material

Supplemental Material - The association between pain self-efficacy and patient-reported outcome measures for hand disorders: a cross-sectional study

Footnotes

Acknowledgements

We would like to thank Sarah Woodbridge and Petra Heijnsbroek for their guidance in this research.

Author contributions

IO researched literature. IO and JA conceived the study. IO and CA were involved in protocol development and gaining ethical approval. IO wrote the first draft of the manuscript. All authors reviewed and edited the manuscript and approved the final version of the manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Guarantor

Ethical Approval

Ethical approval was granted from the University of Derby’s College of Health, Psychology and Social Care Research Ethics Committee (Reference ETH2021-4135) and from the St Antonius Hospital Local Review Ethics Committee (reference Z21.076).

Informed Consent

The Local Review Ethics Committee exempted the study from requesting informed consent.

ORCID iD

Ilona Overduin

Supplemental Material

Supplemental material for this article is available online.

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