Multidimensional Pain Characteristics in Older Adults with Chronic Venous Leg Ulcers

Abstract

Objective: Pain affects wound healing, treatment, and quality of life because it has significant impacts on physical, psychological, and social well-being. Despite the fact that more than half of chronic venous leg ulcer (CVLU) patients experience mild-to-moderate pain, the multidimensional characteristics of CVLU pain are not well documented. The objective of this study was to describe the multidimensional pain characteristics, including the sensory, affective, cognitive, and behavioral dimensions, of CVLU before debridement.

Approach: Participants (N = 40) were recruited from a wound clinic. We conducted a descriptive analysis of clinical data, including pain, wound, and demographic characteristics, collected at the first visit.

Results: The mean age of participants was 70.8 ± 9.1 years, 22 (55%) participants were female, and 35 (87.5%) were white. Participants reported mean current pain intensity (2.9 ± 2.7), least (1.2 ± 2.2) and worst (4.8 ± 3.4) pain intensity in 24 h, and tolerable pain level (4.9 ± 2.64) on a 0–10 scale. They described pain as periodic (66.7%, n = 26) with multiple pain quality descriptors (5.4 ± 2.9). Their past pain treatments provided some pain relief (65%, n = 25). For 68% (n = 27), their pain was the same as they expected. Nearly all had a tendency not to tell others about their pain (95%, n = 38).

Innovation: This study is the first to describe the multidimensional pain characteristics of patients with CVLU as measured with PAINReportIt.

Conclusion: Patients with CVLU reported willingness to tolerate a relatively high level of pain and experience the level of pain they anticipate. Multidimensional pain assessment will assist clinicians to select individualized therapies to manage pain and improve quality of life for these patients.

Joyce Stechmiller, PhD

Introduction

Despite the fact that 46%–100% of the chronic venous leg ulcer (CVLU) patient population experiences mild-to-moderate pain,¹ the multidimensional characteristics of CVLU pain are not well documented. Currently, the intensity and incidence of CVLU pain are described, but other multidimensional characteristics such as sensory, affective, cognitive, and behavioral characteristics of CVLU are inadequately depicted. The purpose of this study was to describe the multidimensional pain characteristics experienced by patients with CVLU.

Pain affects wound healing, and it has significant impact on physical, psychological, and social well-being, which influence treatment and quality of life in the chronic wound population.^2,3 Pain of CVLU co-occurs with other symptoms that negatively affect quality of life and wound healing.^4,5 To date, wound pain experienced by the CVLU population is often addressed in the literature in terms of how it impacts quality of life, and this may be due to complexities correlated with psychoneurologic symptoms such as depression, fatigue, and anxiety.⁶ Although the mechanism of the complexity involving physiologic and psychologic factors is elusive, the emotional aspect is significantly related to wounds, which results in a link between anxiety and pain, as well as wound healing.⁷ Depression is correlated with pain as well because negative mental health is prominent in the CVLU population.⁸ Notably, pain quality descriptors are rarely included in the pain research for the CVLU population. When they are, only about 30–50% of participants with CVLU described sensory pain in terms such as itchy, tender, throbbing, burning, and stinging,⁹ and about 58% of them experienced this type of sensory pain.¹⁰ Moreover, not many studies have focused on other sensory characteristics or the affective, cognitive, and behavioral dimensions of pain from CVLU. Only one group of researchers reported that 51% of study participants with CVLU described pain using affective descriptors, 28% used evaluative descriptors, and 32% used miscellaneous descriptors.¹¹ Current studies that examined pain from CVLU are limited to describing the sensory dimension of pain, with inadequate simultaneous characterization of the multiple dimensions of pain.

Considering the complexity of pain from CVLU and its influence on quality of life, characterizing pain from a multidimensional perspective would provide insights for the design of appropriate pain interventions to improve health outcomes in this population. Understanding the complexity of pain experienced by CVLU patients would enable clinicians to provide effective pain management to improve wound healing and quality of life.

We assessed wound pain with PAINReportIt, an adaptation of the McGill Pain Questionnaire, to characterize pain as a multidimensional experience, including its sensory, affective, cognitive, and behavioral dimensions, among older adults with CVLU before debridement. The sensory dimension of pain refers to attributes of pain such as location, intensity, quality, and temporal pattern. The affective dimension of pain refers to the emotional component of the pain experience. The cognitive dimension of pain refers to the thoughts, beliefs, appraisals, and expectations related to pain. The behavioral dimension of pain refers to activities or actions that increase or decrease the pain and tendencies to communicate about the pain and take pain medications.¹² The detailed information derived from this assessment can assist clinicians to select therapies to personalize pain management and improve quality of life for these patients.

Clinical Problem Addressed

The CVLU is the most prevalent type of ulcer located in the lower legs, and it affects two million people per year, including 4% of all people over 65 years of age.¹³ Treatment costs are estimated at $2.5–3.5 billion per year in the United States.¹⁴ Pain is the most significant symptom that affects the quality of life in people with CVLU.² Despite the high disease burden and negative impact caused by wound pain on quality of life in the CVLU population,¹⁵ the multidimensional characteristics of their pain are not well described.¹ Understanding temporal characteristics of the pain is essential for deciding optimal timing for pain management and evaluation.¹ Pain quality descriptors provide insights into the nature of the pain, which can be used as a guide for selecting different therapies. Therefore, multidimensional pain assessment, including a measure of its impact, is crucial for pain management.¹⁶ The specific aim of this study was to describe the sensory, affective, cognitive, and behavioral dimensions of CVLU before debridement.

Materials and Methods

Study design

As a part of a prospective, longitudinal, observational study (R01 NR016986), we conducted a descriptive analysis of pain at the first study visit. The university's institutional review board approved the study (IRB201700566).

Subjects and setting

A total of 40 subjects who were recruited from August 2018 to February 2019 at a wound care clinic were included in this analysis. The criteria for clinical diagnosis of venous leg ulcers follow the definition of the American Venous Forum.¹⁷ Chronic status of venous leg ulcers was confirmed by a duration of greater than 30 days.^18,19 Inclusion and exclusion criteria required for subjects are described in Table 1.

Table 1.

Inclusion and exclusion criteria of the study participants

Inclusion

Exclusion

(1) Were aged 55 or older (2) Had a venous leg ulcer confirmed by clinical diagnosis (3) Had an adequate arterial blood perfusion (ABI between 0.7 and 1.3, inclusive or no occlusion as determined by Doppler measurement (4) Had a chronic venous ulceration duration of more than 30 days (5) Had a scheduled weekly sharp debridement at a wound care clinic (6) Were fluent in English (7) Were cognitively intact as determined by a minimum score of 24 on the MMSE

(1) Were undergoing kidney dialysis for renal failure (2) Were receiving immunosuppressant treatment, including systemic steroids or topical steroids in the wound within 4 weeks before the study (3) Had a systemic infection (4) Had participated within the last 30 days in another clinical research trial related to wounds or an intervention that could interfere with the integrity of this study (5) Were on chemotherapy, including antimetabolites, alkylating agents, platinum containing agents, or other cancer drugs known to be significant immunomodulators within 4 weeks before study entry (6) Had a concomitant condition that would make the participant unlikely to complete all visits as scheduled, for example, unstable COPD with frequent hospital admissions (7) Had immune suppression (HIV, transplant status) or autoimmune disorders, including lupus erythematosus, Crohn's disease, rheumatoid arthritis, or other autoimmune diseases that alter the systemic inflammatory environment (8) Had a recent (within 6 months) history of C. Difficile (9) Had severe or significant hypoalbuminemia (albuminemia <30 g/L, and/or prealbumin <5 mg/dL), or hypoproteinemia (proteinemia <55 g/L) (10) Did not have an ABPI between 0.7 and 1.3 or indication of occlusion as determined by Doppler measurement (11) Had a history of nonadherence to scheduled clinic appointments

ABI, ankle brachial index; ABPI, ankle brachial pressure index; COPD, chronic obstructive pulmonary disease; MMSE, mini-mental state examination.

Procedures

The eligible participants were contacted by the research coordinator during the clinic visit. The research coordinator explained the study purpose and procedure and obtained written informed consent. Data were collected from participants during the regular procedures of a clinic visit. Because debridement was the only surgical procedure performed routinely for the patients during a clinic visit, pain data were collected before the wound was debrided. In rare situations for an undocumented number of patients, the pain data were collected before and continued during debridement to prevent interference with the clinic work flow.

Instruments

Participant characteristics

Demographic characteristics of the sample included age, gender, race, ethnicity, education level, and marital status. These data were collected from a demographic questionnaire and electronic health records.

The Charlson comorbidity index (CCI)²⁰ is a disease-specific severity system that ranges from 0 to 5 and provides an objective consistent method to define disease burden using diagnostic information (ICD-10-CM). Since 1987, the CCI system has been validated extensively in many inpatient, ambulatory, rehabilitation, and long-term care settings. A CCI severity score reflects the degree of abnormality of individual signs and symptoms of a patient's disease(s). The kappa score for interrater reliability among dialysis patients has been reported as 0.93,²¹ and its validity for predicting in-hospital mortality is good-to-excellent.²²

The body mass index (BMI) was calculated by dividing a person's weight (kg) by the square of height (m²). The BMI provides a reliable measure of a person's body composition related to underweight, normal weight, and obesity categories.

Pain medications were collected using the medication module within PAINReportIt. Patients were asked what medications they took to relieve pain within 24 h before visiting the clinic. The research coordinator entered the data into the PAINReportIt application.

Wound characteristics

To measure wound size, wound perimeter, area, and volume were measured by the Silhouette (ARANZ Medical). The Silhouette is a handheld device that minimizes variability between clinicians who measure wounds. It provides laser-guided accuracy of the length, width, and depth of the wound in millimeters. The software also provides other calculations, including volume. The Silhouette has demonstrated a high level of reliability, validity, and reproducibility across studies.²³ Wound duration was the length of days that patients had wounds measured from self-reported records on a treatment monitoring form.

Pain

Pain was measured by PAINReportIt^® (Nursing Consult LLC, Seattle, WA) an adapted Internet-based version of the 1970 version of the McGill Pain Questionnaire.^24,25 PAINReportIt is a computerized tool that is designed for an individual to touch the computer screen to tell others about their pain.²⁶ A research version of PAINReportIt is available at https://painrelieveit.ahc.ufl.edu/PRIT/SignIn with permission (diwilkie@ufl.edu). The PAINReportIt is a valid and reliable measure of pain^27,28 as a multidimensional experience, inclusive of sensory pain (location, intensity, quality, pattern), and the affective, cognitive, and behavioral dimensions of pain. Its analgesic medication module allows calculation of pain medication behaviors, such as analgesic adherence. Pain intensity was measured on a scale from 0 (no pain) to 10 (the worst it could be), for each of current pain (now), least pain in the past 24 h, and worst pain in the past 24 h. Pain quality was measured by the words selected by participants from 78 verbal descriptors. The 78 descriptors are subgrouped into 20 groups representing different types of pain within four dimensions: 42 sensory descriptors (temporal, spatial, pressure, thermal, and other experiences), 14 affective descriptors (tension, fear, and autonomic properties), 5 evaluative descriptors (overall appraisal of severity), and 17 miscellaneous descriptors.²⁹ The sensory and miscellaneous descriptors can be counted to represent neuropathic pain (28 descriptors) and nociceptive pain (26 descriptors).²⁷ Other subscale scores that can be calculated from PAINReportIt include: the pain rating index-sensory (PRI-S), the pain rating index-affective (PRI-A), the pain rating index-evaluative (PRI-E), the pain rating index-miscellaneous (PRI-M), the pain rating index-total (PRI-T), and the number of words chosen.²⁹ A multidimensional score can be derived from the pain location, intensity, quality, and pattern data and is known as the composite pain index (CPI).³⁰ Finally, a total of pain pattern score (TotPat) is derived from the nine pain pattern descriptors, and the average pain intensity (AVG-PI) is derived from the current, least, and worst pain intensity variables.³¹ The calculations to derive scores for each variable and ranges^30,32 are summarized in Table 2.

Table 2.

Calculated pain variables in PAINReportIt^23,24

Variable	Operational Meaning	Calculation	Range
PRI-S (N = 39)	Pain rating index-sensory	42 words; the no. of the word selected the one most severe word for each subscale group29	0–42
PRI-A (N = 39)	Pain rating index-affective	14 words; the no. of the word selected the one most severe word for each subscale group	0–14
PRI-E (N = 39)	Pain rating index-evaluative	5 words; the no. of the word selected the one most severe word for each subscale group	0–5
PRI-M (N = 39)	Pain rating index-miscellaneous	17 words; the no. of the word selected the one most severe word for each subscale group	0–17
PRI-T (N = 39)	Pain rating index-total	Sum of PRI-S, PRI-A, PRI-E, and PRI-M scores	0–78
TotPat (N = 39)	Total pain pattern score	Sum of pain pattern scores31 3 points-constant, continuous, steady 2 points-brief, momentary, transient 1 point-intermittent, periodic, rhythmic	0–6
AVG-PI	Average pain intensity	Mean of pain now, pain worst, and pain least in past 24 h	0–10
CPI (N = 39)	Composite pain index	Sum of no. of pain sites, intensity, PRI-T, and pain pattern scores converted to proportional scores30	0–100

Statistical analysis

All participants enrolled to date (N = 40) in the ongoing study were included in this analysis. While frequentist null hypothesis testing, and therefore, statistical power, is not relevant for the Bayesian approach used in this article, there is a correspondence between sample sizes required for frequentist and Bayesian approaches (see, e.g., Inoue et al.³³). Using PASS 2019,³⁴ moderate correlations of 0.40 or greater produce a 95% confidence interval (CI) halfwidth of 0.29 or less. Descriptive statistics (e.g., means, standard deviations [SD], frequencies, percent, and range) appropriate to measurement level were computed for all variables. Checks for outliers, distributional forms, and missingness were performed on the data. As the distributions of the pain characteristics were highly skewed, robust correlations were calculated as a measure of the strength of linear association between those variables. In keeping with the analysis methods proposed in the parent grant (R01 NR016986), Bayesian methods were applied to the correlational analyses among the pain characteristic variables. Bayesian methods have several advantages over traditional frequentist approaches, with better small-sample performance and the focus on parameter estimation and quantification of uncertainty being of particular bearing for this analysis.³⁵ The Bayesian analysis was performed using the “correlation” package³⁶ in R version 4.0.3.³⁷ Options selected in the “correlation” package included “pearson,” “robust,” and a medium Bayesian prior of 1/3, as was calculation of the 95% Highest Density Interval credibility intervals, Region of Practical Equivalence (ROPE), Bayes factor, and probability of direction. The ROPE utilized was −0.05 to 0.05, corresponding to that suggested for correlation by Kruschke and Liddell.³⁸ The Bayes factors were calculated as $\frac{P\left\{Data|Correlation\ne 0\right\}}{P\left\{Data|Correlation=0\right\}}$.

Results

Participants' characteristics

The personal characteristics of participants are described in Table 3. A total of 40 participants were included in this analysis. Among them, 22 (55%) participants were female, 38 (95%) participants were non-Hispanic, and 35 (87.5%) participants were white. The mean age of participants was 70.8 (SD = 9.1) years, 27 (67.5%) had at least some college education, and 23 (57.5%) of the participants were married. The mean CCI was 5.24 (SD = 1.67), and the average BMI was 34.9 (SD = 13.8). Participants reported using a variety of oral nonopioid and opioid pain medications within 24 h of the clinic visit (Table 4).

Table 3.

Personal characteristics (N = 40)

Variables	Categories/Range	N (%)	Mean (SD)	Min.–Max.
Gender	Male	18 (45.0)
	Female	22 (55.0)
Ethnicity	Non-Hispanic	38 (95.0)
	Hispanic	2 (5.0)
Race	White	35 (87.5)
	Black	5 (12.5)
	Others	0 (0.0)
Education	High school	13 (32.5)
	Some college	16 (40.0)
	College or more	11 (27.5)
Marital status	Married	23 (57.5)
	Divorce	10 (25.0)
	Widowed	3 (7.5)
	Never married	4 (10.0)
Age			70.8 (9.1)	55.0–89.0
Charlson comorbidity index			5.24 (1.67)	2–8
Body mass index			34.9 (13.8)	16.6–83.4

SD, standard deviations.

Table 4.

Oral pain medications used within 24 h before the clinic visit (N = 40)

Medication type	Generic drug	Nos. of patients prescribed (%)	Mean (SD) Frequency of pain medication use within 24 h	Min-Max of frequency
Nonopioid	Acetaminophen	14 (37)	1.60 (1.30)	0, 4
	Ibuprofen	3 (8)	1.70 (1.50)	0, 3
	Ketorolac	1 (3)	0.00 (NA)	0, 0
	Naproxen	8 (21)	0.88 (0.35)	0, 1
	Acetylsalicylic acid	3 (8)	0.70 (0.60)	0, 1
Opioid	Codeine with acetaminophen	1 (3)	0.00 (NA)	0, 0
	Tramadol	1 (3)	1.00 (NA)	1, 1
	Morphine sulfate	1 (3)	3.00 (NA)	3, 3
	Oxycodone	1 (3)	2.00 (NA)	2, 2
	Oxycodone with acetaminophen	4 (10)	3.70 (0.50)	3, 4
	Fentanyl	1 (3)	1.00 (NA)	0,1

One participant marked both Advil and Tylenol; one participant marked aspirin, Naprosyn, and Tylenol; one participant marked both aspirin and Percocet; and one participant marked both Naprosyn and Tylenol with codeine.

NA, not applicable.

Wound characteristics

Participants' wound characteristics appear in Table 5. A total of 39 (97.5%) participants were suffering from wounds located in lower legs; only one participant had a wound on the foot. The participants had wounds for an average of 340 days (SD = 521) at the time of the initial clinic visit. The mean size of the wound perimeter was 123.32 mm (SD = 91.05), area was 2633.95 mm² (SD = 8005.46), and volume was 7170.35 mm³ (SD = 29353.25).

Table 5.

Wound characteristics

Variables	Categories	N (%)	Mean (SD)	Min.–Max.
Wound locations	Lower extremity	39 (97.5)
	Foot	1 (2.5)
	Heel	0 (0.0)
Duration of wound (days)			340.12 (521.31)	23–2783
Wound perimeter (mm) (N = 38)			123.32 (91.05)	24–373
Wound area (mm2) (N = 40)			2633.95 (8005.46)	47–48,950
Wound volume (mm3) (N = 40)			7170.35 (29353.25)	3–153,781

Wound pain characteristics

Pain variables measured by PAINReportIt appear in Table 6. The variables include those that represent pain as a multidimensional variable (more than one dimension) or as a single dimension. Together, the variables characterize the CVLU pain as a multidimensional experience.

Table 6.

Wound-related pain measures²³ by PAINReportIt (N = 39)

Variables	Categories	N (%)	Mean (SD)	Min, Max
Multiple dimensions
Pain rating index	PRI-total		14.62 (9.19)	2, 42
	No. of words chosen		5.40 (2.9)	1, 13
	PRI-miscellaneous		1.41 (2.3)	0, 10
Composite pain index			19.63 (12.29)	1.38, 49.2
Sensory dimension
No. of pain sites	1	35 (89.7)
	2	1 (2.6)
	3	1 (2.6)
	4	2 (5.1)
Pain intensity	Current pain		2.9 (2.7)	0, 9
	Worst pain in last 24 h		4.8 (3.4)	0, 10
	Least pain in last 24 h		1.2 (2.2)	0, 9
Average pain intensity			2.93 (2.49)	0, 9.33
Worst toothache	0–10		8.6 (2.4)	0, 10
Worst headache	0–10		6.9 (2.6)	0, 10
Worst stomachache	0–10		5.6 (2.7)	2, 10
Pain rating index	PRI-sensory		9.46 (6.19)	0, 23
Sensory words	No. of nociceptive words		1.9 (1.6)	0, 6
	No. of neuropathic words		2.2 (1.9)	0, 3
Pain pattern	Constant	1 (2.6)
	Momentary	0 (0.0)
	Steady	6 (15.4)
	Continuous	4 (10.3)
	Intermittent	19 (48.7)
	Rhythmic	6 (15.4)
	Transient	1 (2.6)
	Brief	2 (5.1)
	Periodic	26 (66.7)
Total pattern			1.56 (1.19)	0, 4
Affective dimension
Pain rating index	PRI-affective		1.64 (1.22)	0, 4
Cognitive dimension
Pain rating index	PRI-evaluative		2.10 (1.41)	0, 5
No. of hours in past 24 that pain was less than the tolerable level	0–6 h	9 (22.5)
	7–12 h	6 (15.0)
	13–18 h	8 (20.0)
	19–24 h	17 (42.5)
Satisfaction with pain level	Yes	19 (47.5)
	No	19 (47.5)
	Not sure	2 (5.0)
Past pain treatment	No pain relief	0 (0)
	Some pain relief	25 (62)
	Good pain relief	15 (38)
Pain expectation	Worse than expected	4 (10)
	Same as expected	27 (68)
	Not bad as expected	9 (22)
Behavioral dimension
Tendency to tell others about pain	Tell others	2 (5.0)
	Keep to myself	38 (95.0)
Past pain medication use	Small amounts of pain without medicine	5 (12.5)
	Moderate amounts of pain without medicine	29 (72.5)
	Large amounts of pain without medicine	6 (15.0)

PRI, pain rating index.

Multidimensional pain variables

The mean of the PRI-T was 14.62 (range 2–42, SD = 9.19), and the mean PRI-M (1.41, range 0–10, SD = 2.3) appears in Table 6. Table 6 also displays the mean number of words chosen (5.4; range 1–13, SD = 2.9). The mean CPI was 19.63 (range 1.38–49.2, SD = 12.29).

Sensory dimension pain variables

A total of 89.7% (n = 35) of participants had one pain site among their wounds. Only 5.1% of them (n = 2) had four pain sites among their wounds (Table 6). The mean pain intensity at the time of assessment (current pain) was 2.9 (SD = 2.7). The mean of worst pain intensity in the last 24 h was 4.8 (SD = 3.4), and the least pain intensity in the last 24 h was 1.2 (SD = 2.2). The AVG-PI (the mean of pain now, pain worst, and pain least) experienced by the participants was 2.93 (SD = 2.49). In terms of past pain experiences, participants reported that their worst toothache pain previously experienced was 8.6 (SD = 2.4), worst headache was 6.9 (SD = 2.6), and worst stomachache was 5.6 (SD = 2.7) (Table 6).

The sensory quality of pain as represented by the mean PRI-S was 9.46 (range 0–23, SD = 6.19). Among descriptors endorsed, the average number of nociceptive words that participants chose was 1.9 (SD = 1.6), and the average number of neuropathic words that participants chose was 2.2 (SD = 1.9) (Table 6). The detailed frequency of pain quality descriptors appears in Table 7. Among the neuropathic descriptors, “itchy” (38.5%, n = 15) was the most frequent descriptor that participants used to describe their pain. Other neuropathic descriptors that participants selected include “shooting,” “stabbing,” “burning,” “stinging,” “aching,” “spreading,” “radiating,” “penetrating,” “tight,” “numb,” and “cold.” Among the nociceptive pain descriptors, “sharp” or “tender” (43.6%, n = 17) was the most frequent descriptor that participants used to describe their pain. Among other descriptors, “tiring” or “annoying” was the most frequent descriptor used (61.6%, n = 24, Table 7).

Table 7.

Frequency of pain quality descriptors (N = 39)

Sensory	n (%)	Affective	n (%)	Evaluativea	n (%)	Miscellaneous	n (%)
Flickering	0 (0.0)	Tiring	24 (61.6)	Annoyinga	24 (61.6)	Spreading	4 (10.3)
Quivering	0 (0.0)	Exhausting	5 (12.8)	Troublesomea	12 (30.8)	Radiating	3 (7.7)
Pulsing	3 (7.7)	Sickening	0 (0.0)	Miserablea	4 (10.3)	Penetrating	2 (5.1)
Throbbing	13 (33.3)	Suffocating	0 (0.0)	Intensea	2 (5.1)	Piercing	2 (5.1)
Beating	0 (0.0)	Fearful	1 (2.6)	Unbearablea	3 (7.7)	Tight	6 (15.4)
Pounding	5 (12.8)	Frightening	0 (0.0)			Numb	1 (2.6)
Shooting	10 (25.6)	Terrifying	0 (0.0)			Drawing	0 (0.0)
Flashing	0 (0.0)	Punishing	2 (5.1)			Squeezing	0 (0.0)
Jumping	0 (0.0)	Grueling	1 (2.6)			Tearing	0 (0.0)
Pricking	1 (2.6)	Cruel	1 (2.6)			Cool	0 (0.0)
Boring	0 (0.0)	Vicious	0 (0.0)			Cold	1 (2.6)
Drilling	0 (0.0)	Killing	1 (2.6)			Freezing	0 (0.0)
Stabbing	10 (25.6)	Wretched	0 (0.0)			Nagginga	3 (7.7)
Lancinating	0 (0.0)	Blinding	1 (2.6)			Nauseating	0 (0.0)
Sharp	17 (43.6)					Agonizing	1 (2.6)
Cutting	0 (0.0)					Dreadful	1 (2.6)
Lacerating	0 (0.0)					Torturing	0 (0.0)
Pinching	3 (7.7)
Pressing	1 (2.6)
Gnawing	0 (0.0)
Cramping	1 (2.6)
Crushing	0 (0.0)
Tugging	2 (5.1)
Pulling	2 (5.1)
Wrenching	0 (0.0)
Hot	2 (5.1)
Burning	11 (28.2)
Scalding	0 (0.0)
Searing	1 (2.6)
Tingling	4 (10)
Itchy	15 (38.5)
Smarting	0 (0.0)
Stinging	8 (20.5)
Dull	4 (10.3)
Sore	6 (15.4)
Hurting	2 (5.1)
Aching	8 (20.5)
Heavy	0 (0.0)
Tender	17 (43.6)
Taut	0 (0.0)
Rasping	0 (0.0)
Splitting	0 (0.0)

Neuropathic descriptors appear in italic font; nociceptive descriptors appear in bold font; affective descriptors appear underlined; other descriptors appear in normal font.

^aEvaluative descriptors.

A total of 66.7% (n = 26) of participants described their pain pattern as periodic, 48.7% (n = 19) as intermittent, and 15.4% (n = 6) as steady and rhythmic (Table 6). Typically, participants described their pain using multiple pain pattern descriptors like experiencing periodic and intermittent together. The mean TotPat score was 1.56 (range 0–4, SD = 1.19, Table 6).

Cognitive dimension pain variables

As shown in Table 6, the mean PRI-E was 2.1 (range 0–5, SD = 1.41) and represented the overall evaluation or appraisal of the severity of the pain. The participants described their pain goal as the average optimal pain and the average tolerable pain. The average optimal pain level was 0.6 (SD = 1.9, range 0–10), and the average tolerable pain level was 4.9 (SD = 2.64, range 0–10). A total of 42.5% (n = 17) of participants reported that their pain was less than their tolerable level for 19–24 h a day. A total of 47.5% (n = 19) of the participants were satisfied with pain level that they experienced, and the same number of participants were not satisfied with their pain level. A total of 65% (n = 25) of the participants reported that their previous pain treatments provided some pain relief. A total of 10% (n = 4) of the participants described that their experienced pain was worse than expected, and 22% (n = 9) of them described their pain as not as bad as expected (Table 6).

Affective dimension pain variables

The mean PRI-A score was 1.64 (range 0–4, SD = 1.22, Table 6). The affective descriptors that appear as part of the PRI-M (nauseating, agonizing, dreadful, and torturing) were selected rarely (Table 7).

Behavioral dimension pain variables

A total of 95% (n = 38) of participants had a tendency not to tell others about their pain, whereas only 5% (n = 2) of them tended to tell others about their pain. A total of 72.5% (n = 29) of the participants experienced moderate amounts of pain before they took medicine, whereas 15% (n = 6) of them experienced large amounts of pain before they took medication (Table 6).

Among oral nonopioid pain medications that participants reported they took within 24 h of the clinic visit, acetaminophen was most frequently taken (n = 14, 37%) among oral nonopioid pain medications, and oxycodone/acetaminophen was the opioid medication most frequently taken (n = 4, 10%, Table 4). Only nine (22.5%) of the participants reported taking an opioid for pain control (Table 4). Interestingly, the participants reported that they took pain medications on average one to three times during the 24 h before the clinic visit.

Correlations among pain variables

Results of the robust correlation analyses between the seven pain characteristics and three pain intensity variables are provided in Table 8. Correlations were weak-to-moderate in strength, ranging from 0.26 (PRI-M with Pain Now and PRI-A with Pain Least) to 0.58 (Total Pattern with Pain Now and Pain Least). Applying Jeffreys' suggested interpretation of Bayes factors,³⁹ 13 of the 21 correlations (62%) had at least very strong evidence (Bayes factor value of 30 or greater) for the existence of an association, and only two correlations (10%), PRI-M with Pain Now and PRI-A with Pain Least, demonstrated at most anecdotal evidence for an association (Bayes factor values of 1–3).

Table 8.

Estimated robust correlation coefficient, [95% highest probability density credibility interval], and {Bayes factor; % in region of practical equivalence; probability of direction} between pain variables and intensity

	Pain Now	Pain Least	Pain Worst
PRI-sensory	0.41 [0.20, 0.61] {21.6; 2.3%; 99.9%}	0.40 [0.22, 0.62] {17.4; 1.1%; 99.9%}	0.46 [0.25, 0.65] {62; 0.57%; 100%}
PRI-affective	0.33 [0.12, 0.55] {4.1; 5.9%; 98.8%}	0.26 [0.02, 0.46] {1.5; 14.2%; 96.4%}	0.32 [0.10, 0.53] {4.3; 5.3%; 98.6%}
PRI-evaluative	0.52 [0.33, 0.69] {267; 0%; 100%}	0.44 [0.24, 0.61] {35.9; 0.88%; 99.8%}	0.36 [0.13, 0.55] {6.1; 3.7%; 99.2%}
PRI-miscellaneous	0.26 [0.05, 0.50] {1.7; 13.4%; 95.0%}	0.46 [0.27, 0.65] {65.0; 0.38%; 100%}	0.33 [0.11, 0.53] {4.2; 5.4%; 98.1%}
PRI-total	0.48 [0.30, 0.67] {99.9; 0.27%; 99.9%}	0.50 [0.31, 0.68] {154; 0.20%; 100%}	0.50 [0.31, 0.68] {151; 0.07%; 100%}
Number of words chosen	0.54 [0.36, 0.71] {650; 0.15%; 99.9%}	0.51 [0.33, 0.68] {185; 0.52%; 100%}	0.54 [0.34, 0.69] {432; 0.20%; 100%}
Total pattern	0.58 [0.40, 0.73] {>1000; 0.38%; 100%}	0.58 [0.41, 0.74] { > 1000; 0%; 100%}	0.50 [0.30, 0.66] {140; 0.38%; 100%}

Bayes factor is $\frac{P\left\{Data|Correlation\ne 0\right\}}{P\left\{Data|Correlation=0\right\}}$. ROPE defined as −0.05 to 0.05 for correlation coefficients.

ROPE, region of practical equivalence.

Table 9 provides the results of the correlation analyses among the seven pain variables. Correlation coefficients ranged from 0.21 (PRI-M with PRI-A) to 0.96 (Number of Words Chosen with PRI-T). Fourteen of the 21 correlations (67%) had at least very strong evidence (Bayes factor value of 30 or greater) for the existence of an association, whereas only the correlation between PRI-M and PRI-A failed to provide even anecdotal evidence for the presence of an association.

Table 9.

Estimated robust correlation coefficient, [95% highest probability density credibility interval], and {Bayes factor; % in region of practical equivalence; probability of direction} among pain variables

	PRI-Sensory	PRI-Affective	PRI-Evaluative	PRI-Miscellaneous	PRI-Total	NWC
PRI-affective	0.40 [0.18, 0.59] {13.8; 2.5%; 99.7%}
PRI-evaluative	0.34 [0.14, 0.56] {5.1; 4.5%; 99.2%}	0.42 [0.22, 0.61] {23.9; 0.95; 99.8%}
PRI-miscellaneous	0.47 [0.27, 0.65] {61.8; 0.68%; 99.6%}	0.21 [−0.04, 0.42] {1.0; 20.3%; 90.8%}	0.32 [0.09, 0.53] {3.9; 6.9%; 98.2%}
PRI-total	0.93 [0.89, 0.96] {>1000; 0%; 100%}	0.50 [0.32, 0.69] {150; 0%; 100%}	0.52 [0.35, 0.69] {239; 0%; 100%}	0.61 [0.45, 0.76] {>1000; 0%; 100%}
Number words chosen	0.91 [0.87, 0.95] {>1000; 0%; 100%}	0.54 [0.37, 0.71] {565; 0.07%; 100%}	0.53 [0.35, 0.71] {309; 0%; 100%}	0.55 [0.36, 0.70] {616; 0%; 100%}	0.96 [0.95, 0.98] {>1000; 0%; 100%}
Total pattern	0.43 [0.24, 0.63] {27.1; 1.2%; 100%}	0.38 [0.17, 0.57] {11.1; 2.2%; 99.5%}	0.44 [0.23, 0.63] {35.7; 1.3%; 99.9%}	0.54 [0.35, 0.69] {311; 0.3%; 100%}	0.54 [0.37, 0.71] {512; 0.1%; 100%}	0.51 [0.35, 0.69] {257; 0%; 100%}

Bayes factor is $\frac{P\left\{Data|Correlation\ne 0\right\}}{P\left\{Data|Correlation=0\right\}}$. ROPE defined as −0.05 to 0.05 for correlation coefficients.

NWC, number of words chosen.

Discussion

Pain is a complex and multidimensional phenomenon. In this study of patients with CVLU, we examined their pain characteristics with PAINReportIt, a multidimensional pain measure, to describe the pain characteristics of CVLU. To the best of our knowledge, this study is the first to describe the sensory, affective, cognitive, and behavioral pain dimensions among patients with CVLU. In this sample with pain of CVLU in the mild-to-moderate intensity levels, the bivariate correlations between the various pain dimension scores reflected those expected based on their theoretical and structural basis. There were moderate-to-strong correlations between pain variables and between sensory dimension variables and PRI-E. Weak-to-moderate correlations were observed between PRI-A and other dimensions. These correlations are consistent with those observed in a variety of pain conditions such as cancer and low back pain.^40,41

Sensory dimension of pain

To fully describe the sensory dimension of pain, pain locations, intensity, quality, and pattern should be addressed. Since the majority of pain assessment utilizes numeric rating scales in practice, pain quality descriptors and patterns are rarely addressed in CVLU. In this study, we measured all sensory dimensions of pain in patients with CVLU.

Our study demonstrated that patients experienced, on average, mild-to-moderate pain intensity (2.93, SD = 2.49). Pain intensity is the most frequently described pain characteristic in studies involving CVLU.¹ Our findings for pain intensity are consistent with a current meta-analysis that patients experienced mild-to-moderate wound-related pain.¹ However, those studies measured pain in a manner different than our multidimensional evaluation. We measured pain intensity using current, least, and worst pain over 24 h and calculated the average of pain intensity from those values. In other studies, a point estimate was used, with pain intensity simply measured at the time of being asked, regardless of the time window. That point estimate provides an incomplete assessment of the pain experience. To more fully understand patient pain experience, clinicians need to incorporate measures that include a time window. Pain intensity with time window will help in determining frequency of pain treatment regimens.

In this study, we found that patients likely experience both nociceptive and neuropathic pain from venous leg ulcers. Participants used 1.9 nociceptive pain descriptors and 2.2 neuropathic descriptors to describe their pain. Within the pain descriptors, words that participants used most frequently were itchy, sharp, tender, annoying, and tiring, whereas in other studies, common pain descriptors were aching, stabbing, sharp, tender, nagging, throbbing, and tiring.^42,43 Findings suggest that the CVLU population may suffer neuropathic pain,⁴⁴ which is consistent with other studies that have examined pain quality. Pain mechanisms differ between neuropathic and nociceptive pain. Neuropathic pain is caused by conditions affecting the somatosensory system,^45,46 whereas nociceptive pain is caused by potential or actual tissue damage.⁴⁷ When addressing pain quality, it is important to choose a pain medication regimen that aligns with the pain mechanism. In addition, considering the nature of existing multiple comorbidities in patients with CVLU, treatment decisions regarding pain medication regimens should be established following careful and thorough assessment of pain and the potential contraindicated pain treatments given for comorbidities.

In our study, we found that 48.7% of participants experienced intermittent pain from CVLU, which was the most used pain pattern descriptor among participants. There is only one study that described the pain pattern and associated factors in CVLU. Goto et al. found that pain pattern was continuous or intermittent, which was inversely associated with nerve growth factor concentration in wound fluid.⁴⁸ Since pain pattern helps determine the interval for analgesics for pain relief and the appropriate times to introduce other treatments, assessing pain pattern is important for pain management.

Cognitive dimension of pain

Participants in this study reported, on average, that a tolerable pain goal was 4.9 (0–10 scale). Half of participants were not satisfied with pain experienced at the time of answering, and 72.5% of them experienced moderate pain without medication in the past. To the best of our knowledge, this study is the first study that describes the cognitive dimension of pain in CVLU. These results demonstrated that current pain management in CVLU does not fully meet individuals' pain goals. Even though patients with CVLU reported willingness to tolerate a relatively high level of pain (4.9, SD = 2.64) and nearly 80% of them experienced more or the same amount of pain than they expected, half were not satisfied with their pain level. Assessment of the cognitive dimension is important for understanding pain from a holistic perspective. Beliefs, attitudes, expectations, and past experiences about pain affect pain perception and individuals' response to pain therapy. Therefore, to achieve the most effective pain treatment, clinicians need to include an assessment of cognitive dimensions of pain and be aware of patients' needs for pain management.

In our study, patients with CVLU tended to accept pain from wounds and reported that previous pain treatments were partially helpful to control their pain. A total of 15% of participants reported that pain was relieved by previous pain treatment, whereas 62% reported that only some pain was relieved by previous pain treatment, indicating only partial effectiveness of pain treatment. A total of 68% of participants reported that pain is the same as they expected, which means that participants recognize that wounds are painful.

Affective dimension of pain

We found minimal contribution of the affective pain dimension to the pain of CVLU. The mean and range of PRI-A scores were relatively low in comparison to other pain conditions.⁴⁹ Although the pain was fatiguing as indicated by frequent selection of tiring and exhausting, other affective descriptors were never or rarely selected. Pain and fatigue are a well-known symptom cluster in other pain populations.⁵⁰ Nearly one-fourth (23%) of the participants appraised their pain severity as miserable, intense, or unbearable, and they are at risk for negative emotions, such as anxiety, fear, and anger.

Negative emotions affect unrelieved pain and stimulate the sympathetic nervous system, which releases norepinephrine and results in increased nociceptive and neuropathic pain intensity. Another affective condition, depression, is associated with increased pain intensity. Patients with pressure ulcers who have more depression also experienced more severe pain intensity.^51,52 However, the associations between depressive symptoms and other negative emotions with pain experience have never been examined among the CVLU population. Examination of potential associations between the affective dimension of pain and negative emotions may provide information to better design interventions to reduce pain. Further study is needed to examine treatment effectiveness related to participants' negative emotions (e.g., depression and anxiety). If clinicians provide emotional support and an appropriate pain regimen, treatment may be more successful in controlling pain. PAINReportIt provides some but limited indicators of the affective dimension of pain. It, however, could be used to screen for those at risk for affective dimension issues and the need for additional measures, such as catastrophizing, depressive symptoms, and anxiety scales, to better inform treatment planning.

Behavioral dimension of pain

In this study, 95% of participants tended not to tell others about their pain; most of them kept their pain to themselves. Stoicism about pain is common among the elderly and has been associated with resilience in coping with pain.⁵³ Tendency not to tell others about pain is also associated with mild-to-moderate pain but as pain intensity increases in severity, the behavior tendency changes to telling others about the pain.⁵⁴ Health care providers should actively query patients about their pain experience and be vigilant regarding verbal and behavioral clues rather than assuming that they will volunteer information about pain.

Participants with CVLU engaged in behaviors to control pain by taking their pain medication, which is appropriate for self-management of pain to their tolerable levels. They took their medications typically once or twice a day, but some participants reported taking the medications three or four times in the previous 24 h. The pattern of analgesic use appears to be safe except for one person who reported taking aspirin and a nonsteroidal anti-inflammatory drug (NSAID), which is not recommended due to potential for side effects. Nociceptive pain usually responds to acetaminophen, NSAIDs, or opioids depending on severity, whereas neuropathic pain responds to adjuvant drugs such as tricyclic antidepressants, anticonvulsants, neuroleptics, clonidine, and baclofen. Since participants with CVLU may experience both nociceptive and neuropathic pain, clinicians should establish individuals' pain regimens corresponding to individuals' pain characteristics, including patients' comorbidities.

Multidimension of pain

The study findings depicted multidimensional pain phenomena experienced from patients with CVLU that have never been described in this population. Although the study characterized sensory, cognitive, behavioral, and affective dimensions of pain, describing affective dimension of pain was limited due to a lack of indicators related to the affective dimension in PAINReportIt. Affective dimension issues have a significant role in patients with venous leg ulcers (VLUs) and it has been addressed in a few studies. The odds of depression was 2.53 (95% CI 5 [1.26–5.08]) when patients with VLUs experienced pain.⁵⁵ In addition, negative symptoms (e.g., depression and anxiety) are associated with nonhealing wound in CVLUs.⁵⁶ Well-described multidimensional pain may enable clinicians to establish better treatment plans to reduce pain and facilitate wound healing for this population. To elaborate affective dimension of pain in this population, further studies are needed that describe the affective dimension of pain and examine the effects of treating negative emotions on pain control.

Innovation

Pain characteristics experienced by the CVLU population have never been described through a multidimensional lens. We described the four dimensions of pain characteristics assessed by PAINReportIt. The CVLU population experiences moderate and intermittent pain, both nociceptive and neuropathic, and they tend to be willing to tolerate relatively high levels of pain but experience pain levels not satisfactory to them. However, these patients tend to expect pain from wounds and experience previous pain treatment as partially helpful to control pain. Therefore, clinicians need to assess their pain thoroughly with regard not only to pain intensity but also pain location, quality, and pattern, as well as cognitive, behavioral, and affective dimensions of pain to provide effective pain management.

Key Findings

• The AVG-PI with current, least, and worst pain in 24 h is mild-to-moderate (2.93, SD = 2.49) in CVLU patients.

• Throbbing, itchy, sharp, tender, annoying, and tiring are the most frequently used pain descriptors in CVLU patients.

• Patients with CVLU report willingness to tolerate a relatively high level of pain, but half are not satisfied with their experienced pain intensity. A total of 95% of patients with CVLU tend not to express their pain to others.

• Patients with CVLU tend to accept pain from wounds and reported that previous pain treatment is partially helpful to control their pain.

Abbreviations and Acronyms

ABI

ankle brachial index

ABPI

ankle brachial pressure index

AVG-PI

average pain intensity

BMI

body mass index

CCI

Charlson comorbidity index

CI

confidence interval

COPD

chronic obstructive pulmonary disease

CPI

composite pain index

CVLU

chronic venous leg ulcer

MMSE

mini-mental state examination

NSAID

nonsteroidal anti-inflammatory drug

PRI-A

pain rating index-affective

PRI-E

pain rating index-evaluative

PRI-M

pain rating index-miscellaneous

PRI-S

pain rating index-sensory

PRI-T

pain rating index-total

ROPE

region of practical equivalence

SD

standard deviations

TotPat

total of pain pattern score

VLUs

venous leg ulcers

Author Disclosure and Ghostwriting

All authors declared no conflict of interest. J.K., D.J.W., and J.S. conceived the idea and wrote the article for the review. All authors wrote, critically reviewed, and revised the article. No ghostwriters were used to write this article.

About The Authors

Junglyun Kim, PhD, is an Assistant Professor at the Chungnam National University College of Nursing in the South Korea and a Courtesy Assistant Professor at the University of Florida College of Nursing. Dr. Kim has extensive clinical experience in chronic wounds and knowledge in biobehavioral symptom science. Diana J. Wilkie, PhD, is a Professor and the Prairieview Trust—Earl and Margo Powers Endowed Professor at the University of Florida College of Nursing. Michael Weaver, PhD, is Professor and Associate Dean for Research at the University of Florida College of Nursing. Debra Lyon, PhD, is a Professor and the Kirbo Endowed Chair and Executive Associate Dean of Biobehavioral Nursing Science of the University of Florida College of Nursing. Debra L. Kelly, PhD, is an Associate Professor and Associate dean for academic affairs at the University of Florida College of Nursing. Susan B. Millan, MD, is a family medicine specialist at the University of Florida Health Wound Care and Hyperbaric Center. Jungmin Park, RN, is a Research Coordinator at the University of Florida College of Nursing. Joyce Stechmiller, PhD, is a Professor at the University of Florida College of Nursing. Dr. Stechmiller has extensive experience and expertise in wound science, with a special emphasis on biobehavioral approaches to enhancing wound healing.