Patient factors associated with activation level in peripheral artery disease

Abstract

Introduction:

As a chronic and incurable condition, lower extremity peripheral artery disease (PAD) and its optimal self-management requires patient participation in treatment. Patient activation (knowledge, skills, and confidence to manage one’s health) is known to improve chronic disease outcomes. We aimed to identify factors associated with activation in patients with PAD.

Methods:

In this single-center study, participants with PAD completed a survey assessing demographics, activation, PAD knowledge, and functional health literacy (FHL). The primary outcome, activation, was measured by the Patient Activation Measure (PAM-13). The PAD knowledge score was the percentage of correct responses, and FHL was assessed using the Short Test of Functional Health Literacy in Adults (S-TOFHLA). Bivariable analysis and logistic regression identified factors associated with activation.

Results:

Of the 91 participants (49.5% women, mean ± SD age: 68.6 ± 11.9 years, 29.7% Black), 72.6% were activated, 78.7% demonstrated adequate FHL, and the mean knowledge score ± SD was 79.1% ± 13.3%. White race (p = 0.025), higher income (p = 0.015), ability to ambulate (p = 0.023), and increased knowledge score (p = 0.002) were associated with activation in bivariable analyses. In a logistic regression model, younger age (p = 0.029), higher income (p = 0.016), and higher knowledge score (p = 0.012) independently correlated with odds of greater activation.

Conclusions:

Many participants were activated, demonstrated adequate FHL, and scored well on the PAD knowledge test. The remaining 27.5% were inactivated, which was associated with poor PAD knowledge and certain demographic characteristics. Future studies should focus on developing and implementing patient-centric educational interventions for inactivated patients and strategies to increase activation.

Keywords

chronic disease health literacy patient activation patient-centered care peripheral artery disease (PAD)self-management

Introduction

Lower extremity peripheral artery disease (PAD) is a chronic and incurable condition that affects an estimated 21 million Americans and 230 million people worldwide.^1,2 The clinical presentation of PAD is heterogeneous and can vary from exertional leg pain to tissue loss and gangrene, also called chronic limb-threatening ischemia (CLTI).³ PAD is associated with twofold increased risks of stroke, myocardial infarction, and 10-year mortality.^4,5 Successful management and prevention of disease progression relies upon adoption and continued adherence to risk-modifying behaviors, such as compliance with guideline-directed medical therapy and walking therapy.^6,7

Effective management of chronic diseases such as PAD requires patient activation, or the knowledge, confidence, and skills to engage in the management of one’s health.^8,9 Activation has been studied in patients with chronic illnesses such as diabetes, metabolic syndrome, cancer, and chronic kidney disease.^10
–13 More highly activated participants have been shown to be more likely to engage in health-promoting behaviors and adhere to treatment regimens.^14
–16 Activation has also been shown to be modifiable, and interventions that increase activation have resulted in improved health outcomes.^17
–19

Health literacy also influences outcomes and is a predictor of understanding and using information for health choices.²⁰ Health literacy has been classified into three different levels with progressively increasing autonomy and empowerment for the patient.²¹ The first level is functional health literacy (FHL), where one can apply basic literacy skills to health-related materials.²² Interactive health literacy refers to one’s ability to understand multiple forms of communication and apply information. Critical health literacy is the ability to critically analyze information and work towards exerting control over life events and situations.^21,23,24 Assessing FHL will allow clinicians to determine patient ability to learn and tailor education about disease processes. To our knowledge, few studies have examined FHL and the association with activation level among patients with PAD.

Though activation and its promise for attenuating quality of life outcomes has been studied in other chronic diseases,²⁵ the degree of activation among patients with PAD is largely unknown. Furthermore, the relationships between activation, health literacy, and knowledge of PAD are unclear. The goals of this study are to quantify the prevalence of activation among patients with an established diagnosis of PAD and to identify the patient factors associated with activation. We hypothesized that activation levels of patients with PAD would correlate with their level of PAD knowledge, FHL, and sociodemographic factors.

Methods

Data source

This is a single-center cross-sectional study of adults with an established diagnosis of PAD who were recruited from a single vascular surgery practice between June 2023 and March 2024. The protocol was approved by the Northwestern University Institutional Review Board. All participants provided written informed consent prior to study participation. Data has been anonymized and participants were aware that data would be published.

Study population

Patients with a documented diagnosis of PAD who were treated as inpatients at Northwestern Memorial Hospital for PAD-related problems or the outpatient vascular clinic were eligible for inclusion. Participants were excluded if they were under 18 years of age, unable to provide written informed consent, or were not able to read English at the sixth grade reading level (Figure 1).

Figure 1.

CONSORT diagram illustrating participant selection.

Survey development

A paper survey was developed by a multidisciplinary team of vascular surgeons, health education experts, and a psychometrician. Demographic questions were developed with choices based on terminology used in the US Census.²⁶ The survey had a total of 45 questions, with 43 multiple-choice and true/false questions written at a sixth-grade reading level evaluating PAD knowledge and two questions on awareness of PAD diagnosis. Of the 43 knowledge questions, there were 33 questions on risk factors for and outcomes of PAD²⁷ and 10 questions on the clinical presentation and management of PAD. These 45 questions were placed at the beginning of the survey to ensure the maximum attentiveness from participants and therefore obtain an accurate representation of their knowledge. Validated measures of patient activation, using the Patient Activation Measure (13 items, PAM-13),⁹ and FHL, using the Short Test of Functional Health Literacy in Adults (36 items, S-TOFHLA),²⁸ were also administered. The survey was tested in a pilot group of adults with PAD for readability, clarity, and appropriateness. The survey was revised, based on feedback, to its final form (Supplemental data).

Primary outcome

The primary outcome was a binary classification of patient activation status as either ‘activated’ or ‘inactivated.’ Responses to the PAM-13 were scored using the validated assessment’s scoring instructions as one of four levels of activation.^9,29 Level 1 is the lowest level of activation (disengaged and overwhelmed); level 2 indicates passivity in care (becoming aware but still struggling); level 3 participants are beginning to understand their disease and build skills (taking action and gaining control); and level 4 participants take responsibility for their health (maintaining behaviors and pushing further).³⁰ Activation levels were then dichotomized into two classes, as previously reported.^31
–34 Level 1 or level 2 were classified as ‘inactivated’ and level 3 or level 4 were classified as ‘activated.’

Independent variables

Awareness of the diagnosis of PAD was evaluated with two questions: (1) ‘Do you have peripheral artery disease, sometimes known as “PAD” or “PVD”?’ and (2) ‘Do you have blockages or narrowing in the blood vessels to your legs?’ Awareness of PAD diagnosis was defined by affirmative responses to both questions.

The PAD knowledge score was based on the 43 PAD knowledge questions and calculated as the percentage of correct responses.

The S-TOFHLA was categorized as 0–16, 17–22, and 23–36 (out of 36) correct responses, which correspond to ‘inadequate,’ ‘marginal,’ and ‘adequate’ FHL, respectively.²⁸ Participants who scored as ‘inadequate’ or ‘marginal’ were grouped as ‘poor’ FHL for analysis.

Demographics, including sex, age, race and ethnicity, marital status, income, highest education level, smoking history, and chronicity of PAD diagnosis were self-reported. Other self-reported variables were living status, defined as the type of primary residence, and ambulation status, defined by the ability to ambulate unassisted.

Medical and vascular surgery history and medications at the time of study enrollment were obtained from the electronic health record. The comorbidity-polypharmacy score was calculated as the sum of the number of daily medications and the number of known comorbidities.^35,36

Statistical analysis

Bivariable analysis was used to assess the relationship between independent variables and the primary outcome. Chi-squared tests were used to test the association between categorical variables and the primary outcome, and two-sample t-tests or Pearson correlation coefficients were used for continuous variables. A multivariable logistic regression analysis was used to assess the relationship between activation and PAD knowledge scores while controlling for demographic, socioeconomic, and other patient variables. Statistical significance was defined as p < 0.05. Analyses were completed using Stata SE version 18.0 (College Station, TX, USA).

Results

Ninety-one participants (mean ± SD age: 68.6 ± 11.9 years, 49.5% women and 45.1% non-White individuals) completed the survey. The participation rate was 77.1%. Most participants (75.6%, n = 68) were aware of the diagnosis of PAD and many (55.0%, n = 50) reported that they have had PAD for less than 5 years. All characteristics are shown in Table 1.

Table 1.

Baseline participant characteristics (N = 91).

	Value
Female sex	45 (49.5)
Age (years), mean ± SD	68.6 ± 11.9
Race
White	50 (55.0)
Black or African American	27 (29.7)
Asian or Asian American	3 (3.3)
American Indian or Alaska Native	2 (2.2)
Other	8 (8.8)
Prefer not to answer	1 (1.1)
Hispanic ethnicity	7 (7.7)
Marital status
Married	42 (46.2)
Single/widowed/divorced/other	49 (53.9)
Living status
Home	87 (95.6)
Assisted living, nursing home, or other	4 (4.4)
Caregiver
Independent (no caregiver)	60 (65.9)
Any caregiver	31 (34.1)
Education attained
Less than a high school degree or equivalent or prefer not to answer	8 (8.8)
High school graduate	16 (17.6)
Some college but not a college degree	27 (29.7)
College degree or more	40 (44.0)
Annual household income
Unsure or prefer not to answer	21 (23.1)
< $49,000	32 (35.2)
$50,000 – $100,000	19 (20.9)
> $100,000	19 (20.9)
Smoking status
Former smoker	51 (56.0)
Current smoker	13 (14.3)
Never smoker	27 (29.7)
Ambulatory status
Ambulates independently	53 (58.9)
Ambulates with walker	24 (26.7)
Cannot ambulate	13 (14.4)
Chronicity of PAD diagnosis^a
Not sure	6 (6.7)
I do not think I have PAD	7 (7.8)
< 5 years	50 (55.0)
> 5 years	27 (29.7)
Aware of PAD diagnosis	68 (75.6)
PAD presentation
Asymptomatic	12 (13.2)
Claudication	32 (35.2)
CLTI	47 (51.7)
Endovascular leg revascularization	61 (67.0)
Open leg revascularization	32 (35.2)
Hybrid leg revascularization	11 (12.1)
Minor amputation^b	20 (22.0)
Major amputation^c	16 (17.6)
Diabetes mellitus	53 (58.9)
Hypertension	79 (86.8)
Chronic kidney disease or end-stage renal disease	18 (19.8)
Stroke	20 (22.2)
Coronary artery disease	36 (39.6)
Body mass index (kg/m²), mean ± SD	27.0 ± 5.5
CPPS, mean ± SD	20.8 ± 7.8

Data are expressed as n (%) unless otherwise stated.

n = 90.

Minor amputation includes toe, ray, or transmetatarsal amputation.

Major amputation includes below knee, through knee, or above knee amputation.

CLTI, chronic limb-threatening ischemia; CPPS, Comorbidity-Polypharmacy Score; PAD, peripheral artery disease.

The median FHL score was 33 (IQR = [27, 35]) out of a maximum score of 36. Most participants (78.7%, n = 70) received an ‘adequate’ FHL score, but 20.1% (n = 19) received a score of ‘inadequate’ or ‘marginal,’ indicating poor FHL. As shown in Figure 2A, the PAD knowledge scores were skewed with a median of 79.1% (IQR = [72.1, 83.7]).

Figure 2.

(A) Histogram of peripheral artery disease knowledge test scores, defined as the percentage of correctly answered knowledge questions. (B) Participant activation levels as determined by the 13-item Patient Activation Measure (PAM-13) score. PAM-13 levels 1 and 2 are classified as ‘inactivated’ and levels 3 and 4 are classified as ‘activated.’

The median activation score was 70.2 (IQR = [53.2, 84.8]) out of a maximum of 100 (Figure 2B). There were four participants (4.4%) who scored as a level 1, 21 (23.1%) who scored as a level 2, 23 (25.3%) who scored as a level 3, and 43 (47.3%) who scored as a level 4. After dichotomizing participants based on activation levels, 72.6% (n = 66) were classified as activated and 27.4% (n = 25) were classified as inactivated.

The bivariable analysis of activation is shown in Table 2. There were significant associations between activation and race, income, knowledge scores, and ambulation. The multivariable logistic regression analysis is shown in Table 3. Activation was significantly correlated with PAD knowledge score (odds ratio [OR] 1.2, p = 0.012), income less than $49,000 (OR 0.06, p = 0.016), and age (OR 0.94, p = 0.029) after controlling for race, chronicity of PAD diagnosis, and FHL. Each additional correct response on the PAD knowledge questions is associated with 20% increased odds of being activated. An increase in age by 1 year is associated with 6% decreased odds of activation. When compared to participants with a self-reported household income of greater than $100,000 per year, participants who reported annual household incomes of less than $49,999 were 94% less likely to be activated. There were no significant differences in activation status by race, chronicity of PAD diagnosis, or FHL.

Table 2.

Bivariable analysis of associations between activation and study measures.

Baseline characteristics	Activated(n = 66)	Inactivated(n = 25)	p-value
Female sex	34 (51.5)	11 (44.0)	0.52
Age (years), mean ± SD	67.4 ± 1.5	71.8 ± 2.2	0.11
Non-White race	25 (37.9)	16 (64.0)	0.025
Hispanic ethnicity	6 (9.1)	1 (4.0)	0.42
Married	34 (51.5)	8 (32.0)	0.096
Lives at home	64 (97.0)	23 (92.0)	0.30
College degree or more	30 (45.5)	10 (40.0)	0.64
Annual household income
Unsure or prefer not to answer	14 (21.2)	6 (25.0)	0.015
< $49,999	18 (27.3)	14 (58.3)
$50,000–100,000	16 (24.2)	3 (12.5)
> $100,000	18 (27.3)	1 (4.2)
Smoking status
Former smoker	37 (56.1)	14 (56.0)	0.49
Current smoker	11 (16.7)	2 (8.0)
Never smoker	18 (27.3)	9 (36.0)
CPPS, mean ± SD	20.8 ± 7.5	20.96 ± 8.6	0.93
Knowledge and literacy
Knowledge score (%), mean ± SD	78.1 ± 1.5	68.6 ± 2.8	0.0016
Functional health literacy
Poor	12 (18.5)	7 (29.2)	0.27
Adequate	53 (81.5)	17 (70.8)
Aware of PAD diagnosis	51 (78.5)	17 (68.0)	0.30
PAD history
Ambulatory status
Ambulates independently	7 (10.8)	6 (24.0)	0.023
Ambulates with walker	14 (21.5)	10 (40.0)
Cannot ambulate	44 (67.7)	9 (36.0)
Chronicity of PAD diagnosis
Not sure	4 (6.2)	2 (8.0)	0.80
I do not think I have PAD	4 (6.2)	3 (12.0)
< 5 years	37 (56.9)	13 (52.0)
> 5 years	20 (30.8)	7 (28.0)
PAD presentation
Asymptomatic	10 (15.2)	2 (8.0)	0.16
Claudication	26 (39.4)	6 (24.0)
CLTI	30 (45.5)	17 (68.0)
Endovascular leg revascularization	40 (60.6)	21 (84.0)	0.034
Open leg revascularization	23 (34.9)	9 (36.0)	0.92
Hybrid leg revascularization	8 (12.1)	3 (12.0)	0.99
Lower-extremity amputation	17 (25.8)	11 (44.0)	0.092

Data are expressed as n (%) unless otherwise stated.

Bolded p-values represent significance < 0.05.

CLTI, chronic limb-threatening ischemia; CPPS, Comorbidity-Polypharmacy Score; PAD, peripheral artery disease.

Table 3.

Multivariable logistic regression of associations with activation.

Variable	Odds ratio	95% CI	p-value
Non-White race	0.43	0.1–2.0	0.28
Age	0.94	0.89–0.99	0.029
Annual household income
Unsure/prefer not to answer	0.34	0.03–4.1	0.39
< $49,999	0.06	0.01–0.6	0.016
$50,000–100,000	0.32	0.02–4.1	0.38
$100,000	Ref.
Chronicity of PAD diagnosis
Not sure	19.6	0.5–792.7	0.12
< 5 years	1.4	0.4–5.6	0.62
> 5 years	Ref.
I do not think I have PAD	1.4	0.1–14.4	0.76
Number of correct responses on PAD knowledge questions	1.2	1.0–1.4	0.012
Functional health literacy
Poor	4.4	0.8–25.0	0.092
Adequate	Ref.

Bolded p-values represent significance < 0.05.

PAD, peripheral artery disease.

Discussion

In this single-center study of participants with PAD who were referred to a vascular surgeon, 72.5% of participants were classified as activated based on the PAM-13 score, and activation status was independently associated with PAD knowledge and income and inversely associated with age (see graphical abstract in supplemental material).

Activation in chronic illnesses is associated with improved treatment adherence, self-monitoring, and regularity of medical care.^14,15,37 Poorly activated patients are more likely to have unmet medical needs, delays in medical care, and are less likely to seek out health information.^16,17,38 Low activation is also associated with increased healthcare costs both for individual patients and on the larger health care system.⁸ When considered along with other data showing improved outcomes and better reported care experiences for patients with high activation levels,²⁵ assessing activation is a first step in the goal of increasing patient engagement. This step is especially compelling because patient-centered care, measured by patient-reported outcomes, is considered a fundamental aspect of healthcare.³⁹

Activation in patients with PAD is poorly understood. In a single-center study of patients attending outpatient vascular surgery clinic that included 29 patients with CLTI, Humphries et al. found that activation was high, with 66% of patients with CLTI scoring as activation level 3 or 4, which was not associated with demographic factors.⁴⁰ However, poorly activated patients may not have responded to the voluntary survey, potentially skewing the observed activation towards a higher level. Health literacy and PAD knowledge were also not assessed. Though we found comparable overall rates of activation in our study of people with an established diagnosis of PAD, we found that activation was inversely associated with age and positively associated with PAD knowledge but not FHL.

The inverse association of age with activation after controlling for race, income, chronicity of PAD diagnosis, knowledge score, and FHL is important because PAD prevalence increases with age. Older patients are also more likely to have multiple comorbidities that require management.⁴¹ The association of age and activation status has been investigated previously by Chubak et al., where activation in a cohort of patients with diabetes or heart disease was measured at baseline and then 1 year later.⁴² Patients who were older than 75 years were more likely to have lower activation levels at baseline and to have a decrease in activation level after 1 year. Blakemore et al. also demonstrated that older age was associated with lower patient activation among adults in the United Kingdom with multiple comorbidities.⁴³ Thus, older patients may represent a subset of all patients with PAD who are at risk of low activation and would potentially benefit from more frequent monitoring or additional interventions to increase engagement in the treatment plan.

Our finding that disease-specific knowledge is associated with activation has also been demonstrated in other chronic diseases. Hendriks et al. found that patients with diabetes who knew what type of diabetes they had, the possible side effects of their medications, and how to treat hyperglycemia were more likely to have higher levels of activation than those who scored poorly on diabetes knowledge questions.¹³ Similarly, increased disease knowledge and understanding has been associated with higher activation in studies of patients with hypercholesterolemia and cancer.^44,45 There are, however, examples of chronic diseases where activation and disease knowledge are not related. A study of patients with heart failure found that knowledge was not associated with activation levels, and that activation levels were more influential on self-care than knowledge.⁴⁶ As there are multiple treatment options for PAD depending on symptoms and functional status, including medications, walking therapy, and invasive procedures,⁴⁶ adequate knowledge of PAD will allow patients to participate in shared decision-making (SDM) and understand treatment goals.⁴⁷

Several studies have investigated the relationship between number of comorbidities and activation. As patients age and prevalence of dementia increases, the decrease in cognitive function may affect self-management of comorbidities.⁴⁸ In our study, participants had an average of nine chronic medical conditions, including PAD (Table 1), and there was no association between the number of comorbid conditions with activation (Table 2). In contrast, others have found that activation³¹ and self-management⁴⁹ are inversely related to the number of comorbidities. Additionally, having risk factors for cardiovascular disease was associated with decreases in activation level. In a study of patients with multiple chronic conditions, Bos-Touwen et al. found lower activation levels among patients with higher comorbidity indices.⁵⁰ Notably, the associations of age, education level, body mass index, financial distress, and illness perception on activation status were independent of disease process, suggesting that most factors influencing activation have consistent effects across different diseases.

Contrary to our initial hypothesis, we did not find a significant association between FHL and activation. In a 2007 study, Hibbard et al. investigated the association of health literacy, numeracy, and activation with the comprehension of hospital performance reports and making an informed health care choice.⁵¹ After showing participants hospital performance data that included quality of care and cost assessments, they found FHL and numeracy to be stronger predictors of comprehension than activation and there was low correlation between FHL and activation. However, among those with low FHL, having higher activation levels correlated with better comprehension and choices. Nijman et al. also found activation to be a stronger predictor than FHL for seeking and using health information.⁵² These findings suggest that improving PAD knowledge, regardless of FHL, may be a requisite component of strategies to improve activation among people with PAD, but these educational strategies may need to be tailored toward specific levels of FHL.

Activated patients have better health outcomes and report more positive care experiences.^8,15,37 Our study demonstrates that activation status is an important patient factor in the management of patients with PAD. Patients who are activated may have a different phenotype than clinicians expect, as they may not demonstrate high levels of FHL. Conversely, poorly activated patients may have high FHL. We found no association between activation status and chronicity of PAD diagnosis or PAD symptoms, and therefore clinicians should not assume that patients who have more severe symptoms or a long history of PAD will be more engaged in their treatment plan.

Activation can be determined relatively quickly by administering the PAM-13, which takes roughly 5 minutes to complete and is validated in multiple languages.³⁰ Assessing activation level at all stages of PAD may help to identify individual patient needs, which may be dynamic over time. Whereas highly activated patients may benefit from SDM in PAD management, poorly activated patients may require intensive PAD education, coaching, and confidence-building before they can be expected to participate meaningfully in their treatment plan or SDM. The United States Preventive Services Task Force has included SDM in many of their recommendations.⁵³ The SHARE Approach, developed by the Agency for Healthcare Research and Quality, outlines a five-step process for SDM between clinicians and patients to promote meaningful conversation about a patient’s goals.⁵⁴ These steps are to (1) seek patient participation, (2) help the patient explore treatment options, (3) assess patient values and preferences, (4) reach a decision together, and (5) evaluate the decision. SDM is encouraged in clinical treatment paradigms for CLTI, with the 2020 Global Vascular Guidelines providing direction for evidence-based leg revascularization.⁵⁵ In this framework, vascular surgeons are encouraged to participate in SDM to determine suitability of revascularization.⁵⁶ Activation is a prerequisite to the widespread adoption of these frameworks in a patient-centered way. Among 1222 adults with diabetes and cardiovascular disease, patient activation is associated with patients’ experience of SDM over 1 year, and the relationship between activation and SDM experience is dominated by baseline patient activation.⁵⁷ Our findings that older adults and patients with less PAD knowledge may have lower activation suggest that interventions targeting knowledge and activation will help them benefit from SDM.

The development of strategies to improve patient knowledge of PAD will require further investigation with large-scale implementation and testing, and our findings suggest initial steps for practitioners who want to improve patient activation. A first step is to screen for patient activation level. Next steps are to identify individualized goals based on current activation level, with a focus on self-management and coaching by healthcare providers.^17,37,58 In a study of activation in patients with heart failure by Shively et al., patients randomized to the activation intervention had increased activation levels and fewer hospitalizations than the group randomized to usual care.⁵⁸ These processes can be facilitated by assessment of FHL to ensure that the information provided is accessible and appropriate. For example, when educating a patient with a high activation level and low FHL, it may be necessary to provide a basic overview about PAD treatment with detailed instructions on how to adhere to them in repeated in-person clinic visits. However, for a patient with low activation and high FHL, explaining PAD risk factors and a treatment plan in a brief office visit may be sufficient to effectively communicate the necessary information.

This study has several strengths. First, we quantified activation, PAD knowledge, and FHL concurrently. Second, we used validated measures of activation and FHL. Third, our cohort has diverse sociodemographic features, suggesting that the deficiency of activation in 27.4% of patients with PAD is likely a generalized phenomenon. We also identified patient factors associated with poor activation. As poorly activated patients are more likely to experience adverse healthcare outcomes, strategies to improve activation will likely improve clinical and patient-reported outcomes.

Limitations

These findings should be interpreted in the context of several limitations. First, this was a single-practice and single-center study of patients with PAD. Second, given the modest size of our cohort, we were not able to investigate the associations between activation and other factors, such as history of limb amputation or revascularization. Third, our paper survey was only administered in English, so participants with dementia, non-English speakers, and people with low literacy were excluded, which may have skewed the findings toward people with higher activation levels. Fourth, although many of the PAD knowledge questions in the current study were used in previously published work,²⁷ they have not been validated for evaluation of knowledge among patients with PAD. Finally, though we defined a participant as ‘activated’ if they scored a level 3 or 4 on the PAM-13, it is not yet established which activation level is optimal for patients with PAD. Similarly, we were not able to establish a minimum level of PAD knowledge corresponding to activated status.

Conclusions

We found overall high levels of activation and PAD-specific knowledge among patients with an established diagnosis of PAD. Low income, low PAD knowledge, and increasing age were independently associated with low activation. Interventions tailored to these specific groups to improve patient knowledge and activation may help to improve compliance with PAD treatment plans, participation in SDM, and clinical and patient-centered outcomes.

Supplemental Material

sj-jpg-2-vmj-10.1177_1358863X251318652 – Supplemental material for Patient factors associated with activation level in peripheral artery disease

Supplemental material, sj-jpg-2-vmj-10.1177_1358863X251318652 for Patient factors associated with activation level in peripheral artery disease by Margaret A Reilly, Megan E Alagna, Cassandra Iroz, Emily Ho, Alexander Lundberg, Andrew W Hoel, Ashley K Vavra, Julie K Johnson and Karen J Ho in Vascular Medicine

Supplemental Material

sj-pdf-1-vmj-10.1177_1358863X251318652 – Supplemental material for Patient factors associated with activation level in peripheral artery disease

Supplemental material, sj-pdf-1-vmj-10.1177_1358863X251318652 for Patient factors associated with activation level in peripheral artery disease by Margaret A Reilly, Megan E Alagna, Cassandra Iroz, Emily Ho, Alexander Lundberg, Andrew W Hoel, Ashley K Vavra, Julie K Johnson and Karen J Ho in Vascular Medicine

Footnotes

Acknowledgements

An editorial by Whipple MO⁵⁹ accompanies this article.

Declaration of conflicting interests

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

Funding

Margaret A Reilly is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health award number T32HL094293. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes for Health.

ORCID iDs

Margaret A Reilly

Julie K Johnson

Karen J Ho

Data availability

Deidentified summary data are available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

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