ABSTRACT
Standardized self-management supports are an integral part of care delivery for many chronic conditions. We used the validated Patient Activation Measure (PAM®) to assess level of engagement for self-management from a sample of 165 people living with HIV (PLWH) and 163 people with diabetes. We conducted multivariable logistic regression to assess associations between demographics and PAM® scores. PLWH had high levels of activation that were no different from those of people with diabetes (mean score = 67.2, SD = 14.2 versus 65.0, SD = 14.9, p = 0.183). After adjusting for patient characteristics, only being on disability compared to being employed or a student was associated with being less activated (AOR = 0.276, 95%CI = 0.103–0.742). Our findings highlight the potential for the implementation of existing standardized chronic disease self-management programs to enhance the care delivery for PLWH, with people on disability as potential target populations.
Introduction
With the availability of effective antiretroviral therapy, HIV has become a chronic illness requiring ongoing management over time (Deeks, Lewin, & Havlir, Citation2013; Justice, Citation2010). Patient self-management strategies enable patients to monitor and manage illness symptoms, appropriately modify life-style, and engage in communication and collaboration with their provider (Damush et al., Citation2009). The Patient Activation Measure (PAM®) survey is validated to assess patients’ levels of engagement across several chronic conditions (Hibbard, Mahoney, Stockard, & Tusler, Citation2005), but few studies have measured patient activation among people living with HIV (PLWH) (Crouch, Hochheiser, Rose, Johnson, & Janson, Citation2015; Fiscella et al., Citation2015; Marshall et al., Citation2013), and Marshall et al. reported that higher levels of activation are associated with CD4 cell count >200 cells/mL3, viral suppression, and antiretroviral adherence, independent of social demographic indicators.
Although HIV-tailored self-management approaches improve outcomes among PLWH (Côté et al., Citation2015; Houston & Osborn, Citation2015; Merlin et al., Citation2015), there is a lack of clarity about whether standardized chronic disease self-management programs could be effective for this population (Millard, Elliott, & Girdler, Citation2013). The objectives of this study were to establish a baseline measure of activation using the PAM® among PLWH and to compare PAM® scores between PLWH and with Diabetes mellitus (diabetes) to help inform future approaches to self-management support for PLWH. Diabetes is a chronic disease for which self-management strategies have been extensively studied and reported on in the literature, thus providing a strong basis for comparison (Bolen et al., Citation2014).
Methods
Study design
We conducted a cross-sectional quantitative survey of two cohorts, PLWH and people living with diabetes (type 1 or 2).
Setting
The study was conducted at The Ottawa Hospital, a tertiary care academic teaching hospital located in Ottawa, Ontario, Canada.
Study population and recruitment
We recruited a convenience sample of adults living with HIV or diabetes who presented to care between June and September 2016. Participants could complete the survey on paper or a tablet in English or French. A minimum of 151 participants per cohort was required to detect a difference in mean PAM® scores of 5% assuming a SD of 15.44, with 80% power using a two-sided test at a 5% level of significance.
Measurements
The survey included 11 demographic questions and the 13 question validated PAM® tool (Hibbard, Stockard, Mahoney, & Tusler, Citation2004b). The PAM® assesses belief in the importance of actively managing one’s health, confidence level, and knowledge and ability to take action and to maintain care under stress (Hibbard et al., Citation2005). Possible responses are: disagree strongly, disagree, agree, agree strongly, and not applicable. Raw scores are mapped on a scale of 0–100 using a proprietary weighting system (Hibbard, Stockard, Mahoney, & Tusler, Citation2004a) and assigned to one of four activation levels () (Hibbard & Gilburt, Citation2014).
Table 1. The levels of patient activation.
Analysis
Descriptive statistics were used to summarize characteristics of the cohorts. We reported mean activation scores and the distribution of the four activation levels according to condition (HIV versus diabetes). We used chi-square tests for categorical variables and analysis of variance for continuous variables to evaluate distributional differences. We dichotomized the respondents’ PAM® scores comparing people scoring in levels 1–3 to people scoring in level 4. We used unadjusted bivariate logistic regression to estimate the association between condition and being fully activated (level 4). We constructed a multivariable logistic regression model adjusted for demographic characteristics, excluding associated variables. We used a significance level of 0.05 and SPSS 24.0 (IBM Corp, Citation2016) for data analysis. Ethical approval was obtained from the Ottawa Health Science Network Research Ethics Board and the Bruyère Continuing Care Research Ethics Board.
Role of the funding source
The study was funded by the Canadian Institutes of Health Research (CIHR) grant number FRNTT5–128270.
Results
Demographic information of study participants
Response rates for the HIV and diabetes cohorts were 44.7% (156/349 invited) and 47.3% (163/345 invited) respectively. Most participants responded in English (96.9% people with diabetes and 76.9% PLWH) but more people with diabetes answered the paper-based survey (81.0% versus 42.9% PLWH). Respondents living with HIV and diabetes had a similar mean age of 50.5 and 52.5 years (). Most respondents identified as Caucasian (52.6% PLWH versus 76.7% people with diabetes, p < 0.01), but a greater proportion of PLWH were African/Caribbean/Black (28.2%) or Aboriginal (4.5%). Respondents were highly educated (66.7% PLWH versus 63.8% people with diabetes had post-secondary education, p = 0.22). A greater proportion of PLWH were working (53.2%) or identified as disabled (16%), and more people with diabetes were retired (30.7%) (p < 0.01).
Table 2. Characteristics of participants with HIV and with diabetes.
Patient activation levels
PLWH had a PAM® score similar to that of people with diabetes (mean 67.16, SD 14.23 versus 64.97, SD 14.94, p = 0.18) (). The greatest proportion of people in both cohorts scored in level 3 (46.2% versus 47.2%) (). Overall, the greatest proportion of people with a high mean activation score had completed post-secondary education (mean score 67.98, SD 14.55), and reported being retired or currently employed (mean score 68.49, SD 15.81 and 67.18, SD 13.53 respectively). When we restricted our analysis to PLWH, the greatest proportion of people with a high mean PAM® score were retired or employed (or students) compared to being unemployed or on disability (Appendix A).
Table 3. PAM scores among participants with HIV and with diabetes.
Table 4. Participant characteristics across level of activation by PAM score.
Using logistic regression, after adjustment, we found no association between condition and scoring in PAM® level 4 (adjusted odds ratio (AOR) = 1.228, 95% confidence interval (CI) = 0.62–2.43) (). Only being on disability compared to currently employed was associated with a lower probability of scoring in PAM® level 4 (AOR = 0.276, 95%CI = 0.10–0.74). When we restricted our model to PLWH (), after adjustment, people on disability were less likely to score in PAM® level 4 than people who were employed (AOR = 0.22, 95%CI = 0.06–0.85).
Table 5. Logistic regression analysis of predictors of activation using a dichotomized PAM score (Levels 1–3 versus Level 4).
Table 6. Predictors of activation using a dichotomized PAM score (Levels 1–3 versus Level 4) among HIV patients.
Discussion
There are three key findings from this study that advance our understanding of the potential role for self-management strategies among PLWH. First, many PLWH had high activation levels, thus establishing the relevance of self-management interventions for this population. Patients with a high PAM® score are more likely to adhere to treatment plans than those with lower scores (Hibbard & Greene, Citation2013; Schiøtz et al., Citation2012). Specifically among PLWH, higher PAM® scores are associated with improved antiretroviral therapy adherence, CD4 count >200 cells/mL3 and suppression of HIV-1 RNA viral load (Crouch et al., Citation2015; Fiscella et al., Citation2015; Marshall et al., Citation2013). High PAM® scores have also been associated with engagement in preventative behaviours, such as regular screening, and maintaining a healthy life-style (Fowles et al., Citation2009; Hibbard & Greene, Citation2013; Salyers et al., Citation2009). Patients who score low on the PAM® are also less likely to ask questions of their provider and to be aware of their condition’s treatment guidelines (Fowles et al., Citation2009; Rogvi, Tapager, Almdal, Schiøtz, & Willaing, Citation2012).
Second, among several patient characteristics, only being on disability compared to currently being employed or a student was associated with lower activation in both cohorts, providing insights into targeted populations for self-management interventions. PLWH with disability face additional care barriers (Drainoni et al., Citation2006). Marshall et al. (Citation2013) found that individuals with a high school degree had greater activation than people without. We did not find this association, in our cohort employment status and level of education were highly associated.
Third, PLWH and people with diabetes had comparable activation levels, which is novel and has important implications. Patient self-management strategies as components of adequate chronic care are well established to improve health outcomes (Aung, Donald, Williams, Coll, & Doi, Citation2016; Brady et al., Citation2011), with extensive evidence among people with diabetes (Dorn et al., Citation2015; Eikelenboom et al., Citation2016; Lorig et al., Citation2010; Machtinger et al., Citation2015). However, existing self-management programs do not reach all people who could benefit from using them (Liddy, Johnston, Nash, Irving, & Davidson, Citation2016). Our finding suggests the potential to implement self-management programs among PLWH that are generalized for people with chronic conditions rather than HIV-specific programs, which have been the focus of most HIV self-management programs to date (Swendeman, Ingram, & Rotheram-Borus, Citation2009).
Our study has limitations. We only included patients receiving care at tertiary clinics in one hospital. In Ontario, the majority of PLWH are engaged in care (91.4%) and 55.6% access services at tertiary care clinics (Kendall et al., Citation2015), but our findings may not be generalizable to other PLWH. Our survey may under-ascertain some sociodemographic identities, but patient characteristics have a minimal impact on PAM® scores (Greene, Hibbard, Sacks, Overton, & Parrotta, Citation2015). Given demographic differences between cohorts it is possible that residual confounding persists in our findings. We cannot know whether non-respondents have different levels of activation than participants. Finally, we did not ask participants to self-report comorbidities, but feel our study reflects the principle that people with chronic diseases experience common functional challenges rather than disease-specific barriers to self-management (Liddy, Blazkho, & Mill, Citation2014).
In conclusion, our study has confirmed high levels of patient activation for self-management among PLWH and highlights the potential for generalized self-management approaches to improving patient-centred care for this population. Future program interventions should focus on patients who are unemployed or on disability, as they have lower levels of activation and may accrue greater benefit, given that greater activation translates into improved health outcomes.
Acknowledgements
We thank the people who generously donated their time and filled out the surveys, and we thank the staff of the Foustanellas Endocrine and Diabetes Centre and the Immunodeficiency Clinic (HIV/AIDS) at The Ottawa Hospital for supporting our study. We confirm that all patient identifiers have been removed such that patients described are not identifiable and cannot be identified through the details of the story. We are also grateful to Piragas Puveendran and John Flynn who administered the surveys to participants.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
References
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Appendix
Table A1. Predictors of level of activation by PAM levels among HIV patients.