Lynda Tyer-Viola PhD RN, Kathleen Sullivan PhD RN, Paula Reid PhD RN , Inge Corless PhD RN FAAN ,

Patrice Nicholas PhD RN FAAN, and A. J. Guarino PhD  

HIV INTERNATIONAL HIV/AIDS NURSING RESEARCH NETWORK

HIV Nursing Research NetworkA network of nurses actively researching

international topics concerning persons living with HIV/AIDS

The Network’s Theoretical Foundation posits that HIV/AIDS remains a significant world wide threat to public health

The Network’s Research Agenda will positively influence quality of care and patient outcomes across the spectrum of HIV disease.

Funding is external and internal (and mostly personal)

(see Holzemer, 2007)

International collaborative Network Studies

Study I: Predictors of Adherence in HIV/AIDSUS sites: Birmingham, AB; Boston, MA Highland, NY; Honolulu, HI; Oakland, Sacramento, San Francisco, California; Seattle, WA; Tampa, FL International sites: London, England; Oslo, Norway; Sao Paulo, Brazil

Study II: Symptom Management for Persons with HIV DiseaseUS sites: Boston, MA; New York, NY; Palo Alto, San Fancisico, CA; Patterson, NJ; International sites: Oslo, Norway

Study III: Self-care Symptom Management in HIV/AIDS. US sites: Boston, Fall River, MA; Columbus, OH; Fresno, San Francisco, CA; Harlingen, Temple, TX; New York, NY; Patterson, NJ Richmond, VA; San Juan, PR; Wilmington, NC. International sites: Bogota, Colombia; Oslo, Norway; Taipei, Taiwan

Study IV: The Efficacy of the HIV/AIDS Symptom Management ManualUS sites: Boston, MA; Chicago, IL; Corpus Christi, Harlingen, Houston, TX; Philadelphia, PA; Salt Lake City, UT; San Diego, San Francisco, CA; San Juan, Vega Baja, PR International sites: Nairobi, Kenya; Gauteng, South Africa; Mbabane, Swaziland

Study V: Study V: Exploring the Role of Self-compassion, Self-efficacy and Self esteem for HIV-positive Individuals Managing Their Disease. US sites: Boston, MA; Chicago, ILs; Corpus Christi, Harlingen, Austin, TX; San Francisco, CA; Cleveland, OH, Durham, NC, Honolulu, HI, Newark, NJ, New York, NY & San Juan, PR, International sites: Namibia, China & Bangkok.

BackgroundComprehensive review of the adherence literature to HAART

concluded women to be less adherent than men (Puskas et al, 2011).

Social support and perceived satisfaction with one’s social relationships, influences PLWH medication adherence. The influence of support and satisfaction with one’s healthcare provider in relation to self, is currently unknown. (Johnson et al, 2006).

Although the relationship between self-efficacy and HIV medication adherence is well documented, the connection between self and adherence has not been investigated (Johnson et al, 2007).

In a meta-analysis of predictors of adherence in women, depression was common however, the concepts of self-esteem, self-compassion and sense of coherence and the role they may play on HIV management has not been so well studied (Voils et al, 2007).

Focus on Self

Sense of CoherenceAn attribute that depicts an individual’s capacity

to respond to stressors and “a reflection of an individual’s overall well-being and ability to cope with stress” (Pham, Vinck, Kinkodi and Weinstein , 2010).

Self Efficacy Individual’s actions are based on social behaviors

and cognitive processes. Self efficacy is based on external influences and self perceptions.

Adherence self-efficacy is confidence in one’s ability to comply with a treatment plan, has been consistently linked to adherence over time. 

Self CompassionExtending feelings of kindness to oneself (Neff &

Vonk, 2009). People are often harder on themselves than on others for fear of becoming self indulgent.

Self criticism can result in negative feelings and can be a poor motivational force

Self Esteem Evaluation of oneself in relation to others. Can be viewed in comparison to self compassion

as having the same benefit of positivity towards oneself.

Study Aim & Research QuestionsTo identify what contextual, environmental

and regulatory factors affect adherence to ARV medication in women residing in North America.

Research QuestionIs there a relationship between contextual,

environmental and regulatory factors and the outcome of medication adherence?

Of these correlates, what factors predict medication adherence?

Theoretical FrameworkPatient Characteristics

DepressionHealth care Provider

EngagementStigma

Adherence Self-efficacy

Self-compassionSelf-esteem

Sense of coherence

Medication adherence

Environmental/Contextual factors Regulatory

factors

Outcomes

Moderator/Target of interest: gender

Variables of interest of Social Action Theory (Ewart, 1991)

MethodsData for this cross-sectional study was obtained from

the International Nursing Network for HIV/AIDS Research, Study V: Exploring the Role of Self-compassion, Self-efficacy and Self esteem for HIV-positive Individuals Managing Their Disease

A subset of 338 women currently on ART were studied from the full data file of 2182 patients comprising 16 sites from five countries and Puerto Rico.

After consent, participants self-completed a study packet

Remuneration varied from site to site depending on funding. US gift cards ranging from $15 to $25 for each

participant

Study VariablesContextual / Environmental Demographics: age, education, race, children,

income

Center for Epidemiology Studies Depression Scale (CES-D) The CES-D 20-item scale. non-diagnostic screening tool that measures the current level of depressive symptoms in community populations (Radloff, 1977) Cronbach’s alpha overall = 0.91

Perceived Stigma Scale. 40-item scale. measures the stigma perceived by people with HIV, using Goffman’s definition of stigma. (Berger, Ferrans, & Lashley, 2001) Cronbach’s alpha overall = 0.94

Regulatory Sense of Coherence Scale (SOC)

13-item instrument consisting of four meaningfulness, five comprehensibility, and four manageability items to measure sense of coherence (Antonovsky, 1993; Konttinen, Haukkala, & Uutela, 2008). Cronbach’s alpha overall = 0.60

Self-Compassion Scale (SCS) 12-item scale participants rate how they deal with difficult situations on a 5 point Likert scale (Neff, 2003). Cronbach’s alpha overall = 0.72

Rosenberg Self-Esteem Scale (SE) 10-item scale. overall feelings of self-worth or self-acceptance. Cronbach’s alpha overall = 0.72

HIV- Adherence Self-Efficacy (ASE)12- item scale . patient confidence to carry out health-related behaviors (asking physician questions, keeping appointments, adhering to medication) (Johnson et al, 2006).

Engagement with Health Care Provider (HCPE) 13-item scale. Participants rate the nature of their interactions with their main health care provider on a four-point scale with 1=always true and 4=never. Cronbach’s alpha overall = 0.96

Outcome Variables3-Day and 30-Day Visual Analog Scale. Participants are

asked to mark how often they took their medications in the past 3 days (30 days), on a scale of 0% of the time to 100% of the time.

Target of InterestGender (n = 338) women currently on ART medications.

Sample DemographicsOf the 450 women who participated in the

study from North America, 338 stated they were taking medications now.

Most participants had a High School education (39%) or less (37%).

Mean age 45 (sd=9.1) 50% were African American82% had children 59% said their income was barely adequate66% screened positive for depression

symptoms (CESD > 16)

ResultsIs there a relationship between contextual,

environmental and regulatory factors and the outcome of medication adherence?

The following variables were significantly related to 3 and 30 day adherence (p = .01)Contextual/Environment Factors

Age Fewer symptoms of depression(CESD)

Regulatory FactorsSelf Compassion (SCS)Self Esteem (SE)Adherence Self Efficacy (ASE) Sense of Coherence (SOC)

Correlations among study variables and adherence.

Variable1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. adher3d 1 .699** -.102 -.230** .245** -.239** .421** .174** -.107 .053 -.001 -.023 .128* .060

2. adher30d .699** 1 -.102 -.254** .254** -.278** .450** .257** -.094 .044 .063 -.095 .121* .082

3. HCPE -.102 -.102 1 .089 -.098 .113* -.157** -.180** .110* -.079 -.057 -.090 -.099 -.017

4. CESD -.230** -.254** .089 1 -.643** .612** -.273** -.639** .386** -.093 -.183** .010 -.100 -.030

5. SCS .245** .254** -.098 -.643** 1 -.693** .365** .603** -.293** .086 .132* -.072 .164** .048

6. SE -.239** -.278** .113* .612** -.693** 1 -.388** -.589** .336** -.123* -.153** .028 -.152** .045

7. ASE .421** .450** -.157** -.273** .365** -.388** 1 .332** -.165** .059 .167** -.025 .054 .045

8. SOC .174** .257** -.180** -.639** .603** -.589** .332** 1 -.346** .097 .171** .039 .064 -.017

9. STIGMA -.107 -.094 .110* .386** -.293** .336** -.165** -.346** 1 .042 -.170** .017 -.096 -.120*

10. EDU .053 .044 -.079 -.093 .086 -.123* .059 .097 .042 1 -.139* -.039 .133* .061

11.INCOME -.001 .063 -.057 -.183** .132* -.153** .167** .171** -.170** -.139* 1 -.004 .041 -.053

12.CHILDREN -.023 -.095 -.090 .010 -.072 .028 -.025 .039 .017 -.039 -.004 1 .050 -.167**

13.AGE .128* .121* -.099 -.100 .164** -.152** .054 .064 -.096 .133* .041 .050 1 -.009

14.ETHNICITY .060 .082 -.017 -.030 .048 .045 .045 -.017 -.120* .061 -.053 -.167** -.009 1

**. Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed)

Results What Contextual, Environmental and/or Regulatory factors predict

medication adherence? The Contextual factors were represented by age, having children, income, and

ETHNICITY. Only age was significantly correlated with 3 (r = .14) and 30 day (r = .13) adherence yet it was not significant in simultaneous regression analyses (p < .05).

The Environmental factors were represented by stigma and depression (CESD), and health care provider engagement (HCPE). The variables were all correlated (p < .05). The dependent variables of 3 day and 30 day adherence were regressed on all four independent variables. The models accounted for 5 and 7% of the variance respectively in adherence and the F values were significant (F = 5.300, p < .000, F= 6.155, p <.000). Examination of the standardized coefficients revealed that CESD was the only significant predictor (p = .000) with squared partial correlation of 3.2% for both results. A lower screening score for depression predicts self reported adherence.

The Regulatory factors were represented by sense of coherence, self compassion, self esteem and adherence self efficacy and chronic disease self efficacy. The variables were all correlated (p <.05). The dependent variables of 3 day and 30 day adherence were regressed on all five variables. The models accounted for 19 and 22% of the variance respectively for adherence and the F values were significant (F = 14.685, p < .000, F = 17.89, p < .000). Examination of the squared partial coefficients revealed that adherence self efficacy was the only significant predictor (p = .000) with squared partial correlations of 9.6 and 9.9% respectively. A higher score of adherence self efficacy predicts self reported adherence.

Results cont. Taking into account the results of the three separate

regressions only adherence self efficacy and screening for depression were predictive of adherence.

The model for 3 day adherence accounted for 19% of the variance, F(6, 332) = 37.08, p < .001). Examination of squared part-coefficient revealed that 14% of 3 day adherence is uniquely explained by Adherence Self Efficacy and 1% by fewer symptoms of depression

The model for 30 day adherence accounted for 22% of the variance, F(6, 332) = 45.16, p < .001). Examination of squared part-coefficient revealed that 15% of 30 day adherence is uniquely explained by adherence self efficacy and 2% by fewer symptoms of depression

DiscussionRegulatory factors have a medium to strong

correlation with medication adherence (p < .01).Health care provider engagement and stigma

were not related to adherence. In the overall sample, HCPE was significant

(Corless et al, 2012). Self esteem and self compassion are often highly

correlated (r = -.693) and are related to life satisfaction, a meaningful life, happiness, optimism, and positive affect (Neff et al, 2007a, 2007b). The difference is that self compassion is relevant

when self esteem tends to falter- when one fails or feels inadequate (Neff, 2009, p. 567). This variable needs to be evaluated further.

Discussion cont.Although regulatory factors were highly

correlated, Adherence self efficacy and fewer symptoms of depression were the only predictors of adherence at 3 and 30 days. Research continues to show that depression

affects adherence and should be addressed in relation to self efficacy throughout treatment.

Adherence self efficacy addresses behaviors that affect care and could be a target of interventions beyond the provider relationship

LimitationsVariation in enrollment of women between sitesSelf selection of participantsOverall, non-random recruitment may introduce

biasSelf report of adherence was measured with an

estimate of what percentage of time medications were taken and was heavily weighted to the positive.

There was no validated measure biological marker of adherence.

ConclusionsRegulatory factors are highly correlated. Although

described as separate, self esteem and self compassion are intrinsically linked with this population.

Depression in women continues to play a role in medication adherence and screening should be on going.

Adherence self efficacy and its constructs should be a focal point of adherence interventions such as what helps with treatment integration into every day life and ‘sticking to’ a treatment plan with deviations.

Future research is warranted related to concepts of self as regulatory factors.

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