Understanding the psychosocial context of employment and occupational productivity among women living with HIV: A mixed-methods study

Abstract

BACKGROUND:

Women living with HIV (WLHIV) are particularly vulnerable to poor employment outcomes, impacting their socioeconomic independence and personal sense of empowerment.

OBJECTIVE:

This article presents the results of a mixed methods study, which examined the personal, clinical, and socioeconomic contexts associated with employment and occupational productivity among employed WLHIV (n=164) in the Southern United States.

METHODS:

The Stanford Presenteeism Scale-6 was used to assess the perceived impact of HIV disease on the ability to maintain focus and complete tasks at work. Correlational and hierarchical regression techniques were applied to examine the relationships between personal, clinical, and socioeconomic contexts and occupational productivity.

RESULTS:

In this sample, 62% of women perceived no impact on their ability to work or capacity to complete work related to living with HIV. In multivariable modeling, empowerment, neurocognition, socioeconomic status, and psychological health were associated with occupational productivity. In-depth interviews (n=29) provided rich contexts and meaning surrounding employment among WLHIV, and indicated that quality of life, work-life balance, empowerment, social support, and psychological health influenced the experience of work.

CONCLUSION:

Psychosocial and structural interventions are needed to improve occupational outcomes in this vulnerable population.

1. Introduction

Employment impacts our livelihood, financial stability, human capital, social connectedness, and overall health and wellbeing [1–4]. It feeds our basic human need for self-determination and enhances overall quality of life [1, 5–7]. For people living with HIV (PLHIV), employment may improve HIV-specific clinical outcomes (i.e., CD4 count, viral load, medication adherence), and help counter the cumulative disadvantage associated with living with HIV [4, 8–11]. Yet, in spite of the evidence that most PLHIV are now able to work, an estimated 60% of PLHIV do not work. People living with chronic disease, including HIV, are more likely to attend work while ill, and may carry substantial symptom burden related to pain and fatigue that may interfere with their ability to attain employment and be productive at work [8, 12–15]. Women living with HIV (WLHIV) are less likely to be hired and more likely to lose their jobs compared to men living with HIV [16, 17], and gender-based differences (i.e., personality, emotional coping, perceived self-efficacy, social support, and cognition) may influence productivity at work and job maintenance among women [6, 18–26].

Evidence suggests that personal and social contexts influence occupational productivity, in addition to health [4, 13, 27–31]. Yet, the full contexts influencing occupational productivity and employment in WLHIV are largely undocumented. Therefore, the purpose of this study was to improve our understanding of the personal, social, and health-related context influencing the meaning and value of employment among WLHIV in the Southern United States and to examine the sociodemographic, psychosocial, and health-related factors associated with occupational productivity among employed WLHIV in the Southern United States (U.S.). We chose the Southern U.S. as it is currently the epicenter of the HIV-epidemic in the U.S., and continues to have a unique cultural context (i.e., racial discrimination, gender roles, HIV-stigmatization), which impacts employment among WLHIV [32–35].

2. Methods

This study was conducted as an ancillary study to the Women’s Interagency HIV Study (WIHS) which was established by the National Institutes of Health in 1993) to study the overall impact of HIV infection through the inclusion of women living with (n=3,677) or at risk for acquiring HIV (n=1,305) [36] across the United States. Four WIHS sites (Birmingham, AL, Jackson, MS, Atlanta, GA, and Chapel Hill, NC) were selected to collect qualitative and quantitative data. During 2013–2015, the WIHS enrolled WLHIV who were 25–60 years old, and without prior use of sub-therapeutic antiretroviral therapy, except as indicated for pregnancy or as pre- or post-prophylaxis treatment [36]. Participants attended study visits every six months for clinical, behavioral, neurocognitive, and psychosocial assessments [36]. Qualitative interviews were conducted following quantitative data collection in a subset of women who completed questionnaires at a previous WIHS visit. Qualitative and quantitative analysis were conducted concurrently.

2.1. Collection of qualitative data

Employed WLHIV (≤64 years of age) (n=164), who attended WIHS study visits between October 2017 and March 2018 were eligible to participate in qualitative interviews. The purpose of the interviews was to gain insight into the lived experience and contexts impacting employment among WLHIV. Seven or eight women were recruited from each site, with purposeful variance in the woman’s socioeconomic background and familial responsibilities. Women (n=29) were consented in compliance with the site’s Institutional Review Board (IRB), and, a demographic questionnaire was administered to assess age, education, job type, duration of employment, and familial responsibility. Semi-focused interviews (Table 1) were conducted by phone, recorded, and transcribed verbatim by a professional transcription service.

Table 1.

Qualitative interview script.

INTRO	I’m going to ask you questions related to how your life affects your job and what your job means to you. First, let’s start with the basics.
1	What does work mean to you personally? I’d like you to describe how work adds to your value or worth as a person, or is it more of a means to an end for you?
2	What do you do for work? What kind of tasks do you do on a daily basis? What kind of hours do you work?
3	Tell me how you made the decision to accept your current job. What about the job was most appealing to you?
4	Since you’ve been working, what are your reasons for staying with the job? What kind of benefits does working provide you outside of money?
5	Can you describe some of the work-related challenges you face? What techniques or strategies have you used to handle them?
6	Do you have reliable transportation? What kind? If no, how do you manage getting to and from your job? How does that affect your ability to work?
7	Tell me about what you’ve had to give up personally in order to work. How do you balance work with other important things in your life? I’d like you to describe your current work-life balance.
8	What are your responsibilities to take care of outside of work? Can you tell me how you manage those responsibilities? Can you tell me about a situation where you couldn’t manage your real-life responsibilities because of your work? What did you do?
9	How has living with HIV affected your work? Has working affected your medications? Has working affected your doctor’s appointments? How have you managed?
10	Please describe how your family or friends support or hinder your ability to work. What have you done to help find support or how have you handled friends and family if they have hindered you working? Tell me about that.
11	I’d like you to describe any accommodations your work provides to help make life easier for you? For example, do they allow for flexible scheduling or shifts, or are they flexible with your doctor’s appointments and other important things that come up in life? Tell me about a time you had to speak up for yourself or use certain strategies to get work to accommodate your needs. Do you feel like you can speak up at work? Tell me more about that.
12	Please describe any arrangements that help balance your work and personal lives. This includes things like childcare, support from family and friends, doctor visits, and time for you.
13	Overall, do you feel like you have more control or less control over your life because of your job? I’d like you to tell me about at least one example when you felt this way.

2.2. Collection of quantitative data

WLHIV (N=164) were included if they were employed and completed the Stanford Presenteeism Scale, which assesses the impact of health problems on the ability to complete tasks, avoid distraction, and stay focused during work [12]. The scale was adapted to PLHIV by replacing “health problem” with “HIV-infection. Other variables of interest collected during the WIHS core visit included socioeconomic, personal, and health-related data.

2.2.1. Socioeconomic variables.

Age, race, marital status, exposure to abuse, household income, child-care responsibility, educational attainment, housing stability, and access to medical insurance were assessed during biannual core WIHS visits.

2.2.2. Psychosocial variables.

Internalized HIV-stigma, symptoms of stress, symptoms of depression, anxiety, perceived adequacy of emotional/informational and tangible social support, and personal empowerment were assessed using the HIV-Stigma Scale [37], Perceived Stress Scale [38], Center for Epidemiological Studies-Depression Scale [39], Generalized Anxiety Scale-7 [40], MOS Social Support Survey [41], and the Personal Progress Scale-Revised [42]. Cognitive health was assessed using the Hopkins Verbal Learning Test-Revised, Trail Making Test Part B, Stroop Test, Symbol Digit Modalities Test, Grooved Pegboard testing, and semantic and fluency testing. Global scores were created using demographically adjusted t-scores from each domain (learning, memory, attention, executive function, psychomotor accuracy and speed, and verbal function) [43]. Health-related quality of life (QOL) was assessed though the MOS-HIV scale [44], summarized through Bozette’s QOL index (0.20*physical function + 0.17*pain +0.28*fatigue + 0.20*emotional wellbeing + 0.05*social function + 0.10*role function) [45].

2.2.3. Clinical variables.

Hypertension was assessed by blood pressure reading (>140/90 mmHg), current use of antihypertensive medications, or self-report. Diabetes was assessed by fasting blood glucose ≥126 mg/dl, hemoglobin A1C ≥6.5%, current use of anti-diabetic medications, or self-report. Anemia was indicated by hemoglobin level <12g/dl, and obesity was indicated by a body mass index ≥30kg/m². Excessive alcohol use, drug use, and tobacco use were evaluated through self-report. Adherence to HIV-appointments during the last six months, HIV-viral load ≤200 copies/ml, and CD4 count/mm³) were assessed via self-report or blood draw.

2.3. Qualitative data analysis

Two coders (JW and CO) used hermeneutic phenomenological approach [46] and worked independently and collaboratively to extrapolate themes using a stepwise, iterative process until all data were coded in a manner that accurately portrayed the experience and meaning of employment as described by participants. Codebooks were developed collaboratively between the two coders, and any discrepancies in coding decisions were discussed rigorously with 100% agreement in coding decisions being met following this process.

2.4. Quantitative data analysis

Statistical analyses were conducted using SPSSv24. Descriptive statistics were employed to summarize and compare the socioeconomic, psychosocial, and clinical factors previously supported to impact occupational productivity among employed women living with HIV, with and without perceived impairment in occupational productivity. Pearson’s correlation co-efficient was computed to assess the linear relationship between continuous variables of interest and occupational productivity. Correlation tests (Chi-squared and Fischer’s) were used to assess the association between categorical variables and occupational productivity, as indicated in Table 3. Hierarchical regression modeling was used to better elucidate the combined effect of socioeconomic, psychosocial, and clinical characteristics on occupational productivity based on a priori literature review. To enhance interpretability of results, occupational productivity scores were re-coded into a categorical variable with scores of 30 recoded to “no impairment” and all other scores (12–29) coded as“impaired”.

Table 3.

Categorical variables and correlations with occupational productivity.

	Employed	Perceived Impairment in Occupational
	WLHIV	Productivity in Employed WLHIV
		YES N = 62	NO N = 102
Race		N (%)	N (%)	Cramer’s V	p
White	13 (7.9)	4 (6.5)	9 (8.8)	0.066	0.868
Hispanic	4 (2.4)	1 (1.6)	3 (2.9)
Black/African American	145 (88.4)	56 (90.3)	89 (87.3)
Other	2 (1.2)	1 (1.6)	1 (1.0)
Highest Education Level
7th–11th Grade	37 (22.6)	18 (29.0)	19 (18.6)	0.187	0.057*
High School	44 (26.8)	20 (32.3)	24 (23.5)
Attended or Graduated College	83 (50.6)	24 (38.7)	59 (57.8)
Residence
House/Apartment	160 (96.7)	60 (96.8)	100 (98)	0.166	0.105
≤1 month Duration at Residence	4 (2.4)	3 (5.0)	1 (1.0)	0.134	0.237
Household Income
≤12,000	39 (23.8)	20 (32.3)	19 (18.6)	0.185	0.252
12,001–24,000	58 (35.4)	20 (32.3)	38 (37.3)
24,001–36,000	31 (18.9)	13 (21)	18 (17.6)
36,001–75,000	27 (16.5)	8 (12.9)	19 (18.6)
≥75,000	2 (1.2)	0 (0)	2 (2.0)
Familial Responsibility
Married or Living with Partner	44 (26.8)	16 (25.8)	28 (27.5)	0.029	0.719
Provides Care for own Child	46 (28.0)	20 (32.3)	26 (25.5)	0.109	0.39
Provides Care for Someone Else’s Child	16 (9.8)	5 (8.1)	11 (10.8)
Health Indicators
Health insurance, ADAP or Ryan White	159 (97.0)	60 (96.8)	99 (97.1)	0.008	0.918
Indication of Hypertension	81 (49.4)	29 (46.8)	52 (51.0)	0.041	0.601
Indication of Diabetes	25 (15.2)	11 (17.7)	14 (13.7)	0.054	0.488
Cigarette Use	56 (34.1)	23 (37.1)	33 (32.4)	0.049	0.534
≥7 Alcoholic Drinks/Weekb	11 (6.7)	7 (11.3)	4 (3.9)	0.143	0.067*
IV Drug Useb	1 (0.6)	1 (1.6)	0 (0)	0.102	.195
Other Recreational Drug Useb	42 (25.6)	16 (25.8)	26 (25.5)	0.008	0.917
Serious Physical Abuseb	1 (0.6)	1 (1.6)	0 (0)	0.1	.200
HIV Medication Adherence ≥95% b	137 (83.5)	48 (77.4)	89 (87.3)	0.155	.080*
Viral Load Suppression (≤200/copies/ml)	134 (81.7)	46 (74.2)	88 (86.3)	0.152	0.052*
Missed HIV Care Appointmentsb	13 (7.9)	8 (12.9)	5 (4.9)	0.14	0.069*

^aCramer’s V effect size interpretation: small (0.10). medium (0.30). large (0.50).

^bLast six months

^*p<0.1.

2.5. Data triangulation

Because our qualitative data collection on understanding the lived experience of employment for WLHIV was not solely focused on occupational productivity (our quantitative outcome of interest), we could not assess for convergence and divergence directly. However, qualitative and quantitative data were considered for complementarity.

3. Results

3.1. Qualitative findings

Qualitative interviews (n=29) were conducted to better understand the meaning and experience of employment among WLHIV. Women were black (n=27, 93%), not married or living with a partner (n=16, 55%), and approximately 1/3 reporting responsibility for a child under 19 years of age (n=8) or another adult (n=3). The majority of women (n=18, 62%) had attended college, with 35% (n=10) having earned an associate degree or higher. Few (n=3, 10%) reported sub-optimal transportation (i.e., reliance on public transportation or taxi services). Job types varied, and women reported employment in the service industry (n=15, 52 %), as unlicensed health care employees (n=9, 31 %), in professional roles (n=3, 10 %), and as administrators (n=2, 7%). Most women (n=17, 59%) reported being in their current position for more than one year, and 52% (n=15) reported receiving academic and/or technical training for their current job. Five themes emerged that captured the significance, experience, and contexts impacting employment among WLHIV: 1) Quality of Life, 2) Work-Life Balance; 3) Empowerment, 4) Social Support, and 5) Psychological Health. Exemplar quotes portraying each theme can be found in Fig. 1.

Fig. 1.

Exemplar quotes of qualitative themes.

3.1.1. Quality of life.

Most (n=26, 90%) women reported that work improved their quality of life, both through traditional benefits (i.e., income and health insurance) (n=10, 35%), and through increased satisfaction, depth, and confidence in life (n=22, 76%). Work served as an outlet from the more mundane aspects of life as well as a distraction from life’s stressors (n=13, 45%). For many women (n=18, 62%), work provided a sense of purpose, and created a positive sense of responsibility and identity. Although most women viewed employment in a positive light, some (n=3, 10%) women described that work negatively impacted their ability to exert control and practice self-determination

3.1.2. Work-life balance (including health care).

Quality of life hinged, in part, on the ability to achieve work-life balance. Although most (n=16, 55%) women reported that some sort of personal sacrifice was necessary to work (i.e., losing time with family, self, or delaying other goals), very few (n=3, 10%) reported poor work-life balance. For many women (n=18, 62%), their routines, skill sets, and attributes facilitated their ability to achieve work-life balance. For example, women (n=15, 52%) with greater work-life balance had established what their personal priorities were, and structured their lives accordingly to accommodate self-care, recreation, relationships, and personal causes which were deemed important. When asked about non-work responsibilities, women (n=19, 66%) reported familial duties, but also emphasized the importance of self-care (n=6, 21%), and the critical role health care played (n=6, 21%) in maintaining quality in both their personal and work lives. Most (n=24, 83%) felt that their employers provided reasonable flexibility in scheduling and did not perceive that work interfered with their ability to adhere to HIV-medications or keep doctor’s appointments. Women (n=3, 10%) who did report poor-work life balance, described difficulty managing conflicting role and time expectations, resulting in increased stress.

3.1.3. Empowerment.

Women described that the ability to set and enforce personal boundaries, and advocate for themselves greatly influenced the experience of employment, as well as overall work-life balance. Individual skillsets played a large role in personal empowerment and the ability to navigate conflict at work. The work environment significantly influenced their ability for women to effectively exercise these skill sets. Most women described working environments characterized by respect and active listening, allowing them to engage in difficult conversations and voice their needs. However, women who described fear-driven working environments were less likely to address confrontational situations for fear of repercussion.

3.1.4. Social support.

Social support, within and outside of the work environment, influenced the impact of employment on quality of life, work-life balance, and personal empowerment. Some women described how their social support systems encouraged positivity and resiliency, improving their ability to stay motivated and manage stressors at work. Others described how functional support, such as being part of a team or having additional problem-solving support, facilitated less role-strain and enhanced the experience of work. Women also described how organizational social support impacted the experience of employment, with the capacity to either enhance work-life balance or negatively influence quality of life. Women described how low cohesion within the work environment, or the acceptance of a negative work culture negatively influenced the experience of work. Intersectional stigma within the workplace was also reported to negatively influence the ability to get and keep a job.

3.1.5. Psychological health.

Many women described how work improved psychological health by providing a means for self-determination and greater autonomy. Some women described that the income facilitated financial independent, while other focused on the ability to be able to take care of their loved ones. Women described that their ability to view challenges as a blessing influenced resiliency, and their ability to handle stress at work; whereas, the use of negative coping mechanisms, such as avoiding conflict, added to the stress and strain of work. Working environments which facilitated empowerment and autonomy in the workplace provided an opportunity for meaningful work, and allowed women to build new skillsets, and form a sense of identity and purpose from being able to contribute to something larger than themselves. However, work environments that made women feel unproductive, unappreciated, and not listened to, undermined the ability for work to add personal value.

3.2. Quantitative results

Women (n=164) completed the occupational productivity assessment across four WIHS sites, with a collective employment rate of 38%. Participation numbers varied across sites, related to the total number of women followed at each site, and differences in employment rates by region. Employed women participating at the Atlanta site represented 35.4% of participants, followed by Chapel Hill (34.1%), Jackson (19.5%), and Birmingham (11.0%). Tables 2 and 3 present the demographic, socioeconomic and health characteristics of our sample. Women, on average, were 44.8 years of age, unmarried (69.1%), and educated. Most (77.8%) had received at least a high school education and 50.6% reported attending college. Although most women were not responsible for a child under the age of 19 years (58.5%), those that reported caring for a child provided care for an average of 1.9 children over 11.5 hours per week. Women worked an average of 36.6 hours per week, and most (62%) indicated that their HIV-infection had little impact on their ability to complete tasks and stay focused at work.

Table 2.

Continuous variables and correlations with occupational productivity.

	Employed	Perceived Impairment in Occupational
	WLHIV	Productivity in Employed WLHIV
	N = 164	YES N = 62	NO N = 102
MOS-HIV Scale a(See Footnote)		Mean (SD)	Mean (SD)	Adjusted R2	p
Physical Function	84.2 (22.5)	86.4 (21.9)	80.6 (23.2)	0.009	0.114
Social Function	88.9 (20.5)	91.8 (18.7)	84.2 (22.6)	0.026	<0.05*
Pain	81 (20.1)	82.2 (20.2)	79.1 (20.1)	0	0.343
Emotional Wellbeing	78.8 (22.9)	82.4 (22.7)	72.8 (22.1)	0.036	<0.05*
Role Function	92.9 (16.8)	93.3 (16.9)	92.3 (16.7)	0	0.719
Energy/Fatigue	67.1 (25.6)	70.7 (26.3)	61.1 (23.5)	0.027	<0.05*
Quality of Life	78.9 (17)	81.5 (16.7)	74.7 (16.8)	0.031	<0.05*
Neurocognitive Ratingb
Executive Domain	2.5 (1.4)	2.3 (1.2)	3.1 (1.6)	0.051	<0.05*
Speed Domain	2.3 (1.3)	2.1 (1.1)	2.6 (1.5)	0.035	<0.05*
Attention Domain	2.8 (1.6)	2.7 (1.6)	3.1 (1.7)	0.009	0.137
Learning Domain	3 (1.9)	2.8 (1.9)	3.4 (1.8)	0.018	0.052
Memory Domain	3.1 (1.9)	2.9 (1.8)	3.5 (2.2)	0.026	<0.05*
Motor Domain	2.1 (1.3)	2 (1.3)	2.3 (1.3)	0.014	0.076
Verbal Domain	2.7 (1.6)	2.7 (1.5)	2.7 (1.6)	0	0.523
Global Rating	3.4 (1.7)	3.2 (1.7)	3.9 (1.7)	0.035	<0.05*
Social Supportc
Emotional/Tangible Support	4.1 (1)	4.2 (1.1)	3.9 (1)	0.008	0.126
Functional Social Support	4.1 (1.1)	4.3 (1)	3.8 (1.2)	0.053	<0.05*
Psychological Health
Depressive Symptomsd	9.3 (10.7)	7.7 (10)	4.7 (5.3)	0.033	<0.05*
Anxiety (GAD-7)e	3.8 (5)	3.3 (4.7)	10.7 (6.9)	0.013	0.081
Perceived Stressf	8.4 (6.8)	7 (6.4)	5.5 (0.9)	0.064	<0.05*
Empowermentg	5.9 (0.8)	6.2 (0.6)	5.5 (0.9)	0.156	<0.001*
Internalized HIV-Stigmah	1.8 (0.7)	1.7 (0.6)	2.0 (0.8)	0.061	<0.05*
Health Indicators
Age	44.8 (8.6)	44.9 (9)	44.6 (8.1)	0	0.818
Hemoglobin (gm/dl)	12.5 (1.2)	12.8 (1.1)	12.2 (1.3)	0.053	<0.05*
Hematocrit (%)	38.2 (3.4)	38.9 (3)	37 (3.7)	0.067	<0.05*
Hemoglobin A1C (%)	5.7 (1.3)	5.7 (1.1)	5.8 (1.6)	0	0.549
Body Mass Index (kg/meter2)	35.2 (9.3)	35.2 (9.5)	35.3 (9)	0	0.95
CD4 count (cells/mm3)	753.5 (349.5)	799.2 (369.6)	679.4 (302.7)	0.022	<0.05*

Note:

R² effect size interpretation. MOS-HIV Scale Range is from 0–100, with 100 being best^a.

Neurocognitive ratings greater than 5 indicate impairment^b.

Social support range is from 1–5, with 5 being best^c.

Depressive symptoms: score ≥16 indicates depression^d.

Anxiety symptoms: score ≥10 indicates anxiety^e.

Perceived Stress range is 0–40, with 0 being best^f.

Empowerment range is 1–7, with 7 being best^g.

Internalized HIV Stigma range is 1–4, with 1 being best^h.

Possible score ranges for occupational productivity were 6–30, with higher scores indicating better productivity at work. The mean score was 27.9 (±3.7), and over half (62.3%) of women completing this measure scored 30, indicating no perceived impairment. Using simple regression analysis, differences were found in personal, health-related, and socioeconomic variables associated with productivity among WLHIV (Tables 2 and 3).

Better neurocognitive function (R²=0.035), and especially higher executive function (R²=0.051), lower stress (R²=0.064), depressive symptomology (R²=0.033), and internalized HIV-stigma (R²=0.061), and higher levels of educational attainment (R²=0.187), functional social support (R²=0.053) and personal empowerment (R²=0.156) were associated with occupational productivity among WLHIV. HIV-viral load suppression (Cramer’s V=0.152) and adherence to HIV care visits (R²=0.143) were also associated with occupational productivity among our sample.

Table 4 presents the detailed results of hierarchical regression modeling for occupational productivity among employed WLHIV. Model 1 accounted for factors associated with the management and impact of living with HIV (R²=0.182), while Model 2 added socioeconomic contexts (R²=0.224), and the final model accounted for personal characteristics previously associated with occupational productivity (R²=0.388). In the final model (p<0.001), personal empowerment (β=0.441, p<0.001), global neurocognitive function (β=–0.172, p<0.05), housing stability (β=–0.148, p<0.05), and education (β=0.123, p=0.074), demonstrated a significant impact on occupational productivity, controlling for quality of life, viral suppression, and adherence to HIV care. Complementarity of qualitative and quantitative data, and potential areas of divergence are presented in Fig. 2.

Table 4.

Hierarchical regression models of predicting occupational productivity among WLHIV.

Model		B	Std. Error	Beta	p	Adjusted R2	Std.Error of the Estimate
1	(Constant)	19.178	2.239		0.000	0.182	3.35273
	Quality of Life*	0.063	0.016	0.297	0.000
	Viral Load Suppression	0.165	0.782	0.017	0.833
	Global Neurocognitive Rating	−0.464	0.164	−0.215	0.005
	HIV-Care visit Adherence	2.737	1.101	0.203	0.014
2	(Constant)	16.007	2.842		0.000	0.224	3.26573
	Quality of Life*	0.052	0.017	0.247	0.003
	Viral Load Suppression	−0.207	0.790	−0.022	0.793
	Global Neurocognitive Rating	−0.434	0.163	−0.201	0.009
	HIV-Care Adherence	2.995	1.077	0.223	0.006
	Education	0.640	0.349	0.140	0.069
	Functional Social Support	0.418	0.282	0.123	0.140
	Housing Stability	−0.679	0.355	−0.142	0.058
3	(Constant)	13.129	3.500		0.000	0.388	2.89994
	Quality of Life*	0.011	0.019	0.050	0.579
	Viral Load Suppression	−0.451	0.743	−0.047	0.545
	Global Neurocognitive Rating	−0.371	0.148	−0.172	0.014
	HIV-Care Visit Adherence	1.615	0.988	0.120	0.105
	Education	0.562	0.312	0.123	0.074
	Functional Social Support	−0.154	0.267	−0.045	0.564
	Housing Stability	−0.704	0.317	−0.148	0.028
	Perceived Stress	−0.041	0.050	−0.075	0.416
	Personal Empowerment	2.037	0.389	0.441	0.000
	Depression ≥16	−0.950	0.832	−0.104	0.256

Note:

^*Quality of Life=(0.2*physical function (fx)+0.17*pain + 0.28*fatigue +0.2*emotional wellbeing + 0.05*social fx + 0.1*role fx) [45].

Fig. 2.

Complementarity and divergence among qualitative and quantitative data.

4. Discussion

The purpose of this study was to gain insights into the personal, social, and health-related contexts influencing employment and occupational productivity among employed WLHIV. Overall, we found that health-related factors (including HIV) did not largely influence the experience of employment among WLHIV, particularly in the context of appropriate chronic disease management. While social factors, such as educational attainment and functional social support, did impact the experience of employment and perceptions related to occupational productivity, personal characteristics, including psychological health and personal empowerment, played the largest role on influencing both the subjective value of work the ability to remain productive in the working environment. Most women found value in employment based on its ability to provide autonomy and income and enhance purpose and quality of life. These positive attributes associated with the experience of employment (and occupational productivity) were heighted among women with positive psychological mindsets, higher cognitive function, and the ability to set and enforce personal boundaries, both in and out of work.

Our findings are consistent with the literature that socioeconomic status influences employment and job maintenance through its impact on structural (i.e., education, housing, income) and personal (i.e., health and psychosocial) resources [1, 5, 28, 29, 47]. Women who have reduced access to the financial and structural resources necessary for adequate physical health, may have difficulty accessing the psychosocial resources (i.e., positive coping and effective problem-solving skills, influential social networks) that facilitate positive employment outcomes [42, 48–52]. Further, this study adds to the body of evidence that attitudes, thoughts, and behaviors associated with psychological health (i.e., the use of positive psychology techniques vs. neuroticism) and those associated with overall empowerment (self-efficacy, human capital, boundary setting, and assertiveness) influence the experience of employment and employment maintenance through its impact on occupational productivity [29, 48, 52–57].

Although there has been some concern in the past that employment may interfere with the ability for PLHIV to properly manage their HIV infection [58–60], the results of our study support the newer evidence that that employment is a positive social determinant of health and may facilitate daily management and improved health and quality of life through its many benefits [10, 61, 62]. The results of this study also support that previous concerns over reduced productivity among individuals with chronic disease [17, 18, 65, 66] may be mitigated with proper adherence to care regimens and special attention to the unique vocational needs WLHIV may possess. Interventions to address these needs may be necessary to address other social determinants of health impacting employment, improve psychological resiliency, refine cognitive skillsets, and promote personal empowerment to achieve more equitable employment outcomes [17, 31, 63–66].

Practical implications from this study include the integration of routine psychological health and social service screenings into HIV-care, including the identification of current vocational needs. A reconceptualization of vocational needs should be considered to evaluate not only deficits or strengths in traditional skillsets, but also identify needs for neurocognitive training, interpersonal skill development and behavioral therapies supported to improve positive employment outcomes [30]. To enhance patient outcomes and linkage to care, providers should work within an interdisciplinary team to effectively screen for needs and promote continuum of care.

We acknowledge that while this study contributes to the literature by informing our understanding of what contexts influence employment outcomes among WLHIV, it is limited by the fact that the women in our sample represent the WLHIV who were successful in gaining employment, and likely have personal characteristics, behaviors, and the access to the psychosocial and structural factors which promote positive employment outcomes. Further, the results generated from this study are limited by our analytic approach as complex causal relationships among predictors are not possible to capture through the use of regression models [67, 68]. Future research is needed to better understand the individual differences moderating the impact of the environment on employment and occupational productivity among employed and unemployed WLHIV. Structural equation modeling may also be considered in the future to elucidate the direct and indirect pathways influencing employment outcomes among WLHIV to better tailor interventions to reduce inequities.

5. Conclusion

The results of this study confirm the limited body of evidence that employment is not detrimental to the management of HIV but has the potential to improve health and quality of life. It fills a gap in the literature by improving our understanding of the barriers and protective factors associated with positive employment outcomes among WLHIV and provides both theoretical backing and practical implications to inform interventions to improve employment related outcomes and reduce employment-related inequities among this population. As we continue to understand the value of employment and the comprehensive factors impacting employment outcomes among WLHIV, the need for a more integrative, interdisciplinary approach to identify and meet the complex vocational needs of WLHIV becomes increasingly evident. Academic researchers, clinical care providers, vocational rehabilitation specialist, and employers invested in a productive and diverse workforce must join in the conversation to better understand and address successful occupational and personal outcomes in a population coming forward as willing, able, and grateful to work.