Introduction

Antiretroviral therapy (ART) has transformed the trajectory of Human Immunodeficiency Virus (HIV) from an acute, and often terminal, illness into a manageable chronic illness. This has allowed many people living with HIV (PLHIV) to experience healthy lives [1], with life expectancy approaching that of the general population [2]. The effectiveness of biomedical management allows clinical research and practice to broaden its scope and explore issues pertaining to psychosocial factors, such as quality of life (QoL). Research suggests that despite the success of HIV treatments, several psychosocial challenges remain and generally diminish QoL [3, 4]. In particular, HIV-related stigma/discrimination, social disconnection, and mental health difficulties remain prevalent among this population and have harmful effects on QoL [5, 6]. Further understanding of the relationship between factors associated with poorer QoL among PLHIV is important for the development of effective strategies to support this population [7].

Quality of Life

The 2014 Joint United Nations Programme on HIV/AIDS (UNAIDS) global ‘90–90–90’ target for HIV management [8], particularly achieving viral suppression, is traditionally used to measure treatment success and has a clear biomedical focus [9, 10]. These targets are progressively being achieved globally; in Australia, HIV has largely been controlled through ART with recent estimates suggesting Australia’s Cascade is currently 90–92–97 [11, 12]. Despite this biomedical success, QoL among many PLHIV remains poor [13, 14] and thus a more holistic model encompassing QoL is considered integral to treatment success.

QoL is multifaceted and impacted by the complex interplay between a range of physical, psychological, social, and environmental factors [12], and is “not merely the presence or absence of disease” [12, p. 2]. The current medical targets fail to address psychosocial comorbidities and consequently cannot optimize QoL. Research demonstrates that although ART improves QoL for PLHIV, the residual impact of psychosocial comorbidities means PLHIV still experience poorer QoL than the general population, regardless of effective medical interventions [6, 15,16,17]. Additionally, QoL amongst PLHIV is more closely linked to psychosocial factors than physiological or medical aspects of HIV [5, 18]. Consequently, understanding the psychosocial determinants of QoL is vital.

Recognizing Psychosocial Comorbidities

Recent literature has recognized the importance of QoL, advocating for the addition of a ‘fourth-90’ to the UNAIDS ‘90–90–90’ targets; that is, Health Related Quality of Life (HRQoL) [19]. HRQoL is a multidimensional construct encompassing physical, psychological, and social domains of health [19, 20]. HRQoL can be conceptualized as the aspects of QoL which impact/are impacted by health factors, distinct from QoL which is much broader [21]. HRQoL focuses on living well with HIV long-term, surpassing VL suppression as the primary goal [6], and captures the needs of PLHIV who have achieved VL suppression yet continue to face psychosocial challenges which diminish QoL.

While HRQoL issues are important in their own right, research has also shown that these psychosocial comorbidities (particularly HIV-related stigma) impede capacity to engage in medical care; that is, HIV-testing, treatment uptake and medication adherence [22,23,24,25]. Therefore, although VL suppression is achieved through ART, psychosocial comorbidities can disrupt adherence and persist as barriers to sustained biomedical management [26]. Consequently, addressing psychosocial factors and optimizing QoL is instrumental in augmenting HIV management [18].

HIV-Related Stigma/Discrimination

It is widely recognized that HIV-related stigma remains prevalent, negatively impacting QoL amongst PLHIV [4, 23, 24, 27, 28]. HIV-related stigma reflects the devalued status that society attributes to PLHIV, encompassing negative beliefs, feelings and attitudes [29, 30], and often manifests as discrimination and unjust treatment. Additionally, HIV-related stigma can be experienced as internalized stigma, considered to be negative feelings and beliefs about HIV applied to oneself [24, 31], which can damage self-esteem and psychological QoL [31,32,33] and can prevent PLHIV from satisfying social and medical needs [33, 34]. In Australia, there are high rates of transmission among men who have sex with men (MSM; [18]). Other populations deemed ‘at risk’ of HIV transmission are people who inject drugs, transgender people, people who engage in sex work, prisoners, and other incarcerated people [35]. Consequently, researchers suggest that PLHIV can experience multi-layered stigma, relating not only to their HIV status but also their membership of a minority group [22, 28, 32]. This has been associated with compounding deleterious effects on QoL [22, 29, 36].

Social Disconnection

Social connection is an individual’s perception of belonging to a social network of satisfactory support, affection, and mutual aid [14]. It can be considered as structural (i.e., the size of the network, or quantity of connections) or functional (i.e., the perceived quality of connections; [37,38,39]). The literature has established a strong relationship between greater perceived social connectedness and greater QoL among PLHIV [18, 40, 41], in addition to documenting the protective and stress-buffering effects of social support [1, 42,43,44]. However, research also suggests that in general, PLHIV report social disconnection [18] and poor social support satisfaction [1, 45, 46].

The association between HIV-related stigma and social disconnection is well documented [42, 43, 46]. HIV-related stigma has been strongly associated with concerns about disclosing HIV-status, and subsequent non-disclosure [37, 47]. The degree of disclosure has been positively associated with social support satisfaction [45], with disclosure concerns, and subsequent non-disclosure, associated with poorer perceived social support and QoL [1, 48,49,50,51]. Similarly, disclosure can result in negative reactions and reduced social support due to stigma [52, 53], and ultimately poorer QoL [15, 54]. Conversely, social support has been shown to mediate the detrimental effects of stigma on QoL and depression [43]. Collectively, the literature demonstrates a complex relationship between HIV-related stigma, social connection and QoL.

Mental Health Difficulties

Research indicates that mental health disorders are more prevalent among PLHIV compared to the general population [42, 55,56,57], with a mental health diagnosis associated with poorer QoL [3, 18]. This may be due to the unique psychosocial challenges faced by PLHIV, such as disclosure concerns, disclosure decision making, and changes to social networks following diagnosis [1, 42, 44], which make these individuals particularly vulnerable to psychological distress [3]. There is also some suggestion that those with a pre-existing psychiatric conditions may be more vulnerable to contracting HIV as a result of sexual risk-taking [58], a pathway which also likely impacts QoL.

The literature also points to a complex relationship between stigma and mental health [42, 50], where stigma and discrimination can create harmful social environments which may detrimentally impact mental health [22]. Consequently, stigmatized minority groups are likely at greater risk of developing mental health disorders [59], which can impact QoL. Given HIV disproportionately affects traditionally marginalized groups, compounding stigma sources place PLHIV at an elevated risk of developing mental health concerns [22, 28, 59].

Mental illness is generally associated with poorer perceived social connectedness, with social withdrawal a transdiagnostic symptom of many psychiatric disorders [60], suggesting mental health difficulties may exacerbate the relationship between stigma and social disconnection referred to earlier [48, 50, 52, 54]. The literature to date considers the impact of these variables on QoL, though the specific relationship between them has so far not been investigated.

The Present Study

Much of the existing literature regarding the factors associated with QoL has been conducted internationally. Psychosocial factors, including stigma, differ according to sociocultural contexts [27]. Therefore, the international literature may not accurately reflect the experiences of PLHIV in Australia, and research is required to identify whether international trends are reflected in an Australian cohort given approximately 80% of PLHIV in Australia live in urban regions that are generally well resourced [18]. Moreover, the existing literature primarily explores the impact of psychosocial variables on QoL in isolation, rather than considering their impact comorbidly.

The present study aims to explore the relationships between factors which impact QoL in a well-resourced, urban context. Although the inclusion of the ‘fourth-90’ focuses on HRQoL, the present study sought to investigate the broader concept of QoL. This allowed the inclusion of sociodemographic variables, which likely impact functioning and QoL, to be included in addition to health-specific factors, and the use of a QoL scale which has been empirically validated with an Australian sample of PLHIV. It is also consistent with the current New South Wales (NSW) and national Australian HIV Strategies, which specifically include a QoL target [35, 61]. The study explores the relationships between psychosocial factors and the subsequent impact of these relationships on QoL. More specifically, it is hypothesized that HIV-related stigma, social connectedness, and mental health will predict QoL. It is also hypothesized that social connectedness will mediate the relationship between HIV-related stigma and QoL. Additionally, it is expected that mental health will moderate the mediation between HIV-related stigma and social connectedness to impact QoL.

Methods

Participants

Participants were a sample of 122 patients recruited from The Albion Centre (Albion), a multidisciplinary HIV treatment centre in Sydney, Australia. This sample represents approximately 10% of PLHIV accessing Albion for medical HIV care. Participation was voluntary for clients over 18 years-old, proficient in English language, living with HIV and attending Albion for HIV specialist medical care. Questionnaires could be completed online or on paper. One participant was excluded due to missing data.

Measures

The PozQoL is a 13-item self-report scale specifically designed to assess QoL for PLHIV [13]. It explores QoL across four domains: health concerns, psychological, social, and functional. Each domain is measured by three or four items, rated along a five-point Likert scale ranging from ‘not at all’ (1) to ‘extremely’ (5). Higher scores indicate higher QoL. The PozQoL has been empirically validated within an adult Australian sample of PLHIV, demonstrating good reliability (Cronbach α = 0.95) and validity [13, 60, 62], and identifies specific cut-offs for qualitative appraisals of QoL (Low, Moderate, High, Very High).

The Scale of Perceived Social Support in HIV (PSS-HIV) is a 12-item self-report measure that evaluates perceptions of social support among PLHIV [38]. It assesses social support satisfaction through exploring the quality, not quantity, of contacts [63]. The PSS-HIV comprises three sub-scales which capture different levels-of-need within social support [38]. This includes belonging (two-items); esteem (four-items); and self-development (six-items). Each item is rated on a five-point Likert scale, ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5). Scores range from 12 to 60. Higher scores indicate higher perceived social support. The PSS-HIV has been validated among PLHIV, demonstrating good reliability (Cronbach α = 0.91) and validity [38, 64].

The HIV Stigma Scale-Short Form (HSS-SF) is a 12-item self-report measure that explores perceptions of HIV-related stigma among PLHIV, in the domains of personalized stigma, disclosure concerns, concerns about public attitudes, and negative self-image [65]. Each domain is measured by three items rated on a four-point Likert scale, ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (4) (6). Scores range from 12 to 48. Higher scores indicate higher perceived HIV-related stigma. The HSS-SF has demonstrated good reliability (Cronbach α > 0.7 for all domains) and validity within HIV populations [65, 66].

The Diagnostic and Statistical Manual, 5th Ed (DSM-5) Level 1 Cross-Cutting Symptom Measure-Adult (DSM-XC) is a psychiatric self-report clinical screening tool [67]. The DSM-XC comprises 23-items that assess the symptomology of 13 psychiatric domains. Each item is rated on a five-point Likert scale, ranging from ‘none’ (0) to ‘severe’ (4), which aims to assess the presence and severity of specific symptoms in line with respective DSM-5 criterion [67]. Higher scores indicate a higher degree of mental health symptomology (i.e., poorer mental health). The DSM-XC is typically used for clinical purposes; however, it has demonstrated utility in research settings [68,69,70,71]. The DSM-XC was selected as it screens a broad range of mental health disorders, facilitating more meaningful information compared to other measures which are limited to fewer psychiatric categories [70]. Notably, substances listed in Question 23 use US drug names and were therefore adapted to suit an Australian cohort (i.e., ‘Vicodin’ changed to ‘opioid/codeine-based medications’; ‘Adderall’ changed to ‘Dexamphetamine’).

Procedure

A research advisory group, comprising researchers and clinicians in the HIV sector as well as PLHIV peers, were involved in the design of the study. Ethics approval was obtained from the University of Technology Sydney (UTS; HREC ETH21-5827) and South Eastern Sydney Local Health District (SESLHD; HREC 2020/ETH01434). Recruitment strategies included waiting room flyers, clinician recruitment, and SMS recruitment due to COVID-19 limitations. Data collection occurred from February 2021 until September 2021. Participation involved completing measures on Qualtrics [72], a secure questionnaire platform regularly used in research settings. Participants could elect to complete the questionnaires online (via a QR-code or URL) or on paper. Additionally, consent was given by participants to access their medical record for information, such as VL and illness duration. Participation took approximately 25 min, and participants were provided a $25 grocery voucher for their time.

Statistical Analysis

Bivariate Pearson’s correlation analyses were conducted to explore potential relationships between the variables. A multiple linear regression analysis was conducted to explore hypothesis 1 and ascertain whether the variables of interest predicted the dependent variable (QoL). Exploratory analyses were conducted using the SPSS v.27 (SPSS v.27, Armonk, NY, USA) ‘PROCESS’ macro (v. 3.5.3; [73]), to explore whether specific relationships between the variables predicted the dependent variable. Hypothesis 2 was tested through a mediation analysis (PROCESS macro model 4), exploring the indirect effects of stigma (independent variable) on QoL (dependent variable), through social connectedness (mediating variable). Hypothesis 3 was tested through a moderated mediation analysis (PROCESS macro model 7), exploring conditional indirect effects. That is, whether the relationship between stigma (independent variable) and social connectedness (mediating variable) varied at different levels of mental health symptomology (moderating variable), which in turn effects QoL (dependent variable).

Results

The assumptions of a multiple regression analysis were tested and satisfied using SPSS v.27. This included multicollinearity, which was found to be within acceptable limits (no VIF value greater than 2 for any study variable), and normality (as assessed using histograms and normal Q–Q plots). Descriptive statistics provided information regarding demographic and independent variables. Items on measures were recoded, and subscales/totals summed, according to their respective instructions.

Demographic Information

Demographic information is described in Table 1. Categorical variable groups were collapsed according to the number in each category, if the merge made conceptual sense. For example, ‘Transgender’ and ‘Other’ were collapsed into one category because of the low numbers in each cell. The mean age of participants was 50.32 years (SD = 12.85; range 27–77 years). The sample predominantly comprized male participants (n = 107 [87.7%]; Table 1), who identified as gay/queer (Table 1), consistent with the HIV-epidemic profile in Australia. The mean illness duration among participants was 16.29 years (SD = 10.58, range 0.5–38 years). Regarding participants’ VL, there were n = 4 missing; n = 117 undetectable VL; and n = 1 detectable VL.

Table 1 Demographic information
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Descriptive Statistics

Descriptive statistics for questionnaires to measure HIV-related stigma (HSS-SF- HIV), perceived social support (PSS-HIV) and mental health symptomology measures (DSM-XC) are shown in Table 2.

Table 2 Descriptive statistics
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During the development of the PozQoL, the researchers noted a broadly even distribution across the qualitative markers of QoL [13, 74]. The PozQoL results in the present study reflect a similar distribution (Table 3).

Table 3 Thresholds for interpreting the PozQoLa [73]
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Bivariate Pearson’s Correlations

Bivariate Pearson's correlations were conducted to assess potential associations between age, illness duration, QoL, HIV-related stigma, perceived social connectedness and mental health symptomology. Table 4 presents a correlation matrix of the primary study variables.

Table 4 Pearson correlation matrix (n = 122)
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Multiple Linear Regression

A multiple regression analysis was conducted to predict QoL from age, illness duration, gender, income level, HIV-related stigma, perceived social disconnection and mental health symptomology. The respective reference groups (comprising the greatest number of participants) were ‘male’ and ‘$0–$37,000’. For the purpose of these analyses, income was used as a proxy for socio-economic status (SES), which has occurred in previous studies (e.g., [75]).

The multiple regression model 1 significantly predicted QoL, (F[6, 115] = 3.14, p 0.007, adj. R2 = 0.096). The independent variables included in model 1 explained 9.6% of the variance in QoL. The multiple regression model 2 significantly predicted QoL, (F[9, 112] = 25.68, p < 0.001, adj. R2 = 0.647), with the independent variables explaining 64.7% of the variance in QoL. The respective regression coefficients are outlined in Table 5.

Table 5 Multiple regression results for QoL (n = 122)
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Mediation Analysis

A mediation analysis (Fig. 1), using PROCESS macro model 4 [73], explored hypothesis 2. HIV-related stigma was negatively and significantly associated with perceived social connectedness (t = − 3.157, p < 0.002, 95% CI − 0.5500: − 0.1260). Social connectedness was positively and significantly associated with QoL (t = 4.299, p < 0.001, 95% CI 0.1850; 0.5011) and HIV-related stigma was negatively and significantly associated with QoL (t = − 8.767, p < 0.001, 95% CI − 1.0470; − 0.6612). The overall mediation model was supported, with a negative and significant indirect effect of HIV-related stigma on QoL, operating through social connectedness (F[1,120] = 93.727, IE = − 0.116, 95% CI − 0.2325; − 0.0354).

Fig. 1
figure 1

General pathway model describing social connectedness as a mediator for the relationship between HIV-related stigma and QoL, based on the PROCESS macro model 4 [73]. **p < 0.001, *p < 0.05

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Moderated Mediation Analysis

A moderated mediation analysis, using PROCESS macro model 7 [73], was performed to explore hypothesis 3. In this model (Fig. 2), HIV-related stigma was negatively, yet non-significantly, associated with social connectedness (t = − 1.976, p 0.051, 95% CI − 0.4479; 0.0005), while mental health was negatively and significantly associated with social connectedness (t = − 2.986, p < 0.003, 95% CI − 0.2683; − 0.0543). The relationship between social connectedness and QoL was positive and significant (t = 4.299, p < 0.001, 95% CI 0.1850; 0.5011). The relationship between HIV-related stigma and QoL was negative and significant (t = − 8.767, p < 0.001, 95% CI − 1.0470; − 0.6612). The 95% confidence interval for the index of moderated mediation contained zero (t = 0.188, p < 0.851, 95% CI − 0118; 0.0142), suggesting there were no differences in the indirect effects at different levels of the moderator.

Fig. 2
figure 2

General pathway model describing mental health as a moderator for the mediated relationship between HIV-related stigma and QoL, based on the PROCESS macro model 7 [73]. **p < 0.001, *p < 0.05

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Independent Samples T-test

An independent samples t-test compared the QoL mean scores for those obtained pre-COVID lockdown (n = 45) to those that were completed during lockdown (n = 77), and no significant difference was found (t[120] = − 0.89, p = 0.137).

Discussion

While there is a significant evidence-base regarding the factors associated with QoL in PLHIV, there are relatively few Australian studies which have considered the variables comorbidly and explored how the relationships between them impact QoL. There was variability in QoL ratings among the present sample, consistent with previous research conducted among PLHIV in Australia [13, 18]. The results discussed below provide insight into this variability.

Independent Effects of Stigma, Connectedness, and Mental Health Symptomology on QoL

This Australian-based study indicates HIV-related stigma, social disconnection, and mental health symptomology significantly predict QoL, consistent with international literature. In the present study, PLHIV who reported worse HIV-related stigma experienced poorer QoL. The construct of HIV-related stigma is multifaceted, covering internalized stigma, overt rejection and discrimination, and/or anticipated social stigma [24, 34], and each stigma-mechanism has been shown to negatively impact QoL [31, 35, 76, 77]. In the present study, although the HSS-SF only captured HIV-related stigma, the compounding deleterious effects of multi-layered stigma, including related to minority group status (e.g., MSM), may also contribute to this relationship [22, 29, 36].

As expected, a significant positive relationship was found between social connectedness and QoL, consistent with previous research [18, 40]. Social support has protective and stress buffering effects which not only improve QoL [41, 78], but may also protect against the effects of stigma and psychological distress [28, 40, 43, 44, 76] and promote coping following an HIV diagnosis [1]. In particular, the stress buffering effects of emotional support have been shown to improve QoL among PLHIV [41, 79]. Our findings suggests that the inverse may also be true, where social disconnection predicts poorer QoL.

Finally, increased mental health symptomology predicted poorer QoL in the current sample. It is well understood that the prevalence of mental health symptomatology in PLHIV is greater than the general population (e.g., [41]). More recently, the risk of composite mental illness, or comorbidity, has been found to be higher in PLHIV [80]. Given the established association between mental health and QoL (e.g., [18]), the present results are consistent within this context.

The Relationship Between HIV-Related Stigma, Social Connectedness and QoL (Mediation Analysis)

While the evidence-base consistently reflects the associations discussed, relatively little research has explored the specific relationship between the variables, and their overall impact on QoL; understanding this, especially with an Australian cohort of PLHIV, is an important step in addressing these concerns. A mediation analysis was conducted to explore the relationship between psychosocial comorbidities and the subsequent impact of these relationships on QoL. Higher perceived HIV-related stigma was associated with poorer perceived social connectedness. Previous research suggests this may be due to the harmful effects of non-disclosure on social support satisfaction [47,48,49] and/or adverse reactions following disclosure [15, 53]. Recent surveillance data highlights the prevalence of HIV-related stigma in Australia, with more than half of respondents reporting the experience of stigma related to their HIV-status in the preceding 12-months, including from healthcare workers [18]. In the same survey, almost one third of participants noted that ‘almost nobody knows about my HIV’ [18], pointing to the link between HIV-related stigma and disclosure demonstrated in other Australian studies [27]; this ultimately has the potential to negatively impact social connectedness. In the present study greater perceived social connectedness was associated with greater QoL, and higher levels of HIV-related stigma were associated with poorer QoL [4, 23, 28]; as such a significant indirect effect of HIV-related stigma on QoL, operating through social connectedness, is indicated.

Several mechanisms are proposed to explain the link between HIV-related stigma, connectedness and QoL. The first pertains to the perceived quality of social support, a major component of social connectedness. Previous research has demonstrated that the degree of personal disclosure is positively associated with social support satisfaction [44]. However, stigma can influence how PLHIV navigate the challenging terrain of disclosure within relationships [1, 81]. Consequently, HIV-related stigma has been strongly associated with non-disclosure [37, 46], as a stigma-avoidant coping mechanism to preserve connectedness [82, 83]. Paradoxically, if personal disclosure enhances social connection, the effects of stigma and non-disclosure may create a barrier for connection with others. Consequently, stigma and non-disclosure have been previously associated with poorer perceived social support and QoL [1, 29, 47, 48, 77]. Additionally, some research suggests that stigma can be associated with unsupportive and adverse reactions following HIV disclosure [15, 45, 52, 53]. Therefore, stigma may enhance social disconnection which ultimately negatively impacts QoL.

Conversely, the protective and stress-buffering effects of social support may lessen the negative consequences of stigma on QoL. Researchers have found that social support can mitigate the harmful effects of stigma on QoL among PLHIV [42]. Similarly, the protective and stress buffering effects of social support have been well-documented and suggest greater perceived social connectedness may have the potential to reduce the harmful effects of stigma on QoL [1, 18, 28, 32, 39, 41, 43, 76, 78]. Our findings are consistent with international trends and indicate a complex relationship between HIV-related stigma, social connectedness and QoL in an Australian context, and further our understanding of these relationships.

The Relationship Between HIV-Related Stigma, Social Connectedness, Mental Health and QoL (Moderated Mediation)

While the significant mediation model provides insight into the complex relationship between HIV-related stigma, social connectedness and QoL, it neglects the important role of mental health. A moderated mediation model was assessed to explore the impact of mental health on the relationship between stigma, connectedness and QoL. In the present study, mental health symptomology was significantly associated with poorer perceived social connectedness. This may be due to social withdrawal, a transdiagnostic feature of many psychological disorders [59]. It may also relate to the source of support; though the present study did not formally assess this, the importance of peer/community engagement for MSM and the associated positive impact on mental health symptomatology [84] cannot be discounted. It is, therefore, possible these results might reflect the absence of such support. Interestingly, HIV-related stigma was negatively, yet not significantly, associated with social connectedness in this model. This is inconsistent with the mediation results and previous research discussed above.

Contrary to hypothesis 3, the overall moderated mediation model was not supported suggesting worsening levels of mental health symptomology did not exacerbate the effects of stigma on connectedness to impact QoL. The Pearson’s correlation analysis suggests that mental health symptomology was highly correlated with all study variables. Additionally, previous research demonstrates a relationship between mental health and stigma [3, 59]; social connectedness [42]; and QoL [18]. The inclusion of mental health symptomatology to the model clearly changes the relationship between stigma and connectedness, and their impact on QoL, which suggests that mental health is implicated in this relationship; however, its effects were not captured by this model. Alternatively, it is possible that mental health symptomology is intrinsically related to stigma, connectedness, and mental health, such that the independent effects of mental health could not be determined statistically. To the authors’ knowledge, this is the first study to explore mental health as an independent variable in this way. Future research could explore the way in which mental health impacts QoL as a psychosocial comorbidity.

It is noteworthy that data collection partly occurred when the 2021 State government restrictions on face-to-face consults were in place, as part of the pandemic response to COVID-19, which may have impacted QoL. However, the independent samples t-test indicated no significant difference in QoL scores among PLHIV before and during the lockdown. This suggests that the findings discussed above reflect generalizable psychosocial challenges which impact QoL among PLHIV in Australia.

Limitations

Due to the cross-sectional nature of this research design, true causality and mediation cannot be confirmed; as such, inferences should be drawn with caution. Moreover, utilizing the DSM-XC as a measure of mental health in the context of research bears limitations. The DSM-XC was used to measure mental health as it is brief, readily available and covers mental health symptomology across multiple psychiatric disorders. However, the measure is primarily used in a clinical setting to screen for mental health symptomology and is not diagnostic. Additionally, it is possible that the DSM-XC is too broad and does not account for the potential impact of symptoms—just their presence. The above limitations may have negated the study’s capacity to accurately capture mental health, which could explain the results of the moderated mediation analysis. Therefore, the results discussed above should be interpreted cautiously.

Directions for Future Research

While the present study has contributed to our understanding of QoL in an Australian sample, the model explained 64.7% of the variance which suggests other factors which were not captured and should be the focus of future research. The present findings suggest that psychosocial comorbidities impact QoL in a complex way. Previous research demonstrates that mental health remains prevalent among PLHIV [55, 57, 79], and the results suggest that mental health is strongly correlated with all study variables and poorer QoL. However, the moderated mediation analysis suggests that mental health does not interact with psychosocial comorbidities to impact QoL as initially predicted. Therefore, the impact of mental health on QoL, and its relationship with the other variables of interest, remains unknown and requires further exploration. Additionally, research considering the specific forms of stigma and social connection may be warranted to further explore the intricacies of these variables. It is also possible that reports of social connectedness and mental health were impacted by the COVID-19 lockdown; as such, a replication study is recommended.

Implications

The present study provides a novel analysis of the relationship between the variables of interest and how they impact QoL in an Australian context. While existing literature considers the impact of psychosocial variables on QoL, the variables are often considered in isolation; however, these factors often present comorbidly. The mediating effect of social connectedness on the relationship between HIV-related stigma and QoL offers new insights into the complexities of these relationships, providing guidance for clinical intervention.

The findings of the present study were consistent with QoL trends reported in international literature, reflecting that many psychosocial challenges experienced by PLHIV are universal. It is noteworthy that 117 of the 122 participants had achieved VL suppression, highlighting that, despite effective biomedical management, the residual impact of psychosocial comorbidities ultimately detrimentally effects QoL. This supports previous research, suggesting QoL among PLHIV extends beyond traditional medical targets [19]. It is possible, therefore, that QoL among PLHIV in Australia may be more closely linked to psychosocial than biomedical factors [5, 18], strengthening the argument that optimal HIV-management should extend beyond viral suppression. Failing to do so likely ultimately limits the effectiveness of a purely medical healthcare delivery model. The present results support the evolution of HIV-management towards a multidisciplinary model of long-term condition management, whereby psychosocial services play an integral role to holistically optimize QoL.

The results of the present study also demonstrate the importance of specific factors in understanding QoL, providing practitioners with a point of clinical intervention. This is important when considering the Australian Eighth National HIV Strategy, as well as the current NSW: 2021–2025 strategy, which include a QoL target for the first time [35, 61]. This study also strongly supports consideration of the psychosocial determinants of QoL and is consistent with recent Australian Standards for Psychological Support for Adults with HIV [85]. Specifically, interventions to reduce stigma surrounding HIV to improve QoL among PLHIV might be beneficial, in addition to targeting social connectedness to minimize the harmful effects of stigma and improve QoL. There is scope to do this at an organizational level; research suggests that the type of social support (i.e., emotional) is more important than the source of support (e.g., friend versus clinician; [42]), highlighting the important role of mental health practitioners and the therapeutic process itself. Additionally, healthcare services could create avenues to promote connectedness at an individual level, such as optimizing patient supports or implementing peer support programs. Clinical psychosocial interventions could focus on reducing the impact of stigma on mental health, social support, healthcare access and capacity to engage in medical care. This is particularly important when considering the current NSW HIV Strategy: 2021–2025, which explicitly includes a stigma reduction target [32].

Conclusions

These findings suggest that HIV-related stigma, perceived social connectedness and mental health symptomology are three psychosocial factors that impact QoL among PLHIV in Australia. The results suggest that when these psychosocial factors occur together, the effects of stigma on QoL can operate indirectly through social connectedness. While the present study did not fully capture the relationship of mental health symptomatology to these factors, it is clearly implicated. Collectively, these findings indicate a complex relationship between mental health, stigma, connectedness and QoL, which likely varies across individuals and requires further investigation. By developing this understanding further, practitioners can ensure optimal healthcare delivery and contribute to the expansion of the HIV Cascade beyond viral suppression, to work towards improved wellbeing for PLHIV.