Abstract
Background
Alcohol use disorders (AUD) are a common cause of poor treatment outcomes among people with HIV (PWH). In Malawi, routine screening for AUD among PWH is unavailable. We piloted the utility of the Alcohol Use Disorders Identification Test (AUDIT) in screening for AUD among PWH and assessed its adoption, acceptability and fidelity in HIV clinics in Malawi.
Methods
We implemented the AUDIT tool at Mchinji, Kapiri and Kochirira hospitals in Mchinji District between April and May 2021. AUD were defined and classified based on WHO classification as low-risk, harmful/hazardous alcohol use or alcohol dependence. We calculated the prevalence of AUD, the proportion of providers who conducted AUD screening (adoption) and the proportion of providers who conducted AUD screening as intended (fidelity) and compared between clinics. Lastly, we assessed acceptability through a survey among providers.
Results:
Out of 2036 PWH, 875 (43%) were screened for AUD and 51% were female, mean age was 41 years (SD±12) and 338 (39%) had AUD. Adoption was highest at Mchinji (58%) compared to Kapiri (31%) and Kochiria (29%) (P<0.001). Overall Fidelity was 96%, and it was highest at Kapiri (99%) compared to Mchinji (95%) and Kochirira (98%) (P=0.01). AUD screening with AUDIT was highly acceptable as most providers agreed or completely agreed that the AUDIT was important (100%), easy to use (96%), satisfactory (96%), agreed to continue use (61%) and recommended it for other facilities in the district (100%).
Conclusion:
AUD were common among PWH. While the adoption of AUDIT for AUD screening was moderate, acceptability and fidelity were high. The impact of AUD on HIV treatment outcomes needs to be assessed to determine the role of routine AUD screening in HIV clinics in Malawi.
Keywords: Alcohol Use Disorders, People with HIV, Alcohol Use Disorder Test, Adoption, Acceptability, Fidelity
Introduction
The harmful use of alcohol ranks among the top five risk factors for disease, disability and death throughout the world with its net effect being approximately 3 million deaths (5.3% of all deaths) each year (WHO, 2022) Alcohol use is common among people with HIV (PWH). The pooled prevalence of Alcohol Use Disorders (AUD) among PWH is estimated at 30% worldwide (Duko et al., 2019). In Africa, the prevalence of AUD among PWH is high with hazardous alcohol use alone accounting for an estimated at 34% (Duko et al., 2019).
Among PWH, hazardous alcohol use is associated with poor adherence to ART resulting in poor HIV viral suppression, which may lead to opportunistic infections and death (Azar et al., 2010; Hendershot et al., 2009). In addition, hazardous alcohol use is associated with risky sexual behaviors such as having unprotected sex and multiple sexual partners (Azar et al., 2010; Hendershot et al., 2009).
The Alcohol Use Disorders Identification Test (AUDIT) is a 10-item screening tool developed by the World Health Organization (WHO) to assess alcohol consumption, drinking behaviors, and alcohol-related problems (Piccinelli et al., 1997; Saunders et al., 1993). AUDIT is a highly suitable screening tool for all types of alcohol use disorders (AUD) and can be used by both health professionals and non-health professionals in any setting (Babor et al., 2001). Utilization of the AUDIT in screening for AUD in PWH is very important for early identification and provision of effective care and management and ultimately, improve treatment outcomes (Kresina et al., 2016).
To date, screening for AUD using AUDIT is not standard of care for PWH in Malawi, hence data on the burden of AUD in this population is scarce. We estimated the burden of AUD among PWH and assessed the adoption, acceptability and fidelity of using the AUDIT tool for screening of AUD among PWH attending HIV clinics in Mchinji District, Malawi.
Materials and methods
Study design and setting
We conducted a cross-sectional implementation study testing the adoption, acceptability and fidelity of the AUDIT tool in AUD screening among PWH in HIV clinics. The study was conducted at Mchinji District Hospital, Kapiri Mission Hospital, and Kochirira Mission Hospital in Mchinji district, Malawi, between the April and May 2021. Mchinji district is a busy transborder trade district which borders Zambia. It has a population of about 630,560 people. Together, Mchinji district hospital, Kochirira and Kapiri hospital cater to a catchment population of about 171,333 people with about 31,320 PWH. HIV care is largely provided by clinicians (nurses, clinical officers and medical assistants) at the facilities with the help of expert clients and health surveillance assistants (HSAs) who mainly provide services such as dispensation of antiretroviral therapy (ART) in the community. Health services within the district are managed by the District Health Management Team (DHMT).
Study population
Our study population consisted of HIV care providers (clinicians, nurses, clinical officers, medical assistants) at the outpatient HIV care clinics at the three facilities, and DHMT members and policy makers who participated in a survey. In addition, we used records of PWH who attended the facilities during the study period.
Community engagement and training
To ensure good implementation of the AUDIT tool, we conducted local consensus meetings with community leaders and DHMT members to obtain buy-in, and trained clinic staff on use of the AUDIT and conduct of the study. We conducted three consensus meetings with traditional leaders and trained healthcare providers.
Data collection
Using a study-specific data collection form, we collected data on the number of PWH who accessed care at the study facilities and their demographic characteristics (age and sex) from HIV clinic records. The AUDIT tool was distributed to all provider clinic rooms and collected from the clinic rooms daily for data entry. The outcome of AUD screening (AUDIT score) and the full details of the AUDIT assessments were recorded on the AUDIT tools by the providers and abstracted to a data collection form.
Acceptability survey
Further, we administered a Likert scale survey to assess acceptability. The acceptability survey was developed by combining constructs from the acceptability of intervention measure (AIM), feasibility of intervention measure (FIM) and the intervention appropriateness measure (IAM). The survey was administered to purposively selected clinicians, expert clients and policy makers. The scale ranged from 1 to 5 (1 = completely disagree, 2 = disagree, 3 = neutral, 4 = agree and 5 = completely agree)
Classification of AUD and outcome measures
We classified alcohol use disorders using AUDIT decision tree as published by the WHO: total abstinence (AUDIT score 0), low-risk drinking use (AUDIT score: 1 – 7), harmful/hazardous use (AUDIT score: 8 – 14), and alcohol dependence (moderate to severe use) (AUDIT score: ≥15 )(WHO, 2013).
The burden of AUD among PWH was calculated as the proportion of PWH who screened positive out of all the PWH who were screened for AUD during the study period at the three facilities. To assess adoption of the AUDIT tool for AUD screening by providers, we calculated the proportion of PWH screened for AUD against the number of PWH who attended the three facilities during the study period. Fidelity of the providers to use of the AUDIT tool was calculated as the proportion of AUDIT tools that were fully completed versus the total number of AUDIT tools completed. The prevalence, adoption and fidelity were compared between facilities using the test of proportions at α=0.05 significance level. The acceptability of using the AUDIT to screen for AUD among HIV clinic by providers, expert clients, and policy makers was calculated as a percentage for each of the Likert scale responses.
Statistical analysis
We summarized categorical variables using frequencies and percentages. The association between categorical variables was assessed using either chi-square test or Fisher’s exact test, depending on the expected cell counts. For variables with more than two categories, analysis of variance (ANOVA) was used. For normally distributed continuous variables, we presented the mean and the corresponding standard deviation (SD). Statistical significance was evaluated at 0.05 alpha level. All statistical analyses were performed using STATA version 16 software.
Ethical consideration
The study was reviewed and approved by National Health Sciences Research Committee and permission to conduct this study was obtained from District Health Officer for the Mchinji District Health Office. All participants provided informed consent to participate in the study.
RESULTS
Between April and May 2021, there were 2036 PWH who visited the three facilities. Of the 2036 PWH, 875 (43.0%) were screened for AUD by providers using the AUDIT tool. At Mchinji district hospital, Kapiri hospital, and Kochirira hospital, 525/902 (58%), 250 /795 (31%), and 100/339 (29%) were screened for AUD, respectively. The adoption of AUD screening using AUDIT was highest at Mchinji compared to the other facilities (P<0.001) (Table 1). Of the 875 that were screened for AUD the mean age was 41 years (SD ±11) and 51% were females (Table 1). We interviewed 24 DHMT members and HIV care providers for the qualitative survey.
Table 1:
Demographic characteristics among PWH who attending HIV clinics at Mchinji, Kochirira and Kapiri hospital and AUDIT screening and implementation outcomes
| ALL | MCHINJI | KOCHILIRA | KAPIRI | p-value | |
|---|---|---|---|---|---|
| PWH visiting facility | 2036 | 902 | 339 | 795 | |
| Level of adoption n (%) | 875 (43) | 525 (58) | 100 (29) | 250 (31) | <0.001* |
| n=875 | |||||
|
| |||||
| Age | |||||
| Mean (±SD) | 41(12) | 39 (11) | 38 (12) | 45 (12) | <0.001** |
| Gender, n (%) | |||||
| Male | 425 (49) | 220 (42) | 27 (27) | 178 (71) | <0.001* |
| Female | 448 (51) | 304 (58) | 72 (73) | 72 (29) | |
| AUDIT score | |||||
| Median (IQR) | 0 (0, 12) | 0 (0, 3) | 0 (0, 0) | 12 (0,19) | <0.001** |
| AUD Diagnosed, n (%) | |||||
| Abstinence | 508 (60) | 358 (72) | 78 (78) | 72 (29) | |
| Low risk | 65 (8) | 35 (7) | 11 (11) | 19 (8) | <0.001* |
| Harmful/hazardous | 103 (12) | 32 (6) | 8 (9) | 63 (25) | |
| Alcohol dependence | 170 (20) | 72 (15) | 2 (2) | 96 (38) | |
| Fidelity, n (%) | |||||
| Yes | 840 (96) | 497 (95) | 98 (98) | 245 (99) | 0.012* |
| No | 33 (4) | 28 (5) | 2 (2) | 3 (1) | |
29 had missing AUD diagnosis. 2 had missing fidelity responses, p-value from:
Chi-squared/Fisher’s exact test,
ANOVA test.
Out of the 875 screened for AUDs, 338 (39%) screened positive for AUDs using the AUDIT tool. Out of those screened positive for AUD, 19% (65/338) had low risk AUD, 30% (103/338) had harmful/hazardous use, and 50% (170/338) had alcohol dependence (Figure 1). We found that Kapiri had the highest prevalence of AUD among the three hospitals with a rate of 71% (178/250), which was significantly higher than Mchinji’s 29% (139/524) and Kochirira’s 21% (21/99) (P<0.001). Similarly, Kapiri had the highest AUDIT median score of 12 (IQR: 0,19) compared to Mchinji (0 IQR: 0,3) and Kochirira (0 IQR: 0,0) (P<0.001) (Table 1).
Figure 1:
AUD screening and distribution of AUD among people with HIV in HIV clinics in Mchinji District
Overall, fidelity of use of the AUDIT tool was 96% (840/875). Kapiri had the highest level of fidelity (99%) compared to Mchinji (95%) and Kochirira (98%) (P=0.012) (Table 1). The adoption of AUDIT based on the survey results was perceived to be high. The majority agreed or completely agreed that it is easy to use (96%), important (100%) and reliable (92%) (Figure 2).
Figure 2:
Adoption of AUDIT tool for AUD Screening among providers
For the acceptability survey, the acceptability of the AUDIT as a screening tool for AUD was high among providers, DHMT members, and policy makers. Most participants either agreed or completely agreed that the AUDIT tool was easy to use (96%), time saving (71%), made work easy (100%), satisfactory (96%), easy to use (96%), important (100%) and recommend for all facilities in Mchinji district (100%) and expressed interest to continue using AUDIT (61%). Most participants also completely disagreed or disagreed that the AUDIT interfered with work (100%), increased workload (84%), had low expertise to use AUDIT (91%), and that AUD screening negatively affected with routine work (96%) (Figure 3)
Figure 3:
Acceptability of AUDIT tool for AUD Screening among Providers
Discussion
This study assessed the adoption, acceptability and fidelity of the AUDIT as a screening tool for alcohol use disorders among people with HIV attending HIV care clinics in Malawi. To our knowledge this is the first study conducted to assess the use of the AUDIT tool in screening alcohol use disorders among PWH in Malawi. We found that the adoption of the AUDIT tool was moderate while acceptability and fidelity were high. Furthermore, alcohol use disorders were common among PWH.
Generally, data on adoption, acceptability and fidelity of the AUDIT tool among healthcare workers is scarce locally and within the region, and our study addressed this important gap. A study of health service managers in South Africa found that health worker perceptions and attitudes towards an innovation were important determinants of adoption of interventions (Brooke-Sumner et al., 2019). Surprisingly, though the perceptions and attitudes towards the AUDIT tool assessed through the adoption and acceptability surveys seemed favorable, adoption was moderate. We observed differences in the level of adoption across the three facilities with one facility (Kapiri) registering low level of adoption. In addition, other organizational readiness factors such as resource perceptions, motivation, organization culture, and change commitment and efficacy may have equally influenced the levels of adoption across the sites, though not directly measured in this study. Qualitative assessment would have been useful to validate if the structural factors above impacted our results.
Despite the moderate level of adoption, the AUDIT tool was highly acceptable. Acceptability of an intervention by participants is critical for its successful implementation and acceptability is augmented by knowledge of an intervention (Weiner, 2009; Wilhelm et al., 2016). In our study, we conducted consensus meetings and trained healthcare providers, DHMT members and traditional leaders. We believe the consensus meetings and training may have contributed towards good knowledge and understanding of our intervention thereby creating buy-in and potentially influencing the level of acceptability. In addition, other implementation drivers such as competence and leadership drivers, not measured in this study, may have influenced the level of adoption. Understanding the barriers to adoption can provide valuable insights into how to improve implementation and increase the uptake of the AUDIT tool.
Similar to acceptability, fidelity of use of the AUDIT tool was high. This suggests that despite the challenges with adoption, due to the high acceptability, providers who used the AUDIT tool implemented it with a high degree of accuracy and consistency. Additionally, the high fidelity may also suggest that the AUDIT tool is user-friendly and can be implemented at primary and secondary care facilities in resource-limited settings. Our findings suggest that if barriers to adoption are addressed, screening of AUD using the AUDIT tool can be well adopted and used well. However, reporting bias and social desirability bias may have influenced the high level of acceptability.
Surprisingly, the burden of alcohol use disorders of 39% in our study was slightly higher than we expected for our setting. The AUD prevalence in our study was higher than pooled prevalence of 29.8% (Duko et al., 2019) and 31.52 % ( Necho et al., 2020) from recent systematic reviews of AUD using AUDIT test results. More studies that assessed alcohol and/or substance use through self-report among PWH have also reported lower burden of AUD. Wandera et al. reported that 33% of participants disclosed any alcohol use, 18.6% reported alcohol misuse, and 5.2% drank at hazardous levels (Wandera et al., 2015).
In our study, the prevalence of hazardous alcohol use was 6 times higher than Wandera et al. and the prevalence of alcohol dependence was alarmingly high (50%). Our results suggest a large burden of alcohol use disorders that necessitate engagement in care, either psychosocial and/or medical. Our findings also highlight the need for larger studies to quantify the burden of AUD, test targeted interventions for alcohol use and harm reduction among PWH and to inform policy in Malawi. Although we did not assess HIV treatment outcomes such ART drug adherence, retention in care and viral load suppression in this study, the high prevalence of alcohol use in our study pose potential threat to HIV treatment outcomes, and potentially undermining progress made towards attaining the third 95% UNAIDS target for viral suppression. It is commendable that the Malawi Ministry of Health recognizes the alarming increase of mental health problems including alcohol abuse (Mental Health Policy (MHP), 2020; MOH, 2017-2022), and the need to provide quality mental health services through evidence-based decision making (Ministry of Health (MOH), 2017-2022) (Manthalu, 2017).
Due to scarcity of local and regional data on the adoption, acceptability and fidelity of use of the AUDIT tool, we could not compare our findings with those of other researchers. Nonetheless, we believe we addressed a very important gap in literature that other researchers will also explore. Another potential limitation of our study could be variations in provider attitudes and perceptions of the AUDIT tool at the three facilities which may have contributed to differences in organizational readiness across the sites, however we did not measure organizational readiness as it was not within the scope of this study. In addition, we did not assess barriers and facilitators to the implementation of the AUIDT tool for AUD screening potentially missing other factors that could have influenced our results. However, our results provide a basis for further research to elucidate the barriers and facilitators to alcohol disorder screening among PWH in Malawi. Lastly, a concurrent assessment of HIV treatment outcomes with the adoption, acceptability and fidelity of the AUDIT tool would have provided a more comprehensive assessment of impact of alcohol use disorders among PWH and would have further amplified the importance of our study. We believe our study is timely and has exposed the need for efforts to implement AUD screening and care among PWH.
In conclusion, AUD among PWH constitute a considerable burden in Malawi and may threaten HIV clinical outcomes. However, research is required to quantify the impact of AUD on HIV clinical outcomes in Malawi to inform policy. The AUDIT tool is user-friendly and highly acceptable; however, barriers should be identified addressed before integrating alcohol use disorder screening to HIV care in resource-limited settings.
HIGHLIGHTS:
Alcohol use disorders are common among people living with HIV in Malawi
Use of the AUDIT tool for AUD screening is acceptable among providers
The use of the AUDIT tool for AUD screening among providers was sub-optimal
Among providers who accept to use the AUDIT tool, level of fidelity is high
Funding
Research reported in this publication was supported by the National Institute of Mental Health of the National Institutes of Health under Award Number U19MH113202. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. MM was supported by the NIH NIAID grant number: D43TW010060, 1U19AI144177 and 75N93022C00024.
Footnotes
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Declaration of competing interest
The authors declare no competing interests.
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