African Journal for Physical, Health Education, Recreation and Dance
(AJPHERD) Supplement 1 (September), 2014, pp. 105-115.
Identification of over-compliant patients and pill dumpers with
the ‘mixed’ pill count method at an antiretroviral treatment
clinic
TITILOPE A. AWOLOLA1 JOHANNA
SUMMERS1 AND SUZANNE JOHNSON2
C.
MEYER1,
BEVERLEY
1
Department of Pharmacy, University of Limpopo (Medunsa Campus), South Africa, P.O. Box
218, Medunsa 0204, South Africa. E-mail: hannelie.meyer@ul.ac.za
2
Foundation for Professional Development, Struland Office Park, The Willows, Pretoria 0184,
South Africa
Abstract
Near perfect levels of adherence to antiretroviral treatment (ART) are required for maximal viral
suppression and avoidance of drug resistance. Pill counts are an objective method of measuring
adherence, but can be invalidated if patients manipulate the number of tablets returned. This
research aimed to investigate whether the ‘mixed’ pill count method was capable of identifying
patients who were engaging in pill manipulation (dumping) at a public sector antiretroviral
(ARV) clinic in South Africa. At baseline, 370 adults on ART were recruited. On the first return
visit, a standard/normal pill count was used to calculate adherence and extra tablets were
dispensed without the patients’ knowledge. At the second return visit, adherence was calculated
with the ‘mixed’ pill count. Patients were grouped into three categories based on calculated
adherence: truthfully non-adherent, adherent and over-compliant. Three hundred and forty-four
(92.9%) patients completed the study. At the second return visit, with the ‘mixed’ pill count, 43
patients (12.5%) were identified as over-compliant based on the adherence calculated for their
regimens. The ‘mixed’ pill count identified pill dumpers, although overall adherence was better
on the second return visit compared to the first. The significance of this research lies in the fact
that it indicates that continuous individual patient counselling and informing patients of their
exact adherence score contributed to motivating them to adhere well to their treatment.
Keywords: Dump, mask, over-compliance, adherence, antiretroviral treatment, mixed pill count.
How to cite this article:
Awolola, T.A., Meyer, J.C., Summers, B. & Johnson, S. (2014). Identification of over-compliant
patients and pill dumpers with the ‘mixed’ pill count method at an antiretroviral treatment clinic.
African Journal for Physical, Health Education, Recreation and Dance, September (Supplement
1), 105-115.
Introduction
Strict adherence to antiretroviral treatment (ART) is essential for treatment
success (Ford et al., 2010). Many patients on ART struggle to take their
medicines consistently for various reasons. It is therefore crucial that health care
providers use efficient and reliable tools to identify sub-optimal adherence and
address the problem timeously.
106 Awolola, Meyer, Summers and Johnson
Current standard measures to assess adherence to antiretrovirals (ARVs) such as
pill counts, directly administered antiretroviral therapy (DAART), therapeutic
drug monitoring, self-reported adherence and electronic medication monitoring
systems (MEMS), all have advantages and limitations (Nachega, Knowlton,
Deluca & Schoeman, 2006; Deschamps et al., 2008; Altice & Springer, 2010).
Presently no accepted ‘gold standard’ exists by which to measure adherence to
ART and the above-mentioned methods are used individually or in combination
(Berg & Arnsten, 2006; Chesney, 2006; Ross-Degnan et al., 2010; Steel,
Nwokike, Joshi & Ntengu, 2011). The need for efficient and reliable measures of
adherence has initiated debate on how best to measure medication-taking
behaviour in public sector ART settings.
Although the pill count is an indirect, objective method to assess adherence, it
tends to overestimate adherence and does not indicate true medication-taking
behaviour in terms of timing and dosage (Ross-Degnan et al., 2010). Evidence
from the literature (Steel et al., 2011) and anecdotal evidence from some ART
sites in South Africa, suggest that the pill count method can be invalidated by
patients if they manipulate the number of tablets returned to the clinic, in an
attempt to appear adherent at the follow-up visit. Allegedly, these patients
deliberately fail to return all their tablets or discard (dump) the remaining tablets
before coming to the clinic for their monthly pill count and medication refill. To
detect the conjectured manipulations, the ‘mixed’ pill count method was
implemented to measure adherence in this study. The ‘mixed’ pill count is a
practice whereby the pharmacist deliberately dispenses extra tablets to a patient
(a predetermined ‘n’ number of extra tablets more than the usual 30-day supply)
and records the number of extra tablets in the patient’s medication file without
the patient’s knowledge. When the patient returns for a repeat prescription at the
follow-up visit, the tablets remaining in the container are counted and the ‘n’
number of extra tablets dispensed is taken into consideration. The hypothesised
advantage of the ‘mixed’ pill count over the ‘normal’ pill count lies in the fact
that patients are not informed that extra tablets have been dispensed. As a result,
it is assumed that the following three scenarios could ensue:
• An adherent patient would return to the clinic with the extra tablets
in the container because he/she is sure that all the tablets were taken as
prescribed, resulting in an adherence rating of 100%.
• A truthfully non-adherent patient would return to the clinic with the extra
tablets (and more) in the container because he/she is not attempting to mask nonadherence and, therefore, would have no need to discard any tablets (including
the extra ones), resulting in an adherence rating of <100%.
• The over-compliant patient (suggestive of masking non-adherence or
‘pill dumping’) would return to the clinic without the extra tablets in the
container because his/her calculation would not have accounted for the “n”
Identification of over-compliant patients and pill dumpers 107
number of extra tablets when manipulating the pill count in order to mask nonadherence, resulting in an adherence rating of >100%.
In all these instances, the extra tablets should act to safeguard the validity of the
pill count. Inability to account for the extra tablets would allow the pharmacist to
easily identify patients who may have attempted to mask non-adherence by
dumping tablets and also allow the health care worker to probe for and address
the issues behind non-adherence masking. The end result would be improved
ability to identify non- adherence, which previously would have been
successfully masked. This study aimed to investigate if the ‘mixed’ pill count
was capable of identifying patients who were engaging in pill manipulation.
Methodology
Study design
A prospective and longitudinal design was followed over a period of six months
at Ntshembo public sector ARV Clinic in Mamelodi Hospital, Gauteng Province,
South Africa.
Study population and sampling
All treatment-experienced patients were invited to participate in the study.
Patients were informed that adherence would be monitored with a pill count, but
were semi-blinded, as they did not know that extra tablets would be added to
their containers during the second study visit (i.e. first return visit). Purposive
sampling was used to select participants who were HIV-positive adults ≥18
years, on first-line ARV regimens and patients who would be receiving their
ARVs at the study site for the full duration of the study period. Patients who
were on TB treatment, pregnant patients and those who were down-referred to
another ART site were excluded from this study. At the end of the recruitment
period, 370 patients were enrolled into the study.
Data collection procedures and instruments
At enrolment (baseline visit) participants were given a normal pill count, all
tablets returned were collected from them and each patient was dispensed the
usual supply of his/her ARV medication. The correct number of tablets
consumed would then be used for adherence calculation at the two return visits.
Patients were reminded to bring their medication containers during return visits.
A questionnaire, available in English and Setswana, was used to record
demographic and clinical data.
108 Awolola, Meyer, Summers and Johnson
On Return Visit 1, patients received a normal pill count and extra dosage units of
each ARV medication were dispensed to them without their knowledge. At
Return Visit 2, patients received a ‘mixed’ pill count. A pill count sheet was used
for the normal pill count as well as the ‘mixed’ pill count, to record the number
of tablets that the patients returned to the clinic. Pill count results were calculated
as a percentage of the expected consumption as follows:
% Adherence = Number of tablets taken home – number of tablets returned X 100
Number of tablets that should have been taken
The pill count sheet designed specifically for this study was used during the
study period in addition to the in-house pill count sheet normally used by the
clinic. At Return Visits 1 and 2 patients were informed of their exact adherence
percentage and counselled by the clinic counsellors according to normal clinic
procedures.
Pilot study
This study was pilot-tested amongst 29 patients at Masibambane ARV Clinic,
Tshwane District Hospital, an ART site different from the main study site
(Adeyinka, Meyer, Summers & Johnson, 2010). According to the pilot study
results, the ‘mixed’ pill count method appeared to be capable of detecting overcompliance and pill dumpers. The concept was therefore used as part of normal
practice during the main study.
Statistical analysis
Data were analysed with Statistical Analysis System (SAS®) software. The
Fisher’s exact- and McNemar’s tests were performed to determine any
significant difference in adherence between the variables compared, with p≤0.05
regarded as statistically significant. Demographic data were summarised and
expressed as means and percentages.
Ethical considerations
The University of Limpopo, Medunsa Campus Research and Ethics Committee
granted ethical clearance for the study. Approval to conduct the pilot study and
main study was granted by the Chief Executive Officer of the respective study
sites. All participants provided written consent prior to enrolment and were
assured of confidentiality of data.
Identification of over-compliant patients and pill dumpers 109
Results
Three-hundred-and-forty-four patients (93.0%; n=370) completed the study.
Dropout (7%) included 11 patients who switched regimen, eight patients who
defaulted during the course of the study, and seven patients who were transferred
to another ART clinic.
Socio-demographic characteristics
Socio-demographic characteristics at baseline are summarised in Table 1. The
mean age of the study population (n=344) was 40.1±9.11 years, with females
predominating (205; 59.6%). On average, participants were on ART for 30
months with a median time of 24 months.
Table 1: Socio-demographic characteristics of the study population at baseline
Characteristics
Male (n=139)
Female (n=205)
No (%)1
No (%)1
18-30
12 (8.6%)
39 (19.0%)
Age group
(years)
31-40
55 (39.6%)
90 (43.9%)
41-50
49 (35.3%)
48 (23.4%)
>50
23 (16.5%)
28 (13.7%)
Black
135 (97.1%)
202 (98.5%)
Race
Coloured
4 (2.9%)
3 (1.5%)
Afrikaans
5 (3.6%)
5 (2.4%)
Language
Zulu
25 (18.0%)
32 (15.6%)
Tswana
10 (7.2%)
17 (8.3%)
Sotho
33 (23.7%)
57 (27.8%)
66 (47.5%)
94 (45.9%)
Other2
None / primary not
13 (9.4%)
22 (10.7%)
Level of
completed
education
Primary completed
69 (49.6%)
102 (49.8%)
Secondary completed
49 (35.3%)
72 (35.1%)
Tertiary / vocational
8 (5.8%)
9 (4.4%)
77 (55.4%)
82 (40%)
Employment Employed
status
Unemployed
62 (44.6%)
123 (60%)
Single
83 (59.7%)
135 (65.9%)
Marital
status
Married
38 (27.3%)
47 (22.9%)
Widowed
8 (5.8%)
16 (7.8%)
Divorced
10 (7.2%)
7 (3.4%)
<6 months
4 (2.9%)
3 (1.5%)
Duration on
ART
6 – 12 months
27 (19.4%)
44 (21.5%)
13 – 24 months
42 (30.2%)
50 (24.4%)
1
% of total in the category; 2Ndebele, Pedi, Shona or Tsonga
Total (N=344)
No (%)1
51 (14.8%)
145 (42.2%)
97 (28.2%)
51 (14.8%)
337 (98.0%)
7 (2.0%)
10 (2.9%)
57 (16.6%)
27 (7.9%)
90 (26.2%)
160 (46.5%)
35 (10.2%)
171 (49.7%)
121 (35.2%)
17 (5.0%)
159 (46.2%)
185 (53.8%)
218 (63.4%)
85 (24.7%)
24 (7.0%)
17 (5.0%)
7 (2.0%)
71 (20.6%)
92 (26.7%)
110 Awolola, Meyer, Summers and Johnson
Adherence at different optimal thresholds
Adherence of ≥95% is generally regarded as optimal because at this level
maximal viral suppression, CD4+ cell count improvement, as well as minimal
resistance to medication are observed (Lima et al., 2008; Ford et al., 2010). The
best response though to ART is observed when adherence is 100% (Cauldbeck et
al., 2009). Because of the design of this study, 100% adherence was regarded as
optimal, to be able to distinguish between truthfully non-adherent patients and
over-compliant patients. Table 2 shows the proportion of patients within each
category of adherence at the two return visits, based on the 100% threshold, as
well as the 95-100% threshold for optimal adherence.
Table 2: Proportion of patients per adherence category at the two return visits according to
different thresholds for optimal adherence
100% threshold
<100%
Truthful
nonadherent
=100%
Adherent
95-100% threshold
>100%
Overcompliant
<95%
Truthful
Nonadherent
Pill Count
Normal Pill
174
95
75
71
Count
(27.6%)
(21.8%)
(20.6%)
(Return Visit 1) (50.6%)
(N=344)
Mixed Pill
55
246
43
22
Count
(71.5%)
(12.5%)
(6.4%)
(Return Visit 2) (16.0%)
(N=344)
Note: Mean adherence was calculated for each patient’s regimen.
95-100%
Adherent
>100%
Overcompliant
198
(57.6%)
75
(21.8%)
279
(81.1%)
43
(12.5%)
Comparison of adherence results with different pill counts
Table 3 indicates that 12 patients (3.5%) were over-compliant (returning too few
dosage units) with both pill count methods. The proportion of over-compliant
patients with the ‘mixed’ pill count (43; 12.5%) was found to be significantly
smaller than with the normal pill count (75; 21.8%) (p=0.001; McNemar’s test).
The proportion of patients with 100% adherence improved at Return Visit 2
(71.5% versus 27.6%), as fewer patients were non-adherent or over-compliant.
Although over-compliance reduced for the overall population at Return Visit 2
(Table 3), when only the 43 patients who were over-compliant at Return Visit 2
were considered, fewer of them (12; 27.9%) were previously over-compliant; i.e.
the rate of over-compliance increased at Return Visit 2 for these 43 patients.
From Table 4, it is evident that the proportion of patients returning too few
dosage units at Return Visit 2 was the highest for the fixed-dose combination of
lamivudine and zidovudine (93.3% at Return Visit 2).
Identification of over-compliant patients and pill dumpers 111
Table 3: Proportion of patients within each category of adherence for both pill counts (N=344)
Normal Pill Count
(Return Visit 1)
Mixed Pill Count
(Return Visit 2)
Adherence
Category*
<100%
Truthful nonadherent
100%
Adherent
>100%
Overcompliant
Total
<100% Truthful
non-adherent
32
(9.3%)
119
(34.6%)
23
(6.7%)
174
(50.6%)
100%
Adherent
9
(2.6%)
78
(22.7%)
8
(2.3%)
95
(27.6%)
>100%
Over-compliant
14
(4.1%)
49
(14.2%)
12
(3.5%)
75#
(21.8%)
55
246
43#
344
(16.0%)
(71.5%)
(12.5%)
(100%)
Note: Mean adherence was calculated for each patient’s regimen; #p=0.001; McNemar’s test
Total
Over-compliance was observed and was statistically significant for all the ARVs
except for nevirapine and tenofovir. It is worth noting, though, that the sample
size for these two ARVs was smaller than for the other ARVs.
Table 4: Proportion of over-compliant patients returning too few tablets (>100% adherence) per
individual ARV for the two pill count methods (n=43)
ARV medication
Stavudine
Lamivudine
Efavirenz
Nevirapine
Fixed-dose combination#
Tenofovir
Normal pill count
at Return Visit 1
n*
No (%)
28
7 (25.0%)
28
7 (25.0%)
34
5 (14.7%)
10
5 (50.0%)
12
2 (16.7%)
4
2 (50.0%)
Mixed pill count
at Return Visit 2
n
No (%)
24
21 (87.5%)
27
24 (88.9%)
32
21 (65.6%)
12
9 (75.0%)
15
14 (93.3%)
5
2 (40.0%)
P-value
(Fisher’s
exact test)
<0.001
<0.001
<0.001
0.378
<0.001
1.000
#
Lamivudine plus zidovudine; *Number of patients taking on individual ARV medicine, which is
different because not all patients were on the same ARV combination at the two visits
Discussion
A predominance of females (59.6%) over males (40.4%) as observed in this
study, is similar to the patient distribution reported by other studies conducted at
ART sites in South Africa (Chabikuli, Datonye, Nachega & Ansong, 2010; Ford
et al., 2010; Peltzer, Friend-Du Preez, Ramlagan & Anderson, 2010).
At Return Visit 1, the number of non-adherent patients decreased from 174
(50.6%) to 71 (20.6%) when the threshold for adherence was lowered from
112 Awolola, Meyer, Summers and Johnson
100% to 95-100%. The proportion of patients who were optimally (100%)
adherent at Return Visit 1, as determined by the normal pill count, was low
(27.6%). When the threshold for optimal adherence was lowered to 95-100%, the
proportion of patients with optimal adherence at this visit was much higher
(57.6%). This figure compares to adherence rates reported by Mokoena, Meyer,
Gous and Zweygarth (2009) with a normal pill count method, in which 59.3%
(n=100) of the patients in a military setting in South Africa were ≥95% adherent.
International data on adherence rates do not seem to be much different. A review
of 84 observational studies across 20 countries (33 199 adults on ART), revealed
that on average only 62% of patients achieved adherence levels of at least 90%
of their ARV doses (Ortego et al., 2011).
Although the pilot study indicated that the ‘mixed’ pill count method can
identify patients who are masking non-adherence, the degree of over-compliance
among all patients was lower at Return Visit 2 with the ‘mixed’ pill count. This
decrease in over-compliance was the opposite of what was expected, and it
appeared as though the ‘mixed’ pill count did not detect over-compliant patients
as well as expected. On the other hand, if only the patients who were overcompliant with the ‘mixed’ pill count (n=43) were considered, the degree of
over-compliance worsened at Return Visit 2. This implies that there was a
decline in the adherence levels as detected by the ‘mixed’ pill count method in
this particular group of patients. The decline in adherence at Return Visit 2 for
this defined group of patients was in the opposite direction of the much higher
adherence levels, compared to Return Visit 1, observed in the overall population.
This favourable increase in adherence level at Return Visit 2 could be attributed
to the fact that, in the previous visit (Return Visit 1), patients were notified in
detail of their sub-optimal adherence, which motivated them to adhere better to
their ART. Although adherence counselling was already a routine practice at the
study site, patients’ exact adherence percentage was hardly communicated to
them because the counsellors were not calculating the actual adherence
percentage. On the other hand, when the pill count sheet developed for the study
was used, the exact adherence was known and patients were counselled
accordingly. The study pill count sheet turned out to be an intervention at the
ART clinic during the study, although that was not intended originally.
Previous evidence highlighted the benefit of adherence tools used in combination
with counselling about missed doses in improving adherence (Sabin et al., 2011).
Recommendations
Periodic implementation of the ‘mixed’ pill count method could assist clinic staff
to better identify non-adherent maskers and allow for more timely intervention in
order to improve patients’ medication behaviour and potentially treatment
outcomes.
Identification of over-compliant patients and pill dumpers 113
An important recommendation from this study is regular individual counselling
of patients to promote adherence and patient care. Counselling should take place
at every clinic visit for patients on repeat prescriptions and not only when there
is virological failure or a sharp decline in CD4+ cell count. Most importantly,
during counselling, feedback must be given to the patients on the exact
adherence percentage achieved over the period since their last visit. The study
pill count sheet could be implemented as part of normal clinic procedures to
facilitate the calculation of exact adherence rates. In addition to regular pill
counts, the ‘mixed’ pill count should be used intermittently and in particular for
patients who are suspected of pill manipulation.
Limitations
This study had notable limitations. The process of data collection and enrolment
of patients into the study was time-consuming and required more data collectors
than were available, which contributed to the relatively low sample size in the
study. Secondly, the fact that there was a data collector present in the counselling
room seemed to have positively influenced the counselling behaviour of the
counsellor, which ultimately led to an improvement in the adherence levels of
the study patients.
Conclusion
From the findings of this study, it is evident that the ‘mixed’ pill count can detect
deliberate masking of non-adherence and ‘pill dumpers’. The study highlights
the important role played by adherence counselling from healthcare workers at
ART clinics, as targeted counselling of patients reinforces the importance of
taking ARVs as prescribed.
Acknowledgements
The study was carried out with support of the Foundation for Professional
Development (FPD) and the Department of Pharmacy, University of Limpopo
(Medunsa Campus). The authors would like to thank the patients who
participated in the study and the management and staff of Mamelodi Hospital for
their support. Our sincere gratitude goes to Prof Herman Schoeman for statistical
analysis of the data.
The pilot study of this research was presented as a poster at the XVIII
International AIDS Conference, Vienna, Austria, 18-23 July 2010. The main
study was presented as a podium at the 6th SAHARA Conference in Port
Elizabeth, South Africa, 28 November to 2 December 2011.
114 Awolola, Meyer, Summers and Johnson
References
Adeyinka, T.A., Meyer, J.C., Summers, B. & Johnson, S. (2010). Investigation of the method of
“mixed pill counts” as a tool to detect deliberate masking of non-adherence to antiretroviral
therapy (ART): A pilot study. THPE0426. XVIII International AIDS Conference, Vienna,
Austria, 18-23 July 2010.
Altice, F.L. & Springer, S.A. (2010). DAART for Human Immunodeficiency Virus-infected
patients: Studying subjects not at risk for nonadherence and use of untested interventions.
Archives of Internal Medicine, 170(1), 109-110.
Berg, K.M. & Arnsten, J.H. (2006). Practical and conceptual challenges in measuring
antiretroviral adherence. Journal of Acquired Immune Deficiency Syndromes, 43(1), 79-87.
Cauldbeck, M.B., O’Connor, C., O’Connor, M.B., Saunders, J.A., Rao, B., Mallesh, V.G.,
Kumar, N.K.P., Mamtha, G., Mcgoldrick, C., Laing, R.B.S. & Satish, K.S. (2009). Adherence to
anti-retroviral therapy among HIV patients in Bangalore, India. AIDS Research and Therapy,
6(7), 1-8.
Chabikuli, N.O., Datonye, D.O., Nachega, J. & Ansong, D. (2010). Adherence to Antiretroviral
Therapy, Virologic Failure and Workload at the Rustenburg Provincial Hospital. South African
Family Practice, 52(4), 350-355.
Chesney, M.A. (2006). The elusive gold standard. Future perspectives for HIV adherence
assessment and interventions. Journal of Acquired Immune Deficiency Syndromes, 43(1), 149155.
Deschamps, A.E., De Geest, S., Vandamme, A.M., Bobbaers, H., Peetermans, W.E. & Van
Wijngaerden, E. (2008). Diagnostic value of different adherence measures using electronic
monitoring and virologic failure as reference standards. AIDS Patient Care and STDs, 22(98),
735-743.
Ford, N., Darder, M., Spelman, T., Maclean, E., Mills, E. & Boulle, A. (2010). Early adherence
to antiretroviral medication as a predictor of long-term HIV virological suppression: five-year
follow
up
of
an
observational
cohort.
PLoS
ONE,
5(5):
e10460.
doi:10.1371/journal.pone.0010460.
Lima, V.D., Harrigan, R., Murray, M., Moore, D.M., Wood, E., Hogg, R.S. & Montaner, J.S.G.
(2008). Differential impact of adherence on long-term treatment response among naive HIVinfected individuals. AIDS, 22, 2371-2380.
Mokoena, M., Meyer, J.C., Gous, A.G.S. & Zweygarth, M. (2009). 12-month adherence to
antiretroviral therapy (ART) at 1 Military Hospital, Pretoria. South African Association of
Hospital and Institutional Pharmacists, 23rd Annual Conference, Champagne Sports Resort,
Drakensberg, 2-5 April 2009.
Nachega, J.B., Knowlton, A.R., Deluca, A. & Schoeman, J.H. (2006). Treatment supporter to
improve adherence to antiretroviral therapy in HIV-infected South African adults. Journal of
Acquired Immune Deficiency Syndromes, 43(1), S127-133.
Ortego, C., Huedo-Medina, T.B., Llorca, J., Sevilla, L., Santos, P., Rodríguez, E., Warren, M.R.
& Vejo, J. (2011). Adherence to highly active antiretroviral therapy (HAART): a meta-analysis.
AIDS Behaviour, 15(7), 1381-1396.
Identification of over-compliant patients and pill dumpers 115
Peltzer, K., Friend-Du Preez, N., Ramlagan, S. & Anderson, J. (2010). Antiretroviral treatment
adherence among HIV patients in KwaZulu-Natal, South Africa. BMC Public Health, 10, 111120.
Ross-Degnan, D., Pierre-Jacques, M., Zhang, F., Tadeg, H., Gitau, L., Ntaganira, J.,
Balikuddembe, R., Chalker, J., Wagner, A.K. & INRUD IAA. (2010). Measuring adherence to
antiretroviral treatment in resource-poor settings: The clinical validity of key indicators. BMS
Health Services Research, 10(42), 1-10.
Sabin, L.L., DeSilva, M.B., Hamer, D.H., Xu, K., Zhang, J., Li, T., Wilson, I.B. & Gill, C.J.
(2010). Using electronic drug monitor feedback to improve adherence to antiretroviral therapy
among HIV- positive patients in China. AIDS Behaviour, 14(3), 580-589.
Steel G., Nwokike J., Joshi M.P. & Ntengu M. (2011). Development and Implementation of a
Multi-Method Medication Adherence Assessment Tool Suitable for Antiretroviral Therapy
Facilities in Resource- Constrained Settings. Third International Conference for Improving Use
of Medicines. Antalya, Turkey, 14-18 November 2011, (online) at http://www.
inrud.org/ICIUM/ConferenceMaterials/1115-steel-_a.pdf 27 March 2014.