Discussion
In this study we describe the state of the art of the existing
scientific experimental evidence on the factors and determinants that
influence patients’ adherence to treatment. As can be seen in the
results section and the Supplementary Material, many studies have
examined the effects of several factors and determinants on adherence to
treatment. In particular regarding socioeconomic factors, most studies
have considered determinants from the patients’ background or
environment including their financial status, education, employment
status, and living condition. Besides that significant associations have
been found, these factors and determinants are difficult to modify or
influence. Other factors studied relate to the existence of social
support networks, which have been found to significantly affect
adherence to treatment by several studies (Siregar and Andayani, 2020;
Zullig et al., 2015; Reddy et al., 2017). Easily modifiable patient
lifestyle factors have also been identified to have a significant
contribution to adherence levels (Meggetto et al., 2017; Sieben et al.,
2021; Llorca et al., 2021; Nascimento et al., 2016; Shankari et al.,
2020). Multiple studies have explored the effect of those factors on
adherence related to the patient-HCP relationship and to the different
figures and institutions involved in healthcare. From these, the most
relevant factor associated with adherence to treatment is the provision
of education and follow-up to patients. In fact, several studies have
identified its effect on the level of adherence to treatment (Tola et
al., 2016; Bonetti et al., 2018; Hohmann et al., 2014; Hovland et al.,
2020; Kamal et al., 2015; Ababneh et al., 2019; Wan et al., 2016; Asgari
et al., 2021; Alfian et al., 2020; Jahn et al., 2014; Wang et al.,
2020), although some studies did not find any significant relation. This
evidence is highly relevant as it can guide future interventions and
guidelines that can help improve patients’ adherence to treatment.
The characteristics of the treatment-related factors, the duration and
its symptomatology have also been identified as having a strong
influence on the patients’ adherence levels. Furthermore, not only the
condition but also the treatment characteristics have been identified as
strong influencers, with complexity and duration of the treatment being
the major factors (Flicoteaux et al., 2017; Gillespie et al., 2014;
Kuypers et al., 2013; Suffoletto et al., 2012; Wooldrich et al., 2015;
Sieben et al., 2021; Kamal et al., 2015). The relevance of identifying
treatment complexity as an adherence determinant may help HCPs when
deciding on the treatment options available for a specific patient and
the associated risk of non-adherence to such treatment.
Finally, there are some factors that are related to the physical and
behavioral characteristics of the patients and their environment.
Factors like age, gender and ethnicity that are unalterable for the
treatment purpose have been identified by many studies as being
associated with treatment adherence. However, not all studies agree on
the direction of the effect of these factors, which indicates that the
effects of these factors can be highly dependent on the study setting
(e.g., type of disease, type of treatment, intervention, participants
included). Other factors identified as modifiers of the adherence levels
were factors related to the patients’ health literacy and pre-existing
beliefs and concerns about the condition and the treatment (outcomes)
(Crowley et al., 2014; Nieuwkerk et al., 2012; Crowley et al., 2012;
Beckers et al., 2012; Al-Haj Mohd et al., 2016; Shankari et al., 2020;
Siregar and Andayani, 2020; Llorca et al., 2021). Other relevant factors
are those related to the patients’ lifestyle, their self-efficacy and
planning abilities (Gillespie et al., 2014; Mugo et al., 2014; Wan,
2016; Llorca et al., 2021; Shankari et al., 2020; Kuypers et al., 2013;
Crowley et al. 2014). The identification of these factors related to the
competences of the patients, their behaviors, and psychosocial factors
is highly relevant to better understand a patient’s behavior towards
recommended treatments and to better design approaches to improve the
patient’s adherence levels.
It should be noted, however, that this study has some limitations.
First, the eligibility criteria limited the search to those studies
published in the last decade in English. Still, most studies nowadays
are published in English, and we see the studies do not show a bias
towards studies based on English-speaking regions. Second, our SR has
shown that regarding adherence to treatment, most studies focus on
adherence to medication and do not include additional treatment options,
such as lifestyle changes, which are necessary in most cases.
Subsequently, we also see that most of the studies rely only on
self-reported data (N=31), a small number of studies used pill counts
(N=7) or devices on medication (N=7), and only 2 used biochemical
analytic data. Furthermore, most studies have used only one type of
adherence measurement, making it difficult to compare the outcomes.
Especially considering that differences in measuring methodology may
lead to differences in the assessment of adherence levels. Importantly,
the fact that self-reported data carries the biases of recall and social
desirability, along with its lack of granularity and general
overestimation of adherence, is a limitation for the accuracy and
precision of the data collected. Third, none of the studies have
included patient adherence to treatment across the most common diseases
(e.g., cardiovascular, oncology, immunology, neurology, endocrinology,
and rare disease), making a comprehensive understanding of patient
adherence difficult. In fact, only a limited number of the included
studies covered multiple of these condition areas, and most focused only
on one area. Another important lesson learned is that most of the
studies consider participants from one country only, which makes it
challenging to assess generalizability of the obtained results to other
countries or regions where socioeconomic and healthcare system-related
factors might significantly differ. Remarkably, none of the studies
included the cost of treatment in their analyses, although this is an
important determinant of adherence to treatment, considering the
importance of the socioeconomic factors in selected studies. Fourth,
regarding the review process, having such a broad topic and scope
(including several kinds of conditions, treatments, measures of
adherence, etc.) challenges the proper feeding of the ASReview tool.
This limitation has been overcome by performing several additional
training rounds before getting the final prioritization algorithm.
Lastly, most of the literature studying factors influencing adherence to
treatment relies on patient self-reported data, which, as discussed
above, carries its own biases. These are vital lessons learned for
future steps in scientific research in patient adherence to treatment.