Based on our predefined criteria (i.e., easy to use and interpret, assessing both taking and timing of medication intake and validated extensively), only two self-report instruments can be recommended for use in transplant populations: the Brief Antiretroviral Adherence Index (AACTG) and the Medication Adherence Self-Report Inventory (MASRI) (indicated in grey in Tables 3 and 4).
The AACTG questionnaire requires assistance from a healthcare professional and is, therefore, more labor intensive. The clinician first makes a list, together with the patient, of all medications taken; the patient is then asked to rate how many doses were missed the previous day, then 2, 3, and 5 days ago, for each specific drug taken. The short recall period makes it easier for patients to remember what has happened during this time. A more general question at the end of the questionnaire asks the patient to indicate the last time a dose of medication was missed. A question is also included asking about regularity of medication intake in general, without referring to a specific time frame. These questions can easily be adapted for use in transplant populations.
The MASRI also starts by asking how many doses were missed yesterday, the day before yesterday, and 3 days ago. However, these answers are not used to determine whether a patient is adherent or not but only serve to stimulate a patient's reflection on his or her medication-taking behavior. The questions that require patients to indicate their percentage adherence, that is, what proportion of doses of the drugs were taken (or taken within 2 hr of the prescribed regimen), might be difficult for patients to comprehend, and answers are largely dependent on the patient's personal reference standard. For instance, a very conscientious patient may report a score of 70 if they were 15-min late with medication intake a couple of times over the last week, whereas another patient who does not know that timing is important may report a score of 90 even if they did not take the tablets at fixed time points. As such, this subjective scoring system may render comparisons between patients difficult.
Before discussing our findings, we need to acknowledge that self-report is not the gold standard for adherence assessment, because some patients may be reluctant to disclose adherence problems or may have problems recalling their medication-taking behavior preceding the assessment. Electronic monitoring is often promoted as the best assessment for adherence research purposes, as it allows monitoring of medication intake and timing over a period of time and has superior validity compared with other measurement methods. However, despite being an accurate and valid tool, its use in clinical practice is limited because (a) most electronic monitoring devices may lead to practical or confidentiality issues as the devices are rather large; (b) their use is labor intensive for professionals; (c) devices are expensive; and (d) they allow monitoring of a single drug only (17).
Taking these points into consideration and given that all existing measurement tools have advantages and disadvantages, the current recommendation is to combine several measurement methods; this is often referred to as “triangulation” (11). Recently, Schäfer-Keller et al. found that the following algorithm showed a sensitivity of 72% and a specificity of 43% when using electronic monitoring as the reference value: self-reported nonadherence or at least one clinician (physician or nurse) reporting nonadherence or subtherapeutic blood levels. More specifically, a patient is considered to be nonadherent if at least one of these measures classifies the patient as nonadherent (12). These methods can be implemented easily in clinical practice but underscore the need for a well-validated self-report instrument as a part of the triangulation strategy.
Given that self-report tends to underestimate nonadherence, selecting the optimal instrument is crucial to allow identification of the maximum number of patients with problematic adherence. Based on our European survey and systematic literature review, consensus was reached within the transplant360 Task Force that three self-report instruments can be recommended for use in transplant clinical practice; the BAASIS, the AACTG questionnaire, and the MASRI, which are available on request from the developers, are recommended for the following reasons:
The members of the transplant360 Task Force are as follows: Fabienne Dobbels (Chair), University Hospitals of Leuven and Centre for Health Services and Nursing Research, Katholieke Universiteit Leuven, Belgium; Christiane Kugler, Integrated Research and Treatment Centre, Hannover Medical School, Hannover, Germany; Lut Berben, Institute of Nursing Science of the Faculty of Medicine at the University of Basel, Switzerland; Lisa Burnapp, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom; Sabina De Geest, Institute of Nursing Science of the Faculty of Medicine at the University of Basel, Switzerland, and Centre for Health Services and Nursing Research, Katholieke Universiteit Leuven, Belgium; Gerda Drent, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands; Håkan Hedman, Savedalen, Sweden; Annette Lennerling, Transplant Institute at Sahlgrenska University Hospital in Gothenburg, Sweden; Sandra Martin, University Hospitals Leuven, Belgium Catholic School of Nursing, Leuven, Belgium; Dawn McPake, Queen Elizabeth Hospital, Birmingham, UK Birmingham Hospital, Birmingham, United Kingdom; María Sarrias, Hospital Universitari Vall d'Hebron, Spain; Nadine Stohler, Aesch, Basel, Switzerland; Clare Whittaker, Royal London Hospital, London, United Kingdom. The Task Force members were selected based on their expertise on adherence research (Berben, De Geest, Dobbels, Drent, Kugler, and Lennerling), their role as a chair of European patient organizations (Hedman and Stohler), their active membership of the International Transplant Nurses Society (Martin and Whittaker), or their nationally or internationally recognized clinical leadership (Burnapp, McPake, and Sarrias).
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