Computer-based interview for screening blood donors for risk of HIV transmission

Locke, Steven E.; Kowaloff, Hollis B.; Safran, Charles; Slack, Warner V.; Cotton, David; Hoff, R.; Popovsky, Mark; McGuff, J.; Page, Peter L.

doi:10.1001/jama.268.10.1301

Cited by 89 publications

(50 citation statements)

References 14 publications

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“…Studies in many domains have demonstrated that computer administration of sensitive questions has been shown to increase reporting levels of sensitive behaviors, particularly in comparison with interviewer-based administration [73,74] as patients prefer and are more willing to disclose sensitive information to a computer rather than an interviewer [74][75][76][77][78][79][80][81][82][83][84][85][86][87]. Direct computer entry further enhances the quality of data by not allowing double or ambiguous answers [88], and it is often associated with a lower rate of unanswered questions than paper forms [80,82,85,88,89] because patients must provide a valid response to a question and/or press the "next" button to move on.…”

Section: Recommendations For Optimizing the Validity Of Self-report Mmentioning

confidence: 99%

Self-report measures of medication adherence behavior: recommendations on optimal use

Stirratt

Dunbar‐Jacob

Crane

et al. 2015

Behav. Med. Pract. Policy Res.

608

528

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Medication adherence plays an important role in optimizing the outcomes of many treatment and preventive regimens in chronic illness. Self-report is the most common method for assessing adherence behavior in research and clinical care, but there are questions about its validity and precision. The NIH Adherence Network assembled a panel of adherence research experts working across various chronic illnesses to review selfreport medication adherence measures and research on their validity. Self-report medication adherence measures vary substantially in their question phrasing, recall periods, and response items. Self-reports tend to overestimate adherence behavior compared with other assessment methods and generally have high specificity but low sensitivity. Most evidence indicates that self-report adherence measures show moderate correspondence to other adherence measures and can significantly predict clinical outcomes. The quality of self-report adherence measures may be enhanced through efforts to use validated scales, assess the proper construct, improve estimation, facilitate recall, reduce social desirability bias, and employ technologic delivery. Self-report medication adherence measures can provide actionable information despite their limitations. They are preferred when speed, efficiency, and low-cost measures are required, as is often the case in clinical care. KeywordsAdherence, Compliance, Self-management, Medication, Self-report Valid measurement of medication adherence plays a crucial role in healthcare and health research. When a patient is not benefiting from a medication regimen, clinicians need sound adherence information to determine whether the medication is ineffective or not being taken as prescribed. Assessing medication adherence during routine clinical care can further ensure that individuals in need of adherence support interventions receive them, ideally before deleterious outcomes occur. In the context of clinical research, proper interpretation of proof-of-concept trials testing new pharmacologic regimens requires valid adherence data, because any null findings may stem from poor adherence rather than a lack of drug efficacy. Research designed to understand and promote medication adherence also requires precise methods of adherence assessment.Among many approaches to assessing medication adherence, patient self-report measures remain the most common method [1][2][3][4][5][6]. These measures are defined by asking respondents to characterize their medication adherence behavior. Self-report measures of medication adherence range from simple singleitem questions regarding missed doses to complex multi-item assessments that incorporate reasons for nonadherence [7]. The widespread use of self-report adherence measures in clinical care and research reflects their low cost and ease of implementation across a large variety of medication regimens.There are two primary challenges related to selfreport measures of medication adherence. ImplicationsPractice: Routine assessment of medication...

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Section: Recommendations For Optimizing the Validity Of Self-report Mmentioning

confidence: 99%

Self-report measures of medication adherence behavior: recommendations on optimal use

Stirratt

Dunbar‐Jacob

Crane

et al. 2015

Behav. Med. Pract. Policy Res.

608

528

View full text Add to dashboard Cite

show abstract

“…It would seem sensible to test alternative formats since questions focused on stimulating self-deferral rather than generating useful epidemiological data might be more acceptable to the public (again see provisional examples in table 3). It is probable that computer-based questionnaires would generate more reliable responses than paper-based surveys or face-to-face interviews (see Katz et al, 2007;Locke et al, 1992;O'Brien et al, 2006) and certainly, online materails the current… questionnaire" (ibid; 750) might say as much about respondent's views on the study's methodology as it does about opinions on practice-based assessments.…”

Section: Reforming Pre-donation Questionnairesmentioning

confidence: 99%

Blood, sex and trust: The limits of the population-based risk management paradigm

Kesby

Sothern

2014

Health & Place

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1 Blood, sex and trust: the limits of the population-based risk management paradigm.Keywords: Blood donation; HIV; risk-group; trust; MSM AbstractBlood screening is imperfect so Donor Health Check questionnaires (DHC) are used to defer those whose 'behaviour' suggests disproportionate risk of Blood Borne Infection (BBI).Taking the UK case, we compare deferment of three sub-populations with different HIV prevalence; Men-who-have-Sex-with-Men (4.7%), black-Africans (3.7%) and 'the-general-(heterosexual)-population' (c.0.09%) arguing that, with respect to STIs, DHCs assess risk based on broad population-level risk-groups not behaviour. This approach relies on an imaginative geography that distances heterosexual risk from the domestic population. Most DHCs knowingly commit the ecological fallacy allowing population-level statistics to obscure within-group diversity, identifying inadequately the risk posed by 'low-risk-groups'. The disjuncture between ontological risk phenomenon (diverse sexual practice) and the epistemological grid used to map risk (homogenized risk-groups) needs examination.Unpacking the category 'heterosexual' would both better differentiate risk within this group and change the relative-risk calculated for 'high-risk groups'. We call for practice-based DHCs that more accurately assess all potential donors.

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“…The use of computers has been found to decrease the effect of social desirability and increase the amount of information disclosed [23][24]. Findings suggest that patients prefer to reveal information of a personal and potentially embarrassing nature to a computer rather than a person [25][26][27]. The use of computer-based screening and advice can improve the effectiveness of behavioural counselling through improved consistency of counselling and closer matching of intervention to patient characteristics and recommended guidelines.…”

Section: Introductionmentioning

confidence: 99%

Computerized lifestyle intervention in routine primary health care: Evaluation of usage on provider and responder levels

Carlfjord

Nilsen

Leijon

et al. 2009

Patient Education and Counseling

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Computer-based interview for screening blood donors for risk of HIV transmission

Abstract: Concern about the safety ofthe nation s blood supply continues to grow because of the expanding number of HIV-infected

Cited by 89 publications

References 14 publications

Self-report measures of medication adherence behavior: recommendations on optimal use

Self-report measures of medication adherence behavior: recommendations on optimal use

Blood, sex and trust: The limits of the population-based risk management paradigm

Computerized lifestyle intervention in routine primary health care: Evaluation of usage on provider and responder levels

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