Study, year, country | Objective(s) | CRC screening tests | No. of attributes | Procedure-related characteristics | Test characteristics | Benefits | Harms | Structural characteristics of health care | Level of evidence | Risk of biasa |
---|---|---|---|---|---|---|---|---|---|---|
Rating | ||||||||||
Hawley et al., 2008, USA [46] | To analyse preferences for CRC screening tests of racially/ethnically diverse primary care patients | FOBT, SIG, COL, DCBE, FIT, V-COL | 5 | ✓ | ✓ | ✓ | Critical | |||
Ranking | ||||||||||
Gyrd-Hansen et al., 2001, Denmark [58] | To analyse public preferences for attributes associated with participation in cancer screening programmes | FOBT | 4 | ✓ | ✓ | ✓ | ✓ | Serious | ||
Discrete choice | ||||||||||
Generic | ||||||||||
Salkeld et al., 2000, Australia [55] | To measure consumer preferences for an existing and a hypothetical new CRC screening test | Bowel scan test kit (status quo) and a hypothetical new bowel test | 5 | ✓ | ✓ | ✓ | Critical | |||
Salkeld et al., 2003, Australia [56] | To elicit community preferences for CRC screening by faecal occult blood test based on harms and benefits | FOBT | 3 | ✓ | ✓ | ✓ | Serious | |||
Marshall et al., 2007, Canada [39] | To analyse preferences for various CRC screening tests | FOBT, SIG, COL, DCBE, DNA stool tests, V-COL | 6 | ✓ | ✓ | ✓ | ✓ | Moderate | ||
Howard et al., 2009, Australia [43] | To explore the effect of attribute framing within the context of CRC screening preferences.b | FITs | 6 | ✓ | ✓ | ✓ | Moderate | |||
Marshall et al., 2009, Canada, USA [47] | To analyse and compare general-population and physician preferences for attributes of CRC screening tests | FOBT, SIG, COL, DCBE, DNA stool tests, V-COL | 9 | ✓ | ✓ | ✓ | ✓ | Critical | ||
Van Dam et al., 2010, The Netherlands [36] | To analyse how procedural characteristics of CRC screening tests determine preferences for participation and how individuals weigh these against the expected health benefits from participating in CRC screening | FOBT, SIG, COL | 7 | ✓ | ✓ | ✓ | Critical | |||
Nayaradou et al., 2010, France [59] | To identify population preferences for CRC screening test characteristics | Stool test, blood test | 7 | ✓ | ✓ | ✓ | ✓ | Serious | ||
Pignone et al., 2012, USA [44] | To compare two methods for eliciting and clarifying patient values for decision-making aboutCRC screening.b | FOBT, SIG, COL, CT-COL | 6 | ✓ | ✓ | ✓ | ✓ | Critical | ||
Brenner et al., 2014, USA, Australia [45] | To compare the effects of three methods of values clarification on decision-making about CRC screening.b | FOBT, SIG, COL, radiological testing | 5 | ✓ | ✓ | ✓ | Critical | |||
Groothuis-Oudshoorn et al., 2014, The Nerlands, UK [53] | To analyse public preferences for various CRC screening tests | FIT, SIG, COL, nanopill | 6 | ✓ | ✓ | ✓ | Serious | |||
Pignone et al., 2014, USA [48] | To analyse how vulnerable populations value different aspects of CRC screening tests | Stool test, COL, CT-COL | 4 | ✓ | ✓ | Critical | ||||
Kistler et al., 2015, USA [49] | To analyse older adults’ preferences for CRC screening tests | FOBT, SIG, COL | 4 | ✓ | ✓ | ✓ | Critical | |||
Martens et al., 2016, USA [50] | To analyse preferences of the Hispanic immigrant community in North Carolina for CRC screening test characteristics and barriers and facilitators around CRC screening | Stool test, COL, CT COL | 4 | ✓ | ✓ | Critical | ||||
Osborne et al., 2018, Australia [57] | To analyse population preferences for CRC screening tests | Stool test, blood test, saliva test | 3 | ✓ | ✓ | ✓ | Serious | |||
Mansfield et al., 2018, USA [51] | To analyse preferences for the features of CRC screening tests | FOBT, FIT, SIG, COL | 5 | ✓ | ✓ | ✓ | ✓ | Critical | ||
Ramezani_Doroh et al., 2019, Iran [60] | To analyse the preferences for CRC screening tests | gFOBT, FIT, SIG, COL, DCBE, stool DNA test | 9 | ✓ | ✓ | ✓ | ✓ | ✓ | Critical | |
De Bekker-Grob et al., 2019, The Netherlands [41] | To determine whether the number of alternatives in a DCE choice task should reflect the actual decision context, and how complex the choice model needs to be to be able to predict real-world healthcare choices.b | FOBT | 5 | ✓ | ✓ | ✓ | ✓ | Serious | ||
Phisalprapa et al., 2021, Thailand [61] | To analyse preferences and willingness to pay of individuals at risk of CRC | FIT, SIG, COL, DCBE, CT COL | 6 | ✓ | ✓ | ✓ | ✓ | Critical | ||
Labelled | ||||||||||
Hol et al., 2010, The Netherlands [38] | To analyse preferences for and to predict the uptake of CRC screening tests | FOBT, SIG, COL | 2 | ✓ | ✓ | Critical | ||||
Benning et al., 2014, The Netherlands [52] | To analyse potential screening participants’ preferences for different non-invasive CRC screening tests | Stool test, blood test, combi test | 4 | ✓ | ✓ | ✓ | Critical | |||
Benning et al., 2014, The Netherlands [54] | To analyse how much individuals’ participation decision in non-invasive screening is affected by the presence or absence of detailed information about invasive follow-up testing | Stool test, blood test, combi test | 5 | ✓ | ✓ | ✓ | ✓ | Critical |