Predictors of treatment dropout in self-guided web-based interventions for depression: an ‘individual patient data’ meta-analysis
Open accessAbstract
Background: It is well known that web-based interventions can be effective treatments for depression. However, dropout rates in web-based interventions are typically high, especially in self-guided web-based interventions. Rigorous empirical evidence regarding factors influencing dropout in self-guided web-based interventions is lacking due to small study sample sizes. In this paper we examined predictors of dropout in an individual patient data meta-analysis to gain a better understanding of who may benefit from these interventions. Method: A comprehensive literature search for all randomized controlled trials (RCTs) of psychotherapy for adults with depression from 2006 to January 2013 was conducted. Next, we approached authors to collect the primary data of the selected studies. Predictors of dropout, such as socio-demographic, clinical, and intervention characteristics were examined. Results: Data from 2705 participants across ten RCTs of self-guided web-based interventions for depression were analysed. The multivariate analysis indicated that male gender [relative risk (RR) 1.08], lower educational level (primary education, RR 1.26) and co-morbid anxiety symptoms (RR 1.18) significantly increased the risk of dropping out, while for every additional 4 years of age, the risk of dropping out significantly decreased (RR 0.94). Conclusions: Dropout can be predicted by several variables and is not randomly distributed. This knowledge may inform tailoring of online self-help interventions to prevent dropout in identified groups at risk.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The study found no evidence for many previously identified predictive factors for adherence including baseline symptom levels, gender, age, or education.
“In contrast to previous studies on adherence in depression and anxiety interventions, we found no evidence for many of the previously identified predictive factors for adherence including baseline symptom levels, gender, age, or education (Christensen et al., 2009; Farrer et al., 2014; Karyotaki et al., 2015; Beatty et al., 2017).”
From Predictors of acceptability and engagement in a self-guided online program for depression and anxiety (2021) · cites this paper as Karyotaki et al., 2015
The citation supports the citing authors’ reference to previously identified predictors: the Main findings section reports that gender, age, and education predicted dropout. But the Wider context section says baseline depression severity did not significantly predict dropout overall, although a separate CES-D analysis found a small association. The citing authors’ statement that they themselves found no evidence is not a finding attributed to this source. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe results coincide with literature indicating that people treated with Internet-based programs report high levels of acceptability and high satisfaction.
“Our results coincide with the literature indicating that people treated with Internet-based programs report high levels of acceptability and high satisfaction (58, 73–78).”
From Exploring the relationship between the acceptability of an internet-based intervention for depression in primary care and clinical outcomes: Secondary analysis of a randomized controlled trial (2019) · cites this paper as [78]
The Introduction (page not provided) says self-guided web-based treatments can preserve anonymity and reduce concerns about stigma, making them more acceptable to many people. It does not report high acceptability ratings from treated participants or high satisfaction; a search for satisfaction found no such finding. (LLM, conf=0.82)
Experimental — accuracy not yet measuredAvailable research shows that the effect of eHealth interventions does not depend on age and that older adults are even more adherent than younger adults.
“Although available research shows that the effect of eHealth interventions does not depend on age and that older adults are even more adherent than younger adults [58], several precautions will be taken to reduce dropout and heighten compliance throughout this study.”
From An Internet-based Acceptance and Commitment Therapy intervention for older adults with anxiety complaints: study protocol for a cluster randomized controlled trial. (2018) · cites this paper as [58]
The Abstract and ‘Predictors of dropout’ section report that dropout decreased with increasing age among participants in self-guided web-based interventions for depression, supporting the adherence comparison. The paper does not establish that intervention effectiveness is independent of age; it examines dropout rather than age-related differences in treatment effects. Page numbers were not available in our copy. (LLM, conf=0.90)
Experimental — accuracy not yet measuredPrevious efforts to identify nontechnological factors influencing attrition in online interventions have yielded inconclusive results.
“although previous efforts to identify nontechnological factors influencing attrition in online interventions have yielded inconclusive results [71-75].”
From Short-term effectiveness of web-based guided self-help for phobic outpatients: randomized controlled trial. (2014) · cites this paper as [74]
The Introduction says earlier studies of dropout predictors often lacked the power to find reliable effects, supporting the characterization of previous results as inconclusive. The paper addresses self-guided web-based interventions for depression, however, rather than online interventions generally. (LLM, conf=0.82)
Experimental — accuracy not yet measuredNearly 40% of participants withdrew before completing at least 25% of all treatment modules in self-guided W-MHIs.
“Nearly 40% of participants withdrew before completing at least 25% of all treatment modules in self-guided W-MHIs”
From Young People’s Barriers and Facilitators of Engagement with Web-Based Mental Health Interventions for Anxiety and Depression: A Qualitative Study (2024) · cites this paper as [13]
More than 83% of participants withdrew before completing the entire programmes in self-guided W-MHIs.
“and more than 83% of participants withdrew before completing the entire programmes [13].”
From Young People’s Barriers and Facilitators of Engagement with Web-Based Mental Health Interventions for Anxiety and Depression: A Qualitative Study (2024) · cites this paper as [13]
Low adherence is a common challenge in web-based interventions, particularly in self-guided interventions.
“Adherence is a common challenge in web-based interventions (Sieverink et al., 2017), particularly in self-guided interventions (Karyotaki et al., 2015).”
From Efficacy of a web-based psychoeducational intervention, Fex-can sex, for young adult childhood cancer survivors with sexual dysfunction: A randomized controlled trial (2024) · cites this paper as Karyotaki et al., 2015
A recent IPDM showed that lower educational level significantly increased the risk of dropping out.
“A recent IPDM showed that a lower educational level significantly increased the risk of dropping out (78).”
The IPDM revealed that men had a greater risk of dropping out.
“The IDPM, mentioned above (78), revealed that men had a greater risk of dropping out.”
There is evidence that women are more aware of health problems than men.
“Moreover, there is also evidence supporting the idea that women are more aware of health problems than men (78, 79).”
According to a recent IPDM, younger ages were related to more dropouts.
“According to a recent individual patient data meta-analysis (IPDM) (78), younger ages were related to more dropouts.”
Women try harder to cope with depression than men.
“It should also be taken into account that women try harder to cope with depression than men (78), which would indicate a greater willingness to continue and complete IBIs and be more satisfied with them.”
Literature shows average adherence in unguided web-based interventions for depression was 26%, compared to 72% in guided interventions.
“Furthermore, the literature shows that in unguided web-based interventions for depression, compared to guided web-based interventions, average levels of adherence were estimated at 26% in unguided interventions and 72% in guided interventions (22, 78).”
Unguided interventions are easier to implement and less costly than guided web-based interventions.
“unguided interventions have been shown to be much easier to implement and less costly than guided web-based interventions [72]”
From An Internet-based treatment for flying phobia (NO-FEAR Airlines): Study protocol for a randomized controlled trial (2016) · cites this paper as [72]
Because there was systematic attrition in this trial, the significant differences between completers and dropouts may provide valuable information to identify focal points for targeted attrition reduction.
“Because there was systematic attrition in this trial, the significant differences between completers and dropouts may provide valuable information to identify focal points for targeted attrition reduction, although previous efforts to identify nontechnological factors influencing attrition in online interventions have yielded inconclusive results [71-75].”
From Short-term effectiveness of web-based guided self-help for phobic outpatients: randomized controlled trial. (2014) · cites this paper as [74]
The effects of EFIs on engagement have not yet been demonstrated.
“Their effects on engagement have not yet been demonstrated (Karyotaki et al., 2015).”
From Predictors of acceptability and engagement in a self-guided online program for depression and anxiety (2021) · cites this paper as Karyotaki et al., 2015
The Introduction and Main findings examine predictors of dropout and adherence in self-guided web-based depression interventions. A search for EFIs and their effects on engagement found no passage addressing whether those effects have been demonstrated. (LLM, conf=0.72)
Experimental — accuracy not yet measuredIn unguided digital interventions, almost 70% of participants dropped out before completing 75% of the intervention.
“Considering only unguided digital interventions, a meta-analytic study by Karyotaki and colleagues [42] showed that almost 70% of participants dropped out before completing 75% of the intervention.”
From Use of the Principles of Design Thinking to Address Limitations of Digital Mental Health Interventions for Youth: Viewpoint (2019) · cites this paper as [42]
Attrition and low adherence are even bigger challenges among children and adolescents; the younger the participant sample, the greater the dropout rate.
“Attrition and low adherence are even bigger challenges among children and adolescents; the younger the participant sample, the greater the dropout rate [37,42].”
From Use of the Principles of Design Thinking to Address Limitations of Digital Mental Health Interventions for Youth: Viewpoint (2019) · cites this paper as [42]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The CES-D Scale: A Self-Report Depression Scale for Research in the General Population
Radloff, L. S. (1977) · Applied Psychological Measurement · doi:10.1177/014662167700100306 · Cited by 53,267 · see citing works
An inventory for measuring depression
BECK, A. T. (1961) · Archives of General Psychiatry · doi:10.1001/archpsyc.1961.01710120031004 · Cited by 38,032 · see citing works
A Modified Poisson Regression Approach to Prospective Studies with Binary Data
Zou, G. (2004) · American Journal of Epidemiology · doi:10.1093/aje/kwh090 · Cited by 9,760 · see citing works
(2008) · Cited by 3,790 · see citing works
Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: A meta-analysis
SPEK, V., CUIJPERS, P., NYKLÍČEK, I., RIPER, H., KEYZER, J., & POP, V. (2007) · Psychological Medicine · doi:10.1017/s0033291706008944 · Cited by 1,586 · see citing works
Self-citationComputer-based psychological treatments for depression: A systematic review and meta-analysis
Richards, D., & Richardson, T. (2012) · Clinical Psychology Review · doi:10.1016/j.cpr.2012.02.004 · Cited by 1,442 · see citing works
Internet-Based and Other Computerized Psychological Treatments for Adult Depression: A Meta-Analysis
Andersson, G., & Cuijpers, P. (2009) · Cognitive Behaviour Therapy · doi:10.1080/16506070903318960 · Cited by 1,368 · see citing works
Self-citationAndrews, G., Cuijpers, P., Craske, M. G., McEvoy, P., & Titov, N. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013196 · Cited by 1,311 · see citing works
Self-citationAdherence in Internet Interventions for Anxiety and Depression
Christensen, H., Griffiths, K. M., & Farrer, L. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1194 · Cited by 1,133 · see citing works
Self-citationMohr, D. C., Cuijpers, P., & Lehman, K. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1602 · Cited by 1,097 · see citing works
Self-citationA Systematic Review of the Impact of Adherence on the Effectiveness of e-Therapies
Donkin, L., Christensen, H., Naismith, S. L., Neal, B., Hickie, I. B., & Glozier, N. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1772 · Cited by 876 · see citing works
Self-citationCuijpers, P., Donker, T., van Straten, A., Li, J., & Andersson, G. (2010) · Psychological Medicine · doi:10.1017/s0033291710000772 · Cited by 832 · see citing works
Self-citationInternet-based psychological treatments for depression
Johansson, R., & Andersson, G. (2012) · Expert Review of Neurotherapeutics · doi:10.1586/ern.12.63 · Cited by 509 · see citing works
Self-citationBeck Depression Inventory ( BDI )
Rosner, R. I. (2015) · The Encyclopedia of Clinical Psychology · doi:10.1002/9781118625392.wbecp261 · Cited by 420 · see citing works
GELLATLY, J., BOWER, P., HENNESSY, S., RICHARDS, D., GILBODY, S., & LOVELL, K. (2007) · Psychological Medicine · doi:10.1017/s0033291707000062 · Cited by 419 · cited 1× · see citing works
“…patients work through on their own without guidance) show less promising results than guided web-based interventions that are delivered with support from a coach or therapist (Gellatly et al. 2007; Spek et al. 2007a; Andersson & Cuijpers, 2009; Cuijpers et al. 2011; Richards & Richardson, 2012).”
BackgroundWaller, R., & Gilbody, S. (2009) · Psychological Medicine · doi:10.1017/s0033291708004224 · Cited by 393 · cited 2× · see citing works
“A few studies have already investigated this issue (Christensen et al. 2009; Waller & Gilbody, 2009).”
BackgroundClarke, G., Eubanks, D., Reid, E., Kelleher, C., O'Connor, E., DeBar, L. L., Lynch, F., Nunley, S., & Gullion, C. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.2.e16 · Cited by 372 · cited 2× · see citing works
“We were unable to retrieve the data from three studies (Clarke et al. 2002, 2005, 2009) and included 10 RCTs in the present IPD meta-analysis (77%).”
BackgroundMethodMeyer, B., Berger, T., Caspar, F., Beevers, C. G., Andersson, G., & Weiss, M. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1151 · Cited by 363 · see citing works
Self-citationBower, P., Kontopantelis, E., Sutton, A., Kendrick, T., Richards, D. A., Gilbody, S., Knowles, S., Cuijpers, P., Andersson, G., Christensen, H., et al. (2013) · BMJ · doi:10.1136/bmj.f540 · Cited by 341 · see citing works
Self-citationSPEK, V., NYKLÍČEK, I., SMITS, N., CUIJPERS, P., RIPER, H., KEYZER, J., & POP, V. (2007) · Psychological Medicine · doi:10.1017/s0033291707000542 · Cited by 307 · see citing works
Self-citationBerger, T., Caspar, F., Richardson, R., Kneubühler, B., Sutter, D., & Andersson, G. (2011) · Behaviour Research and Therapy · doi:10.1016/j.brat.2010.12.007 · Cited by 265 · cited 3× · see citing works
“during a diagnostic interview; Johansson and Andersson, 2012) or include referral by a therapist (Marks & Cavanagh, 2009; Berger et al. 2011), which may add to feelings of accountability.”
BackgroundSelf-citationClarke, G., Reid, E., Eubanks, D., O'Connor, E., DeBar, L. L., Kelleher, C., Lynch, F., & Nunley, S. (2002) · Journal of Medical Internet Research · doi:10.2196/jmir.4.3.e14 · Cited by 256 · cited 2× · see citing works
“We were unable to retrieve the data from three studies (Clarke et al. 2002, 2005, 2009) and included 10 RCTs in the present IPD meta-analysis (77%).”
BackgroundMethodSelf-guided psychological treatment for depressive symptoms: a meta-analysis
Cuijpers, P., Donker, T., Johansson, R., Mohr, D. C., van Straten, A., & Andersson, G. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021274 · Cited by 250 · see citing works
Self-citationPsychological treatment of depression: A meta-analytic database of randomized studies
Cuijpers, P. J., van Straten, A., Warmerdam, L., & Andersson, G. (2008) · BMC Psychiatry · doi:10.1186/1471-244x-8-36 · Cited by 241 · see citing works
Self-citationVernmark, K., Lenndin, J., Bjärehed, J., Carlsson, M., Karlsson, J., Öberg, J., Carlbring, P., Eriksson, T., & Andersson, G. (2010) · Behaviour Research and Therapy · doi:10.1016/j.brat.2010.01.005 · Cited by 226 · see citing works
Self-citationRiley, R. D., Simmonds, M. C., & Look, M. P. (2007) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2006.09.009 · Cited by 195 · see citing works
de Graaf, L. E., Gerhards, S. A. H., Arntz, A., Riper, H., Metsemakers, J. F. M., Evers, S. M. A. A., Severens, J. L., Widdershoven, G., & Huibers, M. J. H. (2009) · British Journal of Psychiatry · doi:10.1192/bjp.bp.108.054429 · Cited by 190 · see citing works
Self-citationClarke, G., Kelleher, C., Hornbrook, M., DeBar, L., Dickerson, J., & Gullion, C. (2009) · Cognitive Behaviour Therapy · doi:10.1080/16506070802675353 · Cited by 154 · see citing works
Donker, T., Bennett, K., Bennett, A., Mackinnon, A., van Straten, A., Cuijpers, P., Christensen, H., & Griffiths, K. M. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2307 · Cited by 154 · see citing works
Self-citationFarrer, L., Christensen, H., Griffiths, K. M., & Mackinnon, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0028099 · Cited by 140 · see citing works
Self-citationA randomized controlled trial of internet-based therapy in depression
Moritz, S., Schilling, L., Hauschildt, M., Schröder, J., & Treszl, A. (2012) · Behaviour Research and Therapy · doi:10.1016/j.brat.2012.04.006 · Cited by 140 · see citing works
Predictors of outcome of group and internet-based cognitive behavior therapy
Spek, V., Nyklíček, I., Cuijpers, P., & Pop, V. (2008) · Journal of Affective Disorders · doi:10.1016/j.jad.2007.05.001 · Cited by 134 · see citing works
Computer-Aided Psychological Treatments: Evolving Issues
Marks, I., & Cavanagh, K. (2009) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.032408.153538 · Cited by 133 · cited 1× · see citing works
“…the program but also more often than unguided interventions include human contact before treatment (e.g. during a diagnostic interview; Johansson and Andersson, 2012) or include referral by a therapist (Marks & Cavanagh, 2009; Berger et al. 2011), which may add to feelings of accountability.”
BackgroundBabwah, F., Baksh, S., Blake, L., Cupid-Thuesday, J., Hosein, I., Sookhai, A., Poon-King, C., & Hutchinson, G. (2006) · Revista Panamericana de Salud Pública · doi:10.1590/s1020-49892006000200002 · Cited by 63 · see citing works
de Graaf, L. E., Gerhards, S. A. H., Arntz, A. R., Riper, H. M., Metsemakers, J. F. M., Evers, S., Severens, J. L., Widdershoven, G. A. M., & Huibers, M. J. H. (2010) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/j.jbtep.2010.07.003 · Cited by 46 · see citing works
Self-citation
Flagged first, then by citations
2 of the 37 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Carlbring, P., Andersson, G., Cuijpers, P., Riper, H., & Hedman-Lagerlöf, E. (2018) · Cognitive Behaviour Therapy · doi:10.1080/16506073.2017.1401115 · Cited by 1,232 · see citing works
Self-citationKaryotaki, E., Riper, H., Twisk, J., Hoogendoorn, A., Kleiboer, A., Mira, A., Mackinnon, A., Meyer, B., Botella, C., Littlewood, E., et al. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.0044 · Cited by 691 · see citing works
Self-citationGood intentions are not enough: how informatics interventions can worsen inequality
Veinot, T. C., Mitchell, H., & Ancker, J. S. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy052 · Cited by 704 · see citing works
Karyotaki, E., Ebert, D. D., Donkin, L., Riper, H., Twisk, J., Burger, S., Rozental, A., Lange, A., Williams, A. D., Zarski, A. C., et al. (2018) · Clinical Psychology Review · doi:10.1016/j.cpr.2018.06.007 · Cited by 303 · see citing works
Self-citationGan, D. Z. Q., McGillivray, L., Han, J., Christensen, H., & Torok, M. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.764079 · Cited by 305 · see citing works
Self-citationTorok, M., Han, J., Baker, S., Werner-Seidler, A., Wong, I., Larsen, M. E., & Christensen, H. (2020) · The Lancet Digital Health · doi:10.1016/s2589-7500(19)30199-2 · Cited by 273 · see citing works
Self-citationStubbs, B., Vancampfort, D., Rosenbaum, S., Ward, P. B., Richards, J., Soundy, A., Veronese, N., Solmi, M., & Schuch, F. B. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.10.019 · Cited by 284 · see citing works
Andrews, G., Bell, C., Boyce, P., Gale, C., Lampe, L., Marwat, O., Rapee, R., & Wilkins, G. (2018) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867418799453 · Cited by 243 · see citing works
Digital mental health: challenges and next steps
Smith, K., Blease, C. R., Faurholt‐Jepsen, M., Firth, J., Daele, T. V., Moreno, C., Carlbring, P., Ebner‐Priemer, U., Koutsouleris, N., Riper, H. M., et al. (2023) · BMJ Mental Health · doi:10.1136/bmjment-2023-300670 · Cited by 236 · see citing works
Self-citationInternet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions
Webb, C. A., Rosso, I. M., & Rauch, S. L. (2017) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000139 · Cited by 217 · see citing works
Brown, M., Glendenning, A., Hoon, A. E., & John, A. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6200 · Cited by 198 · see citing works
“For example, Karyotaki et al [66] advocate intervention completion to be defined as, completion of 75% or more of the total modules.”
BackgroundColombo, D., Fernández-Álvarez, J., Patané, A., Semonella, M., Kwiatkowska, M., García-Palacios, A., Cipresso, P., Riva, G., & Botella, C. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8040465 · Cited by 194 · see citing works
Self-citationEngagement and retention in digital mental health interventions: a narrative review
Boucher, E. M., & Raiker, J. S. (2024) · BMC Digital Health · doi:10.1186/s44247-024-00105-9 · Cited by 200 · see citing works
Was Eysenck right after all? A reassessment of the effects of psychotherapy for adult depression
Cuijpers, P. J., Karyotaki, E., Reijnders, M., & Ebert, D. D. (2018) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796018000057 · Cited by 174 · see citing works
Self-citationKlein, J. P., Berger, T., Schröder, J., Späth, C., Meyer, B., Caspar, F., Lutz, W., Arndt, A., Greiner, W., Gräfe, V., et al. (2016) · Psychotherapy and Psychosomatics · doi:10.1159/000445355 · Cited by 145 · see citing works
Self-citationRozental, A., Magnusson, K., Boettcher, J., Andersson, G., & Carlbring, P. (2017) · Journal of Consulting and Clinical Psychology · doi:10.1037/ccp0000158 · Cited by 137 · see citing works
Self-citationScholten, H., & Granic, I. (2019) · Journal of Medical Internet Research · doi:10.2196/11528 · Cited by 138 · see citing works
Karekla, M., Kasinopoulos, O., Neto, D. D., Ebert, D. D., Van Daele, T., Nordgreen, T., Höfer, S., Oeverland, S., & Jensen, K. L. (2019) · European Psychologist · doi:10.1027/1016-9040/a000349 · Cited by 117 · see citing works
Alfonsson, S., Olsson, E., & Hursti, T. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5352 · Cited by 118 · see citing works
Philipp, R., Kriston, L., Lanio, J., Kühne, F., Härter, M., Moritz, S., & Meister, R. (2019) · Clinical Psychology & Psychotherapy · doi:10.1002/cpp.2345 · Cited by 114 · see citing works
Self-citationSuicide Postvention Service Models and Guidelines 2014–2019: A Systematic Review
Andriessen, K., Krysinska, K., Kõlves, K., & Reavley, N. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02677 · Cited by 114 · see citing works
The association between adherence and outcome in an Internet intervention for depression
Fuhr, K., Schröder, J., Berger, T., Moritz, S., Meyer, B., Lutz, W., Hohagen, F., Hautzinger, M., & Klein, J. P. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.12.028 · Cited by 97 · see citing works
Self-citationInternet interventions for depression: new developments
Schröder, J., Berger, T., Westermann, S., Klein, J. P., & Moritz, S. (2016) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2016.18.2/jschroeder · Cited by 105 · see citing works
Self-citationMindfulness for pregnancy: a randomised controlled study of online mindfulness during pregnancy
Krusche, A., Dymond, M., Murphy, S. E., & Crane, C. (2018) · Midwifery · doi:10.1016/j.midw.2018.07.005 · Cited by 97 · see citing works
Leech, T., Dorstyn, D., Taylor, A. M., & Li, W. (2021) · Children and Youth Services Review · doi:10.1016/j.childyouth.2021.106073 · Cited by 102 · see citing works
Lindqvist, K., Mechler, J., Carlbring, P., Lilliengren, P., Falkenström, F., Andersson, G., Johansson, R., Edbrooke-Childs, J. H., Dahl, H. J., Bergsten, K. L., et al. (2020) · Journal of Medical Internet Research · doi:10.2196/18047 · Cited by 95 · see citing works
Self-citationPredictors of Dropout in Internet-Based Cognitive Behavioral Therapy for Depression
Ezawa, I. D., Forand, N. R., & Strunk, D. R. (2018) · Cognitive Therapy and Research · doi:10.1007/s10608-018-9979-5 · Cited by 92 · see citing works
Fonseca, A., Alves, S., Monteiro, F., Gorayeb, R., & Canavarro, M. C. (2020) · Behavior Therapy · doi:10.1016/j.beth.2019.09.007 · Cited by 82 · see citing works
The challenger app for social anxiety disorder: New advances in mobile psychological treatment
Miloff, A., Marklund, A., & Carlbring, P. (2015) · Internet Interventions · doi:10.1016/j.invent.2015.08.001 · Cited by 87 · see citing works
Self-citationZarski, A.-C., Berking, M., Reis, D., Lehr, D., Buntrock, C., Schwarzer, R., & Ebert, D. D. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8814 · Cited by 87 · see citing works
“The findings of previous studies can, however, explain the variance in adherence only to some extent [9-12], with findings of, inter alia, 11% [13].”
ResultGan, D. Z. Q., McGillivray, L., Larsen, M. E., Christensen, H. M., & Torok, M. H. (2022) · Digital Health · doi:10.1177/20552076221098268 · Cited by 80 · see citing works
Self-citationLöbner, M., Pabst, A., Stein, J., Dorow, M., Matschinger, H., Luppa, M., Maroß, A., Kersting, A., König, H.-H., & Riedel-Heller, S. G. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2018.06.008 · Cited by 72 · see citing works
Rozental, A., Shafran, R., Wade, T., Egan, S., Nordgren, L. B., Carlbring, P., Landström, A., Roos, S., Skoglund, M., Thelander, E., et al. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2017.05.015 · Cited by 76 · see citing works
Self-citationTwomey, C. D., O’Reilly, G., Bültmann, O., & Meyer, B. (2020) · PLoS ONE · doi:10.1371/journal.pone.0228100 · Cited by 75 · see citing works
Self-citationRozental, A., Andersson, G., & Carlbring, P. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00589 · Cited by 74 · see citing works
Self-citationSmail-Crevier, R., Powers, G., Noël, C., & Wang, J. (2018) · Journal of Medical Internet Research · doi:10.2196/11224 · Cited by 75 · see citing works
Chatbot-Based Assessment of Employees’ Mental Health: Design Process and Pilot Implementation
Hungerbuehler, I., Daley, K., Cavanagh, K., Garcia Claro, H., & Kapps, M. (2021) · JMIR Formative Research · doi:10.2196/21678 · Cited by 73 · see citing works
Karin, E., Dear, B. F., Heller, G. Z., Crane, M. F., & Titov, N. (2018) · JMIR Mental Health · doi:10.2196/mental.8363 · Cited by 67 · see citing works
Andersson, G., Carlbring, P., & Rozental, A. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00749 · Cited by 71 · see citing works
“Second, predictors of dropout (85) may ultimately be more illuminating, even if a given IPDMA was on self-guided ICBT for depressive symptoms.”
BackgroundSelf-citationMira, A., Bretón-López, J., García-Palacios, A., Quero, S., Baños, R. M., & Botella, C. (2017) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s130994 · Cited by 71 · see citing works
Self-citationDe Jaegere, E., van Landschoot, R., van Heeringen, K., van Spijker, B. A. J., Kerkhof, A. J. F. M., Mokkenstorm, J. K., & Portzky, G. (2019) · Behaviour Research and Therapy · doi:10.1016/j.brat.2019.05.003 · Cited by 71 · see citing works
Kolovos, S., van Dongen, J. M., Riper, H., Buntrock, C., Cuijpers, P., Ebert, D. D., Geraedts, A. S., Kenter, R. M., Nobis, S., Smith, A., et al. (2018) · Depression and Anxiety · doi:10.1002/da.22714 · Cited by 63 · see citing works
Self-citationPsychoeducation for breast cancer: A systematic review and meta-analysis
Setyowibowo, H., Yudiana, W., Hunfeld, J. A. M., Iskandarsyah, A., Passchier, J., Arzomand, H., Sadarjoen, S. S., de Vries, R., & Sijbrandij, M. (2022) · The Breast · doi:10.1016/j.breast.2022.01.005 · Cited by 74 · see citing works
Wallert, J., Gustafson, E., Held, C., Madison, G., Norlund, F., von Essen, L., & Olsson, E. M. G. (2018) · doi:10.2196/preprints.10754 · Cited by 63 · see citing works
Fernández-Álvarez, J., Díaz-García, A., González-Robles, A., Baños, R., García-Palacios, A., & Botella, C. (2017) · Internet Interventions · doi:10.1016/j.invent.2017.09.001 · Cited by 60 · see citing works
Self-citationOehler, C., Görges, F., Rogalla, M., Rummel‐Kluge, C., & Hegerl, U. (2020) · Journal of Medical Internet Research · doi:10.2196/15361 · Cited by 56 · see citing works
Jardine, J., Nadal, C., Robinson, S., Enrique, Á., Hanratty, M., & Doherty, G. J. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3635472 · Cited by 55 · see citing works
Probst, G. H., Berger, T., & Flückiger, C. (2022) · Verhaltenstherapie · doi:10.1159/000503432 · Cited by 54 · see citing works
Self-citationMeyer, B., Weiss, M., Holtkamp, M., Arnold, S., Brückner, K., Schröder, J., Scheibe, F., & Nestoriuc, Y. (2019) · Epilepsia · doi:10.1111/epi.14673 · Cited by 53 · see citing works
Self-citationKok, R. N., van Straten, A., Beekman, A. T. F., & Cuijpers, P. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3429 · Cited by 50 · see citing works
Self-citationMathiasen, K., Riper, H., Andersen, T. E., & Roessler, K. K. (2018) · Journal of Medical Internet Research · doi:10.2196/10927 · Cited by 48 · see citing works
Self-citationGulliver, A., Calear, A. L., Sunderland, M., Kay-Lambkin, F., Farrer, L. M., & Batterham, P. J. (2021) · Internet Interventions · doi:10.1016/j.invent.2021.100400 · Cited by 44 · see citing works
“…adherence in depression and anxiety interventions, we found no evidence for many of the previously identified predictive factors for adherence including baseline symptom levels, gender, age, or education (Christensen et al., 2009; Farrer et al., 2014; Karyotaki et al., 2015; Beatty et al., 2017).”
BackgroundSelf-citationBüscher, R., Beisemann, M., Doebler, P., Micklitz, H. M., Kerkhof, A. J. F. M., Cuijpers, P. J., Batterham, P. J., Calear, A. L., Christensen, H. M., Jaegere, E. D., et al. (2022) · Evidence-Based Mental Health · doi:10.1136/ebmental-2022-300540 · Cited by 49 · see citing works
Self-citationCooper, A. A., Kline, A. C., Baier, A. L., & Feeny, N. C. (2018) · Behavior Modification · doi:10.1177/0145445518792251 · Cited by 47 · see citing works
Esfandiari, N., Mazaheri, M. A., Akbari-Zardkhaneh, S., Sadeghi-Firoozabadi, V., & Cheraghi, M. (2021) · International Journal of Preventive Medicine · doi:10.4103/ijpvm.ijpvm_208_21 · Cited by 45 · see citing works
Online psychotherapy: trailblazing digital healthcare
McDonald, A., Eccles, J. A., Fallahkhair, S., & Critchley, H. D. (2020) · BJPsych Bulletin · doi:10.1192/bjb.2019.66 · Cited by 45 · see citing works
Zheng, S., Edney, S. M., Goh, C. H., Tai, B. C., Mair, J. L., Castro, Ó., Salamanca-Sanabria, A., Kowatsch, T., van Dam, R. M., & Müller‐Riemenschneider, F. (2023) · EClinicalMedicine · doi:10.1016/j.eclinm.2023.102309 · Cited by 51 · see citing works
Alfonsson, S., Johansson, K., Uddling, J., & Hursti, T. J. (2017) · BMC Psychology · doi:10.1186/s40359-017-0172-5 · Cited by 46 · see citing works
Spence, S. H., March, S., & Donovan, C. L. (2019) · Internet Interventions · doi:10.1016/j.invent.2019.100268 · Cited by 45 · see citing works
Haller, K., Becker, P., Niemeyer, H., & Boettcher, J. (2023) · Internet Interventions · doi:10.1016/j.invent.2023.100635 · Cited by 46 · see citing works
Effects of sex, race, ethnicity, and education on online aging research participation
Ashford, M. T., Eichenbaum, J., Williams, T., Camacho, M. R., Fockler, J., Ulbricht, A., Flenniken, D., Truran, D., Mackin, R. S., Weiner, M. W., et al. (2020) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12028 · Cited by 44 · see citing works
Steubl, L., Sachser, C., Baumeister, H., & Domhardt, M. (2021) · European Journal of Psychotraumatology · doi:10.1080/20008198.2021.1879551 · Cited by 42 · see citing works
Wyssen, A., Meyer, A. H., Messerli‐Bürgy, N., Forrer, F., Vanhulst, P., Lalanne, D., & Munsch, S. (2021) · European Eating Disorders Review · doi:10.1002/erv.2856 · Cited by 40 · see citing works
Microinterventions produce immediate but not lasting benefits in mood and distress
Elefant, A. B., Contreras, O., Muñoz, R. F., Bunge, E. L., & Leykin, Y. (2017) · Internet Interventions · doi:10.1016/j.invent.2017.08.004 · Cited by 41 · see citing works
Karin, E., Crane, M. F., Dear, B. F., Nielssen, O., Heller, G. Z., Kayrouz, R., & Titov, N. (2021) · JMIR Mental Health · doi:10.2196/22700 · Cited by 36 · see citing works
McClure, Z., Fuller‐Tyszkiewicz, M., Messer, M., & Linardon, J. (2023) · International Journal of Eating Disorders · doi:10.1002/eat.24078 · Cited by 40 · see citing works
Schröder, J., Werkle, N., Cludius, B., Jelinek, L., Moritz, S., & Westermann, S. (2020) · Depression and Anxiety · doi:10.1002/da.23105 · Cited by 40 · see citing works
Self-citationPredictive modeling in e-mental health: A common language framework
Becker, D., van Breda, W., Funk, B., Hoogendoorn, M., Ruwaard, J., & Riper, H. M. (2018) · Internet Interventions · doi:10.1016/j.invent.2018.03.002 · Cited by 40 · see citing works
Self-citationPredicting early dropout in online versus face-to-face guided self-help: A machine learning approach
Gonzalez Salas Duhne, P., Delgadillo, J., & Lutz, W. (2022) · Behaviour Research and Therapy · doi:10.1016/j.brat.2022.104200 · Cited by 38 · see citing works
Furukawa, T. A., Tajika, A., Toyomoto, R., Sakata, M., Luo, Y., Horikoshi, M., Akechi, T., Kawakami, N., Nakayama, T., Kondo, N., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03639-1 · Cited by 40 · see citing works
Self-citationLawler, K., Earley, C., Timulák, L., Enrique, Á., & Richards, D. (2021) · JMIR Formative Research · doi:10.2196/26221 · Cited by 38 · see citing works
Newman, M. G., Kanuri, N., Rackoff, G. N., Jacobson, N. C., Bell, M. J., & Taylor, C. B. (2021) · Psychotherapy · doi:10.1037/pst0000383 · Cited by 34 · see citing works
User engagement in clinical trials of digital mental health interventions: a systematic review
Elkes, J., Cro, S., Batchelor, R., O’Connor, S., Yu, L., Bell, L., Harris, V., Sin, J., & Cornelius, V. R. (2024) · BMC Medical Research Methodology · doi:10.1186/s12874-024-02308-0 · Cited by 37 · see citing works
Beshai, S., Bueno, C., Yu, M., Feeney, J. R., & Pitariu, A. (2020) · Behaviour Research and Therapy · doi:10.1016/j.brat.2020.103724 · Cited by 35 · see citing works
Mathiasen, K., Andersen, T. E., Lichtenstein, M. B., Ehlers, L. H., Riper, H., Kleiboer, A., & Roessler, K. K. (2022) · Journal of Medical Internet Research · doi:10.2196/36577 · Cited by 34 · see citing works
Self-citationMira, A., González-Robles, A., Molinari, G., Miguel, C., Díaz-García, A., Bretón-López, J., García-Palacios, A., Quero, S., Baños, R., & Botella, C. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00180 · Cited by 35 · see citing works
Self-citationDigitalising mental health care: Practical recommendations from the European Psychiatric Association
Kalman, J. L., Burkhardt, G., Samochowiec, J., Gebhard, C., Dom, G., John, M., Kılıç, Ö., Kurimay, T., Lien, L., Schouler‐Ocak, M., et al. (2023) · European Psychiatry · doi:10.1192/j.eurpsy.2023.2466 · Cited by 34 · see citing works
Opie, J. E., Vuong, A. T., Welsh, E. T., Gray, R. J., Pearce, N., Marchionda, S., Mutch, R., & Khalil, H. (2024) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-024-00469-4 · Cited by 35 · see citing works
Exploring the features of an app-based just-in-time intervention for depression
Everitt, N., Broadbent, J., Richardson, B., Smyth, J. M., Heron, K. E., Teague, S. J., & Fuller‐Tyszkiewicz, M. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.05.021 · Cited by 33 · see citing works
Farrall, A., Taylor, J., Ainsworth, B., & Alexander, J. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581188 · Cited by 32 · see citing works
Lukka, L., & Palva, J. M. (2023) · JMIR Serious Games · doi:10.2196/42173 · Cited by 32 · see citing works
Predicting treatment effects in unipolar depression: A meta-review
Gillett, G., Tomlinson, A., Efthimiou, O., & Cipriani, A. (2020) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2020.107557 · Cited by 33 · see citing works
Domhardt, M., Nowak, H., Engler, S., Baumel, A., Grund, S., Mayer, A., Terhorst, Y., & Baumeister, H. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2021.102084 · Cited by 32 · see citing works
Opie, J. E., Vuong, A. T., Welsh, E. T., Esler, T. B., Khan, U. R., & Khalil, H. (2024) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-024-00468-5 · Cited by 39 · see citing works
Fassnacht, D. B., Ali, K., van Agteren, J. E., Iasiello, M. P., Mavrangelos, T., Furber, G., & Kyrios, M. (2022) · JMIR Mental Health · doi:10.2196/37292 · Cited by 31 · see citing works
Kenter, R. M. F., Gjestad, R., Lundervold, A. J., & Nordgreen, T. (2023) · Internet Interventions · doi:10.1016/j.invent.2023.100614 · Cited by 30 · see citing works
Kerber, A., Beintner, I., Burchert, S., & Knaevelsrud, C. (2023) · JMIR Mental Health · doi:10.2196/45068 · Cited by 32 · see citing works
A New Research Model for Artificial Intelligence–Based Well-Being Chatbot Engagement: Survey Study
Yang, Y., Tavares, J., & Oliveira, T. (2024) · JMIR Human Factors · doi:10.2196/59908 · Cited by 42 · see citing works
Mira, A., Soler, C., Alda, M., Baños, R., Castilla, D., Castro, A., García-Campayo, J., García-Palacios, A., Gili, M., Hurtado, M., et al. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00325 · Cited by 29 · see citing works
“According to a recent individual patient data meta-analysis (IPDM) (78), younger ages were related to more dropouts.”
BackgroundInfluentialSelf-citationNegative effects in internet-based interventions for depression: a qualitative content analysis
Fenski, F., Rozental, A., Heinrich, M., Knaevelsrud, C., Zagorscak, P., & Boettcher, J. (2021) · Internet Interventions · doi:10.1016/j.invent.2021.100469 · Cited by 28 · see citing works
Pontén, M., Jonsjö, M. A., Vadenmark, V., Moberg, E., Grannas, D., Andersson, G., Boersma, K., Hedman‐Lagerlöf, E., Kleinstäuber, M., Weise, C., et al. (2023) · Psychological Medicine · doi:10.1017/s0033291723003033 · Cited by 31 · see citing works
Self-citationZainal, N. H., Soh, C. P., Doren, N. V., & Benjet, C. L. (2024) · Clinical Psychology Review · doi:10.1016/j.cpr.2024.102518 · Cited by 32 · see citing works
Kolovos, S., Kenter, R. M. F., Bosmans, J. E., Beekman, A. T. F., Cuijpers, P. J., Kok, R. N., & van Straten, A. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.04.025 · Cited by 29 · see citing works
Self-citationIntegrating storytelling into the theory and practice of contextual behavioral science
Davis, C. H., Gaudiano, B. A., McHugh, L., & Levin, M. E. (2021) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2021.04.004 · Cited by 29 · see citing works
Moshe, I., Terhorst, Y., Paganini, S., Schlicker, S., Pulkki-Råback, L., Baumeister, H., Sander, L. B., & Ebert, D. D. (2022) · Journal of Medical Internet Research · doi:10.2196/38261 · Cited by 28 · see citing works
“In a meta-analysis of individual patient data, Karyotaki et al [33] found that being male, having a lower education level, younger age, and comorbid anxiety symptoms significantly increased the risk of dropout from self-guided digital interventions for depression.”
InfluentialCastro, A., Roca, M., Ricci‐Cabello, I., Garcı́a-Toro, M., Serra, P. R., Coronado-Simsic, V., Pérez-Ara, M. Á., & Gili, M. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182413268 · Cited by 28 · see citing works
Chow, P. I., Drago, F., Kennedy, E. M., & Cohn, W. F. (2019) · JMIR Cancer · doi:10.2196/15750 · Cited by 28 · see citing works
Adaptive Systems for Internet-Delivered Psychological Treatments
Mukhiya, S. K., Wake, J. D., İnal, Y., & Lamo, Y. (2020) · IEEE Access · doi:10.1109/access.2020.3002793 · Cited by 28 · see citing works
Development of an Internet Intervention to Promote Wellbeing in College Students
Stallman, H. M., & Kavanagh, D. J. (2018) · Australian Psychologist · doi:10.1111/ap.12246 · Cited by 27 · see citing works
Wade, T. D., Kay, E., de Valle, M. K., Egan, S. J., Andersson, G., Carlbring, P., & Shafran, R. (2019) · Clinical Psychologist · doi:10.1111/cp.12193 · Cited by 27 · see citing works
Self-citation
- Authors
- Karyotaki, E., Kleiboer, A., Smit, F., Turner, D. T., Pastor, A. M., Andersson, G., Berger, T., Botella, C., Breton, J. M., Carlbring, P., Christensen, H., de Graaf, E., Griffiths, K., Donker, T., Farrer, L., Huibers, M. J. H., Lenndin, J., Mackinnon, A., Meyer, B., Moritz, S., Riper, H., Spek, V., Vernmark, K., & Cuijpers, P.
- Affiliations
- Amsterdam Public Health (NL)
- Trimbos Institute (NL)
- Universitat Jaume I (ES)
- Linköping University (SE)
- University of Bern (CH)
- Stockholm University (SE)
- Black Dog Institute (AU)
- Australian National University (AU)
- The University of Melbourne (AU)
- City, University of London (GB)
- University Medical Center Hamburg-Eppendorf (DE)
- Avans University of Applied Sciences (NL)
- Corresponding author
- Karyotaki, E.
- ORCID
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2015-04-17
- Volume
- 45
- Issue
- 13
- Pages
- 2717-2726
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- OpenAlex
- W2133074847
- Cited by
- 408
- References
- 37
- Citations by year
- 2026: 38 · 2025: 47 · 2024: 57 · 2023: 46 · 2022: 39 · 2021: 44 · 2020: 33 · 2019: 32 · 2018: 29 · 2017: 23 · 2016: 14 · 2015: 4 · 2014: 1
- FWCI
- 3.25
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Psychological Medicine (publishedVersion)
- Research portal (Tilburg University) (publishedVersion)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- Repositori UJI (Universitat Jaume I) (acceptedVersion)
- reroDoc Digital Library (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- BORIS (University Library Bern) (submittedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- ANU Open Research (Australian National University) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Open Access CRIS of the University of Bern
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Keywords
- treatment discontinuation, depression, predictors of dropout, online self-help, individual patient data, gender differences, educational attainment, anxiety comorbidity, age, intervention tailoring
- MeSH terms
- Anxiety, Depression, Humans, Patient Dropouts, Prognosis, Psychotherapy, Randomized Controlled Trials as Topic, Internet
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
