| Literature DB >> 33824504 |
Adrià López-Fernández1, Guillermo Villacampa2, Elia Grau3, Mónica Salinas3, Esther Darder4, Estela Carrasco1,5, Sara Torres-Esquius1, Silvia Iglesias3, Ares Solanes6, Neus Gadea5, Angela Velasco4, Gisela Urgell7, Maite Torres1, Noemí Tuset7, Joan Brunet4, Sergi Corbella8, Judith Balmaña9,10.
Abstract
PURPOSE: To identify predictors of patient acceptance of non-in-person cancer genetic visits before and after the COVID-19 pandemic and assess the preferences of health-care professionals.Entities:
Mesh:
Year: 2021 PMID: 33824504 PMCID: PMC8023774 DOI: 10.1038/s41436-021-01157-2
Source DB: PubMed Journal: Genet Med ISSN: 1098-3600 Impact factor: 8.822
Demographic, clinical, and psychological characteristics of the patients participating in the study.
| Before the COVID-19 pandemic (T0 and T1) | During the COVID-19 pandemic (T2) | |
|---|---|---|
| Female | 433 (74.9) | 333 (75.9) |
| Male | 145 (25.1) | 106 (24.1) |
| 48.2 [39–58]a | 46.7 [39–55]a | |
| <30 | 57 (9.9) | 43 (9.8) |
| 31–40 | 115 (19.9) | 96 (21.9) |
| 41–50 | 171 (29.6) | 148 (33.7) |
| 51–60 | 123 (21.2) | 90 (20.5) |
| 61–70 | 79 (13.7) | 45 (10.2) |
| >70 | 33 (5.7) | 17 (3.9) |
| High school or more | 495 (85.6) | 319 (72.7) |
| Up to secondary school | 83 (14.4) | 120 (27.3) |
| Yes | 443 (76.6) | 328 (74.7) |
| No | 135 (23.4) | 111 (25.3) |
| Yes | 312 (54) | 236 (53.8) |
| No | 266 (46) | 203 (46.2) |
| cancer | 249 (43.1) | 190 (43.2) |
| Multiple cancers | 63 (10.9) | 46 (10.5) |
| Breast cancer | 201 (64.5) | 160 (67.8) |
| Ovarian cancer | 46 (14.7) | 27 (11.4) |
| Colorectal cancer | 20 (6.4) | 16 (6.8) |
| Other cancer | 45 (14.4) | 33 (14) |
| Single PV testing | 259 (44.8) | 197 (44.9) |
| Panel testing | 319 (55.2) | 242 (55.1) |
| No PV detected | 432 (74.7) | 328 (74.7) |
| PV detected | 146 (25.3) | 111 (25.3) |
| Baseline | 11.2 [9–13]a | 11.1 [9–13]a |
| Post-test | 10.9 [8–12.75]a | 10.8 [9–12]a |
| 6.3 [2–9]a | 6.2 [2–9]a | |
| Neuroticism | ||
| High | 326 (56.4) | 244 (55.6) |
| Medium | 145 (25.1) | 107 (24.3) |
| Low | 107 (18.5) | 88 (20.1) |
| Extraversion | ||
| High | 114 (19.7) | 84 (19.1) |
| Medium | 193 (33.4) | 153 (34.9) |
| Low | 271 (46.9) | 202 (46) |
| Openness | ||
| High | 143 (24.7) | 123 (28) |
| Medium | 192 (33.2) | 141 (32) |
| Low | 243 (42.1) | 175 (40) |
| Agreeableness | ||
| High | 141 (24.4) | 112 (25.5) |
| Medium | 196 (33.9) | 153 (34.9) |
| Low | 241 (41.7) | 174 (39.6) |
| Conscientiousness | ||
| High | 125 (21.6) | 96 (21.9) |
| Medium | 135 (23.4) | 106 (24.1) |
| Low | 318 (55) | 237 (54) |
PV pathogenic variant.
aMedian [IQR].
Fig. 1Evolution of patients’ reported acceptance of non-in-person visits before and after the lockdown caused by COVID-19.
Acceptors (dark), decliners (light) of non-in-person visits.
Fig. 2Univariate and multivariate analyses of predictors of reported acceptance to pretest and result disclosure telephone-based visits, before the COVID-19 pandemic (N = 578).
a pretest and b result disclosure telephone-based visits. The percentage of acceptance with 95% CI is plotted for each variable. Odds ratio with 95% CI and p-values were calculated using the logistic model. PV pathogenic variant.
Fig. 3Univariate and multivariate analyses of predictors of reported acceptance to pretest and result disclosure videoconference-based visits, before the COVID-19 pandemic (N = 578).
a pretest and b result disclosure videoconference-based visits. The percentage of acceptance with 95% CI is plotted for each variable. Odds ratio with 95% CI and p-values were calculated using the logistic model. PV pathogenic variant.