ABSTRACT
The COVID-19 epidemic has hastened the growth of Virtual Communities and is affecting virtually every part of work in the public and business sectors. Virtual communities, popular forums for communication and entertainment, increasingly affected the users' decisions. Though many technology adoption models/theories are available, a distinctive model for decision-making in a virtual environment is scarce. This research developed the virtual communities' decision model and empirically tested its performance. This study examined 16 well-established theories/models of information technology, social science, marketing, and behavioral finance and extracted nine constructs from 58 identified constructs considering theoretical cohesiveness along with the three-stage method proposed by Moore and Benbasat. A unified model for virtual communities' decisions (VCDM) is developed and validated using the data collected from individual capital market investors in Bangladesh. The structural equation modeling technique is used to analyze the data. The upshot implies that VCDM performs adequately and explains the maximum variances in intention to decision and investment. VCDM also outperforms the majority of the related theoretical models. The acceptance levels of fit indices and all significant relationships among different constructs are also empirically validated. The moderating effect of the virtual group use experience is also confirmed. Future research can use VCDM in marketing, behavioral finance, ecommerce, information systems and social science context. VCDM thus facilitates a beneficial tool for managers, service providers, and other users to assess the likelihood of effectiveness for decisions in a virtual environment.
ABSTRACT
Background The outbreak of COVID-19 pandemic in China has greatly impacted the radiotherapy (RT) strategy forbreast cancer (BC) patients, which might lead to an increased distressing psychological symptom. Thus, we performa multi-center cross-section survey aiming to investigate the prevalence of fears of cancer recurrence (FCR) andexplore predictors for FCR in BC patients referred for RT during pandemic. Methods: 542 BC patients who referredfor RT between 24 Jan and 30 April 2020 during pandemic were consecutively enrolled from 14 hospitals aroundChina including Yangtze Delta River Region, Guangdong and Shanxi province. Patients' sociodemographic,treatment information as well as psychological characteristics were collected using an information sheet, Fear ofprogression questionnaire-short form (FoP-Q-SF), Hospital Anxiety and Depression Scale ( HADS) and EORTCQLQ-C30. The influence of pandemic on RT schedule was divided into four categories: “delay” was defined as >12weeks from surgery to RT in patients without chemotherapy or >8 weeks from last time of anti-tumor therapy(including chemotherapy and surgery) to RT in patients with chemotherapy;“Special normal” was defined thatpatients themselves believed to have delayed RT initiation but actually not;“Interruption” was defined as anyunplanned gaps in original RT regime and all other would be classified into “normal”. Another type of influence on th th Advertisement RT strategy was that patients had to shift planned RT hospital from Grade-A tertiary hospital to local hospitals.Univariable analyses of FCR were performed in a one-way analysis of variance (ANOVA) or student t-test orPearson correlation analyses and candidate variables with P<0.2 were included Hierarchical multiple regressionmodels to investigate predictors for FCR. Guangdong province was chosen as reference in models. Results 488patients with complete data were eligible for the present analysis and none of patients and their family members hadbeen diagnosed as COVID-19. The RT strategy was affected in 265 (54.3%) patients, including 143 with delayed RTinitiation, 66 with “special normal” schedule, 24 (4.9%) with RT interruptions, 19 shifting to local hospitals for RT, andthe remaining 13 being influenced on both RT schedule and planned RT hospitals. Most of patients with affected RTstrategy occurred in late January and February, when was peak of COVID-19 pandemic in China. The mean FCRscores was 24.83 (SD=8.554) and 84 patients (17.3%) were classified as dysfunctional level of FCR (sum score≥34). In univariable analyses, FCR were significantly higher in patients who received RT in Guangdong provinceand in hospitals with < 100 BC cases per year. In term of during pandemic, a significant difference in FCR wasobserved in terms of influence on RT schedule (p<0.001). and changes of hospital levels(p=0.009). There weresignificant correlations between FCR and anxiety/depressive in HADS or all five function scales (physical, role,emotional, cognitive and social) and global QoL in QLQ-C30 (p<0.001). Finally, the model explained 59.7% ofobserved variances in FCR and showed that influence of RT strategy during pandemic had significantly impacted onFCR (ΔR2=0.01, ΔF=2.966, p=0.019). Hospitals in Shanxi province (β=-0.117, p=0.001), emotional function(β=-0.19, p<0.001), social function (β=-0.111, p=0.006), anxiety (β=0.434, p<0.001) and RT interruption (β=0.071,p=0.035) were independent predictors for FCR. Conclusions RT strategy for BC patients was greatly influencedduring pandemic. RT interruption is an independent predictor for high FCR. Our findings emphasize the necessity toensure the continuum of RT in BC patients, and efforts should be taken to alleviate the FCR through psychologicalinterventions.