Reaching Hard-to-Survey Populations: Mode Choice and Mode Preference

This study assesses the effect of response-mode choices on response rates, and responsemode preferences of hard-to-survey populations: young adults, full-time workers, big city inhabitants, and non-Western immigrants. Using address-based sampling, a stratified sample of 3,496 households was selected. The first group of sample members was contacted face to face and could choose between a CAPI and web response mode. The second group, contacted by telephone, could choose between CATI and web. The third group, contacted by telephone, was randomly allocated to a response mode. Our address-based sampling technique was successful in reaching most of the hard-to-survey groups. Insufficient numbers of non- Western immigrants were reached; therefore this group was excluded from our analyses. In our mixed-effect models, no significant effects on the willingness to participate were found for mode choice. We found that full-time workers and young adults were significantly more likely to choose web over CAPI when contacted face to face

Educational inequalities in cancer survival: A role for comorbidities and health behaviours?

Aim: To describe educational inequalities in cancer survival and to what extent these can be explained by comorbidity and health behaviours (smoking, physical activity and alcohol consumption). Methods: The GLOBE study sent postal questionnaires to individuals in The Netherlands in 1991 resulting in 18 973 respondents (response 70%). Questions were asked on education, health and health-related behaviours. Participants were linked for cancer diagnosis (1991-2008), comorbidity and survival (up to 2010) with the population-based Eindhoven Cancer Registry; 1127 tumours were included in the analyses. Results: 5-year crude survival was best in highly educated patients as compared with low educated patients for all cancers combined: 49% versus 32% in male subjects (log rank: p<0.0001), 65% versus 49% in female subjects (p=0.0001). Compared with highly educated, low educated prostate cancer patients had an increased risk of death (HR 2.9 (95% CI 1.7 to 5.1), adjusted for age, stage and year). No or inconsistent associations between educational level and risk of death were seen in multivariable analyses for breast, colon and non-small cell lung cancer. Although survival in prostate cancer patients was affected by comorbidities (HR2_vs_0_comorbidities: 2.6 (1.5 to 4.4)), physical activity (HRno/little_vs__moderate_physical__activity: 2.0 (1.2 to 3.4)) and smoking (HRcurrent_vs_never_smokers: 2.6 (1.0-6.8)), these did not contribute to educat

Small but significant socioeconomic inequalities in axillary staging and treatment of breast cancer in the Netherlands

Background: The use of sentinel node biopsy (SNB), lymph node dissection, breast-conserving surgery, radiotherapy, chemotherapy and hormonal treatment for breast cancer was evaluated in relation to socioeconomic status (SES) in the Netherlands, where access to care was assumed to be equal. Methods: Female breast cancer patients diagnosed between 1994 and 2008 were selected from the nationwide population-based Netherlands Cancer Registry (N=176 505). Socioeconomic status was assessed based on income, employment and education at postal code level. Multivariable models included age, year of diagnosis and stage. Results: Sentinal node biopsy was less often applied in high-SES patients (multivariable analyses, ≤49 years: odds ratio (OR) 0.70 (95% CI: 0.56-0.89); 50-75 years: 0.85 (0.73-0.99)). Additionally, lymph node dissection was less common in low-SES patients aged ≥76 years (OR 1.34 (0.95-1.89)). Socioeconomic status-related differences in treatment were only significant in the age group 50-75 years. High-SES women with stage T1-2 were more likely to undergo breast-conserving surgery (radiotherapy) (OR 1.15 (1.09-1.22) and OR 1.16 (1.09-1.22), respectively). Chemotherapy use among node-positive patients was higher in the high-SES group, but was not significant in multivariable analysis. Hormonal therapy was not related to SES. Conclusion: Small but significant differences were observed in the use of SNB, lymph node dissection and breast-conserving surgery according to SES in Dutch breast cancer patients despite assumed equal access to health care

Habit formation of preventive behaviours during the COVID-19 pandemic: a longitudinal study of physical distancing and hand washing

Background: Since the outbreak of the COVID-19 pandemic, physical distancing and hand washing have been used as effective means to reduce virus transmission in the Netherlands. However, these measures pose a societal challenge as they require people to change their customary behaviours in various contexts. The science of habit formation is potentially useful for informing policy-making in public health, but the current literature largely overlooked the role of habit in predicting and explaining these preventive behaviours. Our research aimed to describe habit formation processes of physical distancing and hand washing and to estimate the influences of habit strength and intention on behavioural adherence. Methods: A longitudinal survey was conducted between July and November 2020 on a representative Dutch sample (n = 800). Respondents reported their intentions, habit strengths, and adherence regarding six context-specific preventive behaviours on a weekly basis. Temporal developments of the measured variables were visualized, quantified, and mapped onto five distinct phases of the pandemic. Regression models were used to test the effects of intention, habit strength, and their interaction on behavioural adherence. Results: Dutch respondents generally had strong intentions to adhere to all preventive measures and their adherence rates were between 70% and 90%. They also self-reported to experience their behaviours as more automatic over time, and this increasing trend in habit strength was more evident for physical-distancing than for hand washing behaviours. For all six behaviours, both intention and habit strength predicted subsequent adherence (all ps < 2e-16). In addition, the predictive power of intention decreased over time and was weaker for respondents with strong habits for physical distancing when visiting supermarkets (B = -0.63, p <.0001) and having guests at home (B = -0.54, p <.0001) in the later phases of the study, but not for hand washing. Conclusions: People’s adaptations to physical-distancing and hand washing measures involve both intentional and habitual processes. For public health management, our findings highlight the importance of using contextual cues to promote habit formation, especially for maintaining physical-distancing practices. For habit theories, our study provides a unique dataset that covers multiple health behaviours in a critical real-world setting

Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data

Background: Social distancing has been implemented by many countries to curb the COVID-19 pandemic. Understanding public support for this policy calls for effective and efficient methods of monitoring public opinion on social distancing. Twitter analysis has been suggested as a cheaper and faster-responding alternative to traditional survey methods. The current empirical evidence is mixed in terms of the correspondence between the two methods. Objective: We aim to compare the two methods in the context of monitoring the Dutch public's opinion on social distancing. For this comparison, we quantified the temporal and spatial variations in public opinion and their sensitivities to critical events using data from both Dutch Twitter users and respondents from a longitudinal survey. Methods: A longitudinal survey on a representative Dutch sample (n = 1,200) was conducted between July and November 2020 to measure opinions on social distancing weekly. From the same period, near 100,000 Dutch tweets were categorized as supporting or rejecting social distancing based on a model trained with annotated data. Average stances for the 12 Dutch provinces and over the 20 weeks were computed from the two data sources and were compared through visualizations and statistical analyses. Results: Both data sources suggested strong support for social distancing, but public opinion was much more varied among tweets than survey responses. Both data sources showed an increase in public support for social distancing over time, and a strong temporal correspondence between them was found for most of the provinces. In addition, the survey but not Twitter data revealed structured differences among the 12 provinces, while the two data sources did not correspond much spatially. Finally, stances estimated from tweets were more sensitive to critical events happened during the study period. Conclusions: Our findings indicate consistencies between Twitter data analysis and survey methods in describing the overall stance on social distancing and temporal trends. The lack of spatial correspondence may imply limitations in the data collections and calls for surveys with larger regional samples. For public health management, Twitter analysis can be used to complement survey methods, especially for capturing public's reactivities to critical events amid the current pandemic

Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data

BackgroundSocial distancing has been implemented by many countries to curb the COVID-19 pandemic. Understanding public support for this policy calls for effective and efficient methods of monitoring public opinion on social distancing. Twitter analysis has been suggested as a cheaper and faster-responding alternative to traditional survey methods. The current empirical evidence is mixed in terms of the correspondence between the two methods.ObjectiveWe aim to compare the two methods in the context of monitoring the Dutch public's opinion on social distancing. For this comparison, we quantified the temporal and spatial variations in public opinion and their sensitivities to critical events using data from both Dutch Twitter users and respondents from a longitudinal survey.MethodsA longitudinal survey on a representative Dutch sample (n = 1,200) was conducted between July and November 2020 to measure opinions on social distancing weekly. From the same period, near 100,000 Dutch tweets were categorized as supporting or rejecting social distancing based on a model trained with annotated data. Average stances for the 12 Dutch provinces and over the 20 weeks were computed from the two data sources and were compared through visualizations and statistical analyses.ResultsBoth data sources suggested strong support for social distancing, but public opinion was much more varied among tweets than survey responses. Both data sources showed an increase in public support for social distancing over time, and a strong temporal correspondence between them was found for most of the provinces. In addition, the survey but not Twitter data revealed structured differences among the 12 provinces, while the two data sources did not correspond much spatially. Finally, stances estimated from tweets were more sensitive to critical events happened during the study period.ConclusionsOur findings indicate consistencies between Twitter data analysis and survey methods in describing the overall stance on social distancing and temporal trends. The lack of spatial correspondence may imply limitations in the data collections and calls for surveys with larger regional samples. For public health management, Twitter analysis can be used to complement survey methods, especially for capturing public's reactivities to critical events amid the current pandemic

3-Deazaadenosine alleviates senescence to promote cellular fitness and cell therapy efficiency in mice

International audienc