Like many countries, the COVID-19 pandemic has forced Statistics Netherlands to make changes in its fieldwork strategy. Since mid-March 2020, there have been limited opportunities to conduct face-to-face interviews. Therefore, from September 2020, CAPI sampled people are offered the opportunity to respond by telephone. For this purpose, face-to-face interviewers are instructed to persuade the potential respondent at the doorway. When people refuse a face-to-face interview, interviewers ask for a telephone number and try to make an appointment to conduct the interview by telephone. The aim of our study was to investigate the effects of conducting the interview by telephone instead of face-to-face on important survey outcome variables. We were particularly interested in whether differences are due to selection effects or caused by mode-specific measurement errors. Because we did not have the time or capacity to set up a controlled experiment, we performed regression analyses to decompensate the differences between selection effects and mode-specific measurement errors. We used data of the Labour Force Survey (LFS) and the Housing Survey (WoON). Our analysis showed that there were differences in important target variables, for both LFS and WoON. These differences were, however, mainly caused by selection effects – which can be taken into account for during weighting – and were less likely to be caused by mode specific measurement errors. Although there are important limitations and caveats, these findings are supportive to further implement this field strategy.
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The pervasive phenomenon of adaptivity in face-to-face interaction isdescribed inconsistently, using numerous concepts (e.g. alignment/attunement/complementarity/imitation/reciprocity/scaffolding/synchrony), impeding the streamlining of adaptivity research. Weexplored 33 adaptivity concepts and various adaptivity theories fromdifferentfields. We developed a theory-based conceptual frameworkconsisting of two key dimensions.Relatednessrefers to how people’sactions should relate to each other to be considered adaptive and isdescribed in terms of sameness (e.g. both friendly), oppositeness (e.g.dominant/submissive), or specified attentiveness (dissimilar acts).Responsivityrefers to the timing of people’s actions (sequential/simultaneous). The framework helps to understand what key elementsadaptivity consists of. The framework can help transcending theconcept and discipline level and examining and synthesizing research pertaining to adaptivity with similar dimensional characteristics.
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The problem of single-use personal protective equipment (PPE) made from non-renewable resources polluting the environment encouraged the creation of a circular face mask. The main factors that influence the design of a face mask that protects the user from COVID-19 were investigated. According to the findings, these are filtration, fit performance, and comfortability. Therefore, the two following goals were set for this project, to design a face mask (1) produced in the Netherlands using 50% local circular materials and 50% recyclable materials and (2) that perfectly fits men's and women’s faces
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This paper introduces the Analysis Framework of Face Interaction (AFFI) which is developed based on a new face dimension termed Face Confirmation − Face Confrontation at two levels: Individual level within the group and Collective level between groups. This proposed framework of face analysis reveals a dearth of research on face confrontation as essential communication strategies. It also points out how the mainstream research on facework has been limited on the collective level of analysis. The authors argue that using AFFI will help researchers reduce cultural over-generalisation; enable them to involve more specific cultural, contextual and situational characteristics of each face case to analyse face negotiation from a more holistic perspective.
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BACKGROUND: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. OBJECTIVE: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. METHODS: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. RESULTS: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R2=0.049; face-to-face R2=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R2=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R2=0.164). CONCLUSIONS: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research. TRIAL REGISTRATION: Netherlands Trial Register NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113.
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Een webapplicatie om opvattingen over excellentie inzichtelijk te maken.
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Background: Blended face-to-face and web-based treatment is a promising mode to deliver smoking cessation treatment. In an outpatient clinic in a Dutch Hospital effectiveness of a blended treatment (BSCT) was compared to usual face-to-face treatment (F2F). The results from 6 months post-treatment follow-up are presented here.Methods: In this open-label two-arm non-inferiority RCT patients (N=344) of a Dutch outpatient smoking cessation clinic were assigned either to the blended smoking cessation treatment (BSCT, N=167) or a face-to-face treatment with identical ingredients and duration (F2F, N=177). CO-validated point prevalence abstinence at 6 months follow-up, taken shortly after end of treatment was analyzed. Intention-to-treat analyses were performed, retaining missing participants as continuing smokers. Non-inferiority was assessed based on a one-sided margin of five percentage points difference between arms. Additionally, a Bayes Factor was estimated (with a BF>3 supporting non-inferiority, and a <.3 rejecting non-inferiority).Method: At 6 months follow up, 23 BSCT participants (13.8%) and 31 F2F participants (17.5%) were abstinent, with a difference of 3.7% (95%CI: 11.4;-4.0) in favor of F2F. Furthermore, a BF=1.28 was found.Discussion: Based on observed biochemically validated abstinence rates, this RCT suggests that delivering outpatient smoking cessation treatment in a blended mode yields comparable quit rates as full face-to-face treatment mode. However, non-inferiority could not be supported conclusively. Ignoring patient preferences for either of the delivery modes may explain these inconclusive findings.
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This presentation explores how AI face anonymization impacts empathy and source credibility in documentaries, balancing privacy protection with audience engagement.
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Background:Tobacco consumption is a leading cause of death and disease, killing >8 million people each year. Smoking cessation significantly reduces the risk of developing smoking-related diseases. Although combined treatment for addiction is promising, evidence of its effectiveness is still emerging. Currently, there is no published research comparing the effectiveness of blended smoking cessation treatments (BSCTs) with face-to-face (F2F) treatments, where web-based components replace 50% of the F2F components in blended treatment.Objective:The primary objective of this 2-arm noninferiority randomized controlled trial was to determine whether a BSCT is noninferior to an F2F treatment with identical ingredients in achieving abstinence rates.Methods:This study included 344 individuals who smoke (at least 1 cigarette per day) attending an outpatient smoking cessation clinic in the Netherlands. The participants received either a blended 50% F2F and 50% web-based BSCT or only F2F treatment with similar content and intensity. The primary outcome measure was cotinine-validated abstinence rates from all smoking products at 3 and 15 months after treatment initiation. Additional measures included carbon monoxide–validated point prevalence abstinence; self-reported point prevalence abstinence; and self-reported continuous abstinence rates at 3, 6, 9, and 15 months after treatment initiation.Results:None of the 13 outcomes showed statistically confirmed noninferiority of the BSCT, whereas 4 outcomes showed significantly (P<.001) inferior abstinence rates of the BSCT: cotinine-validated point prevalence abstinence rate at 3 months (difference 12.7, 95% CI 6.2-19.4), self-reported point prevalence abstinence rate at 6 months (difference 19.3, 95% CI 11.5-27.0) and at 15 months (difference 11.7, 95% CI 5.8-17.9), and self-reported continuous abstinence rate at 6 months (difference 13.8, 95% CI 6.8-20.8). The remaining 9 outcomes, including the cotinine-validated point prevalence abstinence rate at 15 months, were inconclusive.Conclusions:In this high-intensity outpatient smoking cessation trial, the blended mode was predominantly less effective than the traditional F2F mode. The results contradict the widely assumed potential benefits of blended treatment and suggest that further research is needed to identify the critical factors in the design of blended interventions.Trial Registration:Netherlands Trial Register 27150; https://onderzoekmetmensen.nl/nl/trial/27150
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