Hein de Vries

Prof. Hein de Vries

Maastricht University, Maastricht, Limburg, The Netherlands
orcid

Research Focus & Metrics

Academic Career Length

31Years (1996-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
23 March 2017 in BMC Public Health
Verified
Journal Article
Open access
PDF file
KCKei Long Cheung
Kei Long Cheung
Peter ten KloosterPeter ten Klooster
Peter ten Klooster
CSCees Smit
Cees Smit
HVHein de Vries
Hein de Vries
MPMarcel E. Pieterse
Marcel E. Pieterse
In public health monitoring of young people it is critical to understand the effects of selective non-response, in particular when a controversial topic is involved like substance abuse or sexual behaviour. Research that is dependent upon voluntary subject participation is particularly vulnerable to sampling bias. As respondents whose participation is hardest to elicit on a voluntary basis are also more likely to report risk behaviour, this potentially leads to underestimation of risk factor prevalence. Inviting adolescents to participate in a home-sent postal survey is a typical voluntary recruitment strategy with high non-response, as opposed to mandatory participation during school time. This study examines the extent to which prevalence estimates of adolescent health-related characteristics are biased due to different sampling methods, and whether this also biases within-subject analyses. Cross-sectional datasets collected in 2011 in Twente and IJsselland, two similar and adjacent regions in the Netherlands, were used. In total, 9360 youngsters in a mandatory sample (Twente) and 1952 youngsters in a voluntary sample (IJsselland) participated in the study. To test whether the samples differed on health-related variables, we conducted both univariate and multivariable logistic regression analyses controlling for any demographic difference between the samples. Additional multivariable logistic regressions were conducted to examine moderating effects of sampling method on associations between health-related variables. As expected, females, older individuals, as well as individuals with higher education levels, were over-represented in the voluntary sample, compared to the mandatory sample. Respondents in the voluntary sample tended to smoke less, consume less alcohol (ever, lifetime, and past four weeks), have better mental health, have better subjective health status, have more positive school experiences and have less sexual intercourse than respondents in the mandatory sample. No moderating effects were found for sampling method on associations between variables. This is one of first studies to provide strong evidence that voluntary recruitment may lead to a strong non-response bias in health-related prevalence estimates in adolescents, as compared to mandatory recruitment. The resulting underestimation in prevalence of health behaviours and well-being measures appeared large, up to a four-fold lower proportion for self-reported alcohol consumption. Correlations between variables, though, appeared to be insensitive to sampling bias.

9 March 2017 in Psychology and Behavioral Science International Journal
Verified
Journal Article
Open access
HVHein de Vries
Hein de Vries

7 February 2021 in Behaviour & Information Technology
Verified
Journal Article
Open access
JMJoão Mariano
João Mariano
SMSibila Marques
Sibila Marques
MRMiguel R. Ramos
Miguel R. Ramos
FGFilomena Gerardo
Filomena Gerardo
CCCátia Lage da Cunha
Cátia Lage da Cunha
HVHein de Vries
Hein de Vries
Older adults are often stereotyped as having less technological ability than younger age groups. As a result, older individuals may avoid using technology due to stereotype threat, the fear of confirming negative stereotypes about their social group. The present research examined the role of stereotype threat within the Technology Acceptance Model (TAM). Across two studies, experiencing stereotype threat in the technological domain was indirectly associated with lower levels of technology use among older adults. This was found for subjective (Study 1) and objective measures (Study 2) of use behaviour, and for technology use in general (Study 1) and computer use in particular (Study 2). In line with the predictions of the Technology Acceptance Model, this relationship was mediated by anxiety, perceived ease of use, perceived usefulness, and behavioural intention. Specifically, stereotype threat was negatively associated with perceived ease of use (Studies 1 and 2) and anxiety mediated this relationship (Study 2). These findings suggest that older adults underuse technology due to the threat of confirming ageist stereotypes targeting their age group. Stereotype threat may thus be an important barrier to technology acceptance and usage in late adulthood.

KRKim Romijnders
Kim Romijnders
LOLiesbeth van Osch
Liesbeth van Osch
HVHein de Vries
Hein de Vries
RTReinskje Talhout
Reinskje Talhout
This paper aims to provide an in-depth understanding of the attractiveness of e-cigarettes for several different groups. For this purpose, perceptions of and reasons for e-cigarette use were systematically reviewed as reported by e-cigarette users, cigarette smokers, dual users, and non-users, among both adults and youth. MEDLINE® and Scopus were used to search for relevant articles, and references of included studies were also investigated. Two reviewers screened all titles and abstracts independently, blinded to authors and journal titles (Cohen’s Kappa = 0.83), resulting in 72 eligible articles. Risk perceptions, perceived benefits, and reasons for e-cigarette use were categorized in themes and sub-themes. Risk perceptions included harmfulness in general, and specific health risks. Perceived benefits included improved taste and smell, and safety for bystanders. Reasons for use included (health) benefits, curiosity, smoking cessation, and friends using e-cigarettes. The findings highlight that there is a variety of perceptions and reasons mentioned by adult and youth e-cigarette users, cigarette smokers, dual users, and non-users. As such, this overview provides valuable information for scientists, public health professionals, behavior change experts, and regulators to improve future research, risk communication, and possibilities to effectively regulate e-cigarettes.

18 May 2012 in BMC Public Health
Verified
Journal Article
Open access
PDF file
Gera NagelhoutGera Nagelhout
Gera Nagelhout
DBDianne de Korte-De Boer
Dianne de Korte-De Boer
AKAnton Kunst
Anton Kunst
RMRegina M van der Meer
Regina M van der Meer
HVHein de Vries
Hein de Vries
MWMarc C Willemsen
Marc C Willemsen
Widening of socioeconomic status (SES) inequalities in smoking prevalence has occurred in several Western countries from the mid 1970’s onwards. However, little is known about a widening of SES inequalities in smoking consumption, initiation and cessation.

30 October 2018 in International Journal of Behavioral Nutrition and Physical Activity
Verified
Journal Article
Open access
PDF file
RGRianne Golsteijn
Rianne Golsteijn
CBCatherine Bolman
Catherine Bolman
EVEsmee Volders
Esmee Volders
DPDenise Peels
Denise Peels
HVHein de Vries
Hein de Vries
Lilian LechnerLilian Lechner
Lilian Lechner
Physical activity (PA) is beneficial in improving negative physical and psychological effects of cancer and cancer treatment, but adherence to PA guidelines is low. Computer-tailored PA interventions can reach large populations with little resources. They match with patients’ preference for home-based, unsupervised PA programs and are thus promising for the growing population of cancer survivors. The current study assessed the efficacy of a computer-tailored PA intervention in (four subgroups of) prostate and colorectal cancer survivors. Prostate and colorectal cancer patients and survivors were randomized to the OncoActive intervention group (N = 249), or a usual-care waiting-list control group (N = 229). OncoActive participants received a pedometer and computer-tailored PA advice, both Web-based via an interactive website and with printed materials. Minutes moderate-to-vigorous PA (MVPA) and days ≥30 min PA were assessed with an accelerometer (ActiGraph) at baseline and 6 months. Further, questionnaires were used to assess self-reported PA, fatigue, distress, and quality of life at baseline, 3 and 6 months. Differences between both groups were assessed using linear regression analyses (complete cases and intention-to-treat). In addition, efficacy in relation to age, gender, education, type of cancer, and time since treatment was examined. Three months after baseline OncoActive participants significantly increased their self-reported PA (PA days: d = 0.46; MVPA: d = 0.23). Physical functioning (d = 0.23) and fatigue (d = − 0.21) also improved significantly after three months. Six months after baseline, self-reported PA (PA days: d = 0.51; MVPA: d = 0.37) and ActiGraph MVPA (d = 0.27) increased significantly, and ActiGraph days (d = 0.16) increased borderline significantly (p = .05; d = 0.16). Furthermore, OncoActive participants reported significantly improvements in physical functioning (d = 0.14), fatigue (d = − 0.23) and depression (d = − 0.32). Similar results were found for intention-to-treat analyses. Higher increases in PA were found for colorectal cancer participants at 3 months, and for medium and highly educated participants’ PA at 6 months. Health outcomes at 6 months were more prominent in colorectal cancer participants and in women. The OncoActive intervention was effective at increasing PA in prostate and colorectal cancer patients and survivors. Health-related effects were especially apparent in colorectal cancer participants. The intervention provides opportunities to accelerate cancer recovery. Long-term follow-up should examine further sustainability of these effects. The study was registered in the Dutch Trial Register ( NTR4296 ) on October 17 2018.