Sharing Data Collected with Smartphone Sensors: Willingness, Participation, and Nonparticipation Bias.

Smartphone sensors allow measurement of phenomena that are difficult or impossible to capture via self-report (e.g., geographical movement, physical activity). Sensors can reduce respondent burden by eliminating survey questions and improve measurement accuracy by replacing/augmenting self-reports. However, if respondents who are not willing to collect sensor data differ on critical attributes from those who are, the results can be biased. Research on the mechanisms of willingness to collect sensor data mostly comes from (nonprobability) online panels and is hypothetical (i.e., asks participants about the likelihood of participation in a sensor-based study). In a cross-sectional general population randomized experiment, we investigate how features of the request and respondent characteristics influence willingness to share (WTS) and actually sharing smartphone-sensor data. We manipulate the request to either mention or not mention (1) how participation will benefit the participant, (2) participants' autonomy over data collection, and (3) that data will be kept confidential. We assess nonparticipation bias using the administrative records. WTS and actually sharing varies by sensor task, participants' autonomy over data sharing, their smartphone skills, level of privacy concerns, and attitudes toward surveys. Fewer people agree to share photos and a video than geolocation, but all who agreed to share photos or a video actually did. Some nonresponse and nonparticipation biases are substantial and make each other worse, but others jointly reduce the overall bias. Our findings suggest that sensor-data-sharing decisions depend on sample members' situation when asked to share and the nature of the sensor task rather than the sensor type.

Understanding Willingness to Share Smartphone-Sensor Data.

The growing smartphone penetration and the integration of smartphones into people's everyday practices offer researchers opportunities to augment survey measurement with smartphone-sensor measurement or to replace self-reports. Potential benefits include lower measurement error, a widening of research questions, collection of in situ data, and a lowered respondent burden. However, privacy considerations and other concerns may lead to nonparticipation. To date, little is known about the mechanisms of willingness to share sensor data by the general population, and no evidence is available concerning the stability of willingness. The present study focuses on survey respondents' willingness to share data collected using smartphone sensors (GPS, camera, and wearables) in a probability-based online panel of the general population of the Netherlands. A randomized experiment varied study sponsor, framing of the request, the emphasis on control over the data collection process, and assurance of privacy and confidentiality. Respondents were asked repeatedly about their willingness to share the data collected using smartphone sensors, with varying periods before the second request. Willingness to participate in sensor-based data collection varied by the type of sensor, study sponsor, order of the request, respondent's familiarity with the device, previous experience with participating in research involving smartphone sensors, and privacy concerns. Willingness increased when respondents were asked repeatedly and varied by sensor and task. The timing of the repeated request, one month or six months after the initial request, did not have a significant effect on willingness.

Barriers to ideal palliative care in multiple care settings: the nurses' point of view.

BACKGROUND: Nurses and certified nursing assistants (CNA) have a crucial role in 24/7 continuity of palliative care for many vulnerable patients and families, however, their perspective has been largely omitted in reported barriers to palliative care. AIM: To describe barriers to ideal palliative care that are specific to nurses and CNAs working in all care settings. METHODS: A cross-sectional, online survey was distributed to members of the Dutch Nurses' Association. FINDINGS: Almost 50% of the participating 2377 nurses and CNAs experienced more than five barriers to ideal palliative care in their work situation; nurses and CNAs employed in regional hospitals, mental healthcare and nursing home settings encountered more barriers than those working in other settings. CONCLUSION: The three most common barriers were: lack of proactive care planning, lack of internal consultation possibilities and lack of assessment of care recipients' preferences and needs for a seamless transition to another setting.

Incidence and recurrence of common mental disorders after abortion: Results from a prospective cohort study.

Research in the field of mental health consequences of abortion is characterized by methodological limitations. We used exact matching on carefully selected confounders in a prospective cohort study of 325 women who had an abortion of an unwanted pregnancy and compared them 1-to-1 to controls who did not have this experience. Outcome measures were incidence and recurrence of common DSM-IV mental disorders (mood, anxiety, substance use disorders, and the aggregate measure 'any mental disorder') as measured with the Composite International Diagnostic Interview (CIDI) version 3.0, in the 2.5-3 years after the abortion. Although non-matched data suggested otherwise, women in the abortion group did not show significantly higher odds for incidence of 'any mental disorder', or mood, anxiety and substance use disorders, compared to matched controls who were similar in background variables but did not have an this experience. Having an abortion did not increase the odds for recurrence of the three disorder categories, but for any mental disorder the higher odds in the abortion group remained significant after matching. It is unlikely that termination of an unwanted pregnancy increases the risk on incidence of common mental disorders in women without a psychiatric history. However, it might increase the risk of recurrence among women with a history of mental disorders.

The unique roles of intrapersonal and social factors in adolescent smoking development.

Adolescence is a vulnerable period for the initiation and peak of many harmful risk-taking behaviors such as smoking, which is among the most addictive and deadliest behaviors. Generic metatheories like the theory of triadic influence (TTI) suggest that interrelated risk factors across multiple domains (i.e., intrapersonal and social/environmental) jointly contribute to adolescent smoking behavior. Yet, studies are lacking that investigate risk factors across different domains in the same study, which obscures whether each makes a unique contribution to the increase in smoking throughout adolescence or whether there is overlap across the domains. Hence, to fill this gap using a latent growth approach, the current accelerated longitudinal study investigated the collective contribution of multiple intrapersonal and social risk factors in the development of smoking behavior from ages 12 to 17 in 574 ethnically diverse Dutch adolescents. Results from the latent growth model showed that whereas the contribution of motivational-intrapersonal factors like sensation-seeking was no longer significant in the stringent multivariate model, higher levels of impulsivity (cognitive-intrapersonal) and overt peer pressure (social) at age 12 proved to be robust and unique predictors of linear increases in adolescent smoking up until age 17. Consistent with the TTI, adolescent smoking progression does not occur in isolation and the determinants are wide-ranging as they stem from both intrapersonal and social domains. Thus focusing on such confluence of intrapersonal and social risk factors via prevention programs from as young as age 12 might halt the deadly increase in smoking behavior throughout adolescence. (PsycINFO Database Record

Explaining end-users' intentions to use innovative medical and food biotechnology products.

Low public acceptance hinders the successful introduction of biotechnological innovations, such as genetically modified foods or vaccinations against infectious diseases. Earlier studies indicated that a lack of knowledge is not a key barrier to acceptance. This was confirmed in the current study, which examined an integrated theoretical model tested among 579 participants from the Dutch public. The results suggest that communication strategies should instead target attitudes, social norms, and risk perceptions, and appeal to people's tendency (or lack thereof) to be innovative.

Differential effects of baseline drinking status: effects of an alcohol prevention program targeting students and/or parents (PAS) among weekly drinking students.

The effects of an intervention designed to prevent onset of weekly drinking in non drinking students (PAS) were investigated in the group of students that was already drinking at baseline. A cluster randomized trial was used including 3,490 Dutch early adolescents (M age = 12.66, SD = 0.49) randomized over four conditions; 1) parent intervention, 2) student intervention, 3) combined intervention and 4) control group. Outcome measures were amount and growth of weekly alcohol drinking measured 10, 22 and 34 months after baseline. The combined intervention significantly curbed the growth of drinking among both non-drinkers (the target group of the intervention) and drinkers at baseline. Overall, less strong increases of drinking over time are found among non-drinkers compared to drinkers at baseline. Thus, the combined PAS intervention is also effective in curbing adolescents' drinking behaviour in those who already were drinking at baseline. Broad implementation of the combined parent-student intervention is recommended.

Adolescents' use of nicotine replacement therapy for smoking cessation: predictors of compliance trajectories.

RATIONALE: Previous research has shown limited efficacy of nicotine replacement therapy (NRT) among adolescents and generally low compliance rates. As higher compliance rates are associated with improved abstinence rates, the present study examined predictors of NRT compliance. OBJECTIVES: This study aims to test whether different NRT compliance trajectories can be distinguished among adolescents, to test whether these trajectories can be predicted by demographic, smoking-related, and personality factors, and to examine abstinence rates for each trajectory. METHODS: Data were used from a randomized controlled trial that tested the efficacy of nicotine patches versus placebo patches among 265 Dutch adolescents. During NRT treatment, adolescents filled out six online questionnaires in which they reported on the number of days they used the patches. Predictors (i.e., demographic and smoking-related factors and personality characteristics) and end-of-treatment abstinence were also administered through these self-reports. Latent class growth analysis (LCGA) was used to analyze compliance data by classifying individuals into similar growth trajectories. RESULTS: Three compliance trajectories were found (i.e., "compliers" (n = 89), "moderate decreasers" (n = 41), and "strong decreasers" (n = 127)). The compliers can be characterized by higher levels of conscientiousness and agreeableness and lower levels of extraversion compared with the strong decreasers, and by higher levels of conscientiousness and education compared with the moderate decreasers. Among the compliers, a substantially higher percentage of adolescents achieved abstinence at end-of-treatment (10 %) compared with the moderate decreasers (3 %) and the strong decreasers (6 %). CONCLUSIONS: These findings could be the starting point for person-tailored interventions that aim to enhance NRT compliance rates among adolescents.

Facing off with Scylla and Charybdis: a comparison of scalar, partial, and the novel possibility of approximate measurement invariance.

Measurement invariance (MI) is a pre-requisite for comparing latent variable scores across groups. The current paper introduces the concept of approximate MI building on the work of Muthén and Asparouhov and their application of Bayesian Structural Equation Modeling (BSEM) in the software Mplus. They showed that with BSEM exact zeros constraints can be replaced with approximate zeros to allow for minimal steps away from strict MI, still yielding a well-fitting model. This new opportunity enables researchers to make explicit trade-offs between the degree of MI on the one hand, and the degree of model fit on the other. Throughout the paper we discuss the topic of approximate MI, followed by an empirical illustration where the test for MI fails, but where allowing for approximate MI results in a well-fitting model. Using simulated data, we investigate in which situations approximate MI can be applied and when it leads to unbiased results. Both our empirical illustration and the simulation study show approximate MI outperforms full or partial MI In detecting/recovering the true latent mean difference when there are (many) small differences in the intercepts and factor loadings across groups. In the discussion we provide a step-by-step guide in which situation what type of MI is preferred. Our paper provides a first step in the new research area of (partial) approximate MI and shows that it can be a good alternative when strict MI leads to a badly fitting model and when partial MI cannot be applied.