Validation of a Seven-Factor Structure for the Motives for Playing Drinking Games Measure

Playing drinking games can be characterized as a high-risk drinking activity because games are typically designed to promote heavy alcohol consumption. While research suggests that young adults are motivated to play drinking games for a variety of reasons (e.g., for thrills/fun, for the competition), the Motives for Playing Drinking Games measure has received limited empirical attention. We examined the psychometric properties of this measure with a confirmation sample of young adults recruited from Amazon's MTurk ( N = 1,809, ages 18-25 years, 47% men; 41% not currently enrolled in college) and a validation sample of college students ( N = 671; ages 18-23 years; 26% men). Contrary to the 8-factor model obtained by Johnson and Sheets in a study published in 2004, examination of the factor structure with our confirmation sample yielded a revised 7-factor model that was invariant across race/ethnicity and college student status. This model was also validated with the college student sample. In the confirmation sample, enhancement/thrills and sexual pursuit motives for playing drinking games were positively associated with gaming frequency/consumption and negative gaming consequences. Furthermore, conformity motives for playing drinking games were positively associated with negative gaming consequences, while competition motives were positively associated with gaming frequency. These findings have significant implications for research and prevention/intervention efforts.

Latent-level relations between DSM-5 PTSD symptom clusters and problematic smartphone use

Common mental health consequences following the experience of potentially traumatic events include Posttraumatic Stress Disorder (PTSD) and addictive behaviors. Problematic smartphone use is a newer manifestation of addictive behaviors. People with anxiety severity (such as PTSD) may be at risk for problematic smartphone use as a means of coping with their symptoms. Unique to our knowledge, we assessed relations between PTSD symptom clusters and problematic smartphone use. Participants (N = 347), recruited through Amazon's Mechanical Turk (MTurk), completed measures of PTSD and smartphone addiction. Results of the Wald tests of parameter constraints indicated that problematic smartphone use was more related to PTSD's negative alterations in cognitions and mood (NACM) than to PTSD's avoidance factor, Wald χ²(1, N = 347) = 12.51, p = 0.0004; and more to PTSD's arousal compared to PTSD's avoidance factor, Wald χ²(1, N = 347) = 14.89, p = 0.0001. Results indicate that problematic smartphone use is most associated with negative affect and arousal among trauma-exposed individuals. Implications include the need to clinically assess problematic smartphone use among trauma-exposed individuals presenting with higher NACM and arousal severity; and targeting NACM and arousal symptoms to mitigate the effects of problematic smartphone use.

Survey Satisficing Inflates Reliability and Validity Measures: An Experimental Comparison of College and Amazon Mechanical Turk Samples

This study examined the predictors and psychometric outcomes of survey satisficing, wherein respondents provide quick, "good enough" answers (satisficing) rather than carefully considered answers (optimizing). We administered surveys to university students and respondents-half of whom held college degrees-from a for-pay survey website, and we used an experimental method to randomly assign the participants to survey formats, which presumably differed in task difficulty. Based on satisficing theory, we predicted that ability, motivation, and task difficulty would predict satisficing behavior and that satisficing would artificially inflate internal consistency reliability and both convergent and discriminant validity correlations. Indeed, results indicated effects for task difficulty and motivation in predicting survey satisficing, and satisficing in the first part of the study was associated with improved internal consistency reliability and convergent validity but also worse discriminant validity in the second part of the study. Implications for research designs and improvements are discussed.

A Comparison of Three Online Recruitment Strategies for Engaging Parents

Family scientists can face the challenge of effectively and efficiently recruiting normative samples of parents and families. Utilizing the Internet to recruit parents is a strategic way to find participants where they already are, enabling researchers to overcome many of the barriers to in-person recruitment. The present study was designed to compare three online recruitment strategies for recruiting parents: e-mail Listservs, Facebook, and Amazon Mechanical Turk (MTurk). Analyses revealed differences in the effectiveness and efficiency of data collection. In particular, MTurk resulted in the most demographically diverse sample, in a short period of time, with little cost. Listservs reached a large number of participants and resulted in a comparatively homogeneous sample. Facebook was not successful in recruiting a general sample of parents. Findings provide information that can help family researchers and practitioners be intentional about recruitment strategies and study design.

Cloud Based Surveys to Assess Patient Perceptions of Health Care: 1000 Respondents in 3 days for US $300

BACKGROUND

There are many challenges in conducting surveys of study participants, including cost, time, and ability to obtain quality and reproducible work. Cloudsourcing (an arrangement where a cloud provider is paid to carry out services that could be provided in-house) has the potential to provide vastly larger, less expensive, and more generalizable survey pools.

OBJECTIVE

The objective of this study is to evaluate, using Amazon's Mechanical Turk (MTurk), a cloud-based workforce to assess patients' perspectives of health care.

METHODS

A national online survey posted to Amazon's MTurk consisted of 33 multiple choice and open-ended questions. Continuous attributes were compared using t tests.

RESULTS

We obtained 1084 responses for a total cost of US $298.10 in less than 3 days with 300 responses in under 6 hours. Of those, 44.74% (485/1084) were male and 54.80% (594/1084) female, representing 49 out of 50 states and aged 18 to 69 years.

CONCLUSIONS

Amazon's MTurk is a potentially useful survey method for attaining information regarding public opinions and/or knowledge with the distinct advantage of cost, speed, and a wide and relatively good representation of the general population, in a confidential setting for respondents.

When Lying Feels the Right Thing to Do

Fraud is a pervasive and challenging problem that costs society large amounts of money. By no means all fraud is committed by 'professional criminals': much is done by ordinary people who indulge in small-scale opportunistic deception. In this paper, we set out to investigate when people behave dishonestly, for example by committing fraud, in an online context. We conducted three studies to investigate how the rejection of one's efforts, operationalized in different ways, affected the amount of cheating and information falsification. Study 1 demonstrated that people behave more dishonestly when rejected. Studies 2 and 3 were conducted in order to disentangle the confounding factors of the nature of the rejection and the financial rewards that are usually associated with dishonest behavior. It was demonstrated that rejection in general, rather than the nature of a rejection, caused people to behave more dishonestly. When a rejection was based on subjective grounds, dishonest behavior increased with approximately 10%, but this difference was not statistically significant. We subsequently measured whether dishonesty was driven by the financial loss associated with rejection, or emotional factors such as a desire for revenge. We found that rejected participants were just as dishonest when their cheating did not led to financial gain. However, they felt stronger emotions when there was no money involved. This seems to suggest that upon rejection, emotional involvement, especially a reduction in happiness, drives dishonest behavior more strongly than a rational cost-benefit analysis. These results indicate that rejection causes people to behave more dishonestly, specifically in online settings. Firms wishing to deter customers and employees from committing fraud may therefore benefit from transparency and clear policy guidelines, discouraging people to submit claims that are likely to be rejected.

Anchoring in Destination-Therapy Left Ventricular Assist Device Decision Making: A Mechanical Turk Survey

BACKGROUND

People with end-stage heart failure may have to decide about destination-therapy left ventricular assist device (DT-LVAD). Individuals facing difficult decisions often rely on heuristics, such as anchoring, which predictably bias decision outcomes. We aimed to investigate whether showing a larger historical Heartmate XVE creates an anchoring effect, making the smaller Heartmate II (HMII) appear more favorable.

METHODS

With the use of Amazon Mechanical Turk, participants watched videos asking them to imagine themselves dying of end-stage heart failure, then were presented the option of LVAD as potentially life-prolonging therapy. Participants were randomized to a control group who were only shown the HMII device, and the intervention group who saw the XVE device before the HMII. Participants then completed surveys.

RESULTS

A total of 487 participants completed the survey (control = 252; intervention = 235); 79% were <40 years of age, 84% were white, and 55% were male. The intervention group was not more likely to accept the LVAD therapy (68% vs 61%; P = .37). However, participants in the intervention group were more likely (51% vs 17%; P < .01) to agree or strongly agree with the statement that the HMII was "smaller than expected." Participants in the intervention group were also more likely to rate the size of the device as "important" or "very important" in their decision (61% vs 46%; P < .01).

CONCLUSIONS

Although the XVE anchor did not affect likelihood of accepting the LVAD, it did affect device perception. This article highlights an important point with clinical implications: factors such as anchoring have the potential to inappropriately influence perceptions and decisions and should be carefully considered in research and practice.

Crowdsourcing for quantifying transcripts: An exploratory study

This exploratory study attempts to demonstrate the potential utility of crowdsourcing as a supplemental technique for quantifying transcribed interviews. Crowdsourcing is the harnessing of the abilities of many people to complete a specific task or a set of tasks. In this study multiple samples of crowdsourced individuals were asked to rate and select supporting quotes from two different transcripts. The findings indicate that the different crowdsourced samples produced nearly identical ratings of the transcripts, and were able to consistently select the same supporting text from the transcripts. These findings suggest that crowdsourcing, with further development, can potentially be used as a mixed method tool to offer a supplemental perspective on transcribed interviews.

The impact of overtly listing eligibility requirements on MTurk: An investigation involving organ donation, recruitment scripts, and feelings of elevation

RATIONALE

Investigations conducted through Amazon's Mechanical Turk (MTurk) sometimes explicitly note eligibility requirements when recruiting participants; however, the impact of this practice on data integrity is relatively unexplored within the MTurk context.

OBJECTIVE

Contextualized in the organ donor registration domain, the current study assessed whether overtly listing eligibility requirements impairs the accuracy of data collected on MTurk.

METHODS

On day 1, the first and third round of data collection did not list eligibility requirements; the second and fourth round overtly listed a qualification requirement: status as a non-registered organ donor. On day 2, the approach was identical, except the order was reversed-the first and third round overtly listed the study qualifications, while the second and fourth did not. These procedures provided eight different waves of data. In addition, all participants were randomly assigned to read an elevating (i.e., morally inspiring) story or a story not intended to elicit any emotion. Regardless of recruitment approach, only participants who were not registered as donors were included in the analysis.

RESULTS

Results indicated that the recruitment script that explicitly requested non-registered donors resulted in the collection of participants with higher mean intentions scores than the script that did not overtly list the eligibility requirements. Further, even though the elevation induction increased intentions to register as a donor, there was not a significant interaction between recruitment approach and the influence of the elevation manipulation on registration intentions.

CONCLUSION

Explicitly listing eligibility requirements can influence the accuracy of estimates derived from data collected through MTurk.

Stated and revealed inequality aversion in three subject pools

This paper reports data from three subject pools (n=717 subjects) using techniques based on those of Loewenstein, et al. (1989) and Blanco, et al. (2011) to obtain parameters, respectively, of stated and revealed inequality aversion. We provide a replication opportunity for those papers, with two innovations: (i) a design which allows stated and revealed preferences to be compared at the individual level; (ii) assessment of robustness of findings across subjects from a UK university, a Turkish university and Amazon Mechanical Turk. Our findings on stated aversion to inequality are qualitatively similar to those of Loewenstein, et al. in each of our subject pools, whereas there are notable differences between some of our findings on revealed preference and those of Blanco, et al. We find that revealed advantageous inequality aversion is often stronger than revealed dis-advantageous inequality aversion. In most subject pools, we find some (weak) correlation between corresponding parameters of stated and revealed inequality aversion.

What is the link between synaesthesia and sound symbolism?

Sound symbolism is a property of certain words which have a direct link between their phonological form and their semantic meaning. In certain instances, sound symbolism can allow non-native speakers to understand the meanings of etymologically unfamiliar foreign words, although the mechanisms driving this are not well understood. We examined whether sound symbolism might be mediated by the same types of cross-modal processes that typify synaesthetic experiences. Synaesthesia is an inherited condition in which sensory or cognitive stimuli (e.g., sounds, words) cause additional, unusual cross-modal percepts (e.g., sounds trigger colours, words trigger tastes). Synaesthesia may be an exaggeration of normal cross-modal processing, and if so, there may be a link between synaesthesia and the type of cross-modality inherent in sound symbolism. To test this we predicted that synaesthetes would have superior understanding of unfamiliar (sound symbolic) foreign words. In our study, 19 grapheme-colour synaesthetes and 57 non-synaesthete controls were presented with 400 adjectives from 10 unfamiliar languages and were asked to guess the meaning of each word in a two-alternative forced-choice task. Both groups showed superior understanding compared to chance levels, but synaesthetes significantly outperformed controls. This heightened ability suggests that sound symbolism may rely on the types of cross-modal integration that drive synaesthetes' unusual experiences. It also suggests that synaesthesia endows or co-occurs with heightened multi-modal skills, and that this can arise in domains unrelated to the specific form of synaesthesia.

Bedtime procrastination: introducing a new area of procrastination

Background: Procrastination is a prevalent and problematic phenomenon that has mostly been studied in the domain of academic behavior. The current study shows that procrastination may also lead to harmful outcomes in the area of health behavior, introducing bedtime procrastination as an important factor related to getting insufficient sleep and consequently affecting individual well-being. Bedtime procrastination is defined as failing to go to bed at the intended time, while no external circumstances prevent a person from doing so.

Methods: To empirically support the conceptual introduction of bedtime procrastination, an online survey study was conducted among a community sample (N = 177). The relationship between bedtime procrastination and individual difference variables related to self-regulation and general procrastination was assessed. Moreover, it was investigated whether bedtime procrastination was a predictor of self-reported sleep outcomes (experienced insufficient sleep, hours of sleep, fatigue during the day).

Results: Bedtime procrastination was negatively associated with self-regulation: people who scored lower on self-regulation variables reported more bedtime procrastination. Moreover, self-reported bedtime procrastination was related to general reports of insufficient sleep above and beyond demographics and self-regulation.

Conclusions: Introducing a novel domain in which procrastinators experience problems, bedtime procrastination appears to be a prevalent and relevant issue that is associated with getting insufficient sleep.

An online daily diary study of alcohol use using Amazon's Mechanical Turk

INTRODUCTION AND AIMS

In recent years, unprecedented levels of Internet access and the widespread growth of emergent communication technologies have resulted in significantly greater population access for substance use researchers. Despite the research potential of such technologies, the use of the Internet to recruit individuals for participation in event-level research has been limited. The purpose of this paper is to provide a brief account of the methods and results from an online daily diary study of alcohol use.

DESIGN AND METHODS

Participants were recruited using Amazon's Mechanical Turk. Eligible participants completed a brief screener assessing demographics and health behaviours, with a subset of individuals subsequently recruited to participate in a 2 week daily diary study of alcohol use.

RESULTS

Multilevel models of the daily alcohol data derived from the Mechanical Turk sample (n = 369) replicated several findings commonly reported in daily diary studies of alcohol use.

DISCUSSION AND CONCLUSIONS

Results demonstrate that online participant recruitment and survey administration can be a fruitful method for conducting daily diary alcohol research.