Heavy/at-risk alcohol use among young adults is an important public health problem given its association with health risk behavior and negative consequences. Dual process models of self-control characterize heavy/at-risk alcohol use as a function of (1) automatic appetitive processes and (2) conscious control processes. While existing interventions typically focus on individuals’ conscious control processes, recent research has focused on targeting automatic appetitive processes directly through strategies such as Cognitive Bias Modification (CBM). Although there is some evidence that CBM may improve outcomes for patients in treatment for alcohol use disorder, there is less evidence for its efficacy among young adults. This has been attributed to utilizing CBM as a stand-alone intervention and recruiting samples with low motivation to change drinking in prior studies. To address these limitations, this study examined the efficacy of CBM as an adjunct to brief web-based motivational intervention among young adults interested in changing their drinking. Heavy drinkers, ages 18-34, were recruited through social media platforms and completed an online screener. Eligible participants (N = 81) completed baseline assessment and a web-based motivational intervention (NIAAA- Rethinking Drinking). Participants were randomized to one of two adjunct intervention conditions—CBM or SHAM (control)—that was completed following the motivational intervention and over 4 sessions in the ensuing week. Weekly number of drinks, weekend drinking, alcohol-related consequences, readiness to change, and implicit biases toward alcohol were measured at baseline, 1-week and 1-month follow-up. Intervention condition did not significantly predict the primary outcomes of weekly drinking or consequences at 1-month, controlling for sex. In addition, intervention condition was not associated with implicit bias toward alcohol at 1-week or 1-month follow-up, controlling for sex. Post-hoc analyses revealed the intervention may be differentially efficacious for individuals high, versus low, in readiness to change. Overall, this web based CBM intervention did not reduce drinking behavior, consequences, or implicit biases compared to SHAM. Future work should focus on alternative strategies to modify automatic processes to enhance motivational web-based interventions, particularly among individuals highly motivated to change their behavior.

Social media and online discussion forums have allowed people to hide behind a veil of anonymity, which has made the platforms feel unsafe for people with a different opinion than the majority. Recent research on robots and bots have found that they are a good option when it comes to inducing cooperation or acting as a conversation partner to encourage critical thinking. These robots and bots are based on an algorithm that is able to identify and classify comments, usually into positive and negative comments, left by users. The problem attended to in this thesis is to explore the possibility of creating an algorithm that can classify and pick out a minority opinion with an accuracy of at least 90%. The purpose is to create one of the vital algorithms for a larger project. The goal of this thesis is to provide a functioning algorithm with an accuracy of at least 90% for future implementations. In this thesis, the research approach is quantitative. The results show that it is possible to create an algorithm with the ability to classify and identify comments that also can pick out a minority opinion. Furthermore, the algorithm also achieved an accuracy of at least 90% when it comes to classification of comments, which makes the search for a minority opinion much easier. / Sociala medier och diskussionsforum online har tillåtit människor att gömma sig bakom sin datorskärm och vara anonym. Detta har gjort sociala medier till en osäker plats för människor som inte delar samma åsikt som majoriteten om olika diskussionsämnen. Ny forskning om robotar och sociala botar har funnit att dem är effektiva med att få människor att samarbeta samt att dem är en bra konversationspartner som framkallar mer kritiskt tänkande. Dessa robotar och sociala botar är baserade på en algoritm som kan identifiera och klassificera kommentarer, oftast till positiva eller negativa kommentarer som användare av sociala medier har lämnat. Problemet som avhandlingen försöker lösa är om det är möjligt att skapa en algoritm som kan identifiera och klassificera kommentarer, men även hitta och ta fram en åsikt som inte är en del av majoriteten med en träffsäkerhet på minst 90%. Ändamålet är att skapa en viktig byggsten för ett större forskningsprojekt. Målet med avhandlingen är att skapa en funktionerande algoritm för framtida undersökning som förhoppningsvis kan motarbeta partiskhet i sociala medier. Avhandlingens ståndpunkt är kvantitativ. Resultaten från avhandlingen visar att det är möjligt att skapa en algoritm som kan klassificera samt hitta en åsikt som inte är en del av majoriteten. Dessutom har algoritmen hög noggrannhet när det gäller klassificeringen vilket underlättar sökandet av en åsikt.

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Background: Multiple studies have shown that people who have experienced a serious health problem such as an injury tend to overrate the quality of health they had before that event. The main objective of this study was to test whether the phenomenon of respondents overrating their past health can also be observed in people from the general population. A second aim was to test whether habitual optimism is indeed focused on events in the future. Method: A representatively selected community sample from Leipzig, Germany (n = 2282, age range: 40–75 years) was examined. Respondents were asked to assess their current health, their past health (5 years before), and their expected future health (in 5 years) on a 0–100 scale. In addition, the study participants completed several questionnaires on specific aspects of physical and mental health. Results: Respondents of all age groups assessed their health as having been better in the past than it was at present. Moreover, they also assessed their earlier state of health more positively than people 5 years younger did their current state. Habitual optimism was associated with respondents having more positive expectations of how healthy they will be in 5 years time (r = 0.37), but the correlation with their assessments of their current health was nearly as high (r = 0.36). Conclusion: Highly positive scores of retrospectively assessed health among people who have experienced a health problem cannot totally be accounted for by a response to that health problem.

Industry bias is the bias associated with polling estimates, and that is caused by systematic errors. We aim to test for its presence in Swedish political polling from 2010 to 2022 and simulate industry bias as a consequence of nonresponse bias. We estimate industry bias per party as the mean error of the last polls per polling house before an election and calculate the probability of observing the number of polling underestimates and overestimates per party and election year. Our results indicate that industry bias is present to varying degrees in each Swedish parliamentary election year from 2010 to 2022. Moreover, our results indicate that polls with and without industry bias as a consequence of nonrespondent bias can be replicated.

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The purpose of this study was to examine how race and gender bias influence music educators' perceptions of musical style and evaluations of brief jazz and classical piano performances. Previous research has shown that race and gender bias and stereotype activation influence our judgment of others. These factors could result in biased evaluations of musical performances, including ensemble auditions and college level juries. I constructed an instrument designed to test these biases by experimentally manipulating race and gender variables of jazz and classical performances. Videos of a black male, white male, white female, and black female pianist were synchronized with identical audio recordings to control for performer ability. The first experiment measured how stereotypes influence participants' proper identification of jazz and classical styles in a series of 2-second video clips. The second experiment measured how race and gender bias influence participants' evaluations of jazz and classical performances in a series of 10-second video clips. The participants in this study were a national sample of applied music faculty (n=315). Participants were randomly assigned to four test conditions in a 2x2 (performer race X performer gender) between subjects blind experimental design. The dependent variables were classical jury grade predictions, jazz jury grade predictions, and accuracy of style identification. Results of a 2x2 ANOVA revealed significant differences in style identification by gender and interaction of race and gender. Participants were more likely to associate female performers with classical music and the black male performer with jazz. There were also significant differences in classical jury grade predictions by race, and jazz jury grade predictions by the interaction of race and gender. The black male performer received the lowest average jury grade predictions in both jazz and classical performances, scoring between 0.5 and 1 letter grade lower than the other performers. Results suggest that a negative association of females and jazz music still exists, as well as a stereotype of a black male jazz performer. While females did not receive significantly lower jazz jury grade predictions than the male performers, they may still feel marginalized in college jazz programs and ensembles. The results also suggest that black males may be at a significant disadvantage in college music admissions, auditions, and juries. These results have serious implications for music educators at every level. We must strive for fair and equitable audition processes and ensure that every child, regardless of race or gender, has an equal opportunity to participate in ensembles and music programs. / Music Education