667 Matching Annotations
  1. Sep 2023
    1. Characteristic path length (CPL)

      Broadly refers to how efficiently information is transferred within a neural network of the brain. Important for measuring and analyzing brain connectivity patterns.

    2. transitivity

      Broadly refers to how interconnected or organized a neural network of the brain is. Important for understanding the structure and function of neural networks.

    3. PLV

      Phase-locking value. A statistical measure of the extent to which oscillatory activity in different brain networks is synchronized, for the purpose of determining how interconnected those brain networks are.

    4. .

      Power and connectivity in the delta frequency band increase during unconsciousness, possibly because thalamocortical neurons rapidly alternate between increased and decreased activity at that time. Functional connectivity of the brain may become less complex during unconsciousness due to this rapid alternation.

    5. Figure 2.

      Characteristic path length (CPL) and transitivity of consciousness and nonconsciousness based on phase-locking values.

    6. Table 1.

      TMS-induced and TMS-evoked spectral power in frontal and parietal regions did not significantly differ between consciousness and nonconsciousness in any bands.

    7. Figure 1.

      Phase-locking value was significantly higher for states of nonconsciousness than for states of consciousness in the delta and theta bands. It was also significantly higher for states of consciousness than for states of nonconsciousness in the alpha and beta bands.

    8. .

      The current study evaluated the effects of TMS perturbation on functional connectivity during consciousness and unconsciousness. It was predicted that synchronization of oscillatory activity would be higher in consciousness than in unconsciousness (because of coordinated bistability being higher), and that local aspects of functional segregation would happen strongly during unconsciousness.

    9. delta (1–4 Hz) frequency band

      A range of frequencies which appear on EEG recordings and which denote the occurrence of NREM sleep (deep, dreamless sleep).

    10. negative EEG peak amplitude

      EEG recording of the brain exhibiting a downward deflection/decrease in electrical activity when compared to baseline.

    11. coordinated bistability

      The ability of neuronal networks to coordinate activity between two stable states, e.g., between high activity (high rate of depolarization) and low activity (high rate of hyperpolarization).

    12. Using this approach,a recent study found that spectral power in the delta band in posterior cortex was higher during reported uncon-sciousness than during reported consciousness 23 . Furthermore, using a within-state design in NREM sleep, ithas been found that TMS triggers a larger negative EEG peak amplitude during reported unconsciousness thanduring reported consciousness, indicating that differences in consciousness within the same physiological stateare related to local alterations in the cortical bistability of posterior brain regions 21.
    13. Previous studies have mostly compared wakefulness with sleep or anesthesia to evaluate features associatedwith the level of consciousness in healthy individuals 14,18,19 . However, such studies are confounded by otherchanges that occur across global state shifts, such as changes in the cardiovascular, respiratory, and neuromus-cular systems 20 . To address this issue, recent studies have measured the presence or absence of consciousnesswithin the same physiologically categorized state using a within-state paradigm21–23.
    14. spectral power

      The intensity/magnitude of electrical activity at specific frequencies (in this case, the delta band) within a neural signal measured using EEG.

    15. .

      TMS can effectively probe functional connectivity differences between conscious and unconscious brain states. EEG studies have demonstrated that functional connectivity breaks down in unconscious states by showing that brain responses to TMS are less complex during said states.

    16. Together these resultssuggest that alterations in spectral and spatial characteristics of network properties in posterior brainareas, in particular decreased local (segregated) connectivity at low frequencies, is a potential indicatorof consciousness during sleep.
    17. The neuronal connectivity patterns that differentiate consciousness from unconsciousness remainunclear. Previous studies have demonstrated that effective connectivity, as assessed by transcranialmagnetic stimulation combined with electroencephalography (TMS–EEG), breaks down duringthe loss of consciousness.
  2. Apr 2023
    1. .

      The stress and responsibilities of reintegrating into society are especially challenging for dually diagnosed persons, as many of them lack the interpersonal and life skills to do so. It is therefore important for mental healthcare professionals to assist them in developing these skills.

    2. .

      Dually-diagnosed persons may have an especially difficult time avoiding drug use due to lack of satisfying activities and relationships in their lives, further emphasizing the importance of providing them with opportunities to engaging in enjoyable activities relationships in the context of treatment.

    3. .

      Many participants reported relapsing due to negative emotional states or to self-medicate for psychiatric conditions.

    4. .

      Relapse was common among participants, and boredom was one of the most frequently cited reasons for participant relapse. It is therefore important for dually-diagnosed persons to engage in structured social and recreational activities as part of their SUD treatment. The study was unable to determine how much of a role physical cravings play in the desire of dually-diagnosed individuals to use substances.

    1. .

      Implications of these findings are that preventative measures regarding substance use should be implemented in the ASD population, and that comprehensive psychiatric examinations should be done in individuals with ADHD, ID, and ASD to determine what SUD treatment methods are most effective for each. Another implication is that attempts to treat SUD in ASD should consider vulnerabilities of first degree family members.

    2. We aimed to investigate the risk of substance use-relatedproblems in ASD. We also tested if any association betweenASD and substance use-related problems could be related tocomorbidity with ADHD or intellectual disability (ID). Toelucidate if shared familial factors underlie both ASD andsubstance use-related problems, we examined the pattern ofsubstance use-related problems also among unaffected rela-tives of individuals with ASD.
    3. .

      The study was limited in that it was not able to determine whether shared familial background between ASD and substance use-related problems was due to genetic or environmental factors, and in that it did not differentiate between different forms of autism (although the DSM-5 does not distinguish between types of autism).

    4. In other words, register-based stud-ies are likely to underestimate the absolute prevalence ofsubstance use disorder since users not in contact with thetreatment system are not taken into account (EMCDDA2004).
    5. Second, we could stratify our analysis on comorbidADHD and ID only when those disorders were diagnosed,but it impossible to rule out that patients with seemingly“pure” ASD have undiagnosed ID, ADHD, or subthresh-old ADHD-symptoms involving substance use-relatedproblems
    6. .

      The study may have been biased in that it targeted populations which were more likely to have substance-use related problems in addition to ASD. However, it also found the same results in populations that weren't as likely to have substance-use related problems in addition to ASD.

    7. Strengths include the large scale population-based design,prospectively collected data from nationwide registries,stratification by comorbid disorders, statistical control forsocio-demographic confounders, and analysis of familialaggregation data from relatives. Nevertheless, some limita-tions deserve comments.
    8. .

      Non-autistic relatives of autistic probands were at an increased risk for substance use-related problems. This correlation provides evidence for shared familiar liability regardless of ASD diagnosis. There are several possible explanations: that ASD and substance use-related problems share genetic risk variants, that parental SUD increases rates of mutations involved in ASD due to teratogenic effects of substances, or that associations between ASD and substance use-related problems are caused by shared environmental factors.

    9. We can only speculate that the same familial factors maybe causal in substance use-related problems among ASDprobands may lead also to higher risks of substance-relateddeath among their non-ASD relatives.
    10. As a result, it turned out that patients with ASD only andASD with ADHD are actually on comparable risks of sub-stance use-related problems (OR 1.6 vs. 1.9) and previouslydescribed extremely high risk in patents with ASD andADHD seems to be due diagnostic biases.
  3. Feb 2023
    1. .

      In the study, the three most commonly cited strategies to stop substance use were 12-step meetings, formal treatment, and quitting "cold turkey." The effectiveness of formal treatment has been well-documented for both dual-diagnosed and single-diagnosed persons. While 12-step programs have been found to be effective for single-diagnosed persons, the effectiveness of 12-step for dually-diagnosed persons has been under-researched. Quitting drugs "cold turkey" has been documented in both dual-diagnosed and single-diagnosed drug users, but is much less common.

    2. .

      In this study, one of the most frequent motivations to cease substance use was the negative consequences of substance use. Dually diagnosed substance users often consider only short term consequences of substance use, and so do not take them into consideration when using substances. Over time, however, the long term consequences of substance use become bad enough that even dually diagnosed people curb or decrease their substance use.

    3. .

      Participants usually started using substances to "fit in" with peers during adolescence. It may be the case that mentally ill adolescents have an especially strong need to fit, since being mentally ill may cause them to feel alienated from their peers. It has been suggested that they seek out drugs because of this, and often find belonging in drug-related social networks where people are more accepting of differences.

    4. Table 3

      The first table depicts mean percentages for participants' descriptions of "what [was] going on inside of [them]" that triggered them to return to substance use after a drug-free period of one month or longer. The most common responses were "lonely, bored" (31%) and "craved, wanted to use" (31%).

      The second table depicts mean percentages for participants' descriptions of "what happened in the outside world (social situation, event)" that triggered them to return to substance use after a drug free period of one month or longer. The most common responses were "temptations" (28%) and "stress/responsibilities" (28%).

    5. Table 2

      The first table depicts mean percentages for participants' stated reasons as to why they stopped using drugs. The most common reason participants gave for no longer using was "wanted a better life/tired of drugs" (54%).

      The second table depicts mean percentages for participants' stated methods for stopping drug use. The most commonly cited methods by participants were "12-step/self-help groups" (45%), "treatment" (34%), and "cold turkey/willpower" (30%).

    6. Table 1

      The first table depicts mean percentages for each substance (alcohol, marijuana, cocaine, heroin, hallucinogens, tranquilizers, other pills, or other drugs) participants mentioned (first mention or any mention) when asked the question "at the time when you first started, what did you use?" Most used substances, regardless of whether first mentioned or mentioned at all, were alcohol and marijuana.

      The second table depicts mean percentages for the most commonly cited reasons (wanted to fit in with peers, family member/caretaker used, emotional/mental issues, fun/experiment/curiosity, problems at home or school, traumatic, stressful event, wanted to drink/use) participants started using by diagnosis (total, schizophrenia, bipolar, or depression). Overall, the highest percentage of participants said they started using to fit in with peers.

    7. .

      It is additionally important to investigate reasons for wanting to stop substance use and resources used to attain abstinence in dually-diagnosed individuals, for the purpose of designing more effective interventions in this population. However, this area of study has also been under-researched.

    8. .

      While the biological and pharmacological factors impacting dual diagnosis have been well investigated, the psychosocial factors impacting it (including substance users' stated reasons for substance use) have not. Following Fishbein's theory of reasoned action, it has been proposed that substance users' personal beliefs about why they use substances may largely determine their substance use behaviors. In particular, dually-diagnosed peoples' perception of the interplay between SMI and SUD may play a major role in their substance use, but this area of study is under-researched.

    9. 1. to examine stated reasons for initiation of andrelapse to substance use,2. to examine reasons and strategies used for quit-ting, and3. to explore the perceived association betweensubstance use and mental illness among a largesample of persons with co-occurring SMI andSUD.
    10. The aims of this articleare
    11. Fishbein’s(1980) theory of reasoned action postulates that be-havior is based on attitudes that, in turn, are based onpersonal beliefs. Beliefs rest in large part on what islearnt and experienced; in particular, beliefs that arebased on personal experience have been found tohave a stronger influence in the formation of attitudesthan information gained in other ways and to betterpredict later behavior (Fazio & Zanna, 1981).
    12. The supersensitivity model, wherebybiological vulnerability due to psychiatric disorderresults in sensitivity to small amounts of alcoholand drugs, leading to substance misuse, has alsoreceived some support (e.g., Lieberman, Kane, &Alvir, 1987).
    13. .

      Several models have been proposed to explain the high rate of comorbidity between SUDs and SMIs. These include family history, ASPD, and the super-sensitivity model. The self-medication model states that specific substances are used to alleviate certain painful affects, but it is not empirically supported. The "alleviation of dysphoria" model is empirically supported, and states that people with SMIs are prone to dysphoric states that predispose them to drug use, which results in them becoming addicted to drugs.

    14. .

      It is important to better understand causes of substance use in individuals with co-occurring SUDs and SMIs, as the reasons for which they use substances may radically differ from the reasons for which individuals with only SUDs use substances. Increasing our understanding in this area will be important for increasing the effectiveness of therapeutic interventions.

    15. .

      SUDs have a high rate of co-occurrence with SMIs (severe mental illnesses). Individuals with co-occurring SUD and SMI have a heightened vulnerability to medical, legal, social, and financial problems. Such problems tend to decrease when said individuals attain abstinence and engage in treatment interventions.

    16. The etiology of substance use among persons with severe mental illness remains unclear. Thisstudy investigates stated reasons for substance use among persons in recovery from co-occurringdisorders of serious mental illness and substance abuse and dependence. The desire to fit in withpeers played a key role in the initiation of substance use; boredom, loneliness, temptations to use,and stress were cited most as relapse triggers.
    1. .

      There are numerous potential reasons as to why it was historically believed that ASD is a protective factor against substance use-related problems. One likely explanation is that substance use in general was less common in the past, so those with ASD were less likely to have substance use-related problems, and research at the time reflected this. Another explanation is that past diagnostic criteria for ASD was narrow and excluded individuals with ASD and substance use-related problems, which also would have been reflected by research at the time.

    2. Increased risk of substance use-related problems seemsto contradict global negative attitudes towards psychoac-tive substances observed among ASD patients (Ramos etal. 2013). Individuals with ASD may find them helpful toreduce tension and enhance social skills more often thannon-ASD controls do (Cludius et al. 2013).
    3. Table 3

      Table depicting means (with standard deviations) of proband relatives (full siblings, half siblings, and parents) with various substance use problems (any problem, substance use disorder, alcohol, drugs, tobacco, crime, death, or somatic disease). Also depicts univariate (crude) analyses of the odds ratios (with CIs) for these substance related problems overall, in the presence of a proband with ASD alone, in the presence of a proband with ASD and comorbid ADHD, in the presence of a proband with ASD and comorbid ID, and in the presence of a proband with ASD and comorbid ADHD and ID. Many of the univariate analyses of the odds ratios were statistically significant, meaning that many substance-related problems are significantly likely to occur in relatives of probands with ASD and other comorbid disorders.

    4. Table 2

      Table depicting univariate (crude) and multivariate (adjusted for parental age, region of birth, education, and family income) analyses of the odds ratios (with CIs) for various substance use related problems in the presence of ASD comorbid with other conditions (none, ADHD, ID, and ADHD and ID). Univariate and multivariate analyses of the odds ratios were statistically significant for many substance-related problems in the presence ASD by itself, ASD comorbid with ID, and ASD comorbid with ADHD And ID, and for all substance-related problems in the presence of ASD comorbid with ADHD. This means that substance related problems are equally and significantly likely to co-occur in individuals with ASD alone, ASD comorbid with ID, and ASD comorbid with ADHD. They are also more and significantly likely to co occur in individuals in individuals with comorbid ASD and ADHD.

    5. Despite limited and ambiguous empirical data,substance use-related problems have been assumed to berare among patients with autism spectrum disorders (ASD).
    6. .

      It is widely believed by experts that ASD is not a risk factor for substance use-related problems, but many of the studies that support this assertion compared substance use in people with ASD to substance use in people with other psychiatric conditions that predispose substance use, so their results may have been biased. Another more recent study examined whether ASD traits predispose substance use, but not whether ASD diagnoses does.

    7. We found that ASD was associated with increased risk fora range of substance use-related problems, and the familydata suggested that this was due to shared liability betweenASD and substance use-related problems between relatives.
    8. Table 1

      Table depicting the means (with standard deviations) of patients (ASD and non-ASD) with various substance related problems (any problem, substance use disorder, alcohol, drugs, tobacco, crime, somatic disease, or death). Also depicts univariate (crude) and multivariate (adjusted for parental age, region of birth, education, and family income) analyses of the odds ratios (with CIs) for these substance related problems in the presence of ASD. Almost all of the univariate and multivariate analyses of the odds ratios were statistically significant, meaning that almost all of the substance related problems are significantly likely to co-occur with ASD.

    9. Odds ratios (ORs)

      A statistic that quantifies the strength of association between two events, A and B. It is the ratio of the odds of A in the presence of B, the odds of A in the absence of B, the odds of B in the presence of A, or the odds of B in the absence of A.

    10. probands

      A person that serves as the starting point for a genetic familial study.

    11. We conclude that ASD is arisk factor for substance use-related problems. The elevatedrisks among relatives of probands with ASD suggest sharedfamilial (genetic and/or shared environmental) liability.
    12. .

      Although substance use is thought to be rare in people with ASD, it has been documented in a significant percentage of that population (19-30%). This may be because there is a high rate of comorbidity between ASD and ADHD, which is linked to substance use. While older studies of clinical populations suggest that ADHD is the risk factor underlying increased substance use in people with ASD, newer studies of non-clinical populations suggest that ASD alone could be a risk factor for increased substance use.

  4. Aug 2022
    1. Thus, our research contributes to aburgeoning literature on cross-group friendships by showingthat the positive effects of friendship can extend beyond inter-group attitudes per se to institutional attitudes, and by directlytesting causal links from cross-race friendships to positiveintergroup outcomes (cf. Pettigrew, 1998).
    2. To the extent that a friend’s perceivedmembership in the university in-group is salient, cross-groupfriendship may increase the likelihood that minority-groupstudents will eventually incorporate a university identity as partof themselves.
    3. Therefore, friendships with majority-group peers may be key in the development of dual identityamong minority-group students, and may provide a route towardrelational diversity within institutions of higher education.
    4. Our research underscoresthe importance of the interpersonal climate for addressing issuesof access and diversity within such institutions, and shows thatthe development of affiliative ties across group boundariesprovides an important vehicle for achieving relational diversity.
    5. Together, thefindings of these studies suggest that efforts to increase cross-group friendship are not incompatible with institutional effortsto clearly communicate acceptance of the minority group bysupporting organizations or activities centered on the ethnic orracial background of that group.
    6. This analysisrevealed the predicted three-way interaction, b 5 0.80, F(1, 126)5 6.10, p < .02.

      Replicated the finding that minority group individuals with high race-based rejection anxiety having friendships with majority-group peers increased university satisfaction. Additionally, minority group individuals with high race-based rejection anxiety are overall less satisfied with the university than minority group individuals with low race-based rejection anxiety.

    7. .

      Participants attended three friendship-intervention sessions. For the first two sessions, they asked and answered increasingly personal questions about one another for 45 minutes. For the third session, they played a game of Jenga together and then filled out a questionnaire assessing university satisfaction.

    8. .

      Participants were informed about the nature of the study, filled out RS-race and RS-personal questionnaires, and then gave their informed consent.

    9. Within 2 weeks of theinformation session, participants were randomly assigned to asame- or cross-group partner, with the restriction that partnersneeded to have compatible schedules.

      Participants were randomly assigned to an experimental (cross-group) or control (same-group) condition. The independent variable being manipulated is race of person interacted with (different or the same), and the dependent variable being measured was is university satisfaction.

    10. Over the course of data collec-tion, the ethnic composition of the undergraduate population atthe university was, on average, 34.4% White and 12.0% Latino.Our sample consisted of 76 White participants and 59 Latinoparticipants.
    11. The model for university satisfaction revealed a significant in-teraction between number of majority-group friends and RS-race, b 5 0.46, F(1, 34) 5 7.19, p 5 .01.

      Minority group individuals with high race-based rejection anxiety having friendships with majority-group peers decreased dissatisfaction at their university.

    12. The analysis for belonging revealed a significant main effect ofRS-race, b 5 0.25, F(1, 34) 5 6.17, p < .02.

      minority group individuals with high race-based rejection anxiety having friendships with majority-group peers decreased lack of belonging.

    13. We specifically addressed thequestion of whether friendships developed with majority-grouppeers over the 1st year of college predicted feelings of belongingin the university 1 to 2 years later, as well as change in satis-faction with the university over this time period.
    14. Study 1 was a 3-year longitudinal study of two cohorts of AfricanAmerican college students at a university where African Amer-icans represented less than 10%, and Whites represented morethan 50%, of the student body over the course of data collection(see Mendoza-Denton et al., 2002).
    15. Given these converging lines of research, we tested whetherfriendships with majority-group peers would buffer minoritystudents who are high in RS-race from feelings of alienation anddiscomfort in historically White university settings.
    16. In a longitudinalstudy of African American students (Study 1), cross-groupfriendships with majority-group peers buffered studentshigh in RS-race from lack of belonging and dissatisfactionat their university. An experimental intervention (Study 2)that induced cross-group friendship replicated the findingsand established their specificity for minority-group stu-dents.
    17. Givenresearch documenting the benefits of cross-group friend-ship for intergroup attitudes, we tested whether friend-ships with majority-group peers would attenuate theeffects of RS-race within these contexts
  5. www.researchgate.net www.researchgate.net
    1. More specifically, we ex-pected that the development of a cross-group friendship wouldlead to more initiation of intergroup interactions during the diaryperiod, particularly among those who were originally predisposedto anxiety in such interactions. We further hypothesized that par-ticipants higher in RS-race would report more anxious mood overthe diary period but that this anxiety would be attenuated throughthe development of cross-group friendship.
    2. Bringing together the above literatures, we hypothesized thatonly participants who are likely to experience anxiety in intergroupcontexts (either because of RS-race or implicit prejudice) shouldshow signs of hormonal stress responses when they first meet across-group partner, but that cross-group friendship should atten-uate such stress responses over the course of friendship develop-ment. As a corollary, participants who scored lower on measuresof RS-race or implicit prejudice were not expected to show suchattenuation in the cross-group condition because they should havebeen less likely to exhibit hormonal stress responses in the firstplace.
    3. On the one hand, we hypothesized that cortisol reactivityshould be the least pronounced among participants who werepredisposed to anxiety in intergroup contexts but also paired witha cross-group partner with prior intergroup contact. On the otherhand, a series of recent findings have led to an alternate hypothesisthat participants with prior intergroup contact may engendergreater threat among outgroup partners who are vigilant for cues ofrejection in intergroup encounters.
    4. Generally, we propose that cross-group friendship improvesintergroup interactions through systematic disconfirmations ofnegative expectations about intergroup experiences (Mendoza-Denton, Page-Gould, & Pietrzak, 2006).
    5. Zande, 1999), we report a study in which friendship was inducedbetween same- and cross-group dyads of Latinos/as and Whites.
    6. Building on the experimental paradigm used by Wright andcolleagues (Wright et al., 1998, 2002, 2005; Wright & van der
    7. Wright and his colleagues(see Wright, Aron, & Tropp, 2002; Wright, Brody, & Aron, 2005;Wright, Ropp, & Tropp, 1998; Wright & van der Zande, 1999)described research that provided initial evidence for the causaleffects of cross-group friendship on self-reported anxiety.
    8. Even though interactions between members of different socialgroups are sometimes characterized by anxiety and threat (Blas-covich, Mendes, Hunter, Lickel, & Kowai-Bell, 2001; Mendes,Blascovich, Lickel, & Hunter, 2002; Stephan & Stephan, 1985,2000), a growing body of research suggests that cross-groupfriendship can attenuate such anxiety.
    9. These findings provide experimental evidence that cross-group friendship is beneficial forpeople who are likely to experience anxiety in intergroup contexts.
    10. Cross-group friendship led to decreases incortisol reactivity (a hormonal correlate of stress; W. R. Lovallo & T. L. Thomas, 2000) over 3 friendshipmeetings among participants high in race-based rejection sensitivity (R. Mendoza-Denton, G. Downey,V. J. Purdie, A. Davis, & J. Pietrzak, 2002) and participants high in implicit prejudice (A. G. Greenwald,B. A. Nosek, & M. R. Banaji, 2003). Cross-group partners’ prior intergroup contact moderated therelationship between race-based rejection sensitivity and cortisol reactivity. Following the manipulation,participants kept daily diaries of their experiences in an ethnically diverse setting. Implicitly prejudicedparticipants initiated more intergroup interactions during the diary period after making a cross-groupfriend. Participants who had made a cross-group friend reported lower anxious mood during the diaryperiod, which compensated for greater anxious mood among participants high in race-based rejectionsensitivity.
    11. The authors induced cross-group friendship between Latinos/as and Whites to test the effects ofcross-group friendship on anxiety in intergroup contexts.
  6. Jun 2022
    1. To address these limitations, in Experiment 1, we requiredparticipants to rate their confidence after each individual response(rather than after each pair of responses).
    2. In Experiment 4, we manipulated participants’ confidence priorto administration of the MRT. All participants first completed aline judgment task that was intentionally difficult, so that par-ticipants would be unable to gauge their performance.
    3. Upon completion of the line judgment task, participants wererandomly informed that their performance on the line judgmenttask was either above average (‘‘high confidence’’condition) orbelow average (‘‘low confidence’’ condition).
    4. Ifconfidence mediates mental rotation performance, then partic-ipants in the high confidence condition should outperform theircounterparts in the low confidence condition.
    5. Cooke-Simpson and Voyer (2007) provided tentative evi-dence that confidence predicted MRT performance, but thatstudy had several critical limitations.
    6. correlation was comparable to that observed in prior studies(r = ?.69; Cooke-Simpson & Voyer, 2007).
    7. As illustrated in Fig. 2, confidence predicted accuracy acrossboth sexes, r(67) = ?.56, p\.001, and the strength of this
    8. Fig. 6

      Accuracy percentage as a function of confidence within male and female participants in experiment 3.

      Accuracy and confidence were significantly positively correlated for both males and females.

    9. Fig. 5

      Accuracy percentage as a function of confidence between male and female participants in Experiment 3.

      Accuracy and confidence were significantly positively correlated for both males and females, and females increased their accuracy as a function of confidence more so than males did.

    10. Thisresult replicates the general pattern observed in Experiment 1(Fig. 3), and indicates that both males’ and females’ confi-dence was indeed calibrated to their performance.
    11. Experiment3 therefore supported the hypothesis that mental rotation ismediated by confidence.
    12. Experiment 3 provided a further test of whether the sex differencein performance is better explained by confidence or by omissions.
    13. Results are summarized in Table 1. The sex difference in accu-racy was replicated in the omission condition but not in the com-mission condition.
    14. Thus, the sex difference in mental rotationwas attributable to confidence rather than omissions.
    15. mediates mental rotation. If confidence was unrelated to mentalrotation, then the sex difference should be equivalent acrossgroups (i.e., no interaction should occur).
    16. Critically, an inter-action in either direction would suggest that confidence
    17. .

      It could also be the case that confidence would have more of an effect on the commission group than the omission group, which would exacerbate the sex difference in MRT performance.

    18. .

      There were two conditions in this experiment, one in which participants could omit trials at their discretion (omission) and one in which they had to respond to every trial (commission). The idea here was that confidence would have less of an effect on the commission group than the omission group, which would eliminate the sex difference in MRT performance.

    19. In Experiment 2, we sought to attenuate the sex difference inmental rotation performance by rendering confidence irrelevantto the task.
    20. Fig. 4

      Shows the mediating relationships between sex, confidence, and mental rotation, via Baron and Kenny's regression method for simple mediation.

      Sex negatively predicted both confidence rating and mental rotation score, whereas confidence positively predicted mental rotation score. Confidence seems to mediate the sex difference in MRT performance.

    21. In conclusion, Experiment 1 corroborated the finding thatconfidence predicted mental rotation performance both acrossand within sexes (Cooke-Simpson & Voyer, 2007). Experiment1 further demonstrated, for the first time, that confidence pre-dicted mental rotation performance within individuals: Partic-ipants were more accurate on trials for which they were moreconfident. These results thus provide the most precise evidenceto date of the relation between confidence and mental rotation.Finally, Experiment 1 also provided the first evidence of thedirection of this relationship: Mediation analyses revealed thatconfidence mediated the sex difference in mental rotation per-formance whereas mental rotation performance did not mediatethe sex difference in confidence.
    22. If confidence mediates mental rotation performance,then confidence ought to predict accuracy on the MRT acrosssexes, within each sex, and possibly even within individuals.
    23. In Experiment 1, we tested whether confidence predicted men-tal rotation performance between sexes, within each sex, andwithin individuals.
    24. Thus, mental rotation performance did notmediate the sex difference in confidence, but rather confidencestrongly mediated the sex difference in mental rotation per-formance.
    25. Fig. 3

      Accuracy percentage as a function of confidence rating within male and female participants in experiment 1.

    26. Fig. 2

      Accuracy percentage as a function of confidence rating between male and female participants in experiment 1.

    27. So, together, Figs. 2 and 3 reveal thatmales and females were similarly successful at calibrating theirconfidence to their accuracy (Fig. 3), though males tendedtoward the upper part of the distribution on both confidence andaccuracy (Fig. 2).
    28. Table 1

      Mean accuracy percentage (along with sample size and standard deviation) for males and females and effect size of sex difference in accuracy percentage for all conditions of each experiment.

      Effect size of sex difference in accuracy percentage was significant in the first and second experiments (p < .05; p < .01), the confidence condition of the third experiment (p < .001), the high confidence condition of the fourth experiment (p < .01), and the low confidence condition of the fourth experiment (p < .06).

    29. As expected, an independent samples t-test revealed that males(M = 5.61, SD = 1.02) were more confident than females (M =4.62, SD = 1.41), d = .74, t(65) = 3.26, p\.01.
    30. Specifically, if confidence medi-ates mental rotation, then (1) confidence should predict mentalrotation scores not only between sexes, but also within sexes, (2)rendering confidence irrelevant to the task should attenuate thesex difference, and (3) manipulating participants’ confidenceshould affect their mental rotation performance.
    31. .

      Women provide fewer responses to the MRT than men, which means that they deliberately abstain from responding to some MRT questions. This could indicate that women are less confident of their MRT responses than men are.

    32. Because confidence appears tobe an important component of the MRT, it stands as a plausiblemediator of performance.
    33. The most common measure of mental rotation performanceis the Mental Rotations Test (MRT; Vandenberg & Kuse, 1978),which is based on the 3-dimensional block figures introduced byShepard and Metzler (1971) and updated by Peters et al. (1995).
    34. .

      Evidence from previous research indicates that confidence mediates performance on cognitive tasks, but the relationship between confidence and spatial ability is under studied and not well understood.

    35. Preliminary evidence suggests that confidence might indeedunderlie the sex difference in mental rotation.
    36. .

      Multiple studies have found that stereotype threat (especially for sex stereotypes) can affect performance on cognitive tasks by influencing confidence.

    37. We therefore tested whether confidence mediatedmental rotation performance.
    38. basic cognitive skills, such as attention, memory, and judgment(e.g., Schmader et al., 2008), which ultimately would affectperformance.
    39. The beliefthat one (or one’s social group) is skilled or poor at a given taskmay well affect one’s confidence when approaching that taskand this effect on confidence may have cascading effects on
    40. Much of the research on gender role and sex stereotype effectsassumes confidence as a potential cognitive mechanism bywhich those social factors exert their effect.
    41. So, in summary, beliefs about and aware-ness of sex stereotypes are both related to the sex difference inmental rotation performance. But how exactly might sex ste-reotypes affect performance?
    42. Mental rotation performance may also be affected by mereawareness of, rather than belief in, the stereotype that men aresuperior to women on spatial tasks.
    43. .

      Research has suggested that women who hold the stereotypical belief that men are better than women at spatial tasks might perform worse on these spatial tasks as a result of this belief.

    44. Performance on spatialtasks thus is clearly related to gender role beliefs and traits.
    45. Gender role beliefs and traits may partially explain the sex dif-ference in mental rotation performance.
    46. Here, we examined whether one suchsociocognitive factor, namely participants’ confidence, contrib-uted to this sex difference in mental rotation performance.Although this presumed relation between confidence and men-tal rotation performance has received little empirical attention,related research on gender roles, sex stereotypes, and stereotypethreat provides a rich source of supportive evidence.
    47. .

      Research has reliably demonstrated that men perform better at the MRT than women do. It is unlikely that there is a purely biological explanation for this sex difference, and sociocognitive factors probably play a role in the sex difference.

    48. Given the complexity of the taskand the magnitude of the sex difference, it likely has multi-ple causes or mediators.
    49. Of all cognitive sex differences, the mental rotation of abstractfigures in 3-dimensional space is the most robust (Halpern, 2000;Hines, 2004; Linn & Petersen, 1985; Maccoby & Jacklin, 1974).
    50. Thus, confidence medi-ates the sex difference in mental rotation performance and hencethe sex difference appears to be a difference of performancerather than ability. Results are discussed in relation to otherpotential mediators and mechanisms, such as gender roles,sex stereotypes, spatial experience, rotation strategies, work-ing memory, and spatial attention.
    51. On tasks that require the mental rotation of 3-dimensional figures, males typically exhibit higher accuracythan females. Using the most common measure of mental rota-tion (i.e., the Mental Rotations Test), we investigated whetherindividual variability in confidence mediates this sex differ-ence in mental rotation performance.
    1. Table 1

      Average percentage of problems attempted for males and females in sets 1 and 2 for the 3 minute and 6 minute time conditions in study 2. Significant overall effects are shown for time (3 min or 6 min), test half (set 1 or 2), sex (male or female), interaction between time and sex, and interaction between time and test half.

      Percentage of problems attempted was generally higher in the 6 min condition than in the 3 min condition (time difference), in the 2nd set than in the 1st set (practice effect), and for males than for females (sex difference). The interaction effect between time and sex indicates that males attempt more problems than females throughout, but that the difference decreases as more time is given. The interaction effect between time and test half indicates that participants attempt more problems in the second half of the test than in the first half, but that the difference decreases as more time is given.

    2. Table 2

      Mean amount of problems solved (with SD) for males and females in the 3 minute and 6 minute time conditions of study 2. Significant main effects are shown for sex (male or female) and time (3 min or 6 min).

      Main effect of sex indicates that on average, males solved more problems than females. Main effect of time indicates that on average, participants solved more problems in the 6 min condition than in the 3 min condition.

    3. Fig. 3.

      Magnitude of effect size in sex differences as a function of problem position.

      Shows that the magnitude of sex difference effect size increased the further subjects got into the set. I.e., the further subjects got into the set, the greater the sex difference in performance was (males outperformed females).

    4. Fig. 1.

      The figures that are shown in the Vandenburg and Kuse MRT. The target stimulus is the leftmost stimulus shown here. Two of the stimuli to the left of the target figure are rotated versions of the target figure, and two of them are distractor figures. Participants had to identify which figures were rotated versions of the target figure.

    5. Fig. 2.

      Percentage of problems attempted as a function of problem position for males and females in the first and second sets of study 1.

      Both males and females would attempt less problems the further they got in the set, but this effect was greater for females than for males. Also, both males and females attempted more problems the further they got in the second set than in the first set, revealing a practice effect.

    6. .

      Varying the amount of stimuli presented to the participants in the MRT could reveal sex differences as a result of women spending more time making sure that their MRT answers are correct than men do.

    7. Thus, the third approach to the issue of Sex differencesand the time factor in the MRT examined the sex differ-ence in a RT paradigm where only two mental rotationfigures were used.
    8. .

      A past study found evidence to support the assertion that women take more time than men do on the MRT because women spend extra time making sure that their answer is correct while men do not do this. This is an alternative explanation to women taking more time than men do on the MRT because they simply cannot solve spatial problems as fast as men can.

    9. For this reason, Study 2, which manipulatestime directly, compares sex differences under the stan-dard condition with sex differences which are observedwhen time is increased, but within limits.
    10. Here, we administered the MRT under identical con-ditions, but allowing two durations.
    11. .

      Large sample size allows for the examination of sex differences on the MRT as it progresses. This condition documents the effect of time constraints on MRT performance between sexes (baseline condition).

    12. If time pressure is a significant factor in per-formance, we expect to see two indicators in the data.First, we expect to see that females attempt significantlyfewer problems than males and, second, we expect to seethat the magnitude of the sex difference increases as theproblem position increases.
    13. In the present study, three different approaches to theproblem of time constraints are taken, each examining adifferent aspect of how time might affect the sex differ-ences on the MRT.
    14. Thus, our understanding of the role of time con-straints in MRT sex differences remains inconclusive.
    15. Several studies find that when enough time is pro-vided for the V&K MRT, sex differences on the MRTdisappear (Goldstein, Haldane, & Mitchell, 1990;Voyer, 1997), leading to the conclusion that sex differ-ences arise because the sexes differ in the amount of timetaken to perform the mental rotation.
    16. The idea that the activational effects of hormones mightlead to relatively faster mental rotations touches uponthe time factor in MRT sex differences.
    17. That males and females differ in performance on Van-denberg and Kuse (1978) mental rotation task is wellknown (Voyer, Voyer, & Bryden, 1995). The causes areless well understood.
    18. .

      Sex differences may arise because of qualitative differences in how the sexes solve spatial problems, or because of spatial problem solving ability being modulated by hormonal differences between the sexes.

    19. We conclude that performancefactors may play a role in sex difference on mental rotation tasks, but do not account for all of the differences.
    20. In accounting for the well-established sex differences on mental rotation tasks that involve cube stimuli of the Shepard and Met-zler (Shepard & Metzler, 1971) kind, performance factors are frequently invoked.
    1. .

      Lots of research has investigated the cause of sex differences in MRT performance. One proposed explanation is that men and women emphasize different instructional aspects under timed conditions. For this reason, men are able to complete more items than women do when taking the MRT.

    2. Gender differences in favor of men in spatial abilities are one of the most commonly replicated finding inpsychology research (Hedges & Nowell, 1995; Linn & Petersen, 1985; Voyer, Voyer, & Bryden, 1995). Among thetasks that produce such differences, the Mental Rotations Test (MRT), developed by Vandenberg and Kuse (1978),produces the largest effects (Linn & Petersen, 1985; Peters, 2005).
    3. Eighty undergraduate students (40 males, 40 females) completed the MRT while ratingtheir confidence in the accuracy of their answers for each item. As expected, gender differences in favor of men were obtained.Results also indicated a positive correlation between confidence ratings and scores on the MRT, as well as negative correlationsbetween confidence ratings and MRT outcomes presumed to reflect propensity to guess. More elaborate analyses using a measureof accuracy of predictions (the Brier score) indicated that men have a more accurate perception of their performance on the MRTthan women do.



    1. Further support for a constant anduniform biological explanation comes from studies that findsimilar effect sizes for gender across cultures (Silverman,Phillips, & Silverman, 1996).
    2. The distinct hormonal environments of men and womenmay play a role.
    3. .

      Hormones having an activational effect on cognitive functioning in adulthood could also cause sex differences in the MRT. Research has suggested that greater exposure to androgens/estrogens in adulthood can affect cognitive functioning.

    4. .

      Organizational effects during prenatal development could also play a role in MRT sex differences, since these effects could cause the brain to develop differently based on androgen or estradiol exposure. They could also occur as a result of hemispheric specialization. Right hemisphere specialization favors spatial tasks, and left hemisphere specialization favors verbal tasks, and male brains are more lateralized to the right while female brains are more bilateral. For this reason, men may have an advantage in spatial processing that causes them to be better at the MRT. .

    5. When brain imaging studies are done on subjects per-forming mental rotation tasks, there is some evidence ofactivation in motor areas of the brain.
    6. .

      Neuroimaging studies have shown that mental rotation involves parietal region activation. Specifically, males activate the left inferior parietal region and the right head of the caudate nucleus while completing MRTs and females activate the parietal lobe in general while completing MRTs.

    7. Biological factors have also been discussed as potentialcauses for this difference. Biological theories stress theimportance of genetics, hormonal influence, brain organi-zation, and maturational factors.
    8. There is,however, no consensus as to the role of task complexity ongender differences in mental rotation.
    9. Task difficulty is one potential performance factor thathas been explored (Bryden, George, & Inch, 1990; Collins& Kimura, 1997).
    10. .

      Differences in performance on the mental rotation task could be due to cultural norms subconsciously influencing performance or due to task variables that inflate male performance advantage (such as task difficulty, previous task exposure, time limits, and weighted scoring systems).

    11. .

      The mental rotations test (MRT) was created by Vandenberg and Kuse (1978). It uses line drawing of block stimuli and consists of two 10-item sections in which the subject is required to match two of four choices to a target figure.

    12. A number of explanations have been advanced for theexistence of the gender difference in mental rotation.
    13. Voyer, Voyer, & Bryden’s (1995) meta-analysis of sexdifferences in spatial abilities, found that the average differ-ence (using Cohen’s d = (M1 − M2)/σ) between men andwomen on the (MRT; Vandenberg & Kuse, 1978), was 0.94(this represents a very large effect), indicating that men per-form nearly one standard deviation above the average per-formance of women.
    14. The ability to mentally rotate an object has been foundto produce one of the largest sex differences in the cogni-tive literature (Linn & Petersen, 1985).
    15. The visuospatial ability referred to as mental rotation has been shown to produce one of the largest and most consistent sex differences,in favor of males, in the cognitive literature.
    16. Sex differences were also seen in the patterns of correlations between rotation tasks and other neuropsycho-logical measures. Current results suggest men may rely more on left hemisphere processing than women when engaged in rotational tasks.© 2003 Elsevier Ltd. All rights reserved.



    1. .

      If men have a visuospatial advantage and global bias, and if women have a local advantage, then men should be better at classifying line orientation than women, and men should exhibit a global advantage and women should exhibit a local advantage regardless of relevant classification property. It could also be that men would be faster than women in global classification and women would be faster than men in local classification regardless of relevant classification property, Likewise, if gender differences in global-local processing are only related to visuospatial performance, then global bias for men and local bias for women would only be observed for line orientation classification but not for closure classification.

    2. .

      Global-local processing is typically tested using hierarchical stimuli (larger figures are composed of smaller figures). Generally speaking, people usually display a global advantage (faster responses to larger figures than smaller figures) in processing the hierarchical stimuli. Also, they typically display global-to-local interference (conflicting information between the larger figures and the smaller figures interferes with responses to the smaller figures but not the larger ones). Global advantage can be confounded by factors like visual angle, exposure duration, retinal position, density of elements, number and relative size of elements, and the nature of the stimuli at the global and local level.

    3. .

      Men and women were shown hierarchical stimuli that differed in closure (open/closed shape) and line orientation (oblique/horizontal or vertical line) at the global or local level. They had to classify the stimuli on the basis global variation or local variation.

    4. Pre-vious results with similar stimuli and mixed groups of participants(Han, Humphreys, & Chen, 1999; Kimchi, 1994) showed the globaladvantage that is typically observed with hierarchical stimuli (e.g.Kimchi, 1992; Navon, 1977), as well as faster classification by clo-sure than by line orientation. In addition, the global advantage wasmore pronounced when local classification was based on line ori-entation than on closure (Han et al., 1999; Kimchi, 1994).
    5. Thus, in this study, we examined gender differences in global–local processing with a visuospatial judgment task (line orienta-tion) and a shape judgment task (open vs. closed shape).
    6. .

      The stimuli used in this study were specifically designed to evoke the typical global advantage. The study also included both spatial and non-spatial task contexts to see if sex differences in global-local perception only happened in spatial task contexts.

    7. The investigation of gender differences in global–localprocessing in the context of a spatial and a non-spatial task will al-low us to examine whether these differences, if they exist, charac-terize visual perception of women and men in general, or whetherthey are related only to visuospatial performance.
    8. The main purpose of the present study was to systematicallyexamine gender differences in global–local processing.
    9. The inconsistencies in the results of these studies are mostprobably due to the differences in stimulus and task variables,which are known to affect global–local performance, as discussedearlier.
    10. Direct examinations of gender differences in global–local pro-cessing are sparse, and the results are equivocal.
    11. .

      Gender differences in global-local bias could be the result of hemispheric specialization differences in men and women. Women are better at cognitive tasks that use the left hemisphere, which is more implicated in local processing, and men are better at cognitive tasks that use the right hemisphere, which is more implicated in global processing.

    12. .

      Research suggests that men use more "global" reference points (such as the position of the sun in the sky) when navigating, while women use more "local" reference points (such as landmarks) when navigating.

    13. The gender differences in navigation and way-finding also ap-pear to suggest a global bias for men versus a local bias for women.
    14. .

      Gender differences in mental rotation tasks could be accounted for by men and women using different strategies to mentally rotate an object. Research suggests that men use a more holistic or "global" approach when mentally rotating objects, while women use a more segmented or "local" approach when when mentally rotating objects.

    15. .

      Men outperform women on a variety of spatial tasks, from mental rotation tasks to maze navigation tasks.

    16. Gender differences in spatial abilities have been reported in anumber of studies over the years (see Voyer, Voyer, & Bryden,1995, for a review).
    17. Direct examinations of gender differences in global–local processing are sparse, and the results are incon-sistent. We examined this issue with a visuospatial judgment task and with a shape judgment task.Women and men were presented with hierarchical stimuli that varied in closure (open or closed shape)or in line orientation (oblique or horizontal/vertical) at the global or local level. The task was to classifythe stimuli on the basis of the variation at the global level (global classification) or at the local level (localclassification).
    18. This finding suggests that women aremore distracted than men by misleading global oriented context when performing local orientation judg-ments, perhaps because women and men differ in their ability to use cognitive schemes to compensatefor the distracting effects of the global context. Our findings further suggest that whether or not genderdifferences arise depends not only on the nature of the visual task but also on the visual context.



    1. .

      This study found that there are significant sex differences in number line estimation task performance and in confidence judgments about performance. Women/girls are significantly less precise on their number line estimation task performance than men are, and are significantly less confident about performance than men are.

    2. Nevertheless, we conducted linear mixedmodels to statistically test for developmental effects to assess whether the magnitude of genderdifferences in confidence increases (or decreases) with grade and found no evidence ofdevelopmental effects in gender differences in confidence (Appendix 4).
    3. Finally, our analyses included data from participants ranging from early childhood toadulthood, but we chose not to focus on developmental trends in our outcomes of interest.
    4. .

      This study couldn't evaluate sex differences in degree of overconfidence on number-line estimates because judgments must be made on the same scale as performance, and this was not the case for many of the experiments talked about here.

    5. .

      Measures of number line estimation performance were not detailed enough to be able to calculate absolute accuracy (degree of overconfidence) on them, so sex differences in absolute accuracy were not able to be determined.