Identifying Mental Disorder from the Faces of Women with Borderline Personality Disorder

Although appearance-based cues can help to diagnose physical illness, visual manifestations of mental disorder may be more elusive. Here, we investigated whether individuals could distinguish women with a serious mental disorder (borderline personality disorder) from demographically- and IQ-matched non-psychiatric controls. Participants rated mentally ill targets as more likely to have a mental disorder from photos more accurately than chance, despite not believing that such judgments were possible. The configuration of facial cues played an important role in these judgments, as interfering with the spatial relationships between facial features reduced participants’ accuracy to chance guessing. Further investigation showed similar results when participants rated the targets for specific mental disorders (borderline personality disorder, major depressive disorder) and rated the mentally ill targets as more depressed, angry, anxious, disgusted, emotionally unstable, distressed, and less happy. Moreover, the depression ratings significantly correlated with the targets’ actual depressive symptoms. Thus, individuals may be able to infer aspects of mental disorder from minimal facial cues.     

Accelerometry analysis of physical activity and sedentary behavior in older adults: a systematic review and data analysis

Accelerometers objectively monitor physical activity and sedentary patterns and are increasingly used in the research setting. It is important to maintain consistency in data analysis and reporting, therefore, we: (1) systematically identified studies using accelerometry (ActiGraph, Pensacola, FL, USA) to measure moderate-to-vigorous physical activity (MVPA) and sedentary time in older adults, and (2) based on the review findings, we used different cut-points obtained to analyze accelerometry data from a sample of community-dwelling older women. We identified 59 articles with cut-points ranging between 574 and 3,250 counts/min for MVPA and 50 and 500 counts/min for sedentary time. Using these cut-points and data from women (mean age, 70 years), the median MVPA minutes per day ranged between 4 and 80 min while percentage of sedentary time per day ranged between 62 % and 86 %. These data highlight (1) the importance of reporting detailed information on the analysis assumptions and (2) that results can differ greatly depending on analysis parameters.     

Looking for homogeneous groups of respondents and nonrespondents using latent class analysis

Concerns about decreasing response rates have led to many nonresponse studies. Unfortunately, usually only a limited amount of data is available on nonrespondents. Linking administrative data makes information available on all the sampled units including nonrespondents. Statistics Netherlands has constructed a database in which several administrative records and several surveys are connected. In this explorative study we use this dataset to look for homogenous groups of respondents and nonrespondents in survey research using latent class cluster analysis. Latent class techniques can provide insight into the problem of selective nonresponse and currently under-represented societal groups. We identify four different latent classes in a recent Dutch survey and replicate the findings for the same survey conducted 4 years later. Two of the types of sampled units have above-average response rates and the other two have below-average response rates. We also evaluate various latent class models with other response outcomes to gain insight into the contact and cooperation process.     

High precision implementation of Steck's recursion method for use in goodness-of-fit tests

Classical continuous goodness-of-fit (GOF) testing is employed for examining whether the data come from an assumed parametric model. In many cases, GOF tests assume a uniform null distribution and examine extreme values of the order statistics of the samples. Many of these statistics can be expressed by a function of the order statistics and the p-values amount to a joint probability statement based on the uniform order statistics. In this paper, we utilize Steck''s recursion method and propose two high precision computing algorithms to compute the p-values for these GOF statistics. The numerical difficulties in implementing Steck''s method are discussed and compared with solutions provided in high precision libraries.     

FEMALE SEX WORK,NON-WORK SEX AND HIV IN PERTH

This study is based on repeated interviews with twelve heterosexual female commercial sex workers (SWs) in Perth. These informants deploy, with various degrees of success, strategies to demarcate ‘work-sex’, with its socially ascribed stigma, from ‘non-work sex’. Such strategies inhibit the spread of HIV at work but, ironically, increase the risk of HIV transmission during non-work sex. SWs recognise this risk and construct a variety of rationales to reduce their fear of contracting HIV and justify their strategies of demarcating work-sex from non-work sex. Efforts to reduce the risk of HIV infection among Perth SWs would seem to depend upon addressing not only these strategies of demarcation but these rationales in a supportive environment that recognises the creative complexities of their lives.