How talking therapists experience working with adult clients who have autism

This research aims to gain new insight by exploring the thoughts, feelings and experiences of therapists working with clients who have autism. Three professional talking therapists participated in the study. Unstructured interviews were conducted and analysed using interpretive phenomenological analysis. Six main themes and 13 sub-themes were found which include therapists’ validation of autism, how therapists integrated autism when addressing mental health problems, how their personal experiences of autism impacted on their work and how they experienced the situation in which autism emerges during the therapy. Helpful suggestions are made for clinicians, namely, to zoom-in and zoom-out of autism, hold the knowledge that people with autism process information differently, incorporate working with trauma, consider disclosing a personal connection to autism and consider carefully whether, or not, to tell a client that they may have autism.     

The Connection between Perceived Workplace Discrimination and Viewing Work as a Spiritual Calling

Research shows that perceived workplace discrimination shapes an individual's job satisfaction and intent to leave a job. This study considers whether these impacts may be attenuated if an individual views their work as a spiritual calling. Using data from a nationally representative survey (N = 9,907), our analysis shows that perceived work discrimination due to race, gender, and religion are all independently associated with less job satisfaction net of a variety of other measures. Viewing work as a spiritual calling is associated with greater job satisfaction, even when accounting for traditional measures of religiosity. The negative impact of perceived discrimination on job satisfaction is weaker among those who view work as a spiritual calling. These findings provide evidence of the mechanisms underlying job satisfaction and have implications for understanding how religion might help mitigate the negative consequences of perceived discrimination in the workplace, or allow discrimination to potentially go unaddressed.     

Question-Answering for Intelligent On-Line Help: The Process of Intelligent Responding

This article examines the process of specifying a question-answering help facility in the context of UNIX mail. The specification was based upon experimental expert-user facilitative dialogues. These dialogues were analyzed using a classification scheme developed for the purpose. The scheme provides a metalanguage for describing patterns of intent and rhetorical structure in dialogue. Using the scheme as a tool, common patterns in expert-user dialogue emerged, providing insights into both tutoring strategy and the linguistic forms required to generate help output. These were refined to form a set of frames consisting of stereotypical patterns of rhetorical predicates to answer different types of questions which could be adapted to the needs of a particular user. The significance of the system developed from this specification is discussed.     

iTemplate: A template-based eye movement data analysis approach

Current eye movement data analysis methods rely on defining areas of interest (AOIs). Due to the fact that AOIs are created and modified manually, variances in their size, shape, and location are unavoidable. These variances affect not only the consistency of the AOI definitions, but also the validity of the eye movement analyses based on the AOIs. To reduce the variances in AOI creation and modification and achieve a procedure to process eye movement data with high precision and efficiency, we propose a template-based eye movement data analysis method. Using a linear transformation algorithm, this method registers the eye movement data from each individual stimulus to a template. Thus, users only need to create one set of AOIs for the template in order to analyze eye movement data, rather than creating a unique set of AOIs for all individual stimuli. This change greatly reduces the error caused by the variance from manually created AOIs and boosts the efficiency of the data analysis. Furthermore, this method can help researchers prepare eye movement data for some advanced analysis approaches, such as iMap. We have developed software (iTemplate) with a graphic user interface to make this analysis method available to researchers.     

The andrew system: The role of human interface guidelines in the design of multimedia applications

As computer systems are becoming more advanced, the user interface issues involved in system design are increasing in complexity. Multimedia applications add yet another layer of complexity to this already intricate task and guidelines are needed to help ensure consistency, both within a given computer system as well as across systems. The Human Factors Design Group of the Information Technology Center (ITC) at Carnegie Mellon University has developed a set of user interface guidelines for the Andrew system. These guidelines are intended to assist application developers, both within the ITC and externally, in creating application programs whose interfaces are consistent with the look and feel of Andrew. The ITC is a joint venture between IBM and Carnegie Mellon University. This work would not have been possible without the support of these organizations.     

AGSuite: Software to conduct feature analysis of artificial grammar learning performance

To simplify the problem of studying how people learn natural language, researchers use the artificial grammar learning (AGL) task. In this task, participants study letter strings constructed according to the rules of an artificial grammar and subsequently attempt to discriminate grammatical from ungrammatical test strings. Although the data from these experiments are usually analyzed by comparing the mean discrimination performance between experimental conditions, this practice discards information about the individual items and participants that could otherwise help uncover the particular features of strings associated with grammaticality judgments. However, feature analysis is tedious to compute, often complicated, and ill-defined in the literature. Moreover, the data violate the assumption of independence underlying standard linear regression models, leading to Type I error inflation. To solve these problems, we present AGSuite, a free Shiny application for researchers studying AGL. The suite’s intuitive Web-based user interface allows researchers to generate strings from a database of published grammars, compute feature measures (e.g., Levenshtein distance) for each letter string, and conduct a feature analysis on the strings using linear mixed effects (LME) analyses. The LME analysis solves the inflation of Type I errors that afflicts more common methods of repeated measures regression analysis. Finally, the software can generate a number of graphical representations of the data to support an accurate interpretation of results. We hope the ease and availability of these tools will encourage researchers to take full advantage of item-level variance in their datasets in the study of AGL. We moreover discuss the broader applicability of the tools for researchers looking to conduct feature analysis in any field.     

Sidman or statistics?

Murray Sidman's statements regarding variability, experimental control, and generality are interwoven with examples from the literature on conditional discrimination. Sidman's position was that statistical inferences from group studies produce no information about the behavior of individual subjects and that statistical treatment of individual subject data masks variability which may represent conditions that are not controlled. Sidman's work on conditional discrimination provides excellent examples of how complex discriminations should be examined in detail with accuracy levels obtained for each type of discrimination within an experiment. Sidman made important contributions to the foundation of behavior analysis with extensive basic research as well as applications of methods and principles to clinical and educational settings.     

CowLog: Open-source software for coding behaviors from digital video

We have developed CowLog, which is open-source software for recording behaviors from digital video and is easy to use and modify. CowLog tracks the time code from digital video files. The program is suitable for coding any digital video, but the authors have used it in animal research. The program has two main windows: a coding window, which is a graphical user interface used for choosing video files and defining output files that also has buttons for scoring behaviors, and a video window, which displays the video used for coding. The windows can be used in separate displays. The user types the key codes for the predefined behavioral categories, and CowLog transcribes their timing from the video time code to a data file. CowLog comes with an additional feature, an R package called Animal, for elementary analyses of the data files. With the analysis package, the user can calculate the frequencies, bout durations, and total durations of the coded behaviors and produce summary plots from the data.     

Determining Decision Values of Context Awareness in Ubiquitous Computing Environments

Research on context‐aware computing has been focusing on the technology aspect of context acquisition and interpretation of users' surrounding environment or physical context. There is no operational mechanism for integrating context awareness that is driven by user context such as users' ongoing activities and tasks. Although the necessity of integration of sensed context data with users' intent of conduct has been recognized by many researchers, it has never been empirically investigated. Using Analytic Hierarchy Process, we propose an integrated and comprehensive approach that takes into consideration both user and physical context in defining overall context awareness value. The approach is tested using secondary data of user activities in various situations and surrounding environment scenarios. The results suggest several preliminary guidelines for determining representative measures of user and physical context approaches in the design and evaluation of context‐aware systems. Copyright © 2011 John Wiley & Sons, Ltd.     

PSAAL: A LabVIEW 3 program for data acquisition and analysis in psychophysiological experiments

PSAAL (Physiological Signals Acquisition and Analysis in LabVIEW language) is a group of seven programs, written in LabVIEW 3.0 language and specialized for acquisition, analysis, reduction, and display of peripheral and central physiological data. The main characteristics of the programs are the wide range of use for most short-duration psychophysiological paradigms and the easy-to-use graphic interface. In addition, two noteworthy features of LabVIEW are included: the portability of the programs on Macintosh, PowerMac, IBM, HP-UX, and SUN computers, and the capability of handling acquisition on many National Instruments A/D boards, including the low-cost ones. PSAAL performs acquisition and simple reduction of peripheral physiological responses with 12- or 16-bit resolution according to the A/D board used. Analysis includes conversion of electrocardiogram into heart rate, the elaboration of the main parameters of skin conductance responses, electromyogram, startle reflex, and averaging of evoked potentials or other event-related physiological responses, under different experimental conditions. The programs allow the user to perform the organization of the data in a spreadsheet ready for most statistical packages and without the use of other spreadsheet applications.     

Introducing naturalistic cycling data: What factors influence bicyclists’ safety in the real world?

Presently, the collection and analysis of naturalistic data is the most credited method for understanding road user behavior and improving traffic safety. Such methodology was developed for motorized vehicles, such as cars and trucks, and is still largely applied to those vehicles. However, a reasonable question is whether bicycle safety can also benefit from the naturalistic methodology, once collection and analyses are properly ported from motorized vehicles to bicycles. This paper answers this question by showing that instrumented bicycles can also collect analogous naturalistic data. In addition, this paper shows how naturalistic cycling data from 16 bicyclists can be used to estimate risk while cycling. The results show that cycling near an intersection increased the risk of experiencing a critical event by four times, and by twelve times when the intersection presented some form of visual occlusion (e.g., buildings and hedges). Poor maintenance of the road increased the risk tenfold. Furthermore, the risk of experiencing a critical event was twice as large when at least one pedestrian or another bicyclist crossed the bicyclist’s trajectory. Finally, this study suggests the two most common scenarios for bicycle accidents, which result from different situations and thus require different countermeasures. The findings presented in this paper show that bicycle safety can benefit from the naturalistic methodology, which provides data able to guide development and evaluation of (intelligent) countermeasures to increase cycling safety.     

Automated 3-D tracking of video-captured movement using the example of an aquatic mollusk

We describe a computer program that tracks the three-dimensional coordinates of a snail (moving within a tank) from images captured by a single video camera. The tank and a mirror placed at 45° to one side are viewed to provide direct and reflected images of a pond snail,Lymnaea stagnalis, moving around the tank. The output of the camera is captured with an IBM-compatible PC using a frame-grabbing VideoBlaster board. The main features of our Windows program is the frame-by-frame analysis of the captured video, enhancement of contrast, location of dark “snails,” discrimination by size, trigonometric determination of thex, y, z coordinates, and the final export of data in a spreadsheet-ready format. After the user has outlined the position of the tank on the screen and set the discrimination thresholds, no further user activity is required. This makes the analysis of slowly moving mollusks much less operator intensive and less tedious. The method is applicable to other faster moving organisms (e.g., fish) because the analysis is performed on captured video sequences.     

A graphical user interface for infant ERP analysis

Recording of event-related potentials (ERPs) is one of the best-suited technologies for examining brain function in human infants. Yet the existing software packages are not optimized for the unique requirements of analyzing artifact-prone ERP data from infants. We developed a new graphical user interface that enables an efficient implementation of a two-stage approach to the analysis of infant ERPs. In the first stage, video records of infant behavior are synchronized with ERPs at the level of individual trials to reject epochs with noncompliant behavior and other artifacts. In the second stage, the interface calls MATLAB and EEGLAB (Delorme & Makeig, Journal of Neuroscience Methods 134(1):9–21, 2004) functions for further preprocessing of the ERP signal itself (i.e., filtering, artifact removal, interpolation, and rereferencing). Finally, methods are included for data visualization and analysis by using bootstrapped group averages. Analyses of simulated and real EEG data demonstrated that the proposed approach can be effectively used to establish task compliance, remove various types of artifacts, and perform representative visualizations and statistical comparisons of ERPs. The interface is available for download from http://www.uta.fi/med/icl/methods/eeg.html in a format that is widely applicable to ERP studies with special populations and open for further editing by users.     

Marijuana effects on human forgetting functions

It has long been known that acute marijuana administration impairs working memory (e.g., the discrimination of stimuli separated by a delay). The determination of which of the individual components of memory are altered by marijuana is an unresolved problem. Previous human studies did not use test protocols that allowed for the determination of delay-independent (initial discrimination) from delay-dependent (forgetting or retrieval) components of memory. Using methods developed in the experimental analysis of behavior and signal detection theory, we tested the acute effects of smoked marijuana on forgetting functions in 5 humans. Immediately after smoking placebo, a low dose, or a high dose of marijuana (varying in delta9-THC content), subjects completed delayed match-to-sample testing that included a range of retention intervals within each test session (0.5, 4, 12, and 24 s). Performances (discriminability) at each dose were plotted as forgetting functions, as described and developed by White and colleagues (White, 1985; White & Ruske, 2002). For all 5 subjects, both delta9-THC doses impaired delay-dependent discrimination but not delay-independent discrimination. The outcome is consistent with current nonhuman studies examining the role of the cannabinoid system on delayed matching procedures, and the data help illuminate one behavioral mechanism through which marijuana alters memory performance.     

APL functions for interactive data analysis: Principal components analysis

APL functions to support principal components analysis are presented: a general-purpose function to obtain eigen values and eigen vectors, a more specialized function to convert these into the results commonly given by principal components analysis, and a user interface function that accesses filed data, offers flexibility in data selection, and produces labeled output. A brief introduction to the logic and uses of principal components analysis is included. General-purpose support functions to simplify file use and to increase the range of options available to the user are also provided.     

Using synthetic speech for remote access to information

The availability of unlimited text-to-speech synthesis systems provides the potential for remote access to databases over existing telephone systems. This paper describes some of the intelligibility and user interface problems associated with such applications and reports work aimed at understanding and solving these problems. In particular, it describes an approach to intelligibility problems based on the understanding and manipulation of listeners’ adaptation to synthetic speech, and user interface work examining use of a simulated travel information system.     

When your face doesn't fit: employment discrimination against people with facial disfigurements

This study aimed to investigate the recruitment prospects of people with facial disfigurement and a contrasting group of wheelchair users, representing a functional impairment with little aesthetic impact. Three applications were made to each of 144 vacancies using three CVs and cover letters rotated around conditions in which one applicant was described as a wheelchair user, another had a noncontagious facial disfigurement, and the third (control condition) had neither. There was evidence of discrimination against people with facial disfigurement in jobs requiring high (but not low) levels of customer contact, and against wheelchair users for jobs entailing high or low‐customer contact. Aesthetic considerations, social norms, and the possibility of stigma by association are discussed as potential underlying factors.     

Predicting Suicide Intent: The Roles of Experiencing or Committing Violent Acts

According to the interpersonal theory of suicide (Joiner, 2005), repeated exposure to painful or provocative experiences is associated with lethal or nearly lethal suicide attempts. However, suicide research often focuses on suicide ideation or attempts, rather than intent. Using data from the Collaborative Psychiatric Epidemiological Surveys, we examined traumatic experiences, with a focus on repeated exposure to traumas, in individuals who described their suicide attempts as a strong intent to die versus a cry for help. Only repeated acts of committing violence were associated with high suicide intent, suggesting that individuals who engage in violence are at heightened risk for suicide.