VideoNoter: A productivity tool for video data analysis

The software described in this paper, VideoNoter, addresses the need for tools that support annotation and retrieval of video data and organize the presentation of multiple analyses of the same data. Video is widely perceived as an important medium for psychological research, because video recording makes the fleeting particulars of human interaction available as data for detailed analysis, while retaining much of the context of the event. Though the benefits of using video data are high, the process can be prohibitively time-consuming. We have developed a prototype computer-based video analysis tool that can enhance the productivity of the video analysis process. In this paper, we report on the design and implementation of VideoNoter, and we discuss how it facilitates video data analysis.     

C-quence: A tool for analyzing qualitative sequential data

C-quence is a software application that matches sequential patterns of qualitative data specified by the user and calculates the rate of occurrence of these patterns in a data set. Although it was designed to facilitate analyses of face-to-face interaction, it is applicable to any data set involving categorical data and sequential information. C-quence queries are constructed using a graphical user interface. The program does not limit the complexity of the sequential patterns specified by the user.     

Validation of the Cycling Behavior Questionnaire: A tool for measuring cyclists' road behaviors

IntroductionEven though cycling is an activity whose benefits in terms of urban mobility and health are globally recognized, its disproportional growth during the past few decades has led to some unexpected dynamics. In fact, the increasing number of traffic injuries and deaths involving cyclists has a high cost for public health systems. Considering the available empirical evidence, aberrant and positive behaviors on the road constitute relevant predictors for the injuries suffered by road users. Nevertheless, the scarcity of tools that measure and evaluate the behavior of road users, especially in the case of cyclists, constitutes a serious lack in terms of explaining, intervening and preventing traffic crashes through behavioral approaches.ObjectiveThis study had two essential purposes: first, to describe in detail the validation of measurement of risky and positive road user behaviors of cyclists using the Cycling Behavior Questionnaire. Second, to compare the mean scores of the validated version of the CBQ according to demographic and cycling-related factors.MethodAs a part of a larger collaborative research project, our data was collected from 1064 Spanish-speaking cyclists (between 17 and 80 years old) from 20 countries, who filled out an anonymous electronic survey on their riding behaviors. The data was analyzed using competitive Confirmatory Factor Analyses (CFA), thus obtaining basic psychometric values and an optimized structure for the scale.ResultsThe obtained results suggest that the CBQ has a clear factorial structure, items with high factorial weight, and good internal consistency. In particular, the results of the latent variable model with three factors, which were labeled errors, violations and positive behaviors, show that the CBQ is satisfactorily adjusted.ConclusionThe findings of this research support the idea that the CBQ may have important applications in the improvement of road safety through the study of cyclists' behavioral factors and their relationship to demographic and cycling-related factors.     

The Observer: A software system for collection and analysis of observational data

The Observer is a general-purpose software package for event recording and data analysis in behavioral research. It allows any IBM-type personal computer to serve as an event recorder. In addition, The Observer can generate dedicated event-recording programs for several types of non-IBM-compatible portable and hand-held computers and transfer files between the PC and such computers. The user specifies options through menus. The configuration can be either used directly for event recording on the PC or passed on to a program generator that creates a program to collect data on a hand-held computer. Observational data from either type of computer can be analyzed by the program. Event-recording configurations can be tailored to many different experimental designs. Keys can be designated as events, and modifiers can be used to indicate the limits of an event. The program allows grouping of events in classes and distinction between mutually exclusive versus nonexclusive events and duration events versus frequency events. Timing of events is accurate to 0.1 sec. An on-line electronic notepad permits notes to be made during an observation session. The program also includes on-line error correction. User comments as well as independent variables can be stored together with the observational data. During data analysis, the user can select the level of analysis and the type of output file. The Observer calculates frequency of occurrence and duration for classes of events, individual events, or combinations of events. For analysis of concurrence, one can select the number of nesting levels and the order of nesting. Output can be generated in the form of sorted event sequence files, text report files, and tabular ASCII files. The results can be exported to spreadsheet and statistical programs.     

EthoSeq: A tool for phylogenetic analysis and data mining in behavioral sequences

This article introduces the software program called EthoSeq, which is designed to extract probabilistic behavioral sequences (tree-generated sequences, or TGSs) from observational data and to prepare a TGS-species matrix for phylogenetic analysis. The program uses Graph Theory algorithms to automatically detect behavioral patterns within the observational sessions. It includes filtering tools to adjust the search procedure to user-specified statistical needs. Preliminary analyses of data sets, such as grooming sequences in birds and foraging tactics in spiders, uncover a large number of TGSs which together yield single phylogenetic trees. An example of the use of the program is our analysis of felid grooming sequences, in which we have obtained 1,386 felid grooming TGSs for seven species, resulting in a single phylogeny. These results show that behavior is definitely useful in phylogenetic analysis. EthoSeq simplifies and automates such analyses, uncovers much of the hidden patterns of long behavioral sequences, and prepares this data for further analysis with standard phylogenetic programs. We hope it will encourage many empirical studies on the evolution of behavior.     

The Chemnitz LogAnalyzer: A tool for analyzing data from hypertext navigation research

Computer-based studies usually produce log files as raw data. These data cannot be analyzed adequately with conventional statistical software. The Chemnitz LogAnalyzer provides tools for quick and comfortable visualization and analyses of hypertext navigation behavior by individual users and for aggregated data. In addition, it supports analogous analyses of questionnaire data and reanalysis with respect to several predefined orders of nodes of the same hypertext. As an illustration of how to use the Chemnitz LogAnalyzer, we give an account of one study on learning with hypertext. Participants either searched for specific details or read a hypertext document to familiarize themselves with its content. The tool helped identify navigation strategies affected by these two processing goals and provided comparisons, for example, of processing times and visited sites. Altogether, the Chemnitz LogAnalyzer fills the gap between log files as raw data of Web-based studies and conventional statistical software.     

Pure orientation filtering: A scale-invariant image-processing tool for perception research and data compression

A method is described for scale-invariant segregation of image structure solely on the basis of orientation content. This kind of image decomposition is an unexplored image-processing method that is complementary to the well-explored method of filtering in spatial frequency bands; the latter technique is rotation-invariant, whereas the former technique is scale-invariant. The complementarity of these two approaches is explicit in the fact that orientation and spatial frequency are orthogonal variables in the two-dimensional Fourier plane, and the filters employed in the one method depend only on the radial variable, whereas those employed in the other method depend only on the angular variable. The biological significance of multiscale (spatial frequency selective) image analysis has been well-recognized and often cited, yet orientation selectivity is a far more striking property of neural architecture in cortical visual areas. In the present paper, we begin to explore some coding properties of the scale-invariant orientation variable, paying particular attention to its perceptual significance in texture segmentation and compact image coding. Examples of orientation-coded pictures are presented with data compression to 0.3 bits per pixel.     

SCRIPTKELL: A tool for measuring cognitive effort and time processing in writing and other complex cognitive activities

We present SCRIPTKELL, a computer-assisted experimental tool that makes it possible to measure the time and cognitive effort allocated to the subprocesses of writing and other cognitive activities. SCRIPTKELL was designed to easily use and modulate Kellogg’s (1986) triple-task procedure, which consists of a combination of three tasks: a writing task (or another task), a reaction time task (auditory signal detection), and a directed retrospection task (after each signal detection during writing). We demonstrate how this tool can be used to address several novel empirical and theoretical issues. In sum, SCRIPTKELL should facilitate the flexible realization of experimental designs and the investigation of critical issues concerning the functional characteristics of complex cognitive activities.     

A Biased Inferential Naivety learning model for a network of agents

We propose a Biased Inferential Naivety social learning model. In this model, a group of agents tries to determine the true state of the world and make the best possible decisions. The agents have limited computational abilities. They receive noisy private signals about the true state and observe the history of their neighbors' decisions. The proposed model is rooted in the Bayesian method but avoids the complexity of fully Bayesian inference. In our model, the role of knowledge obtained from social observations is separated from the knowledge obtained from private observations. Therefore, the Bayesian inferences on social observations are approximated using inferential naivety assumption, while purely Bayesian inferences are made on private observations. The reduction of herd behavior is another innovation of the proposed model. This advantage is achieved by reducing the effect of social observations on agents' beliefs over time. Therefore, all the agents learn the truth, and the correct consensus is achieved effectively. In this model, using two cognitive biases, there is heterogeneity in agents' behaviors. Therefore, the growth of beliefs and the learning speed can be improved in different situations. Several Monte Carlo simulations confirm the features of the proposed model. The conditions under which the proposed model leads to asymptotic learning are proved.     

DynAOI: A tool for matching eye-movement data with dynamic areas of interest in animations and movies

Analyzing gaze behavior with dynamic stimulus material is of growing importance in experimental psychology; however, there is still a lack of efficient analysis tools that are able to handle dynamically changing areas of interest. In this article, we present DynAOI, an open-source tool that allows for the definition of dynamic areas of interest. It works automatically with animations that are based on virtual three-dimensional models. When one is working with videos of real-world scenes, a three-dimensional model of the relevant content needs to be created first. The recorded eye-movement data are matched with the static and dynamic objects in the model underlying the video content, thus creating static and dynamic areas of interest. A validation study asking participants to track particular objects demonstrated that DynAOI is an efficient tool for handling dynamic areas of interest.     

Epidemiological considerations in transgender health: A systematic review with focus on higher quality data

Abstract

Background: High quality data pertaining to the size of the transgender and gender diverse (TGD) population are scant, however, several recently published studies may provide more reliable contemporary estimates.

Aims: To summarize the estimated number and proportion of TGD individuals overall and across age groups, based on most accurate data.

Methods: This systematic review focused on recent studies (published from 2009 through 2019) that utilized sound methodology in assessing the proportion of TGD people in the general population. Publications were included if they used clear definitions of TGD status, and calculated proportions based on a well-defined sampling frame. Nineteen eligible publications represented two broad categories of studies: those that used data from large health care systems; and those that identified TGD individuals from population surveys.

Results: Among health system-based studies, TGD persons were identified using relevant diagnostic codes or clinical notes. The proportions of individuals with a TGD-relevant diagnosis or other recorded evidence ranged between 17 and 33 per 100,000 enrollees. In population surveys TGD status was ascertained based on self-report with either narrow or broad definitions. The survey-based estimates were orders of magnitude higher and consistent across studies using similar definitions. When the surveys specifically inquired about ‘transgender’ identity, the estimates ranged from 0.3% to 0.5% among adults, and from 1.2% to 2.7% among children and adolescents. When the definition was expanded to include broader manifestations of ‘gender diversity’, the corresponding proportions increased to 0.5-4.5% among adults and 2.5-8.4% among children and adolescents. Upward temporal trends in the proportion of TGD people were consistently observed.

Conclusions: Current data indicate that people who self-identify as TGD represent a sizable and increasing proportion of the general population. This proportion may differ, depending on inclusion criteria, age, and geographic location, but well-conducted studies of similar type and design tend to produce comparable results.     

A Brief Online Video-Based Intervention to Promote Mental Health Help-Seeking in the Context of Injuries for Athletes: A pilot study

In the athletic population, sports injuries are often associated with mental health decline. Despite the availability of services, athletes frequently do not seek help for mental health problems. A range of barriers to help-seeking in athletes have been proposed, including poor mental health literacy and limited help-seeking knowledge. To address this, the current study piloted a newly designed online intervention that aimed to increase help-seeking attitudes, intentions, and mental health literacy (specifically depression literacy) in an athletic population. Using a pre-test post-test design, a total of 207 athletes were recruited using online convenience sampling from across Australia. Athletes were from a range of sports and competition levels and were provided a brief online intervention comprising three short educational videos with content addressing: (1) the athlete’s response to injury; (2) help-seeking and social support; and (3) signs/symptoms of depression. Participants completed pre- and post-intervention surveys which measured attitudes and intentions towards mental health help-seeking, and depression literacy. Data were analysed using RM-MANOVA, which demonstrated significant within-group improvement from pre-to post-intervention for help-seeking intentions, particularly when seeking help from mental health professionals, F(1, 93) = 24.64, p < .001, and online/phone services, F(1, 93) = 29.75, p < .001. Two separate paired samples t-test demonstrated a significant increase from pre-to post-intervention for both help-seeking attitudes, t(206) = 9.04, p < .001, d = 0.628, and depression literacy, t(203) = 8.66, p < .001, d = 0.606. The current study shows promise for brief video-based interventions that provide information targeting help-seeking during times of injury. However, further research using a rigorous randomised controlled trial design is needed. Additionally, more work is required to explore if an improvement in attitudes or intentions corresponds with increased help-seeking behaviour.     

Intentional memory and online data collection: A test of the effects of animacy and threat on episodic memory

As research in the behavioural sciences increasingly relies on Amazon’s Mechanical Turk (MTurk) for recruiting participants, it is an empirical question whether an intentional memory experiment could be conducted online and whether performance of MTurk participants and college students would be comparable. College students and MTurk participants viewed threatening and nonthreatening items that were animate or inanimate and completed a recall test. Recent research indicates that human memory systems evolved to prioritise survival-relevant information, including animacy of items. The results of both studies indicated that participants recalled more animate than inanimate items and recalled more threatening items than nonthreatening items. The results indicate that it is possible to conduct memory experiments online and that results match patterns found in laboratory studies of the animacy effect (Nairne, VanArsdall, Pandeirada, Cogdill, & LeBreton, 2013), but that researchers should include safeguards to ensure the online participants are attending to and following directions.     

The Yale Children''s Inventory—A screening tool for attention deficits and related disorders. Normative data for boys

Norwegian populated-based normative data on the Yale Children's Inventory (YCI) were provided for boys. All parents of boys aged 8 through 11 years in the county of Hammerfest received the YCI, and 77% responded. Mean scores on the YCI scales attention, activity, tractability, and fine motor were significantly lower in the Norwegian sample compared to the US normative data. Factor analysis of the 40 scale items yielded factors that corresponded generally well to the YCI scale constructs derived from US samples. We conclude that the scale constructs of the YCI seem to be transferable across these two cultures, but that restandardization is warranted. Further research is needed to establish cut-off values for clinical screening purposes. The Yale Children's Inventory has the potential to become a valuable screening tool for behavioral problems at school-age.     

A method of optimal scaling for multivariate ordinal data and its extensions

This paper develops a method of optimal scaling for multivariate ordinal data, in the framework of a generalized principal component analysis. This method yields a multidimensional configuration of items, a unidimensional scale of category weights for each item and, optionally, a multidimensional configuration of subjects. The computation is performed by alternately solving an eigenvalue problem and executing a quasi-Newton projection method. The algorithm is extended for analysis of data with mixed measurement levels or for analysis with a combined weighting of items. Numerical examples and simulations are provided. The algorithm is discussed and compared with some related methods.Earlier results of this research appeared in Saito and Otsu (1983). The authors would like to acknowledge the helpful comments and encouragement of the editor.     

Psychometric properties and standardised data for questionnaires measuring negative affect, dispositional style and daily hassles. A nation-wide sample

Within the behavioral field, self-report inventories measuring emotional condition from a state/trait perspective are in frequent use. Some of these measures have insufficient standardisation and/or are out of date. In order to upgrade some of the frequently used self-report inventories a nation-wide survey ( N =2500) was performed. Measures of negative affect (state-anxiety STAI-S , trait-anger STAS-T ), and depression ( CES-D ), dispositional style ( LOT ) and daily hassles ( DH ) were examined. Psychometric data and demographic differences for all the inventories used are presented. The reliability measures for the scales show high consistency, ranging from 0.76 to 0.95 (Cronbach's alpha). The overall results indicate that females are more hassled, depressed, anxious, hostile, and have a more negative dispositional style than males. These results are most pronounced among younger females.     

The double-alternative, double-start experimental apparatus: A new procedure for measuring preference

A new experimental chamber is described that permits rats to demonstrate behavioral preference for one of two conditions by running towards a goal chamber by one of two routes that are correlated with the different conditions. In a preliminary study, rats chose a route correlated with relatively lower shock, demonstrating the sensitivity of the apparatus. We also report evidence using this device that, of 10 rats tested, all preferred unsignaled rather than signaled, inescapable, unavoidable shock.     

Evaluating sources of baseline data using dual-criteria and conservative dual-criteria methods: A quantitative analysis

Scheithauer et al. (2020) recently demonstrated that differences in the source of baseline data extracted from a functional analysis (FA) may not affect subsequent clinical decision-making in comparison to a standard baseline. These outcomes warrant additional quantitative examination, as correspondence of visual analysis has sometimes been reported to be unreliable. In the current study, we quantified the occurrence of false positives within a dataset of FA and baseline data using the dual-criteria (DC) and conservative dual-criteria (CDC) methods. Results of this quantitative analysis suggest that false positives were more likely when using FA data (rather than original baseline data) as the initial treatment baseline. However, both sources of baseline data may have acceptably low levels of false positives for practical use. Overall, the findings provide preliminary quantitative support for the conclusion that determinations of effective treatment may be easily obtained using different sources of baseline data.