An economical system for collecting and reducing heart-rate data,using someone else’s small computer

Hardware and program are described for a heart-rate data collection and reduction system that uses a small computer at a time removed from the actual data collection. The system is portable and inexpensive; exclusive of the computer, it can cost under $1,500. It uses an ordinary tape recorder to record discrete signals upon each occurrence of a heart beat, and it returns edited second-by-second averages of interheart-beat intervals.     

An MS-DOS-compatible data logger for recording subjects’ self-ratings

Some research designs require subjects to make ratings of their own internal cognitive or affective states or the behavior of other subjects. An ideal device for this purpose should allow for electronic data storage and be easy to use for research subjects. The communication box (Markman & Poltrock, 1982) has been popular for this purpose but consists of dated technology. Other data-logging devices are too complicated for subjects’ use. This paper describes an electronic data logger which uses readily available hardware. A dual-tone multiple-frequency (DTMF) telephone keypad encoder is used to generate unique tones that are stored on the audio track of a videotape or on an audio tape. A DTMF receiver decoder IC is used to decode the audio signals. The decoded signals can be read on a light-emitting diode display or entered directly into a personal computer file via an RS-232 serial interface.     

Clowning—An opportunity for ministry

Experiences over five years interacting with patients as the clown Jingles and the experiment and experience of one afternoon as the clown Hairie in a hospital led the authors to reflect on the deeper meaning of clowns, their appearance during the centuries, their impact on people and relation to ministry. The presence of a clown changes the atmosphere and dynamics; clowns touch people in their deep feelings and may free them to laugh, to cry, or to play. Relating to others in lively ways brings up questions about the connections between the clown and God.     

“Sound” alternatives to visual graphics for exploratory data analysis

Efficient exploratory data analysis (EDA) may be aided by succinct, but informative, graphical representations (e.g., Tukey plots) that convey information about central tendency, variability, and shape of distributions, and that permit detection of outliers. Using research strategies adapted from studies of cross-modal perceptual equivalence, we show how auditory analogies of such displays may offer an effective alternative to visual plots for EDA.     

Association rule learning in neuropsychological data analysis for Alzheimer’s disease

Efficient methods of analysis readily available for clinicians continue to be limited within neuropsychological assessment at the raw data level. Here, a novel approach for generating predictive response patterns and analysing neuropsychological raw data is offered. In order to assess the usefulness of association rule learning as an analysis tool for neuropsychological raw data, Frequent Pattern Growth (FP-Growth) was used to mine patterns from the Consortium to Establish a Registry for Alzheimer’s Disease Neuropsychological Battery (CERAD-NB) database. Complete assessment data for 84 post-mortem confirmed Alzheimer’s disease (AD) cases and 294 age, race, and education matched controls were analysed across baseline and one-year follow-up using FP-Growth, for the purpose of assessing the clinical utility of a finer analysis at the raw data level and the feasibility of predicting response patterns for clinical/control groups. Output from FP-Growth, in terms of the number of frequent itemsets retained across both evaluation timepoints, was discernable between controls, mild, and moderate to severe Alzheimer’s disease cases (p < .001, and η² = .488). Patterns within raw data scores, both in terms of frequent itemsets and predictive association rules, appear to be differentiable across groups within neuropsychological analysis, which indicates that FP-Growth is applicable as a supplementary analysis tool for neuropsychological assessment by means of offering an additional level of data analysis, predictive item response capabilities, and aiding in clinical decision making.     

Robust regression for single-case data analysis: How can it help?

This study examined the degree to which outliers were present in a convenience sample of published single-case research. Using a procedure for analyzing single-case data Allison &; Gorman (Behaviour Research and Therapy, 31, 621–631, 1993), this study compared the effect of outliers using ordinary least squares (OLS) regression to a robust regression method and attempted to answer four questions: (1) To what degree does outlier detection vary from OLS to robust regression? (2) How much do effect sizes differ from OLS to robust regression? (3) Are the differences produced by robust regression in more or less agreement with visual judgments of treatment effectiveness? (4) What is a typical range of effect sizes for robust regression versus OLS regression for data from “effective interventions”? Results suggest that outliers are common in single-case data. The effects of outliers in single-case data are explored, and the implications for researchers and practitioners using single-case designs are discussed.     

When are item response models consistent with observed data?

The problem of deciding whether a set of mental test data is consistent with any one of a large class of item response models is considered. The classical assumption of locla independence is weakened to a new condition, local nonnegative dependence (LND). Necessary and sufficient conditions are derived for a LND item response model to fit a set of data. This leads to a condition that a set of data must satisfy if it is to be representable by any item response model that assumes both local independence and monotone item characteristic curves. An example is given to show that LND is strictly weaker than local independence. Thus rejection of LND models implies rejection of all item response models that assume local independence for a given set of data.This research was supported in part by Grant NIE-G-78-0157 to ETS from the NIE, by the Program Statistics Research Project, and by TOEFL Program Research. I would like to thank Dr. Douglas Jones of ETS for stimulating discussions during the early stages of this research, Dr. Frederick Lord of ETS for his encouragement of this work and comments on earlier drafts of this paper and Professor Robert Berk of Rutgers University for pointing out that conditions (a), (b) and (c) of Theorem 2 were also sufficient for LND and Monotonicity. Dr. Donald Alderman of ETS provided financial support for the development of a computer program to apply these results to data from the TOEFL program.     

An evolutionary hypothesis for obsessive compulsive disorder: a~psychological immune system?

A new hypothesis is presented within the framework of evolutionary psychology that attempts to explain the origins of obsessive-compulsive disorder. It is suggested that obsessions and compulsions originate from the overactivity of a mental module that the majority of humans possess and has the function of generating risk scenarios without voluntary intervention. It is hypothesised that obsessional phenomena function as an off-line risk avoidance process, designed to lead to risk avoidance behaviour at a future time, thus distinguishing it from anxiety and related phenomena as on-line emotional states, designed to lead to the avoidance of immediate and direct risks. Finally, the hypothesis makes a number of specific predictions that are testable and refutable. It is contended that the present hypothesis if supported by empirical evidence could serve as a basis for future research on this important disorder.     

VRS—A programming system for visual electrophysiological research

VRS is a system of separate routines programmed to perform one or more of the functions for mapping neuronal receptive fields and determining neuronal response characteristics. The organization and use of the programming system are described along with the details of the routines.     

A similarity-based range—frequency model for two-category rating data

This research examines whether an extension of range-frequency theory (Parducci, 1965) could successfully predict context effects on discrimination between stimuli for two-category rating data. The new model proposes that similarity comparisons between stimulus values and rating category prototypes take place on an implicit range—frequency scale, and thus it entails effects of context on both mean ratings and discrimination indices. Predictions of the similarity-based range—frequency model were tested in an experiment in which the frequency distribution was manipulated by varying the range and relative frequencies of squares, with participants rating square sizes on a two-category scale. The model provided a parsimonious account of how discriminability of common stimuli increases with a decrease in stimulus range or an increase in the density of stimuli within a subrange.     

A computerized system for recording and analysis of self-observations of couples’ interaction

This paper describes a method for recording couples’ observations of their communications during an ongoing interaction sequence. The procedure allows the recording and decoding of immediate reactions, while maintaining an ecologically valid observation environment. Responses are encoded on a stereo cassette tape player and are decoded by a PDP-11/10 computer with two Schmitt triggers that count the peaks in the tones. The computer provides analysis of the response value and time. Applications for other research problems in the areas of social and applied clinical psychology are discussed.     

A computer program for Spearman-Kärber and probit analysis of psychometric function data

PMETRIC is a computer program for the analysis of observed psychometric functions. It can estimate the parameters of these functions, using either probit analysis (a parametric technique) or the Spearman-Kärber method (a nonparametric one). For probit analysis, either a maximum likelihood or a minimum χ² criterion may be used for parameter estimation. In addition, standard errors of parameter estimates can be estimated via bootstrapping. The program can be used to analyze data obtained from either yes-no orm-alternative forced-choice tasks. To facilitate the use of PMETRIC in simulation work, an associated program, PMETGEN, is provided for the generation of simulated psychometric function data. Use of PMETRIC is illustrated with data from a duration discrimination task.     

A computer program for Spearman-K?rber and probit analysis of psychometric function data.

PMETRIC is a computer program for the analysis of observed psychometric functions. It can estimate the parameters of these functions, using either probit analysis (a parametric technique) or the Spearman-K?rber method (a nonparametric one). For probit analysis, either a maximum likelihood or a minimum chi 2 criterion may be used for parameter estimation. In addition, standard errors of parameter estimates can be estimated via bootstrapping. The program can be used to analyze data obtained from either yes-no or m-alternative forced-choice tasks. To facilitate the use of PMETRIC in simulation work, an associated program, PMETGEN, is provided for the generation of simulated psychometric function data. Use of PMETRIC is illustrated with data from a duration discrimination task.     

Do cyclists need HMIs in future automated traffic? An interview study

Cyclists are expected to interact with automated vehicles (AVs) in future traffic, yet we know little about the nature of this interaction and the safety implications of AVs on cyclists. On-bike human–machine interfaces (HMIs) and connecting cyclists to AVs and the road infrastructure may have the potential to enhance the safety of cyclists. This study aimed to identify cyclists’ needs in today’s and future traffic, and explore on-bike HMI functionality and the implications of equipping cyclists with devices to communicate with AVs. Semi-structured interviews were conducted with 15 cyclists in Norway and 15 cyclists in the Netherlands. Thematic analysis was used to identify and contextualise the factors of cyclist-AV interaction and on-bike HMIs. From the analysis, seven themes were identified: Interaction, Bicycles, Culture, Infrastructure, Legislation, AVs, and HMI. These themes are diverse and overlap with factors grouped in sub-themes. The results indicated that the cyclists prefer segregated future infrastructure, and in mixed urban traffic, they need confirmation of detection by AVs. External on-vehicle or on-bike HMIs might be solutions to fulfil the cyclists’ need for recognition. However, the analysis suggested that cyclists are hesitant about being equipped with devices to communicate with AVs: Responsibility for safety should lie with AV technology rather than with cyclists. A device requirement might become a barrier to cycling, as bicycles are traditionally cheap and simple, and additional costs might deter people from choosing cycling as a transport mode. Future studies should investigate user acceptance of on-bike HMIs among cyclists on a larger scale to test the findings’ generalisability, and explore other, perhaps more viable solutions than on-bike HMIs for enhancing AV-cyclist interaction.     

Iterative inverse factor analysis—A rapid method for clustering persons

By interchanging persons and items, iterative inverse factor analysis provides a relatively inexpensive way of clustering persons according to their patterns of response to the items. In addition to permitting the clustering of large numbers of persons, the technique enables one to determine the bases for such clustering. The items of behavior used can be heterogeneous in content and form.     

Commentaries on “Beyond statistical significance: Five principles for the new era of data analysis and reporting”

Three commentaries below provide different perspectives on data analysis and reporting. They generally focus on how the quality of the measures and manipulations determines the value of the analysis. Norbert Schwarz and Fritz Strack's comment is less on the right statistic and more on “sloppy reasoning, gaps between theoretical concepts and their operationalizations, and blissful ignorance of the situated nature of human thinking, feeling, and doing contribute more to the limited reproducibility of empirical findings than the choice of a particular test statistic.” They propose that particular effects are contextual and inappropriately labeled as true or false. Instead, our job is to focus on general constructs that make sense of the diversity of human experience and psychological reactions. Too often studies replicating psychological effects in the noisy and confounded conditions of the marketplace result in statistical uncertainty of garbage in, garbage out. Researchers instead need to look toward tests of specific interactions, which can clarify the influencing factors based on theoretical considerations. The second comment is by Andrew Gelman, an outstanding psychological statistician. He proposes that “once the data have been collected, the most important decisions have already been done.” He then provides four recommendations that enable the statistics to work appropriately. The first requirement of an effective study is to be sure that the measures address the construct of interest. Similar to the position of Schwarz and Strack, it is important to articulate the relevance of a statistically significant finding. The second recommendation seeks to curb large number of studies with inflated effect sizes built from narrow studies and unwarranted optimism. The third recommendation is to simulate data from a model and consider the distribution of possible results. That is often done to test a new analysis method, but it can be even more important in marketplace studies where novel characteristics of the sample and experimental conditions are included in the analysis. Finally, he recommends that one consider likely analyses needed before getting the data. Such foresight would encourage, for example, thinking about the kind of data needed to defend the equality of the control demographics against the treatment. The final commentary is by Stijn van Osselaer. He agrees that p-values reflect the detailed methods from a given study but do not focus on the problem of generalizability. Like Gelman, he sees designs focused on effect sizes may have generated too many studies that do not replicate. He contrasts broad explorations with narrowly defined existence tests that provide evidence that an effect exists somewhere but are mute on other contexts where they may apply. For theoretical problems relevant to applications, it is important to identify moderators through broad sampling across population characteristics, stimuli, and situations. He proposes that consumer psychologists should not try to do everything in one paper, but to build practically relevant, applicable knowledge across multiple articles. Different articles, authors, and research methods play various roles, with each article focusing on important stages in the process from generating hypotheses, providing existence proofs, and exploring their broad applicability. That pragmatic approach can integrate theoretical silos that seek to resolve complex human problems and has promise as a criterion for relevant publications.     

Men’s strategies for preserving emotional well-being in advanced prostate cancer: An interpretative phenomenological analysis

Objective: This study explores men with advanced prostate cancers’ own practices for promoting and maintaining emotional well-being using Interpretative Phenomenological Analysis.

Design: Five men with advanced prostate cancer participated in face-to-face, semi-structured, in-depth interviews.

Results: Within rich narratives of lost and regained well-being, two super-ordinate themes emerged – ‘living with an imminent and uncertain death’ and ‘holding on to life.’ Well-being was threatened by reduced sense of the future, isolation and uncertainty. Yet, the men pursued well-being by managing their emotions, striving for the future whilst enjoying life in the present, taking care of their families and renegotiating purpose. Running through participant’s accounts was a preference for taking action and problem-solving. Sense of purpose, social connectedness, and life engagement were revealed as concepts central to improving well-being, indicating areas which practitioners could explore with men to help them re-establish personal goals and life purpose.

Conclusions: The findings also add weight to the evidence base for the potential value of psychological interventions such as cognitive behaviour therapy and mindfulness in men with prostate cancer.     

Can independence be observed in a dependent system? The case of tip-of-the-tongue states.

Caramazza and Miozzo (1997) found that speakers experiencing tip-of-the-tongue states are able to report phonological information independently from syntactic information. They used this finding to reject sequential models of production, in which syntactic units (lemmas) are retrieved before form units (lexemes). To see whether this conclusion is warranted, we performed two simulation experiments based on sequential architectures. Both models we simulated produced statistically uncorrelated syntax and phonology despite sequentially retrieving lemmas and lexemes. Finally, we analyzed a corpus of Spanish errors, finding syntactic constraints on phonological word substitution errors that are not easily explained without sequentiality.