Qualitatively driven mixed‐methods approaches to counselling and psychotherapy research

Many researchers and clinicians take an ‘either, or’ position regarding factors responsible for change when conducting research. Qualitatively driven mixed methods privilege the qualitative approach and offer the opportunity to generate multi‐dimensional material, permitting a more holistic insight into experiences that can be understood from a combination of epistemological and ontological stances. A qualitatively driven mixed‐methods approach apply a ‘both, and’ position when exploring the elements that produce change or that are under investigation, which can be of particular value to counselling and psychotherapy research. There are various ways of engaging with qualitatively driven mixed methods. Some designs include both qualitative and quantitative components, where the former is the core element. The secondary component may also be qualitative, known as a multimethod design. Yet, other designs mix different qualitative approaches, through the application of different qualitative analyses to the same data (pluralistic qualitative research). This paper discusses the application and value of qualitatively driven mixed methods in counselling and psychotherapy research through the presentation of two research case studies; one which mixes both qualitative and quantitative components to investigate the experiences of pain alleviation following a CBT pain management programme; and one which applies a pluralistic approach to a counselling psychology doctorate exploring the experiences and meanings attached to self‐harming. Through illustration and discussion of the case studies’ mixed‐methods approaches, this paper demonstrates that qualitatively driven mixed methods produce a more enhanced and holistic understanding into phenomena, and therefore a more balanced perspective to counselling and psychotherapy research.     

Evidence for Mixed Processes in Normal/Mirror Discrimination of Rotated Letters: A Bayesian Model Comparison Between Single- and Mixed-Distribution Models1

When determining whether a rotated letter is normal or mirrored, an observer mentally rotates the letter to its canonical orientation. To account for patterns of response times (RTs) for the normal/mirror discrimination of rotated letters, previous research formulated a model that postulated a mixture of trials with and without mental rotation. While this model could explain the curvilinear relationship that has been found between averaged RT and letter orientations, the curved RT function is still open to alternative explanations without assuming mixed processes. To address this issue and test the mixed-process hypothesis more directly, we analyzed trial-by-trial RT data instead of averaged RTs by employing a Bayesian model comparison technique. If rotation and non-rotation trials are mixed, trial-by-trial RTs for letters in a particular orientation should not follow a single distribution but a mixed one formed from the superposition of two separate distributions, one for rotation and one for non-rotation trials. In the present study, we compared single- and mixed-distribution models. Bayes-factor analysis showed decisive support for the mixed-distribution model over the single-distribution model. In addition, using the widely applicable information criterion (WAIC), the predictive accuracy of the mixed-distribution model was found to be as high as that of the single-distribution model. These results indicated the involvement of mixed processes in normal/mirror discrimination of rotated letters. The usefulness of statistical modeling in psychological study and necessary precautions to take in the interpretation of the parameters of unconfirmed models are also discussed.     

Utilizing Community Partnerships to Devise a Framework for Cultural Adaptations to Evidence-Based Mental Health Practice in Diverse Communities

Mental health disparities for diverse communities (particularly immigrants and people of color) in terms of access to evidence-based treatments, lack of education/awareness about mental health symptoms and treatment options, and lack of culturally responsive treatments have been frequently documented. Hence, diversity considerations in the diagnosis, assessment, and treatment of psychological disorders remain vital and imperative in clinical practice. There is also substantial work indicating that cultural values likely play an essential role in shaping how individuals conceptualize and experience mental or emotional health. Therefore, the present study was developed for community-engaged clinicians and researchers to outline the process by which to create a culturally responsive, evidence-based treatment framework for community mental health interventions in close partnership with communities of color. This study was conceptualized and designed collaboratively with community leaders across five different communities of color: African American/Black, Latino/a, Native American, Pacific Islander, and African immigrant communities in a major U.S. city. This paper describes the mixed methods for such a community-engaged collaboration, highlighting critical elements for ongoing culturally engaged clinical work/research, and providing recommendations for culturally adapted interventions for mental health based on specific process observations made in the current example.     

Exploring behavioral validity of driving simulator under time pressure driving conditions of professional drivers

Driving simulators have become an important tool in human factors research, given that they are appropriately validated. Therefore, this study aims to explore the behavioral (absolute and relative) validity of a fixed-base driving simulator by analyzing different driving behavior measures such as speed, longitudinal acceleration, lateral acceleration, and brake pedal force. Thirty professional drivers participated in the experiment and the data was collected in real and simulated worlds under No Time Pressure (NTP) and Time Pressure (TP) driving conditions. Initially, comparative analyses were conducted on different driving behavior measures using Wilcoxon-signed rank test to examine absolute validity of the driving simulator. Finally, Generalized Linear Mixed (GLM) models were developed for computing the effective distance between real and simulated worlds by quantifying the parameters and for establishing relative validity. In general, the continuous profiles of driving behavior measures followed similar trends in real and simulated worlds and comparative analyses indicated relative validity of the driving simulator. The GLM models showed significant interaction effect of driving environments (real-world and simulated world) and driving conditions (NTP and TP) where high driving speed, high brake pedal force, and low lateral acceleration were observed in simulated world under TP driving condition than real-world under TP driving condition. Overall, the statistical analyses showed qualitative correspondence (relative validity) of the driving behavior measures in between real and simulated worlds. The findings from the current study showed expediency of the driving simulator and its effectiveness in conducting research on human factors and driver safety.     

Developmental trajectory of intersubjectivity in the second and third year of life: Study of fixed-population and random-individual effects

Colwyn Trevarthen claimed that babies have an intrinsic motivation to communicate and engage with others that he called intersubjectivity. Around the ninth month of life, this motivation changes and passes from person-to-person dyadic (primary intersubjectivity) to triangulate a person–person–object relationship (secondary intersubjectivity). Despite the scientific consensus on this developmental leap, few empirical studies explore the trajectory of this more complex form of intersubjectivity between the second and third year of life. One hundred and fifteen free play sessions from 27 mother–child dyads (13 girls and 14 boys) between 9 and 37 months were filmed and were categorized based on the Level of Intersubjective Attunement Scale. The data were analysed using a linear mixed-effects model. Results show both a population trajectory of the levels of intersubjective attunement and random individual differences. We discuss these results in relation to the binomial typical developmental route and interindividual variability.     

Introducing Emotioncy as a Potential Source of Test Bias: A Mixed Rasch Modeling Study

This article attempts to present emotioncy as a potential source of test bias to inform the analysis of test item performance. Emotioncy is defined as a hierarchy, ranging from exvolvement (auditory, visual, and kinesthetic) to involvement (inner and arch), to emphasize the emotions evoked by the senses. This study hypothesizes that when individuals have high levels of emotioncy for specific words, their test performance may systematically change, resulting in test bias. To this end, 355 individuals were asked to take a 40-item vocabulary test along with the emotioncy scale. Mixed Rasch model was employed to flag differential item functioning items. Results illustrated that the test takers with high emotioncy toward specific words outperformed the ones in the low-emotioncy group, characterizing emotioncy as a potential source of test bias.     

The relationship between alliance ruptures and hope for change through counseling: A mixed methods study

The negative impact of alliance ruptures on clients’ experiences within the therapeutic process is well documented. One such negative influence may include clients’ hope for counseling as a helpful process. This study used a mixed methods design to explore how alliance ruptures are related to hope for change through counseling. Quantitative data (N = 105) indicated that those who experienced ruptures reported lower levels of the components of hope for change through counseling, (a) pathways and agency, and (b) goal identification. More frequent ruptures and rupture repairs were significantly related to participants’ (n = 35) pathways and agency. Phenomenological analysis of qualitative participants’ (N = 5) experiences elicited 218 meaning units grouped into four themes: disengagement and mistrust in therapy, deepened distress, questioning one’s hope for and belief in therapy, and resilience for therapy. Qualitative and quantitative data indicate that alliance ruptures are related to lower degrees of hope for change through counseling. Results suggest that clients’ perceptions of ruptures fostered disengagement and mistrust of therapists. However, when therapists act to repair ruptures, they may effectively re-engage some degree of hope for change through counseling in clients. Lastly, the role of clients’ persistence in therapy despite experiencing ruptures is discussed.     

Analyzing temporal patterns of infant sleep and negative affective behavior: a comparison between different statistical models

Objective

Variability in infant sleep and negative affective behavior (NAB) is a developmental phenomenon that has long been of interest to researchers and clinicians. However, analyses and delineation of such temporal patterns were often limited to basic statistical approaches, which may prevent adequate identification of meaningful variation within these patterns. Modern statistical procedures such as additive models may detect specific patterns of temporal variation in infant behavior more effectively.

Method

Hundred and twenty-one mothers were asked to record different behaviors of their 4–44 weeks old healthy infants by diaries for three days consecutively. Circadian patterns as well as individual trajectories and day-to-day variability of infant sleep and NAB were modeled with generalized linear models (GLMs) including a linear and quadratic polynomial for time, a GLM with a polynomial of the 8th order, a GLM with a harmonic function, a generalized linear mixed model (GLMM) with a polynomial of the 8th order, a generalized additive model, and a generalized additive mixed model (GAMM).

Results

The semi-parametric model GAMM was found to fit the data of infant sleep better than any other parametric model used. GLMM with a polynomial of the 8th order and GAMM modeled temporal patterns of infant NAB equally well, although the GLMM exhibited a slightly better model fit while GAMM was easier to interpret. Besides the well-known evening clustering in infant NAB we found a significant second peak in NAB around midday that was not affected by the constant decline in the amounts of NAB across the 3-day study period.

Conclusion

Using advanced statistical procedures (GAMM and GLMM) even small variations and phenomena in infant behavior can be reliably detected. Future studies investigating variability and temporal patterns in infant variables may benefit from these statistical approaches.