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Record W4318537305 · doi:10.2196/40542

Enhancing Therapeutic Processes in Videoconferencing Psychotherapy: Interview Study of Psychologists’ Technological Perspective

2023· article· en· W4318537305 on OpenAlexvenueno aff
Francesco Cataldo, Antonette Mendoza, Shanton Chang, George Buchanan, Nicholas T. Van Dam

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsVideoconferencingTelehealthThematic analysisPsychologyPerspective (graphical)CognitionTherapeutic relationshipPsychotherapistApplied psychologyTelemedicineQualitative researchComputer scienceMultimediaSociologyPsychiatryHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic caused a surge in the use of telehealth platforms. Psychologists have shifted from face-to-face sessions to videoconference sessions. Therefore, essential information that is easily obtainable via in-person sessions may be missing. Consequently, therapeutic work could be compromised. OBJECTIVE: This study aimed to explore the videoconference psychotherapy (VCP) experiences of psychologists around the world. Furthermore, we aimed to identify technological features that may enhance psychologists' therapeutic work through augmented VCP. METHODS: In total, 17 psychologists across the world (n=7, 41% from Australia; n=1, 6% from England; n=5, 29% from Italy; n=1, 6% from Mexico; n=1, 6% from Spain; and n=2, 12% from the United States) were interviewed. We used thematic analysis to examine the data collected from a sample of 17 psychologists. We applied the Chaos Theory to interpret the system dynamics and collected details about the challenges posed by VCP. For collecting further information about the technology and processes involved, we relied on the Input-Process-Output (IPO) model. RESULTS: The analysis resulted in the generation of 9 themes (input themes: psychologists' attitude, trust-reinforcing features, reducing cognitive load, enhancing emotional communication, and engaging features between psychologists and patients; process themes: building and reinforcing trust, decreasing cognitive load, enhancing emotional communication, and increasing psychologist-patient engagement) and 19 subthemes. Psychologists found new strategies to deal with VCP limitations but also reported the need for more technical control to facilitate therapeutic processes. The suggested technologies (eye contact functionality, emergency call functionality, screen control functionality, interactive interface with other apps and software, and zooming in and out functionality) could enhance the presence and dynamic nature of the therapeutic relationship. CONCLUSIONS: Psychologists expressed a desire for enhanced control of VCP sessions. Psychologists reported a decreased sense of control within the therapeutic relationship owing to the influence of the VCP system. Great control of the VCP system could better approximate the critical elements of in-person psychotherapy (eg, observation of body language). To facilitate improved control, psychologists would like technology to implement features such as improved eye contact, better screen control, emergency call functionality, ability to zoom in and out, and an interactive interface to communicate with other apps. These results contribute to the general perception of the computer as an actual part of the VCP process. Thus, the computer plays a key role in the communication, rather than remaining as a technical medium. By adopting the IPO model in the VCP environment (VCP-IPO model), the relationship experience may help psychologists have more control in their VCP sessions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.006
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.240
GPT teacher head0.548
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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