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Record W2394721401 · doi:10.2196/mental.5169

Do Patients Look Up Their Therapists Online? An Exploratory Study Among Patients in Psychotherapy

2016· article· en· W2394721401 on OpenAlexvenueno aff
Christiane Eichenberg, Adam Sawyer

Bibliographic record

VenueJMIR Mental Health · 2016
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsCuriosityThe InternetPsychologyPsychotherapistGermanMental healthPerceptionExploratory researchClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The use of the Internet as a source of health information is growing among people who experience mental health difficulties. The increase in Internet use has led to questions about online information-seeking behaviors, for example, how psychotherapists and patients use the Internet to ascertain information about each other. The notion of psychotherapists seeking information about their patients online (patient-targeted googling, PTG) has been identified and explored. However, the idea of patients searching for information online about their psychotherapists (therapist-targeted googling, TTG) and the associated motives and effects on the therapeutic relationship remain unclear. OBJECTIVE: This study investigated former and current German-speaking psychotherapy patients' behavior and attitudes relating to TTG. In addition, patients' methods of information gathering, motives, and success in searching for information were examined. Furthermore, patients' experiences and perceptions of PTG were explored. METHODS: Overall, 238 former and current psychotherapy patients responded to a new questionnaire specifically designed to assess the frequency, motives, use, and outcomes of TTG as well as experiences and perceptions of PTG. The study sample was a nonrepresentative convenience sample recruited online via several German-speaking therapy platforms and self-help forums. RESULTS: Of the 238 former and current patients who responded, 106 (44.5%) had obtained information about their therapists; most of them (n=85, 80.2%) had used the Internet for this. Besides curiosity, motives behind information searches included the desire to get to know the therapist better by attempting to search for both professional and private information. TTG appeared to be associated with phases of therapy in which patients felt that progress was not being made. Patients being treated for personality disorders appear to engage more frequently in TTG (rphi = 0.21; P=.004). In general, however, information about therapists sought for online was often not found. Furthermore, most patients refrained from telling their therapist about their information searches. CONCLUSIONS: Patients appear to engage in TTG to obtain both professional and private information about their psychotherapists. TTG can be viewed as a form of client-initiated disclosure. It is therefore important to include TTG as a subject in therapists' education and also to raise awareness within patient education. This investigation provides the first findings into TTG to begin debate on this subject.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.047
GPT teacher head0.419
Teacher spread0.371 · 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 designObservational
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

Citations18
Published2016
Admission routes1
Has abstractyes

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