ArticleJournal of clinical psychology in medical settings2022
The Formation Mechanism of Trust in Patient from Healthcare Professional's Perspective: A Conditional Process Model.
Article in Journal of clinical psychology in medical settings, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Deprescribing decisions in palliative care: a qualitative meta-synthesis of multi-stakeholder experiences and influencing factors.BMC palliative care · 2026Pooled it
- Divergent dynamics of nurse-patient trust during COVID-19 in China: the mediating effects of medical expectations and communication skills.BMC nursing · 2025Article
- A cross-sectional study examining the role of doctors' trust in patients' requests for antibiotics: a neglected perspective.Archives of public health = Archives belges de sante publique · 2025Article
- Development of a measurement of doctor-patient communication quality scale.Frontiers in public health · 2025Article
- Reduction of surgical-site infections and improvement of scar parameters with a uniform fractional ultra-pulse CO₂ laser protocol in cosmetic surgery: a five-center retrospective cohort.Frontiers in medicine · 2025Article
- Research on collaborative development mechanism of multiple stakeholders in medical institutions based on rough set.BMC public health · 2024Article
- Association among Doctor-Patient Communication, Trust, and Patients' Negative Stereotypes for Healthcare Professionals during COVID-19: A Cross-Sectional Study.Journal of nursing management · 2023Article
- Patient satisfaction impact indicators from a psychosocial perspective.Frontiers in public health · 2023Article
- Explicating the Cognitive Process of a Physician's Trust in Patients: A Moderated Mediation Model.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Based on an integrated model of doctor-patient psychological mechanisms, the formation mechanism of doctor--patient trust was systematically demonstrated from the healthcare professional (HCP)'s perspective integrating intergroup relations (expectations), interpersonal relations (communication), and psychosocial (stereotypes). The results of a survey of 3000 doctors and nurses from 14 provinces in eastern, central, and western China support the rationality of an integrated model of doctor-patient psychological mechanisms. The establishment of doctor-patient trust is influenced by the direct role of primary intergroup factors, the indirect role of immediate interpersonal interactions, and the moderating role of social psychology. Specifically, (1) doctor-patient trust is directly predicted by HCP's expectation and indirectly influenced by communication; (2) stereotypes regulate the relationship between HCP's expectation, communication, and doctor-patient trust: the activation of positive stereotypes enhances the positive relationship among the three; Negative stereotypes only positively contribute to mediated pathway-communication behaviors and have a weaker facilitation effect compared to positive stereotypes.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.