Social Norms and the Physician-Patient Relationship

Last registered on June 11, 2025

Pre-Trial

Trial Information

General Information

Title
Social Norms and the Physician-Patient Relationship
RCT ID
AEARCTR-0015964
Initial registration date
June 03, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 11, 2025, 6:39 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Region

Primary Investigator

Affiliation
UMIT TIROL - Private University for Health Sciences and Health Technology

Other Primary Investigator(s)

PI Affiliation
University of Hamburg

Additional Trial Information

Status
Completed
Start date
2025-06-03
End date
2025-06-11
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
An important aspect of healthcare use and outcomes lies in the quality of the physician-patient relationship with better perceived quality leading to better outcomes (Deniz et al., 2021; Kelley et al., 2014; Olaisen et al., 2020; Samuel et al., 2020). There is a growing body of research suggesting a more active involvement of patients in medical decision-making, such as shared decision-making to improve the quality of physician-patient interactions (Deniz et al., 2021). Though patients report preferences to be involved in medical decision-making (Chewning et al., 2012), and research highlights the variability of these preferences across individual-specific factors (Say et al., 2006), it remains unclear how the general population is actually involved in medical decision-making and how the actual role and the preferences of this role in physician-patient relationships is influenced by social factors.
For instance, social norms surrounding the physician-patient relationship – such as expectations about how the physician-patient relationship ought to be (injunctive norm) and is perceived to be (descriptive norm) in society – may shape these preferences (Reid et al., 2010) and may either facilitate or hinder the active participation and involvement in medical decision-making by influencing how patients perceive their role in healthcare decisions and how physicians navigate their professional responsibilities and authority (Brabers et al., 2016). Given the challenges in directly observing physician-patient interactions across the population, these social norms may often be subject to significant misperception (Bursztyn & Yang, 2022).
The underlying study aims to gain a deeper understanding of how social norms shape the dynamics of the physician-patient relationship by investigating (i) the perception about the descriptive and injunctive norms regarding the physician-patient relationship, (ii) the actual norms regarding the role of patients in medical encounters, (iii) the preferences regarding this role and (iv) how the actual norms may affect these preferences among the general population.

References
Brabers, A. E., van Dijk, L., Groenewegen, P. P., & de Jong, J. D. (2016). Do social norms play a role in explaining involvement in medical decision-making? Eur J Public Health, 26(6), 901-905. https://doi.org/10.1093/eurpub/ckw069
Bursztyn, L., & Yang, D. Y. (2022). Misperceptions About Others. Annual Review of Economics, 14(1), null. https://doi.org/https://doi.org/10.1146/annurev-economics-051520-023322
Chewning, B., Bylund, C. L., Shah, B., Arora, N. K., Gueguen, J. A., & Makoul, G. (2012). Patient preferences for shared decisions: A systematic review. Patient education and counseling, 86(1), 9-18. https://doi.org/https://doi.org/10.1016/j.pec.2011.02.004
Deniz, S., Akbolat, M., Çimen, M., & Ünal, Ö. (2021). The Mediating Role of Shared Decision-Making in the Effect of the Patient-Physician Relationship on Compliance With Treatment. J Patient Exp, 8, 23743735211018066. https://doi.org/10.1177/23743735211018066
Kelley, J. M., Kraft-Todd, G., Schapira, L., Kossowsky, J., & Riess, H. (2014). The Influence of the Patient-Clinician Relationship on Healthcare Outcomes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. PLoS ONE, 9(4), e94207. https://doi.org/10.1371/journal.pone.0094207
Olaisen, R. H., Schluchter, M. D., Flocke, S. A., Smyth, K. A., Koroukian, S. M., & Stange, K. C. (2020). Assessing the Longitudinal Impact of Physician-Patient Relationship on Functional Health. Ann Fam Med, 18(5), 422-429. https://doi.org/10.1370/afm.2554
Reid, A., Cialdini, R., & Aiken, L. (2010). Social Norms and Health Behavior. In (pp. 263-274). https://doi.org/10.1007/978-0-387-09488-5_19
Samuel, C. A., Mbah, O., Schaal, J., Eng, E., Black, K. Z., Baker, S., . . . Cykert, S. (2020). The role of patient-physician relationship on health-related quality of life and pain in cancer patients. Support Care Cancer, 28(6), 2615-2626. https://doi.org/10.1007/s00520-019-05070-y
Say, R., Murtagh, M., & Thomson, R. (2006). Patients’ preference for involvement in medical decision making: A narrative review. Patient education and counseling, 60(2), 102-114. https://doi.org/https://doi.org/10.1016/j.pec.2005.02.003

External Link(s)

Registration Citation

Citation
Angerer, Silvia and Johanna Kokot. 2025. "Social Norms and the Physician-Patient Relationship." AEA RCT Registry. June 11. https://doi.org/10.1257/rct.15964-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Information about the distribution of patient involvement in the physician-patient relationship (measured in a first wave of data collection, see AEARCTR-0015749) is provided.
Intervention (Hidden)
Information about the distribution of patient involvement in the physician-patient relationship measured in 5 categories in a first wave of data collection (see AEARCTR-0015749) is provided. The five categories contain two categories for an active role, one category describing shared-decision making and two categories representing a passive role in the physician-patient relationship. The five categories are represented in a bar chart along a verbal description.
Intervention Start Date
2025-06-03
Intervention End Date
2025-06-11

Primary Outcomes

Primary Outcomes (end points)
Preferences for patient involvement using the Control Preference Scale (CPS).
Primary Outcomes (explanation)
The scale assesses preferences by asking respondents to choose one of five options, ranging from an active patient role (otions 1/2), through shared decision-making (option 3), to a passive patient role (options 4/5).

The outcome is treated as a categorical variable with three categories, as an indicator variable and as an continuous variable. The indicator is treated as passive role (1) vs. not. The categorical variable is coded as: (1) active role, (2) shard decision-making , (3) passive role. And the continuous variable uses the answers with the five orderings from active (1) to passive (5).

Secondary Outcomes

Secondary Outcomes (end points)
Expectations about physicians’ preferences regarding patient involvement.
Secondary Outcomes (explanation)
The scale assesses expectations by asking respondents to choose one of five options, ranging from an active patient role (otions 1/2), through shared decision-making (option 3), to a passive patient role (options 4/5).

The outcome is treated as a categorical variable with three categories, as an indicator variable and as an continuous variable. The indicator is treated as passive role (1) vs. not. The categorical variable is coded as: (1) active role, (2) shard decision-making , (3) passive role. And the continuous variable uses the answers with the five orderings from active (1) to passive (5).

Experimental Design

Experimental Design
To investigate the research questions an online survey experiment is conducted. It comprises random assignment of people from the general population aged 18 to 75 years in Austria to one of three experimental groups in a 3:3:1 ratio: (i) Control, (ii) Social Norm Info (and (iii) Control 0) . The sample is (online) representative of the general population with respect to age, gender, education and federal state. The survey is administered by the company "Bilendi" which has access to an online representative sample of the Austrian population.
Experimental Design Details
To investigate the research questions an online survey experiment comprising two waves of data collection is conducted.

Wave 1
In the first wave (AEARCTR-0015749), the perception of social norms, the actual social norms and the preferences regarding the patient role is measured. Measurement of the preferences is conducted using the Control Preference Scale (CPS). Based on this measure and applying the Krupka-Weber method, descriptive and injunctive norms regarding the physician-patient relationship are measured (Krupka & Weber, 2013).

Wave 2
To answer the main research question on the impact of social norms on preferences, a second online survey wave with a different online representative sample of the general population is planned in which an information provision experiment is conducted to identify the causal effect of norm information on preferences regarding the physician-patient relationship. In this experiment, the sample is randomly divided into three groups in a 3:3:1 ratio: Control (C1), the Social Norm Info and Control (C0). The Social Norm Info group receives the information about the actual social norm measured in wave 1 (see description of intervention below), the control groups C1 and C0 do not receive the information on the actual social norm. To assess whether reflecting on the social norm affects preferences, C0 is not presented with the corresponding belief elicitation questions and thus acts as additional control.
Measurement of the preferences is conducted using the Control Preference Scale (CPS). Based on this measure and applying the Krupka-Weber method, descriptive and injunctive norms regarding the physician-patient relationship are measured (Krupka & Weber, 2013).

The survey waves are administered by the company "Bilendi" which has access to an online representative sample of the Austrian population.
Randomization Method
Randomization done by computer program used for the survey.
Randomization Unit
Individual randomization. Participants are allocated to one of three groups in a 3:3:1 ratio.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
3,000-3,500
Sample size: planned number of observations
3,000-3,500
Sample size (or number of clusters) by treatment arms
1285-1500 in Control
1285-1500 in Social Norm Info
(428-500 in Control 0)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Categorical variable: Using multinomial logistic regression with the passive role as the reference category, the minimum detectable effect size is an odds ratio of 1.323 for both active and shared decision-making roles in the treatment group using a simulation-based approach with a power of 0.8 and 3,000 individuals (1,500 per treatment arm). Binary variable: With a power of 0.8, alpha 0.05 and the sample size of 3,000, the minimum detectable effect size is a delta of 0.05113 (5.113 percentage points). Ordinal (treated as continuous from 1 to 5): With a power of 0.8, alpha 0.05 and the sample size of 1.000, the minimum detectable effect size is 0.11 standard deviations.
IRB

Institutional Review Boards (IRBs)

IRB Name
RCSEQ (Research Committee for Scientific Ethical Questions) Privatuniversität UMIT TIROL und fh gesundheit
IRB Approval Date
2025-03-18
IRB Approval Number
3544

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials