Mode Effects on Self-Reported Health Across Web-Based, Interviewer-Administered, and Nurse-Administered Modes: Population-Based Study

Abstract Background Probability-based surveys remain essential to epidemiology, but expanding mixed-mode data collection, which combines web self-completion and interviewer-administered surveys, raises concerns that administration mode and interviewer presence may influence health reporting. These concerns warrant further investigation of interviewer-related biases and mode differences in health reporting. Objective This study assessed whether responses to the 12-item General Health Questionnaire (GHQ-12) and 12-item Short Form Health Survey (SF-12), both self-completed, differed by interviewer presence and role: online without an interviewer, during a social interviewer visit, or during a nurse visit. It also assessed mode effects on doctor-diagnosed conditions recorded by interviewers in computer-assisted personal interviewing (CAPI) and when self-completed online. We further examined possible variation by sex and age. Methods The analysis used randomized mode allocation embedded within wave 12 (2019) of the UK Household Longitudinal Study Innovation Panel. After applying relevant exclusions, the final analytic sample comprised 1111 households (1779 participants) across the 3 randomly assigned survey modes: web-based self-completion, interviewer-administered CAPI, or nurse-administered CAPI. The sample was predominantly White British, with a broadly balanced sex distribution and participants from diverse age, employment, education, and household income groups. Participants did not always complete the survey in their randomly assigned mode. Effects were estimated using a two-stage residual inclusion instrumental variable approach, with randomized mode as an instrument for actual mode, to address confounding arising from nonrandom selection into actual mode. Results No statistically significant differences were observed across self-completion contexts for the GHQ-12 or the SF-12 mental and physical component scores. We found no statistically significant evidence of mode effects on doctor-diagnosed conditions. For example, no statistically significant mode effects in psychiatric conditions were identified across the comparisons: nurse relative to social interviewer (odds ratio [OR] 0.72, 95% CI 0.40‐1.29; P =.53), web relative to social interviewer (OR 0.45, 95% CI 0.17‐1.18; P =.14), and web relative to nurse (OR 0.63, 95% CI 0.27‐1.49; P =.59). There was little evidence overall that mode-related differences varied by age or sex. Conclusions Our findings may support embedding self-completion modules within interviewer-administered surveys for the collection of SF-12 and GHQ-12. Meanwhile, potential mode-related differences should be considered when designing mixed-mode surveys and interpreting self-reported health data.

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Publication Details

Journal
JMIR Human Factors
Published
2026-10-16
DOI
https://doi.org/10.2196/89896
Primary Topic
Survey Methodology and Nonresponse
Type
article
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article

Mode Effects on Self-Reported Health Across Web-Based, Interviewer-Administered, and Nurse-Administered Modes: Population-Based Study

Tarek Al Baghal, Jonathan Burton, Meena Kumari B, Yunlong Liang
JMIR Human Factors
Survey Methodology and Nonresponse
article

Mode Effects on Self-Reported Health Across Web-Based, Interviewer-Administered, and Nurse-Administered Modes: Population-Based Study

Tarek Al Baghal, Jonathan Burton, Meena Kumari B, Yunlong Liang
article en

Abstract

Abstract Background Probability-based surveys remain essential to epidemiology, but expanding mixed-mode data collection, which combines web self-completion and interviewer-administered surveys, raises concerns that administration mode and interviewer presence may influence health reporting. These concerns warrant further investigation of interviewer-related biases and mode differences in health reporting. Objective This study assessed whether responses to the 12-item General Health Questionnaire (GHQ-12) and 12-item Short Form Health Survey (SF-12), both self-completed, differed by interviewer presence and role: online without an interviewer, during a social interviewer visit, or during a nurse visit. It also assessed mode effects on doctor-diagnosed conditions recorded by interviewers in computer-assisted personal interviewing (CAPI) and when self-completed online. We further examined possible variation by sex and age. Methods The analysis used randomized mode allocation embedded within wave 12 (2019) of the UK Household Longitudinal Study Innovation Panel. After applying relevant exclusions, the final analytic sample comprised 1111 households (1779 participants) across the 3 randomly assigned survey modes: web-based self-completion, interviewer-administered CAPI, or nurse-administered CAPI. The sample was predominantly White British, with a broadly balanced sex distribution and participants from diverse age, employment, education, and household income groups. Participants did not always complete the survey in their randomly assigned mode. Effects were estimated using a two-stage residual inclusion instrumental variable approach, with randomized mode as an instrument for actual mode, to address confounding arising from nonrandom selection into actual mode. Results No statistically significant differences were observed across self-completion contexts for the GHQ-12 or the SF-12 mental and physical component scores. We found no statistically significant evidence of mode effects on doctor-diagnosed conditions. For example, no statistically significant mode effects in psychiatric conditions were identified across the comparisons: nurse relative to social interviewer (odds ratio [OR] 0.72, 95% CI 0.40‐1.29; P =.53), web relative to social interviewer (OR 0.45, 95% CI 0.17‐1.18; P =.14), and web relative to nurse (OR 0.63, 95% CI 0.27‐1.49; P =.59). There was little evidence overall that mode-related differences varied by age or sex. Conclusions Our findings may support embedding self-completion modules within interviewer-administered surveys for the collection of SF-12 and GHQ-12. Meanwhile, potential mode-related differences should be considered when designing mixed-mode surveys and interpreting self-reported health data.

JMIR Human FactorsVol. 13
University of Essex (GB)
Good health and well-being
Openalex Percentile: Top 5%
Survey Methodology and Nonresponse
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