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Record W4416015384 · doi:10.2196/73245

Motivational Framing Strategies in Health Care Information Security Training: Randomized Controlled Trial

2025· article· en· W4416015384 on OpenAlexvenueno aff
Thomas Keller, Julia Warwas, Julia Klein, Richard Henkenjohann, Manuel Trenz, Simon Trang

Bibliographic record

VenueJMIR Medical Education · 2025
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsnot available
Fundersnot available
KeywordsFraming (construction)Health careRandomized controlled trialFraming effectHealth informationEmpathy

Abstract

fetched live from OpenAlex

BACKGROUND: Information security is a critical challenge in the digital age, especially for hospitals, which are prime targets for cyberattacks due to the monetary worth of sensitive medical data. Given the distinctive security risks faced by health care professionals, tailored Security Education, Training, and Awareness (SETA) programs are needed to increase both their ability and willingness to integrate security practices into their workflows. OBJECTIVE: This study investigates the effectiveness of a video-based security training, which was customized for hospital settings and enriched with motivational framing strategies to build information security skills among health care professionals. The training stands out from conventional interventions in this context, particularly by incorporating a dual-motive model to differentiate between self- and other-oriented goals as stimuli for skill acquisition. The appeal to the professional values of responsible health care work, whether absent or present, facilitates a nuanced examination of differential framing effects on training outcomes. METHODS: A randomized controlled trial was conducted with 130 health care professionals from 3 German university hospitals. Participants within 2 intervention groups received either a self-oriented framing (focused on personal data protection) or an other-oriented framing (focused on patient data protection) at the beginning of a security training video. A control group watched the same video without any framing. Skill assessments using situational judgment tests before and after the training served to evaluate skill growth in all 3 groups. RESULTS: Members of the other-oriented intervention group, who were motivated to protect patients, exhibited the highest increase in security skills (ΔM=+1.13, 95% CI 0.82-1.45), outperforming both the self-oriented intervention group (ΔM=+0.55, 95% CI 0.24-0.86; P=.04) and the control group (ΔM=+0.40, 95% CI 0.10-0.70; P=.004). Conversely, the self-oriented framing of the training content, which placed emphasis on personal privacy, did not yield significantly greater improvements in security skills over the control group (mean difference=+0.15, 95% CI -0.69 to 0.38; P>.99). Further exploratory analyses suggest that the other-oriented framing was particularly impactful among participants who often interact with patients personally, indicating that a higher frequency of direct patient contact may increase receptiveness to this framing strategy. CONCLUSIONS: This study underscores the importance of aligning SETA programs with the professional values of target groups, in addition to adapting these programs to specific contexts of professional action. In the investigated hospital setting, a motivational framing that resonates with health care professionals' sense of responsibility for patient safety has proven to be effective in promoting skill growth. The findings offer a pragmatic pathway with a theoretical foundation for implementing beneficial motivational framing strategies in SETA programs within the health care sector.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.861
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.317
Teacher spread0.309 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations1
Published2025
Admission routes1
Has abstractyes

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