We designed this study as a cross-sectional study using the READHY questionnaire.

It was registered at ClinicalTrials.gov before initiation. Identifier: NCT04745117 [11]. The study was reported per The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement [12].

The study was conducted at the Department of Plastic Surgery at Odense University Hospital. The participants were constituted by a convenience sample obtained from 01.03.2021 through 31.12.2021. All patients referred to us with suspected breast cancer were asked to participate. Our department receives patients from the area of Funen and the surrounding islands. The exclusion criteria were: not being able to understand and read Danish.

Patients were referred via the official screening program for breast cancer in Denmark, where all women between 50 - and 69 years are offered a mammogram every two years. If the clinical mammogram raised suspicion of breast cancer, they were referred to us as the closest breast surgery centre. Additionally, all patients of all ages with clinical suspicion of breast cancer were referred by general practitioners. We asked the patients to complete the questionnaire on their first or second visit to our department.

The patients answered the questionnaires electronically using a tablet. If the patients wanted to fill out the questionnaires on paper, this was arranged by the attending nurse. The patients were informed orally and in writing about the study before giving consent to participate. The questionnaire constituted a section of demographic data and the READHY tool.

We collected the following demographic data: gender, age, the highest level of education, cohabitation status, and source of income. We also asked the participants if they owned a smartwatch, tablet, or computer and their primary purpose when using information technology (IT).

The READHY tool was used to assess readiness for health technology. The tool consists of the eHealth Literacy Questionnaire (eHLQ) [13], which includes seven scales, supplemented with four scales from the Health Education Impact Questionnaire (heiQ) [14] and two scales from the Health Literacy Questionnaire (HLQ) [15]. The individual scales and associated questionnaires can be found in Fig. 1. Together, these scales capture eHealth literacy, self-management, and social context. The READHY tool is a validated assessment tool [10]. The 13 scales were assessed using 65 items. Each item was presented to the participant as a statement and scored on a 4-point rating scale, ranging from 1 = strongly disagree to 4 = strongly agree. The overall score of each scale was calculated as the mean score of the 4–6 items (i.e., statements) that constitute the scale. If less than 50% of items in a scale were answered, the scale was regarded as missing; in those cases, the survey was considered incomplete.

Readiness and Enablement Index for Health Technology (READHY) scale scores for the three identified profiles based on cluster analysis. heiQ: Health Education Impact Questionnaire; HLQ: Health Literacy Questionnaire; eHLQ: eHealth Literacy Questionnaire. Data are presented as mean (SD). heiQ8 was reversed (i.e., a high score indicated a low level of emotional distress)

We consulted a clinical statistician before initiating the study. Based on previously published data using the READHY tool, we were advised to aim for approximately one hundred participants.

Our data-analysis method was based on a previously published study with a similar aim by Thorsen et al. [8]. We used a data-driven approach with a combination of hierarchical and K-means cluster analysis to divide participants into clusters depending on their level of readiness for health technology. We have chosen to refer to these clusters as profiles.

We used the two-step k-means analysis and Bonferroni post hoc analyses using the one-way analysis of variance (ANOVA) to decide the optimal number of clusters. The results assessed three profiles as the best fit and two as the second best fit. We conducted K-means cluster analyses for three profiles in 8 iterations. The difference between profiles for each ready scale was assessed using a one-way ANOVA.

For sociodemographic and IT-related data, the differences between the profiles were tested using the Fisher exact test for frequencies and the one-way ANOVA for continuous variables. Frequencies are reported as numbers and proportions, and continuous variables are reported as mean and standard deviation (SD).

Data were analysed as observed. No imputations were used to replace missing data.

Data were analysed using SPSS version 28 [16]. The statistical analyses were performed under the guidance of a clinical statistician.