Exploring Access as a Process of Adaptation in a Self-Monitoring Perinatal eHealth System: Mixed Methods Study From a Sociomaterial Perspective
Bibliographic record
Abstract
BACKGROUND: The development and quality assurance of perinatal eHealth self-monitoring systems is an upcoming area of inquiry in health science. Building patient engagement into eHealth development as a core component has potential to guide process evaluation. Access, 1 attribute of patient engagement, is the focus of study here. Access to eHealth self-monitoring programs has the potential to influence pregnancy health and wellness outcomes. Little is known about how pregnant users' ability to obtain resources is influenced by their own adaptive activities and the mediating activities of eHealth systems during the process of real-world testing of these systems. OBJECTIVE: Here, we examine the patient engagement process of access occurring during the adaptation of eHealth self-monitoring use from a sociomaterial perspective. METHODS: In this mixed methods convergent evaluation design, we interviewed women about perceptions of the adaptation process of using an eHealth self-monitoring system. Deductive analysis was conducted guided by the definition of access as an attribute of patient engagement. After initial qualitative and quantitative data collection and analysis, participants were spilt based on their level of use of the eHealth system (physical wear time of self-monitoring device). Content analysis was then conducted according to user group, using a conceptual matrix developed from ontological perspectives of sociomateriality. RESULTS: Pregnant users' adaptive activities and the mediation activities of the eHealth system represent a cocreation process that resulted in user group-specific characteristics of accessing and using the system. The high- and low-use groups experienced different personal adaptation and eHealth mediation during this process of cocreation. Differences were noted between high- and low-use groups, with the high-use group giving attention to developing skills in recording and interpreting data and the low-use group discussing the manual adding of activities to the system and how the system worked best for them when they used it in their mother tongue. CONCLUSIONS: A cocreation process between pregnant users and the eHealth system was identified, illustrating access as a useful core component of perinatal eHealth self-monitoring systems. Researchers and clinicians can observe reasons for why pregnant users access eHealth systems in unique ways based on their personal preferences, habits, and values. Mediation activities of the eHealth system and the different user adaptive activities represent a cocreation process between the users and the eHealth system that is necessary for the personalization of perinatal eHealth systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".