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Record W2917165792 · doi:10.2196/10992

Impact of New Technologies for Middle-Aged and Older Patients: In-Depth Interviews With Type 2 Diabetes Patients Using Continuous Glucose Monitoring

2019· article· en· W2917165792 on OpenAlex
Ching‐Ju Chiu, Yu-Hsuan Chou, Yen-Ju Chen, Ye‐Fong Du

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Diabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsGlycated hemoglobinMedicineDiabetes mellitusType 1 diabetesFeelingDiabetes managementContinuous glucose monitoringBlood glucose monitoringBlood Glucose Self-MonitoringType 2 diabetesSelf-monitoringPhysical therapyPsychologySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Continuous glucose monitoring (CGM) uses subcutaneous sensors and records the average interstitial sensor current every 5 min in the recorder; data are subsequently exported to a computer 4 to 7 days later when calibration with self-measured blood glucose is made retrospectively. How middle-aged and older patients perceive the added technology intervention is not clear. OBJECTIVE: The study aimed to understand the factors associated with the adoption of new technology in diabetes care, to understand the feelings and behaviors while using it, and to determine the changes in attitudes and behavior after completing the use of the new technology at the 3-month follow-up. METHODS: Middle-aged and older type 2 diabetes patients who had received professional continuous glucose monitoring (iPro 2 [Medtronic]) were invited for semistructured in-depth interviews on the day of the CGM sensor removal and at 3 months after CGM-based counseling. A phenomenography approach was used to analyze the interview data. RESULTS: A total of 20 type 2 diabetes patients (aged 53 to 72 years, 13 males and 7 females, 4 to 40 years duration of diabetes, mean glycated hemoglobin 8.54% [SD 0.71%]) completed 2 sections of semistructured in-depth interviews. Physician guidance and participant motivation toward problem solving were found to be factors associated with adoption of the device. Participants indicated that technology can be a reminder, a supervisor, and a visualizer of blood glucose, all of which are helpful for disease management. However, CGM is somewhat inconvenient, and some participants also reported that the provision of this new technology might be a hint of disease progression. There was a higher percentage of women compared with men who reported that CGM can be a reminder or a supervisor to help them with diet control. CONCLUSIONS: Physician guidance and participants' degree of motivation are keys to adopting new technology in the case of middle-aged and older adults. Although the CGM sensor may cause inconvenience to patients on their limited body movement when wearing the device, it is helpful for diet control and is an effective behavioral modification tool that offers support, especially in the case of women.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.030
GPT teacher head0.314
Teacher spread0.284 · 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