Evidence map›Paper›PMID 30221168›Full record

ArticlemHealth2018

Evaluation of the effectiveness of mobile diabetes management system with social networking and cognitive behavioural therapy (CBT) for T2D.

Turki Alanzi, Naif Radi Alanazi, Robert Istepanian, Nada Philip

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in mHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Turki AlanziHealth Information Management and Technology Department, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Naif Radi AlanaziNaval Technical Institute Clinic, Dammam, Saudi Arabia.
Robert IstepanianDepartment of Electrical and Electronic Engineering, Imperial College, London, UK.
Nada PhilipMedical Information and Network Technologies Research Centre, Kingston University, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the Saudi Arabia region there are no previous studies related to the use of social networks combined with the management of mobile diabetes. In this sense, the aim of this feasibility investigation is to evaluate the application and utility of the SANAD system (Saudi Arabia Networking for Aiding Diabetes) to support Saudi type 2 diabetes adult patients.

methodsTwenty patients from a clinic in Saudi Arabia-Dammam were recruited to use the SANAD system. The study design was a randomized controlled trial (RCT) with two groups: an intervention group using SANAD system and a control group using conventional diabetes treatment. Glycated hemoglobin (HbA1c), diabetes knowledge test (DKT) and Self-efficacy Scale (SES) were documented.

resultsNineteen patients completed the study. Mean baseline HbA1c (%) was 8.14 (SD 1.20) and decreased to 7.54 (SD 0.96) after the SANAD intervention process [mean (SEM) decrease 0.600 (0.102)]. A paired-samples

conclusionsThis study demonstrates that using of SANAD system is acceptable, and feasible in supporting diabetes care in Saudi Arabia. This study is the first in Saudi Arabia to demonstrate similar benefits of using this technology on social diabetes and management. A national clinical trial is needed to assess precise benefits of self-care and knowledge.

Indexed as

diabetesmHealthSaudi Arabia

Identifiers

PMID30221168
PMCPMC6131530

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.