Evidence map›Paper›PMID 36365994›Full record

ArticleSensors (Basel, Switzerland)2022

Capacity Strengthening Undertaking-Farm Organized Response of Workers against Risk for Diabetes: (C.S.U.-F.O.R.W.A.R.D. with Cal Poly)-A Concept Approach to Tackling Diabetes in Vulnerable and Underserved Farmworkers in California.

Angelos K Sikalidis, Aleksandra S Kristo, Scott K Reaves, Franz J Kurfess, Ann M DeLay, Kathryn Vasilaky, Lorraine Donegan

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
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

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 1 institution in 1 country.

Angelos K SikalidisNutrition Program, Department of Food Science and Nutrition, California Polytechnic State University, San Luis Obispo, CA 93407, USA.ORCID 0000-0003-3487-4120
Aleksandra S KristoNutrition Program, Department of Food Science and Nutrition, California Polytechnic State University, San Luis Obispo, CA 93407, USA.ORCID 0000-0002-0733-4041
Scott K ReavesNutrition Program, Department of Food Science and Nutrition, California Polytechnic State University, San Luis Obispo, CA 93407, USA.
Franz J KurfessDepartment of Computer Science and Software Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA.
Ann M DeLayDepartment of Agriculture Education and Communication, California Polytechnic State University, San Luis Obispo, CA 93407, USA.
Kathryn VasilakyDepartment of Economics, Orfalea College of Business, California Polytechnic State University, San Luis Obispo, CA 03497, USA.ORCID 0000-0002-9778-4379
Lorraine DoneganDepartment of Graphic Communication, California Polytechnic State University, San Luis Obispo, CA 93407, USA.
California Polytechnic State University · US

Funding

United States Department of Agriculture 2020-70001-31296
6 · The paper itself

Abstract

In our project herein, we use the case of farmworkers, an underserved and understudied population at high risk for Type-2 Diabetes Mellitus (T2DM), as a paradigm of an integrated action-oriented research, education and extension approach involving the development of long-term equitable strategies providing empowerment and tailored-made solutions that support practical decision-making aiming to reduce risk of T2DM and ensuing cardiovascular disease (CVD). A Technology-based Empowerment Didactic module (TEDm) and an Informed Decision-Making enhancer (IDMe) coupled in a smart application (app) for farmworkers aiming to teach, set goals, monitor, and support in terms of nutrition, hydration, physical activity, sleep, and circadian rhythm towards lowering T2DM risk, is to be developed and implemented considering the particular characteristics of the population and setting. In parallel, anthropometric, biochemical, and clinical assessments will be utilized to monitor risk parameters for T2DM and compliance to dietary and wellness plans. The app incorporating anthropometric/clinical/biochemical parameters, dietary/lifestyle behavior, and extent of goal achievement can be continuously refined and improved through machine learning and re-programming. The app can function as a programmable tool constantly learning, adapting, and tailoring its services to user needs helping optimization of practical informed decision-making towards mitigating disease symptoms and associated risk factors. This work can benefit apart from the direct beneficiaries being farmworkers, the stakeholders who will be gaining a healthier, more vibrant workforce, and in turn the local communities.

Indexed as

Diabetes Mellitus, Type 2FarmersCaliforniaFarmsHumansPoly APoly Aagricultureartificial intelligence (AI)farm workersmachine learningnutritionpractical decision makingtype 2 diabetes mellitus (T2DM)

Identifiers

PMID36365994
PMCPMC9654638
OpenAlexW4307945209

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.