Evidence map›Paper›PMID 37165660›Full record

Trial reportPublic health nutrition2023

Effectiveness of a text-messaging intervention on intuitive eating: a randomised controlled trial.

Batoul Manana, Claire El-Jor, Joelle Abi Kharma, Nadine Zeeni

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Public health nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.9field-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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
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 at 1 institution in 1 country.

Batoul MananaDepartment of Natural Sciences, School of Arts and Sciences, Lebanese American University, 36-Byblos, Lebanon.
Claire El-JorDepartment of Natural Sciences, School of Arts and Sciences, Lebanese American University, 36-Byblos, Lebanon.
Joelle Abi KharmaDepartment of Natural Sciences, School of Arts and Sciences, Lebanese American University, 36-Byblos, Lebanon.
Nadine ZeeniDepartment of Natural Sciences, School of Arts and Sciences, Lebanese American University, 36-Byblos, Lebanon.ORCID 0000-0003-1747-6016
Lebanese American University · LB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intuitive eating (IE) is a concept based on mind-body integration of instinct, emotion and rational thought, to improve eating behaviours, physical and mental health. Several attempts were developed to teach IE principles including text-messaging interventions given that they are easy to implement and low cost.

objectiveThe present study aimed to assess the effectiveness of a 5-week text message-based IE intervention on IE, while correcting for perceived stress (PS) and self-compassion (SC).

designA randomised controlled trial.

settingOnline, in Lebanon.

participantsAdults (

resultsResults indicated improvements in IE scores in the two intervention groups (

conclusionText-messaging interventions might be efficient in enhancing IE. Results shed light on the need for further large-scale interventions that use visual aids and provide practical guidance to teach IE, while further characterising the relation between IE, SC and stress.

Indexed as

Text MessagingAdultAudiovisual AidsExerciseFeeding BehaviorHumansNutritional StatusEating behaviourIntuitive eatingPerceived stressRandomised controlled trialSelf-compassion

Identifiers

PMID37165660
PMCPMC10410380
OpenAlexW4376132134

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.