Evidence map›Paper›PMID 38577315›Full record

ArticleDigital health

Perceptions and effectiveness of episodic future thinking as digital micro-interventions based on mobile health technology.

Dan Roland Persson, Jakob E Bardram, Per Bækgaard

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

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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

3 authors.

Dan Roland PerssonDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark.ORCID https://orcid.org/0000-0002-4258-6949
Jakob E BardramDepartment of Health Technology, Technical University of Denmark, Denmark.ORCID https://orcid.org/0000-0003-1390-8758
Per BækgaardDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark.ORCID https://orcid.org/0000-0002-6720-1128

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Delay discounting denotes the tendency for humans to favor short-term immediate benefits over long-term future benefits. Episodic future thinking (EFT) is an intervention that addresses this tendency by having a person mentally "pre-experience" a future event to increase the perceived value of future benefits. This study explores the feasibility of using mobile health (mHealth) technology to deliver EFT micro-interventions. Micro-interventions are small, focused interventions aiming to achieve goals while matching users' often limited willingness or capacity to engage with interventions. We aim to explore whether EFT delivered as digital micro-interventions can reduce delay discounting, the users' perceptions, and if there are differences between regular EFT and goal-oriented EFT (gEFT), a variant where goals are embedded into future events. Method: A randomized study was conducted with 208 participants allocated to either gEFT, EFT, or a control group for a 21-day study. Results: Results indicate intervention groups when combined achieved a significant reduction of Conclusions: Overall, user perceptions indicate gEFT may be slightly better for use in micro-interventions. However, perceptions also indicate that audio-based EFT micro-interventions were not always preferable to users, with findings suggesting that future EFT micro-interventions should be delivered using different forms of multimedia based on user preference and context and supported by other micro-interventions to maintain interest.

Indexed as

delay discountingepisodic future thinkinggoal-orientedmicro-interventionsmobile health (mHealth)

Identifiers

PMID38577315
PMCPMC10993675

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.