Evidence map›Paper›PMID 41721382›Full record

ArticleBMC sports science, medicine & rehabilitation2026

From screen to field: the impact of digital sports participation on leisure time satisfaction.

Nurgül Özdemi̇r, Neşe Akpinar Kocakulak

Abstract read
In one paragraph

Article in BMC sports science, medicine & rehabilitation, 2026. 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
–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

0 citing papers in PubMed.

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

2 authors.

Nurgül Özdemi̇rFaculty of Health Sciences, Department of Exercise and Sports Sciences, Izmir Democracy University, Izmir, Turkey. nurgul.ozdemir@idu.edu.tr.ORCID http://orcid.org/0000-0002-6124-6982
Neşe Akpinar KocakulakFaculty of Health Sciences, Department of Exercise and Sports Sciences, Izmir Democracy University, Izmir, Turkey.ORCID http://orcid.org/0000-0001-5798-263X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study is to determine the levels of leisure time satisfaction among individuals who engage in digital sports and to examine differences based on demographic and participation variables. The study employed a descriptive survey model with a cross-sectional design. The sample consisted of 381 digital sports participants (188 males, 193 females) selected through convenience sampling. Data were collected using the “Leisure Satisfaction Scale (LSS).” Since the data were not normally distributed, non-parametric tests (Mann-Whitney U and Kruskal-Wallis H) were utilized for statistical analysis. The results indicated that male participants exhibited significantly higher satisfaction scores in the relaxation sub-dimension compared to females (p < .05). Participants who earned income from digital sports reported significantly higher physical (p < .01) and aesthetic (p = .05) satisfaction levels. Conversely, participants who did not engage in competitions demonstrated higher psychological satisfaction compared to competitive players (p < .01). Furthermore, individuals engaging in physical exercise 3–5 days per week reported significantly higher satisfaction in the social, relaxation, physical, and aesthetic sub-dimensions (p < .05). In conclusion, digital sports contribute to leisure satisfaction multifacetedly; however, this impact is significantly modulated by gender, competitive status, and physical activity frequency.

Indexed as

Digital sportsLeisure time satisfactionSurvey modelTechnology

Identifiers

PMID41721382
PMCPMC13067600

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.