MétaCan
Menu
Back to cohort
Record W4401314856 · doi:10.1080/07053436.2024.2368678

Impact of digital technology on family life and leisure activities: An approach from families with adolescents

2024· article· en· W4401314856 on OpenAlexvenueno aff
Estefanía de los Dolores Gil García, Pedro Francisco Alemán Ramos, Juan Carlos Martín Quintana

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersEuropean Social Fund
KeywordsPsychologyFamily lifeLeisure timeDevelopmental psychologySociologyGender studiesPhysical activityMedicinePhysical therapy

Abstract

fetched live from OpenAlex

This study investigates parents’ perceptions of the impact of digital technology on family life and leisure activities for adolescents (11–17 years old). Through three focus groups, 19 parents aged 33 to 56 participated. The discourse analysis, conducted using NVivo software and grounded theory, revealed how families access and use digital technology and its impact on parental supervision and family leisure activities. Parents noted the importance of digital skills to protect adolescents from online risks and to engage in virtual activities together. The study highlights the need for parents to improve their digital competencies to effectively manage and participate in their children’s digital lives. Future research should explore the digital skill levels of parents to identify barriers to effective digital inclusion and develop strategies to address these gaps. This will enable families to better navigate the digital landscape and ensure a balanced and safe integration of technology into their daily lives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.306
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueLoisir et Société / Society and LeisureSame topicChild Development and Digital TechnologyFrench-language works237,207