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Record W2768534460 · doi:10.2196/mental.8139

Sharing Family Life Information Through Video Calls and Other Information and Communication Technologies and the Association With Family Well-Being: Population-Based Survey

2017· article· en· W2768534460 on OpenAlexvenueno aff
Chen Shen, Man Ping Wang, Joanna Ting Wai Chu, Alice Wan, Kasisomayajula Viswanath, Sophia Siu Chee Chan, TH Lam

Bibliographic record

VenueJMIR Mental Health · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessPhonePsychologyPopulationFamily lifeMobile phoneSocial mediaInternet privacySocial psychologyMedicineWorld Wide WebSociologyComputer scienceEnvironmental healthSocioeconomicsTelecommunications

Abstract

fetched live from OpenAlex

BACKGROUND: The use of information and communication technologies (ICTs) for information sharing among family members is increasing dramatically. However, little is known about the associated factors and the influence on family well-being. OBJECTIVE: The authors investigated the pattern and social determinants of family life information sharing with family and the associations of different methods of sharing with perceived family health, happiness, and harmony (3Hs) in Hong Kong, where mobile phone ownership and Internet access are among the most prevalent, easiest, and fastest in the world. METHODS: A territory-wide population-based telephone survey was conducted from January to August 2016 on different methods of family life information (ie, information related to family communication, relationships with family members, emotion and stress management) sharing with family members, including face-to-face, phone, instant messaging (IM), social media sites, video calls, and email. Family well-being was assessed by three single items on perceived family health, happiness, and harmony, with higher scores indicating better family well-being. Adjusted prevalence ratios were used to assess the associations of sociodemographic factors with family life information sharing, and adjusted beta coefficients for family well-being. RESULTS: Of 2017 respondents, face-to-face was the most common method to share family life information (74.45%, 1502/2017), followed by IM (40.86%, 824/2017), phone (28.10%, 567/2017), social media sites (11.91%, 240/2017), video calls (5.89%, 119/2017), and email (5.48%, 111/2017). Younger age and higher education were associated with the use of any (at least one) method, face-to-face, IM, and social media sites for sharing family life information (all P for trend <.01). Higher education was most strongly associated with the use of video calls (adjusted prevalence ratio=5.61, 95% CI 2.29-13.74). Higher household income was significantly associated with the use of any method, face-to-face, and IM (all P for trend <.05). Sharing family life information was associated with a higher level of perceived family well-being (beta=0.56, 95% CI 0.37-0.75), especially by face-to-face (beta=0.62, 95% CI 0.45-0.80) and video calls (beta=0.34, 95% CI 0.04-0.65). The combination of face-to-face and video calls was most strongly associated with a higher level of perceived family well-being (beta=0.81, 95% CI 0.45-1.16). CONCLUSIONS: The differential use of ICTs to share family life information was observed. The prevalence of video calls was low, but associated with much better family well-being. The results need to be confirmed by prospective and intervention studies to promote the use of video calls to communicate and share information with family, particularly in disadvantaged groups.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.318
Teacher spread0.297 · 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.

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

Citations43
Published2017
Admission routes1
Has abstractyes

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