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Record W1972611183 · doi:10.1080/08870440008405587

Parent-adolescent health conversations as action: Theoretical and methodological issues

2000· article· en· W1972611183 on OpenAlexaff
Richard A. Young, M. Judith Lynam, Ladislav Valach, Helen Novak, Iona Brierton, Ada Christopher

Bibliographic record

VenuePsychology and Health · 2000
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyAction (physics)Health promotionMeaning (existential)Identification (biology)Social psychologyPromotion (chess)Qualitative researchDevelopmental psychologyApplied psychologyPsychotherapistPublic healthSociologyMedicineNursingSocial science

Abstract

fetched live from OpenAlex

A qualitative research method based on action theory is proposed and illustrated for use in health psychology and health promotion research. Action refers to the goal-directed and intentional behaviors of individual and groups. Action theory has the advantage of using the perspectives provided by manifest behavior, internal processes, and social meaning in the analysis of action. In this article, the actions under consideration are the health-related conversations of parents and their adolescent children. The approach is premised on an understanding of health promotion as a family task constructed through actions such as conversations between family members. Health conversations in two parent-adolescent dyads are used to illustrate the method. The analysis includes the identification of goals, functional steps, and elements and their relation to the family health promotion project. Specific attention is paid to data gathering and analysis issues and their implications for health promotion research.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.344
metaresearch head score (Gemma)0.263
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.344
Threshold uncertainty score0.809

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3440.263
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.010
Science and technology studies0.0130.021
Scholarly communication0.0180.013
Open science0.0080.014
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.467
GPT teacher head0.641
Teacher spread0.174 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
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

Citations14
Published2000
Admission routes1
Has abstractyes

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