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Using thematic analysis in psychology

Qualitative Research in Psychology(2006)10.1191/1478088706qp063oaSource: DataRank Database

Using thematic analysis in psychology is a research paper published in Qualitative Research in Psychology (2006). On theSindex it has a DataRank of 1.8. It has been cited 174,192 times.

N/A
1.8DataRank · unranked
1.8
Open Access174192 citations · base score 12.1
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Increasingly, adult Indigenous language learners are being identified as the “missing generation” of learners who hold great potential to contribute to the revival of Indigenous languages by acting as the middle ground between Elders, children and youth within their communities. Our research project NEȾOLṈEW̱ ‘one mind, one people’ investigated adult Indigenous language learning through the popular Mentor-Apprentice Program (MAP) method (Leanne Hinton, 2001). Over the course of 14 months, our team conducted 133 interviews with four groups of participants involved in MAP. The participants were current and past apprentices, mentors, and administrators of MAP programs in British Columbia, Canada. Our primary interest was to learn about the successes and challenges of MAP for language learning, but we also included interview questions that gave participants space to share how participating in MAP may have affected them. During thematic analysis of the interviews (Braun & Clarke, 2006, 2014) we noticed repeating comments across all four participant groups on how their involvement with MAP impacted their own and their community’s wellbeing. Six exploratory themes were identified: • Language loss negatively impacts the wellbeing of Indigenous people: “[the word] doesn’t just mean a bad, misbehaving child, it also means a poor child that has been uprooted […] and is disconnected from their culture” • The relationship between burden and wellbeing among participants in MAP: “there’s so much to be done. […] that’s the exhausting part of it. It’s trying to learn and teach at the same time” • Strengthening MAP apprentices to become future community leaders: “it brings a huge sense of pride […] and helps me be an inspiration to anyone else” • Elder’s healing through becoming language mentors: “we once again have that believe in ourselves where we can feel free” • Cultural and spiritual health and healing: “I am keeping something very precious alive by speaking my language” • Health outcomes: “it was […] the language that... pushed me to sobriety, […] it gave me... a sense of who I was”. Although studies have reported protective effects of Indigenous language use on health (Ball & Moselle, 2013; Hallett, Chandler, & Lalonde, 2007; McIvor, 2013), health-related outcomes of language revitalization efforts, including MAP, remain underexplored (Whalen, Moss, & Baldwin, 2016). In addition to discussing the six exploratory themes from our study, our paper also proposes that these themes can inform future research in the area of language revitalization and wellbeing. References Ball, J., & Moselle, K. (2013). Contributions of culture and language in aboriginal head start in urban and northern communities to children’s health outcomes: A review of theory and research. Prepared for Division of Children, Seniors & Healthy Development, Health Promotion and Chronic Disease Prevention Branch. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77–101. http://doi.org/10.1191/1478088706qp063oa Braun, V., & Clarke, V. (2014). What can “thematic analysis” offer health and wellbeing researchers? International Journal of Qualitative Studies on Health and Well-Being, 9, 26152. http://doi.org/10.3402/qhw.v9.26152 Hallett, D., Chandler, M. J., & Lalonde, C. E. (2007). Aboriginal language knowledge and youth suicide. Cognitive Development, 22(3), 392–399. http://doi.org/10.1016/j.cogdev.2007.02.001 Hinton, L. (2001). The master-apprentice language learning program. In L. Hinton & K. Hale (Eds.), The green book of language revitalization in practice (pp. 217–226). San Diego, CA: Academic Press. McIvor, O. (2013). Protective effects of language learning, use and culture on the health and well-being of Indigenous people in Canada. In Proceedings of the 17th FEL Conference, FEL XVII: Endangered Languages Beyond Boundaries: Community Connections, Collaborative Approaches and Cross-Disciplinary Research (pp. 123–131). Foundation for Endangered Languages in association with the University of Carleton. Whalen, D. H., Moss, M., & Baldwin, D. (2016). Healing through language: Positive physical health effects of indigenous language use. F1000Research, 5(852). http://doi.org/10.12688/f1000research.8656.1

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (1/2)
  • Open Access
Interoperable (0/2)
    Reusable (0/3)

      FAIR checklist signals are shown for context only and do not affect DataRank scoring.

      DataRank Breakdown

      Base Score 100%Citation Network 0%

      Base Score Contribution

      1.8

      From this paper's citation signal

      Citation Network Contribution

      0

      Citation network not refreshed for this result

      This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

      Learn more about DataRank methodology →
      Why this DataRank?

      DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.

      Base score B(p)
      log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
      Network N(p)
      Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
      Damping factor d = 0.85
      DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
      Self-citations excluded
      Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

      Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

      Read the full methodology →

      Authors (2)

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