Player Perceptions: Playing Up Qualitative Analysis

Primary keyword: playing up qualitative analysis. According to the PLOS One study, playing up an age grade in youth Camogie can accelerate technical and psychosocial development while increasing physical and psychological demands. The PLOS One study interviewed 15 adolescent players between May 1 and August 31, 2024, and reported concrete trade-offs that coaches, researchers and clubs must weigh. This post refracts those findings through the lens of AI-enabled qualitative research and shows how teams and researchers can use automated transcription, thematic coding and cross-segment analysis to turn interview data into actionable player-centred policy.

Key Takeaways

According to the PLOS One article by O’Keeffe and Lane (published August 11, 2026), youth Camogie players report that playing up an age grade frequently boosts skill and psychosocial development but also raises injury, scheduling and motivation risks.

Sample and timing: the PLOS One study interviewed n = 15 adolescent players aged 14.4 ± 1.1 years between May 1 and August 31, 2024.
Prevalence and prior exposure: the PLOS One study reports 100% of participants were currently playing up and 67% had played up in previous years.
Balance of perceptions: the PLOS One article found 80% of participants expressed overall favourable views of playing up while also describing increased pressure and social challenges as of August 11, 2026.
Practical recommendation: players in the PLOS One study advised stronger social inclusion, coach support and player autonomy to reduce risks and improve retention.

What happened and how the study worked

What happened: O’Keeffe and Lane conducted semi-structured Zoom interviews with 15 club Camogie players to explore perceptions of playing up an age grade, as reported in the PLOS One article.

How data were measured and analysed: the PLOS One study collected audio-recorded interviews between May 1 and August 31, 2024, produced automatic transcriptions, and applied reflexive thematic analysis in a six-step process to generate themes and exemplar quotes.

Constraints and sample details: the PLOS One article notes participants had on average 7.2 ± 2.2 years of playing experience and most (80%) were playing up at club level only; ethical approval was granted (#2023/262).

Findings snapshot

Date / Source	Metric	Value	Implication
May 1 – Aug 31, 2024 (PLOS One)	Interviews conducted	n = 15, each ≥ 40 minutes	Rich, in-depth qualitative data for thematic analysis
Published Aug 11, 2026 (PLOS One)	Mean age	14.4 ± 1.1 years	Adolescent perspective; maturation varies across sample
PLOS One results	Previously played up	67% (10 of 15)	Majority had prior exposure, shaping perceptions
PLOS One results	Overall favourable perception	80% of participants	Playing up often viewed as developmentally positive

Implications for coaches and researchers

Implication summary: the PLOS One study shows playing up can speed technical and psychosocial gains but requires safeguards to mitigate injury, overcommitment and social exclusion.

For coaches: the PLOS One authors recommend assessing individual readiness rather than applying a one-size-fits-all policy, using phased integration and autonomy-supportive coaching to protect motivation.

For researchers: the PLOS One article highlights the need for multi-stakeholder qualitative work that includes coaches and parents, and for objective maturation measures if bio-banding is considered.

Policy implication: the PLOS One study points to the Gaelic Games 2030 Vision and recommends player-centred, scientifically informed guidelines that balance development and welfare.

How Evidano helps: AI-enabled steps from interview to policy

Problem: Slow transcription and inconsistent transcripts → Solution: Rapid accurate transcripts

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.

How it maps to the PLOS One workflow: O’Keeffe and Lane used Zoom audio and automatic transcription; Evidano accelerates that step with high-accuracy speech-to-text plus custom dictionaries for sport terms and PII redaction.

Practical benefit: faster, cleaner transcripts free researchers to iterate on interview guides and reach information power sooner.

Problem: Manual coding is slow and hard to compare → Solution: Thematic and cross-segment analysis

Evidano provides reflexive thematic workflows that mirror the six-step reflexive thematic analysis used in the PLOS One study, enabling reproducible codebooks and transparent theme development.

How it maps to the PLOS One findings: researchers can tag quotes like “you get used to all that stuff quick enough” (P11) and quantify co-occurrence across themes such as competence, pressure and social inclusion.

Practical benefit: produce evidence tables, exemplar quotes and frequency counts that make qualitative findings directly usable for coach education.

Problem: Multiple sources and formats → Solution: Ingest transcripts, surveys, and documents

Evidano ingests interview transcripts, survey spreadsheets and policy documents to support the multi-source synthesis the PLOS One article calls for.

How it maps to PLOS One recommendations: combine player interviews with coach surveys and club training logs to detect schedule clashes and quantify training load patterns relevant to injury risk.

Practical benefit: cross-segment filters let you compare rural versus urban player experiences as the PLOS One article notes differences in prevalence across settings.

Problem: Communicating findings to stakeholders → Solution: Shareable visualizations and exportable evidence

Evidano produces word clouds, co-occurrence networks and hierarchical code trees so clubs and governing bodies can see, for example, how the theme 'pressure' clusters with 'injury' and 'homework' in players’ narratives.

How it maps to the PLOS One aims: turn thematic insight and exemplar quotes into clear coach-education materials and evidence-backed policy briefs for retention strategies.

Practical benefit: stakeholder-ready reports that speed evidence into practice.

Problem: Ongoing interviews and monitoring → Solution: AI chat and iterative reanalysis

Evidano supports AI chat over uploaded documents so researchers can ask targeted questions about coded themes and run follow-up queries as new interview waves arrive.

How it maps to PLOS One limitations: the study suggests including coaches and parents in future work; Evidano lets you add those transcripts later and rerun cross-segment analyses without restarting coding from scratch.

FAQ: playing up qualitative analysis

How did researchers collect data in the PLOS One study on playing up?

Answer: The PLOS One study used online semi-structured interviews conducted over Zoom between May 1 and August 31, 2024.

Supporting detail: O’Keeffe and Lane audio-recorded each interview, generated automatic transcripts, and used reflexive thematic analysis to produce themes and exemplar quotes.

What exactly did players say about the benefits of playing up?

Answer: Players reported enhanced competence, faster skill development and psychosocial gains when playing up, according to the PLOS One article.

Supporting detail: participants said playing up exposed them to higher-quality coaching and faster decision-making environments and used quotes like, “it’s just a better level really overall” (P15) to illustrate that perceived benefit.

What risks did the PLOS One study identify for players who play up?

Answer: The PLOS One study identified increased pressure, scheduling conflicts, social exclusion and heightened perceived injury risk as main concerns.

Supporting detail: participants described feeling magnified scrutiny and clashes between matches and training, and the authors warned about overtraining and maturation-related injury risk.

How can AI change how we do qualitative research on topics like playing up?

Answer: AI accelerates transcription, harmonises coding, and enables rapid cross-segment comparisons that make findings actionable for coaches and policy makers.

Supporting detail: mirroring the PLOS One methodology, AI-enabled platforms reduce manual workload so teams can iterate interview guides, quantify theme frequencies and export stakeholder-ready reports.

Can the PLOS One qualitative findings be combined with objective measures?

Answer: Yes, the PLOS One authors recommend combining player voice with objective maturation and load data to inform bio-banding and readiness decisions.

Supporting detail: the article cautions that coaches’ subjective estimates of maturity are invalid and calls for objective measurements if bio-banding is implemented.

Conclusion & Next Steps

Recap: the PLOS One study of 15 players (mean age 14.4 ± 1.1 years) shows playing up often accelerates skill and psychosocial development but raises pressure, scheduling and injury concerns.

Actionable next step for researchers: replicate multi-stakeholder qualitative work and add objective maturation metrics before implementing bio-banding at scale, as recommended by O’Keeffe and Lane.

Actionable next step for coaches and clubs: use phased integration, autonomy-supportive coaching and social inclusion strategies to protect player welfare and retention.

If you want to turn interview transcripts into reproducible themes and stakeholder-ready evidence, explore how AI-enabled workflows speed the process and reduce manual bias with tools like Evidano.

Start analysing faster: Try Evidano for free.

Topics

playing up qualitative analysis
playing up camogie study
youth sport qualitative research
AI qualitative research

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