AI Qualitative Analysis of Help-Seeking in Criminal Justice

The PLOS ONE study (published July 30, 2026) found that help-seeking among people in contact with the criminal justice system is not purely individual but emerges from interactions between desire, ability, and social context, especially network-level influences (PLOS ONE).

• 50 interviews were analysed in the study conducted between November 1, 2023 and July 31, 2024, according to the PLOS ONE article published on July 30, 2026.
• The PLOS ONE article (July 30, 2026) cites prevalence estimates of more than 40% meeting criteria for a substance use disorder, over 10% for major depressive or psychotic disorders, and 75% for any personality disorder in related probation samples.
• The PLOS ONE study (July 30, 2026) reports that relational influences in social networks (norms, trust, and resource flows) often enabled or blocked help-seeking, indicating multi-level interventions are required.

Answer: The PLOS ONE study used semi-structured interviews and social network methods to map influences on help-seeking among justice-involved people living in the community.

According to the PLOS ONE article (published July 30, 2026), researchers recruited 50 adults with criminal justice contact from two Scottish local authority areas and interviewed them between November 1, 2023 and July 31, 2024.

According to the PLOS ONE article (July 30, 2026), data collection combined audio-recorded interviews with participant-aided sociograms using Network Canvas, transcripts were pseudo-anonymised, and framework analysis with NVivo was used to code themes.

Direct participant quotes that illustrate themes included statements such as "I have dealt with it for almost twenty odd years by myself… I don’t like going to doctors because I think they are a waste of time, " attributed to participant P12 in the PLOS ONE study, and "you just kind of can’t get away from the social, every time you try and do something good basically they will get you on it and you will be wrecked and miss what you are going to do, " attributed to participant P13 in the PLOS ONE study.

Answer: Researchers and teams designing interventions must measure relational and contextual variables, not just individual attitudes.

According to the PLOS ONE article (published July 30, 2026), social network norms, epistemic mistrust, and local service availability frequently determined whether help-seeking attempts succeeded or failed.

According to the PLOS ONE article (July 30, 2026), qualitative designs that combine participant-aided sociograms with interviews can surface how network structure (closed versus diverse) alters access to emotional, informational, and practical resources.

Practical takeaway: plan instruments and coding frameworks that tag relational dynamics (endorsements, sabotage, trust) and time-stamp events such as crises that trigger help-seeking, as these were decisive in the PLOS ONE analysis.

Answer: AI-enabled qualitative analysis makes it practical to scale rigorous, relationally-aware research like the PLOS ONE study and to transform findings into actionable intervention targets.

Researchers can reproduce the PLOS ONE approach (Connell et al., published July 30, 2026) by combining interviews, participant-aided sociograms, and a framework that codes desire, ability, and context while paying special attention to network-level norms and trust.

If you run qualitative or mixed-methods studies and need faster, reproducible synthesis of quotes, codes, and cross-segment frequencies, Evidano can help, see our features for tools that match this workflow.

To try these capabilities on your own interviews and sociogram outputs, Try Evidano for free.