An Interpretative Phenomenological Analysis of Extratherapeutic Factors Leading Criminal Offenders to Successful Rehabilitation.

  • Published In: Journal of Systemic Therapies, 2023, v. 42, n. 2. P. 86 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wyble, John W.; Solórzano, Bernadette H. 3 of 3

Abstract

As systems shift from punitive to rehabilitative measures, correctional departments aim to reduce recidivism; however, an overlooked consideration is the quality of systems and interactions to which the person returns to live. In this qualitative study, we examined if extratherapeutic factors were essential for recidivism reduction. We analyzed two interviews conducted with former offenders to examine their lived experiences surrounding incarceration, rehabilitation, and reintegration. Five themes (Loyalty, Situational Stressors, Community, Work/Livelihood, Support System) and one subtheme (Hope) emerged after analyzing the transcribed interviews. Although each participant's experience was vastly different, shared meanings emerged leading to common themes between participants ' lived experiences. Interestingly enough, hope emerged as essential for one participant. Results indicated factors influencing change can occur, promoting successful community reentry with assistance from personal support systems. Limitations are covered along with ideas for future research, as well as implications for clinical practice in psychology. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Systemic Therapies. 2023/06, Vol. 42, Issue 2, p86
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2023
  • ISSN:1195-4396
  • DOI:10.1521/jsyt.2023.42.2.86
  • Accession Number:173452786
  • Copyright Statement:Copyright of Journal of Systemic Therapies is the property of Guilford Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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