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(as of Apr 19, 2025 17:44:19 UTC – Details)
Recovering addicts are faced with many challenges, and these challenges can often extend to their romantic partners. During the recovery period, couples often struggle with overcoming feelings of betrayal and frustration, and may have a hard time rebuilding trust and closeness. While there are many resources available to recovering addicts, there are limited resources for the people who love them.
In Loving Someone in Recovery, therapist Beverly Berg offers powerful tools for the partners of recovering addicts. Based in mindfulness, attachment theory, and neurobiology, this book will help readers sustain emotional stability in their relationships, increase effective communication, establish boundaries, and take real steps toward reigniting intimacy.
The material in this book is drawn from the author’s successful Conscious Couples Recovery Workshop. With more than 25 years in the field, she has developed a unique set of exercises that address the issues faced by couples in recovery. This book addresses the roles that both partners play in recovery, and aims to help readers develop a new appreciation for one another and improve self-confidence and acceptance.
The road to recovery is never an easy one, but by building a strong support system, the chances of success are exponentially greater. For more information on Berg’s work, visit consciouscouplesrecovery.com
ASIN : 1608828980
Publisher : New Harbinger Publications; 1st edition (February 2, 2014)
Language : English
Paperback : 232 pages
ISBN-10 : 9781608828982
ISBN-13 : 978-1608828982
Item Weight : 11.2 ounces
Dimensions : 6 x 0.65 x 9 inches
Customers say
Customers find the book helpful and informative, with one review highlighting its clear examples and exercises. Moreover, they appreciate its readability and consider it the best relationship book for couples in recovery, with one customer noting it’s a must-read for both therapists and couples. Additionally, the book features friendly humor and a loving approach.
AI-generated from the text of customer reviews
