Beyond self-reflection: introducing the concept of rumination in personal informatics

by | May 10, 2021 | Research Publications

Author(s):

Elizabeth Victoria Eikey

Clara Marques Caldeira

Mayara Costa Figueiredo

Yunan Chen

Jessica L. Borelli

Melissa Mazmanian

Kai Zheng

Abstract:

Personal informatics tools can help users self-reflect on their experiences. When reflective thought occurs, it sometimes leads to negative thought and emotion cycles. To help explain these cycles, we draw from Psychology to introduce the concept of rumination—anxious, perseverative cognition focused on negative aspects of the self—as a result of engaging with personal data. Rumination is an important concept for the Human Computer Interaction community because it can negatively affect users’ well-being and lead to maladaptive use. Thus, preventing and mitigating rumination is beneficial. In this conceptual paper, we differentiate reflection from rumination. We also explain how self-tracking technologies may inadvertently lead to rumination and the implications this has for design. Our goal is to expand self-tracking research by discussing these negative cycles and encourage researchers to consider rumination when studying, designing, and promoting tools to prevent adverse unintended consequences among users.

Documentation:

https://doi.org/10.1007/s00779-021-01573-w

References::
  1. Li I, Dey A, Forlizzi J (2011) Understanding my data, myself: supporting self-reflection with ubicomp technologies. In: Proceedings of the 13th international conference on Ubiquitous Computing. ACM, Beijing, China, pp 405–414Chapter  Google Scholar 
  2. Baumer EPS, Khovanskaya V, Matthews M, Reynolds L, Schwanda Sosik V, Gay G (2014) Reviewing reflection: on the use of reflection in interactive system design. Proc 2014 Conf Des Interact Syst – DIS ’14 93–102. https://doi.org/10.1145/2598510.2598598
  3. Meyer AN, Murphy GC, Zimmermann T, Fritz T (2017) Retrospecting on work and productivity: a study on self-monitoring software developers’ work. Proc ACM Hum-Comput Interact 1(79):1–79:24. https://doi.org/10.1145/3134714Article  Google Scholar 
  4. Li I, Dey A, Forlizzi J (2010) A stage-based model of personal informatics systems. In: Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM, Atlanta, Georgia, p 557 Google Scholar 
  5. Epstein DA, Ping A, Fogarty J, Munson SA (2015) A lived informatics model of personal informatics. Proc 2015 ACM Int Jt Conf Pervasive Ubiquitous Comput – UbiComp ’15 731–742. https://doi.org/10.1145/2750858.2804250
  6. Rooksby J, Rost M, Morrison A, Chalmers MC (2014) Personal tracking as lived informatics. Proceedings of the CHI Conference on Human Factors in Computing Systems, In, pp 1163–1172 Google Scholar 
  7. Eikey EV, Reddy MC (2017) “It’s definitely been a journey”: a qualitative study on how women with eating disorders use weight loss apps. In: ACM CHI Conference on Human Factors in Computing Systems (CHI ’17). ACM, Denver, CO, pp 1–13 Google Scholar 
  8. Figueiredo MC, Caldeira C, Reynolds TL, Victory S, Zheng K, Chen Y (1AD) Self-tracking for fertility care: collaborative support for a highly personalized problem. Pacmhci (Cscw 2018) 2
  9. Kelley C, Lee B, Wilcox L (2017) Self-tracking for mental wellness: understanding expert perspectives and student experiences. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, pp 629–641Chapter  Google Scholar 
  10. Ancker JS, Witteman HO, Hafeez B, Provencher T, Van De Graaf M, Wei E (2015) “You get reminded you’re a sick person”: personal data tracking and patients with multiple chronic conditions. J Med Internet Res 17. 17:e202. https://doi.org/10.2196/jmir.4209
  11. Epstein DA, Caraway M, Johnston C, Ping A, Fogarty J, Munson SA (2016) Beyond abandonment to next steps: understanding and designing for life after personal informatics tool use. In: Proceedings of the CHI Conference on Human Factors in Computing Systems, pp 1109–1113 Google Scholar 
  12. Mols I, van den Hoven E, Eggen B (2016) Informing design for reflection: an overview of current everyday practices. In: NordiCHI. ACM, Gothenburg, Sweden, pp 1–10 Google Scholar 
  13. Smith JM, Alloy LB (2010) A roadmap to rumination: a review of the definition, assessment, and conceptualization of this multifaceted construct. Clin Psychol Rev 29:116–128. https://doi.org/10.1016/j.cpr.2008.10.003.AArticle  Google Scholar 
  14. Morin A (2006) Levels of consciousness and self-awareness: a comparison and integration of various neurocognitive views. Conscious Cogn 15:358–371. https://doi.org/10.1016/j.concog.2005.09.006Article  Google Scholar 
  15. Lengelle R, Luken T, Meijers F (2016) Is self-reflection dangerous? Preventing rumination in career learning. Aust J Career Dev 25:99–109. https://doi.org/10.1177/1038416216670675Article  Google Scholar 
  16. Trapnell PD, Campbell JD (1999) Trapnell and Campbell (1999).pdf. J. Pers. Soc. Psychol. 76:284–304Article  Google Scholar 
  17. van Dijk ET, Beute F, Westerink JHD, Ijsselsteijn WA (2015) Unintended effects of self-tracking. In: CHI’15. Seoul, South-Korea, p 5 Google Scholar 
  18. Konrad A, Isaacs E, Whittaker S (2016) Technology-mediated memory: is technology altering our memories and interfering with well-being? ACM Trans Comput Interact 23:1–29. https://doi.org/10.1145/2934667Article  Google Scholar 
  19. Konrad A, Tucker S, Crane J, Whittaker S (2016) Technology and reflection: mood and memory mechanisms for well-being. Psychol Well Being 6:5. https://doi.org/10.1186/s13612-016-0045-3Article  Google Scholar 
  20. Hollis V, Konrad A, Springer A, Antoun M, Antoun C, Martin R, Whittaker S (2017) What does all this data mean for my future mood? Actionable Analytics and Targeted Reflection for Emotional Well-Being. Human-Computer Interact 32:208–267. https://doi.org/10.1080/07370024.2016.1277724Article  Google Scholar 
  21. Isaacs E, Konrad A, Walendowski A, Lennig T, Hollis V, Whittaker S (2013) Echoes from the past: how technology mediated reflection improves well-being. Conf Hum Factors Comput Syst – Proc:1071–1080. https://doi.org/10.1145/2470654.2466137
  22. Harrington R, Loffredo DA (2011) Insight, rumination, and self-reflection as predictors of well-being. J Psychol Interdiscip Appl 145:39–57. https://doi.org/10.1080/00223980.2010.528072Article  Google Scholar 
  23. Rawal A, Park RJ, Williams JMG (2010) Rumination, experiential avoidance, and dysfunctional thinking in eating disorders. Behav Res Ther 48:851–859. https://doi.org/10.1016/j.brat.2010.05.009Article  Google Scholar 
  24. Morin A (2003) Let’s Face It. Evol Psychol 1:161–171Article  Google Scholar 
  25. Joireman JA, III LP, Hammersla J (2002) Empathy and the self-absorption paradox: support for the distinction between self-rumination and self-reflection. Self Identity 1:53–65. https://doi.org/10.1080/152988602317232803Article  Google Scholar 
  26. Atkins S, Murphy K (1993) Reflection: a review of the literature. J Adv Nurs 18:1188–1192. https://doi.org/10.1046/j.1365-2648.1993.18081188.xArticle  Google Scholar 
  27. Takano K, Tanno Y (2009) Self-rumination, self-reflection, and depression: self-rumination counteracts the adaptive effect of self-reflection. Behav Res Ther 47:260–264. https://doi.org/10.1016/j.brat.2008.12.008Article  Google Scholar 
  28. Ryan P (2009) Integrated theory of health behavior change: background and intervention development. Clin Nurse Spec 23:161–172. https://doi.org/10.1097/NUR.0b013e3181a42373.IntegratedArticle  Google Scholar 
  29. Pirzadeh A, He L. Human ES-CEA on, 2013 undefined Personal informatics and reflection: a critical examination of the nature of reflection. dl.acm.org
  30. Watkins ER (2008) Constructive and unconstructive repetitive thought. Psychol Bull 134:163–206. https://doi.org/10.1037/0033-2909.134.2.163Article  Google Scholar 
  31. Choe EK, Kientz JA, Halko S, Fonville A, Sakaguchi D, Watson NF (2010) Opportunities for computing to support healthy sleep behavior. In: CHI ’10 Extended Abstracts on Human Factors in Computing Systems. ACM, New York, NY, USA, pp 3661–3666 Google Scholar 
  32. Baumer EPS (2015) Reflective Informatics. Proc 33rd Annu ACM Conf Hum Factors Comput Syst – CHI ’15 585–594. https://doi.org/10.1145/2702123.2702234
  33. Chen R, Orand M, Choi S, CHI LC-P of the 2018, 2018 undefined An empirical exploration of mindfulness design using solo travel domain. dl.acm.org
  34. Hollis V, Konrad A, Whittaker S (2015) Change of heart: emotion tracking to promote behavior change. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, pp 2643–2652Chapter  Google Scholar 
  35. Hollis V (2015) of Hea art : Emo otion T Tracking g to Pro omote Behav ior Cha ange. 2643–2652
  36. Figueiredo MC, Caldeira C, Eikey EV, Mazmanian M, Chen Y (2018) Engaging with health data: the interplay between self-tracking activities and emotions in fertility struggles. In: CSCW 2018. ACM, Jersey City Google Scholar 
  37. Morin A (2017) Toward a glossary of self-related terms. Front Psychol 8:1–9. https://doi.org/10.3389/fpsyg.2017.00280
  38. Nolen-Hoeksema (2015) Rethinking rumination. 19:1301–1307. https://doi.org/10.1111/j.1745-6924.2008.00088.x
  39. Martin L, Tesser A (1996) Ruminative thoughts. Psychology Press
  40. McIntosh WD, Harlow TF, Martin LL (1995) Linkers and nonlinkers: goal beliefs as a moderator of the effects of everyday hassles on rumination, depression, and physical complaints. J Appl Soc Psychol 25:1231–1244. https://doi.org/10.1111/j.1559-1816.1995.tb02616.xArticle  Google Scholar 
  41. Michl LC, Mclaughlin KA, Shepherd K, Nolen-hoeksema S (2013) Rumination as a mechanism linking stressful life events to symptoms of depression and anxiety: longitudinal evidence in early adolescents and adults. J Abnorm Psychol 122:339–352. https://doi.org/10.1037/a0031994.RuminationArticle  Google Scholar 
  42. Blagden JC, Craske MG (1996) Effects of active and passive rumination and distraction: a pilot replication with anxious mood. J Anxiety Disord 10:243–252. https://doi.org/10.1016/0887-6185(96)00009-6Article  Google Scholar 
  43. Mellings TMB, Alden LE (2000) Cognitive processes in social anxiety: the effects of self-focus, rumination and anticipatory processing. Behav Res Ther 38:243–257. https://doi.org/10.1016/S0005-7967(99)00040-6Article  Google Scholar 
  44. Nolen-Hoeksema S (2000) The role of rumination in dpressive disorders and mixed ancity/depressive symptoms. J Abnorm Psychol 109:504–511Article  Google Scholar 
  45. Roger D, Najarian B (1989) The construction and validation of a new scale for measuring emotion control. Pers Individ Dif 10:845–853. https://doi.org/10.1016/0191-8869(89)90020-2Article  Google Scholar 
  46. Rusting CL, Nolen-Hoeksema S (1998) Regulating responses to anger: effects of rumination and distraction on angry mood. J Pers Soc Psychol 74:790–803. https://doi.org/10.1037/0022-3514.74.3.790Article  Google Scholar 
  47. Caprara GV, Gargaro T, Pastorelli C, Prezza M, Renzi P, Zelli A (1987) Individual differences and measures of aggression in laboratory studies. Pers Individ Dif 8:885–893. https://doi.org/10.1016/0191-8869(87)90140-1Article  Google Scholar 
  48. Miranda R, Nolen-Hoeksema S (2007) Brooding and reflection: rumination predicts suicidal ideation at 1-year follow-up in a community sample. Behav Res Ther 45:3088–3095. https://doi.org/10.1016/j.brat.2007.07.015Article  Google Scholar 
  49. Morrison R, O’Connor RC (2008) A systematic review of the relationship between rumination and suicidality. Suicide Life-Threatening Behav 38:523–538. https://doi.org/10.1521/suli.2008.38.5.523Article  Google Scholar 
  50. Nolen-Hoeksema S, Morrow J (1993) Effects of rumination and distraction on naturally occurring depressed mood. Cogn Emot 7:561–570. https://doi.org/10.1080/02699939308409206Article  Google Scholar 
  51. Şimşek ÖF (2013) The relationship between language use and depression: illuminating the importance of self-reflection, self-rumination, and the need for absolute truth. J Gen Psychol 140:29–44. https://doi.org/10.1080/00221309.2012.713407Article  Google Scholar 
  52. Butler LD, Nolen-Hoeksema S (1994) Gender differences in responses to depressed mood in a college sample. Sex Roles 30:331–346. https://doi.org/10.1007/BF01420597Article  Google Scholar 
  53. Elliott I, Coker S (2008) Independent self-construal, self-reflection, and self-rumination: a path model for predicting happiness. Aust J Psychol 60:127–134. https://doi.org/10.1080/00049530701447368Article  Google Scholar 
  54. Greenberg J, Musham C (1981) Avoiding and seeking self-focused attention. J Res Pers 15:191–200. https://doi.org/10.1016/0092-6566(81)90018-0Article  Google Scholar 
  55. Duval S, Wicklund RA (1972) A theory of objective self awareness. Academic Press, Oxford, England Google Scholar 
  56. Ayobi A (2018) Informing the Design of Personal Informatics Technologies for Unpredictable Chronic Conditions. In: CHI’18 Extended Abstracts, pp 1–4 Google Scholar 
  57. Katz D, Price B, Holland S, Dalton N (2018) Data, data everywhere, and still too hard to link: insights from user interactions with diabetes apps. Montréal, CanadaBook  Google Scholar 
  58. Ayobi A, Marshall P, Cox AL, Chen Y (2017) Quantifying the body and caring for the mind: self-tracking in multiple sclerosis. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, pp 6889–6901Chapter  Google Scholar 
  59. Horvath L, Penkler M, Harrer S, Sicart M (2018) Fitter, happier, more productive? The Normative Ontology of Fitness Trackers. Ext Abstr 2018 CHI Conf Hum Factors Comput Syst 1–10
  60. Eikey EV (2017) The health journey of college women with eating disorder behaviors: a qualitative study on the use and unintended consequences of mobile weight loss applications. The Pennsylvania State University
  61. Snyder J, Murnane E, Lustig C, Voida S (2019) Visually encoding the lived experience of bipolar disorder. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp 1–14 Google Scholar 
  62. Consolvo S, McDonald DW, Landay JA (2009) Theory-driven design strategies for technologies that support behavior change in everyday life. Proc 27th Int Conf Hum factors Comput Syst – CHI 09:405. https://doi.org/10.1145/1518701.1518766Article  Google Scholar 
  63. Kanfer FH, Gaelick L (1975) Self-management methods. In: Helping People Change: A Textbook of Methods. England, Oxford, pp 309–355 Google Scholar 
  64. Katz D, Dalton N, Holland S, O’Kane A, Price BA (2017) Questioning the reflection paradigm for diabetes mobile apps. Lect Notes Inst Comput Sci Soc Telecommun Eng LNICST 181 LNICST:315–326 . doi: https://doi.org/10.1007/978-3-319-49655-9_39
  65. McFall RM (1970) Effects of self-monitoring on normal smoking behavior. J Consult Clin Psychol 35:135–142Article  Google Scholar 
  66. Espeland WN, Stevens ML (2008) A sociology of quantification. Arch Eur Sociol 49:401–436. https://doi.org/10.1017/S0003975609000150Article  Google Scholar 
  67. Abend P, Fuchs M, Reichert R, Selves IQ, Bodies S (2016) Quantified selves and statistical bodies. Digit Cult Soc 2
  68. Lupton D (2013) Quantifying the body: monitoring and measuring health in the age of mHealth technologies. Crit Public Health 23:393–403. https://doi.org/10.1080/09581596.2013.794931Article  Google Scholar 
  69. Pennebaker JW, Chung CK (2012) Expressive writing: connections to physical and mental health
  70. Chancellor S, Birnbaum ML, Caine ED, Silenzio VMB, De Choudhury M (2019) A taxonomy of ethical tensions in inferring mental health states from social media. In: Proceedings of the 2019 Conference on Fairness, Accountability, and Transparency, pp 79–88Chapter  Google Scholar 
  71. De Choudhury M, Kiciman E, Dredze M, Coppersmith G, Kumar M (2016) Discovering shifts to suicidal ideation from mental health content in social media. In: Conference on Human Factors in Computing Systems – Proceedings, pp 2098–2110 Google Scholar 
  72. Chancellor S (2018, 2018) Computational methods to understand deviant mental wellness communities. Conf Hum Factors Comput Syst – Proc:1–4. https://doi.org/10.1145/3170427.3173021
  73. Manikonda L, De Choudhury M (2017, 2017) Modeling and understanding visual attributes of mental health disclosures in social media. Conf Hum Factors Comput Syst – Proc:170–181. https://doi.org/10.1145/3025453.3025932
  74. Tran T, Nathan-Roberts D (2018) Design considerations in wearable technology for patients with bipolar disorder. Proc Hum Factors Ergon Soc 2:1187–1191. https://doi.org/10.1177/1541931218621273Article  Google Scholar 
  75. Rooksby J, Morrison A, Murray-Rust D (2019) Student perspectives on digital phenotyping the acceptability of using smartphone data to assess mental health. Conf Hum Factors Comput Syst – Proc. https://doi.org/10.1145/3290605.3300655
  76. Sweeney PD, Anderson K, Bailey S (1986) Attributional style in depression: a meta-analytic review. J Personal Soc Psychol 50:1–2Article  Google Scholar 
  77. Lo CSL, Ho SMY, Hollon SD (2010) The effects of rumination and depressive symptoms on the prediction of negative attributional style among college students. Cogn Ther Res 34:116–123. https://doi.org/10.1007/s10608-009-9233-2Article  Google Scholar 
  78. Farchione TJ, Fairholme CP, Ellard KK, Boisseau CL, Thompson-Hollands J, Carl JR, Gallagher MW, Barlow DH (2012) Unified protocol for transdiagnostic treatment of emotional disorders: a randomized controlled trial. Behav Ther 43:666–678. https://doi.org/10.1016/j.beth.2012.01.001Article  Google Scholar 
  79. Fox S, Duggan M (2012) Mobile health 2012. Pew Internet Am Life Proj
  80. Krebs P, Duncan DT (2015) Health app use among us mobile phone owners: a national survey. JMIR mHealth uHealth 3:1–12. https://doi.org/10.2196/mhealth.4924Article  Google Scholar 
  81. Bol N, Helberger N, Weert JCM (2018) Differences in mobile health app use: a source of new digital inequalities? Inf Soc 34:183–193. https://doi.org/10.1080/01972243.2018.1438550Article  Google Scholar 
  82. Yaemsiri S, Slining MM, Agarwal SK (2011) Perceived weight status, overweight diagnosis, and weight control among US adults: the NHANES 2003–2008 Study. Int J Obes 35:1063–1070. https://doi.org/10.1038/ijo.2010.229Article  Google Scholar 
  83. Ahern AL, Bennett KM, Kelly M, Hetherington MM (2011) A qualitative exploration of young women’s attitudes towards the thin ideal. J Health Psychol 16:70–79. https://doi.org/10.1177/1359105310367690Article  Google Scholar 
  84. Spettigue W, Henderson KA (2004) Eating disorders and the role of the media. Can Child Adolesc Psychiatry Rev 13:16–19 Google Scholar 
  85. Bucchianeri MM, Neumark-Sztainer D (2014) Body dissatisfaction: an overlooked public health concern. J Public Ment Health 13:64–69. https://doi.org/10.1108/JPMH-11-2013-0071Article  Google Scholar 
  86. Juarascio AS, Forman EM, Timko CA, Herbert JD, Butryn M, Lowe M (2011) Implicit internalization of the thin ideal as a predictor of increases in weight, body dissatisfaction, and disordered eating. Eat Behav 12:207–213. https://doi.org/10.1016/j.eatbeh.2011.04.004Article  Google Scholar 
  87. Reba-Harrelson L, Von Holle A, Hamer RM, Swann R, Reyes ML, Bulik CM (2009) Patterns and prevalence of disordered eating and weight control behaviors in women ages 25-45. Eat Weight Disord 14:190–198. https://doi.org/10.1007/BF03325116Article  Google Scholar 
  88. Fayet F, Petocz P, Samman S (2012) Prevalence and correlates of dieting in college women: a cross sectional study. Int J Women’s Heal 4:405–411. https://doi.org/10.2147/IJWH.S33920Article  Google Scholar 
  89. Ackard DM, Croll JK, Kearney-Cooke A (2002) Dieting frequency among college females: association with disordered eating, body image, and related psychological problems. J Psychosom Res 52:129–136. https://doi.org/10.1016/S0022-3999(01)00269-0Article  Google Scholar 
  90. Wade TD, Keski-Rahkonen A, Hudson J (2011) Epidemiology of eating disorders. In: 3rd (ed) Textbook in Psychiatric Epidemiology. M. Tsuang. Wiley, New York, pp 343–360Chapter  Google Scholar 
  91. Shisslak CM, Crago M, Estes LS (1995) The spectrum of eating disturbances. Int J Eat Disord 18:209–219. Article  Google Scholar 
  92. Neumark-Sztainer D, Wall M, Guo J, Story M, Haines J, Eisenberg M (2006) Obesity, disordered eating, and eating disorders in a longitudinal study of adolescents: how do dieters fare 5 years later? J Am Diet Assoc 106:559–568. https://doi.org/10.1016/j.jada.2006.01.003Article  Google Scholar 
  93. Quick VM, Byrd-Bredbenner C (2013) Disturbed eating behaviours and associated psychographic characteristics of college students. J Hum Nutr Diet 26:53–63. https://doi.org/10.1111/jhn.12060Article  Google Scholar 
  94. Schwitzer AM, Choate LH (2015) College women eating disorder diagnostic profile and DSM-5. J Am Coll Heal 63:73–78. https://doi.org/10.1080/07448481.2014.963110Article  Google Scholar 
  95. Schwitzer AM (2012) Diagnosing, conceptualizing, and treating eating disorders not otherwise specified: a comprehensive practice model. J Couns Dev 90:281–289. https://doi.org/10.1002/j.1556-6676.2012.00036.xArticle  Google Scholar 
  96. Berg KC, Frazier P, Sherr L (2009) Change in eating disorder attitudes and behavior in college women: prevalence and predictors. Eat Behav 10:137–142. https://doi.org/10.1016/j.eatbeh.2009.03.003Article  Google Scholar 
  97. Eisenberg D, Nicklett EJ, Roeder K, Kirz NE (2011) Eating disorder symptoms among college students: prevalence, persistence, correlates, and treatment-seeking. J Am Coll Heal 59:70–707. https://doi.org/10.1038/nature13314.AArticle  Google Scholar 
  98. Reinking MF, Alexander LE, Louis S (2005) Prevalence of disordered-eating behaviors athletes and nonathletes. J Athl Train 40:47–51 Google Scholar 
  99. Hoerr SL, Bokram R, Lugo B, Bivins T, Keast DR (2002) Risk for disordered eating relates to both gender and ethnicity for college students. J Am Coll Nutr 21:307–314. https://doi.org/10.1080/07315724.2002.10719228Article  Google Scholar 
  100. Choe EK, Lee B, Zhu H, Riche NH, Baur D (2017) Understanding self-reflection: how people reflect on personal data through visual data exploration. Proc EAI Int Conf Pervasive Comput Technol Healthc (PervasiveHealth ’17)
  101. Gilbert P, Procter S (2006) For people with high shame and self-criticism: overview and pilot study of a group therapy approach. 379:353–379
  102. Neff KD, Rude SS, Kirkpatrick KL (2007) An examination of self-compassion in relation to positive psychological functioning and personality traits. J Res Pers 41:908–916. https://doi.org/10.1016/j.jrp.2006.08.002Article  Google Scholar 
  103. Neff K (2003) The development and validation of a scale to measure self-compassion. Self Identity 2:223–250. https://doi.org/10.1080/15298860309027Article  Google Scholar 
  104. Mantelou A, Karakasidou E (2017) The effectiveness of a brief self-compassion intervention program on self-compassion, positive and negative affect and life satisfaction. Psychology 8:590–610. https://doi.org/10.4236/psych.2017.84038Article  Google Scholar 
  105. Smeets E, Neff K, Alberts H, Peters M (2014) Meeting suffering with kindness: effects of a brief self-compassion intervention for female college students. J Clin Psychol 70:794–807. https://doi.org/10.1002/jclp.22076Article  Google Scholar 
  106. McAdams DP, McLean KC (2013) Narrative identity. Curr Dir Psychol Sci 22:233–238. https://doi.org/10.1177/0963721413475622Article  Google Scholar 
  107. Adler JM, Turner AF, Brookshier KM, Monahan C, Olin FW, Albaugh M (2015) Mental health over several years. 108:476–496. https://doi.org/10.1037/a0038601.Variation
  108. Adler JM, Poulin MJ (2009) The political is personal: narrating 9/11 and psychological well-being. J Pers 77:903–932Article  Google Scholar 
  109. Baddeley J, Singer JA (2010) A loss in the family: silence, memory, and narrative identity after bereavement. Memory 18:198–207. https://doi.org/10.1080/09658210903143858Article  Google Scholar 
  110. McAdams DP, Reynolds J, Lewis M, Patten AH, Bowman PJ (2001) When bad things turn good and good things turn bad: sequences of redemption and contamination in life narrative and then-relation to psychosocial adaptation in midlife adults and in students. Personal Soc Psychol Bull 27:474–485. https://doi.org/10.1177/0146167201274008Article  Google Scholar 
  111. Dunlop WL, Tracy JL (2013) Sobering stories: narratives of self-redemption predict behavioral change and improved health among recovering alcoholics. J Pers Soc Psychol 104:576–590. https://doi.org/10.1037/a0031185Article  Google Scholar 
  112. Lodi-Smith J, Geise AC, Roberts BW, Robins RW (2009) Narrating personality change. J Pers Soc Psychol 96:679–689. https://doi.org/10.1037/a0014611Article  Google Scholar 
  113. Isaacs E, Konrad A, Walendowski A, Lennig T, Hollis V, Whittaker S (2013) Echoes from the past: how technology mediated reflection improves well-being. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, pp 1071–1080Chapter  Google Scholar 
  114. Hilt LM Attribution retraining for therapeutic change: theory, practice, and future directions. Imagin Cogn Personal 23:289–307
  115. Epstein DA, Cordeiro F, Fogarty J, Hsieh G, Munson SA (2016) Crumbs: lightweight daily food challenges to promote engagement and mindfulness. Proc 2016 CHI Conf Hum Factors Comput Syst:5632–5644. https://doi.org/10.1145/2858036.2858044
  116. Peng F, LaBelle V, Yue E, Picard R (2018) A trip to the moon: personalized animated movies for self-reflection. https://doi.org/10.1145/3173574.3173827
  117. Rubenstein LM, Freed RD, Shapero BG, Fauber RL, Alloy LB (2016) Cognitive attributions in depression: bridging the gap between research and clinical practice. J Psychother Integr 26:103–115. https://doi.org/10.1037/int0000030.CognitiveArticle  Google Scholar