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Combining internet-delivered cognitive behavioural therapy and attention bias modification for reducing depressive symptoms in firefighters: a randomized controlled trial

Published online by Cambridge University Press:  25 November 2024

Xiwen Zhou
Affiliation:
Kungming Training Corps of National Fire and Rescue Administration, Kunming, China
Chengxiong Zhou
Affiliation:
Kungming Training Corps of National Fire and Rescue Administration, Kunming, China
Yexing Zheng
Affiliation:
Kungming Training Corps of National Fire and Rescue Administration, Kunming, China
Huaiyi Li
Affiliation:
Kungming Training Corps of National Fire and Rescue Administration, Kunming, China
Chao Tang
Affiliation:
Kungming Training Corps of National Fire and Rescue Administration, Kunming, China
Xiang Liu
Affiliation:
Adai Technology Co., Ltd, Beijing, China
Ming Ma
Affiliation:
Adai Technology Co., Ltd, Beijing, China
Dai Li
Affiliation:
Adai Technology Co., Ltd, Beijing, China
Yuanhui Li
Affiliation:
Adai Technology Co., Ltd, Beijing, China
Liqun Zhang
Affiliation:
Adai Technology Co., Ltd, Beijing, China
Jilai Xie
Affiliation:
Adai Technology Co., Ltd, Beijing, China
Linlin Du*
Affiliation:
Kungming Training Corps of National Fire and Rescue Administration, Kunming, China
*
Corresponding author: Linlin Du; Email: [email protected]

Abstract

Background:

Firefighters are frequently exposed to traumatic events and stressful environments and are at particularly high risk of depressive symptoms.

Aims:

The present study aimed to examine the impact of a combined internet-delivered cognitive behavioral therapy (iCBT) and attention bias modification (ABM) intervention to reduce depressive symptoms in firefighters.

Method:

The study was a randomized controlled trial carried out in Kunming, China, and involved the recruitment of 138 active firefighters as participants. The intervention lasted for an 8-week duration, during which participants participated in ABM exercises on alternating days and concurrently underwent eight modules of iCBT courses delivered through a smartphone application. Baseline and post-intervention assessments were conducted to evaluate the effects of the intervention.

Results and Discussion:

Results indicated that the combined iCBT and ABM intervention was significantly effective in reducing symptoms of depression compared with the no intervention control group (U=1644, p<0.001, Wilcoxon r=0.280). No significant change was observed in attention bias post-intervention (U=2460, p=0.737, Wilcoxon r=0.039), while a significant increase was observed in attention-bias variability (U=3172, p<0.001, Wilcoxon r=–0.287). This study provides evidence for the effectiveness of the combined iCBT and ABM intervention in reducing depressive symptoms among firefighters. This study provides conceptual support and preliminary evidence for the effectiveness of the combined iCBT and ABM intervention in reducing depressive symptoms among firefighters.

Type
Main
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of British Association for Behavioural and Cognitive Psychotherapies

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References

Aemissegger, V., Lopez-Alcalde, J., Witt, C. M., & Barth, J. (2022). Comparability of patients in trials of eHealth and face-to-face psychotherapeutic interventions for depression: meta-synthesis. Journal of Medical Internet Research, 24, e36978. https://doi.org/10.2196/36978 Google ScholarPubMed
American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders: DSM-5TM (5th edn), pp. 481589. Arlington.Google Scholar
Andersson, G., & Berger, T. (2021). Internet approaches to psychotherapy: empirical findings and future directions. In Barkham, M., Lutz, W. , & Castonguay, L. G. (eds), Bergin and Garfield’s Handbook of Psychotherapy and Behavior Change (50th Anniversary), pp. 749772. Wiley.Google Scholar
Blairy, S. (2017). La modification du biais attentionnel dans les troubles anxieux et la dépression: une revue synthétique de la littérature. Annales Médico-psychologiques, revue psychiatrique, 175, 522527. https://doi.org/10.1016/j.amp.2015.11.010 Google Scholar
Bodicherla, K. P., Shah, K., Singh, R., Arinze, N. C., Chaudhari, G., Bodicherla, K. P., Shah, K., Singh, R., Arinze, N. C., & Chaudhari, G. (2021). School-based approaches to prevent depression in adolescents. Cureus Journal of Medical Science, 13. https://doi.org/10.7759/cureus.13443 Google ScholarPubMed
Boettcher, J., Hasselrot, J., Sund, E., Andersson, G., & Carlbring, P. (2014). Combining attention training with internet-based cognitive-behavioural self-help for social anxiety: a randomised controlled trial. Cognitive Behaviour Therapy, 43, 3448. https://doi.org/10.1080/16506073.2013.809141 CrossRefGoogle ScholarPubMed
Carolan, S., Harris, P. R., & Cavanagh, K. (2017). Improving employee well-being and effectiveness: systematic review and meta-analysis of web-based psychological interventions delivered in the workplace. Journal of Medical Internet Research, 19, e271. https://doi.org/10.2196/jmir.7583 CrossRefGoogle ScholarPubMed
Deady, M., Glozier, N., Calvo, R., Johnston, D., Mackinnon, A., Milne, D., Choi, I., Gayed, A., Peters, D., Bryant, R., Christensen, H., & Harvey, S. B. (2022). Preventing depression using a smartphone app: a randomized controlled trial. Psychological Medicine, 52, 457466. https://doi.org/10.1017/S0033291720002081 Google ScholarPubMed
Epstein, J. N., Langberg, J. M., Rosen, P. J., Graham, A., Narad, M. E., Antonini, T. N., Brinkman, W. B., Froehlich, T., Simon, J. O., & Altaye, M. (2011). Evidence for higher reaction time variability for children with ADHD on a range of cognitive tasks including reward and event rate manipulations. Neuropsychology, 25, 427441. https://doi.org/10.1037/a0022155 Google ScholarPubMed
Fairburn, C. G., & Patel, V. (2017). The impact of digital technology on psychological treatments and their dissemination. Behavior Research and Therapy, 88, 1925. https://doi.org/10.1016/j.brat.2016.08.012 Google ScholarPubMed
Hardeveld, F., Spijker, J., Graaf, R. D., Nolen, W. A., & Beekman, A. T. F. (2013). Recurrence of major depressive disorder and its predictors in the general population: results from The Netherlands Mental Health Survey and Incidence Study (NEMESIS). Psychological Medicine, 43, 3948. https://doi.org/10.1017/S0033 291712002395 Google ScholarPubMed
Harvey, S. B., Henderson, M., Lelliott, P., & Hotopf, M. (2009). Mental health and employment: much work still to be done. British Journal of Psychiatry, 194, 201203. https://doi.org/10.1192/bjp.bp.108.055111 Google Scholar
Herrman, H., Kieling, C., McGorry, P., Horton, R., Sargent, J., & Patel, V. (2019). Reducing the global burden of depression: a Lancet–World Psychiatric Association Commission. The Lancet, 393, e42e43. https://doi.org/10.1016/S0140-6736(18)32408-5 Google ScholarPubMed
Hoertel, N., Blanco, C., Oquendo, M. A., Wall, M. M., Olfson, M., Falissard, B., Franco, S., Peyre, H., Lemogne, C., & Limosin, F. (2017). A comprehensive model of predictors of persistence and recurrence in adults with major depression: results from a national 3-year prospective study. Journal of Psychiatric Research, 95, 1927. https://doi.org/10.1016/j.jpsychires.2017.07.022 Google ScholarPubMed
Hu, S., Yuan, X., Li, L., Yang, Y., Long, Z., & Peng, J. (2022). Investigation on current situation of firefighters’ mental health in a certain area in Southwest China. Occupational and Health, 38, 5. https://doi.org/10.13329/j.cnki.zyyjk.2022.0666 Google Scholar
Igboanugo, S., Bigelow, P. L., & Mielke, J. G. (2021). Health outcomes of psychosocial stress within firefighters: a systematic review of the research landscape. Journal of Occupational Health, 63, e12219. https://doi.org/10.1002/1348-9585.12219 Google ScholarPubMed
Ji, G. Y. (2020). Study on the relevant issues of psychological intervention for firefighters. Firefighting Today, 5, 9899+102.Google Scholar
Joling, K. J., Smit, F., van Marwijk, H. W. J., van der Horst, H. E., Scheltens, P., Schulz, R., & van Hout, H. P. J. (2012). Identifying target groups for the prevention of depression among caregivers of dementia patients. International Psychogeriatrics, 24, 298306. https://doi.org/10.1017/S1041610211001633 CrossRefGoogle ScholarPubMed
Levis, B., Benedetti, A., & Thombs, B. D. (2019). Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: Individual participant data meta-analysis. BMJ, 365, l1476. https://doi.org/10.1136/bmj.l1476 Google ScholarPubMed
Li, H., Wei, D., Browning, M., Du, X., Zhang, Q., & Qiu, J. (2016). Attentional bias modification (ABM) training induces spontaneous brain activity changes in young women with subthreshold depression: a randomized controlled trial. Psychological Medicine, 46, 909920. https://doi.org/10.1017/S003329171500238X Google Scholar
Linardon, J., Cuijpers, P., Carlbring, P., Messer, M., & Fuller-Tyszkiewicz, M. (2019). The efficacy of app-supported smartphone interventions for mental health problems: a meta-analysis of randomized controlled trials. World Psychiatry, 18, 325336. https://doi.org/10.1002/wps.20673 Google ScholarPubMed
MacLeod, C., Mathews, A., & Tata, P. (1986). Attentional bias in emotional disorders. Journal of Abnormal Psychology, 95, 1520. https://doi.org/10.1037//0021-843x.95.1.15 Google ScholarPubMed
McDermott, R., & Dozois, D. J. A. (2019). A randomized controlled trial of Internet-delivered CBT and attention bias modification for early intervention of depression. Journal of Experimental Psychopathology, 10, 2043808719842502. https://doi.org/10.1177/2043808719842502 CrossRefGoogle Scholar
Mogg, K., Bradley, B. P., & Williams, R. (1995). Attentional bias in anxiety and depression: the role of awareness. British Journal of Clinical Psychology, 34, 1736. https://doi.org/10.1111/j.2044-8260.1995.tb01434.x Google ScholarPubMed
Murray, C. J. L., Vos, T., Lozano, R., Naghavi, M., Flaxman, A. D., Michaud, C., Ezzati, M., Shibuya, K., Salomon, J. A., Abdalla, S., Aboyans, V., Abraham, J., Ackerman, I., Aggarwal, R., Ahn, S. Y., Ali, M. K., AlMazroa, M. A., Alvarado, M., Anderson, H. R., … & Lopez, A. D. (2012). Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet, 380, 21972223. https://doi.org/10.1016/S0140-6736(12)61689-4 CrossRefGoogle ScholarPubMed
Nguyen, E., Meadley, B., Harris, R., Rajaratnam, S. M. W., Williams, B., Smith, K., Bowles, K.-A., Dobbie, M. L., Drummond, S. P. A., & Wolkow, A. P. (2023). Sleep and mental health in recruit paramedics: a 6-month longitudinal study. Sleep, 46, zsad050. https://doi.org/10.1093/sleep/zsad050 Google ScholarPubMed
Peckham, A. D., McHugh, R. K., & Otto, M. W. (2010). A meta-analysis of the magnitude of biased attention in depression. Depression and Anxiety, 27, 11351142. https://doi.org/10.1002/da.20755 CrossRefGoogle ScholarPubMed
R Development Core Team (2010). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
Rothbaum, B. O., Meadows, E. A., Resick, P., & Foy, D. W. (2000). Cognitive-behavioral therapy. In Effective treatments for PTSD: Practice Guidelines from the International Society for Traumatic Stress Studies (pp. 320325). Guilford Press.Google Scholar
Saijo, Y., Ueno, T., & Hashimoto, Y. (2007). Job stress and depressive symptoms among Japanese firefighters. American Journal of Industrial Medicine, 50, 470480. https://doi.org/10.1002/ajim.20460 Google Scholar
Stanley, I. H., Boffa, J. W., Smith, L. J., Tran, J. K., Schmidt, N. B., Joiner, T. E., & Vujanovic, A. A. (2018). Occupational stress and suicidality among firefighters: examining the buffering role of distress tolerance. Psychiatry Research, 266, 9096. https://doi.org/10.1016/j.psychres.2018.05.058 Google ScholarPubMed
Sun, X., Li, X., Huang, J., & An, Y. (2020). Prevalence and predictors of PTSD, depression and posttraumatic growth among Chinese firefighters. Archives of Psychiatric Nursing, 34, 1418. https://doi.org/10.1016/j.apnu.2019.12.007 Google ScholarPubMed
ten Have, M., de Graaf, R., van Dorsselaer, S., Tuithof, M., Kleinjan, M., & Penninx, B. W. J. H. (2018). Recurrence and chronicity of major depressive disorder and their risk indicators in a population cohort. Acta Psychiatrica Scandinavica, 137, 503515. https://doi.org/10.1111/acps.12874 Google Scholar
World Health Organization (2017). Depression and other common mental disorders: global health estimates (No. WHO/MSD/MER/2017.2).Google Scholar
Zainal, N. H., Hellberg, S. N., Kabel, K. E., Hotchkin, C. M., & Baker, A. W. (2023). Cognitive behavioral therapy (CBT) plus attention bias modification (ABM) reduces anxiety sensitivity and depressive symptoms in panic disorder: a pilot randomized trial. Scandinavian Journal of Psychology, 64, 390400. https://doi.org/10.1111/sjop.12902 CrossRefGoogle ScholarPubMed
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