Guided internet interventions for depression: impact of sociodemographic factors on treatment outcome in Indonesia

Junus M. van der Wal, Retha Arjadi, Maaike H. Nauta, Huibert Burger, Claudi L. H. Bockting

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)

Abstract

Depression is the leading cause of disability worldwide, but an alarming treatment gap exists, especially in lower- and middle income countries (LMIC), where people are exposed to many societal and sociodemographic risk factors. As internet access increases in LMIC, online interventions could decrease this gap, especially when shown suitable for all demographics, including vulnerable groups with low socioeconomic status (SES). We used mixed-model analysis to explore moderating effects of sociodemographic factors (age, sex, education level, SES and urbanicity) on treatment effect in a recent trial in Indonesia, comparing guided online behavioral activation versus online psychoeducation only for depression, in 313 participants from (sub)urban areas. Outcome measures were self-reported Patient Health Questionnaire 9 (PHQ-9) and Inventory of Depressive Symptomatology (IDS-SR). Without correction for multiple testing, we found urbanicity to moderate treatment effect, with stronger treatment effect in suburban relative to urban participants (IDS-SR 24 weeks past baseline, p = 0.04) and a trend towards moderation by SES, with stronger treatment effect in low SES groups (PHQ-9 10 weeks past baseline, p = 0.07). These exploratory results suggest online treatments are a promising mental health intervention for all demographics in a (sub)urban LMIC setting, but hypothesis-testing studies including rural participants are warranted.
Original languageEnglish
Article number103589
JournalBehaviour research and therapy
Volume130
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Depression
  • Dropout rates
  • Indonesia
  • Internet intervention
  • Lay counsellor
  • Lower- and middle income country
  • Moderators
  • Sociodemographic factors
  • Treatment effect

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