Adaptation and validation of a structured version of the Hamilton Depression Rating Scale for use by non-clinicians in South Africa (AFFIRM-HDRS)

"Trajectories of treatment response in a cognitive-behavioral therapy intervention for depression and adherence in persons with HIV in South Africa"

BACKGROUND

People with HIV (PHW) are at greater risk of depression than the general population. Insight into the time-to-treatment-response and predictors of response to psychotherapy may improve implementation in primary care.

METHODS

We assessed depression treatment response among 80 participants in a trial of cognitive-behavioral therapy for adherence and depression (CBT-AD) for PWH with MDD and suboptimal antiretroviral therapy (ART) adherence. Participants self-reported depressive symptoms (CESD) at each therapy session. Clinicians assessed participants' depression (HAMD), along with potential predictors of response, every four months for one year. Latent class analyses examined classes of responders for the active and the post-treatment phases. Regression analyses identified predictors of class membership for each phase.

RESULTS

During the active treatment phase (CESD) we identified an early response (at session 2 and with continued trajectory of improvement) and a non-response group. There were also two classes during post-treatment (HAM-D): early responders (4-month) and late responders (12-month). Distress aversion was associated with lower likelihood of early response to CBT-AD (aOR = 0.74, 95%CI[0.56-0.90], p = .009), and social support was associated with increased likelihood of early response (aOR = 2.24, 95%CI[1.07-5.46], p = .045).

LIMITATIONS

Self-reported depression during the treatment phase may have resulted from social desirability bias.

CONCLUSIONS

Most participants responded to CBT-AD early during treatment (89 %) and had sustained improvements in depression by 4 months (80 %). Distress aversion was a risk factor for late response, and social support was protective. Future research is needed to assess the optimal dose of CBT-AD in resource limited settings.

Educational Intervention Effects on Depression and Anxiety in Patients after Myocardial Infarction: A Randomized Controlled Trial

Depression and anxiety in cardiovascular disease worsen the prognosis of patients. Treatments for these disorders often provide limited improvement. The present study aimed to test, for the first time, the impact of educational technology on anxiety and depressive symptoms in patients participating in a cardiac rehabilitation program. A 12-month randomized controlled trial was conducted, in which 207 patients were randomly assigned to either the experimental (n = 76) or control (n = 69) groups. The intervention involved a structured patient education program provided by medical students who had undergone specially designed training in cardiac rehabilitation. The primary outcomes were death, hospitalization, heart failure, and recurrent myocardial infarction. The study also assessed anxiety and depression. A year later, the experimental group showed a statistically significant decrease in anxiety and depression on the HADS scale, with reductions of 2.0 and 1.9 points, respectively (p < 0.05). The control group showed reductions of 1.5 and 1.2 points (p < 0.05). The difference in the Hamilton Rating Scale for Depression between the groups at 12 months was -1.29 in favor of the main group (95% CI, -0.7 to -1.88), and the standardized mean difference was 0.36 (95% CI, 0.03 to 0.69). No treatment-related adverse events were observed. The results suggest that educational interventions can have a positive impact on mental health. The study's strengths include a structured intervention, randomization, and long-term follow-up. The limitations include the lack of blinding of study participants and a relatively small sample size.

Implementation of a task-shared psychosocial intervention for perinatal depression in South Africa: A grounded theory process evaluation

Perinatal depression carries significant levels of disability for both women and their infants, but there is a large treatment gap for this condition in low and middle-income countries (LMICs). To address this gap, task-sharing using community health workers (CHWs) to provide psychosocial interventions for perinatal depression is increasingly common. Many of these interventions have shown significant positive effects on maternal mood, however not all have done so. This study used data from a task-shared psychosocial intervention for perinatal depression in Cape Town, South Africa, the 'Africa Focus on Intervention Research for Mental Health' (AFFIRM-SA) randomised controlled trial (RCT). It aimed to examine the processes that occurred within the delivery of the counselling intervention, and to use these findings to provide recommendations for psychosocial task sharing in LMICs. A grounded theory analysis was conducted of 234 counselling session transcripts from 39 randomly selected participants from the RCT. This revealed that the effectiveness of the intervention was compromised by the negative influence of participants' socio-economic context, and by counselling strategies that did not align with what was intended in the counselling manual. Despite this, participants provided spontaneous accounts of improvement in mood and cognition, and reasons for these improvements, interpreted as elements that were therapeutically effective for them. Most of these elements aligned with previously identified 'common elements' of therapy. Recommendations for future research and practice include conducting participatory formative research, using an iterative and responsive research design informed by implementation science, incorporating contextually appropriate strategies in interventions such as addressing social determinants of mental health, conducting intensive training and supervision, adopting a staged approach to managing depression, and using common elements of therapy as the basis for psychosocial interventions.

Computer assisted identification of stress, anxiety, depression (SAD) in students: A state-of-the-art review

Stress, depression, and anxiety are a person's physiological states that emerge from various body features such as speech, body language, eye contact, facial expression, etc. Physiological emotion is a part of human life and is associated with psychological activities. Sad emotion is relatable to negative thoughts and recognized in three stages containing stress, anxiety, and depression. These stages of Physiological emotion show various common and distinguished symptoms. The present study explores stress, depression, and anxiety symptoms in student life. The study reviews the psychological features generated through various body parts to identify psychological activities. Environmental factors, including a daily routine, greatly trigger psychological activities. The psychological disorder may affect mental and physical health adversely. The correct recognition of such disorder is expensive and time-consuming as it requires accurate datasets of symptoms. In the present study, an attempt has been made to investigate the effectiveness of computerized automated techniques that include machine learning algorithms for identifying stress, anxiety, and depression mental disorder. The proposed paper reviews the machine learning-based algorithms applied over datasets containing questionnaires, audio, video, etc., to recognize sad details. During the review process, the proposed study found that artificial intelligence and machine learning techniques are well recommended and widely utilized in most of the existing literature for measuring psychological disorders. The various machine learning-based algorithms are applied over datasets containing questionnaires, audio, video, etc., to recognize sad details. There has been continuous monitoring for the body symptoms established in the various existing literature to identify psychological states. The present review reveals the study of excellence and competence of machine learning techniques in detecting psychological disorders' stress, depression, and anxiety parameters. This paper shows a systematic review of some existing computer vision-based models with their merits and demerits.

Task-sharing of psychological treatment for antenatal depression in Khayelitsha, South Africa: Effects on antenatal and postnatal outcomes in an individual randomised controlled trial

The study's objective was to determine the effectiveness of a task-sharing psychological treatment for perinatal depression using non-specialist community health workers. A double-blind individual randomised controlled trial was conducted in two antenatal clinics in the peri-urban settlement of Khayelitsha, Cape Town. Adult pregnant women who scored 13 or above on the Edinburgh Postnatal Depression rating Scale (EPDS) were randomised into the intervention arm (structured six-session psychological treatment) or the control arm (routine antenatal health care and three monthly phone calls). The primary outcome was response on the Hamilton Depression Rating Scale (HDRS) at three months postpartum (minimum 40% score reduction from baseline) among participants who did not experience pregnancy or infant loss (modified intention-to-treat population) (registered on Clinical Trials: NCT01977326). Of 2187 eligible women approached, 425 (19.4%) screened positive on the EPDS and were randomised; 384 were included in the modified intention-to-treat analysis (control: n = 200; intervention: n = 184). There were no significant differences in response on the HDRS at three months postpartum between the intervention and control arm. A task-sharing psychological treatment was not effective in treating depression among women living in Khayelitsha, South Africa. The findings give cause for reflection on the strategy of task-sharing in low-resource settings.

Association between perinatal depressive symptoms and suicidal risk among low-income South African women: a longitudinal study

PURPOSE

The aim of this study was to assess the association between depressive symptoms and suicidal risk over time among perinatal women at risk for depression antenatally, and assess modifying effects of age, perinatal stage and depressive symptom trajectory.

METHODS

A total of 384 adult pregnant women were recruited from two antenatal clinics in an informal settlement near Cape Town, South Africa, and followed up at eight months gestation, and at 3- and 12-month postpartum. The MINI 6.0 Suicidality module and the Hamilton Depression Rating Scale (HDRS) were used to measure suicidal risk and depression, respectively. Generalised Estimating Equations were used to assess the association between change in depressive symptoms from one assessment to the next (predictor) and change in suicide score or change in suicidal risk (score ≥ 9) (outcomes).

RESULTS

HDRS scores were positively correlated with suicide score (95% CI 0.35, 0.78; p < 0.001), and with odds of being at moderate risk for suicide, after controlling for risk of suicide at the previous assessment (adjusted odds ratio = 1.15; 95% CI 1.09, 1.22; p < 0.001). Age was a significant effect modifier: change in HDRS scores was not associated with change in suicide scores among participants aged 35-45 years. Secondary analyses indicated that a decrease in HDRS score was associated with a decrease in suicide scores, but an increase in HDRS score was not associated with change in suicide score.

CONCLUSIONS

Depression and suicide are overlapping but relatively independent phenomena, especially among older or more chronically depressed perinatal women.