Development and Validation of Hospital Mental Health Screen to Detect Psychiatric Morbidity in Medically Ill Patients in India

Roshan Sutar; Anuja Lahiri; Rashida Ali; Vindhya Solanki; Anindo Majumdar; Manoj Sharma; Santosh Chaturvedi

doi:10.1177/02537176241248061

Development and Validation of Hospital Mental Health Screen to Detect Psychiatric Morbidity in Medically Ill Patients in India

Indian J Psychol Med. 2024 May 2:02537176241248061. doi: 10.1177/02537176241248061. Online ahead of print.

Authors

Roshan Sutar¹, Anuja Lahiri², Rashida Ali¹, Vindhya Solanki¹, Anindo Majumdar², Manoj Sharma³, Santosh Chaturvedi⁴

Affiliations

¹ Dept. of Psychiatry, AIIMS Bhopal, Madhya Pradesh, India.
² Dept. of Community and Family Medicine, AIIMS Bhopal, Madhya Pradesh, India.
³ Dept. of Clinical Psychology, NIMHANS, Bangalore, Karnataka, India.
⁴ Jagadguru Kripalu Chikitsalaya, Vrindavan and Barsana, Uttar Pradesh, India.

Abstract

Background: Psychiatric morbidities often go unnoticed in medically ill patients. It is essential to screen patients with medical morbidity so that they can be referred to psychiatrists for early interventions in general hospitals in India. There is a potential lacuna in terms of the availability of a scale that can aptly identify psychiatric symptoms in medically ill patients beyond depression or anxiety, especially in low-resource settings like India.

Aim: The aim was to detect psychiatric morbidity in medically ill patients in India.

Methodology: Items were generated using deductive and inductive approaches. Item-Content Validity Index (I-CVI) and Scale-Content Validity Index/Universal Agreement (S-CVI/UA) were computed by involving eight subject matter specialists. The tool was circulated to 397 medically ill patients for computing The exploratory factor analysis (EFA). Domain-wise reliability using Cronbach's alpha was calculated for six factors. The concurrent criterion validity of the Hospital Mental Health Screen (HMHS) tool was calculated by the receiver operating curve (ROC) against the gold standard of any psychiatric morbidity diagnosed by two psychiatrists in 397 medically ill patients. We used IBM SPSS version 23.

Results: Initially, 34 items were generated. At the I-CVI threshold of 79%, seven items were discarded. The S-CVI/UA of the scale was 85.1%. The Kaiser-Meier-Olkin Measure of Sampling Adequacy (KMO MSA) was found to be 0.916. At a factor loading threshold of 0.4 and an eigenvalue above 1, a six-factor structure was extracted using principal component analysis and varimax rotation. Domain-wise reliability was computed, which was between 0.657 and 0.840. The final tool consisted of 27 Likert items (0 = never to 4 = always). Using the ROC curve at the 19.5 threshold, 91.4% of the positive outcomes were correctly classified and 9.5% of the adverse outcomes were expected to be incorrectly identified by the HMHS screening tool.

Conclusion: HMHS is a valid and reliable tool with good screening properties, designed especially for the Indian setting. This scale can assist in identifying psychiatric morbidity in medically ill patients in low-resource settings. There is further scope for performing confirmatory factor analysis (CFA) to reinforce the factor structure of HMHS.

Keywords: India; Validity; factor analysis; medical morbidity; psychiatric morbidity; reliability; screening tool.