Psychometric properties of outcome measures in non-pharmacological interventions of persons with dementia in low-and middle-income countries: A systematic review.

dementia low middle income countries non-pharmacological therapy outcome measures psychometric properties

Journal

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
ISSN: 1479-8301
Titre abrégé: Psychogeriatrics
Pays: England
ID NLM: 101230058

Informations de publication

Date de publication:
Mar 2021
Historique:
received: 19 08 2020
revised: 07 11 2020
accepted: 26 11 2020
pubmed: 19 12 2020
medline: 19 3 2021
entrez: 18 12 2020
Statut: ppublish

Résumé

Despite high burden of dementia in low-and middle-income countries (LMICs), only a small number of clinical trials of psychosocial interventions for persons with dementia (PwD) have been conducted in these settings. It is essential that such trials use appropriate outcome measures that are methodologically robust and culturally appropriate to evaluate the effectiveness of interventions. We carried out a systematic review to examine the evidence base and psychometric properties of measures employed in these studies in LMICs. A systematic search of published literature on randomised controlled trials (RCT) of psychosocial interventions for PwD in LMICs between 2008 and April 2020 was carried out. Measures employed in each of the eligible studies were identified and through a focused search, we further explored the evidence base and psychometric properties employing Terwee criteria. Data extraction and quality appraisal were conducted by two independent reviewers. The review identified 41 measures from 17 RCTS which fulfilled eligibility criteria and they examined effectiveness across the domains of cognition (n = 16), behaviour and psychological symptoms (n = 11) and quality of life (n = 8). Of these 41, we were able to access relevant literature only for 18 and they were subject to psychometric analysis. Psychometric properties of these 18 instruments were at best modest, with Terwee scores ranging from 3 (low) to 15 (moderate). A majority of the studies were from China (n = 5) and Brazil (n = 6). The evidence base for the routinely employed measures in RCTs of non-pharmacological interventions for PwD in LMICs is limited. The quality of adaptation and validation of these instruments is variable and studies are largely uninformative about their psychometric properties and cultural appropriateness to the study setting. There is an urgent need to develop scientifically robust instruments in LMIC settings that can be confidently employed to measure outcomes in trials of psychosocial interventions for PwD.

Identifiants

pubmed: 33336529
doi: 10.1111/psyg.12647
pmc: PMC7986620
doi:

Types de publication

Journal Article Review Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

220-238

Subventions

Organisme : Medical Research Council
ID : MR/S004009/1
Pays : United Kingdom
Organisme : Global Alliance for Chronic Diseases (GACD)
ID : MH02
Organisme : Indian Council of Medical Research
Organisme : Indian Council of Medical Research (ICMR) UK Medical Research Council (MRC)

Informations de copyright

© 2020 Japanese Psychogeriatric Society.

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Auteurs

Bharath Du (B)

Foundation for Research and Advocacy in Mental health (FRAMe), Mysore, India.

Monisha Lakshminarayanan (M)

Schizophrenia Research Foundation, Chennai, India.

Murali Krishna (M)

Foundation for Research and Advocacy in Mental health (FRAMe), Mysore, India.

Sridhar Vaitheswaran (S)

Schizophrenia Research Foundation, Chennai, India.

Mina Chandra (M)

Atal Bihari Vajpayee Institute of Medical Sciences and Dr Ram Manohar Lohia Hospital, New Delhi, India.

Shaji Kunnukattil Sivaraman (S)

Government Medical College, Thrissur, India.

Satyapal Puri Goswami (SP)

All India Institute of Speech and Hearing, Mysore, India.

Thara Rangaswamy (T)

Schizophrenia Research Foundation, Chennai, India.

Aimee Spector (A)

University College London, London, UK.

Charlotte R Stoner (CR)

University of Greenwich, London, UK.

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Classifications MeSH