“My Wife and I Invariably Go Together”: A Mixed Methods Analysis of Physical Activity and its Influences on Older Adult Dyads

Abstract Background Physical activity (PA) is an imperative factor to healthy cognitive and functional ageing and may act as a protective factor against cognitive decline. Evidence suggests that as we age, PA declines, leaving a large proportion of older adults (OAs) ‘underactive’ and ‘unprotected’. Socialisation/social support is considered a beneficial influence on PA in OAs. It is unclear whether dyadic (e.g. spousal) influences impact PA in healthy ageing, and how this might impact digital activity monitoring or intervention development to support prevention of cognitive decline. This research aims to quantify volume and types of PA and explore influential factors for PA participation in OAs. Method Participants were recruited via the ActivDyad study, where they wore a lumbar‐based‐accelerometer (AX6, Axivity) for 7 days, and completed a 7‐day activity diary. PA (i.e. daily steps) was derived from accelerometers using validated algorithms. Qualitative content analysis of the diaries was adopted for contextual understanding of the types and influences of PA. The Theoretical Domains Framework was utilised to identify common facilitators/barriers of PA in OAs. Result 21 dyads (42 OAs) participated in the study; 10 dyads were included in preliminary analysis (mean age (mean±SD): 68.6±4.8; 100% heterosexual & married; mean relationship time: 45±10 years; 80% retired). Participants carried out an average of 15,680 daily steps (range: 7,243‐22,668), and indicated their most frequent PA as: shopping, gardening, housekeeping, and recreational walks (Table 1). Participants identified potential facilitators (Table 2) and barriers (Table 3) for partaking in PA. Social influence (e.g. partner) was identified as most influential; 75% of participants mentioned this as a facilitator for PA. Environmental context, particularly weather conditions, were frequently discussed as both a facilitator (50%) and barrier (45%) to PA. Conclusion Results suggest that dyadic interactions are a key facilitator of PA in OAs. Weather appears to have a bi‐conditional influence, promoting and/or discouraging PA; this may impact activity monitoring during adverse weather conditions (e.g. lower steps). Adherence may be higher in group PA interventions, and outdoor PA should be promoted in suitable weather. Analysis of the full sample will inform studies focusing activity monitoring and intervention development for dementia‐carer dyads.

Authors

Institutions

Publication Details

Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.089186
Primary Topic
Textile materials and evaluations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

“My Wife and I Invariably Go Together”: A Mixed Methods Analysis of Physical Activity and its Influences on Older Adult Dyads

Gro Gujord Tangen, Louis McCarthy, Nicolas Farina, Vitaveska Lanfranchi et al.
Alzheimer s & Dementia
Textile materials and evaluations
article

“My Wife and I Invariably Go Together”: A Mixed Methods Analysis of Physical Activity and its Influences on Older Adult Dyads

Gro Gujord Tangen, Louis McCarthy, Nicolas Farina, Vitaveska Lanfranchi, J K Wales, Neil Ireson, Calum A. Hamilton, Sayeh Bayat, Ben Hicks, Ríona Mc Ardle
article en

Abstract

Abstract Background Physical activity (PA) is an imperative factor to healthy cognitive and functional ageing and may act as a protective factor against cognitive decline. Evidence suggests that as we age, PA declines, leaving a large proportion of older adults (OAs) ‘underactive’ and ‘unprotected’. Socialisation/social support is considered a beneficial influence on PA in OAs. It is unclear whether dyadic (e.g. spousal) influences impact PA in healthy ageing, and how this might impact digital activity monitoring or intervention development to support prevention of cognitive decline. This research aims to quantify volume and types of PA and explore influential factors for PA participation in OAs. Method Participants were recruited via the ActivDyad study, where they wore a lumbar‐based‐accelerometer (AX6, Axivity) for 7 days, and completed a 7‐day activity diary. PA (i.e. daily steps) was derived from accelerometers using validated algorithms. Qualitative content analysis of the diaries was adopted for contextual understanding of the types and influences of PA. The Theoretical Domains Framework was utilised to identify common facilitators/barriers of PA in OAs. Result 21 dyads (42 OAs) participated in the study; 10 dyads were included in preliminary analysis (mean age (mean±SD): 68.6±4.8; 100% heterosexual & married; mean relationship time: 45±10 years; 80% retired). Participants carried out an average of 15,680 daily steps (range: 7,243‐22,668), and indicated their most frequent PA as: shopping, gardening, housekeeping, and recreational walks (Table 1). Participants identified potential facilitators (Table 2) and barriers (Table 3) for partaking in PA. Social influence (e.g. partner) was identified as most influential; 75% of participants mentioned this as a facilitator for PA. Environmental context, particularly weather conditions, were frequently discussed as both a facilitator (50%) and barrier (45%) to PA. Conclusion Results suggest that dyadic interactions are a key facilitator of PA in OAs. Weather appears to have a bi‐conditional influence, promoting and/or discouraging PA; this may impact activity monitoring during adverse weather conditions (e.g. lower steps). Adherence may be higher in group PA interventions, and outdoor PA should be promoted in suitable weather. Analysis of the full sample will inform studies focusing activity monitoring and intervention development for dementia‐carer dyads.

Alzheimer s & DementiaVol. 20(S7)
Brighton and Sussex Medical School (GB), University of Calgary (CA), Newcastle University (GB), University of Plymouth (GB), University of Sheffield (GB)
Biotechnology and Biological Sciences Research Council, Economic and Social Research Council
Openalex Percentile: Top 80%
Textile materials and evaluations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.