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Record W2786121494 · doi:10.2196/mhealth.8345

Activity Monitors as Support for Older Persons’ Physical Activity in Daily Life: Qualitative Study of the Users’ Experiences

2018· article· en· W2786121494 on OpenAlexvenueno aff
Maria Ehn, Lennie Carlén Eriksson, Nina Åkerberg, Ann‐Christin Johansson

Bibliographic record

VenueJMIR mhealth and uhealth · 2018
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
FundersMälardalens högskolaLandstinget Västmanland
KeywordsPhysical activityQualitative researchGerontologyPsychologyActivities of daily livingApplied psychologyMedicinePhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Falls are a major threat to the health and independence of seniors. Regular physical activity (PA) can prevent 40% of all fall injuries. The challenge is to motivate and support seniors to be physically active. Persuasive systems can constitute valuable support for persons aiming at establishing and maintaining healthy habits. However, these systems need to support effective behavior change techniques (BCTs) for increasing older adults' PA and meet the senior users' requirements and preferences. Therefore, involving users as codesigners of new systems can be fruitful. Prestudies of the user's experience with similar solutions can facilitate future user-centered design of novel persuasive systems. OBJECTIVE: The aim of this study was to investigate how seniors experience using activity monitors (AMs) as support for PA in daily life. The addressed research questions are as follows: (1) What are the overall experiences of senior persons, of different age and balance function, in using wearable AMs in daily life?; (2) Which aspects did the users perceive relevant to make the measurements as meaningful and useful in the long-term perspective?; and (3) What needs and requirements did the users perceive as more relevant for the activity monitors to be useful in a long-term perspective? METHODS: This qualitative interview study included 8 community-dwelling older adults (median age: 83 years). The participants' experiences in using two commercial AMs together with tablet-based apps for 9 days were investigated. Activity diaries during the usage and interviews after the usage were exploited to gather user experience. Comments in diaries were summarized, and interviews were analyzed by inductive content analysis. RESULTS: The users (n=8) perceived that, by using the AMs, their awareness of own PA had increased. However, the AMs' impact on the users' motivation for PA and activity behavior varied between participants. The diaries showed that self-estimated physical effort varied between participants and varied for each individual over time. Additionally, participants reported different types of accomplished activities; talking walks was most frequently reported. To be meaningful, measurements need to provide the user with a reliable receipt of whether his or her current activity behavior is sufficient for reaching an activity goal. Moreover, praise when reaching a goal was described as motivating feedback. To be useful, the devices must be easy to handle. In this study, the users perceived wearables as easy to handle, whereas tablets were perceived difficult to maneuver. Users reported in the diaries that the devices had been functional 78% (58/74) of the total test days. CONCLUSIONS: Activity monitors can be valuable for supporting seniors' PA. However, the potential of the solutions for a broader group of seniors can significantly be increased. Areas of improvement include reliability, usability, and content supporting effective BCTs with respect to increasing older adults' PA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.134
GPT teacher head0.495
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations131
Published2018
Admission routes1
Has abstractyes

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