Translation apps improved staff-patient rapport and engagement in aged-care wards

Description #

In the inductive content analysis of survey and observation responses, the "Engagement" theme found that translation apps engaged patients and improved rapport, including by providing reassurance to anxious patients and by eliciting patient happiness and appreciation when staff attempted to communicate in the patient's language. Observers recorded patients responding positively and cooperating with care after the app was used.

"found that translation apps engaged patients through improving rapport." (Hwang, 2022, p. 582)

""Patient appeared happy when clinician attempted to communicate in her language, and she was appreciative of it." (Observer, site 4, CALD Assist)." (Hwang, 2022, p. 582)

""Patient had some level of spoken English, the app provided reassurance as she is usually anxious and vague." (Observer, site 1, Talk To Me)." (Hwang, 2022, p. 582)

Methods Context #

What? #ⓘ

The observable: patient engagement and staff-patient rapport, characterized qualitatively from observer field notes and open-ended survey responses coded under the "Engagement" theme.

"Engagement refers to how patients and staff responded to the use of the translation app for communication." (Hwang, 2022, p. 581)

How? #ⓘ

Inductive qualitative content analysis of transcribed open-ended survey and observation responses, coded by two researchers to a 75% consensus threshold; apps used were the phrasebook A-0018ArtifactA-0018Initial AI draftCALD Assist translation appA mobile healthcare translation app used by ward staff to communicate low-risk, everyday care messages to older CALD patients with limited English proficiency when a professional interpreter is not available or feasible.… and A-0017ArtifactA-0017Initial AI draftTalk To Me translation appA mobile healthcare translation app used by ward staff to convey low-risk everyday care messages to older CALD patients with limited English proficiency in the absence of a professional interpreter. "Talk To Me was devel… and A-0016ArtifactA-0016Initial AI draftGoogle TranslateA free, general-purpose machine translation app increasingly used as an ad-hoc communication tool in healthcare settings to bridge language barriers with LEP patients, including via voice-to-voice translation. "One such….

"Open-­ended questions from the surveys and observations were thematically analysed using inductive qualitative content analysis" (Hwang, 2022, p. 580)

Who? #ⓘ

Observed and surveyed interactions between nursing/allied health staff and older CALD patients with limited English proficiency on four aged-care hospital wards; 21 analyzed observations across languages including Italian, Greek, Arabic, Vietnamese, Cantonese, Serbian, Macedonian and Spanish.

"The aim of this research was to determine the acceptability and feasibility of using translation apps to overcome communication differences in aged-­care hospital wards between healthcare workers and older CALD individuals." (Hwang, 2022, p. 579)

Other Notes #

The same theme noted apps did not always improve rapport: when an app worked poorly it caused frustration for staff and patients ("Patient and staff became frustrated", Observer, site 2, Google Translate). This is a qualitative, staff/observer-reported benefit, not a measured relational outcome.

Caveats #

• Findings capture staff perceptions not patients' perceptions of the apps The trial captured staff perceptions of app usage but did not directly measure the older patients' own perceptions of engaging with the translation apps. Claims about improved rapport, engagement, and reassurance therefore rest on staff and observer inference rather than the patients' reported experience, limiting the directness of the benefit finding.
• Observational data may be subject to selective reporting bias The study set no specific rules governing when observations of app use were collected, leaving observation to staff discretion in a busy, unpredictable ward. The authors caution that the observational data may therefore be subject to selective reporting bias, which constrains how representative the recorded interactions and the descriptive usage/engagement findings are of app use overall.