Health psychology and behavioral medicine · 2026
Applying behaviour change science to change motivational interaction in physical activity and sports professionals: stepwise development and acceptability pre-test of the MotiStyleSport intervention.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Palsola Minttu, Renko Elina, Puolamäki Melina, Absetz Pilvikki, Haerens Leen, Lintunen Taru, Potthoff Sebastian, Saurio Kaisa, Hankonen Nelli
Аннотация
BACKGROUND: Physical activity (PA) counselling and sports coaching are more effective when professionals use self-determination theory-based need-supportive interaction. Existing interventions generally involve information provision and practical exercise, and show modest, short-term effects. Behaviour change science has rarely been incorporated, despite its potential to support sustainable change.
AIMS: This study systematically applies behaviour change science to develop an intervention to train professionals in motivational interaction behaviours.
METHODS: A four-step mixed-methods design included a needs assessment questionnaire (n = 203), and pre-test acceptability questionnaires and group interviews (n = 15). Systematic intervention development involved: 1) identifying target behaviours, determinants and behaviour change strategies, 2) formulating a theory of change, 3) co-development of intervention materials, and 4) acceptability evaluation. Qualitative data were content analysed and means and medians of quantitative data (58 items, scale 1-5) were explored.
RESULTS: 1) We selected nine motivational interaction behaviours (e.g. open questions, clarifying expectations) alongside seven determinants (e.g. self-efficacy) and intervention strategies. 2) Habit and control theories informed self-monitoring, action and coping planning, and habit formation/disruption activities. The intervention was delivered via 3) an online platform, slide shows, videos, and homework. 4) Overall acceptability was high after iterative optimisation. Prior to optimisation, self-insight maps had low overall acceptability (M = 2.8). Implementation intentions were rated acceptable (M = 3.6), but qualitative data revealed substantial misunderstandings concerning intervention coherence, perceived effectiveness, and self-efficacy.
CONCLUSION: Quantitative-qualitative divergence in implementation intention data underlines the value of mixed-methods evaluation. Habit theory-based exercises show promise, but feasibility and effectiveness testing are needed before conclusions about behavioural impact.
AIMS: This study systematically applies behaviour change science to develop an intervention to train professionals in motivational interaction behaviours.
METHODS: A four-step mixed-methods design included a needs assessment questionnaire (n = 203), and pre-test acceptability questionnaires and group interviews (n = 15). Systematic intervention development involved: 1) identifying target behaviours, determinants and behaviour change strategies, 2) formulating a theory of change, 3) co-development of intervention materials, and 4) acceptability evaluation. Qualitative data were content analysed and means and medians of quantitative data (58 items, scale 1-5) were explored.
RESULTS: 1) We selected nine motivational interaction behaviours (e.g. open questions, clarifying expectations) alongside seven determinants (e.g. self-efficacy) and intervention strategies. 2) Habit and control theories informed self-monitoring, action and coping planning, and habit formation/disruption activities. The intervention was delivered via 3) an online platform, slide shows, videos, and homework. 4) Overall acceptability was high after iterative optimisation. Prior to optimisation, self-insight maps had low overall acceptability (M = 2.8). Implementation intentions were rated acceptable (M = 3.6), but qualitative data revealed substantial misunderstandings concerning intervention coherence, perceived effectiveness, and self-efficacy.
CONCLUSION: Quantitative-qualitative divergence in implementation intention data underlines the value of mixed-methods evaluation. Habit theory-based exercises show promise, but feasibility and effectiveness testing are needed before conclusions about behavioural impact.