title: AI meets psychology: an exploratory study of large language models’ competence in psychotherapy contexts

authors: Tan, Kean Sian

abstract: The increasing prevalence of mental health problems coupled with limited access to professional support has prompted exploration of technological solutions. Large Language Models (LLMs) represent a potential tool to address these challenges, yet their capabilities in psychotherapeutic contexts remain unclear. This study examined the competencies of current LLMs in psychotherapy-related tasks including alignment with evidence-informed clinical standards in case formulation, treatment planning, and implementation. Using an exploratory mixed-methods design, we presented three clinical cases (depression, anxiety, stress) and 12 therapy-related prompts to seven LLMs: ChatGPT-4o, ChatGPT-4, Claude 3.5 Sonnet, Claude 3 Opus, Meta Llama 3.1, Google Gemini 1.5 Pro, and Microsoft Co-pilot. Responses were evaluated by five experienced clinical psychologists using quantitative ratings and qualitative feedback. No single model consistently produced high-quality responses across all tasks, though different models showed distinct strengths. Models performed better in structured tasks such as determining session length and discussing goal-setting but struggled with integrative clinical reasoning and treatment implementation. Higher-rated responses demonstrated clinical humility, maintained therapeutic boundaries, and recognised therapy as collaborative. Current LLMs are more promising as supportive tools for clinicians than as therapeutic applications. This paper highlights key areas for development needed to enhance clinical reasoning abilities for effective mental health use.

text: AI meets psychology: an exploratory study of large language models’ competence in psychotherapy contexts The increasing prevalence of mental health problems coupled with limited access to professional support has prompted exploration of technological solutions. Large Language Models (LLMs) represent a potential tool to address these challenges, yet their capabilities in psychotherapeutic contexts remain unclear. This study examined the competencies of current LLMs in psychotherapy-related tasks including alignment with evidence-informed clinical standards in case formulation, treatment planning, and implementation. Using an exploratory mixed-methods design, we presented three clinical cases (depression, anxiety, stress) and 12 therapy-related prompts to seven LLMs: ChatGPT-4o, ChatGPT-4, Claude 3.5 Sonnet, Claude 3 Opus, Meta Llama 3.1, Google Gemini 1.5 Pro, and Microsoft Co-pilot. Responses were evaluated by five experienced clinical psychologists using quantitative ratings and qualitative feedback. No single model consistently produced high-quality responses across all tasks, though different models showed distinct strengths. Models performed better in structured tasks such as determining session length and discussing goal-setting but struggled with integrative clinical reasoning and treatment implementation. Higher-rated responses demonstrated clinical humility, maintained therapeutic boundaries, and recognised therapy as collaborative. Current LLMs are more promising as supportive tools for clinicians than as therapeutic applications. This paper highlights key areas for development needed to enhance clinical reasoning abilities for effective mental health use.

year: 2025

title: The effects of urban forest restoration and environmental heterogeneity on microbial diversity and ecosystem functioning

authors: Mitchell, Grace

subjects: Restoration

abstract: Increasing global urbanisation poses extensive environmental threats, including the loss of biodiversity and associated ecosystem functions. Ecosystem restoration interventions like native plantings can assist in halting and reversing the degradation of forest patches in urban settings, which is particularly relevant for the United Nations’ decade of ecosystem restoration. While the benefits of restoration plantings for aboveground communities have been well established, belowground community responses remain understudied. It is assumed that the soil microbiome will self-assemble to a pre-disturbance state following restoration. However, as microorganisms are rarely the target of restoration interventions themselves, various questions remain regarding the extent to which microbial communities will respond and recover with aboveground plantings, and how environmental variability might influence trajectories of microbial community reassembly. In this thesis, I contribute to this knowledge gap by investigating the impacts of forest age since restoration alongside a suite of environmental covariates on microbial community responses. My fieldwork took place in a New Zealand-wide chronosequence of restored urban forest sites. I analysed the diversity and taxonomic composition of bacterial, archaeal, fungal, and protist communities from these soil samples using metabarcoding data in chapter 2. Furthermore, I investigated changes in total microbial biomass, bacterial and fungal taxonomic group biomass via PLFA, total basal respiration, the spatial variability of microbial biomass and respiration, and carbon metabolism on substrates of varying recalcitrance using MicroResp™ in chapter 3. My synthesised findings show that environmental variability is typically more explanatory of microbial responses than forest age alone. Plant community factors in particular—such as native woody seedling density and tree species richness—were most often linked with enhanced microbial diversity and respiration, as well as driving increased local spatial variability. Specific phylum-level shifts from metabarcoding data indicated microbiome recovery on a trajectory towards mature forest soil communities, yet PLFA data showed that community composition does not yet reflect fungal dominance as would be expected in a mature or fully recovered forest soil. This thesis provides a holistic assessment of microbial community responses to urban forest restoration interventions, by assessing both diversity and microbial functions at multiple taxonomic resolutions. In conclusion, results from my thesis highlight the importance of taking into account the recovery of the soil microbiome and its associated ecosystem functioning to improve both aboveground and belowground success in future forest restoration projects.

text: The effects of urban forest restoration and environmental heterogeneity on microbial diversity and ecosystem functioning Increasing global urbanisation poses extensive environmental threats, including the loss of biodiversity and associated ecosystem functions. Ecosystem restoration interventions like native plantings can assist in halting and reversing the degradation of forest patches in urban settings, which is particularly relevant for the United Nations’ decade of ecosystem restoration. While the benefits of restoration plantings for aboveground communities have been well established, belowground community responses remain understudied. It is assumed that the soil microbiome will self-assemble to a pre-disturbance state following restoration. However, as microorganisms are rarely the target of restoration interventions themselves, various questions remain regarding the extent to which microbial communities will respond and recover with aboveground plantings, and how environmental variability might influence trajectories of microbial community reassembly. In this thesis, I contribute to this knowledge gap by investigating the impacts of forest age since restoration alongside a suite of environmental covariates on microbial community responses. My fieldwork took place in a New Zealand-wide chronosequence of restored urban forest sites. I analysed the diversity and taxonomic composition of bacterial, archaeal, fungal, and protist communities from these soil samples using metabarcoding data in chapter 2. Furthermore, I investigated changes in total microbial biomass, bacterial and fungal taxonomic group biomass via PLFA, total basal respiration, the spatial variability of microbial biomass and respiration, and carbon metabolism on substrates of varying recalcitrance using MicroResp™ in chapter 3. My synthesised findings show that environmental variability is typically more explanatory of microbial responses than forest age alone. Plant community factors in particular—such as native woody seedling density and tree species richness—were most often linked with enhanced microbial diversity and respiration, as well as driving increased local spatial variability. Specific phylum-level shifts from metabarcoding data indicated microbiome recovery on a trajectory towards mature forest soil communities, yet PLFA data showed that community composition does not yet reflect fungal dominance as would be expected in a mature or fully recovered forest soil. This thesis provides a holistic assessment of microbial community responses to urban forest restoration interventions, by assessing both diversity and microbial functions at multiple taxonomic resolutions. In conclusion, results from my thesis highlight the importance of taking into account the recovery of the soil microbiome and its associated ecosystem functioning to improve both aboveground and belowground success in future forest restoration projects.

year: 2022

title: Te kū o te kupu

authors: Raerino, Heddell Robert

subjects: Māori language

abstract: Ko tēnei tuhingaroa, he rangahau hai wherawhera ake i te āhuatanga o te reo Māori, e kiia ana ko tōna oro, me te kū o ngā kupu kōrero o taua reo. Ko te aronga whakaaro o tēnei rangahau, he rapu i tētahi āhuatanga kāore anō kia tirotirohia, kia tuhia rānei mō te reo Māori. Ehara tēnei rangahau i te kaupapa, i te mahi hou. Otirā, kai te whai te kaituhi i ngā rangahau kua oti kē i wētahi tohunga te wānanga mō wētahi atu reo. Ko tā te kaituhi he whai i ngā tauira a te hunga wetewete reo nei, ka uwhi ai ki runga i te reo Māori hai āwhina i ngā tātaritanga ā te kaituhi mō tōna ake reo, arā, te reo Māori.

Kai te upoko tuatahi ka whaia ngā rerenga whakaaro i pūpū ake ai te taitara 'te kū o te kupu' mō tēnei mahi rangahau. Inā ka tirohia i ahu ngā oro o te reo mai i whea e ai ki tā te Māori wānanga. Mai i ngā oro ka puta ko ngā ku o ngā kupu me ngā kupu o ngā rārangi kōrero.

Hai te upoko tuarua ka tirohia ngā kōrero kua tuhia e ngā tohunga wetewete reo e pā ana ki te kaupapa o tēnei tuhingaroa, arā, te kū o te kupu. Ko ngā tirohanga mō te reo ake, arā, i ahu mai i whea, he aha ōna momo whakaata me tōna pakaritanga ka tirohia i roto i te upoko tuatoru.

Mai i ngā momo whakaata o te reo i roto i ngā momo waiata, ka āta tahuri te kaituhi ki te whakawhānui haere i tana wetewete me tāna tūhononga i ngā rerenga me ngā pekanga o te ku o te kupu.

Kai te upoko tuarima ka tirohia ngā whāinga me ngā aronga ā wētahi kaitito
waiata Māori me wētahi kaikōrero i te reo Māori, mō ō rātau māramatanga ki ngā kū me ngā oro o te reo Māori.

Kai te upoko tuaono e whāriki ana wētahi tauira kōrero Māori, hai whakaata i ngā momo orōmāhara, oro ohorere, ororite, kupu whakahuarua me wērā atu tauira whakaahua i ngā kū o te kupu me ngā oro o te reo Māori.

Ko ngā hua o tēnei rangahau, o tēnei tuhingaroa ka kitea i roto i te upoko
tuawhitu. Kōinei te whakakopinga o tēnei mahi.

text: Te kū o te kupu Ko tēnei tuhingaroa, he rangahau hai wherawhera ake i te āhuatanga o te reo Māori, e kiia ana ko tōna oro, me te kū o ngā kupu kōrero o taua reo. Ko te aronga whakaaro o tēnei rangahau, he rapu i tētahi āhuatanga kāore anō kia tirotirohia, kia tuhia rānei mō te reo Māori. Ehara tēnei rangahau i te kaupapa, i te mahi hou. Otirā, kai te whai te kaituhi i ngā rangahau kua oti kē i wētahi tohunga te wānanga mō wētahi atu reo. Ko tā te kaituhi he whai i ngā tauira a te hunga wetewete reo nei, ka uwhi ai ki runga i te reo Māori hai āwhina i ngā tātaritanga ā te kaituhi mō tōna ake reo, arā, te reo Māori.

Kai te upoko tuatahi ka whaia ngā rerenga whakaaro i pūpū ake ai te taitara 'te kū o te kupu' mō tēnei mahi rangahau. Inā ka tirohia i ahu ngā oro o te reo mai i whea e ai ki tā te Māori wānanga. Mai i ngā oro ka puta ko ngā ku o ngā kupu me ngā kupu o ngā rārangi kōrero.

Hai te upoko tuarua ka tirohia ngā kōrero kua tuhia e ngā tohunga wetewete reo e pā ana ki te kaupapa o tēnei tuhingaroa, arā, te kū o te kupu. Ko ngā tirohanga mō te reo ake, arā, i ahu mai i whea, he aha ōna momo whakaata me tōna pakaritanga ka tirohia i roto i te upoko tuatoru.

Mai i ngā momo whakaata o te reo i roto i ngā momo waiata, ka āta tahuri te kaituhi ki te whakawhānui haere i tana wetewete me tāna tūhononga i ngā rerenga me ngā pekanga o te ku o te kupu.

Kai te upoko tuarima ka tirohia ngā whāinga me ngā aronga ā wētahi kaitito
waiata Māori me wētahi kaikōrero i te reo Māori, mō ō rātau māramatanga ki ngā kū me ngā oro o te reo Māori.

Kai te upoko tuaono e whāriki ana wētahi tauira kōrero Māori, hai whakaata i ngā momo orōmāhara, oro ohorere, ororite, kupu whakahuarua me wērā atu tauira whakaahua i ngā kū o te kupu me ngā oro o te reo Māori.

Ko ngā hua o tēnei rangahau, o tēnei tuhingaroa ka kitea i roto i te upoko
tuawhitu. Kōinei te whakakopinga o tēnei mahi.

year: 2000